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recipes/llama_api_providers/Groq/groq-api-cookbook/function-calling-101-ecommerce/Function-Calling-101-Ecommerce.ipynb

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"The two key parameters we need to include in our chat completion are `tools=tools` and `tool_choice=\"auto\"`, which provides the model with the available tools we've just defined and tells it to use one if appropriate (`tool_choice=\"auto\"` gives the LLM the option of using any, all or none of the available functions. To mandate a specific function call, we could use `tool_choice={\"type\": \"function\", \"function\": {\"name\":\"create_order\"}}`). \n",
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"When the LLM decides to use a tool, the response is *not* a conversational chat, but . From there, we can execute the LLM-identified tool with the LLM-identified parameters, and feed the response *back* to the LLM for a second request so that it can respond with appropriate context from the tool it just used:"
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"When the LLM decides to use a tool, the response is *not* a conversational chat, but a JSON object containing the tool choice and tool parameters. From there, we can execute the LLM-identified tool with the LLM-identified parameters, and feed the response *back* to the LLM for a second request so that it can respond with appropriate context from the tool it just used:"
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recipes/llama_api_providers/Groq/groq-api-cookbook/rag-langchain-presidential-speeches/rag-langchain-presidential-speeches.ipynb

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"attachments": {},
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"cell_type": "markdown",
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"A Groq API Key is required for this demo - you can generate one for free [here](https://console.groq.com/keys). We will be using Pinecone as our vector database, which also requires an API key (you can create one index for a small project there for free on their Starter plan), but will also show how it works with [Chroma DB](https://www.trychroma.com/), a free open source alternative that stores vector embeddings in memory. We will also use the Llama3 8b model for this demo."
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"A Groq API Key is required for this demo - you can generate one for free [here](https://console.groq.com/). We will be using Pinecone as our vector database, which also requires an API key (you can create one index for a small project there for free on their Starter plan), but will also show how it works with [Chroma DB](https://www.trychroma.com/), a free open source alternative that stores vector embeddings in memory. We will also use the Llama3 8b model for this demo."
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recipes/llama_api_providers/Groq/groq-example-templates/conversational-chatbot-langchain/README.md

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## Usage
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You will need to store a valid Groq API Key as a secret to proceed with this example. You can generate one for free [here](https://console.groq.com/keys).
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/Chatbot-with-Conversational-Memory-on-LangChain) or run it on the command line with `python main.py`

recipes/llama_api_providers/Groq/groq-example-templates/crewai-agents/README.md

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- **LangChain Integration**: Incorporates LangChain to facilitate natural language processing and enhance the interaction between the user and the machine learning assistant.
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## Usage
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You will need to store a valid Groq API Key as a secret to proceed with this example. You can generate one for free [here](https://console.groq.com/keys).
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/CrewAI-Machine-Learning-Assistant) or run it on the command line with `python main.py`. You can upload a sample .csv to the same directory as ```main.py``` to give the application a head start on your ML problem. The application will output a Markdown file including python code for your ML use case to the same directory as main.py.
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/CrewAI-Machine-Learning-Assistant) or run it on the command line with `python main.py`. You can upload a sample .csv to the same directory as `main.py` to give the application a head start on your ML problem. The application will output a Markdown file including python code for your ML use case to the same directory as main.py.

recipes/llama_api_providers/Groq/groq-example-templates/groq-quickstart-conversational-chatbot/README.md

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## Usage
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You will need to store a valid Groq API Key as a secret to proceed with this example. You can generate one for free [here](https://console.groq.com/keys).
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/Groq-Quickstart-Conversational-Chatbot) or run it on the command line with `python main.py`.

recipes/llama_api_providers/Groq/groq-example-templates/groqing-the-stock-market-function-calling-llama3/README.md

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## Usage
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You will need to store a valid Groq API Key as a secret to proceed with this example. You can generate one for free [here](https://console.groq.com/keys).
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/Groqing-the-Stock-Market-Function-Calling-with-Llama3) or run it on the command line with `python main.py`.

recipes/llama_api_providers/Groq/groq-example-templates/llamachat-conversational-chatbot-with-llamaIndex/README.md

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You will need to store a valid Groq API Key as a secret to proceed with this example. You can generate one for free [here](https://console.groq.com/keys).
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<!-- markdown-link-check-enable -->

recipes/llama_api_providers/Groq/groq-example-templates/presidential-speeches-rag-with-pinecone/README.md

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You will need to store a valid Groq API Key as a secret to proceed with this example outside of this Repl. You can generate one for free [here](https://console.groq.com/keys).
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You would also need your own [Pinecone](https://www.pinecone.io/) index with presidential speech embeddings to run this code locally. You can create a Pinecone API key and one index for a small project for free on their Starter plan, and visit [this Cookbook post](https://github.com/groq/groq-api-cookbook/blob/dan/replit-conversion/presidential-speeches-rag/presidential-speeches-rag.ipynb) for more info on RAG and a guide to uploading these embeddings to a vector database
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/Presidential-Speeches-RAG-with-Pinecone) or run it on the command line with `python main.py`.

recipes/llama_api_providers/Groq/groq-example-templates/text-to-sql-json-mode/README.md

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You will need to store a valid Groq API Key as a secret to proceed with this example. You can generate one for free [here](https://console.groq.com/keys).
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/Building-a-Text-to-SQL-app-with-Groqs-JSON-mode) or run it on the command line with `python main.py`.
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## Customizing with Your Own Data

recipes/llama_api_providers/Groq/groq-example-templates/verified-sql-function-calling/README.md

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You will need to store a valid Groq API Key as a secret to proceed with this example. You can generate one for free [here](https://console.groq.com/keys).
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You can [fork and run this application on Replit](https://replit.com/@GroqCloud/Execute-Verified-SQL-Queries-with-Function-Calling) or run it on the command line with `python main.py`.
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