From 4b4f6f4c484bb6f97d8da2f782858ef4a4a60530 Mon Sep 17 00:00:00 2001 From: belloibrahv Date: Thu, 9 Oct 2025 01:55:11 +0100 Subject: [PATCH 1/3] feat: Add AWS Bedrock LLM Support This commit adds support for AWS Bedrock for LLM parsing. The implementation follows the approach of other LLM providers and uses the `BEDROCK_API_KEY` and `BEDROCK_REGION` environment variables for authentication. This resolves issue #1162. --- python/cocoindex/llm.py | 1 + python/cocoindex/tests/test_engine_value.py | 19 ++ src/llm/bedrock.rs | 185 ++++++++++++++++++++ src/llm/mod.rs | 11 +- 4 files changed, 215 insertions(+), 1 deletion(-) create mode 100644 src/llm/bedrock.rs diff --git a/python/cocoindex/llm.py b/python/cocoindex/llm.py index 4dc98c429..3f12c90a6 100644 --- a/python/cocoindex/llm.py +++ b/python/cocoindex/llm.py @@ -14,6 +14,7 @@ class LlmApiType(Enum): OPEN_ROUTER = "OpenRouter" VOYAGE = "Voyage" VLLM = "Vllm" + BEDROCK = "Bedrock" @dataclass diff --git a/python/cocoindex/tests/test_engine_value.py b/python/cocoindex/tests/test_engine_value.py index ec603c13c..c8bfd6a5f 100644 --- a/python/cocoindex/tests/test_engine_value.py +++ b/python/cocoindex/tests/test_engine_value.py @@ -1064,6 +1064,25 @@ def test_full_roundtrip_vector_numeric_types() -> None: validate_full_roundtrip(value_u64, Vector[np.uint64, Literal[3]]) +def test_llm_api_type_bedrock() -> None: + """Test that LlmApiType.BEDROCK is available and works.""" + from cocoindex.llm import LlmApiType, LlmSpec + + # Test enum availability + assert hasattr(LlmApiType, "BEDROCK") + assert LlmApiType.BEDROCK.value == "Bedrock" + + # Test LlmSpec creation with Bedrock + spec = LlmSpec( + api_type=LlmApiType.BEDROCK, model="us.anthropic.claude-3-5-haiku-20241022-v1:0" + ) + + assert spec.api_type == LlmApiType.BEDROCK + assert spec.model == "us.anthropic.claude-3-5-haiku-20241022-v1:0" + assert spec.address is None + assert spec.api_config is None + + def test_full_roundtrip_vector_of_vector() -> None: """Test full roundtrip for vector of vector.""" value_f32 = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=np.float32) diff --git a/src/llm/bedrock.rs b/src/llm/bedrock.rs new file mode 100644 index 000000000..59c9cb4eb --- /dev/null +++ b/src/llm/bedrock.rs @@ -0,0 +1,185 @@ +use crate::prelude::*; +use base64::prelude::*; + +use crate::llm::{ + LlmGenerateRequest, LlmGenerateResponse, LlmGenerationClient, OutputFormat, + ToJsonSchemaOptions, detect_image_mime_type, +}; +use anyhow::Context; +use urlencoding::encode; + +pub struct Client { + api_key: String, + region: String, + client: reqwest::Client, +} + +impl Client { + pub async fn new(address: Option) -> Result { + if address.is_some() { + api_bail!("Bedrock doesn't support custom API address"); + } + + let api_key = match std::env::var("BEDROCK_API_KEY") { + Ok(val) => val, + Err(_) => api_bail!("BEDROCK_API_KEY environment variable must be set"), + }; + + // Default to us-east-1 if no region specified + let region = std::env::var("BEDROCK_REGION").unwrap_or_else(|_| "us-east-1".to_string()); + + Ok(Self { + api_key, + region, + client: reqwest::Client::new(), + }) + } +} + +#[async_trait] +impl LlmGenerationClient for Client { + async fn generate<'req>( + &self, + request: LlmGenerateRequest<'req>, + ) -> Result { + let mut user_content_parts: Vec = Vec::new(); + + // Add image part if present + if let Some(image_bytes) = &request.image { + let base64_image = BASE64_STANDARD.encode(image_bytes.as_ref()); + let mime_type = detect_image_mime_type(image_bytes.as_ref())?; + user_content_parts.push(serde_json::json!({ + "image": { + "format": mime_type.split('/').nth(1).unwrap_or("png"), + "source": { + "bytes": base64_image, + } + } + })); + } + + // Add text part + user_content_parts.push(serde_json::json!({ + "text": request.user_prompt + })); + + let messages = vec![serde_json::json!({ + "role": "user", + "content": user_content_parts + })]; + + let mut payload = serde_json::json!({ + "messages": messages, + "inferenceConfig": { + "maxTokens": 4096 + } + }); + + // Add system prompt if present + if let Some(system) = request.system_prompt { + payload["system"] = serde_json::json!([{ + "text": system + }]); + } + + // Handle structured output using tool schema + if let Some(OutputFormat::JsonSchema { schema, name }) = request.output_format.as_ref() { + let schema_json = serde_json::to_value(schema)?; + payload["toolConfig"] = serde_json::json!({ + "tools": [{ + "toolSpec": { + "name": name, + "description": format!("Extract structured data according to the schema"), + "inputSchema": { + "json": schema_json + } + } + }] + }); + } + + // Construct the Bedrock Runtime API URL + let url = format!( + "https://bedrock-runtime.{}.amazonaws.com/model/{}/converse", + self.region, request.model + ); + + let encoded_api_key = encode(&self.api_key); + + let resp = retryable::run( + || async { + self.client + .post(&url) + .header( + "Authorization", + format!("Bearer {}", encoded_api_key.as_ref()), + ) + .header("Content-Type", "application/json") + .json(&payload) + .send() + .await? + .error_for_status() + }, + &retryable::HEAVY_LOADED_OPTIONS, + ) + .await + .context("Bedrock API error")?; + + let resp_json: serde_json::Value = resp.json().await.context("Invalid JSON")?; + + // Check for errors in the response + if let Some(error) = resp_json.get("error") { + bail!("Bedrock API error: {:?}", error); + } + + // Debug print full response (uncomment for debugging) + // println!("Bedrock API full response: {resp_json:?}"); + + // Extract the response content + let output = &resp_json["output"]; + let message = &output["message"]; + let content = &message["content"]; + + let text = if let Some(content_array) = content.as_array() { + // Look for tool use first (structured output) + let mut extracted_json: Option = None; + for item in content_array { + if let Some(tool_use) = item.get("toolUse") { + if let Some(input) = tool_use.get("input") { + extracted_json = Some(input.clone()); + break; + } + } + } + + if let Some(json) = extracted_json { + // Return the structured output as JSON + serde_json::to_string(&json)? + } else { + // Fall back to text content + let mut text_parts = Vec::new(); + for item in content_array { + if let Some(text) = item.get("text") { + if let Some(text_str) = text.as_str() { + text_parts.push(text_str); + } + } + } + text_parts.join("") + } + } else { + return Err(anyhow::anyhow!("No content found in Bedrock response")); + }; + + Ok(LlmGenerateResponse { text }) + } + + fn json_schema_options(&self) -> ToJsonSchemaOptions { + ToJsonSchemaOptions { + fields_always_required: false, + supports_format: false, + extract_descriptions: false, + top_level_must_be_object: true, + } + } +} diff --git a/src/llm/mod.rs b/src/llm/mod.rs index 2145f2d12..12eda662a 100644 --- a/src/llm/mod.rs +++ b/src/llm/mod.rs @@ -18,6 +18,7 @@ pub enum LlmApiType { Voyage, Vllm, VertexAi, + Bedrock, } #[derive(Debug, Clone, Serialize, Deserialize)] @@ -106,6 +107,7 @@ pub trait LlmEmbeddingClient: Send + Sync { } mod anthropic; +mod bedrock; mod gemini; mod litellm; mod ollama; @@ -134,6 +136,9 @@ pub async fn new_llm_generation_client( LlmApiType::Anthropic => { Box::new(anthropic::Client::new(address).await?) as Box } + LlmApiType::Bedrock => { + Box::new(bedrock::Client::new(address).await?) as Box + } LlmApiType::LiteLlm => { Box::new(litellm::Client::new_litellm(address).await?) as Box } @@ -169,7 +174,11 @@ pub async fn new_llm_embedding_client( } LlmApiType::VertexAi => Box::new(gemini::VertexAiClient::new(address, api_config).await?) as Box, - LlmApiType::OpenRouter | LlmApiType::LiteLlm | LlmApiType::Vllm | LlmApiType::Anthropic => { + LlmApiType::OpenRouter + | LlmApiType::LiteLlm + | LlmApiType::Vllm + | LlmApiType::Anthropic + | LlmApiType::Bedrock => { api_bail!("Embedding is not supported for API type {:?}", api_type) } }; From 736b580961b3929736fe414ee0d2b239443540c5 Mon Sep 17 00:00:00 2001 From: belloibrahv Date: Thu, 9 Oct 2025 15:33:51 +0100 Subject: [PATCH 2/3] feat: add bedrock llm extraction example --- examples/bedrock_llm_extraction/.env.example | 10 ++ examples/bedrock_llm_extraction/.gitignore | 1 + examples/bedrock_llm_extraction/README.md | 72 +++++++++ examples/bedrock_llm_extraction/main.py | 138 ++++++++++++++++++ .../bedrock_llm_extraction/manuals/array.pdf | Bin 0 -> 379766 bytes .../bedrock_llm_extraction/manuals/base64.pdf | Bin 0 -> 434195 bytes .../bedrock_llm_extraction/manuals/copy.pdf | Bin 0 -> 194798 bytes .../bedrock_llm_extraction/manuals/glob.pdf | Bin 0 -> 327806 bytes .../bedrock_llm_extraction/pyproject.toml | 9 ++ 9 files changed, 230 insertions(+) create mode 100644 examples/bedrock_llm_extraction/.env.example create mode 100644 examples/bedrock_llm_extraction/.gitignore create mode 100644 examples/bedrock_llm_extraction/README.md create mode 100644 examples/bedrock_llm_extraction/main.py create mode 100644 examples/bedrock_llm_extraction/manuals/array.pdf create mode 100644 examples/bedrock_llm_extraction/manuals/base64.pdf create mode 100644 examples/bedrock_llm_extraction/manuals/copy.pdf create mode 100644 examples/bedrock_llm_extraction/manuals/glob.pdf create mode 100644 examples/bedrock_llm_extraction/pyproject.toml diff --git a/examples/bedrock_llm_extraction/.env.example b/examples/bedrock_llm_extraction/.env.example new file mode 100644 index 000000000..6273ba314 --- /dev/null +++ b/examples/bedrock_llm_extraction/.env.example @@ -0,0 +1,10 @@ +# Postgres database address for cocoindex +COCOINDEX_DATABASE_URL=postgres://cocoindex:cocoindex@localhost/cocoindex + +# Fallback to CPU for operations not supported by MPS on Mac. +# It's no-op for other platforms. +PYTORCH_ENABLE_MPS_FALLBACK=1 + +# AWS Bedrock credentials +BEDROCK_API_KEY=your_bedrock_api_key +BEDROCK_REGION=your_bedrock_region diff --git a/examples/bedrock_llm_extraction/.gitignore b/examples/bedrock_llm_extraction/.gitignore new file mode 100644 index 000000000..4c49bd78f --- /dev/null +++ b/examples/bedrock_llm_extraction/.gitignore @@ -0,0 +1 @@ +.env diff --git a/examples/bedrock_llm_extraction/README.md b/examples/bedrock_llm_extraction/README.md new file mode 100644 index 000000000..b03efcc4a --- /dev/null +++ b/examples/bedrock_llm_extraction/README.md @@ -0,0 +1,72 @@ +# Structured Data Extraction from PDF with AWS Bedrock and CocoIndex + +In this example, we + +* Converts PDFs (generated from a few Python docs) into Markdown. +* Extract structured information from the Markdown using an AWS Bedrock LLM. +* Use a custom function to further extract information from the structured output. + +Please give [Cocoindex on Github](https://github.com/cocoindex-io/cocoindex) a star to support us if you like our work. Thank you so much with a warm coconut hug 🥥🤗. [![GitHub](https://img.shields.io/github/stars/cocoindex-io/cocoindex?color=5B5BD6)](https://github.com/cocoindex-io/cocoindex) + +## Prerequisite + +Before running the example, you need to: + +* [Install Postgres](https://cocoindex.io/docs/getting_started/installation#-install-postgres) if you don't have one. +* Configure your AWS Bedrock credentials. In this example we use AWS Bedrock. You need to get it ready by following [this guide](https://docs.aws.amazon.com/bedrock/latest/userguide/api-keys.html) to create an API key. Alternatively, you can also follow the comments in source code to switch to other LLMs. + +First, copy the example environment file: + +```bash +cp .env.example .env +``` + +Then, open the `.env` file and fill in your AWS Bedrock credentials. The `.env` file is ignored by git, so your secrets will not be committed. + +## Run + + +### Build the index + +Install dependencies: + +```bash +pip install -e . +``` + +Setup: + +```bash +cocoindex setup main.py +``` + +Update index: + +```bash +cocoindex update main.py +``` + +### Query the index + +After index is build, you have a table with name `modules_info`. You can query it any time, e.g. start a Postgres shell: + +```bash +psql postgres://cocoindex:cocoindex@localhost/cocoindex +``` + +And run the SQL query: + +```sql +SELECT filename, module_info->'title' AS title, module_summary FROM modules_info; +``` +You should see results like: + +``` + filename | title | module_summary +---------------------+------------------------+-------------------------- + manuals/asyncio.pdf | "asyncio — Asynchronous" | {"num_classes": 0, "num_methods": 0} + manuals/json.pdf | "json — JSON encoder" | {"num_classes": 0, "num_methods": 0} +(2 rows) +``` + +The output may vary depending on the model you are using. The important part is that the `module_info` and `module_summary` columns are populated with the extracted data. diff --git a/examples/bedrock_llm_extraction/main.py b/examples/bedrock_llm_extraction/main.py new file mode 100644 index 000000000..68745b910 --- /dev/null +++ b/examples/bedrock_llm_extraction/main.py @@ -0,0 +1,138 @@ +import tempfile +import dataclasses + +from marker.converters.pdf import PdfConverter +from marker.models import create_model_dict +from marker.output import text_from_rendered +from marker.config.parser import ConfigParser + +import cocoindex + + +class PdfToMarkdown(cocoindex.op.FunctionSpec): + """Convert a PDF to markdown.""" + + +@cocoindex.op.executor_class(gpu=True, cache=True, behavior_version=1) +class PdfToMarkdownExecutor: + """Executor for PdfToMarkdown.""" + + spec: PdfToMarkdown + _converter: PdfConverter + + def prepare(self): + config_parser = ConfigParser({}) + self._converter = PdfConverter( + create_model_dict(), config=config_parser.generate_config_dict() + ) + + def __call__(self, content: bytes) -> str: + with tempfile.NamedTemporaryFile(delete=True, suffix=".pdf") as temp_file: + temp_file.write(content) + temp_file.flush() + text, _, _ = text_from_rendered(self._converter(temp_file.name)) + return text + + +@dataclasses.dataclass +class ArgInfo: + """Information about an argument of a method.""" + + name: str + description: str + + +@dataclasses.dataclass +class MethodInfo: + """Information about a method.""" + + name: str + args: list[ArgInfo] + description: str + + +@dataclasses.dataclass +class ClassInfo: + """Information about a class.""" + + name: str + description: str + methods: list[MethodInfo] + + +@dataclasses.dataclass +class ModuleInfo: + """Information about a Python module.""" + + title: str + description: str + classes: list[ClassInfo] + methods: list[MethodInfo] + + +@dataclasses.dataclass +class ModuleSummary: + """Summary info about a Python module.""" + + num_classes: int + num_methods: int + + +@cocoindex.op.function() +def summarize_module(module_info: ModuleInfo) -> ModuleSummary: + """Summarize a Python module.""" + return ModuleSummary( + num_classes=len(module_info.classes), + num_methods=len(module_info.methods), + ) + + +@cocoindex.flow_def(name="ManualExtraction") +def manual_extraction_flow( + flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.DataScope +): + """ + Define an example flow that extracts manual information from a Markdown. + """ + data_scope["documents"] = flow_builder.add_source( + cocoindex.sources.LocalFile(path="manuals", binary=True) + ) + + modules_index = data_scope.add_collector() + + with data_scope["documents"].row() as doc: + doc["markdown"] = doc["content"].transform(PdfToMarkdown()) + doc["module_info"] = doc["markdown"].transform( + cocoindex.functions.ExtractByLlm( + llm_spec=cocoindex.LlmSpec( + api_type=cocoindex.LlmApiType.BEDROCK, + model="anthropic.claude-3-haiku-20240307-v1:0", + ), + # Replace by this spec below, to use OpenAI API model instead of ollama + # llm_spec=cocoindex.LlmSpec( + # api_type=cocoindex.LlmApiType.OPENAI, model="gpt-4o"), + # Replace by this spec below, to use Gemini API model + # llm_spec=cocoindex.LlmSpec( + # api_type=cocoindex.LlmApiType.GEMINI, model="gemini-2.0-flash"), + # Replace by this spec below, to use Anthropic API model + # llm_spec=cocoindex.LlmSpec( + # api_type=cocoindex.LlmApiType.ANTHROPIC, model="claude-3-5-sonnet-latest"), + # Replace by this spec below, to use Ollama API model + # llm_spec=cocoindex.LlmSpec( + # api_type=cocoindex.LlmApiType.OLLAMA, model="llama3.2"), + output_type=ModuleInfo, + instruction="Please extract Python module information from the manual.", + ) + ) + doc["module_summary"] = doc["module_info"].transform(summarize_module) + modules_index.collect( + filename=doc["filename"], + module_info=doc["module_info"], + module_summary=doc["module_summary"], + ) + + modules_index.export( + "modules", + 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17 00:00:00 2001 From: belloibrahv Date: Sat, 11 Oct 2025 11:12:49 +0100 Subject: [PATCH 3/3] feat: address feedback on Bedrock LLM support PR - Update documentation to include Bedrock LLM integration. - Remove unnecessary test for LlmApiType.BEDROCK. - Add Bedrock to the existing manuals_llm_extraction example instead of creating a new one. --- docs/docs/ai/llm.mdx | 26 ++++ examples/bedrock_llm_extraction/.env.example | 10 -- examples/bedrock_llm_extraction/.gitignore | 1 - examples/bedrock_llm_extraction/README.md | 72 --------- examples/bedrock_llm_extraction/main.py | 138 ------------------ .../bedrock_llm_extraction/manuals/array.pdf | Bin 379766 -> 0 bytes .../bedrock_llm_extraction/manuals/base64.pdf | Bin 434195 -> 0 bytes .../bedrock_llm_extraction/manuals/copy.pdf | Bin 194798 -> 0 bytes .../bedrock_llm_extraction/manuals/glob.pdf | Bin 327806 -> 0 bytes .../bedrock_llm_extraction/pyproject.toml | 9 -- examples/manuals_llm_extraction/main.py | 3 + python/cocoindex/tests/test_engine_value.py | 19 --- 12 files changed, 29 insertions(+), 249 deletions(-) delete mode 100644 examples/bedrock_llm_extraction/.env.example delete mode 100644 examples/bedrock_llm_extraction/.gitignore delete mode 100644 examples/bedrock_llm_extraction/README.md delete mode 100644 examples/bedrock_llm_extraction/main.py delete mode 100644 examples/bedrock_llm_extraction/manuals/array.pdf delete mode 100644 examples/bedrock_llm_extraction/manuals/base64.pdf delete mode 100644 examples/bedrock_llm_extraction/manuals/copy.pdf delete mode 100644 examples/bedrock_llm_extraction/manuals/glob.pdf delete mode 100644 examples/bedrock_llm_extraction/pyproject.toml diff --git a/docs/docs/ai/llm.mdx b/docs/docs/ai/llm.mdx index 42fdfbb59..a01f79eb1 100644 --- a/docs/docs/ai/llm.mdx +++ b/docs/docs/ai/llm.mdx @@ -28,6 +28,7 @@ We support the following types of LLM APIs: | [LiteLLM](#litellm) | `LlmApiType.LITE_LLM` | ✅ | ❌ | | [OpenRouter](#openrouter) | `LlmApiType.OPEN_ROUTER` | ✅ | ❌ | | [vLLM](#vllm) | `LlmApiType.VLLM` | ✅ | ❌ | +| [Bedrock](#bedrock) | `LlmApiType.BEDROCK` | ✅ | ❌ | ## LLM Tasks @@ -440,3 +441,28 @@ cocoindex.LlmSpec( + +### Bedrock + +To use the Bedrock API, you need to set up AWS credentials. You can do this by setting the following environment variables: + +- `AWS_ACCESS_KEY_ID` +- `AWS_SECRET_ACCESS_KEY` +- `AWS_SESSION_TOKEN` (optional) + +A spec for Bedrock looks like this: + + + + +```python +cocoindex.LlmSpec( + api_type=cocoindex.LlmApiType.BEDROCK, + model="us.anthropic.claude-3-5-haiku-20241022-v1:0", +) +``` + + + + +You can find the full list of models supported by Bedrock [here](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html). diff --git a/examples/bedrock_llm_extraction/.env.example b/examples/bedrock_llm_extraction/.env.example deleted file mode 100644 index 6273ba314..000000000 --- a/examples/bedrock_llm_extraction/.env.example +++ /dev/null @@ -1,10 +0,0 @@ -# Postgres database address for cocoindex -COCOINDEX_DATABASE_URL=postgres://cocoindex:cocoindex@localhost/cocoindex - -# Fallback to CPU for operations not supported by MPS on Mac. -# It's no-op for other platforms. -PYTORCH_ENABLE_MPS_FALLBACK=1 - -# AWS Bedrock credentials -BEDROCK_API_KEY=your_bedrock_api_key -BEDROCK_REGION=your_bedrock_region diff --git a/examples/bedrock_llm_extraction/.gitignore b/examples/bedrock_llm_extraction/.gitignore deleted file mode 100644 index 4c49bd78f..000000000 --- a/examples/bedrock_llm_extraction/.gitignore +++ /dev/null @@ -1 +0,0 @@ -.env diff --git a/examples/bedrock_llm_extraction/README.md b/examples/bedrock_llm_extraction/README.md deleted file mode 100644 index b03efcc4a..000000000 --- a/examples/bedrock_llm_extraction/README.md +++ /dev/null @@ -1,72 +0,0 @@ -# Structured Data Extraction from PDF with AWS Bedrock and CocoIndex - -In this example, we - -* Converts PDFs (generated from a few Python docs) into Markdown. -* Extract structured information from the Markdown using an AWS Bedrock LLM. -* Use a custom function to further extract information from the structured output. - -Please give [Cocoindex on Github](https://github.com/cocoindex-io/cocoindex) a star to support us if you like our work. Thank you so much with a warm coconut hug 🥥🤗. [![GitHub](https://img.shields.io/github/stars/cocoindex-io/cocoindex?color=5B5BD6)](https://github.com/cocoindex-io/cocoindex) - -## Prerequisite - -Before running the example, you need to: - -* [Install Postgres](https://cocoindex.io/docs/getting_started/installation#-install-postgres) if you don't have one. -* Configure your AWS Bedrock credentials. In this example we use AWS Bedrock. You need to get it ready by following [this guide](https://docs.aws.amazon.com/bedrock/latest/userguide/api-keys.html) to create an API key. Alternatively, you can also follow the comments in source code to switch to other LLMs. - -First, copy the example environment file: - -```bash -cp .env.example .env -``` - -Then, open the `.env` file and fill in your AWS Bedrock credentials. The `.env` file is ignored by git, so your secrets will not be committed. - -## Run - - -### Build the index - -Install dependencies: - -```bash -pip install -e . -``` - -Setup: - -```bash -cocoindex setup main.py -``` - -Update index: - -```bash -cocoindex update main.py -``` - -### Query the index - -After index is build, you have a table with name `modules_info`. You can query it any time, e.g. start a Postgres shell: - -```bash -psql postgres://cocoindex:cocoindex@localhost/cocoindex -``` - -And run the SQL query: - -```sql -SELECT filename, module_info->'title' AS title, module_summary FROM modules_info; -``` -You should see results like: - -``` - filename | title | module_summary ----------------------+------------------------+-------------------------- - manuals/asyncio.pdf | "asyncio — Asynchronous" | {"num_classes": 0, "num_methods": 0} - manuals/json.pdf | "json — JSON encoder" | {"num_classes": 0, "num_methods": 0} -(2 rows) -``` - -The output may vary depending on the model you are using. The important part is that the `module_info` and `module_summary` columns are populated with the extracted data. diff --git a/examples/bedrock_llm_extraction/main.py b/examples/bedrock_llm_extraction/main.py deleted file mode 100644 index 68745b910..000000000 --- a/examples/bedrock_llm_extraction/main.py +++ /dev/null @@ -1,138 +0,0 @@ -import tempfile -import dataclasses - -from marker.converters.pdf import PdfConverter -from marker.models import create_model_dict -from marker.output import text_from_rendered -from marker.config.parser import ConfigParser - -import cocoindex - - -class PdfToMarkdown(cocoindex.op.FunctionSpec): - """Convert a PDF to markdown.""" - - -@cocoindex.op.executor_class(gpu=True, cache=True, behavior_version=1) -class PdfToMarkdownExecutor: - """Executor for PdfToMarkdown.""" - - spec: PdfToMarkdown - _converter: PdfConverter - - def prepare(self): - config_parser = ConfigParser({}) - self._converter = PdfConverter( - create_model_dict(), config=config_parser.generate_config_dict() - ) - - def __call__(self, content: bytes) -> str: - with tempfile.NamedTemporaryFile(delete=True, suffix=".pdf") as temp_file: - temp_file.write(content) - temp_file.flush() - text, _, _ = text_from_rendered(self._converter(temp_file.name)) - return text - - -@dataclasses.dataclass -class ArgInfo: - """Information about an argument of a method.""" - - name: str - description: str - - -@dataclasses.dataclass -class MethodInfo: - """Information about a method.""" - - name: str - args: list[ArgInfo] - description: str - - -@dataclasses.dataclass -class ClassInfo: - """Information about a class.""" - - name: str - description: str - methods: list[MethodInfo] - - -@dataclasses.dataclass -class ModuleInfo: - """Information about a Python module.""" - - title: str - description: str - classes: list[ClassInfo] - methods: list[MethodInfo] - - -@dataclasses.dataclass -class ModuleSummary: - """Summary info about a Python module.""" - - num_classes: int - num_methods: int - - -@cocoindex.op.function() -def summarize_module(module_info: ModuleInfo) -> ModuleSummary: - """Summarize a Python module.""" - return ModuleSummary( - num_classes=len(module_info.classes), - num_methods=len(module_info.methods), - ) - - -@cocoindex.flow_def(name="ManualExtraction") -def manual_extraction_flow( - flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.DataScope -): - """ - Define an example flow that extracts manual information from a Markdown. - """ - data_scope["documents"] = flow_builder.add_source( - cocoindex.sources.LocalFile(path="manuals", binary=True) - ) - - modules_index = data_scope.add_collector() - - with data_scope["documents"].row() as doc: - doc["markdown"] = doc["content"].transform(PdfToMarkdown()) - doc["module_info"] = doc["markdown"].transform( - cocoindex.functions.ExtractByLlm( - llm_spec=cocoindex.LlmSpec( - api_type=cocoindex.LlmApiType.BEDROCK, - model="anthropic.claude-3-haiku-20240307-v1:0", - ), - # Replace by this spec below, to use OpenAI API model instead of ollama - # llm_spec=cocoindex.LlmSpec( - # api_type=cocoindex.LlmApiType.OPENAI, model="gpt-4o"), - # Replace by this spec below, to use Gemini API model - # llm_spec=cocoindex.LlmSpec( - # api_type=cocoindex.LlmApiType.GEMINI, model="gemini-2.0-flash"), - # Replace by this spec below, to use Anthropic API model - # llm_spec=cocoindex.LlmSpec( - # api_type=cocoindex.LlmApiType.ANTHROPIC, model="claude-3-5-sonnet-latest"), - # Replace by this spec below, to use Ollama API model - # llm_spec=cocoindex.LlmSpec( - # api_type=cocoindex.LlmApiType.OLLAMA, model="llama3.2"), - output_type=ModuleInfo, - instruction="Please extract Python module information from the manual.", - ) - ) - doc["module_summary"] = doc["module_info"].transform(summarize_module) - modules_index.collect( - filename=doc["filename"], - module_info=doc["module_info"], - module_summary=doc["module_summary"], - ) - - modules_index.export( - "modules", - 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zjU5ZzI(A=*TZ{C8c$$3{=8e_603JwA9SWQHyP)AT6f+i_y=H9`IEq3eww(q&37?v* zC46dD-^<`;v$hs@@6h{}aC(c)Zy{4ed|S}S9W$Vjnk@0O8d+Zqh3HdMShIFjj9kc` zhX2gsbs{W4=8LmmMDHRbW^E%Dh~)P{gAg&i7tcMh>jtgC`nyo4)Xs1y3u5JpH10>`b9-v}}t&c!E01~7fsVBsWlX^Ju)FK;; zgGSCGgGPNblwPtmPpDJ_GO9infFPuf7Bq6s3&;b>d4UFCfPEjzHyFNPN2}HS`%Uri z9p^bk7au)!@SW-T?IOcY_7f-i8CT$c;^l|^CU{N6=O}RzBJMq$>gO@Vuj1B2IK+rI Mbz8Nv9Au^YKgk0sXaE2J diff --git a/examples/bedrock_llm_extraction/pyproject.toml b/examples/bedrock_llm_extraction/pyproject.toml deleted file mode 100644 index c3fb97d6d..000000000 --- a/examples/bedrock_llm_extraction/pyproject.toml +++ /dev/null @@ -1,9 +0,0 @@ -[project] -name = "manuals-llm-extraction" -version = "0.1.0" -description = "Simple example for cocoindex: extract structured information from a Markdown file using LLM." -requires-python = ">=3.11" -dependencies = ["cocoindex>=0.2.8", "marker-pdf>=1.8.5"] - -[tool.setuptools] -packages = [] diff --git a/examples/manuals_llm_extraction/main.py b/examples/manuals_llm_extraction/main.py index e35a7700d..769272269 100644 --- a/examples/manuals_llm_extraction/main.py +++ b/examples/manuals_llm_extraction/main.py @@ -118,6 +118,9 @@ def manual_extraction_flow( # Replace by this spec below, to use Anthropic API model # llm_spec=cocoindex.LlmSpec( # api_type=cocoindex.LlmApiType.ANTHROPIC, model="claude-3-5-sonnet-latest"), + # Replace by this spec below, to use Bedrock API model + # llm_spec=cocoindex.LlmSpec( + # api_type=cocoindex.LlmApiType.BEDROCK, model="us.anthropic.claude-3-5-haiku-20241022-v1:0"), output_type=ModuleInfo, instruction="Please extract Python module information from the manual.", ) diff --git a/python/cocoindex/tests/test_engine_value.py b/python/cocoindex/tests/test_engine_value.py index c8bfd6a5f..ec603c13c 100644 --- a/python/cocoindex/tests/test_engine_value.py +++ b/python/cocoindex/tests/test_engine_value.py @@ -1064,25 +1064,6 @@ def test_full_roundtrip_vector_numeric_types() -> None: validate_full_roundtrip(value_u64, Vector[np.uint64, Literal[3]]) -def test_llm_api_type_bedrock() -> None: - """Test that LlmApiType.BEDROCK is available and works.""" - from cocoindex.llm import LlmApiType, LlmSpec - - # Test enum availability - assert hasattr(LlmApiType, "BEDROCK") - assert LlmApiType.BEDROCK.value == "Bedrock" - - # Test LlmSpec creation with Bedrock - spec = LlmSpec( - api_type=LlmApiType.BEDROCK, model="us.anthropic.claude-3-5-haiku-20241022-v1:0" - ) - - assert spec.api_type == LlmApiType.BEDROCK - assert spec.model == "us.anthropic.claude-3-5-haiku-20241022-v1:0" - assert spec.address is None - assert spec.api_config is None - - def test_full_roundtrip_vector_of_vector() -> None: """Test full roundtrip for vector of vector.""" value_f32 = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=np.float32)

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