diff --git a/docs/README.md b/docs/README.md index 45863c611..d000a9430 100644 --- a/docs/README.md +++ b/docs/README.md @@ -23,7 +23,7 @@ PDL provides the following features: The PDL interpreter takes a PDL program as input and generates data by executing its instructions (calling out to models, code, etc...). -See below for a quick reference, followed by [installation notes](#interpreter_installation) and an [overview](#overview) of the language. A more detailed description of the language features can be found in this [tutorial](https://ibm.github.io/prompt-declaration-language/tutorial). +See below for a quick reference, followed by [installation notes](#interpreter-installation) and an [overview](#overview) of the language. A more detailed description of the language features can be found in this [tutorial](https://ibm.github.io/prompt-declaration-language/tutorial). ## Quick Reference @@ -194,7 +194,7 @@ The same example on Replicate: ```yaml text: - "Hello\n" -- model: replicate/ibm-granite/granite-3.2-8b-instruct +- model: replicate/ibm-granite/granite-3.2-8b-instruct parameters: stop: "!" temperature: 0 @@ -215,24 +215,9 @@ See the [tutorial](https://ibm.github.io/prompt-declaration-language/tutorial) f Consider now an example from AI for code, where we want to build a prompt template for code explanation. We have a JSON file as input containing the source code and some information regarding the repository where it came from. -For example, given the data in this JSON [file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/code/data.yaml): +For example, given the data in this JSON [file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/examples/tutorial/programs/code/data.yaml): ```yaml -source_code: - | - @SuppressWarnings("unchecked") - public static Map deserializeOffsetMap(String lastSourceOffset) throws IOException { - Map offsetMap; - if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { - offsetMap = new HashMap<>(); - } else { - offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); - } - return offsetMap; - } -repo_info: - repo: streamsets/datacollector - path: stagesupport/src/main/java/com/.../OffsetUtil.java - function_name: OffsetUtil.deserializeOffsetMap +--8<-- "./examples/tutorial/programs/code/data.yaml" ``` we would like to express the following prompt and submit it to an LLM: @@ -259,28 +244,10 @@ public static Map deserializeOffsetMap(String lastSourceOffset) } ``` -In PDL, this would be expressed as follows (see [file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/code/code.pdl)): +In PDL, this would be expressed as follows (see [file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/tutorial/programs/code/code.pdl)): ```yaml -description: Code explanation example -defs: - CODE: - read: ./data.yaml - parser: yaml -text: -- "\n${ CODE.source_code }\n" -- model: ollama/granite-code:8b - input: | - Here is some info about the location of the function in the repo. - repo: - ${ CODE.repo_info.repo } - path: ${ CODE.repo_info.path } - Function_name: ${ CODE.repo_info.function_name } - - - Explain the following code: - ``` - ${ CODE.source_code }``` +--8<-- "./examples/tutorial/programs/code/code.pdl" ``` In this program we first define some variables using the `defs` construct. Here `CODE` is defined to be a new variable, holding the result of the `read` block that follows. @@ -310,48 +277,10 @@ public static Map deserializeOffsetMap(String lastSourceOffset) The code is a Java method that takes a string `lastSourceOffset` as input and returns a `Map`. The method uses the Jackson library to deserialize the JSON-formatted string into a map. If the input string is null or empty, an empty HashMap is returned. Otherwise, the string is deserialized into a Map using the `JSON_MAPPER.readValue()` method. ``` -Notice that in PDL variables are used to templatize any entity in the document, not just textual prompts to LLMs. We can add a block to this document to evaluate the quality of the output using a similarity metric with respect to our [ground truth](https://github.com/IBM/prompt-declaration-language/blob/main/examples/code/ground_truth.txt). See [file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/code/code-eval.pdl): +Notice that in PDL variables are used to templatize any entity in the document, not just textual prompts to LLMs. We can add a block to this document to evaluate the quality of the output using a similarity metric with respect to our [ground truth](https://github.com/IBM/prompt-declaration-language/blob/main/examples/tutorial/programs/code/ground_truth.txt). See [file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/tutorial/programs/code/code-eval.pdl): ```yaml -description: Code explanation example -defs: - CODE: - read: ./data.yaml - parser: yaml - TRUTH: - read: ./ground_truth.txt -text: -- "\n${ CODE.source_code }\n" -- model: ollama/granite-code:8b - def: EXPLANATION - input: | - Here is some info about the location of the function in the repo. - repo: - ${ CODE.repo_info.repo } - path: ${ CODE.repo_info.path } - Function_name: ${ CODE.repo_info.function_name } - - - Explain the following code: - ``` - ${ CODE.source_code }``` -- | - - - EVALUATION: - The similarity (Levenshtein) between this answer and the ground truth is: -- def: EVAL - lang: python - code: | - import textdistance - expl = """ - ${ EXPLANATION } - """ - truth = """ - ${ TRUTH } - """ - # (In PDL, set `result` to the output you wish for your code block.) - result = textdistance.levenshtein.normalized_similarity(expl, truth) +--8<-- "./examples/tutorial/programs/code/code-eval.pdl" ``` This program has an input block that reads the ground truth from filename `examples/code/ground_truth.txt` and assigns its contents to variable `TRUTH`. It also assigns the output of the model to the variable `EXPLANATION`, using a `def` construct. In PDL, any block can have a `def` to capture the result of that block in a variable. The last block is a call to Python code, which is included after the `code` field. Notice how code is included here simply as data. We collate fragments of Python with outputs obtained from previous blocks. This is one of the powerful features of PDL: the ability to specify the execution of code that is not known ahead of time. We can use LLMs to generate code that is later executed in the same programming model. This is made possible because PDL treats code as data, like any another part of the document. @@ -385,55 +314,10 @@ PDL allows rapid prototyping of prompts by allowing the user to change prompts a Finally, we can output JSON data as a result of this program, as follows: ```yaml -description: Code explanation example -defs: - CODE: - read: ./data.yaml - parser: yaml - TRUTH: - read: ./ground_truth.txt -text: -- model: ollama/granite-code:8b - def: EXPLANATION - contribute: [] - input: - | - Here is some info about the location of the function in the repo. - repo: - ${ CODE.repo_info.repo } - path: ${ CODE.repo_info.path } - Function_name: ${ CODE.repo_info.function_name } - - - Explain the following code: - ``` - ${ CODE.source_code }``` - parameters: - temperature: 0 -- def: EVAL - contribute: [] - lang: python - code: - | - import textdistance - expl = """ - ${ EXPLANATION } - """ - truth = """ - ${ TRUTH } - """ - # (In PDL, set `result` to the output you wish for your code block.) - result = textdistance.levenshtein.normalized_similarity(expl, truth) -- data: - input: ${ CODE } - output: ${ EXPLANATION } - metric: ${ EVAL } - -``` - -The data block takes various variables and combines their values into a JSON object with fields `input`, `output`, and `metric`. We mute the output of all the other blocks with `contribute` set to `[]`. The `contribute` construct can be used to specify how the result of a block is contributed to the background context. -Setting it to `[]` means no contribution is made from this block to the background context. By default, the result of every block is contributed to the context. For the blocks in the program above, we use a `def` construct to save the intermediate result of each block. +--8<-- "./examples/tutorial/programs/code/code-json.pdl" +``` +The data block takes various variables and combines their values into a JSON object with fields `input`, `output`, and `metric`. The output of this program is the corresponding serialized JSON object, with the appropriate treatment of quotation marks. Similarly PDL can read jsonl files and create jsonl files by piping to a file. ## PDL Language Tutorial diff --git a/docs/tutorial.md b/docs/tutorial.md index b44188469..2f0f37d70 100644 --- a/docs/tutorial.md +++ b/docs/tutorial.md @@ -374,10 +374,10 @@ In this program, we first define a query about the weather in some location (ass ## Data Block -PDL offers the ability to create JSON data as illustrated by the following example (described in detail in the [Overview](https://ibm.github.io/prompt-declaration-language/#overview) section). The `data` block can gather previously defined variables into a JSON structure. This feature is useful for data generation. Programs such as this one can be generalized to read jsonl files to generate data en masse by piping into another jsonl file ([file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/tutorial/programs/code-json.pdl)). +PDL offers the ability to create JSON data as illustrated by the following example (described in detail in the [Overview](https://ibm.github.io/prompt-declaration-language/#overview) section). The `data` block can gather previously defined variables into a JSON structure. This feature is useful for data generation. Programs such as this one can be generalized to read jsonl files to generate data en masse by piping into another jsonl file ([file](https://github.com/IBM/prompt-declaration-language/blob/main/examples/tutorial/programs/code/code-json.pdl)). ```yaml ---8<-- "./examples/tutorial/programs/code-json.pdl" +--8<-- "./examples/tutorial/programs/code/code-json.pdl" ``` Notice that in the `data` block the values are interpreted as Jinja expressions. If values need to be PDL programs to be interpreted, then you need to use diff --git a/examples/code/code-json.pdl b/examples/code/code-json.pdl deleted file mode 100644 index 1f1c7632b..000000000 --- a/examples/code/code-json.pdl +++ /dev/null @@ -1,39 +0,0 @@ -description: Code explanation example -defs: - CODE: - read: ./data.yaml - parser: yaml - TRUTH: - read: ./ground_truth.txt -lastOf: -- model: ollama_chat/granite3.2:2b - def: EXPLANATION - input: - | - Here is some info about the location of the function in the repo. - repo: - ${ CODE.repo_info.repo } - path: ${ CODE.repo_info.path } - Function_name: ${ CODE.repo_info.function_name } - - - Explain the following code: - ``` - ${ CODE.source_code }``` -- def: EVAL - lang: python - code: - | - import textdistance - expl = """ - ${ EXPLANATION } - """ - truth = """ - ${ TRUTH } - """ - result = textdistance.levenshtein.normalized_similarity(expl, truth) -- data: - input: ${ CODE } - output: ${ EXPLANATION } - metric: ${ EVAL } - diff --git a/examples/tutorial/programs/code-json.pdl b/examples/tutorial/programs/code-json.pdl deleted file mode 100644 index e51c1f8b0..000000000 --- a/examples/tutorial/programs/code-json.pdl +++ /dev/null @@ -1,39 +0,0 @@ -description: Code explanation example -defs: - CODE: - read: ../../code/data.yaml - parser: yaml - TRUTH: - read: ../../code/ground_truth.txt -lastOf: -- model: ollama_chat/granite3.2:2b - def: EXPLANATION - input: - | - Here is some info about the location of the function in the repo. - repo: - ${ CODE.repo_info.repo } - path: ${ CODE.repo_info.path } - Function_name: ${ CODE.repo_info.function_name } - - - Explain the following code: - ``` - ${ CODE.source_code }``` -- def: EVAL - lang: python - code: - | - import textdistance - expl = """ - ${ EXPLANATION } - """ - truth = """ - ${ TRUTH } - """ - result = textdistance.levenshtein.normalized_similarity(expl, truth) -- data: - input: ${ CODE } - output: ${ EXPLANATION } - metric: ${ EVAL } - diff --git a/examples/code/README.md b/examples/tutorial/programs/code/README.md similarity index 100% rename from examples/code/README.md rename to examples/tutorial/programs/code/README.md diff --git a/examples/code/code-eval.pdl b/examples/tutorial/programs/code/code-eval.pdl similarity index 70% rename from examples/code/code-eval.pdl rename to examples/tutorial/programs/code/code-eval.pdl index 01cd1a191..7c7ff0303 100644 --- a/examples/code/code-eval.pdl +++ b/examples/tutorial/programs/code/code-eval.pdl @@ -1,17 +1,12 @@ description: Code explanation example defs: - # The variable `CODE` shall be the contents of the parsed YAML file CODE: read: ./data.yaml parser: yaml - # The variable `TRUTH` shall be the text of the file TRUTH: read: ./ground_truth.txt text: -# Print the source code to the console - "\n${ CODE.source_code }\n" -# Use ollama to invoke a Granite model with a prompt. Output AND -# set the variable `EXPLANATION` to the output. - model: ollama_chat/granite3.2:2b def: EXPLANATION input: | @@ -26,14 +21,12 @@ text: ``` ${ CODE.source_code }``` parameters: - # Use no LLM creativity. (Note that 0 is the default; this line has no effect) temperature: 0 - | EVALUATION: The similarity (Levenshtein) between this answer and the ground truth is: -# We aren't only defining `EVAL`, we are also executing it. - def: EVAL lang: python # (Use `pip install textdistance` if needed to install the textdistance package) diff --git a/examples/code/code-json-output.json b/examples/tutorial/programs/code/code-json-output.json similarity index 100% rename from examples/code/code-json-output.json rename to examples/tutorial/programs/code/code-json-output.json diff --git a/examples/tutorial/programs/code/code-json.pdl b/examples/tutorial/programs/code/code-json.pdl new file mode 100644 index 000000000..15108de9b --- /dev/null +++ b/examples/tutorial/programs/code/code-json.pdl @@ -0,0 +1,38 @@ +description: Code explanation example +defs: + CODE: + read: ./data.yaml + parser: yaml + TRUTH: + read: ./ground_truth.txt + EXPLANATION: + model: ollama_chat/granite3.2:2b + input: + | + Here is some info about the location of the function in the repo. + repo: + ${ CODE.repo_info.repo } + path: ${ CODE.repo_info.path } + Function_name: ${ CODE.repo_info.function_name } + + + Explain the following code: + ``` + ${ CODE.source_code }``` + EVAL: + lang: python + code: + | + import textdistance + expl = """ + ${ EXPLANATION } + """ + truth = """ + ${ TRUTH } + """ + result = textdistance.levenshtein.normalized_similarity(expl, truth) +data: + input: ${ CODE } + output: ${ EXPLANATION } + metric: ${ EVAL } + diff --git a/examples/code/code.pdl b/examples/tutorial/programs/code/code.pdl similarity index 88% rename from examples/code/code.pdl rename to examples/tutorial/programs/code/code.pdl index 4c6771899..872c5f9fa 100644 --- a/examples/code/code.pdl +++ b/examples/tutorial/programs/code/code.pdl @@ -21,5 +21,4 @@ text: ``` ${ CODE.source_code }``` parameters: - # Use no LLM creativity. (Note that 0 is the default; this line has no effect) temperature: 0 \ No newline at end of file diff --git a/examples/code/data.yaml b/examples/tutorial/programs/code/data.yaml similarity index 100% rename from examples/code/data.yaml rename to examples/tutorial/programs/code/data.yaml diff --git a/examples/code/ground_truth.txt b/examples/tutorial/programs/code/ground_truth.txt similarity index 100% rename from examples/code/ground_truth.txt rename to examples/tutorial/programs/code/ground_truth.txt diff --git a/pdl-live-react/demos/run.sh b/pdl-live-react/demos/run.sh index 7aab52485..b87ce21f6 100755 --- a/pdl-live-react/demos/run.sh +++ b/pdl-live-react/demos/run.sh @@ -14,8 +14,8 @@ no in europe? yes EOF -pdl --trace "$T"/demo5.json "$TOP"/examples/talk/6-code-json.pdl -pdl --trace "$T"/demo6.json "$UI"/demos/error.pdl || true -pdl --trace "$T"/demo7.json "$TOP"/examples/talk/4-function.pdl +pdl --trace "$T"/demo5.json "$TOP"/examples/tutorial/programs/code/code-json.pdl +# pdl --trace "$T"/demo6.json "$UI"/demos/error.pdl || true +pdl --trace "$T"/demo7.json "$TOP"/examples/tutorial/function_definition.pdl # TODO demo8... pdl --stream none --trace "$T"/demo9.json "$TOP"/examples/gsm8k/gsm8.pdl diff --git a/pdl-live-react/src/demos/demo1.json b/pdl-live-react/src/demos/demo1.json index 52d852373..c3ae5059e 100644 --- a/pdl-live-react/src/demos/demo1.json +++ b/pdl-live-react/src/demos/demo1.json @@ -1 +1 @@ -{"kind": "text", "pdl__id": "text", "description": "Simple LLM interaction", "defs": {}, "text": [{"kind": "data", "pdl__id": "text.0", "defs": {}, "data": {"pdl__expr": "write a hello world example, and explain to me how to run it", "pdl__result": "write a hello world example, and explain to me how to run it"}, "pdl__result": "write a hello world example, and explain to me how to run it", "pdl__timing": {"start_nanos": 1742523918021192000, "end_nanos": 1742523918022233000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.1.model", "pdl__context": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}]}, "pdl__result": "[{\"role\": \"user\", \"content\": \"write a hello world example, and explain to me how to run it\", \"pdl__defsite\": \"text.0\"}]", "pdl__timing": {"start_nanos": 1742523918129394000, "end_nanos": 1742523918130174000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 489, "prompt_tokens": 24}, "pdl__model_input": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "pdl__result": "Sure, I'll provide an example of a \"Hello, World!\" program in two popular programming languages: Python and JavaScript (using Node.js).\n\n**Python:**\n\n```python\n# This is a simple Python script to print \"Hello, World!\"\n\nprint(\"Hello, World!\")\n```\n\nTo run this Python code:\n\n1. Open your preferred text editor or an Integrated Development Environment (IDE) like Visual Studio Code, PyCharm, or Jupyter Notebook.\n2. Copy and paste the above code snippet into a new file with a `.py` extension, e.g., `hello_world.py`.\n3. Save the file in a directory where Python is installed on your system (usually it's located at `C:\\Python39\\` for Python 3.9 or similar).\n4. Open a terminal/command prompt and navigate to the directory containing your `.py` file using the `cd` command, e.g., `cd path/to/your/directory`.\n5. Run the script by typing `python hello_world.py` and pressing Enter. You should see \"Hello, World!\" printed in the terminal or command prompt.\n\n**JavaScript (Node.js):**\n\n```javascript\n// This is a simple JavaScript script to print \"Hello, World!\" using Node.js\n\nconsole.log(\"Hello, World!\");\n```\n\nTo run this JavaScript code on a system that has Node.js installed:\n\n1. Install Node.js from https://nodejs.org/ if you haven't already (it's recommended for running JavaScript on the command line).\n2. Open your terminal or command prompt.\n3. Navigate to the directory where you want to run this script using `cd` command, e.g., `cd path/to/your/directory`.\n4. Create a new file named `hello_world.js` by typing `touch hello_world.js`, then open it with your text editor:\n ```\n nano hello_world.js\n ```\n5. Paste the above JavaScript code into this file, save it (press `Ctrl+X`, then `Y` to confirm, and finally `Enter`).\n6. To run the script from the command line, type `node hello_world.js`. You should see \"Hello, World!\" printed in the terminal or command prompt.\n\nBoth Python and JavaScript scripts achieve the same output \u2013 printing \"Hello, World!\" \u2013 but they're written in different languages and use distinct methods to execute them on a computer system.", "pdl__timing": {"start_nanos": 1742523918129200000, "end_nanos": 1742523958045772000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "write a hello world example, and explain to me how to run itSure, I'll provide an example of a \"Hello, World!\" program in two popular programming languages: Python and JavaScript (using Node.js).\n\n**Python:**\n\n```python\n# This is a simple Python script to print \"Hello, World!\"\n\nprint(\"Hello, World!\")\n```\n\nTo run this Python code:\n\n1. Open your preferred text editor or an Integrated Development Environment (IDE) like Visual Studio Code, PyCharm, or Jupyter Notebook.\n2. Copy and paste the above code snippet into a new file with a `.py` extension, e.g., `hello_world.py`.\n3. Save the file in a directory where Python is installed on your system (usually it's located at `C:\\Python39\\` for Python 3.9 or similar).\n4. Open a terminal/command prompt and navigate to the directory containing your `.py` file using the `cd` command, e.g., `cd path/to/your/directory`.\n5. Run the script by typing `python hello_world.py` and pressing Enter. You should see \"Hello, World!\" printed in the terminal or command prompt.\n\n**JavaScript (Node.js):**\n\n```javascript\n// This is a simple JavaScript script to print \"Hello, World!\" using Node.js\n\nconsole.log(\"Hello, World!\");\n```\n\nTo run this JavaScript code on a system that has Node.js installed:\n\n1. Install Node.js from https://nodejs.org/ if you haven't already (it's recommended for running JavaScript on the command line).\n2. Open your terminal or command prompt.\n3. Navigate to the directory where you want to run this script using `cd` command, e.g., `cd path/to/your/directory`.\n4. Create a new file named `hello_world.js` by typing `touch hello_world.js`, then open it with your text editor:\n ```\n nano hello_world.js\n ```\n5. Paste the above JavaScript code into this file, save it (press `Ctrl+X`, then `Y` to confirm, and finally `Enter`).\n6. To run the script from the command line, type `node hello_world.js`. You should see \"Hello, World!\" printed in the terminal or command prompt.\n\nBoth Python and JavaScript scripts achieve the same output \u2013 printing \"Hello, World!\" \u2013 but they're written in different languages and use distinct methods to execute them on a computer system.", "pdl__timing": {"start_nanos": 1742523918021087000, "end_nanos": 1742523958045857000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file +{"kind": "text", "pdl__id": "text", "description": "Simple LLM interaction", "defs": {}, "context": "dependent", "text": [{"kind": "data", "pdl__id": "text.0", "defs": {}, "data": {"pdl__expr": "write a hello world example, and explain to me how to run it", "pdl__result": "write a hello world example, and explain to me how to run it"}, "pdl__result": "write a hello world example, and explain to me how to run it", "pdl__timing": {"start_nanos": 1750789936107628000, "end_nanos": 1750789936108899000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.1.model", "pdl__context": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}]}, "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "pdl__timing": {"start_nanos": 1750789936205506000, "end_nanos": 1750789936206408000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 496, "prompt_tokens": 21}, "pdl__model_input": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "pdl__result": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nThis single line of code will output the text \"Hello, World!\" when run.\n\nTo run this Python script, follow these steps:\n\n1. **Install Python**: If you haven't already installed Python on your computer, download and install it from the official website (https://www.python.org/downloads/). Make sure to select the option that includes the Python interpreter during installation.\n\n2. **Create a new file**: Open a text editor or an Integrated Development Environment (IDE) like Visual Studio Code, PyCharm, or even Notepad on Windows. Create a new file and save it with a `.py` extension, for example, `hello_world.py`.\n\n3. **Copy the Python code**: Copy the \"Hello, World!\" script provided above into your newly created text file.\n\n4. **Open a terminal/command prompt**: On Windows, press `Win + R`, type `cmd`, and hit Enter to open Command Prompt. On macOS or Linux, use `Terminal`.\n\n5. **Navigate to the directory containing your Python file**: Use the `cd` command (for Unix-based systems) or `cd` followed by the path (for Windows) to change into the folder where you saved `hello_world.py`. For example:\n\n - On Unix/Linux:\n ```\n cd /path/to/your/directory\n ```\n - On macOS:\n ```\n cd ~/Desktop\n ```\n\n6. **Run the Python script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see \"Hello, World!\" printed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When you run a `.py` file, the Python interpreter reads it line by line.\n- The first line of code (`print(\"Hello, World!\")`) tells the interpreter to display the text \"Hello, World!\" on the screen.\n- The `print()` function is a built-in Python function that outputs the specified string (enclosed in quotes) to the console or terminal.\n- After executing this line, the program ends, and control returns to the command prompt or terminal.\n\nThat's it! You've just run your first \"Hello, World!\" program using Python.", "pdl__timing": {"start_nanos": 1750789936205261000, "end_nanos": 1750789973932310000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "write a hello world example, and explain to me how to run itSure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nThis single line of code will output the text \"Hello, World!\" when run.\n\nTo run this Python script, follow these steps:\n\n1. **Install Python**: If you haven't already installed Python on your computer, download and install it from the official website (https://www.python.org/downloads/). Make sure to select the option that includes the Python interpreter during installation.\n\n2. **Create a new file**: Open a text editor or an Integrated Development Environment (IDE) like Visual Studio Code, PyCharm, or even Notepad on Windows. Create a new file and save it with a `.py` extension, for example, `hello_world.py`.\n\n3. **Copy the Python code**: Copy the \"Hello, World!\" script provided above into your newly created text file.\n\n4. **Open a terminal/command prompt**: On Windows, press `Win + R`, type `cmd`, and hit Enter to open Command Prompt. On macOS or Linux, use `Terminal`.\n\n5. **Navigate to the directory containing your Python file**: Use the `cd` command (for Unix-based systems) or `cd` followed by the path (for Windows) to change into the folder where you saved `hello_world.py`. For example:\n\n - On Unix/Linux:\n ```\n cd /path/to/your/directory\n ```\n - On macOS:\n ```\n cd ~/Desktop\n ```\n\n6. **Run the Python script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see \"Hello, World!\" printed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When you run a `.py` file, the Python interpreter reads it line by line.\n- The first line of code (`print(\"Hello, World!\")`) tells the interpreter to display the text \"Hello, World!\" on the screen.\n- The `print()` function is a built-in Python function that outputs the specified string (enclosed in quotes) to the console or terminal.\n- After executing this line, the program ends, and control returns to the command prompt or terminal.\n\nThat's it! You've just run your first \"Hello, World!\" program using Python.", "pdl__timing": {"start_nanos": 1750789936010969000, "end_nanos": 1750789973932402000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file diff --git a/pdl-live-react/src/demos/demo2.json b/pdl-live-react/src/demos/demo2.json index 18f8b5e42..868bc2770 100644 --- a/pdl-live-react/src/demos/demo2.json +++ b/pdl-live-react/src/demos/demo2.json @@ -1 +1 @@ -{"kind": "text", "pdl__id": "text", "description": "Model chaining", "defs": {}, "text": [{"kind": "data", "pdl__id": "text.0", "defs": {}, "data": {"pdl__expr": "write a hello world example, and explain to me how to run it", "pdl__result": "write a hello world example, and explain to me how to run it"}, "pdl__result": "write a hello world example, and explain to me how to run it", "pdl__timing": {"start_nanos": 1742523959317953000, "end_nanos": 1742523959319213000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.1.model", "pdl__context": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}]}, "pdl__result": "[{\"role\": \"user\", \"content\": \"write a hello world example, and explain to me how to run it\", \"pdl__defsite\": \"text.0\"}]", "pdl__timing": {"start_nanos": 1742523959450075000, "end_nanos": 1742523959450991000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 534, "prompt_tokens": 24}, "pdl__model_input": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "pdl__result": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "pdl__timing": {"start_nanos": 1742523959448315000, "end_nanos": 1742524001114763000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.2", "defs": {}, "data": {"pdl__expr": "how about in Rust?", "pdl__result": "how about in Rust?"}, "pdl__result": "how about in Rust?", "pdl__timing": {"start_nanos": 1742524001114837000, "end_nanos": 1742524001114951000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.3.model", "pdl__context": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}, {"content": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "role": "assistant", "pdl__defsite": "text.1.model"}, {"role": "user", "content": "how about in Rust?", "pdl__defsite": "text.2"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.3.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}, {"content": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "role": "assistant", "pdl__defsite": "text.1.model"}, {"role": "user", "content": "how about in Rust?", "pdl__defsite": "text.2"}]}, "pdl__result": "[{\"role\": \"user\", \"content\": \"write a hello world example, and explain to me how to run it\", \"pdl__defsite\": \"text.0\"}, {\"content\": \"Sure, I'd be happy to help with that! Here's a simple \\\"Hello, World!\\\" program in Python, which is one of the most popular programming languages:\\n\\n```python\\nprint(\\\"Hello, World!\\\")\\n```\\n\\nTo run this code, follow these steps:\\n\\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \\\"Add Python to PATH\\\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\\n\\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\\n\\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\\n\\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\\n\\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\\n\\n ```\\n cd C:\\\\Users\\\\YourUsername\\\\Documents\\n ```\\n\\n Or on macOS/Linux:\\n\\n ```\\n cd ~/Documents\\n ```\\n\\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \\\"Hello, World!\\\" displayed in your terminal or command prompt.\\n\\nHere's what happens under the hood:\\n\\n- When Python encounters the line `print(\\\"Hello, World!\\\")`, it interprets this as a command to display the string \\\"Hello, World!\\\" on the console.\\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \\\"Hello, World!\\\".\\n\\nThat's it! You've just written and executed a simple \\\"Hello, World!\\\" program using Python. This is a great starting point for learning programming concepts.\", \"role\": \"assistant\", \"pdl__defsite\": \"text.1.model\"}, {\"role\": \"user\", \"content\": \"how about in Rust?\", \"pdl__defsite\": \"text.2\"}]", "pdl__timing": {"start_nanos": 1742524001116984000, "end_nanos": 1742524001117934000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 629, "prompt_tokens": 578}, "pdl__model_input": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}, {"content": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "role": "assistant", "pdl__defsite": "text.1.model"}, {"role": "user", "content": "how about in Rust?", "pdl__defsite": "text.2"}], "pdl__result": "Absolutely, here's how you can write and run a \"Hello, World!\" program in Rust:\n\n1. **Install Rust**: First, you need to install Rust on your system. Visit the official Rust website (https://www.rust-lang.org/) and follow the instructions for your operating system to download and install Rust. Make sure to add Rust to your PATH during installation so that your terminal can find the `rustc` command.\n\n2. **Create a New Rust File**: Open a text editor or use an Integrated Development Environment (IDE) like Visual Studio Code, IntelliJ IDEA with the Rust plugin, or cargo-edit. For this example, let's use nano, a simple text editor available on most Unix-based systems:\n\n ```\n nano hello_world.rs\n ```\n\n3. **Write Your Code**: Copy and paste the following Rust code into your file:\n\n ```rust\n fn main() {\n println!(\"Hello, World!\");\n }\n ```\n\n This is a simple \"Hello, World!\" program in Rust. The `fn main()` function is the entry point of any Rust program. Inside this function, `println!` is used to print the string \"Hello, World!\" to the console.\n\n4. **Save and Exit**: Save the file with a `.rs` extension (e.g., `hello_world.rs`). If you're using nano, press `Ctrl+X`, then `Y` to confirm saving changes, and finally `Enter`.\n\n5. **Open Terminal/Command Prompt**: Open your terminal or command prompt. On Windows, use PowerShell or Command Prompt; on macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n6. **Navigate to Your Project Directory**: Change into the directory where you saved `hello_world.rs` using the `cd` command:\n\n ```\n cd path/to/your/project\n ```\n\n Replace `path/to/your/project` with the actual path to your project folder.\n\n7. **Compile and Run Your Rust Program**: Use the `rustc` command to compile your Rust code into an executable, then run it using `./`. Here's how:\n\n ```\n rustc hello_world.rs # This compiles your .rs file into an object file (hello_world)\n ./hello_world # This runs the compiled program and prints \"Hello, World!\"\n ```\n\nHere's what happens under the hood:\n\n- `rustc` is Rust's compiler that translates your source code (`hello_world.rs`) into machine code or an executable file (in this case, `hello_world`).\n- The `./` command tells the system to run the compiled binary directly from the current directory.\n- When you run `./hello_world`, it prints \"Hello, World!\" to your terminal because that's what the `println!` function in Rust does \u2013 it outputs a string to the console.\n\nThat's how you write and run a simple \"Hello, World!\" program in Rust! This example demonstrates basic Rust syntax and shows how to compile and execute code using the command line.", "pdl__timing": {"start_nanos": 1742524001115124000, "end_nanos": 1742524059895019000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "write a hello world example, and explain to me how to run itSure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.how about in Rust?Absolutely, here's how you can write and run a \"Hello, World!\" program in Rust:\n\n1. **Install Rust**: First, you need to install Rust on your system. Visit the official Rust website (https://www.rust-lang.org/) and follow the instructions for your operating system to download and install Rust. Make sure to add Rust to your PATH during installation so that your terminal can find the `rustc` command.\n\n2. **Create a New Rust File**: Open a text editor or use an Integrated Development Environment (IDE) like Visual Studio Code, IntelliJ IDEA with the Rust plugin, or cargo-edit. For this example, let's use nano, a simple text editor available on most Unix-based systems:\n\n ```\n nano hello_world.rs\n ```\n\n3. **Write Your Code**: Copy and paste the following Rust code into your file:\n\n ```rust\n fn main() {\n println!(\"Hello, World!\");\n }\n ```\n\n This is a simple \"Hello, World!\" program in Rust. The `fn main()` function is the entry point of any Rust program. Inside this function, `println!` is used to print the string \"Hello, World!\" to the console.\n\n4. **Save and Exit**: Save the file with a `.rs` extension (e.g., `hello_world.rs`). If you're using nano, press `Ctrl+X`, then `Y` to confirm saving changes, and finally `Enter`.\n\n5. **Open Terminal/Command Prompt**: Open your terminal or command prompt. On Windows, use PowerShell or Command Prompt; on macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n6. **Navigate to Your Project Directory**: Change into the directory where you saved `hello_world.rs` using the `cd` command:\n\n ```\n cd path/to/your/project\n ```\n\n Replace `path/to/your/project` with the actual path to your project folder.\n\n7. **Compile and Run Your Rust Program**: Use the `rustc` command to compile your Rust code into an executable, then run it using `./`. Here's how:\n\n ```\n rustc hello_world.rs # This compiles your .rs file into an object file (hello_world)\n ./hello_world # This runs the compiled program and prints \"Hello, World!\"\n ```\n\nHere's what happens under the hood:\n\n- `rustc` is Rust's compiler that translates your source code (`hello_world.rs`) into machine code or an executable file (in this case, `hello_world`).\n- The `./` command tells the system to run the compiled binary directly from the current directory.\n- When you run `./hello_world`, it prints \"Hello, World!\" to your terminal because that's what the `println!` function in Rust does \u2013 it outputs a string to the console.\n\nThat's how you write and run a simple \"Hello, World!\" program in Rust! This example demonstrates basic Rust syntax and shows how to compile and execute code using the command line.", "pdl__timing": {"start_nanos": 1742523959317819000, "end_nanos": 1742524059895091000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file +{"kind": "text", "pdl__id": "text", "description": "Model chaining", "defs": {}, "context": "dependent", "text": [{"kind": "data", "pdl__id": "text.0", "defs": {}, "data": {"pdl__expr": "write a hello world example, and explain to me how to run it", "pdl__result": "write a hello world example, and explain to me how to run it"}, "pdl__result": "write a hello world example, and explain to me how to run it", "pdl__timing": {"start_nanos": 1750789975739696000, "end_nanos": 1750789975740984000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.1.model", "pdl__context": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}]}, "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "pdl__timing": {"start_nanos": 1750789975831792000, "end_nanos": 1750789975832639000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 534, "prompt_tokens": 21}, "pdl__model_input": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}], "pdl__result": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "pdl__timing": {"start_nanos": 1750789975830109000, "end_nanos": 1750790014446954000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.2", "defs": {}, "data": {"pdl__expr": "how about in Rust?", "pdl__result": "how about in Rust?"}, "pdl__result": "how about in Rust?", "pdl__timing": {"start_nanos": 1750790014447055000, "end_nanos": 1750790014447174000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.3.model", "pdl__context": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}, {"content": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "role": "assistant", "pdl__defsite": "text.1.model"}, {"role": "user", "content": "how about in Rust?", "pdl__defsite": "text.2"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.3.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}, {"content": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "role": "assistant", "pdl__defsite": "text.1.model"}, {"role": "user", "content": "how about in Rust?", "pdl__defsite": "text.2"}]}, "pdl__result": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}, {"content": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "role": "assistant", "pdl__defsite": "text.1.model"}, {"role": "user", "content": "how about in Rust?", "pdl__defsite": "text.2"}], "pdl__timing": {"start_nanos": 1750790014449254000, "end_nanos": 1750790014450157000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 629, "prompt_tokens": 568}, "pdl__model_input": [{"role": "user", "content": "write a hello world example, and explain to me how to run it", "pdl__defsite": "text.0"}, {"content": "Sure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.", "role": "assistant", "pdl__defsite": "text.1.model"}, {"role": "user", "content": "how about in Rust?", "pdl__defsite": "text.2"}], "pdl__result": "Absolutely, here's how you can write and run a \"Hello, World!\" program in Rust:\n\n1. **Install Rust**: First, you need to install Rust on your system. Visit the official Rust website (https://www.rust-lang.org/) and follow the instructions for your operating system to download and install Rust. Make sure to add Rust to your PATH during installation so that your terminal can find the `rustc` command.\n\n2. **Create a New Rust File**: Open a text editor or use an Integrated Development Environment (IDE) like Visual Studio Code, IntelliJ IDEA with the Rust plugin, or cargo-edit. For this example, let's use nano, a simple text editor available on most Unix-based systems:\n\n ```\n nano hello_world.rs\n ```\n\n3. **Write Your Code**: Copy and paste the following Rust code into your file:\n\n ```rust\n fn main() {\n println!(\"Hello, World!\");\n }\n ```\n\n This is a simple \"Hello, World!\" program in Rust. The `fn main()` function is the entry point of any Rust program. Inside this function, `println!` is used to print the string \"Hello, World!\" to the console.\n\n4. **Save and Exit**: Save the file with a `.rs` extension (e.g., `hello_world.rs`). If you're using nano, press `Ctrl+X`, then `Y` to confirm saving changes, and finally `Enter`.\n\n5. **Open Terminal/Command Prompt**: Open your terminal or command prompt. On Windows, use PowerShell or Command Prompt; on macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n6. **Navigate to Your Project Directory**: Change into the directory where you saved `hello_world.rs` using the `cd` command:\n\n ```\n cd path/to/your/project\n ```\n\n Replace `path/to/your/project` with the actual path to your project folder.\n\n7. **Compile and Run Your Rust Program**: Use the `rustc` command to compile your Rust code into an executable, then run it using `./`. Here's how:\n\n ```\n rustc hello_world.rs # This compiles your .rs file into an object file (hello_world)\n ./hello_world # This runs the compiled program and prints \"Hello, World!\"\n ```\n\nHere's what happens under the hood:\n\n- `rustc` is Rust's compiler that translates your source code (`hello_world.rs`) into machine code or an executable file (in this case, `hello_world`).\n- The `./` command tells the system to run the compiled binary directly from the current directory.\n- When you run `./hello_world`, it prints \"Hello, World!\" to your terminal because that's what the `println!` function in Rust does \u2013 it outputs a string to the console.\n\nThat's how you write and run a simple \"Hello, World!\" program in Rust! This example demonstrates basic Rust syntax and shows how to compile and execute code using the command line.", "pdl__timing": {"start_nanos": 1750790014447340000, "end_nanos": 1750790071342498000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "write a hello world example, and explain to me how to run itSure, I'd be happy to help with that! Here's a simple \"Hello, World!\" program in Python, which is one of the most popular programming languages:\n\n```python\nprint(\"Hello, World!\")\n```\n\nTo run this code, follow these steps:\n\n1. **Install Python**: If you haven't already, download and install Python from its official website (https://www.python.org/). Make sure to check the box for \"Add Python to PATH\" during installation; this step is crucial as it allows your system to find the Python executable in any directory.\n\n2. **Open a Text Editor**: Use a text editor like Notepad (on Windows), TextEdit (on macOS), or Visual Studio Code, Sublime Text, Atom, etc., for writing your code.\n\n3. **Write Your Code**: Copy and paste the Python code above into your text editor. Save this file with a `.py` extension, for example, `hello_world.py`. You can name it anything you like, but using `.py` ensures that the file is recognized as a Python script.\n\n4. **Open Command Prompt/Terminal**: On Windows, press `Win + R`, type `cmd`, and hit Enter. On macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n5. **Navigate to the Directory**: In the command prompt or terminal window, navigate to the directory where you saved your Python file using the `cd` command followed by the path to that folder. For example:\n\n ```\n cd C:\\Users\\YourUsername\\Documents\n ```\n\n Or on macOS/Linux:\n\n ```\n cd ~/Documents\n ```\n\n6. **Run Your Script**: Type `python hello_world.py` and press Enter. If everything is set up correctly, you should see the output \"Hello, World!\" displayed in your terminal or command prompt.\n\nHere's what happens under the hood:\n\n- When Python encounters the line `print(\"Hello, World!\")`, it interprets this as a command to display the string \"Hello, World!\" on the console.\n- The `python` command at the end of your terminal/command prompt invocation tells the system to use its built-in Python interpreter (or any other Python version you have installed) to run the script.\n- The Python interpreter reads each line in your file, executes it, and prints the result to the console. In this case, it prints \"Hello, World!\".\n\nThat's it! You've just written and executed a simple \"Hello, World!\" program using Python. This is a great starting point for learning programming concepts.how about in Rust?Absolutely, here's how you can write and run a \"Hello, World!\" program in Rust:\n\n1. **Install Rust**: First, you need to install Rust on your system. Visit the official Rust website (https://www.rust-lang.org/) and follow the instructions for your operating system to download and install Rust. Make sure to add Rust to your PATH during installation so that your terminal can find the `rustc` command.\n\n2. **Create a New Rust File**: Open a text editor or use an Integrated Development Environment (IDE) like Visual Studio Code, IntelliJ IDEA with the Rust plugin, or cargo-edit. For this example, let's use nano, a simple text editor available on most Unix-based systems:\n\n ```\n nano hello_world.rs\n ```\n\n3. **Write Your Code**: Copy and paste the following Rust code into your file:\n\n ```rust\n fn main() {\n println!(\"Hello, World!\");\n }\n ```\n\n This is a simple \"Hello, World!\" program in Rust. The `fn main()` function is the entry point of any Rust program. Inside this function, `println!` is used to print the string \"Hello, World!\" to the console.\n\n4. **Save and Exit**: Save the file with a `.rs` extension (e.g., `hello_world.rs`). If you're using nano, press `Ctrl+X`, then `Y` to confirm saving changes, and finally `Enter`.\n\n5. **Open Terminal/Command Prompt**: Open your terminal or command prompt. On Windows, use PowerShell or Command Prompt; on macOS or Linux, open Terminal from Applications > Utilities (macOS) or Spotlight Search (Linux).\n\n6. **Navigate to Your Project Directory**: Change into the directory where you saved `hello_world.rs` using the `cd` command:\n\n ```\n cd path/to/your/project\n ```\n\n Replace `path/to/your/project` with the actual path to your project folder.\n\n7. **Compile and Run Your Rust Program**: Use the `rustc` command to compile your Rust code into an executable, then run it using `./`. Here's how:\n\n ```\n rustc hello_world.rs # This compiles your .rs file into an object file (hello_world)\n ./hello_world # This runs the compiled program and prints \"Hello, World!\"\n ```\n\nHere's what happens under the hood:\n\n- `rustc` is Rust's compiler that translates your source code (`hello_world.rs`) into machine code or an executable file (in this case, `hello_world`).\n- The `./` command tells the system to run the compiled binary directly from the current directory.\n- When you run `./hello_world`, it prints \"Hello, World!\" to your terminal because that's what the `println!` function in Rust does \u2013 it outputs a string to the console.\n\nThat's how you write and run a simple \"Hello, World!\" program in Rust! This example demonstrates basic Rust syntax and shows how to compile and execute code using the command line.", "pdl__timing": {"start_nanos": 1750789975645980000, "end_nanos": 1750790071342592000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file diff --git a/pdl-live-react/src/demos/demo3.json b/pdl-live-react/src/demos/demo3.json index d55cd173d..f16a3989e 100644 --- a/pdl-live-react/src/demos/demo3.json +++ b/pdl-live-react/src/demos/demo3.json @@ -1 +1 @@ -{"kind": "text", "pdl__id": "text", "description": "Fibonacci", "defs": {}, "text": [{"kind": "model", "pdl__id": "text.0.model", "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.0.model", "defs": {}, "data": {"pdl__expr": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n", "pdl__result": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n"}, "pdl__result": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n", "pdl__timing": {"start_nanos": 1742524061607674000, "end_nanos": 1742524061607759000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 292, "prompt_tokens": 24}, "pdl__model_input": [{"role": "user", "content": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n"}], "def": "CODE", "pdl__result": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "pdl__timing": {"start_nanos": 1742524061604264000, "end_nanos": 1742524085633508000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.1", "defs": {}, "data": {"pdl__expr": "\nFind a random number between 1 and 20\n", "pdl__result": "\nFind a random number between 1 and 20\n"}, "pdl__result": "\nFind a random number between 1 and 20\n", "pdl__timing": {"start_nanos": 1742524085633579000, "end_nanos": 1742524085633692000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "code", "pdl__id": "text.2.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "text.2.code", "defs": {}, "data": {"pdl__expr": "import random\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = random.randint(1, 20)\n", "pdl__result": "import random\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = random.randint(1, 20)\n"}, "pdl__result": "import random\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = random.randint(1, 20)\n", "pdl__timing": {"start_nanos": 1742524085633918000, "end_nanos": 1742524085634016000, "timezone": "EDT"}, "pdl__is_leaf": true}, "def": "N", "pdl__result": 16, "pdl__timing": {"start_nanos": 1742524085633858000, "end_nanos": 1742524085634289000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.3", "defs": {}, "data": {"pdl__expr": "\nNow computing fibonacci(${ N })\n", "pdl__result": "\nNow computing fibonacci(16)\n"}, "pdl__result": "\nNow computing fibonacci(16)\n", "pdl__timing": {"start_nanos": 1742524085634334000, "end_nanos": 1742524085635389000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "code", "pdl__id": "text.4.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "text.4.code", "defs": {}, "data": {"pdl__expr": "s = \"\"\"'${ CODE } '\"\"\"\nresult = s.split(\"```\")[1].replace(\"python\", \"\")\n", "pdl__result": "s = \"\"\"'Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear. '\"\"\"\nresult = s.split(\"```\")[1].replace(\"python\", \"\")\n"}, "pdl__result": "s = \"\"\"'Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear. '\"\"\"\nresult = s.split(\"```\")[1].replace(\"python\", \"\")\n", "pdl__timing": {"start_nanos": 1742524085635562000, "end_nanos": 1742524085636319000, "timezone": "EDT"}, "pdl__is_leaf": true}, "def": "EXTRACTED", "pdl__result": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__timing": {"start_nanos": 1742524085635520000, "end_nanos": 1742524085636564000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "code", "pdl__id": "text.5.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "text.5.code", "defs": {}, "data": {"pdl__expr": "${ EXTRACTED }\nresult = fibonacci(${ N })\n", "pdl__result": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n\nresult = fibonacci(16)\n"}, "pdl__result": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n\nresult = fibonacci(16)\n", "pdl__timing": {"start_nanos": 1742524085636673000, "end_nanos": 1742524085637555000, "timezone": "EDT"}, "pdl__is_leaf": true}, "def": "RESULT", "contribute": [], "pdl__result": 610, "pdl__timing": {"start_nanos": 1742524085636634000, "end_nanos": 1742524085637909000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.6", "defs": {}, "data": {"pdl__expr": "The result is: ${ RESULT }", "pdl__result": "The result is: 610"}, "pdl__result": "The result is: 610", "pdl__timing": {"start_nanos": 1742524085637954000, "end_nanos": 1742524085638604000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.7", "defs": {}, "data": {"pdl__expr": "\n\nExplain what the above code does and what the result means\n\n", "pdl__result": "\n\nExplain what the above code does and what the result means\n\n"}, "pdl__result": "\n\nExplain what the above code does and what the result means\n\n", "pdl__timing": {"start_nanos": 1742524085638705000, "end_nanos": 1742524085638789000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.8.model", "pdl__context": [{"content": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "role": "assistant", "pdl__defsite": "text.0.model"}, {"role": "user", "content": "\nFind a random number between 1 and 20\n", "pdl__defsite": "text.1"}, {"role": "user", "content": "16", "pdl__defsite": "text.2.code"}, {"role": "user", "content": "\nNow computing fibonacci(16)\n", "pdl__defsite": "text.3"}, {"role": "user", "content": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__defsite": "text.4.code"}, {"role": "user", "content": "The result is: 610", "pdl__defsite": "text.6"}, {"role": "user", "content": "\n\nExplain what the above code does and what the result means\n\n", "pdl__defsite": "text.7"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.8.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"content": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "role": "assistant", "pdl__defsite": "text.0.model"}, {"role": "user", "content": "\nFind a random number between 1 and 20\n", "pdl__defsite": "text.1"}, {"role": "user", "content": "16", "pdl__defsite": "text.2.code"}, {"role": "user", "content": "\nNow computing fibonacci(16)\n", "pdl__defsite": "text.3"}, {"role": "user", "content": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__defsite": "text.4.code"}, {"role": "user", "content": "The result is: 610", "pdl__defsite": "text.6"}, {"role": "user", "content": "\n\nExplain what the above code does and what the result means\n\n", "pdl__defsite": "text.7"}]}, "pdl__result": "[{\"content\": \"Here is a simple Python function that computes the Fibonacci sequence using recursion:\\n\\n```python\\ndef fibonacci(n):\\n if n <= 0:\\n return \\\"Input should be a positive integer.\\\"\\n elif n == 1:\\n return 0\\n elif n == 2:\\n return 1\\n else:\\n return fibonacci(n - 1) + fibonacci(n - 2)\\n```\\n\\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\\n\\n```python\\ndef fibonacci_iterative(n):\\n if n <= 0:\\n return \\\"Input should be a positive integer.\\\"\\n elif n == 1:\\n return 0\\n elif n == 2:\\n return 1\\n\\n fib_values = [0, 1] + [0] * (n - 2)\\n for i in range(2, n):\\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\\n return fib_values[n - 1]\\n```\\n\\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.\", \"role\": \"assistant\", \"pdl__defsite\": \"text.0.model\"}, {\"role\": \"user\", \"content\": \"\\nFind a random number between 1 and 20\\n\", \"pdl__defsite\": \"text.1\"}, {\"role\": \"user\", \"content\": \"16\", \"pdl__defsite\": \"text.2.code\"}, {\"role\": \"user\", \"content\": \"\\nNow computing fibonacci(16)\\n\", \"pdl__defsite\": \"text.3\"}, {\"role\": \"user\", \"content\": \"\\ndef fibonacci(n):\\n if n <= 0:\\n return \\\"Input should be a positive integer.\\\"\\n elif n == 1:\\n return 0\\n elif n == 2:\\n return 1\\n else:\\n return fibonacci(n - 1) + fibonacci(n - 2)\\n\", \"pdl__defsite\": \"text.4.code\"}, {\"role\": \"user\", \"content\": \"The result is: 610\", \"pdl__defsite\": \"text.6\"}, {\"role\": \"user\", \"content\": \"\\n\\nExplain what the above code does and what the result means\\n\\n\", \"pdl__defsite\": \"text.7\"}]", "pdl__timing": {"start_nanos": 1742524085639053000, "end_nanos": 1742524085639735000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 488, "prompt_tokens": 451}, "pdl__model_input": [{"content": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "role": "assistant", "pdl__defsite": "text.0.model"}, {"role": "user", "content": "\nFind a random number between 1 and 20\n", "pdl__defsite": "text.1"}, {"role": "user", "content": "16", "pdl__defsite": "text.2.code"}, {"role": "user", "content": "\nNow computing fibonacci(16)\n", "pdl__defsite": "text.3"}, {"role": "user", "content": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__defsite": "text.4.code"}, {"role": "user", "content": "The result is: 610", "pdl__defsite": "text.6"}, {"role": "user", "content": "\n\nExplain what the above code does and what the result means\n\n", "pdl__defsite": "text.7"}], "pdl__result": "The provided Python function `fibonacci(n)` calculates the nth number in the Fibonacci sequence using recursion. The Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones, usually starting with 0 and 1 (0, 1, 1, 2, 3, 5, 8, ...).\n\nHere's what the function does step by step:\n\n1. It takes an integer `n` as input.\n2. If `n` is less than or equal to 0, it returns a string \"Input should be a positive integer.\" because the Fibonacci sequence doesn't make sense for non-positive integers.\n3. If `n` equals 1, it returns 0, which is the first number in the Fibonacci series (Fib(1) = 0).\n4. If `n` equals 2, it returns 1, which is the second number in the Fibonacci series (Fib(2) = 1).\n5. For any other positive integer `n`, the function calls itself with arguments `n - 1` and `n - 2`, then adds the results of these two recursive calls to get the nth Fibonacci number:\n ```\n fibonacci(n) = fibonacci(n - 1) + fibonacci(n - 2)\n ```\n\nGiven that we called `fibonacci(16)`, it computed the 16th number in the Fibonacci sequence. Let's break down how this calculation works:\n\n- The function calculates `fibonacci(15)` first, which is `fibonacci(14) + fibonacci(13)`.\n- Then it computes `fibonacci(14)`, then `fibonacci(13)`, and so on, up to calculating the initial values of `fibonacci(0)` as 0 and `fibonacci(-1)` as 1.\n- The function keeps adding pairs of previously computed Fibonacci numbers until it reaches `n = 16`.\n\nThe result `610` is indeed the 16th number in the Fibonacci sequence, which can be found manually by continuing this recursive addition process. This is a well-known number in the Fibonacci series:\n\n```\n0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, ...\n```", "pdl__timing": {"start_nanos": 1742524085638908000, "end_nanos": 1742524144546216000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.\nFind a random number between 1 and 20\n16\nNow computing fibonacci(16)\n\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\nThe result is: 610\n\nExplain what the above code does and what the result means\n\nThe provided Python function `fibonacci(n)` calculates the nth number in the Fibonacci sequence using recursion. The Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones, usually starting with 0 and 1 (0, 1, 1, 2, 3, 5, 8, ...).\n\nHere's what the function does step by step:\n\n1. It takes an integer `n` as input.\n2. If `n` is less than or equal to 0, it returns a string \"Input should be a positive integer.\" because the Fibonacci sequence doesn't make sense for non-positive integers.\n3. If `n` equals 1, it returns 0, which is the first number in the Fibonacci series (Fib(1) = 0).\n4. If `n` equals 2, it returns 1, which is the second number in the Fibonacci series (Fib(2) = 1).\n5. For any other positive integer `n`, the function calls itself with arguments `n - 1` and `n - 2`, then adds the results of these two recursive calls to get the nth Fibonacci number:\n ```\n fibonacci(n) = fibonacci(n - 1) + fibonacci(n - 2)\n ```\n\nGiven that we called `fibonacci(16)`, it computed the 16th number in the Fibonacci sequence. Let's break down how this calculation works:\n\n- The function calculates `fibonacci(15)` first, which is `fibonacci(14) + fibonacci(13)`.\n- Then it computes `fibonacci(14)`, then `fibonacci(13)`, and so on, up to calculating the initial values of `fibonacci(0)` as 0 and `fibonacci(-1)` as 1.\n- The function keeps adding pairs of previously computed Fibonacci numbers until it reaches `n = 16`.\n\nThe result `610` is indeed the 16th number in the Fibonacci sequence, which can be found manually by continuing this recursive addition process. This is a well-known number in the Fibonacci series:\n\n```\n0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, ...\n```", "pdl__timing": {"start_nanos": 1742524061604107000, "end_nanos": 1742524144546300000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file +{"kind": "text", "pdl__id": "text", "description": "Fibonacci", "defs": {}, "context": "dependent", "text": [{"kind": "model", "pdl__id": "text.0.model", "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.0.model", "defs": {}, "data": {"pdl__expr": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n", "pdl__result": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n"}, "pdl__result": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n", "pdl__timing": {"start_nanos": 1750790073536914000, "end_nanos": 1750790073537006000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 292, "prompt_tokens": 24}, "pdl__model_input": [{"role": "user", "content": "Write a Python function to compute the Fibonacci sequence. Do not include a doc string.\n\n"}], "def": "CODE", "pdl__result": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "pdl__timing": {"start_nanos": 1750790073532369000, "end_nanos": 1750790097839995000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.1", "defs": {}, "data": {"pdl__expr": "\nFind a random number between 1 and 20\n", "pdl__result": "\nFind a random number between 1 and 20\n"}, "pdl__result": "\nFind a random number between 1 and 20\n", "pdl__timing": {"start_nanos": 1750790097840106000, "end_nanos": 1750790097840248000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "code", "pdl__id": "text.2.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "text.2.code", "defs": {}, "data": {"pdl__expr": "import random\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = random.randint(1, 20)\n", "pdl__result": "import random\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = random.randint(1, 20)\n"}, "pdl__result": "import random\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = random.randint(1, 20)\n", "pdl__timing": {"start_nanos": 1750790097840626000, "end_nanos": 1750790097840742000, "timezone": "EDT"}, "pdl__is_leaf": true}, "def": "N", "pdl__result": 11, "pdl__timing": {"start_nanos": 1750790097840512000, "end_nanos": 1750790097841165000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.3", "defs": {}, "data": {"pdl__expr": "\nNow computing fibonacci(${ N })\n", "pdl__result": "\nNow computing fibonacci(11)\n"}, "pdl__result": "\nNow computing fibonacci(11)\n", "pdl__timing": {"start_nanos": 1750790097841231000, "end_nanos": 1750790097842661000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "code", "pdl__id": "text.4.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "text.4.code", "defs": {}, "data": {"pdl__expr": "s = \"\"\"'${ CODE } '\"\"\"\nresult = s.split(\"```\")[1].replace(\"python\", \"\")\n", "pdl__result": "s = \"\"\"'Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear. '\"\"\"\nresult = s.split(\"```\")[1].replace(\"python\", \"\")\n"}, "pdl__result": "s = \"\"\"'Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear. '\"\"\"\nresult = s.split(\"```\")[1].replace(\"python\", \"\")\n", "pdl__timing": {"start_nanos": 1750790097842906000, "end_nanos": 1750790097844013000, "timezone": "EDT"}, "pdl__is_leaf": true}, "def": "EXTRACTED", "pdl__result": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__timing": {"start_nanos": 1750790097842833000, "end_nanos": 1750790097844328000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "code", "pdl__id": "text.5.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "text.5.code", "defs": {}, "data": {"pdl__expr": "${ EXTRACTED }\nresult = fibonacci(${ N })\n", "pdl__result": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n\nresult = fibonacci(11)\n"}, "pdl__result": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n\nresult = fibonacci(11)\n", "pdl__timing": {"start_nanos": 1750790097844480000, "end_nanos": 1750790097845736000, "timezone": "EDT"}, "pdl__is_leaf": true}, "def": "RESULT", "contribute": [], "pdl__result": 55, "pdl__timing": {"start_nanos": 1750790097844407000, "end_nanos": 1750790097846042000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.6", "defs": {}, "data": {"pdl__expr": "The result is: ${ RESULT }", "pdl__result": "The result is: 55"}, "pdl__result": "The result is: 55", "pdl__timing": {"start_nanos": 1750790097846096000, "end_nanos": 1750790097846998000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.7", "defs": {}, "data": {"pdl__expr": "\n\nExplain what the above code does and what the result means\n\n", "pdl__result": "\n\nExplain what the above code does and what the result means\n\n"}, "pdl__result": "\n\nExplain what the above code does and what the result means\n\n", "pdl__timing": {"start_nanos": 1750790097847155000, "end_nanos": 1750790097847272000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.8.model", "pdl__context": [{"content": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "role": "assistant", "pdl__defsite": "text.0.model"}, {"role": "user", "content": "\nFind a random number between 1 and 20\n", "pdl__defsite": "text.1"}, {"role": "user", "content": "11", "pdl__defsite": "text.2.code"}, {"role": "user", "content": "\nNow computing fibonacci(11)\n", "pdl__defsite": "text.3"}, {"role": "user", "content": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__defsite": "text.4.code"}, {"role": "user", "content": "The result is: 55", "pdl__defsite": "text.6"}, {"role": "user", "content": "\n\nExplain what the above code does and what the result means\n\n", "pdl__defsite": "text.7"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.8.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"content": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "role": "assistant", "pdl__defsite": "text.0.model"}, {"role": "user", "content": "\nFind a random number between 1 and 20\n", "pdl__defsite": "text.1"}, {"role": "user", "content": "11", "pdl__defsite": "text.2.code"}, {"role": "user", "content": "\nNow computing fibonacci(11)\n", "pdl__defsite": "text.3"}, {"role": "user", "content": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__defsite": "text.4.code"}, {"role": "user", "content": "The result is: 55", "pdl__defsite": "text.6"}, {"role": "user", "content": "\n\nExplain what the above code does and what the result means\n\n", "pdl__defsite": "text.7"}]}, "pdl__result": [{"content": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "role": "assistant", "pdl__defsite": "text.0.model"}, {"role": "user", "content": "\nFind a random number between 1 and 20\n", "pdl__defsite": "text.1"}, {"role": "user", "content": "11", "pdl__defsite": "text.2.code"}, {"role": "user", "content": "\nNow computing fibonacci(11)\n", "pdl__defsite": "text.3"}, {"role": "user", "content": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__defsite": "text.4.code"}, {"role": "user", "content": "The result is: 55", "pdl__defsite": "text.6"}, {"role": "user", "content": "\n\nExplain what the above code does and what the result means\n\n", "pdl__defsite": "text.7"}], "pdl__timing": {"start_nanos": 1750790097847734000, "end_nanos": 1750790097848747000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 479, "prompt_tokens": 427}, "pdl__model_input": [{"content": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.", "role": "assistant", "pdl__defsite": "text.0.model"}, {"role": "user", "content": "\nFind a random number between 1 and 20\n", "pdl__defsite": "text.1"}, {"role": "user", "content": "11", "pdl__defsite": "text.2.code"}, {"role": "user", "content": "\nNow computing fibonacci(11)\n", "pdl__defsite": "text.3"}, {"role": "user", "content": "\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n", "pdl__defsite": "text.4.code"}, {"role": "user", "content": "The result is: 55", "pdl__defsite": "text.6"}, {"role": "user", "content": "\n\nExplain what the above code does and what the result means\n\n", "pdl__defsite": "text.7"}], "pdl__result": "The provided Python code defines a function called `fibonacci` that calculates the nth number in the Fibonacci sequence using recursion. The Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones, usually starting with 0 and 1 (0, 1, 1, 2, 3, 5, 8, ...).\n\nHere's what the code does:\n\n1. It checks if the input `n` is less than or equal to zero; if so, it returns a message indicating that the input should be a positive integer.\n2. If `n` equals 1, it returns 0 (the first number in the Fibonacci sequence).\n3. If `n` equals 2, it returns 1 (the second number in the Fibonacci sequence).\n4. For any other value of `n`, it recursively calls itself with arguments `n - 1` and `n - 2`, then adds the results together to get the nth Fibonacci number.\n\nNow let's compute `fibonacci(11)` using this function:\n\n- The base cases are handled first:\n - `fibonacci(1) = 0`\n - `fibonacci(2) = 1`\n\n- Next, we calculate the value for `n = 3`:\n - `fibonacci(3) = fibonacci(2) + fibonacci(1) = 1 + 0 = 1`\n\n- Then, we compute `fibonacci(4)` using previously calculated values:\n - `fibonacci(4) = fibonacci(3) + fibonacci(2) = 1 + 1 = 2`\n\n- Continuing this process for each value up to `n = 11`:\n\n - `fibonacci(5) = fibonacci(4) + fibonacci(3) = 2 + 1 = 3`\n - `fibonacci(6) = fibonacci(5) + fibonacci(4) = 3 + 2 = 5`\n - ...\n - `fibonacci(11) = fibonacci(10) + fibonacci(9) = 55 + 34 = 89`\n\nThe result of `fibonacci(11)` is **89**. This means that the 11th number in the Fibonacci sequence, starting with 0 and 1, is 89.", "pdl__timing": {"start_nanos": 1750790097847515000, "end_nanos": 1750790158829255000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "Here is a simple Python function that computes the Fibonacci sequence using recursion:\n\n```python\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\n```\n\nThis function takes an integer `n` as input and returns the nth number in the Fibonacci sequence. However, it's important to note that this implementation has exponential time complexity due to repeated calculations of the same subproblems (i.e., it performs a lot of redundant work). For larger inputs, you should use an iterative approach or memoization to improve performance:\n\n```python\ndef fibonacci_iterative(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n\n fib_values = [0, 1] + [0] * (n - 2)\n for i in range(2, n):\n fib_values[i] = fib_values[i - 1] + fib_values[i - 2]\n return fib_values[n - 1]\n```\n\nThis version of the function uses an iterative approach with a list to store previously computed Fibonacci numbers, reducing time complexity to linear.\nFind a random number between 1 and 20\n11\nNow computing fibonacci(11)\n\ndef fibonacci(n):\n if n <= 0:\n return \"Input should be a positive integer.\"\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)\nThe result is: 55\n\nExplain what the above code does and what the result means\n\nThe provided Python code defines a function called `fibonacci` that calculates the nth number in the Fibonacci sequence using recursion. The Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones, usually starting with 0 and 1 (0, 1, 1, 2, 3, 5, 8, ...).\n\nHere's what the code does:\n\n1. It checks if the input `n` is less than or equal to zero; if so, it returns a message indicating that the input should be a positive integer.\n2. If `n` equals 1, it returns 0 (the first number in the Fibonacci sequence).\n3. If `n` equals 2, it returns 1 (the second number in the Fibonacci sequence).\n4. For any other value of `n`, it recursively calls itself with arguments `n - 1` and `n - 2`, then adds the results together to get the nth Fibonacci number.\n\nNow let's compute `fibonacci(11)` using this function:\n\n- The base cases are handled first:\n - `fibonacci(1) = 0`\n - `fibonacci(2) = 1`\n\n- Next, we calculate the value for `n = 3`:\n - `fibonacci(3) = fibonacci(2) + fibonacci(1) = 1 + 0 = 1`\n\n- Then, we compute `fibonacci(4)` using previously calculated values:\n - `fibonacci(4) = fibonacci(3) + fibonacci(2) = 1 + 1 = 2`\n\n- Continuing this process for each value up to `n = 11`:\n\n - `fibonacci(5) = fibonacci(4) + fibonacci(3) = 2 + 1 = 3`\n - `fibonacci(6) = fibonacci(5) + fibonacci(4) = 3 + 2 = 5`\n - ...\n - `fibonacci(11) = fibonacci(10) + fibonacci(9) = 55 + 34 = 89`\n\nThe result of `fibonacci(11)` is **89**. This means that the 11th number in the Fibonacci sequence, starting with 0 and 1, is 89.", "pdl__timing": {"start_nanos": 1750790073405758000, "end_nanos": 1750790158829358000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file diff --git a/pdl-live-react/src/demos/demo4.json b/pdl-live-react/src/demos/demo4.json index b2dd9af92..a273ec807 100644 --- a/pdl-live-react/src/demos/demo4.json +++ b/pdl-live-react/src/demos/demo4.json @@ -1 +1 @@ -{"kind": "text", "pdl__id": "text", "description": "Chatbot", "defs": {}, "text": [{"kind": "read", "pdl__id": "text.0.read", "defs": {}, "read": {"pdl__expr": null}, "message": "What is your query?\n", "multiline": false, "pdl__result": "what is the fastest animal?", "pdl__timing": {"start_nanos": 1742524146487394000, "end_nanos": 1742524146487686000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "repeat", "pdl__id": "text.1.repeat", "defs": {}, "while": true, "repeat": {"kind": "text", "pdl__id": "text.1.repeat.1.text", "defs": {}, "text": [{"kind": "model", "pdl__id": "text.1.repeat.1.text.0.model", "defs": {}, "platform": "litellm", "model": "ollama_chat/granite3.2:2b", "input": "${ pdl_context }", "pdl__timing": {"start_nanos": 1742524160465685000, "end_nanos": 1742524192074275000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "read", "pdl__id": "text.1.repeat.1.text.1.read", "defs": {}, "read": null, "message": "\nIs this a good answer[yes/no]?\n", "multiline": false, "def": "eval", "pdl__timing": {"start_nanos": 1742524192074377000, "end_nanos": 1742524192074637000, "timezone": "EDT"}, "pdl__is_leaf": true}, "\n", {"kind": "if", "pdl__id": "text.1.repeat.1.text.3.if", "defs": {}, "if": "${ eval == 'no' }", "then": {"kind": "text", "pdl__id": "text.1.repeat.0.text.3.if.0.text", "defs": {}, "text": [{"kind": "read", "pdl__id": "text.1.repeat.0.text.3.if.0.text.0.read", "defs": {}, "read": null, "message": "Why not?\n", "multiline": false, "pdl__timing": {"start_nanos": 1742524160463244000, "end_nanos": 1742524160463496000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__timing": {"start_nanos": 1742524160463037000, "end_nanos": 1742524160463571000, "timezone": "EDT"}, "pdl__is_leaf": false}, "pdl__timing": {"start_nanos": 1742524192075487000, "end_nanos": 1742524192076573000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__timing": {"start_nanos": 1742524160465535000, "end_nanos": 1742524192076626000, "timezone": "EDT"}, "pdl__is_leaf": false}, "until": "${ eval == 'yes'}", "join": {"with": ""}, "pdl__trace": [{"kind": "text", "pdl__id": "text.1.repeat.0.text", "defs": {}, "text": [{"kind": "model", "pdl__id": "text.1.repeat.0.text.0.model", "pdl__context": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.repeat.0.text.0.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}]}, "pdl__result": "[{\"role\": \"user\", \"content\": \"what is the fastest animal?\", \"pdl__defsite\": \"text.0.read\"}]", "pdl__timing": {"start_nanos": 1742524146490331000, "end_nanos": 1742524146491814000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 87, "prompt_tokens": 17}, "pdl__model_input": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}], "pdl__result": "The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.", "pdl__timing": {"start_nanos": 1742524146488053000, "end_nanos": 1742524160456680000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "read", "pdl__id": "text.1.repeat.0.text.1.read", "defs": {}, "read": {"pdl__expr": null}, "message": "\nIs this a good answer[yes/no]?\n", "multiline": false, "def": "eval", "pdl__result": "no", "pdl__timing": {"start_nanos": 1742524160456848000, "end_nanos": 1742524160457360000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.1.repeat.0.text.2", "defs": {}, "data": {"pdl__expr": "\n", "pdl__result": "\n"}, "pdl__result": "\n", "pdl__timing": {"start_nanos": 1742524160457445000, "end_nanos": 1742524160458798000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "if", "pdl__id": "text.1.repeat.0.text.3.if", "defs": {}, "if": {"pdl__expr": "${ eval == 'no' }", "pdl__result": true}, "then": {"kind": "text", "pdl__id": "text.1.repeat.0.text.3.if.0.text", "defs": {}, "text": [{"kind": "read", "pdl__id": "text.1.repeat.0.text.3.if.0.text.0.read", "defs": {}, "read": {"pdl__expr": null}, "message": "Why not?\n", "multiline": false, "pdl__result": "in europe?", "pdl__timing": {"start_nanos": 1742524160463244000, "end_nanos": 1742524160463496000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "in europe?", "pdl__timing": {"start_nanos": 1742524160463037000, "end_nanos": 1742524160463571000, "timezone": "EDT"}, "pdl__is_leaf": false}, "if_result": true, "pdl__result": "in europe?", "pdl__timing": {"start_nanos": 1742524160459038000, "end_nanos": 1742524160463635000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.no\nin europe?", "pdl__timing": {"start_nanos": 1742524146487907000, "end_nanos": 1742524160463700000, "timezone": "EDT"}, "pdl__is_leaf": false}, {"kind": "text", "pdl__id": "text.1.repeat.1.text", "defs": {}, "text": [{"kind": "model", "pdl__id": "text.1.repeat.1.text.0.model", "pdl__context": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}, {"content": "The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.", "role": "assistant", "pdl__defsite": "text.1.repeat.1.text.0.model"}, {"role": "user", "content": "no", "pdl__defsite": "text.1.repeat.0.text.1.read"}, {"role": "user", "content": "\n", "pdl__defsite": "text.1.repeat.0.text.2"}, {"role": "user", "content": "in europe?", "pdl__defsite": "text.1.repeat.0.text.3.if.0.text.0.read"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.repeat.1.text.0.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}, {"content": "The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.", "role": "assistant", "pdl__defsite": "text.1.repeat.1.text.0.model"}, {"role": "user", "content": "no", "pdl__defsite": "text.1.repeat.0.text.1.read"}, {"role": "user", "content": "\n", "pdl__defsite": "text.1.repeat.0.text.2"}, {"role": "user", "content": "in europe?", "pdl__defsite": "text.1.repeat.0.text.3.if.0.text.0.read"}]}, "pdl__result": "[{\"role\": \"user\", \"content\": \"what is the fastest animal?\", \"pdl__defsite\": \"text.0.read\"}, {\"content\": \"The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.\", \"role\": \"assistant\", \"pdl__defsite\": \"text.1.repeat.1.text.0.model\"}, {\"role\": \"user\", \"content\": \"no\", \"pdl__defsite\": \"text.1.repeat.0.text.1.read\"}, {\"role\": \"user\", \"content\": \"\\n\", \"pdl__defsite\": \"text.1.repeat.0.text.2\"}, {\"role\": \"user\", \"content\": \"in europe?\", \"pdl__defsite\": \"text.1.repeat.0.text.3.if.0.text.0.read\"}]", "pdl__timing": {"start_nanos": 1742524160465939000, "end_nanos": 1742524160467083000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 241, "prompt_tokens": 170}, "pdl__model_input": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}, {"content": "The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.", "role": "assistant", "pdl__defsite": "text.1.repeat.1.text.0.model"}, {"role": "user", "content": "no", "pdl__defsite": "text.1.repeat.0.text.1.read"}, {"role": "user", "content": "\n", "pdl__defsite": "text.1.repeat.0.text.2"}, {"role": "user", "content": "in europe?", "pdl__defsite": "text.1.repeat.0.text.3.if.0.text.0.read"}], "pdl__result": "Apologies for the confusion earlier. In Europe, the fastest land animal is still the cheetah, as it has not been significantly affected by human activities or other factors that could potentially limit its speed in a specific region compared to the global average. Cheetahs do not naturally exist in Europe due to historical extinction events and conservation efforts, but they are found in neighboring African countries like Tunisia, Algeria, Morocco, and parts of Iran and Pakistan.\n\nIf you're interested in the fastest European animals, it is worth mentioning that the golden eagle (Aquila chrysaetos) is an impressive soaring bird capable of reaching speeds over 240 miles per hour (386 kilometers per hour) during its dives. This speed occurs in a short, intense maneuver when hunting prey like rabbits or other birds on the ground below.\n\nIn marine life, the sailfish is known for being the fastest fish, reaching speeds up to 75 miles per hour (120 kilometers per hour). This fast swimming behavior is used by sailfish as a means of catching and consuming prey like tuna and dolphinfish.\n\nBoth the golden eagle and the sailfish are remarkable examples of speed in European or marine ecosystems, respectively.", "pdl__timing": {"start_nanos": 1742524160465685000, "end_nanos": 1742524192074275000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "read", "pdl__id": "text.1.repeat.1.text.1.read", "defs": {}, "read": {"pdl__expr": null}, "message": "\nIs this a good answer[yes/no]?\n", "multiline": false, "def": "eval", "pdl__result": "yes", "pdl__timing": {"start_nanos": 1742524192074377000, "end_nanos": 1742524192074637000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.1.repeat.1.text.2", "defs": {}, "data": {"pdl__expr": "\n", "pdl__result": "\n"}, "pdl__result": "\n", "pdl__timing": {"start_nanos": 1742524192074698000, "end_nanos": 1742524192075324000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "if", "pdl__id": "text.1.repeat.1.text.3.if", "defs": {}, "if": {"pdl__expr": "${ eval == 'no' }", "pdl__result": false}, "then": {"kind": "text", "pdl__id": "text.1.repeat.0.text.3.if.0.text", "defs": {}, "text": [{"kind": "read", "pdl__id": "text.1.repeat.0.text.3.if.0.text.0.read", "defs": {}, "read": null, "message": "Why not?\n", "multiline": false, "pdl__timing": {"start_nanos": 1742524160463244000, "end_nanos": 1742524160463496000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__timing": {"start_nanos": 1742524160463037000, "end_nanos": 1742524160463571000, "timezone": "EDT"}, "pdl__is_leaf": false}, "if_result": false, "pdl__result": "", "pdl__timing": {"start_nanos": 1742524192075487000, "end_nanos": 1742524192076573000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "Apologies for the confusion earlier. In Europe, the fastest land animal is still the cheetah, as it has not been significantly affected by human activities or other factors that could potentially limit its speed in a specific region compared to the global average. Cheetahs do not naturally exist in Europe due to historical extinction events and conservation efforts, but they are found in neighboring African countries like Tunisia, Algeria, Morocco, and parts of Iran and Pakistan.\n\nIf you're interested in the fastest European animals, it is worth mentioning that the golden eagle (Aquila chrysaetos) is an impressive soaring bird capable of reaching speeds over 240 miles per hour (386 kilometers per hour) during its dives. This speed occurs in a short, intense maneuver when hunting prey like rabbits or other birds on the ground below.\n\nIn marine life, the sailfish is known for being the fastest fish, reaching speeds up to 75 miles per hour (120 kilometers per hour). This fast swimming behavior is used by sailfish as a means of catching and consuming prey like tuna and dolphinfish.\n\nBoth the golden eagle and the sailfish are remarkable examples of speed in European or marine ecosystems, respectively.yes\n", "pdl__timing": {"start_nanos": 1742524160465535000, "end_nanos": 1742524192076626000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.no\nin europe?Apologies for the confusion earlier. In Europe, the fastest land animal is still the cheetah, as it has not been significantly affected by human activities or other factors that could potentially limit its speed in a specific region compared to the global average. Cheetahs do not naturally exist in Europe due to historical extinction events and conservation efforts, but they are found in neighboring African countries like Tunisia, Algeria, Morocco, and parts of Iran and Pakistan.\n\nIf you're interested in the fastest European animals, it is worth mentioning that the golden eagle (Aquila chrysaetos) is an impressive soaring bird capable of reaching speeds over 240 miles per hour (386 kilometers per hour) during its dives. This speed occurs in a short, intense maneuver when hunting prey like rabbits or other birds on the ground below.\n\nIn marine life, the sailfish is known for being the fastest fish, reaching speeds up to 75 miles per hour (120 kilometers per hour). This fast swimming behavior is used by sailfish as a means of catching and consuming prey like tuna and dolphinfish.\n\nBoth the golden eagle and the sailfish are remarkable examples of speed in European or marine ecosystems, respectively.yes\n", "pdl__timing": {"start_nanos": 1742524146487766000, "end_nanos": 1742524192077769000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "what is the fastest animal?The fastest land animal is the cheetah, with an average speed of around 60-70 miles per hour (97-113 kilometers per hour) in short bursts covering distances up to about 1,500 feet (460 meters). This incredible speed is due to its unique physical adaptations, including a long, muscular body, flexible spine, and large, rounded toes that act like suction cups, enabling it to change direction quickly.no\nin europe?Apologies for the confusion earlier. In Europe, the fastest land animal is still the cheetah, as it has not been significantly affected by human activities or other factors that could potentially limit its speed in a specific region compared to the global average. Cheetahs do not naturally exist in Europe due to historical extinction events and conservation efforts, but they are found in neighboring African countries like Tunisia, Algeria, Morocco, and parts of Iran and Pakistan.\n\nIf you're interested in the fastest European animals, it is worth mentioning that the golden eagle (Aquila chrysaetos) is an impressive soaring bird capable of reaching speeds over 240 miles per hour (386 kilometers per hour) during its dives. This speed occurs in a short, intense maneuver when hunting prey like rabbits or other birds on the ground below.\n\nIn marine life, the sailfish is known for being the fastest fish, reaching speeds up to 75 miles per hour (120 kilometers per hour). This fast swimming behavior is used by sailfish as a means of catching and consuming prey like tuna and dolphinfish.\n\nBoth the golden eagle and the sailfish are remarkable examples of speed in European or marine ecosystems, respectively.yes\n", "pdl__timing": {"start_nanos": 1742524146487193000, "end_nanos": 1742524192077831000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file +{"kind": "text", "pdl__id": "text", "description": "A Chatbot that responds to user's questions", "defs": {}, "context": "dependent", "text": [{"kind": "read", "pdl__id": "text.0.read", "defs": {}, "read": {"pdl__expr": null}, "message": "What is your query?\n", "multiline": false, "pdl__result": "what is the fastest animal?", "pdl__timing": {"start_nanos": 1750790161423592000, "end_nanos": 1750790161424042000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "repeat", "pdl__id": "text.1.repeat", "defs": {}, "context": "dependent", "while": true, "repeat": {"kind": "text", "pdl__id": "text.1.repeat.1.text", "defs": {}, "context": "dependent", "text": [{"kind": "model", "pdl__id": "text.1.repeat.1.text.0.model", "defs": {}, "platform": "litellm", "model": "ollama_chat/granite3.2:2b", "input": "${ pdl_context }", "pdl__timing": {"start_nanos": 1750790193774187000, "end_nanos": 1750790241578995000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "read", "pdl__id": "text.1.repeat.1.text.1.read", "defs": {}, "read": null, "message": "\nIs this a good answer[yes/no]?\n", "multiline": false, "def": "eval", "pdl__timing": {"start_nanos": 1750790241579111000, "end_nanos": 1750790241579422000, "timezone": "EDT"}, "pdl__is_leaf": true}, "\n", {"kind": "if", "pdl__id": "text.1.repeat.1.text.3.if", "defs": {}, "context": "dependent", "if": "${ eval == 'no' }", "then": {"kind": "text", "pdl__id": "text.1.repeat.0.text.3.if.0.text", "defs": {}, "context": "dependent", "text": [{"kind": "read", "pdl__id": "text.1.repeat.0.text.3.if.0.text.0.read", "defs": {}, "read": null, "message": "Why not?\n", "multiline": false, "pdl__timing": {"start_nanos": 1750790193772348000, "end_nanos": 1750790193772540000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__timing": {"start_nanos": 1750790193772192000, "end_nanos": 1750790193772608000, "timezone": "EDT"}, "pdl__is_leaf": false}, "pdl__timing": {"start_nanos": 1750790241580453000, "end_nanos": 1750790241581880000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__timing": {"start_nanos": 1750790193774066000, "end_nanos": 1750790241581951000, "timezone": "EDT"}, "pdl__is_leaf": false}, "until": "${ eval == 'yes'}", "join": {"with": ""}, "pdl__trace": [{"kind": "text", "pdl__id": "text.1.repeat.0.text", "defs": {}, "context": "dependent", "text": [{"kind": "model", "pdl__id": "text.1.repeat.0.text.0.model", "pdl__context": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.repeat.0.text.0.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}]}, "pdl__result": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}], "pdl__timing": {"start_nanos": 1750790161431221000, "end_nanos": 1750790161432629000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 337, "prompt_tokens": 13}, "pdl__model_input": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}], "pdl__result": "The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.", "pdl__timing": {"start_nanos": 1750790161428969000, "end_nanos": 1750790193765379000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "read", "pdl__id": "text.1.repeat.0.text.1.read", "defs": {}, "read": {"pdl__expr": null}, "message": "\nIs this a good answer[yes/no]?\n", "multiline": false, "def": "eval", "pdl__result": "no", "pdl__timing": {"start_nanos": 1750790193765504000, "end_nanos": 1750790193766076000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.1.repeat.0.text.2", "defs": {}, "data": {"pdl__expr": "\n", "pdl__result": "\n"}, "pdl__result": "\n", "pdl__timing": {"start_nanos": 1750790193766146000, "end_nanos": 1750790193767113000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "if", "pdl__id": "text.1.repeat.0.text.3.if", "defs": {}, "context": "dependent", "if": {"pdl__expr": "${ eval == 'no' }", "pdl__result": true}, "then": {"kind": "text", "pdl__id": "text.1.repeat.0.text.3.if.0.text", "defs": {}, "context": "dependent", "text": [{"kind": "read", "pdl__id": "text.1.repeat.0.text.3.if.0.text.0.read", "defs": {}, "read": {"pdl__expr": null}, "message": "Why not?\n", "multiline": false, "pdl__result": "in europe?", "pdl__timing": {"start_nanos": 1750790193772348000, "end_nanos": 1750790193772540000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "in europe?", "pdl__timing": {"start_nanos": 1750790193772192000, "end_nanos": 1750790193772608000, "timezone": "EDT"}, "pdl__is_leaf": false}, "pdl__result": "in europe?", "pdl__timing": {"start_nanos": 1750790193767335000, "end_nanos": 1750790193772650000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.no\nin europe?", "pdl__timing": {"start_nanos": 1750790161424514000, "end_nanos": 1750790193772710000, "timezone": "EDT"}, "pdl__is_leaf": false}, {"kind": "text", "pdl__id": "text.1.repeat.1.text", "defs": {}, "context": "dependent", "text": [{"kind": "model", "pdl__id": "text.1.repeat.1.text.0.model", "pdl__context": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}, {"content": "The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.", "role": "assistant", "pdl__defsite": "text.1.repeat.1.text.0.model"}, {"role": "user", "content": "no", "pdl__defsite": "text.1.repeat.0.text.1.read"}, {"role": "user", "content": "\n", "pdl__defsite": "text.1.repeat.0.text.2"}, {"role": "user", "content": "in europe?", "pdl__defsite": "text.1.repeat.0.text.3.if.0.text.0.read"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.repeat.1.text.0.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}, {"content": "The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.", "role": "assistant", "pdl__defsite": "text.1.repeat.1.text.0.model"}, {"role": "user", "content": "no", "pdl__defsite": "text.1.repeat.0.text.1.read"}, {"role": "user", "content": "\n", "pdl__defsite": "text.1.repeat.0.text.2"}, {"role": "user", "content": "in europe?", "pdl__defsite": "text.1.repeat.0.text.3.if.0.text.0.read"}]}, "pdl__result": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}, {"content": "The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.", "role": "assistant", "pdl__defsite": "text.1.repeat.1.text.0.model"}, {"role": "user", "content": "no", "pdl__defsite": "text.1.repeat.0.text.1.read"}, {"role": "user", "content": "\n", "pdl__defsite": "text.1.repeat.0.text.2"}, {"role": "user", "content": "in europe?", "pdl__defsite": "text.1.repeat.0.text.3.if.0.text.0.read"}], "pdl__timing": {"start_nanos": 1750790193774407000, "end_nanos": 1750790193775291000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 343, "prompt_tokens": 371}, "pdl__model_input": [{"role": "user", "content": "what is the fastest animal?", "pdl__defsite": "text.0.read"}, {"content": "The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.", "role": "assistant", "pdl__defsite": "text.1.repeat.1.text.0.model"}, {"role": "user", "content": "no", "pdl__defsite": "text.1.repeat.0.text.1.read"}, {"role": "user", "content": "\n", "pdl__defsite": "text.1.repeat.0.text.2"}, {"role": "user", "content": "in europe?", "pdl__defsite": "text.1.repeat.0.text.3.if.0.text.0.read"}], "pdl__result": "In Europe, the fastest land animal is typically considered to be the greyhound (Canis lupus familiaris). Greyhards are well-known for their exceptional speed and agility in racing events. Here's a brief overview of why they hold this title:\n\n1. Muscular build: Greyhounds have a lean, muscular body with long, slender legs and a flexible spine, which allows them to cover ground quickly.\n2. Short, powerful limbs: Their short, strong legs enable efficient propulsion during high-speed runs.\n3. Lightweight frame: Greyhounds are relatively small dogs with lightweight frames, reducing the amount of energy required for movement.\n4. Specialized paws and nails: They have compact, muscular feet with non-retractable claws that provide traction on various surfaces while minimizing air resistance during high speeds.\n5. Efficient respiratory system: Greyhounds possess a well-developed lung capacity and heart, allowing them to take in more oxygen per breath and pump blood efficiently for sustained performance.\n6. Short coat: Their short, smooth coats help regulate body temperature during intense exercise while providing some protection from the sun's rays.\n7. High-speed running style: Greyhounds run with a unique \"racing\" gait called a trot or lope, where their bodies are almost horizontal to reduce air resistance and maximize speed.\n\nWhile cheetahs are the fastest animal overall, greyhounds excel in European races due to their breeding for speed and adaptation to the terrain they typically race on \u2013 usually flat, open spaces with minimal obstacles. Greyhounds can reach impressive top speeds of around 43-45 miles per hour (70 kilometers per hour), making them formidable competitors in European racing events.", "pdl__timing": {"start_nanos": 1750790193774187000, "end_nanos": 1750790241578995000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "read", "pdl__id": "text.1.repeat.1.text.1.read", "defs": {}, "read": {"pdl__expr": null}, "message": "\nIs this a good answer[yes/no]?\n", "multiline": false, "def": "eval", "pdl__result": "yes", "pdl__timing": {"start_nanos": 1750790241579111000, "end_nanos": 1750790241579422000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.1.repeat.1.text.2", "defs": {}, "data": {"pdl__expr": "\n", "pdl__result": "\n"}, "pdl__result": "\n", "pdl__timing": {"start_nanos": 1750790241579481000, "end_nanos": 1750790241580266000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "if", "pdl__id": "text.1.repeat.1.text.3.if", "defs": {}, "context": "dependent", "if": {"pdl__expr": "${ eval == 'no' }", "pdl__result": false}, "then": {"kind": "text", "pdl__id": "text.1.repeat.0.text.3.if.0.text", "defs": {}, "context": "dependent", "text": [{"kind": "read", "pdl__id": "text.1.repeat.0.text.3.if.0.text.0.read", "defs": {}, "read": null, "message": "Why not?\n", "multiline": false, "pdl__timing": {"start_nanos": 1750790193772348000, "end_nanos": 1750790193772540000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__timing": {"start_nanos": 1750790193772192000, "end_nanos": 1750790193772608000, "timezone": "EDT"}, "pdl__is_leaf": false}, "pdl__result": "", "pdl__timing": {"start_nanos": 1750790241580453000, "end_nanos": 1750790241581880000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "In Europe, the fastest land animal is typically considered to be the greyhound (Canis lupus familiaris). Greyhards are well-known for their exceptional speed and agility in racing events. Here's a brief overview of why they hold this title:\n\n1. Muscular build: Greyhounds have a lean, muscular body with long, slender legs and a flexible spine, which allows them to cover ground quickly.\n2. Short, powerful limbs: Their short, strong legs enable efficient propulsion during high-speed runs.\n3. Lightweight frame: Greyhounds are relatively small dogs with lightweight frames, reducing the amount of energy required for movement.\n4. Specialized paws and nails: They have compact, muscular feet with non-retractable claws that provide traction on various surfaces while minimizing air resistance during high speeds.\n5. Efficient respiratory system: Greyhounds possess a well-developed lung capacity and heart, allowing them to take in more oxygen per breath and pump blood efficiently for sustained performance.\n6. Short coat: Their short, smooth coats help regulate body temperature during intense exercise while providing some protection from the sun's rays.\n7. High-speed running style: Greyhounds run with a unique \"racing\" gait called a trot or lope, where their bodies are almost horizontal to reduce air resistance and maximize speed.\n\nWhile cheetahs are the fastest animal overall, greyhounds excel in European races due to their breeding for speed and adaptation to the terrain they typically race on \u2013 usually flat, open spaces with minimal obstacles. Greyhounds can reach impressive top speeds of around 43-45 miles per hour (70 kilometers per hour), making them formidable competitors in European racing events.yes\n", "pdl__timing": {"start_nanos": 1750790193774066000, "end_nanos": 1750790241581951000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.no\nin europe?In Europe, the fastest land animal is typically considered to be the greyhound (Canis lupus familiaris). Greyhards are well-known for their exceptional speed and agility in racing events. Here's a brief overview of why they hold this title:\n\n1. Muscular build: Greyhounds have a lean, muscular body with long, slender legs and a flexible spine, which allows them to cover ground quickly.\n2. Short, powerful limbs: Their short, strong legs enable efficient propulsion during high-speed runs.\n3. Lightweight frame: Greyhounds are relatively small dogs with lightweight frames, reducing the amount of energy required for movement.\n4. Specialized paws and nails: They have compact, muscular feet with non-retractable claws that provide traction on various surfaces while minimizing air resistance during high speeds.\n5. Efficient respiratory system: Greyhounds possess a well-developed lung capacity and heart, allowing them to take in more oxygen per breath and pump blood efficiently for sustained performance.\n6. Short coat: Their short, smooth coats help regulate body temperature during intense exercise while providing some protection from the sun's rays.\n7. High-speed running style: Greyhounds run with a unique \"racing\" gait called a trot or lope, where their bodies are almost horizontal to reduce air resistance and maximize speed.\n\nWhile cheetahs are the fastest animal overall, greyhounds excel in European races due to their breeding for speed and adaptation to the terrain they typically race on \u2013 usually flat, open spaces with minimal obstacles. Greyhounds can reach impressive top speeds of around 43-45 miles per hour (70 kilometers per hour), making them formidable competitors in European racing events.yes\n", "pdl__timing": {"start_nanos": 1750790161424213000, "end_nanos": 1750790241583341000, "timezone": "EDT"}, "pdl__is_leaf": false}], "pdl__result": "what is the fastest animal?The fastest animal in the world is the cheetah (Acinonyx jubatus). This remarkable creature can reach speeds up to 60-70 miles per hour (97-113 kilometers per hour) over short distances, making it the swiftest land animal. Cheetahs have several adaptations that contribute to their incredible speed:\n\n1. Muscular build: Cheetahs possess a lean, muscular body with long, slender limbs and a flexible spine, which allows for efficient movement during high-speed chases.\n2. Large lungs and heart: Their powerful respiratory system enables them to take in more oxygen per breath, while their enlarged heart pumps blood rapidly to supply the muscles with energy.\n3. Specialized claws: Cheetahs have retractable claws that provide traction during acceleration and help maintain grip on prey or terrain.\n4. Flexible spine: Their flexible spines allow for a running style called \"streaking,\" where the body is almost horizontal, reducing air resistance and enabling faster top speeds.\n5. Short, muscular tail: Cheetahs use their tails as an aerodynamic rudder to help maintain balance during high-speed pursuits.\n6. Blood composition: Their unique blood composition enables efficient oxygen transport, which is crucial for sustaining such intense activity.\n7. Thick fur coat: Cheetahs have a short, dense coat that helps regulate body temperature during high-speed chases and protects them from the sun's harmful rays.\n\nDespite their incredible speed, cheetahs are not built for endurance running; they can only maintain these top speeds for about 30 seconds to a minute before tiring due to the energy demands of such intense activity.no\nin europe?In Europe, the fastest land animal is typically considered to be the greyhound (Canis lupus familiaris). Greyhards are well-known for their exceptional speed and agility in racing events. Here's a brief overview of why they hold this title:\n\n1. Muscular build: Greyhounds have a lean, muscular body with long, slender legs and a flexible spine, which allows them to cover ground quickly.\n2. Short, powerful limbs: Their short, strong legs enable efficient propulsion during high-speed runs.\n3. Lightweight frame: Greyhounds are relatively small dogs with lightweight frames, reducing the amount of energy required for movement.\n4. Specialized paws and nails: They have compact, muscular feet with non-retractable claws that provide traction on various surfaces while minimizing air resistance during high speeds.\n5. Efficient respiratory system: Greyhounds possess a well-developed lung capacity and heart, allowing them to take in more oxygen per breath and pump blood efficiently for sustained performance.\n6. Short coat: Their short, smooth coats help regulate body temperature during intense exercise while providing some protection from the sun's rays.\n7. High-speed running style: Greyhounds run with a unique \"racing\" gait called a trot or lope, where their bodies are almost horizontal to reduce air resistance and maximize speed.\n\nWhile cheetahs are the fastest animal overall, greyhounds excel in European races due to their breeding for speed and adaptation to the terrain they typically race on \u2013 usually flat, open spaces with minimal obstacles. Greyhounds can reach impressive top speeds of around 43-45 miles per hour (70 kilometers per hour), making them formidable competitors in European racing events.yes\n", "pdl__timing": {"start_nanos": 1750790161271896000, "end_nanos": 1750790241583438000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file diff --git a/pdl-live-react/src/demos/demo5.json b/pdl-live-react/src/demos/demo5.json index 9534c25f6..653e0b718 100644 --- a/pdl-live-react/src/demos/demo5.json +++ b/pdl-live-react/src/demos/demo5.json @@ -1 +1 @@ -{"kind": "text", "pdl__id": "text", "description": "Code explanation example", "defs": {"CODE": {"kind": "read", "pdl__id": "text.0.read", "defs": {}, "read": {"pdl__expr": "./data.yaml", "pdl__result": "./data.yaml"}, "message": null, "multiline": false, "pdl__result": "source_code: \n |\n @SuppressWarnings(\"unchecked\")\n public static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n }\nrepo_info: \n repo: streamsets/datacollector\n path: stagesupport/src/main/java/com/.../OffsetUtil.java\n function_name: OffsetUtil.deserializeOffsetMap", "parser": "yaml", "pdl__timing": {"start_nanos": 1742524193622321000, "end_nanos": 1742524193624419000, "timezone": "EDT"}, "pdl__is_leaf": true}, "TRUTH": {"kind": "read", "pdl__id": "text.1.read", "defs": {}, "read": {"pdl__expr": "./ground_truth.txt", "pdl__result": "./ground_truth.txt"}, "message": null, "multiline": false, "pdl__result": "The function `deserializeOffsetMap` takes a string as input and returns a map. It first checks if the input string is null or empty. If it is, it creates a new empty map and returns it. Otherwise, it uses the Jackson library to parse the input string into a map and returns it.\n\nThe `@SuppressWarnings(\"unchecked\")` annotation is used to suppress the warning that the type of the parsed map is not checked. This is because the Jackson library is used to parse the input string into a map, but the specific type of the map is not known at compile time. Therefore, the warning is suppressed to avoid potential issues.", "pdl__timing": {"start_nanos": 1742524193624508000, "end_nanos": 1742524193625221000, "timezone": "EDT"}, "pdl__is_leaf": true}}, "text": [{"kind": "model", "pdl__id": "text.0.model", "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.0.model", "defs": {}, "data": {"pdl__expr": "Here is some info about the location of the function in the repo.\nrepo:\n${ CODE.repo_info.repo }\npath: ${ CODE.repo_info.path }\nFunction_name: ${ CODE.repo_info.function_name }\n\n\nExplain the following code:\n```\n${ CODE.source_code }```\n", "pdl__result": "Here is some info about the location of the function in the repo.\nrepo:\nstreamsets/datacollector\npath: stagesupport/src/main/java/com/.../OffsetUtil.java\nFunction_name: OffsetUtil.deserializeOffsetMap\n\n\nExplain the following code:\n```\n@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n```\n"}, "pdl__result": "Here is some info about the location of the function in the repo.\nrepo:\nstreamsets/datacollector\npath: stagesupport/src/main/java/com/.../OffsetUtil.java\nFunction_name: OffsetUtil.deserializeOffsetMap\n\n\nExplain the following code:\n```\n@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n```\n", "pdl__timing": {"start_nanos": 1742524193627194000, "end_nanos": 1742524193630122000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 481, "prompt_tokens": 146}, "pdl__model_input": [{"role": "user", "content": "Here is some info about the location of the function in the repo.\nrepo:\nstreamsets/datacollector\npath: stagesupport/src/main/java/com/.../OffsetUtil.java\nFunction_name: OffsetUtil.deserializeOffsetMap\n\n\nExplain the following code:\n```\n@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n```\n"}], "def": "EXPLANATION", "contribute": [], "pdl__result": "The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (datacollector) repository, specifically located in the `stagesupport/src/main/java/com/` directory. This function is named `deserializeOffsetMap`. Here's a breakdown of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to deserialize a JSON string into a `Map` object. It assumes that the input string represents an offset map in JSON format.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`. This is expected to contain a JSON-formatted offset map. If this value is null or empty (i.e., `null` or `\"\"`), it defaults to a new `HashMap`.\n\n3. **Return Value**: The method returns a `Map` object that represents the deserialized JSON data.\n\n4. **Code Explanation**:\n\n - `@SuppressWarnings(\"unchecked\")`: This annotation is used to suppress potential warnings related to unchecked or raw type usage. In this case, it's safe because we're explicitly casting the result of `JSON_MAPPER.readValue()` to `Map`.\n \n - `if (lastSourceOffset == null || lastSourceOffset.isEmpty()) {`: This conditional checks if the input string is either null or empty. If true, a new `HashMap` is created and assigned to `offsetMap`.\n\n - `offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class);`: If the input string isn't null or empty, this line uses Jackson's `JSON_MAPPER` (presumably an instance of `ObjectMapper`) to deserialize it into a `Map`. The `readValue()` method takes two arguments:\n - The JSON-formatted offset map as a `String`.\n - The class type to which the JSON data should be converted (`Map.class`).\n\n - `return offsetMap;`: Finally, the function returns the deserialized `Map` object.\n\nIn summary, this method safely converts a JSON string into a `Map`, handling null or empty inputs by defaulting to an empty map. It's part of the StreamSets Data Collector codebase and is likely used for processing offset information in data pipelines.", "pdl__timing": {"start_nanos": 1742524193625403000, "end_nanos": 1742524236741061000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "code", "pdl__id": "text.1.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "text.1.code", "defs": {}, "data": {"pdl__expr": "import textdistance\nexpl = \"\"\"\n${ EXPLANATION }\n\"\"\"\ntruth = \"\"\"\n${ TRUTH }\n\"\"\"\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = textdistance.levenshtein.normalized_similarity(expl, truth)\n", "pdl__result": "import textdistance\nexpl = \"\"\"\nThe provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (datacollector) repository, specifically located in the `stagesupport/src/main/java/com/` directory. This function is named `deserializeOffsetMap`. Here's a breakdown of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to deserialize a JSON string into a `Map` object. It assumes that the input string represents an offset map in JSON format.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`. This is expected to contain a JSON-formatted offset map. If this value is null or empty (i.e., `null` or `\"\"`), it defaults to a new `HashMap`.\n\n3. **Return Value**: The method returns a `Map` object that represents the deserialized JSON data.\n\n4. **Code Explanation**:\n\n - `@SuppressWarnings(\"unchecked\")`: This annotation is used to suppress potential warnings related to unchecked or raw type usage. In this case, it's safe because we're explicitly casting the result of `JSON_MAPPER.readValue()` to `Map`.\n \n - `if (lastSourceOffset == null || lastSourceOffset.isEmpty()) {`: This conditional checks if the input string is either null or empty. If true, a new `HashMap` is created and assigned to `offsetMap`.\n\n - `offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class);`: If the input string isn't null or empty, this line uses Jackson's `JSON_MAPPER` (presumably an instance of `ObjectMapper`) to deserialize it into a `Map`. The `readValue()` method takes two arguments:\n - The JSON-formatted offset map as a `String`.\n - The class type to which the JSON data should be converted (`Map.class`).\n\n - `return offsetMap;`: Finally, the function returns the deserialized `Map` object.\n\nIn summary, this method safely converts a JSON string into a `Map`, handling null or empty inputs by defaulting to an empty map. It's part of the StreamSets Data Collector codebase and is likely used for processing offset information in data pipelines.\n\"\"\"\ntruth = \"\"\"\nThe function `deserializeOffsetMap` takes a string as input and returns a map. It first checks if the input string is null or empty. If it is, it creates a new empty map and returns it. Otherwise, it uses the Jackson library to parse the input string into a map and returns it.\n\nThe `@SuppressWarnings(\"unchecked\")` annotation is used to suppress the warning that the type of the parsed map is not checked. This is because the Jackson library is used to parse the input string into a map, but the specific type of the map is not known at compile time. Therefore, the warning is suppressed to avoid potential issues.\n\"\"\"\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = textdistance.levenshtein.normalized_similarity(expl, truth)\n"}, "pdl__result": "import textdistance\nexpl = \"\"\"\nThe provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (datacollector) repository, specifically located in the `stagesupport/src/main/java/com/` directory. This function is named `deserializeOffsetMap`. Here's a breakdown of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to deserialize a JSON string into a `Map` object. It assumes that the input string represents an offset map in JSON format.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`. This is expected to contain a JSON-formatted offset map. If this value is null or empty (i.e., `null` or `\"\"`), it defaults to a new `HashMap`.\n\n3. **Return Value**: The method returns a `Map` object that represents the deserialized JSON data.\n\n4. **Code Explanation**:\n\n - `@SuppressWarnings(\"unchecked\")`: This annotation is used to suppress potential warnings related to unchecked or raw type usage. In this case, it's safe because we're explicitly casting the result of `JSON_MAPPER.readValue()` to `Map`.\n \n - `if (lastSourceOffset == null || lastSourceOffset.isEmpty()) {`: This conditional checks if the input string is either null or empty. If true, a new `HashMap` is created and assigned to `offsetMap`.\n\n - `offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class);`: If the input string isn't null or empty, this line uses Jackson's `JSON_MAPPER` (presumably an instance of `ObjectMapper`) to deserialize it into a `Map`. The `readValue()` method takes two arguments:\n - The JSON-formatted offset map as a `String`.\n - The class type to which the JSON data should be converted (`Map.class`).\n\n - `return offsetMap;`: Finally, the function returns the deserialized `Map` object.\n\nIn summary, this method safely converts a JSON string into a `Map`, handling null or empty inputs by defaulting to an empty map. It's part of the StreamSets Data Collector codebase and is likely used for processing offset information in data pipelines.\n\"\"\"\ntruth = \"\"\"\nThe function `deserializeOffsetMap` takes a string as input and returns a map. It first checks if the input string is null or empty. If it is, it creates a new empty map and returns it. Otherwise, it uses the Jackson library to parse the input string into a map and returns it.\n\nThe `@SuppressWarnings(\"unchecked\")` annotation is used to suppress the warning that the type of the parsed map is not checked. This is because the Jackson library is used to parse the input string into a map, but the specific type of the map is not known at compile time. Therefore, the warning is suppressed to avoid potential issues.\n\"\"\"\n# (In PDL, set `result` to the output you wish for your code block.)\nresult = textdistance.levenshtein.normalized_similarity(expl, truth)\n", "pdl__timing": {"start_nanos": 1742524236741244000, "end_nanos": 1742524236742586000, "timezone": "EDT"}, "pdl__is_leaf": true}, "def": "EVAL", "contribute": [], "pdl__result": 0.2173103769194974, "pdl__timing": {"start_nanos": 1742524236741177000, "end_nanos": 1742524237823922000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.2.data", "defs": {}, "data": {"pdl__expr": {"input": "${ CODE }", "output": "${ EXPLANATION }", "metric": "${ EVAL }"}, "pdl__result": {"input": {"source_code": "@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n", "repo_info": {"repo": "streamsets/datacollector", "path": "stagesupport/src/main/java/com/.../OffsetUtil.java", "function_name": "OffsetUtil.deserializeOffsetMap"}}, "output": "The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (datacollector) repository, specifically located in the `stagesupport/src/main/java/com/` directory. This function is named `deserializeOffsetMap`. Here's a breakdown of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to deserialize a JSON string into a `Map` object. It assumes that the input string represents an offset map in JSON format.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`. This is expected to contain a JSON-formatted offset map. If this value is null or empty (i.e., `null` or `\"\"`), it defaults to a new `HashMap`.\n\n3. **Return Value**: The method returns a `Map` object that represents the deserialized JSON data.\n\n4. **Code Explanation**:\n\n - `@SuppressWarnings(\"unchecked\")`: This annotation is used to suppress potential warnings related to unchecked or raw type usage. In this case, it's safe because we're explicitly casting the result of `JSON_MAPPER.readValue()` to `Map`.\n \n - `if (lastSourceOffset == null || lastSourceOffset.isEmpty()) {`: This conditional checks if the input string is either null or empty. If true, a new `HashMap` is created and assigned to `offsetMap`.\n\n - `offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class);`: If the input string isn't null or empty, this line uses Jackson's `JSON_MAPPER` (presumably an instance of `ObjectMapper`) to deserialize it into a `Map`. The `readValue()` method takes two arguments:\n - The JSON-formatted offset map as a `String`.\n - The class type to which the JSON data should be converted (`Map.class`).\n\n - `return offsetMap;`: Finally, the function returns the deserialized `Map` object.\n\nIn summary, this method safely converts a JSON string into a `Map`, handling null or empty inputs by defaulting to an empty map. It's part of the StreamSets Data Collector codebase and is likely used for processing offset information in data pipelines.", "metric": 0.2173103769194974}}, "pdl__result": {"input": {"source_code": "@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n", "repo_info": {"repo": "streamsets/datacollector", "path": "stagesupport/src/main/java/com/.../OffsetUtil.java", "function_name": "OffsetUtil.deserializeOffsetMap"}}, "output": "The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (datacollector) repository, specifically located in the `stagesupport/src/main/java/com/` directory. This function is named `deserializeOffsetMap`. Here's a breakdown of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to deserialize a JSON string into a `Map` object. It assumes that the input string represents an offset map in JSON format.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`. This is expected to contain a JSON-formatted offset map. If this value is null or empty (i.e., `null` or `\"\"`), it defaults to a new `HashMap`.\n\n3. **Return Value**: The method returns a `Map` object that represents the deserialized JSON data.\n\n4. **Code Explanation**:\n\n - `@SuppressWarnings(\"unchecked\")`: This annotation is used to suppress potential warnings related to unchecked or raw type usage. In this case, it's safe because we're explicitly casting the result of `JSON_MAPPER.readValue()` to `Map`.\n \n - `if (lastSourceOffset == null || lastSourceOffset.isEmpty()) {`: This conditional checks if the input string is either null or empty. If true, a new `HashMap` is created and assigned to `offsetMap`.\n\n - `offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class);`: If the input string isn't null or empty, this line uses Jackson's `JSON_MAPPER` (presumably an instance of `ObjectMapper`) to deserialize it into a `Map`. The `readValue()` method takes two arguments:\n - The JSON-formatted offset map as a `String`.\n - The class type to which the JSON data should be converted (`Map.class`).\n\n - `return offsetMap;`: Finally, the function returns the deserialized `Map` object.\n\nIn summary, this method safely converts a JSON string into a `Map`, handling null or empty inputs by defaulting to an empty map. It's part of the StreamSets Data Collector codebase and is likely used for processing offset information in data pipelines.", "metric": 0.2173103769194974}, "pdl__timing": {"start_nanos": 1742524237824068000, "end_nanos": 1742524237826625000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "{\"input\": {\"source_code\": \"@SuppressWarnings(\\\"unchecked\\\")\\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\\n Map offsetMap;\\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \\n offsetMap = new HashMap<>(); \\n } else {\\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \\n }\\n return offsetMap;\\n}\\n\", \"repo_info\": {\"repo\": \"streamsets/datacollector\", \"path\": \"stagesupport/src/main/java/com/.../OffsetUtil.java\", \"function_name\": \"OffsetUtil.deserializeOffsetMap\"}}, \"output\": \"The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (datacollector) repository, specifically located in the `stagesupport/src/main/java/com/` directory. This function is named `deserializeOffsetMap`. Here's a breakdown of its purpose and functionality:\\n\\n1. **Purpose**: The primary goal of this method is to deserialize a JSON string into a `Map` object. It assumes that the input string represents an offset map in JSON format.\\n\\n2. **Parameters**:\\n - `lastSourceOffset`: A required parameter of type `String`. This is expected to contain a JSON-formatted offset map. If this value is null or empty (i.e., `null` or `\\\"\\\"`), it defaults to a new `HashMap`.\\n\\n3. **Return Value**: The method returns a `Map` object that represents the deserialized JSON data.\\n\\n4. **Code Explanation**:\\n\\n - `@SuppressWarnings(\\\"unchecked\\\")`: This annotation is used to suppress potential warnings related to unchecked or raw type usage. In this case, it's safe because we're explicitly casting the result of `JSON_MAPPER.readValue()` to `Map`.\\n \\n - `if (lastSourceOffset == null || lastSourceOffset.isEmpty()) {`: This conditional checks if the input string is either null or empty. If true, a new `HashMap` is created and assigned to `offsetMap`.\\n\\n - `offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class);`: If the input string isn't null or empty, this line uses Jackson's `JSON_MAPPER` (presumably an instance of `ObjectMapper`) to deserialize it into a `Map`. The `readValue()` method takes two arguments:\\n - The JSON-formatted offset map as a `String`.\\n - The class type to which the JSON data should be converted (`Map.class`).\\n\\n - `return offsetMap;`: Finally, the function returns the deserialized `Map` object.\\n\\nIn summary, this method safely converts a JSON string into a `Map`, handling null or empty inputs by defaulting to an empty map. It's part of the StreamSets Data Collector codebase and is likely used for processing offset information in data pipelines.\", \"metric\": 0.2173103769194974}", "pdl__timing": {"start_nanos": 1742524193622236000, "end_nanos": 1742524237826689000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file +{"kind": "data", "pdl__id": "data", "description": "Code explanation example", "defs": {"CODE": {"kind": "read", "pdl__id": "data.0.read", "defs": {}, "read": {"pdl__expr": "./data.yaml", "pdl__result": "./data.yaml"}, "message": null, "multiline": false, "pdl__result": "source_code: \n |\n @SuppressWarnings(\"unchecked\")\n public static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n }\nrepo_info: \n repo: streamsets/datacollector\n path: stagesupport/src/main/java/com/.../OffsetUtil.java\n function_name: OffsetUtil.deserializeOffsetMap\n", "parser": "yaml", "pdl__timing": {"start_nanos": 1750790243957561000, "end_nanos": 1750790244091692000, "timezone": "EDT"}, "pdl__is_leaf": true}, "TRUTH": {"kind": "read", "pdl__id": "data.1.read", "defs": {}, "read": {"pdl__expr": "./ground_truth.txt", "pdl__result": "./ground_truth.txt"}, "message": null, "multiline": false, "pdl__result": "The function `deserializeOffsetMap` takes a string as input and returns a map. It first checks if the input string is null or empty. If it is, it creates a new empty map and returns it. Otherwise, it uses the Jackson library to parse the input string into a map and returns it.\n\nThe `@SuppressWarnings(\"unchecked\")` annotation is used to suppress the warning that the type of the parsed map is not checked. This is because the Jackson library is used to parse the input string into a map, but the specific type of the map is not known at compile time. Therefore, the warning is suppressed to avoid potential issues.\n", "pdl__timing": {"start_nanos": 1750790244091798000, "end_nanos": 1750790244092268000, "timezone": "EDT"}, "pdl__is_leaf": true}, "EXPLANATION": {"kind": "model", "pdl__id": "data.2.model", "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "data.2.model", "defs": {}, "data": {"pdl__expr": "Here is some info about the location of the function in the repo.\nrepo:\n${ CODE.repo_info.repo }\npath: ${ CODE.repo_info.path }\nFunction_name: ${ CODE.repo_info.function_name }\n\n\nExplain the following code:\n```\n${ CODE.source_code }```\n", "pdl__result": "Here is some info about the location of the function in the repo.\nrepo:\nstreamsets/datacollector\npath: stagesupport/src/main/java/com/.../OffsetUtil.java\nFunction_name: OffsetUtil.deserializeOffsetMap\n\n\nExplain the following code:\n```\n@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n```\n"}, "pdl__result": "Here is some info about the location of the function in the repo.\nrepo:\nstreamsets/datacollector\npath: stagesupport/src/main/java/com/.../OffsetUtil.java\nFunction_name: OffsetUtil.deserializeOffsetMap\n\n\nExplain the following code:\n```\n@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n```\n", "pdl__timing": {"start_nanos": 1750790244092628000, "end_nanos": 1750790244100100000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": null}, "pdl__usage": {"completion_tokens": 474, "prompt_tokens": 146}, "pdl__model_input": [{"role": "user", "content": "Here is some info about the location of the function in the repo.\nrepo:\nstreamsets/datacollector\npath: stagesupport/src/main/java/com/.../OffsetUtil.java\nFunction_name: OffsetUtil.deserializeOffsetMap\n\n\nExplain the following code:\n```\n@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n```\n"}], "pdl__result": "The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (DC) codebase in the `stagesupport` package within the `com.../OffsetUtil.java` file. This function is designed to deserialize a JSON string containing offsets into a `Map` object. Here's an explanation of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to convert a JSON-formatted offset string (represented as `lastSourceOffset`) into a Java `Map` where keys are strings and values are also strings. This conversion allows for easier manipulation, storage, or further processing in the Data Collector application.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`, which is expected to contain JSON-formatted offset data.\n\n3. **Return Type**: The method returns a `Map`. This means it will return a map where each key and value are strings.\n\n4. **Throws**:\n - `IOException`: In case the JSON string cannot be parsed due to an I/O error (e.g., network issues).\n\n5. **Logic**:\n\n - The method first checks if `lastSourceOffset` is null or empty (`if (lastSourceOffset == null || lastSourceOffset.isEmpty())`). If true, it initializes a new `HashMap` called `offsetMap`.\n - Otherwise, the function uses Jackson's JSON mapper (`JSON_MAPPER`) to deserialize the input string into a `Map`. This is done with `JSON_MAPPER.readValue(lastSourceOffset, Map.class)`.\n\n - The deserialization process converts the JSON string into a Java map, where each key-value pair in the JSON will become an entry in the resulting map.\n\n6. **Security Note**: `@SuppressWarnings(\"unchecked\")` is used to suppress potential warnings about unchecked casts. This is because `JSON_MAPPER.readValue()` returns a `Map`, and there's no need for explicit type casting here, as Java's auto-boxing mechanism handles the conversion from JSON keys/values to `String`.\n\nIn summary, this function serves as an adapter between JSON offset data (in string format) and a standard Java map structure. It ensures that any provided offsets can be easily accessed or manipulated within the Data Collector application.", "pdl__timing": {"start_nanos": 1750790244092378000, "end_nanos": 1750790292307349000, "timezone": "EDT"}, "pdl__is_leaf": true}, "EVAL": {"kind": "code", "pdl__id": "data.3.code", "defs": {}, "lang": "python", "code": {"kind": "data", "pdl__id": "data.3.code", "defs": {}, "data": {"pdl__expr": "import textdistance\nexpl = \"\"\"\n${ EXPLANATION }\n\"\"\"\ntruth = \"\"\"\n${ TRUTH }\n\"\"\"\nresult = textdistance.levenshtein.normalized_similarity(expl, truth)\n", "pdl__result": "import textdistance\nexpl = \"\"\"\nThe provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (DC) codebase in the `stagesupport` package within the `com.../OffsetUtil.java` file. This function is designed to deserialize a JSON string containing offsets into a `Map` object. Here's an explanation of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to convert a JSON-formatted offset string (represented as `lastSourceOffset`) into a Java `Map` where keys are strings and values are also strings. This conversion allows for easier manipulation, storage, or further processing in the Data Collector application.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`, which is expected to contain JSON-formatted offset data.\n\n3. **Return Type**: The method returns a `Map`. This means it will return a map where each key and value are strings.\n\n4. **Throws**:\n - `IOException`: In case the JSON string cannot be parsed due to an I/O error (e.g., network issues).\n\n5. **Logic**:\n\n - The method first checks if `lastSourceOffset` is null or empty (`if (lastSourceOffset == null || lastSourceOffset.isEmpty())`). If true, it initializes a new `HashMap` called `offsetMap`.\n - Otherwise, the function uses Jackson's JSON mapper (`JSON_MAPPER`) to deserialize the input string into a `Map`. This is done with `JSON_MAPPER.readValue(lastSourceOffset, Map.class)`.\n\n - The deserialization process converts the JSON string into a Java map, where each key-value pair in the JSON will become an entry in the resulting map.\n\n6. **Security Note**: `@SuppressWarnings(\"unchecked\")` is used to suppress potential warnings about unchecked casts. This is because `JSON_MAPPER.readValue()` returns a `Map`, and there's no need for explicit type casting here, as Java's auto-boxing mechanism handles the conversion from JSON keys/values to `String`.\n\nIn summary, this function serves as an adapter between JSON offset data (in string format) and a standard Java map structure. It ensures that any provided offsets can be easily accessed or manipulated within the Data Collector application.\n\"\"\"\ntruth = \"\"\"\nThe function `deserializeOffsetMap` takes a string as input and returns a map. It first checks if the input string is null or empty. If it is, it creates a new empty map and returns it. Otherwise, it uses the Jackson library to parse the input string into a map and returns it.\n\nThe `@SuppressWarnings(\"unchecked\")` annotation is used to suppress the warning that the type of the parsed map is not checked. This is because the Jackson library is used to parse the input string into a map, but the specific type of the map is not known at compile time. Therefore, the warning is suppressed to avoid potential issues.\n\n\"\"\"\nresult = textdistance.levenshtein.normalized_similarity(expl, truth)\n"}, "pdl__result": "import textdistance\nexpl = \"\"\"\nThe provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (DC) codebase in the `stagesupport` package within the `com.../OffsetUtil.java` file. This function is designed to deserialize a JSON string containing offsets into a `Map` object. Here's an explanation of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to convert a JSON-formatted offset string (represented as `lastSourceOffset`) into a Java `Map` where keys are strings and values are also strings. This conversion allows for easier manipulation, storage, or further processing in the Data Collector application.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`, which is expected to contain JSON-formatted offset data.\n\n3. **Return Type**: The method returns a `Map`. This means it will return a map where each key and value are strings.\n\n4. **Throws**:\n - `IOException`: In case the JSON string cannot be parsed due to an I/O error (e.g., network issues).\n\n5. **Logic**:\n\n - The method first checks if `lastSourceOffset` is null or empty (`if (lastSourceOffset == null || lastSourceOffset.isEmpty())`). If true, it initializes a new `HashMap` called `offsetMap`.\n - Otherwise, the function uses Jackson's JSON mapper (`JSON_MAPPER`) to deserialize the input string into a `Map`. This is done with `JSON_MAPPER.readValue(lastSourceOffset, Map.class)`.\n\n - The deserialization process converts the JSON string into a Java map, where each key-value pair in the JSON will become an entry in the resulting map.\n\n6. **Security Note**: `@SuppressWarnings(\"unchecked\")` is used to suppress potential warnings about unchecked casts. This is because `JSON_MAPPER.readValue()` returns a `Map`, and there's no need for explicit type casting here, as Java's auto-boxing mechanism handles the conversion from JSON keys/values to `String`.\n\nIn summary, this function serves as an adapter between JSON offset data (in string format) and a standard Java map structure. It ensures that any provided offsets can be easily accessed or manipulated within the Data Collector application.\n\"\"\"\ntruth = \"\"\"\nThe function `deserializeOffsetMap` takes a string as input and returns a map. It first checks if the input string is null or empty. If it is, it creates a new empty map and returns it. Otherwise, it uses the Jackson library to parse the input string into a map and returns it.\n\nThe `@SuppressWarnings(\"unchecked\")` annotation is used to suppress the warning that the type of the parsed map is not checked. This is because the Jackson library is used to parse the input string into a map, but the specific type of the map is not known at compile time. Therefore, the warning is suppressed to avoid potential issues.\n\n\"\"\"\nresult = textdistance.levenshtein.normalized_similarity(expl, truth)\n", "pdl__timing": {"start_nanos": 1750790292307636000, "end_nanos": 1750790292309319000, "timezone": "EDT"}, "pdl__is_leaf": true}, "pdl__result": 0.1991833030852994, "pdl__timing": {"start_nanos": 1750790292307508000, "end_nanos": 1750790293850888000, "timezone": "EDT"}, "pdl__is_leaf": true}}, "data": {"pdl__expr": {"input": "${ CODE }", "output": "${ EXPLANATION }", "metric": "${ EVAL }"}, "pdl__result": {"input": {"source_code": "@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n", "repo_info": {"repo": "streamsets/datacollector", "path": "stagesupport/src/main/java/com/.../OffsetUtil.java", "function_name": "OffsetUtil.deserializeOffsetMap"}}, "output": "The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (DC) codebase in the `stagesupport` package within the `com.../OffsetUtil.java` file. This function is designed to deserialize a JSON string containing offsets into a `Map` object. Here's an explanation of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to convert a JSON-formatted offset string (represented as `lastSourceOffset`) into a Java `Map` where keys are strings and values are also strings. This conversion allows for easier manipulation, storage, or further processing in the Data Collector application.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`, which is expected to contain JSON-formatted offset data.\n\n3. **Return Type**: The method returns a `Map`. This means it will return a map where each key and value are strings.\n\n4. **Throws**:\n - `IOException`: In case the JSON string cannot be parsed due to an I/O error (e.g., network issues).\n\n5. **Logic**:\n\n - The method first checks if `lastSourceOffset` is null or empty (`if (lastSourceOffset == null || lastSourceOffset.isEmpty())`). If true, it initializes a new `HashMap` called `offsetMap`.\n - Otherwise, the function uses Jackson's JSON mapper (`JSON_MAPPER`) to deserialize the input string into a `Map`. This is done with `JSON_MAPPER.readValue(lastSourceOffset, Map.class)`.\n\n - The deserialization process converts the JSON string into a Java map, where each key-value pair in the JSON will become an entry in the resulting map.\n\n6. **Security Note**: `@SuppressWarnings(\"unchecked\")` is used to suppress potential warnings about unchecked casts. This is because `JSON_MAPPER.readValue()` returns a `Map`, and there's no need for explicit type casting here, as Java's auto-boxing mechanism handles the conversion from JSON keys/values to `String`.\n\nIn summary, this function serves as an adapter between JSON offset data (in string format) and a standard Java map structure. It ensures that any provided offsets can be easily accessed or manipulated within the Data Collector application.", "metric": 0.1991833030852994}}, "pdl__result": {"input": {"source_code": "@SuppressWarnings(\"unchecked\")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n", "repo_info": {"repo": "streamsets/datacollector", "path": "stagesupport/src/main/java/com/.../OffsetUtil.java", "function_name": "OffsetUtil.deserializeOffsetMap"}}, "output": "The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (DC) codebase in the `stagesupport` package within the `com.../OffsetUtil.java` file. This function is designed to deserialize a JSON string containing offsets into a `Map` object. Here's an explanation of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to convert a JSON-formatted offset string (represented as `lastSourceOffset`) into a Java `Map` where keys are strings and values are also strings. This conversion allows for easier manipulation, storage, or further processing in the Data Collector application.\n\n2. **Parameters**:\n - `lastSourceOffset`: A required parameter of type `String`, which is expected to contain JSON-formatted offset data.\n\n3. **Return Type**: The method returns a `Map`. This means it will return a map where each key and value are strings.\n\n4. **Throws**:\n - `IOException`: In case the JSON string cannot be parsed due to an I/O error (e.g., network issues).\n\n5. **Logic**:\n\n - The method first checks if `lastSourceOffset` is null or empty (`if (lastSourceOffset == null || lastSourceOffset.isEmpty())`). If true, it initializes a new `HashMap` called `offsetMap`.\n - Otherwise, the function uses Jackson's JSON mapper (`JSON_MAPPER`) to deserialize the input string into a `Map`. This is done with `JSON_MAPPER.readValue(lastSourceOffset, Map.class)`.\n\n - The deserialization process converts the JSON string into a Java map, where each key-value pair in the JSON will become an entry in the resulting map.\n\n6. **Security Note**: `@SuppressWarnings(\"unchecked\")` is used to suppress potential warnings about unchecked casts. This is because `JSON_MAPPER.readValue()` returns a `Map`, and there's no need for explicit type casting here, as Java's auto-boxing mechanism handles the conversion from JSON keys/values to `String`.\n\nIn summary, this function serves as an adapter between JSON offset data (in string format) and a standard Java map structure. It ensures that any provided offsets can be easily accessed or manipulated within the Data Collector application.", "metric": 0.1991833030852994}, "pdl__timing": {"start_nanos": 1750790243957428000, "end_nanos": 1750790293855075000, "timezone": "EDT"}, "pdl__is_leaf": true} \ No newline at end of file diff --git a/pdl-live-react/src/demos/demo6.json b/pdl-live-react/src/demos/demo6.json index b7ece6dd2..4816a2a6d 100644 --- a/pdl-live-react/src/demos/demo6.json +++ b/pdl-live-react/src/demos/demo6.json @@ -1 +1 @@ -{"kind": "text", "pdl__id": "text", "description": "Creating JSON Data", "defs": {"data": {"kind": "read", "pdl__id": "text.0.read", "spec": {"questions": ["str"], "answers": ["obj"]}, "defs": {}, "read": {"pdl__expr": "./gen-data.yaml", "pdl__result": "./gen-data.yaml"}, "message": null, "multiline": false, "pdl__result": "source_code: \n |\n @SuppressWarnings(\"unchecked\")\n public static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n }\nrepo_info: \n repo: streamsets/datacollector\n path: stagesupport/src/main/java/com/.../OffsetUtil.java\n function_name: OffsetUtil.deserializeOffsetMap\n", "parser": "yaml", "pdl__timing": {"start_nanos": 1742524239040868000, "end_nanos": 1742524239042801000, "timezone": "EDT"}, "pdl__is_leaf": true}}, "text": [{"kind": "model", "pdl__id": "text.0.model", "spec": {"name": "str", "age": "int"}, "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "text", "pdl__id": "text.0.model.text", "defs": {}, "text": [{"kind": "error", "pdl__id": "", "defs": {}, "program": {"kind": "read", "pdl__id": "text.0.read", "spec": {"questions": ["str"], "answers": ["obj"]}, "defs": {}, "read": {"pdl__expr": "./gen-data.yaml", "pdl__result": "./gen-data.yaml"}, "message": null, "multiline": false, "pdl__result": "source_code: \n |\n @SuppressWarnings(\"unchecked\")\n public static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n }\nrepo_info: \n repo: streamsets/datacollector\n path: stagesupport/src/main/java/com/.../OffsetUtil.java\n function_name: OffsetUtil.deserializeOffsetMap\n", "parser": "yaml", "pdl__timing": {"start_nanos": 1742524239040868000, "end_nanos": 1742524239042801000, "timezone": "EDT"}, "pdl__is_leaf": true}, "msg": "Type errors during spec checking:\n/Users/lmandel/ml4code/prompt-declaration-language/pdl-live-react/demos/../demos/error.pdl:3 - Missing required field: answers\n/Users/lmandel/ml4code/prompt-declaration-language/pdl-live-react/demos/../demos/error.pdl:3 - Missing required field: questions\n/Users/lmandel/ml4code/prompt-declaration-language/pdl-live-react/demos/../demos/error.pdl:3 - Field not allowed: source_code\n/Users/lmandel/ml4code/prompt-declaration-language/pdl-live-react/demos/../demos/error.pdl:3 - Field not allowed: repo_info", "pdl__is_leaf": true}], "pdl__timing": {"start_nanos": 1742524239045652000, "end_nanos": 0, "timezone": "EDT"}, "pdl__is_leaf": false}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": null, "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": 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+{"kind": "text", "pdl__id": "text", "description": "Creating JSON Data", "defs": {"data": {"kind": "read", "pdl__id": "text.0.read", "spec": {"questions": ["string"], "answers": ["object"]}, "defs": {}, "read": {"pdl__expr": "./gen-data.yaml", "pdl__result": "./gen-data.yaml"}, "message": null, "multiline": false, "pdl__result": "source_code: \n |\n @SuppressWarnings(\"unchecked\")\n public static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n }\nrepo_info: \n repo: streamsets/datacollector\n path: stagesupport/src/main/java/com/.../OffsetUtil.java\n function_name: OffsetUtil.deserializeOffsetMap\n", "parser": "yaml", "pdl__timing": {"start_nanos": 1750777462971916000, "end_nanos": 1750777463090745000, "timezone": "EDT"}, "pdl__is_leaf": true}}, 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"Function def and call", "defs": {}, "context": "dependent", "text": [{"kind": "function", "pdl__id": "text.0.function", "defs": {}, "function": {"sentence": "string", "language": "string"}, "return": {"kind": "lastOf", "pdl__id": "text.3.call.lastOf", "defs": {}, "context": "dependent", "lastOf": ["\nTranslate the sentence '${ sentence }' to ${ language }.\n", {"kind": "model", "pdl__id": "text.3.call.lastOf.model", "defs": {}, "platform": "litellm", "model": "ollama_chat/granite3.2:2b", "input": "${ pdl_context }", "parameters": {"temperature": 0.0, "stop": ["\n"]}, "pdl__timing": {"start_nanos": 1750817130552615000, "end_nanos": 1750817132289604000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__timing": {"start_nanos": 1750817130551448000, "end_nanos": 1750817132289671000, "timezone": "EDT"}, "pdl__is_leaf": false}, "def": "translate", "pdl__result": {"kind": "function", "pdl__id": "text.0.function", "defs": {}, "function": {"sentence": "string", "language": "string"}, "return": 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{"pdl__expr": {"sentence": "I love Paris!", "language": "French"}, "pdl__result": {"sentence": "I love Paris!", "language": "French"}}, "pdl__trace": {"kind": "lastOf", "pdl__id": "text.1.call.lastOf", "defs": {}, "context": "dependent", "lastOf": [{"kind": "data", "pdl__id": "text.1.call.lastOf", "defs": {}, "data": {"pdl__expr": "\nTranslate the sentence '${ sentence }' to ${ language }.\n", "pdl__result": "\nTranslate the sentence 'I love Paris!' to French.\n"}, "pdl__result": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__timing": {"start_nanos": 1750817125416980000, "end_nanos": 1750817125417962000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.1.call.lastOf.model", "pdl__context": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.1.call.lastOf.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}]}, "pdl__result": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}], "pdl__timing": {"start_nanos": 1750817125504641000, "end_nanos": 1750817125505244000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": ["\n"], "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": ["\n"], "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 7, "prompt_tokens": 19}, "pdl__model_input": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}], "pdl__result": "'J'aime Paris !'", "pdl__timing": {"start_nanos": 1750817125500740000, "end_nanos": 1750817130547547000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "'J'aime Paris !'", "pdl__timing": {"start_nanos": 1750817125416851000, "end_nanos": 1750817130547629000, "timezone": "EDT"}, "pdl__is_leaf": false}, "pdl__result": "'J'aime Paris !'", "pdl__timing": {"start_nanos": 1750817125304020000, "end_nanos": 1750817130547679000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "data", "pdl__id": "text.2", "defs": {}, "data": {"pdl__expr": "\n", "pdl__result": "\n"}, "pdl__result": "\n", "pdl__timing": {"start_nanos": 1750817130547749000, "end_nanos": 1750817130548335000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "call", "pdl__id": "text.3.call", "defs": {}, "call": "${ translate }", "args": {"pdl__expr": {"sentence": "I love Madrid!", "language": "Spanish"}, "pdl__result": {"sentence": "I love Madrid!", "language": "Spanish"}}, "pdl__trace": {"kind": "lastOf", "pdl__id": "text.3.call.lastOf", "defs": {}, "context": "dependent", "lastOf": [{"kind": "data", "pdl__id": "text.3.call.lastOf", "defs": {}, "data": {"pdl__expr": "\nTranslate the sentence '${ sentence }' to ${ language }.\n", "pdl__result": "\nTranslate the sentence 'I love Madrid!' to Spanish.\n"}, "pdl__result": "\nTranslate the sentence 'I love Madrid!' to Spanish.\n", "pdl__timing": {"start_nanos": 1750817130551559000, "end_nanos": 1750817130552518000, "timezone": "EDT"}, "pdl__is_leaf": true}, {"kind": "model", "pdl__id": "text.3.call.lastOf.model", "pdl__context": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}, {"content": "'J'aime Paris !'", "role": "assistant", "pdl__defsite": "text.3.call.lastOf.model"}, {"role": "user", "content": "\n", "pdl__defsite": "text.2"}, {"role": "user", "content": "\nTranslate the sentence 'I love Madrid!' to Spanish.\n", "pdl__defsite": "text.3.call.lastOf"}], "defs": {}, "platform": "litellm", "model": {"pdl__expr": "ollama_chat/granite3.2:2b", "pdl__result": "ollama_chat/granite3.2:2b"}, "input": {"kind": "data", "pdl__id": "text.3.call.lastOf.model", "defs": {}, "data": {"pdl__expr": "${ pdl_context }", "pdl__result": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}, {"content": "'J'aime Paris !'", "role": "assistant", "pdl__defsite": "text.3.call.lastOf.model"}, {"role": "user", "content": "\n", "pdl__defsite": "text.2"}, {"role": "user", "content": "\nTranslate the sentence 'I love Madrid!' to Spanish.\n", "pdl__defsite": "text.3.call.lastOf"}]}, "pdl__result": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}, {"content": "'J'aime Paris !'", "role": "assistant", "pdl__defsite": "text.3.call.lastOf.model"}, {"role": "user", "content": "\n", "pdl__defsite": "text.2"}, {"role": "user", "content": "\nTranslate the sentence 'I love Madrid!' to Spanish.\n", "pdl__defsite": "text.3.call.lastOf"}], "pdl__timing": {"start_nanos": 1750817130554889000, "end_nanos": 1750817130555528000, "timezone": "EDT"}, "pdl__is_leaf": true}, "parameters": {"pdl__expr": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": ["\n"], "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}, "pdl__result": {"timeout": null, "temperature": 0.0, "top_p": null, "n": null, "stop": ["\n"], "max_tokens": null, "presence_penalty": null, "frequency_penalty": null, "logit_bias": null, "user": null, "response_format": null, "seed": null, "tools": null, "tool_choice": null, "logprobs": null, "top_logprobs": null, "parallel_tool_calls": null, "extra_headers": null, "functions": null, "function_call": null, "base_url": null, "api_version": null, "api_key": null, "model_list": null, "mock_response": null, "custom_llm_provider": null, "max_retries": null}}, "pdl__usage": {"completion_tokens": 18, "prompt_tokens": 51}, "pdl__model_input": [{"role": "user", "content": "\nTranslate the sentence 'I love Paris!' to French.\n", "pdl__defsite": "text.1.call.lastOf"}, {"content": "'J'aime Paris !'", "role": "assistant", "pdl__defsite": "text.3.call.lastOf.model"}, {"role": "user", "content": "\n", "pdl__defsite": "text.2"}, {"role": "user", "content": "\nTranslate the sentence 'I love Madrid!' to Spanish.\n", "pdl__defsite": "text.3.call.lastOf"}], "pdl__result": "The translation of \"I love Madrid!\" into Spanish is: \"Me encanta Madrid!\"", "pdl__timing": {"start_nanos": 1750817130552615000, "end_nanos": 1750817132289604000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "The translation of \"I love Madrid!\" into Spanish is: \"Me encanta Madrid!\"", "pdl__timing": {"start_nanos": 1750817130551448000, "end_nanos": 1750817132289671000, "timezone": "EDT"}, "pdl__is_leaf": false}, "pdl__result": "The translation of \"I love Madrid!\" into Spanish is: \"Me encanta Madrid!\"", "pdl__timing": {"start_nanos": 1750817130548486000, "end_nanos": 1750817132289706000, "timezone": "EDT"}, "pdl__is_leaf": true}], "pdl__result": "'J'aime Paris !'\nThe translation of \"I love Madrid!\" into Spanish is: \"Me encanta Madrid!\"", "pdl__timing": {"start_nanos": 1750817125207053000, "end_nanos": 1750817132289764000, "timezone": "EDT"}, "pdl__is_leaf": false} \ No newline at end of file diff --git a/pdl-live-react/src/demos/demos.ts b/pdl-live-react/src/demos/demos.ts index 56b5ca2c0..5c11daf8a 100644 --- a/pdl-live-react/src/demos/demos.ts +++ b/pdl-live-react/src/demos/demos.ts @@ -3,7 +3,7 @@ import demo2 from "./demo2.json" import demo3 from "./demo3.json" import demo4 from "./demo4.json" import demo5 from "./demo5.json" -import demo6 from "./demo6.json" +// import demo6 from "./demo6.json" import demo7 from "./demo7.json" import demo8 from "./demo8.json" import demo9 from "./demo9.json" @@ -19,7 +19,7 @@ const demos: Demo[] = [ demo3, demo4, demo5, - demo6, + // demo6, demo7, demo8, demo9, diff --git a/tests/results/examples/tutorial/programs/code-json.0.result b/tests/results/examples/tutorial/programs/code-json.0.result deleted file mode 100644 index 71d5b9c1e..000000000 --- a/tests/results/examples/tutorial/programs/code-json.0.result +++ /dev/null @@ -1 +0,0 @@ -{'input': {'source_code': '@SuppressWarnings("unchecked")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n', 'repo_info': {'repo': 'streamsets/datacollector', 'path': 'stagesupport/src/main/java/com/.../OffsetUtil.java', 'function_name': 'OffsetUtil.deserializeOffsetMap'}}, 'output': 'The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (streamsets/datacollector) repository, specifically located in the `stagesupport` package under `com.../OffsetUtil.java`. This function aims to deserialize a JSON string into a `Map` object, which represents an offset map containing key-value pairs of strings.\n\nHere\'s a breakdown of the code:\n\n1. `@SuppressWarnings("unchecked")`: This annotation is used to suppress potential warnings related to unchecked or raw type usage. In this case, it indicates that the developer knows the type is safe and doesn\'t want to see warnings about it.\n\n2. `public static Map deserializeOffsetMap(String lastSourceOffset) throws IOException`: This line defines a public static method named `deserializeOffsetMap` in the OffsetUtil class. It takes one parameter:\n - `lastSourceOffset`: A string representing a JSON offset map.\n\n3. The function begins with an if-else statement to handle two possible scenarios for `lastSourceOffset`:\n\n a. If `lastSourceOffset` is null or empty (`lastSourceOffset == null || lastSourceOffset.isEmpty()`), the method initializes and returns a new HashMap called `offsetMap`. This indicates that no offset map was provided, so an empty one will be created.\n \n b. Otherwise, if `lastSourceOffset` contains valid JSON data:\n - The function uses `JSON_MAPPER`, presumably a Jackson ObjectMapper instance, to deserialize the input string (`lastSourceOffset`) into a Map of type `Map.class`. This means it converts the JSON string into a HashMap.\n\n4. Finally, the method returns the deserialized `offsetMap` (either an empty one or the JSON-parsed map).\n\nIn summary, this function serves to safely convert a JSON offset map string into a Java Map object. If no valid JSON data is provided as input, it creates and returns an empty HashMap; otherwise, it parses the given JSON string into a Map using Jackson\'s ObjectMapper.', 'metric': 0.22032193158953728} \ No newline at end of file diff --git a/tests/results/examples/tutorial/programs/code-json.1.result b/tests/results/examples/tutorial/programs/code-json.1.result deleted file mode 100644 index eae81ad01..000000000 --- a/tests/results/examples/tutorial/programs/code-json.1.result +++ /dev/null @@ -1 +0,0 @@ -{'input': {'source_code': '@SuppressWarnings("unchecked")\npublic static Map deserializeOffsetMap(String lastSourceOffset) throws IOException {\n Map offsetMap;\n if (lastSourceOffset == null || lastSourceOffset.isEmpty()) { \n offsetMap = new HashMap<>(); \n } else {\n offsetMap = JSON_MAPPER.readValue(lastSourceOffset, Map.class); \n }\n return offsetMap;\n}\n', 'repo_info': {'repo': 'streamsets/datacollector', 'path': 'stagesupport/src/main/java/com/.../OffsetUtil.java', 'function_name': 'OffsetUtil.deserializeOffsetMap'}}, 'output': 'The provided Java function `deserializeOffsetMap` is part of the StreamSets Data Collector (datacollector) repository, specifically located in the `stagesupport/src/main/java/com/` directory. This function is named `OffsetUtil.deserializeOffsetMap`. Here\'s a breakdown of its purpose and functionality:\n\n1. **Purpose**: The primary goal of this method is to deserialize a JSON string into a `Map` object. It assumes that the input JSON represents an offset map with keys as strings (e.g., "record_id", "timestamp") and values also being strings (e.g., "1234567890" or "2022-01-01T00:00:00Z").\n\n2. **Input**: The method takes a single parameter, `lastSourceOffset`, which is expected to be a JSON string representing an offset map. If this input is null or empty (i.e., `null` or `""`), the function initializes and returns a new `HashMap` with no entries.\n\n3. **Deserialization**:\n - When `lastSourceOffset` is not null or empty:\n - The method uses Jackson\'s `JSON_MAPPER`, an instance of `ObjectMapper`, to parse the JSON string into a `Map`. This is done using the `readValue()` method with `Map.class` as the target class.\n - If `lastSourceOffset` is null or empty:\n - The function initializes and returns a new `HashMap` with no entries (i.e., an empty map).\n\n4. **Return Value**: Regardless of whether the input was null or non-empty, this method always returns a `Map`. This ensures that the caller can safely use the returned object without worrying about potential null values.\n\n5. **Exception Handling**: The function does not explicitly handle `IOException`. However, since it\'s called within the context of StreamSets Data Collector (datacollector), any underlying I/O issues are likely to be managed by the framework itself.\n\nIn summary, this method serves as a utility for converting JSON strings into Map objects representing offset data. It ensures that null or empty inputs result in an empty map, while non-empty inputs are parsed using Jackson\'s `JSON_MAPPER`.', 'metric': 0.20593869731800762} \ No newline at end of file diff --git a/tests/results/examples/code/code-eval.0.result b/tests/results/examples/tutorial/programs/code/code-eval.0.result similarity index 100% rename from tests/results/examples/code/code-eval.0.result rename to tests/results/examples/tutorial/programs/code/code-eval.0.result diff --git a/tests/results/examples/code/code-eval.1.result b/tests/results/examples/tutorial/programs/code/code-eval.1.result similarity index 100% rename from tests/results/examples/code/code-eval.1.result rename to tests/results/examples/tutorial/programs/code/code-eval.1.result diff --git a/tests/results/examples/code/code-eval.2.result b/tests/results/examples/tutorial/programs/code/code-eval.2.result similarity index 100% rename from tests/results/examples/code/code-eval.2.result rename to tests/results/examples/tutorial/programs/code/code-eval.2.result diff --git a/tests/results/examples/code/code-json.0.result b/tests/results/examples/tutorial/programs/code/code-json.0.result similarity index 100% rename from tests/results/examples/code/code-json.0.result rename to tests/results/examples/tutorial/programs/code/code-json.0.result diff --git a/tests/results/examples/code/code-json.1.result b/tests/results/examples/tutorial/programs/code/code-json.1.result similarity index 100% rename from tests/results/examples/code/code-json.1.result rename to tests/results/examples/tutorial/programs/code/code-json.1.result diff --git a/tests/results/examples/code/code-json.2.result b/tests/results/examples/tutorial/programs/code/code-json.2.result similarity index 100% rename from tests/results/examples/code/code-json.2.result rename to tests/results/examples/tutorial/programs/code/code-json.2.result diff --git a/tests/results/examples/code/code.0.result b/tests/results/examples/tutorial/programs/code/code.0.result similarity index 100% rename from tests/results/examples/code/code.0.result rename to tests/results/examples/tutorial/programs/code/code.0.result diff --git a/tests/results/examples/code/code.1.result b/tests/results/examples/tutorial/programs/code/code.1.result similarity index 100% rename from tests/results/examples/code/code.1.result rename to tests/results/examples/tutorial/programs/code/code.1.result diff --git a/tests/results/examples/code/code.2.result b/tests/results/examples/tutorial/programs/code/code.2.result similarity index 100% rename from tests/results/examples/code/code.2.result rename to tests/results/examples/tutorial/programs/code/code.2.result diff --git a/tests/results/examples/code/code.3.result b/tests/results/examples/tutorial/programs/code/code.3.result similarity index 100% rename from tests/results/examples/code/code.3.result rename to tests/results/examples/tutorial/programs/code/code.3.result