diff --git a/.github/scripts/check_diff.py b/.github/scripts/check_diff.py index 17f08fe0bbf56..068c75ef01782 100644 --- a/.github/scripts/check_diff.py +++ b/.github/scripts/check_diff.py @@ -300,6 +300,8 @@ def _get_configs_for_multi_dirs( ] != ["README.md"]: dirs_to_run["test"].add(f"libs/partners/{partner_dir}") # Skip if the directory was deleted or is just a tombstone readme + elif file == "libs/packages.yml": + continue elif file.startswith("libs/"): raise ValueError( f"Unknown lib: {file}. check_diff.py likely needs " diff --git a/.github/scripts/prep_api_docs_build.py b/.github/scripts/prep_api_docs_build.py new file mode 100644 index 0000000000000..2c2655e2155a4 --- /dev/null +++ b/.github/scripts/prep_api_docs_build.py @@ -0,0 +1,87 @@ +#!/usr/bin/env python +"""Script to sync libraries from various repositories into the main langchain repository.""" + +import os +import shutil +import yaml +from pathlib import Path +from typing import Dict, Any + + +def load_packages_yaml() -> Dict[str, Any]: + """Load and parse the packages.yml file.""" + with open("langchain/libs/packages.yml", "r") as f: + return yaml.safe_load(f) + + +def get_target_dir(package_name: str) -> Path: + """Get the target directory for a given package.""" + package_name_short = package_name.replace("langchain-", "") + base_path = Path("langchain/libs") + if package_name_short == "experimental": + return base_path / "experimental" + return base_path / "partners" / package_name_short + + +def clean_target_directories(packages: Dict[str, Any]) -> None: + """Remove old directories that will be replaced.""" + for package in packages["packages"]: + if package["repo"] != "langchain-ai/langchain": + target_dir = get_target_dir(package["name"]) + if target_dir.exists(): + print(f"Removing {target_dir}") + shutil.rmtree(target_dir) + + +def move_libraries(packages: Dict[str, Any]) -> None: + """Move libraries from their source locations to the target directories.""" + for package in packages["packages"]: + # Skip if it's the main langchain repo or disabled + if package["repo"] == "langchain-ai/langchain" or package.get( + "disabled", False + ): + continue + + repo_name = package["repo"].split("/")[1] + source_path = package["path"] + target_dir = get_target_dir(package["name"]) + + # Handle root path case + if source_path == ".": + source_dir = repo_name + else: + source_dir = f"{repo_name}/{source_path}" + + print(f"Moving {source_dir} to {target_dir}") + + # Ensure target directory exists + os.makedirs(os.path.dirname(target_dir), exist_ok=True) + + try: + # Move the directory + shutil.move(source_dir, target_dir) + except Exception as e: + print(f"Error moving {source_dir} to {target_dir}: {e}") + + +def main(): + """Main function to orchestrate the library sync process.""" + try: + # Load packages configuration + packages = load_packages_yaml() + + # Clean target directories + clean_target_directories(packages) + + # Move libraries to their new locations + move_libraries(packages) + + print("Library sync completed successfully!") + + except Exception as e: + print(f"Error during library sync: {e}") + raise + + +if __name__ == "__main__": + main() diff --git a/.github/workflows/_integration_test.yml b/.github/workflows/_integration_test.yml index 13051f5efc224..60a74ff08734d 100644 --- a/.github/workflows/_integration_test.yml +++ b/.github/workflows/_integration_test.yml @@ -81,7 +81,6 @@ jobs: ES_URL: ${{ secrets.ES_URL }} ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }} ES_API_KEY: ${{ secrets.ES_API_KEY }} - GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # for airbyte MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }} VOYAGE_API_KEY: ${{ secrets.VOYAGE_API_KEY }} COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }} diff --git a/.github/workflows/_release.yml b/.github/workflows/_release.yml index f84ff3ac28d19..76b9330701730 100644 --- a/.github/workflows/_release.yml +++ b/.github/workflows/_release.yml @@ -289,7 +289,6 @@ jobs: ES_URL: ${{ secrets.ES_URL }} ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }} ES_API_KEY: ${{ secrets.ES_API_KEY }} - GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # for airbyte MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }} VOYAGE_API_KEY: ${{ secrets.VOYAGE_API_KEY }} UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }} diff --git a/.github/workflows/api_doc_build.yml b/.github/workflows/api_doc_build.yml index 442a5ab18ed80..26e2b19cb4602 100644 --- a/.github/workflows/api_doc_build.yml +++ b/.github/workflows/api_doc_build.yml @@ -22,133 +22,29 @@ jobs: repository: langchain-ai/langchain-api-docs-html path: langchain-api-docs-html token: ${{ secrets.TOKEN_GITHUB_API_DOCS_HTML }} - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-google - path: langchain-google - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-datastax - path: langchain-datastax - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-nvidia - path: langchain-nvidia - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-cohere - path: langchain-cohere - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-elastic - path: langchain-elastic - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-postgres - path: langchain-postgres - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-aws - path: langchain-aws - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-weaviate - path: langchain-weaviate - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-ai21 - path: langchain-ai21 - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-together - path: langchain-together - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-experimental - path: langchain-experimental - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-milvus - path: langchain-milvus - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-unstructured - path: langchain-unstructured - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-databricks - path: langchain-databricks - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-ibm - path: langchain-ibm - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-azure - path: langchain-azure - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-mongodb - path: langchain-mongodb - - uses: actions/checkout@v4 - with: - repository: langchain-ai/langchain-redis - path: langchain-redis - + - name: Get repos with yq + id: get-unsorted-repos + uses: mikefarah/yq@master + with: + cmd: yq '.packages[].repo' langchain/libs/packages.yml - - name: Set Git config - working-directory: langchain + - name: Parse YAML and checkout repos + env: + REPOS_UNSORTED: ${{ steps.get-unsorted-repos.outputs.result }} + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} run: | - git config --local user.email "actions@github.com" - git config --local user.name "Github Actions" + # Get unique repositories + REPOS=$(echo "$REPOS_UNSORTED" | sort -u) - - name: Move libs - run: | - rm -rf \ - langchain/libs/partners/google-genai \ - langchain/libs/partners/google-vertexai \ - langchain/libs/partners/astradb \ - langchain/libs/partners/nvidia-trt \ - langchain/libs/partners/nvidia-ai-endpoints \ - langchain/libs/partners/cohere \ - langchain/libs/partners/elasticsearch \ - langchain/libs/partners/upstage \ - langchain/libs/partners/ai21 \ - langchain/libs/partners/together \ - langchain/libs/standard-tests \ - langchain/libs/experimental \ - langchain/libs/partners/milvus \ - langchain/libs/partners/unstructured \ - langchain/libs/partners/databricks \ - langchain/libs/partners/ibm \ - langchain/libs/partners/azure-dynamic-sessions \ - langchain/libs/partners/mongodb \ - langchain/libs/partners/redis - mv langchain-google/libs/genai langchain/libs/partners/google-genai - mv langchain-google/libs/vertexai langchain/libs/partners/google-vertexai - mv langchain-google/libs/community langchain/libs/partners/google-community - mv langchain-datastax/libs/astradb langchain/libs/partners/astradb - mv langchain-nvidia/libs/ai-endpoints langchain/libs/partners/nvidia-ai-endpoints - mv langchain-cohere/libs/cohere langchain/libs/partners/cohere - mv langchain-elastic/libs/elasticsearch langchain/libs/partners/elasticsearch - mv langchain-postgres langchain/libs/partners/postgres - mv langchain-aws/libs/aws langchain/libs/partners/aws - mv langchain-weaviate/libs/weaviate langchain/libs/partners/weaviate - mv langchain-ai21/libs/ai21 langchain/libs/partners/ai21 - mv langchain-together/libs/together langchain/libs/partners/together - mv langchain-experimental/libs/experimental langchain/libs/experimental - mv langchain-milvus/libs/milvus langchain/libs/partners/milvus - mv langchain-unstructured/libs/unstructured langchain/libs/partners/unstructured - mv langchain-databricks/libs/databricks langchain/libs/partners/databricks - mv langchain-ibm/libs/ibm langchain/libs/partners/ibm - mv langchain-azure/libs/azure-dynamic-sessions langchain/libs/partners/azure-dynamic-sessions - mv langchain-mongodb/libs/mongodb langchain/libs/partners/mongodb - mv langchain-redis/libs/redis langchain/libs/partners/redis - - - name: Rm old html - run: - rm -rf langchain-api-docs-html/api_reference_build/html + # Checkout each unique repository + for repo in $REPOS; do + if [ "$repo" != "langchain-ai/langchain" ]; then + REPO_NAME=$(echo $repo | cut -d'/' -f2) + echo "Checking out $repo to $REPO_NAME" + git clone --depth 1 https://github.com/$repo.git $REPO_NAME + fi + done - name: Set up Python ${{ env.PYTHON_VERSION }} + Poetry ${{ env.POETRY_VERSION }} uses: "./langchain/.github/actions/poetry_setup" @@ -158,16 +54,34 @@ jobs: cache-key: api-docs working-directory: langchain - - name: Install dependencies + - name: Install initial py deps working-directory: langchain run: | python -m pip install -U uv - python -m uv pip install --upgrade --no-cache-dir pip setuptools - # skip airbyte due to pandas dependency issue - python -m uv pip install $(ls ./libs/partners | grep -vE "airbyte" | xargs -I {} echo "./libs/partners/{}") + python -m uv pip install --upgrade --no-cache-dir pip setuptools pyyaml + + - name: Move libs with script + run: python langchain/.github/scripts/prep_api_docs_build.py + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + + - name: Rm old html + run: + rm -rf langchain-api-docs-html/api_reference_build/html + + - name: Install dependencies + working-directory: langchain + run: | + python -m uv pip install $(ls ./libs/partners | xargs -I {} echo "./libs/partners/{}") python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental python -m uv pip install -r docs/api_reference/requirements.txt + - name: Set Git config + working-directory: langchain + run: | + git config --local user.email "actions@github.com" + git config --local user.name "Github Actions" + - name: Build docs working-directory: langchain run: | @@ -182,4 +96,4 @@ jobs: - uses: EndBug/add-and-commit@v9 with: cwd: langchain-api-docs-html - message: 'Update API docs build' \ No newline at end of file + message: 'Update API docs build' diff --git a/docs/api_reference/create_api_rst.py b/docs/api_reference/create_api_rst.py index d907eec4c360e..56ec6f870b4e0 100644 --- a/docs/api_reference/create_api_rst.py +++ b/docs/api_reference/create_api_rst.py @@ -530,7 +530,6 @@ def _out_file_path(package_name: str) -> Path: def _build_index(dirs: List[str]) -> None: custom_names = { - "airbyte": "Airbyte", "aws": "AWS", "ai21": "AI21", "ibm": "IBM", @@ -601,9 +600,11 @@ def _build_index(dirs: List[str]) -> None: ] for header_name, dir_ in sorted( zip(integration_headers, integrations), - key=lambda h_d: integrations_to_show.index(h_d[1]) - if h_d[1] in integrations_to_show - else len(integrations_to_show), + key=lambda h_d: ( + integrations_to_show.index(h_d[1]) + if h_d[1] in integrations_to_show + else len(integrations_to_show) + ), )[: len(integrations_to_show)]: integration_grid += f'\n- header: "**{header_name}**"\n content: {_package_namespace(dir_).replace("_", "-")} {_get_package_version(_package_dir(dir_))}\n link: {dir_.replace("-", "_")}/index.html' doc += f"""## Integrations @@ -648,7 +649,7 @@ def main(dirs: Optional[list] = None) -> None: dirs = [ dir_ for dir_ in os.listdir(ROOT_DIR / "libs") - if dir_ not in ("cli", "partners", "standard-tests") + if dir_ not in ("cli", "partners", "standard-tests", "packages.yml") ] dirs += [ dir_ diff --git a/docs/docs/concepts/async.mdx b/docs/docs/concepts/async.mdx index 644c49d1d7bcd..2eab35964b3b5 100644 --- a/docs/docs/concepts/async.mdx +++ b/docs/docs/concepts/async.mdx @@ -73,7 +73,7 @@ in certain scenarios. If you are experiencing issues with streaming, callbacks or tracing in async code and are using Python 3.9 or 3.10, this is a likely cause. -Please read [Propagation RunnableConfig](/docs/concepts/runnables#propagation-RunnableConfig) for more details to learn how to propagate the `RunnableConfig` down the call chain manually (or upgrade to Python 3.11 where this is no longer an issue). +Please read [Propagation RunnableConfig](/docs/concepts/runnables/#propagation-of-runnableconfig) for more details to learn how to propagate the `RunnableConfig` down the call chain manually (or upgrade to Python 3.11 where this is no longer an issue). ## How to use in ipython and jupyter notebooks diff --git a/docs/docs/concepts/chat_history.mdx b/docs/docs/concepts/chat_history.mdx index b22862512a873..5c7c112460d2b 100644 --- a/docs/docs/concepts/chat_history.mdx +++ b/docs/docs/concepts/chat_history.mdx @@ -24,7 +24,7 @@ So a full conversation often involves a combination of two patterns of alternati ## Managing chat history -Since chat models have a maximum limit on input size, it's important to manage chat history and trim it as needed to avoid exceeding the [context window](/docs/concepts/chat_models#context_window). +Since chat models have a maximum limit on input size, it's important to manage chat history and trim it as needed to avoid exceeding the [context window](/docs/concepts/chat_models/#context-window). While processing chat history, it's essential to preserve a correct conversation structure. diff --git a/docs/docs/concepts/chat_models.mdx b/docs/docs/concepts/chat_models.mdx index 1c264fcac1654..67a27efe82c0d 100644 --- a/docs/docs/concepts/chat_models.mdx +++ b/docs/docs/concepts/chat_models.mdx @@ -8,7 +8,7 @@ Modern LLMs are typically accessed through a chat model interface that takes a l The newest generation of chat models offer additional capabilities: -* [Tool calling](/docs/concepts#tool-calling): Many popular chat models offer a native [tool calling](/docs/concepts#tool-calling) API. This API allows developers to build rich applications that enable AI to interact with external services, APIs, and databases. Tool calling can also be used to extract structured information from unstructured data and perform various other tasks. +* [Tool calling](/docs/concepts/tool_calling): Many popular chat models offer a native [tool calling](/docs/concepts/tool_calling) API. This API allows developers to build rich applications that enable AI to interact with external services, APIs, and databases. Tool calling can also be used to extract structured information from unstructured data and perform various other tasks. * [Structured output](/docs/concepts/structured_outputs): A technique to make a chat model respond in a structured format, such as JSON that matches a given schema. * [Multimodality](/docs/concepts/multimodality): The ability to work with data other than text; for example, images, audio, and video. @@ -18,11 +18,11 @@ LangChain provides a consistent interface for working with chat models from diff * Integrations with many chat model providers (e.g., Anthropic, OpenAI, Ollama, Microsoft Azure, Google Vertex, Amazon Bedrock, Hugging Face, Cohere, Groq). Please see [chat model integrations](/docs/integrations/chat/) for an up-to-date list of supported models. * Use either LangChain's [messages](/docs/concepts/messages) format or OpenAI format. -* Standard [tool calling API](/docs/concepts#tool-calling): standard interface for binding tools to models, accessing tool call requests made by models, and sending tool results back to the model. +* Standard [tool calling API](/docs/concepts/tool_calling): standard interface for binding tools to models, accessing tool call requests made by models, and sending tool results back to the model. * Standard API for structuring outputs (/docs/concepts/structured_outputs) via the `with_structured_output` method. -* Provides support for [async programming](/docs/concepts/async), [efficient batching](/docs/concepts/runnables#batch), [a rich streaming API](/docs/concepts/streaming). +* Provides support for [async programming](/docs/concepts/async), [efficient batching](/docs/concepts/runnables/#optimized-parallel-execution-batch), [a rich streaming API](/docs/concepts/streaming). * Integration with [LangSmith](https://docs.smith.langchain.com) for monitoring and debugging production-grade applications based on LLMs. -* Additional features like standardized [token usage](/docs/concepts/messages#token_usage), [rate limiting](#rate-limiting), [caching](#cache) and more. +* Additional features like standardized [token usage](/docs/concepts/messages/#aimessage), [rate limiting](#rate-limiting), [caching](#caching) and more. ## Integrations @@ -44,7 +44,7 @@ Models that do **not** include the prefix "Chat" in their name or include "LLM" ## Interface -LangChain chat models implement the [BaseChatModel](https://python.langchain.com/api_reference/core/language_models/langchain_core.language_models.chat_models.BaseChatModel.html) interface. Because [BaseChatModel] also implements the [Runnable Interface](/docs/concepts/runnables), chat models support a [standard streaming interface](/docs/concepts/streaming), [async programming](/docs/concepts/async), optimized [batching](/docs/concepts/runnables#batch), and more. Please see the [Runnable Interface](/docs/concepts/runnables) for more details. +LangChain chat models implement the [BaseChatModel](https://python.langchain.com/api_reference/core/language_models/langchain_core.language_models.chat_models.BaseChatModel.html) interface. Because [BaseChatModel] also implements the [Runnable Interface](/docs/concepts/runnables), chat models support a [standard streaming interface](/docs/concepts/streaming), [async programming](/docs/concepts/async), optimized [batching](/docs/concepts/runnables/#optimized-parallel-execution-batch), and more. Please see the [Runnable Interface](/docs/concepts/runnables) for more details. Many of the key methods of chat models operate on [messages](/docs/concepts/messages) as input and return messages as output. @@ -65,7 +65,7 @@ The key methods of a chat model are: 2. **stream**: A method that allows you to stream the output of a chat model as it is generated. 3. **batch**: A method that allows you to batch multiple requests to a chat model together for more efficient processing. 4. **bind_tools**: A method that allows you to bind a tool to a chat model for use in the model's execution context. -5. **with_structured_output**: A wrapper around the `invoke` method for models that natively support [structured output](/docs/concepts#structured_output). +5. **with_structured_output**: A wrapper around the `invoke` method for models that natively support [structured output](/docs/concepts/structured_outputs). Other important methods can be found in the [BaseChatModel API Reference](https://python.langchain.com/api_reference/core/language_models/langchain_core.language_models.chat_models.BaseChatModel.html). @@ -104,13 +104,13 @@ ChatModels also accept other parameters that are specific to that integration. T ## Tool calling Chat models can call [tools](/docs/concepts/tools) to perform tasks such as fetching data from a database, making API requests, or running custom code. Please -see the [tool calling](/docs/concepts#tool-calling) guide for more information. +see the [tool calling](/docs/concepts/tool_calling) guide for more information. ## Structured outputs Chat models can be requested to respond in a particular format (e.g., JSON or matching a particular schema). This feature is extremely useful for information extraction tasks. Please read more about -the technique in the [structured outputs](/docs/concepts#structured_output) guide. +the technique in the [structured outputs](/docs/concepts/structured_outputs) guide. ## Multimodality @@ -152,7 +152,7 @@ A semantic cache introduces a dependency on another model on the critical path o However, there might be situations where caching chat model responses is beneficial. For example, if you have a chat model that is used to answer frequently asked questions, caching responses can help reduce the load on the model provider and improve response times. -Please see the [how to cache chat model responses](/docs/how_to/#chat-model-caching) guide for more details. +Please see the [how to cache chat model responses](/docs/how_to/chat_model_caching/) guide for more details. ## Related resources @@ -162,7 +162,7 @@ Please see the [how to cache chat model responses](/docs/how_to/#chat-model-cach ### Conceptual guides * [Messages](/docs/concepts/messages) -* [Tool calling](/docs/concepts#tool-calling) +* [Tool calling](/docs/concepts/tool_calling) * [Multimodality](/docs/concepts/multimodality) -* [Structured outputs](/docs/concepts#structured_output) -* [Tokens](/docs/concepts/tokens) \ No newline at end of file +* [Structured outputs](/docs/concepts/structured_outputs) +* [Tokens](/docs/concepts/tokens) diff --git a/docs/docs/concepts/index.mdx b/docs/docs/concepts/index.mdx index 689db4b06a394..cd7339daa6367 100644 --- a/docs/docs/concepts/index.mdx +++ b/docs/docs/concepts/index.mdx @@ -45,22 +45,22 @@ The conceptual guide does not cover step-by-step instructions or specific implem - **[AIMessageChunk](/docs/concepts/messages#aimessagechunk)**: A partial response from an AI message. Used when streaming responses from a chat model. - **[AIMessage](/docs/concepts/messages#aimessage)**: Represents a complete response from an AI model. - **[astream_events](/docs/concepts/chat_models#key-methods)**: Stream granular information from [LCEL](/docs/concepts/lcel) chains. -- **[BaseTool](/docs/concepts/tools#basetool)**: The base class for all tools in LangChain. +- **[BaseTool](/docs/concepts/tools/#tool-interface)**: The base class for all tools in LangChain. - **[batch](/docs/concepts/runnables)**: Use to execute a runnable with batch inputs a Runnable. -- **[bind_tools](/docs/concepts/chat_models#bind-tools)**: Allows models to interact with tools. +- **[bind_tools](/docs/concepts/tool_calling/#tool-binding)**: Allows models to interact with tools. - **[Caching](/docs/concepts/chat_models#caching)**: Storing results to avoid redundant calls to a chat model. -- **[Chat models](/docs/concepts/multimodality#chat-models)**: Chat models that handle multiple data modalities. -- **[Configurable runnables](/docs/concepts/runnables#configurable-Runnables)**: Creating configurable Runnables. +- **[Chat models](/docs/concepts/multimodality/#multimodality-in-chat-models)**: Chat models that handle multiple data modalities. +- **[Configurable runnables](/docs/concepts/runnables/#configurable-runnables)**: Creating configurable Runnables. - **[Context window](/docs/concepts/chat_models#context-window)**: The maximum size of input a chat model can process. - **[Conversation patterns](/docs/concepts/chat_history#conversation-patterns)**: Common patterns in chat interactions. - **[Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html)**: LangChain's representation of a document. -- **[Embedding models](/docs/concepts/multimodality#embedding-models)**: Models that generate vector embeddings for various data types. +- **[Embedding models](/docs/concepts/multimodality/#multimodality-in-embedding-models)**: Models that generate vector embeddings for various data types. - **[HumanMessage](/docs/concepts/messages#humanmessage)**: Represents a message from a human user. - **[InjectedState](/docs/concepts/tools#injectedstate)**: A state injected into a tool function. - **[InjectedStore](/docs/concepts/tools#injectedstore)**: A store that can be injected into a tool for data persistence. - **[InjectedToolArg](/docs/concepts/tools#injectedtoolarg)**: Mechanism to inject arguments into tool functions. - **[input and output types](/docs/concepts/runnables#input-and-output-types)**: Types used for input and output in Runnables. -- **[Integration packages](/docs/concepts/architecture#partner-packages)**: Third-party packages that integrate with LangChain. +- **[Integration packages](/docs/concepts/architecture/#integration-packages)**: Third-party packages that integrate with LangChain. - **[invoke](/docs/concepts/runnables)**: A standard method to invoke a Runnable. - **[JSON mode](/docs/concepts/structured_outputs#json-mode)**: Returning responses in JSON format. - **[langchain-community](/docs/concepts/architecture#langchain-community)**: Community-driven components for LangChain. @@ -70,20 +70,20 @@ The conceptual guide does not cover step-by-step instructions or specific implem - **[langserve](/docs/concepts/architecture#langserve)**: Use to deploy LangChain Runnables as REST endpoints. Uses FastAPI. Works primarily for LangChain Runnables, does not currently integrate with LangGraph. - **[Managing chat history](/docs/concepts/chat_history#managing-chat-history)**: Techniques to maintain and manage the chat history. - **[OpenAI format](/docs/concepts/messages#openai-format)**: OpenAI's message format for chat models. -- **[Propagation of RunnableConfig](/docs/concepts/runnables#propagation-RunnableConfig)**: Propagating configuration through Runnables. Read if working with python 3.9, 3.10 and async. +- **[Propagation of RunnableConfig](/docs/concepts/runnables/#propagation-of-runnableconfig)**: Propagating configuration through Runnables. Read if working with python 3.9, 3.10 and async. - **[rate-limiting](/docs/concepts/chat_models#rate-limiting)**: Client side rate limiting for chat models. -- **[RemoveMessage](/docs/concepts/messages#remove-message)**: An abstraction used to remove a message from chat history, used primarily in LangGraph. +- **[RemoveMessage](/docs/concepts/messages/#removemessage)**: An abstraction used to remove a message from chat history, used primarily in LangGraph. - **[role](/docs/concepts/messages#role)**: Represents the role (e.g., user, assistant) of a chat message. -- **[RunnableConfig](/docs/concepts/runnables#RunnableConfig)**: Use to pass run time information to Runnables (e.g., `run_name`, `run_id`, `tags`, `metadata`, `max_concurrency`, `recursion_limit`, `configurable`). +- **[RunnableConfig](/docs/concepts/runnables/#runnableconfig)**: Use to pass run time information to Runnables (e.g., `run_name`, `run_id`, `tags`, `metadata`, `max_concurrency`, `recursion_limit`, `configurable`). - **[Standard parameters for chat models](/docs/concepts/chat_models#standard-parameters)**: Parameters such as API key, `temperature`, and `max_tokens`, - **[stream](/docs/concepts/streaming)**: Use to stream output from a Runnable or a graph. - **[Tokenization](/docs/concepts/tokens)**: The process of converting data into tokens and vice versa. - **[Tokens](/docs/concepts/tokens)**: The basic unit that a language model reads, processes, and generates under the hood. - **[Tool artifacts](/docs/concepts/tools#tool-artifacts)**: Add artifacts to the output of a tool that will not be sent to the model, but will be available for downstream processing. - **[Tool binding](/docs/concepts/tool_calling#tool-binding)**: Binding tools to models. -- **[@tool](/docs/concepts/tools#@tool)**: Decorator for creating tools in LangChain. +- **[@tool](/docs/concepts/tools/#create-tools-using-the-tool-decorator)**: Decorator for creating tools in LangChain. - **[Toolkits](/docs/concepts/tools#toolkits)**: A collection of tools that can be used together. - **[ToolMessage](/docs/concepts/messages#toolmessage)**: Represents a message that contains the results of a tool execution. - **[Vector stores](/docs/concepts/vectorstores)**: Datastores specialized for storing and efficiently searching vector embeddings. -- **[with_structured_output](/docs/concepts/chat_models#with-structured-output)**: A helper method for chat models that natively support [tool calling](/docs/concepts/tool_calling) to get structured output matching a given schema specified via Pydantic, JSON schema or a function. +- **[with_structured_output](/docs/concepts/structured_outputs/#structured-output-method)**: A helper method for chat models that natively support [tool calling](/docs/concepts/tool_calling) to get structured output matching a given schema specified via Pydantic, JSON schema or a function. - **[with_types](/docs/concepts/runnables#with_types)**: Method to overwrite the input and output types of a runnable. Useful when working with complex LCEL chains and deploying with LangServe. diff --git a/docs/docs/concepts/lcel.mdx b/docs/docs/concepts/lcel.mdx index 32da281ec1c2e..020bc6f8aa1ed 100644 --- a/docs/docs/concepts/lcel.mdx +++ b/docs/docs/concepts/lcel.mdx @@ -20,8 +20,8 @@ We often refer to a `Runnable` created using LCEL as a "chain". It's important t LangChain optimizes the run-time execution of chains built with LCEL in a number of ways: -- **Optimize parallel execution**: Run Runnables in parallel using [RunnableParallel](#RunnableParallel) or run multiple inputs through a given chain in parallel using the [Runnable Batch API](/docs/concepts/runnables#batch). Parallel execution can significantly reduce the latency as processing can be done in parallel instead of sequentially. -- **Guarantee Async support**: Any chain built with LCEL can be run asynchronously using the [Runnable Async API](/docs/concepts/runnables#async-api). This can be useful when running chains in a server environment where you want to handle large number of requests concurrently. +- **Optimize parallel execution**: Run Runnables in parallel using [RunnableParallel](#runnableparallel) or run multiple inputs through a given chain in parallel using the [Runnable Batch API](/docs/concepts/runnables/#optimized-parallel-execution-batch). Parallel execution can significantly reduce the latency as processing can be done in parallel instead of sequentially. +- **Guarantee Async support**: Any chain built with LCEL can be run asynchronously using the [Runnable Async API](/docs/concepts/runnables/#asynchronous-support). This can be useful when running chains in a server environment where you want to handle large number of requests concurrently. - **Simplify streaming**: LCEL chains can be streamed, allowing for incremental output as the chain is executed. LangChain can optimize the streaming of the output to minimize the time-to-first-token(time elapsed until the first chunk of output from a [chat model](/docs/concepts/chat_models) or [llm](/docs/concepts/text_llms) comes out). Other benefits include: diff --git a/docs/docs/concepts/runnables.mdx b/docs/docs/concepts/runnables.mdx index 4a383e623a3e5..961942c67d92f 100644 --- a/docs/docs/concepts/runnables.mdx +++ b/docs/docs/concepts/runnables.mdx @@ -15,7 +15,7 @@ This guide covers the main concepts and methods of the Runnable interface, which The Runnable way defines a standard interface that allows a Runnable component to be: * [Invoked](/docs/how_to/lcel_cheatsheet/#invoke-a-runnable): A single input is transformed into an output. -* [Batched](/docs/how_to/lcel_cheatsheet/#batch-a-runnable/): Multiple inputs are efficiently transformed into outputs. +* [Batched](/docs/how_to/lcel_cheatsheet/#batch-a-runnable): Multiple inputs are efficiently transformed into outputs. * [Streamed](/docs/how_to/lcel_cheatsheet/#stream-a-runnable): Outputs are streamed as they are produced. * Inspected: Schematic information about Runnable's input, output, and configuration can be accessed. * Composed: Multiple Runnables can be composed to work together using [the LangChain Expression Language (LCEL)](/docs/concepts/lcel) to create complex pipelines. @@ -46,7 +46,7 @@ The async versions of `abatch` and `abatch_as_completed` these rely on asyncio's ::: :::tip -When processing a large number of inputs using `batch` or `batch_as_completed`, users may want to control the maximum number of parallel calls. This can be done by setting the `max_concurrency` attribute in the `RunnableConfig` dictionary. See the [RunnableConfig](/docs/concepts/runnables#RunnableConfig) for more information. +When processing a large number of inputs using `batch` or `batch_as_completed`, users may want to control the maximum number of parallel calls. This can be done by setting the `max_concurrency` attribute in the `RunnableConfig` dictionary. See the [RunnableConfig](/docs/concepts/runnables/#runnableconfig) for more information. Chat Models also have a built-in [rate limiter](/docs/concepts/chat_models#rate-limiting) that can be used to control the rate at which requests are made. ::: @@ -312,7 +312,7 @@ Please read the [Callbacks Conceptual Guide](/docs/concepts/callbacks) for more :::important If you're using Python 3.9 or 3.10 in an async environment, you must propagate the `RunnableConfig` manually to sub-calls in some cases. Please see the -[Propagating RunnableConfig](#propagation-of-RunnableConfig) section for more information. +[Propagating RunnableConfig](#propagation-of-runnableconfig) section for more information. ::: ## Creating a runnable from a function diff --git a/docs/docs/concepts/tools.mdx b/docs/docs/concepts/tools.mdx index 5c079808bd65f..13bf00d43f4f0 100644 --- a/docs/docs/concepts/tools.mdx +++ b/docs/docs/concepts/tools.mdx @@ -141,7 +141,7 @@ See [how to pass run time values to tools](/docs/how_to/tool_runtime/) for more You can use the `RunnableConfig` object to pass custom run time values to tools. -If you need to access the [RunnableConfig](/docs/concepts/runnables/#RunnableConfig) object from within a tool. This can be done by using the `RunnableConfig` annotation in the tool's function signature. +If you need to access the [RunnableConfig](/docs/concepts/runnables/#runnableconfig) object from within a tool. This can be done by using the `RunnableConfig` annotation in the tool's function signature. ```python from langchain_core.runnables import RunnableConfig @@ -160,7 +160,7 @@ The `config` will not be part of the tool's schema and will be injected at runti :::note You may need to access the `config` object to manually propagate it to subclass. This happens if you're working with python 3.9 / 3.10 in an [async](/docs/concepts/async) environment and need to manually propagate the `config` object to sub-calls. -Please read [Propagation RunnableConfig](/docs/concepts/runnables#propagation-RunnableConfig) for more details to learn how to propagate the `RunnableConfig` down the call chain manually (or upgrade to Python 3.11 where this is no longer an issue). +Please read [Propagation RunnableConfig](/docs/concepts/runnables/#propagation-of-runnableconfig) for more details to learn how to propagate the `RunnableConfig` down the call chain manually (or upgrade to Python 3.11 where this is no longer an issue). ::: ### InjectedState diff --git a/docs/docs/concepts/vectorstores.mdx b/docs/docs/concepts/vectorstores.mdx index a42ccf45a4118..aa5bcae7a2cd4 100644 --- a/docs/docs/concepts/vectorstores.mdx +++ b/docs/docs/concepts/vectorstores.mdx @@ -186,6 +186,6 @@ See this [how-to guide on hybrid search](/docs/how_to/hybrid/) for more details. | Name | When to use | Description | |-------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------| | [Hybrid search](/docs/integrations/retrievers/pinecone_hybrid_search/) | When combining keyword-based and semantic similarity. | Hybrid search combines keyword and semantic similarity, marrying the benefits of both approaches. [Paper](https://arxiv.org/abs/2210.11934). | -| [Maximal Marginal Relevance (MMR)](/docs/integrations/vectorstores/pinecone/#maximal-marginal-relevance-searches) | When needing to diversify search results. | MMR attempts to diversify the results of a search to avoid returning similar and redundant documents. | +| [Maximal Marginal Relevance (MMR)](https://python.langchain.com/api_reference/pinecone/vectorstores/langchain_pinecone.vectorstores.PineconeVectorStore.html#langchain_pinecone.vectorstores.PineconeVectorStore.max_marginal_relevance_search) | When needing to diversify search results. | MMR attempts to diversify the results of a search to avoid returning similar and redundant documents. | diff --git a/docs/docs/concepts/why_langchain.mdx b/docs/docs/concepts/why_langchain.mdx index 1eae06eea3705..c6b1d41da3f5d 100644 --- a/docs/docs/concepts/why_langchain.mdx +++ b/docs/docs/concepts/why_langchain.mdx @@ -102,7 +102,7 @@ See our video playlist on [LangSmith tracing and evaluations](https://youtube.co LangChain offers standard interfaces for components that are central to many AI applications, which offers a few specific advantages: - **Ease of swapping providers:** It allows you to swap out different component providers without having to change the underlying code. -- **Advanced features:** It provides common methods for more advanced features, such as [streaming](/docs/concepts/runnables/#streaming) and [tool calling](/docs/concepts/tool_calling/). +- **Advanced features:** It provides common methods for more advanced features, such as [streaming](/docs/concepts/streaming) and [tool calling](/docs/concepts/tool_calling/). [LangGraph](https://langchain-ai.github.io/langgraph/concepts/high_level/) makes it possible to orchestrate complex applications (e.g., [agents](/docs/concepts/agents/)) and provide features like including [persistence](https://langchain-ai.github.io/langgraph/concepts/persistence/), [human-in-the-loop](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/), or [memory](https://langchain-ai.github.io/langgraph/concepts/memory/). diff --git a/docs/docs/how_to/MultiQueryRetriever.ipynb b/docs/docs/how_to/MultiQueryRetriever.ipynb index 4b093af87dba9..d27cca7eaa2a6 100644 --- a/docs/docs/how_to/MultiQueryRetriever.ipynb +++ b/docs/docs/how_to/MultiQueryRetriever.ipynb @@ -164,7 +164,7 @@ "Under the hood, `MultiQueryRetriever` generates queries using a specific [prompt](https://python.langchain.com/api_reference/langchain/retrievers/langchain.retrievers.multi_query.MultiQueryRetriever.html). To customize this prompt:\n", "\n", "1. Make a [PromptTemplate](https://python.langchain.com/api_reference/core/prompts/langchain_core.prompts.prompt.PromptTemplate.html) with an input variable for the question;\n", - "2. Implement an [output parser](/docs/concepts#output-parsers) like the one below to split the result into a list of queries.\n", + "2. Implement an [output parser](/docs/concepts/output_parsers) like the one below to split the result into a list of queries.\n", "\n", "The prompt and output parser together must support the generation of a list of queries." ] diff --git a/docs/docs/how_to/agent_executor.ipynb b/docs/docs/how_to/agent_executor.ipynb index 647e4c6a1176a..1c357632630cd 100644 --- a/docs/docs/how_to/agent_executor.ipynb +++ b/docs/docs/how_to/agent_executor.ipynb @@ -18,7 +18,7 @@ "# Build an Agent with AgentExecutor (Legacy)\n", "\n", ":::important\n", - "This section will cover building with the legacy LangChain AgentExecutor. These are fine for getting started, but past a certain point, you will likely want flexibility and control that they do not offer. For working with more advanced agents, we'd recommend checking out [LangGraph Agents](/docs/concepts/#langgraph) or the [migration guide](/docs/how_to/migrate_agent/)\n", + "This section will cover building with the legacy LangChain AgentExecutor. These are fine for getting started, but past a certain point, you will likely want flexibility and control that they do not offer. For working with more advanced agents, we'd recommend checking out [LangGraph Agents](/docs/concepts/architecture/#langgraph) or the [migration guide](/docs/how_to/migrate_agent/)\n", ":::\n", "\n", "By themselves, language models can't take actions - they just output text.\n", @@ -802,7 +802,7 @@ "That's a wrap! In this quick start we covered how to create a simple agent. Agents are a complex topic, and there's lot to learn! \n", "\n", ":::important\n", - "This section covered building with LangChain Agents. LangChain Agents are fine for getting started, but past a certain point you will likely want flexibility and control that they do not offer. For working with more advanced agents, we'd reccommend checking out [LangGraph](/docs/concepts/#langgraph)\n", + "This section covered building with LangChain Agents. LangChain Agents are fine for getting started, but past a certain point you will likely want flexibility and control that they do not offer. For working with more advanced agents, we'd reccommend checking out [LangGraph](/docs/concepts/architecture/#langgraph)\n", ":::\n", "\n", "If you want to continue using LangChain agents, some good advanced guides are:\n", diff --git a/docs/docs/how_to/chat_token_usage_tracking.ipynb b/docs/docs/how_to/chat_token_usage_tracking.ipynb index c26aa1100911a..cdcf943e84365 100644 --- a/docs/docs/how_to/chat_token_usage_tracking.ipynb +++ b/docs/docs/how_to/chat_token_usage_tracking.ipynb @@ -261,7 +261,7 @@ "id": "6a5d9617-be3a-419a-9276-de9c29fa50ae", "metadata": {}, "source": [ - "You can also enable streaming token usage by setting `stream_usage` when instantiating the chat model. This can be useful when incorporating chat models into LangChain [chains](/docs/concepts#langchain-expression-language-lcel): usage metadata can be monitored when [streaming intermediate steps](/docs/how_to/streaming#using-stream-events) or using tracing software such as [LangSmith](https://docs.smith.langchain.com/).\n", + "You can also enable streaming token usage by setting `stream_usage` when instantiating the chat model. This can be useful when incorporating chat models into LangChain [chains](/docs/concepts/lcel): usage metadata can be monitored when [streaming intermediate steps](/docs/how_to/streaming#using-stream-events) or using tracing software such as [LangSmith](https://docs.smith.langchain.com/).\n", "\n", "See the below example, where we return output structured to a desired schema, but can still observe token usage streamed from intermediate steps." ] diff --git a/docs/docs/how_to/convert_runnable_to_tool.ipynb b/docs/docs/how_to/convert_runnable_to_tool.ipynb index 525fb769bbb3e..0cee498715a22 100644 --- a/docs/docs/how_to/convert_runnable_to_tool.ipynb +++ b/docs/docs/how_to/convert_runnable_to_tool.ipynb @@ -11,8 +11,8 @@ "\n", "This guide assumes familiarity with the following concepts:\n", "\n", - "- [Runnables](/docs/concepts#runnable-interface)\n", - "- [Tools](/docs/concepts#tools)\n", + "- [Runnables](/docs/concepts/runnables)\n", + "- [Tools](/docs/concepts/tools)\n", "- [Agents](/docs/tutorials/agents)\n", "\n", ":::\n", @@ -40,7 +40,7 @@ "id": "2b0dcc1a-48e8-4a81-b920-3563192ce076", "metadata": {}, "source": [ - "LangChain [tools](/docs/concepts#tools) are interfaces that an agent, chain, or chat model can use to interact with the world. See [here](/docs/how_to/#tools) for how-to guides covering tool-calling, built-in tools, custom tools, and more information.\n", + "LangChain [tools](/docs/concepts/tools) are interfaces that an agent, chain, or chat model can use to interact with the world. See [here](/docs/how_to/#tools) for how-to guides covering tool-calling, built-in tools, custom tools, and more information.\n", "\n", "LangChain tools-- instances of [BaseTool](https://python.langchain.com/api_reference/core/tools/langchain_core.tools.BaseTool.html)-- are [Runnables](/docs/concepts/runnables) with additional constraints that enable them to be invoked effectively by language models:\n", "\n", diff --git a/docs/docs/how_to/custom_retriever.ipynb b/docs/docs/how_to/custom_retriever.ipynb index 66939e2e569a5..31600dcf73fce 100644 --- a/docs/docs/how_to/custom_retriever.ipynb +++ b/docs/docs/how_to/custom_retriever.ipynb @@ -38,7 +38,7 @@ "The logic inside of `_get_relevant_documents` can involve arbitrary calls to a database or to the web using requests.\n", "\n", ":::tip\n", - "By inherting from `BaseRetriever`, your retriever automatically becomes a LangChain [Runnable](/docs/concepts#interface) and will gain the standard `Runnable` functionality out of the box!\n", + "By inherting from `BaseRetriever`, your retriever automatically becomes a LangChain [Runnable](/docs/concepts/runnables) and will gain the standard `Runnable` functionality out of the box!\n", ":::\n", "\n", "\n", diff --git a/docs/docs/how_to/custom_tools.ipynb b/docs/docs/how_to/custom_tools.ipynb index 487af8d5260d1..4be054e86c9b5 100644 --- a/docs/docs/how_to/custom_tools.ipynb +++ b/docs/docs/how_to/custom_tools.ipynb @@ -19,7 +19,7 @@ "LangChain supports the creation of tools from:\n", "\n", "1. Functions;\n", - "2. LangChain [Runnables](/docs/concepts#runnable-interface);\n", + "2. LangChain [Runnables](/docs/concepts/runnables);\n", "3. By sub-classing from [BaseTool](https://python.langchain.com/api_reference/core/tools/langchain_core.tools.BaseTool.html) -- This is the most flexible method, it provides the largest degree of control, at the expense of more effort and code.\n", "\n", "Creating tools from functions may be sufficient for most use cases, and can be done via a simple [@tool decorator](https://python.langchain.com/api_reference/core/tools/langchain_core.tools.tool.html#langchain_core.tools.tool). If more configuration is needed-- e.g., specification of both sync and async implementations-- one can also use the [StructuredTool.from_function](https://python.langchain.com/api_reference/core/tools/langchain_core.tools.structured.StructuredTool.html#langchain_core.tools.structured.StructuredTool.from_function) class method.\n", @@ -415,7 +415,7 @@ "source": [ "## Creating tools from Runnables\n", "\n", - "LangChain [Runnables](/docs/concepts#runnable-interface) that accept string or `dict` input can be converted to tools using the [as_tool](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.as_tool) method, which allows for the specification of names, descriptions, and additional schema information for arguments.\n", + "LangChain [Runnables](/docs/concepts/runnables) that accept string or `dict` input can be converted to tools using the [as_tool](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.as_tool) method, which allows for the specification of names, descriptions, and additional schema information for arguments.\n", "\n", "Example usage:" ] diff --git a/docs/docs/how_to/document_loader_csv.ipynb b/docs/docs/how_to/document_loader_csv.ipynb index ebab8d287a1f1..fa2b5f77165eb 100644 --- a/docs/docs/how_to/document_loader_csv.ipynb +++ b/docs/docs/how_to/document_loader_csv.ipynb @@ -157,7 +157,7 @@ " temp_file_path = temp_file.name\n", "\n", "loader = CSVLoader(file_path=temp_file_path)\n", - "loader.load()\n", + "data = loader.load()\n", "for record in data[:2]:\n", " print(record)" ] diff --git a/docs/docs/how_to/extraction_examples.ipynb b/docs/docs/how_to/extraction_examples.ipynb index 764e801f39ca4..3de5417d5fbd4 100644 --- a/docs/docs/how_to/extraction_examples.ipynb +++ b/docs/docs/how_to/extraction_examples.ipynb @@ -9,7 +9,7 @@ "\n", "The quality of extractions can often be improved by providing reference examples to the LLM.\n", "\n", - "Data extraction attempts to generate structured representations of information found in text and other unstructured or semi-structured formats. [Tool-calling](/docs/concepts#functiontool-calling) LLM features are often used in this context. This guide demonstrates how to build few-shot examples of tool calls to help steer the behavior of extraction and similar applications.\n", + "Data extraction attempts to generate structured representations of information found in text and other unstructured or semi-structured formats. [Tool-calling](/docs/concepts/tool_calling) LLM features are often used in this context. This guide demonstrates how to build few-shot examples of tool calls to help steer the behavior of extraction and similar applications.\n", "\n", ":::tip\n", "While this guide focuses how to use examples with a tool calling model, this technique is generally applicable, and will work\n", diff --git a/docs/docs/how_to/extraction_parse.ipynb b/docs/docs/how_to/extraction_parse.ipynb index 597c3ad1bd746..8d6c3a1a04173 100644 --- a/docs/docs/how_to/extraction_parse.ipynb +++ b/docs/docs/how_to/extraction_parse.ipynb @@ -14,7 +14,7 @@ "To extract data without tool-calling features: \n", "\n", "1. Instruct the LLM to generate text following an expected format (e.g., JSON with a certain schema);\n", - "2. Use [output parsers](/docs/concepts#output-parsers) to structure the model response into a desired Python object.\n", + "2. Use [output parsers](/docs/concepts/output_parsers) to structure the model response into a desired Python object.\n", "\n", "First we select a LLM:\n", "\n", diff --git a/docs/docs/how_to/output_parser_structured.ipynb b/docs/docs/how_to/output_parser_structured.ipynb index 6a4b91d0bc431..2cb69c7bbb4f6 100644 --- a/docs/docs/how_to/output_parser_structured.ipynb +++ b/docs/docs/how_to/output_parser_structured.ipynb @@ -96,7 +96,7 @@ "source": [ "## LCEL\n", "\n", - "Output parsers implement the [Runnable interface](/docs/concepts#interface), the basic building block of the [LangChain Expression Language (LCEL)](/docs/concepts#langchain-expression-language-lcel). This means they support `invoke`, `ainvoke`, `stream`, `astream`, `batch`, `abatch`, `astream_log` calls.\n", + "Output parsers implement the [Runnable interface](/docs/concepts/runnables), the basic building block of the [LangChain Expression Language (LCEL)](/docs/concepts/lcel). This means they support `invoke`, `ainvoke`, `stream`, `astream`, `batch`, `abatch`, `astream_log` calls.\n", "\n", "Output parsers accept a string or `BaseMessage` as input and can return an arbitrary type." ] diff --git a/docs/docs/how_to/qa_chat_history_how_to.ipynb b/docs/docs/how_to/qa_chat_history_how_to.ipynb index bf0dfb4a84d1d..c3ad3936bec46 100644 --- a/docs/docs/how_to/qa_chat_history_how_to.ipynb +++ b/docs/docs/how_to/qa_chat_history_how_to.ipynb @@ -41,7 +41,7 @@ "\n", "### Dependencies\n", "\n", - "We'll use OpenAI embeddings and an InMemory vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts#embedding-models), and [VectorStore](/docs/concepts#vectorstores) or [Retriever](/docs/concepts#retrievers). \n", + "We'll use OpenAI embeddings and an InMemory vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts/embedding_models), and [VectorStore](/docs/concepts/vectorstores) or [Retriever](/docs/concepts/retrievers). \n", "\n", "We'll use the following packages:" ] @@ -686,7 +686,7 @@ "source": [ "### Agent constructor\n", "\n", - "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/#langgraph) to construct the agent. \n", + "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/architecture/#langgraph) to construct the agent. \n", "Currently we are using a high level interface to construct the agent, but the nice thing about LangGraph is that this high-level interface is backed by a low-level, highly controllable API in case you want to modify the agent logic." ] }, diff --git a/docs/docs/how_to/qa_citations.ipynb b/docs/docs/how_to/qa_citations.ipynb index 50e6e65958f3a..fda1b1f1daac5 100644 --- a/docs/docs/how_to/qa_citations.ipynb +++ b/docs/docs/how_to/qa_citations.ipynb @@ -254,7 +254,7 @@ "source": [ "## Function-calling\n", "\n", - "If your LLM of choice implements a [tool-calling](/docs/concepts#functiontool-calling) feature, you can use it to make the model specify which of the provided documents it's referencing when generating its answer. LangChain tool-calling models implement a `.with_structured_output` method which will force generation adhering to a desired schema (see for example [here](https://python.langchain.com/api_reference/openai/chat_models/langchain_openai.chat_models.base.ChatOpenAI.html#langchain_openai.chat_models.base.ChatOpenAI.with_structured_output)).\n", + "If your LLM of choice implements a [tool-calling](/docs/concepts/tool_calling) feature, you can use it to make the model specify which of the provided documents it's referencing when generating its answer. LangChain tool-calling models implement a `.with_structured_output` method which will force generation adhering to a desired schema (see for example [here](https://python.langchain.com/api_reference/openai/chat_models/langchain_openai.chat_models.base.ChatOpenAI.html#langchain_openai.chat_models.base.ChatOpenAI.with_structured_output)).\n", "\n", "### Cite documents\n", "\n", diff --git a/docs/docs/how_to/qa_sources.ipynb b/docs/docs/how_to/qa_sources.ipynb index f92564cc280a9..c9d9ce7330f6b 100644 --- a/docs/docs/how_to/qa_sources.ipynb +++ b/docs/docs/how_to/qa_sources.ipynb @@ -14,7 +14,7 @@ "We will cover two approaches:\n", "\n", "1. Using the built-in [create_retrieval_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.retrieval.create_retrieval_chain.html), which returns sources by default;\n", - "2. Using a simple [LCEL](/docs/concepts#langchain-expression-language-lcel) implementation, to show the operating principle.\n", + "2. Using a simple [LCEL](/docs/concepts/lcel) implementation, to show the operating principle.\n", "\n", "We will also show how to structure sources into the model response, such that a model can report what specific sources it used in generating its answer." ] @@ -28,7 +28,7 @@ "\n", "### Dependencies\n", "\n", - "We'll use OpenAI embeddings and a Chroma vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts#embedding-models), [VectorStore](/docs/concepts#vectorstores) or [Retriever](/docs/concepts#retrievers). \n", + "We'll use OpenAI embeddings and a Chroma vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts/embedding_models), [VectorStore](/docs/concepts/vectorstores) or [Retriever](/docs/concepts/retrievers). \n", "\n", "We'll use the following packages:" ] diff --git a/docs/docs/how_to/qa_streaming.ipynb b/docs/docs/how_to/qa_streaming.ipynb index b1e1d3c9e5a3e..18e19fbcb9957 100644 --- a/docs/docs/how_to/qa_streaming.ipynb +++ b/docs/docs/how_to/qa_streaming.ipynb @@ -21,7 +21,7 @@ "\n", "### Dependencies\n", "\n", - "We'll use OpenAI embeddings and a Chroma vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts#embedding-models), [VectorStore](/docs/concepts#vectorstores) or [Retriever](/docs/concepts#retrievers). \n", + "We'll use OpenAI embeddings and a Chroma vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts/embedding_models), [VectorStore](/docs/concepts/vectorstores) or [Retriever](/docs/concepts/retrievers). \n", "\n", "We'll use the following packages:" ] diff --git a/docs/docs/how_to/split_by_token.ipynb b/docs/docs/how_to/split_by_token.ipynb index 0d359b50ec2fe..87aad35bc6460 100644 --- a/docs/docs/how_to/split_by_token.ipynb +++ b/docs/docs/how_to/split_by_token.ipynb @@ -27,7 +27,7 @@ "1. How the text is split: by character passed in.\n", "2. How the chunk size is measured: by `tiktoken` tokenizer.\n", "\n", - "[CharacterTextSplitter](https://python.langchain.com/api_reference/text_splitters/character/langchain_text_splitters.character.CharacterTextSplitter.html), [RecursiveCharacterTextSplitter](https://python.langchain.com/api_reference/text_splitters/character/langchain_text_splitters.character.RecursiveCharacterTextSplitter.html), and [TokenTextSplitter](https://python.langchain.com/api_reference/langchain_text_splitters/base/langchain_text_splitters.base.TokenTextSplitter.html) can be used with `tiktoken` directly." + "[CharacterTextSplitter](https://python.langchain.com/api_reference/text_splitters/character/langchain_text_splitters.character.CharacterTextSplitter.html), [RecursiveCharacterTextSplitter](https://python.langchain.com/api_reference/text_splitters/character/langchain_text_splitters.character.RecursiveCharacterTextSplitter.html), and [TokenTextSplitter](https://python.langchain.com/api_reference/text_splitters/base/langchain_text_splitters.base.TokenTextSplitter.html) can be used with `tiktoken` directly." ] }, { diff --git a/docs/docs/how_to/streaming.ipynb b/docs/docs/how_to/streaming.ipynb index 1f7a7d35b7f02..b7be2ed202077 100644 --- a/docs/docs/how_to/streaming.ipynb +++ b/docs/docs/how_to/streaming.ipynb @@ -32,7 +32,7 @@ "\n", "Streaming is critical in making applications based on LLMs feel responsive to end-users.\n", "\n", - "Important LangChain primitives like [chat models](/docs/concepts/chat_models), [output parsers](/docs/concepts/output_parsers), [prompts](/docs/concepts/prompt_templates), [retrievers](/docs/concepts/retrievers), and [agents](/docs/concepts/agents) implement the LangChain [Runnable Interface](/docs/concepts#interface).\n", + "Important LangChain primitives like [chat models](/docs/concepts/chat_models), [output parsers](/docs/concepts/output_parsers), [prompts](/docs/concepts/prompt_templates), [retrievers](/docs/concepts/retrievers), and [agents](/docs/concepts/agents) implement the LangChain [Runnable Interface](/docs/concepts/runnables).\n", "\n", "This interface provides two general approaches to stream content:\n", "\n", diff --git a/docs/docs/how_to/structured_output.ipynb b/docs/docs/how_to/structured_output.ipynb index 3e333e340b1a7..e1d6f2b68e82e 100644 --- a/docs/docs/how_to/structured_output.ipynb +++ b/docs/docs/how_to/structured_output.ipynb @@ -556,7 +556,7 @@ "id": "498d893b-ceaa-47ff-a9d8-4faa60702715", "metadata": {}, "source": [ - "For more on few shot prompting when using tool calling, see [here](/docs/how_to/function_calling/#Few-shot-prompting)." + "For more on few shot prompting when using tool calling, see [here](/docs/how_to/tools_few_shot/)." ] }, { diff --git a/docs/docs/how_to/tools_chain.ipynb b/docs/docs/how_to/tools_chain.ipynb index 78f88c84715ce..b54fa2c885f8f 100644 --- a/docs/docs/how_to/tools_chain.ipynb +++ b/docs/docs/how_to/tools_chain.ipynb @@ -276,7 +276,7 @@ "\n", "Chains are great when we know the specific sequence of tool usage needed for any user input. But for certain use cases, how many times we use tools depends on the input. In these cases, we want to let the model itself decide how many times to use tools and in what order. [Agents](/docs/tutorials/agents) let us do just this.\n", "\n", - "LangChain comes with a number of built-in agents that are optimized for different use cases. Read about all the [agent types here](/docs/concepts#agents).\n", + "LangChain comes with a number of built-in agents that are optimized for different use cases. Read about all the [agent types here](/docs/concepts/agents).\n", "\n", "We'll use the [tool calling agent](https://python.langchain.com/api_reference/langchain/agents/langchain.agents.tool_calling_agent.base.create_tool_calling_agent.html), which is generally the most reliable kind and the recommended one for most use cases.\n", "\n", diff --git a/docs/docs/integrations/chat/cohere.ipynb b/docs/docs/integrations/chat/cohere.ipynb index 7675306c2658f..841d378f88625 100644 --- a/docs/docs/integrations/chat/cohere.ipynb +++ b/docs/docs/integrations/chat/cohere.ipynb @@ -201,7 +201,7 @@ "source": [ "## Chaining\n", "\n", - "You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/concepts#langchain-expression-language-lcel)" + "You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/concepts/lcel)" ] }, { diff --git a/docs/docs/integrations/chat/naver.ipynb b/docs/docs/integrations/chat/naver.ipynb index 64924cb56374a..651eab5872103 100644 --- a/docs/docs/integrations/chat/naver.ipynb +++ b/docs/docs/integrations/chat/naver.ipynb @@ -17,7 +17,7 @@ "source": [ "# ChatClovaX\n", "\n", - "This notebook provides a quick overview for getting started with Naver’s HyperCLOVA X [chat models](https://python.langchain.com/docs/concepts/#chat-models) via CLOVA Studio. For detailed documentation of all ChatClovaX features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.naver.ChatClovaX.html).\n", + "This notebook provides a quick overview for getting started with Naver’s HyperCLOVA X [chat models](https://python.langchain.com/docs/concepts/chat_models) via CLOVA Studio. For detailed documentation of all ChatClovaX features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.naver.ChatClovaX.html).\n", "\n", "[CLOVA Studio](http://clovastudio.ncloud.com/) has several chat models. You can find information about latest models and their costs, context windows, and supported input types in the CLOVA Studio API Guide [documentation](https://api.ncloud-docs.com/docs/clovastudio-chatcompletions).\n", "\n", diff --git a/docs/docs/integrations/chat/writer.ipynb b/docs/docs/integrations/chat/writer.ipynb index 455f8820ca936..a76752ef2f64c 100644 --- a/docs/docs/integrations/chat/writer.ipynb +++ b/docs/docs/integrations/chat/writer.ipynb @@ -17,7 +17,7 @@ "source": [ "# ChatWriter\n", "\n", - "This notebook provides a quick overview for getting started with Writer [chat models](/docs/concepts/#chat-models).\n", + "This notebook provides a quick overview for getting started with Writer [chat models](/docs/concepts/chat_models).\n", "\n", "Writer has several chat models. You can find information about their latest models and their costs, context windows, and supported input types in the [Writer docs](https://dev.writer.com/home/models).\n", "\n", diff --git a/docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb b/docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb new file mode 100644 index 0000000000000..b3dadb1f0ad81 --- /dev/null +++ b/docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb @@ -0,0 +1,192 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Azure OpenAI Whisper Parser" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">[Azure OpenAI Whisper Parser](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/whisper-overview) is a wrapper around the Azure OpenAI Whisper API which utilizes machine learning to transcribe audio files to english text. \n", + ">\n", + ">The Parser supports `.mp3`, `.mp4`, `.mpeg`, `.mpga`, `.m4a`, `.wav`, and `.webm`.\n", + "\n", + "The current implementation follows LangChain core principles and can be used with other loaders to handle both audio downloading and parsing. As a result of this the parser will `yield` an `Iterator[Document]`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prerequisites" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The service requires Azure credentials, Azure endpoint and Whisper Model deployment, which can be set up by following the guide [here](https://learn.microsoft.com/en-us/azure/ai-services/openai/whisper-quickstart?tabs=command-line%2Cpython-new%2Cjavascript&pivots=programming-language-python). Furthermore, the required dependencies must be installed.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%pip install -Uq langchain langchain-community openai" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `AzureOpenAIWhisperParser`'s method, `.lazy_parse`, accepts a `Blob` object as a parameter containing the file path of the file to be transcribed." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_core.documents.base import Blob\n", + "\n", + "audio_path = \"path/to/your/audio/file\"\n", + "audio_blob = Blob(path=audio_path)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_community.document_loaders.parsers.audio import AzureOpenAIWhisperParser\n", + "\n", + "endpoint = \"\"\n", + "key = \"\"\n", + "name = \"\"\n", + "\n", + "parser = AzureOpenAIWhisperParser(\n", + " api_key=key, azure_endpoint=endpoint, api_version=version, deployment_name=name\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "documents = parser.lazy_parse(blob=audio_blob)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for doc in documents:\n", + " print(doc.page_content)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `AzureOpenAIWhisperParser` can also be used in conjuction with audio loaders, like the `YoutubeAudioLoader` with a `GenericLoader`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_community.document_loaders.blob_loaders.youtube_audio import (\n", + " YoutubeAudioLoader,\n", + ")\n", + "from langchain_community.document_loaders.generic import GenericLoader" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Must be a list\n", + "url = [\"www.youtube.url.com\"]\n", + "\n", + "save_dir = \"save/directory/\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "name = \"\"\n", + "\n", + "loader = GenericLoader(\n", + " YoutubeAudioLoader(url, save_dir), AzureOpenAIWhisperParser(deployment_name=name)\n", + ")\n", + "\n", + "docs = loader.load()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for doc in documents:\n", + " print(doc.page_content)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/docs/integrations/document_loaders/tomarkdown.ipynb b/docs/docs/integrations/document_loaders/tomarkdown.ipynb index 2868fde19b81e..ffc41ea4e5f7c 100644 --- a/docs/docs/integrations/document_loaders/tomarkdown.ipynb +++ b/docs/docs/integrations/document_loaders/tomarkdown.ipynb @@ -113,8 +113,8 @@ "\n", "LCEL is a declarative way to compose chains. LCEL was designed from day 1 to support putting prototypes in production, with no code changes, from the simplest “prompt + LLM” chain to the most complex chains.\n", "\n", - "- **[Overview](/docs/concepts#langchain-expression-language-lcel)**: LCEL and its benefits\n", - "- **[Interface](/docs/concepts#interface)**: The standard interface for LCEL objects\n", + "- **[Overview](/docs/concepts/lcel)**: LCEL and its benefits\n", + "- **[Interface](/docs/concepts/runnables)**: The standard interface for LCEL objects\n", "- **[How-to](/docs/expression_language/how_to)**: Key features of LCEL\n", "- **[Cookbook](/docs/expression_language/cookbook)**: Example code for accomplishing common tasks\n", "\n", diff --git a/docs/docs/integrations/graphs/ontotext.ipynb b/docs/docs/integrations/graphs/ontotext.ipynb index 1d67d8c745ca9..7c28d7d2cca49 100644 --- a/docs/docs/integrations/graphs/ontotext.ipynb +++ b/docs/docs/integrations/graphs/ontotext.ipynb @@ -84,16 +84,20 @@ " You need to wait a couple of seconds for the database to start on `http://localhost:7200/`. The Star Wars dataset `starwars-data.trig` is automatically loaded into the `langchain` repository. The local SPARQL endpoint `http://localhost:7200/repositories/langchain` can be used to run queries against. You can also open the GraphDB Workbench from your favourite web browser `http://localhost:7200/sparql` where you can make queries interactively.\n", "* Set up working environment\n", "\n", - "If you use `conda`, create and activate a new conda env (e.g. `conda create -n graph_ontotext_graphdb_qa python=3.9.18`).\n", + "If you use `conda`, create and activate a new conda environment, e.g.:\n", + "\n", + "```\n", + "conda create -n graph_ontotext_graphdb_qa python=3.12\n", + "conda activate graph_ontotext_graphdb_qa\n", + "```\n", "\n", "Install the following libraries:\n", "\n", "```\n", - "pip install jupyter==1.0.0\n", - "pip install openai==1.6.1\n", - "pip install rdflib==7.0.0\n", - "pip install langchain-openai==0.0.2\n", - "pip install langchain>=0.1.5\n", + "pip install jupyter==1.1.1\n", + "pip install rdflib==7.1.1\n", + "pip install langchain-community==0.3.4\n", + "pip install langchain-openai==0.2.4\n", "```\n", "\n", "Run Jupyter with\n", @@ -255,6 +259,7 @@ " ChatOpenAI(temperature=0, model_name=\"gpt-4-1106-preview\"),\n", " graph=graph,\n", " verbose=True,\n", + " allow_dangerous_requests=True,\n", ")" ] }, @@ -332,6 +337,7 @@ "\u001b[32;1m\u001b[1;3mPREFIX : \n", "PREFIX owl: \n", "PREFIX rdfs: \n", + "PREFIX xsd: \n", "\n", "SELECT ?climate\n", "WHERE {\n", @@ -383,11 +389,9 @@ "\u001b[1m> Entering new OntotextGraphDBQAChain chain...\u001b[0m\n", "Generated SPARQL:\n", "\u001b[32;1m\u001b[1;3mPREFIX : \n", - "PREFIX owl: \n", - "PREFIX rdf: \n", "PREFIX xsd: \n", "\n", - "SELECT (AVG(?boxOffice) AS ?averageBoxOffice)\n", + "SELECT (AVG(?boxOffice) AS ?averageBoxOfficeRevenue)\n", "WHERE {\n", " ?film a :Film .\n", " ?film :boxOffice ?boxOfficeValue .\n", @@ -559,7 +563,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.12.7" } }, "nbformat": 4, diff --git a/docs/docs/integrations/llms/cohere.ipynb b/docs/docs/integrations/llms/cohere.ipynb index 9e294f275cf8e..ebf432a98a6dd 100644 --- a/docs/docs/integrations/llms/cohere.ipynb +++ b/docs/docs/integrations/llms/cohere.ipynb @@ -217,7 +217,7 @@ "source": [ "## Chaining\n", "\n", - "You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/concepts#langchain-expression-language-lcel)" + "You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/concepts/lcel)" ] }, { diff --git a/docs/docs/integrations/llms/google_vertex_ai_palm.ipynb b/docs/docs/integrations/llms/google_vertex_ai_palm.ipynb index 8322e6d780cec..624189296e889 100644 --- a/docs/docs/integrations/llms/google_vertex_ai_palm.ipynb +++ b/docs/docs/integrations/llms/google_vertex_ai_palm.ipynb @@ -335,7 +335,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/concepts#langchain-expression-language-lcel)" + "You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/concepts/lcel)" ] }, { diff --git a/docs/docs/integrations/llms/llamafile.ipynb b/docs/docs/integrations/llms/llamafile.ipynb index 3570c8c3c5ba2..21e7b33ef8bc3 100644 --- a/docs/docs/integrations/llms/llamafile.ipynb +++ b/docs/docs/integrations/llms/llamafile.ipynb @@ -105,7 +105,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "To learn more about the LangChain Expressive Language and the available methods on an LLM, see the [LCEL Interface](/docs/concepts#interface)" + "To learn more about the LangChain Expressive Language and the available methods on an LLM, see the [LCEL Interface](/docs/concepts/runnables)" ] } ], diff --git a/docs/docs/integrations/llms/sambastudio.ipynb b/docs/docs/integrations/llms/sambastudio.ipynb index dd977f37c9532..a173842df8ede 100644 --- a/docs/docs/integrations/llms/sambastudio.ipynb +++ b/docs/docs/integrations/llms/sambastudio.ipynb @@ -9,7 +9,7 @@ "**[SambaNova](https://sambanova.ai/)'s** [Sambastudio](https://sambanova.ai/technology/full-stack-ai-platform) is a platform that allows you to train, run batch inference jobs, and deploy online inference endpoints to run open source models that you fine tuned yourself.\n", "\n", ":::caution\n", - "You are currently on a page documenting the use of SambaStudio models as [text completion models](/docs/concepts/#llms). We recommend you to use the [chat completion models](/docs/concepts/#chat-models).\n", + "You are currently on a page documenting the use of SambaStudio models as [text completion models](/docs/concepts/text_llms). We recommend you to use the [chat completion models](/docs/concepts/chat_models).\n", "\n", "You may be looking for [SambaStudio Chat Models](/docs/integrations/chat/sambastudio/) .\n", ":::\n", diff --git a/docs/docs/integrations/llms/vllm.ipynb b/docs/docs/integrations/llms/vllm.ipynb index 6d45b102dc1ac..1e1baff963161 100644 --- a/docs/docs/integrations/llms/vllm.ipynb +++ b/docs/docs/integrations/llms/vllm.ipynb @@ -246,6 +246,35 @@ ")\n", "print(llm.invoke(\"Rome is\"))" ] + }, + { + "cell_type": "markdown", + "id": "bd3f0f51", + "metadata": {}, + "source": [ + "## LoRA adapter\n", + "LoRA adapters can be used with any vLLM model that implements `SupportsLoRA`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2682ca6c", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_community.llms import VLLM\n", + "from vllm.lora.request import LoRARequest\n", + "\n", + "llm = VLLM(model=\"meta-llama/Llama-2-7b-hf\", enable_lora=True)\n", + "\n", + "LoRA_ADAPTER_PATH = \"path/to/adapter\"\n", + "lora_adapter = LoRARequest(\"lora_adapter\", 1, LoRA_ADAPTER_PATH)\n", + "\n", + "print(\n", + " llm.invoke(\"What are some popular Korean street foods?\", lora_request=lora_adapter)\n", + ")" + ] } ], "metadata": { diff --git a/docs/docs/integrations/providers/databricks.md b/docs/docs/integrations/providers/databricks.md index 54a10c7c6a62c..a45e8e3e03eb2 100644 --- a/docs/docs/integrations/providers/databricks.md +++ b/docs/docs/integrations/providers/databricks.md @@ -14,23 +14,13 @@ Databricks embraces the LangChain ecosystem in various ways: Installation ------------ -First-party Databricks integrations are available in the langchain-databricks partner package. +First-party Databricks integrations are now available in the databricks-langchain partner package. ``` -pip install langchain-databricks +pip install databricks-langchain ``` -🚧 Upcoming Package Consolidation Notice - -This package (`langchain-databricks`) will soon be consolidated into a new package: `databricks-langchain`. The new package will serve as the primary hub for all Databricks Langchain integrations. - -What’s Changing? -In the coming months, `databricks-langchain` will include all features currently in `langchain-databricks`, as well as additional integrations to provide a unified experience for Databricks users. - -What You Need to Know -For now, continue to use `langchain-databricks` as usual. When `databricks-langchain` is ready, we’ll provide clear migration instructions to make the transition seamless. During the transition period, `langchain-databricks` will remain operational, and updates will be shared here with timelines and guidance. - -Thank you for your support as we work toward an improved, streamlined experience! +The legacy langchain-databricks partner package is still available but will be soon deprecated. Chat Model ---------- @@ -38,7 +28,7 @@ Chat Model `ChatDatabricks` is a Chat Model class to access chat endpoints hosted on Databricks, including state-of-the-art models such as Llama3, Mixtral, and DBRX, as well as your own fine-tuned models. ``` -from langchain_databricks import ChatDatabricks +from databricks_langchain import ChatDatabricks chat_model = ChatDatabricks(endpoint="databricks-meta-llama-3-70b-instruct") ``` @@ -69,7 +59,7 @@ Embeddings `DatabricksEmbeddings` is an Embeddings class to access text-embedding endpoints hosted on Databricks, including state-of-the-art models such as BGE, as well as your own fine-tuned models. ``` -from langchain_databricks import DatabricksEmbeddings +from databricks_langchain import DatabricksEmbeddings embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") ``` @@ -83,7 +73,7 @@ Vector Search Databricks Vector Search is a serverless similarity search engine that allows you to store a vector representation of your data, including metadata, in a vector database. With Vector Search, you can create auto-updating vector search indexes from [Delta](https://docs.databricks.com/en/introduction/delta-comparison.html) tables managed by [Unity Catalog](https://www.databricks.com/product/unity-catalog) and query them with a simple API to return the most similar vectors. ``` -from langchain_databricks.vectorstores import DatabricksVectorSearch +from databricks_langchain import DatabricksVectorSearch dvs = DatabricksVectorSearch( endpoint="", diff --git a/docs/docs/integrations/text_embedding/index.mdx b/docs/docs/integrations/text_embedding/index.mdx index 5e4fd4908f7b8..fe2a627192139 100644 --- a/docs/docs/integrations/text_embedding/index.mdx +++ b/docs/docs/integrations/text_embedding/index.mdx @@ -7,7 +7,7 @@ sidebar_class_name: hidden import { CategoryTable, IndexTable } from "@theme/FeatureTables"; -[Embedding models](/docs/concepts#embedding-models) create a vector representation of a piece of text. +[Embedding models](/docs/concepts/embedding_models) create a vector representation of a piece of text. This page documents integrations with various model providers that allow you to use embeddings in LangChain. diff --git a/docs/docs/integrations/tools/passio_nutrition_ai.ipynb b/docs/docs/integrations/tools/passio_nutrition_ai.ipynb index 24899cfea0088..a937e5dbfd807 100644 --- a/docs/docs/integrations/tools/passio_nutrition_ai.ipynb +++ b/docs/docs/integrations/tools/passio_nutrition_ai.ipynb @@ -118,7 +118,7 @@ "source": [ "## Create the agent\n", "\n", - "Now that we have defined the tools, we can create the agent. We will be using an OpenAI Functions agent - for more information on this type of agent, as well as other options, see [this guide](/docs/concepts#agents)\n", + "Now that we have defined the tools, we can create the agent. We will be using an OpenAI Functions agent - for more information on this type of agent, as well as other options, see [this guide](/docs/concepts/agents)\n", "\n", "First, we choose the LLM we want to be guiding the agent." ] @@ -176,7 +176,7 @@ "id": "f8014c9d", "metadata": {}, "source": [ - "Now, we can initialize the agent with the LLM, the prompt, and the tools. The agent is responsible for taking in input and deciding what actions to take. Crucially, the Agent does not execute those actions - that is done by the AgentExecutor (next step). For more information about how to think about these components, see our [conceptual guide](/docs/concepts#agents)" + "Now, we can initialize the agent with the LLM, the prompt, and the tools. The agent is responsible for taking in input and deciding what actions to take. Crucially, the Agent does not execute those actions - that is done by the AgentExecutor (next step). For more information about how to think about these components, see our [conceptual guide](/docs/concepts/agents)" ] }, { @@ -196,7 +196,7 @@ "id": "1a58c9f8", "metadata": {}, "source": [ - "Finally, we combine the agent (the brains) with the tools inside the AgentExecutor (which will repeatedly call the agent and execute tools). For more information about how to think about these components, see our [conceptual guide](/docs/concepts#agents)" + "Finally, we combine the agent (the brains) with the tools inside the AgentExecutor (which will repeatedly call the agent and execute tools). For more information about how to think about these components, see our [conceptual guide](/docs/concepts/agents)" ] }, { diff --git a/docs/docs/introduction.mdx b/docs/docs/introduction.mdx index 7f5afbee628c8..c25c484935190 100644 --- a/docs/docs/introduction.mdx +++ b/docs/docs/introduction.mdx @@ -8,8 +8,8 @@ sidebar_class_name: hidden **LangChain** is a framework for developing applications powered by large language models (LLMs). LangChain simplifies every stage of the LLM application lifecycle: -- **Development**: Build your applications using LangChain's open-source [building blocks](/docs/concepts#langchain-expression-language-lcel), [components](/docs/concepts), and [third-party integrations](/docs/integrations/providers/). -Use [LangGraph](/docs/concepts/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support. +- **Development**: Build your applications using LangChain's open-source [building blocks](/docs/concepts/lcel), [components](/docs/concepts), and [third-party integrations](/docs/integrations/providers/). +Use [LangGraph](/docs/concepts/architecture/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support. - **Productionization**: Use [LangSmith](https://docs.smith.langchain.com/) to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence. - **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/). diff --git a/docs/docs/troubleshooting/errors/INVALID_PROMPT_INPUT.mdx b/docs/docs/troubleshooting/errors/INVALID_PROMPT_INPUT.mdx index 74647e4b06b2d..030881a19c0d0 100644 --- a/docs/docs/troubleshooting/errors/INVALID_PROMPT_INPUT.mdx +++ b/docs/docs/troubleshooting/errors/INVALID_PROMPT_INPUT.mdx @@ -1,6 +1,6 @@ # INVALID_PROMPT_INPUT -A [prompt template](/docs/concepts#prompt-templates) received missing or invalid input variables. +A [prompt template](/docs/concepts/prompt_templates) received missing or invalid input variables. ## Troubleshooting @@ -8,7 +8,7 @@ The following may help resolve this error: - Double-check your prompt template to ensure that it is correct. - If you are using the default f-string format and you are using curly braces `{` anywhere in your template, they should be double escaped like this: `{{` (and if you want to render a double curly brace, you should use four curly braces: `{{{{`). -- If you are using a [`MessagesPlaceholder`](/docs/concepts/messages/#messagesplaceholder), make sure that you are passing in an array of messages or message-like objects. +- If you are using a [`MessagesPlaceholder`](/docs/concepts/prompt_templates/#messagesplaceholder), make sure that you are passing in an array of messages or message-like objects. - If you are using shorthand tuples to declare your prompt template, make sure that the variable name is wrapped in curly braces (`["placeholder", "{messages}"]`). - Try viewing the inputs into your prompt template using [LangSmith](https://docs.smith.langchain.com/) or log statements to confirm they appear as expected. - If you are pulling a prompt from the [LangChain Prompt Hub](https://smith.langchain.com/prompts), try pulling and logging it or running it in isolation with a sample input to confirm that it is what you expect. diff --git a/docs/docs/troubleshooting/errors/INVALID_TOOL_RESULTS.ipynb b/docs/docs/troubleshooting/errors/INVALID_TOOL_RESULTS.ipynb index e2e036521b058..4a1b9b3bdf3dc 100644 --- a/docs/docs/troubleshooting/errors/INVALID_TOOL_RESULTS.ipynb +++ b/docs/docs/troubleshooting/errors/INVALID_TOOL_RESULTS.ipynb @@ -8,7 +8,7 @@ "\n", "You are passing too many, too few, or mismatched [`ToolMessages`](https://api.js.langchain.com/classes/_langchain_core.messages_tool.ToolMessage.html) to a model.\n", "\n", - "When [using a model to call tools](/docs/concepts#functiontool-calling), the [`AIMessage`](https://api.js.langchain.com/classes/_langchain_core.messages.AIMessage.html)\n", + "When [using a model to call tools](/docs/concepts/tool_calling), the [`AIMessage`](https://api.js.langchain.com/classes/_langchain_core.messages.AIMessage.html)\n", "the model responds with will contain a `tool_calls` array. To continue the flow, the next messages you pass back to the model must\n", "be exactly one `ToolMessage` for each item in that array containing the result of that tool call. Each `ToolMessage` must have a `tool_call_id` field\n", "that matches one of the `tool_calls` on the `AIMessage`.\n", diff --git a/docs/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE.ipynb b/docs/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE.ipynb index 904448ae1b3d2..c24eae7329bee 100644 --- a/docs/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE.ipynb +++ b/docs/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE.ipynb @@ -38,7 +38,7 @@ "metadata": {}, "source": [ "These include OpenAI style message objects (`{ role: \"user\", content: \"Hello world!\" }`),\n", - "tuples, and plain strings (which are converted to [`HumanMessages`](/docs/concepts#humanmessage)).\n", + "tuples, and plain strings (which are converted to [`HumanMessages`](/docs/concepts/messages/#humanmessage)).\n", "\n", "If one of these modules receives a value outside of one of these formats, you will receive an error like the following:" ] diff --git a/docs/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE.ipynb b/docs/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE.ipynb index 75d2eb7978d09..147c7851813d3 100644 --- a/docs/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE.ipynb +++ b/docs/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE.ipynb @@ -6,7 +6,7 @@ "source": [ "# OUTPUT_PARSING_FAILURE\n", "\n", - "An [output parser](/docs/concepts#output-parsers) was unable to handle model output as expected.\n", + "An [output parser](/docs/concepts/output_parsers) was unable to handle model output as expected.\n", "\n", "To illustrate this, let's say you have an output parser that expects a chat model to output JSON surrounded by a markdown code tag (triple backticks). Here would be an example of good input:" ] diff --git a/docs/docs/tutorials/agents.ipynb b/docs/docs/tutorials/agents.ipynb index 22d9a37bd91c4..2f1671e7c796d 100644 --- a/docs/docs/tutorials/agents.ipynb +++ b/docs/docs/tutorials/agents.ipynb @@ -370,7 +370,7 @@ "source": [ "## Create the agent\n", "\n", - "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/#langgraph) to construct the agent. \n", + "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/architecture/#langgraph) to construct the agent. \n", "Currently, we are using a high level interface to construct the agent, but the nice thing about LangGraph is that this high-level interface is backed by a low-level, highly controllable API in case you want to modify the agent logic.\n" ] }, @@ -719,7 +719,7 @@ "We've also added in memory so you can have a conversation with them.\n", "Agents are a complex topic with lots to learn! \n", "\n", - "For more information on Agents, please check out the [LangGraph](/docs/concepts/#langgraph) documentation. This has it's own set of concepts, tutorials, and how-to guides." + "For more information on Agents, please check out the [LangGraph](/docs/concepts/architecture/#langgraph) documentation. This has it's own set of concepts, tutorials, and how-to guides." ] }, { diff --git a/docs/docs/tutorials/extraction.ipynb b/docs/docs/tutorials/extraction.ipynb index 4470d47770cac..9a278c383818e 100644 --- a/docs/docs/tutorials/extraction.ipynb +++ b/docs/docs/tutorials/extraction.ipynb @@ -195,7 +195,7 @@ "source": [ "We need to use a model that supports function/tool calling.\n", "\n", - "Please review [the documentation](/docs/concepts#function-tool-calling) for list of some models that can be used with this API." + "Please review [the documentation](/docs/concepts/tool_calling) for list of some models that can be used with this API." ] }, { diff --git a/docs/docs/tutorials/llm_chain.ipynb b/docs/docs/tutorials/llm_chain.ipynb index 0a04d91876f1a..fea5ec33967ed 100644 --- a/docs/docs/tutorials/llm_chain.ipynb +++ b/docs/docs/tutorials/llm_chain.ipynb @@ -29,7 +29,7 @@ "\n", "- Debugging and tracing your application using [LangSmith](https://docs.smith.langchain.com/)\n", "\n", - "- Deploying your application with [LangServe](/docs/concepts/#langserve)\n", + "- Deploying your application with [LangServe](/docs/concepts/architecture/#langserve)\n", "\n", "Let's dive in!\n", "\n", diff --git a/docs/docs/tutorials/qa_chat_history.ipynb b/docs/docs/tutorials/qa_chat_history.ipynb index 8aff4c3a01420..1955abd8c4c4e 100644 --- a/docs/docs/tutorials/qa_chat_history.ipynb +++ b/docs/docs/tutorials/qa_chat_history.ipynb @@ -52,7 +52,7 @@ "\n", "### Dependencies\n", "\n", - "We'll use OpenAI embeddings and a simple in-memory vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts#embedding-models), and [VectorStore](/docs/concepts#vectorstores) or [Retriever](/docs/concepts#retrievers). \n", + "We'll use OpenAI embeddings and a simple in-memory vector store in this walkthrough, but everything shown here works with any [Embeddings](/docs/concepts/embedding_models), and [VectorStore](/docs/concepts/vectorstores) or [Retriever](/docs/concepts/retrievers). \n", "\n", "We'll use the following packages:" ] @@ -786,7 +786,7 @@ "id": "07dcb968-ed9a-458a-85e1-528cd28c6965", "metadata": {}, "source": [ - "Tools are LangChain [Runnables](/docs/concepts#langchain-expression-language-lcel), and implement the usual interface:" + "Tools are LangChain [Runnables](/docs/concepts/lcel), and implement the usual interface:" ] }, { @@ -817,7 +817,7 @@ "source": [ "### Agent constructor\n", "\n", - "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/#langgraph) to construct the agent. \n", + "Now that we have defined the tools and the LLM, we can create the agent. We will be using [LangGraph](/docs/concepts/architecture/#langgraph) to construct the agent. \n", "Currently we are using a high level interface to construct the agent, but the nice thing about LangGraph is that this high-level interface is backed by a low-level, highly controllable API in case you want to modify the agent logic." ] }, diff --git a/docs/docs/tutorials/rag.ipynb b/docs/docs/tutorials/rag.ipynb index 1f7a7799e4315..ef49ec4c40c2e 100644 --- a/docs/docs/tutorials/rag.ipynb +++ b/docs/docs/tutorials/rag.ipynb @@ -237,7 +237,7 @@ "## 1. Indexing: Load {#indexing-load}\n", "\n", "We need to first load the blog post contents. We can use\n", - "[DocumentLoaders](/docs/concepts#document-loaders)\n", + "[DocumentLoaders](/docs/concepts/document_loaders)\n", "for this, which are objects that load in data from a source and return a\n", "list of\n", "[Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html).\n", @@ -518,7 +518,7 @@ "\n", "First we need to define our logic for searching over documents.\n", "LangChain defines a\n", - "[Retriever](/docs/concepts#retrievers/) interface\n", + "[Retriever](/docs/concepts/retrievers) interface\n", "which wraps an index that can return relevant `Documents` given a string\n", "query.\n", "\n", @@ -680,7 +680,7 @@ "id": "4516200c", "metadata": {}, "source": [ - "We’ll use the [LCEL Runnable](/docs/concepts#langchain-expression-language-lcel)\n", + "We’ll use the [LCEL Runnable](/docs/concepts/lcel)\n", "protocol to define the chain, allowing us to \n", "\n", "- pipe together components and functions in a transparent way \n", @@ -731,7 +731,7 @@ "source": [ "Let's dissect the LCEL to understand what's going on.\n", "\n", - "First: each of these components (`retriever`, `prompt`, `llm`, etc.) are instances of [Runnable](/docs/concepts#langchain-expression-language-lcel). This means that they implement the same methods-- such as sync and async `.invoke`, `.stream`, or `.batch`-- which makes them easier to connect together. They can be connected into a [RunnableSequence](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableSequence.html)-- another Runnable-- via the `|` operator.\n", + "First: each of these components (`retriever`, `prompt`, `llm`, etc.) are instances of [Runnable](/docs/concepts/lcel). This means that they implement the same methods-- such as sync and async `.invoke`, `.stream`, or `.batch`-- which makes them easier to connect together. They can be connected into a [RunnableSequence](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableSequence.html)-- another Runnable-- via the `|` operator.\n", "\n", "LangChain will automatically cast certain objects to runnables when met with the `|` operator. Here, `format_docs` is cast to a [RunnableLambda](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableLambda.html), and the dict with `\"context\"` and `\"question\"` is cast to a [RunnableParallel](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableParallel.html). The details are less important than the bigger point, which is that each object in the chain is a Runnable.\n", "\n", @@ -933,10 +933,10 @@ "\n", "We've covered the steps to build a basic Q&A app over data:\n", "\n", - "- Loading data with a [Document Loader](/docs/concepts#document-loaders)\n", - "- Chunking the indexed data with a [Text Splitter](/docs/concepts#text-splitters) to make it more easily usable by a model\n", - "- [Embedding the data](/docs/concepts#embedding-models) and storing the data in a [vectorstore](/docs/how_to/vectorstores)\n", - "- [Retrieving](/docs/concepts#retrievers) the previously stored chunks in response to incoming questions\n", + "- Loading data with a [Document Loader](/docs/concepts/document_loaders)\n", + "- Chunking the indexed data with a [Text Splitter](/docs/concepts/text_splitters) to make it more easily usable by a model\n", + "- [Embedding the data](/docs/concepts/embedding_models) and storing the data in a [vectorstore](/docs/how_to/vectorstores)\n", + "- [Retrieving](/docs/concepts/retrievers) the previously stored chunks in response to incoming questions\n", "- Generating an answer using the retrieved chunks as context\n", "\n", "There’s plenty of features, integrations, and extensions to explore in each of\n", diff --git a/docs/docs/tutorials/retrievers.ipynb b/docs/docs/tutorials/retrievers.ipynb index 2eefbdd7499e1..9c9bd12e04741 100644 --- a/docs/docs/tutorials/retrievers.ipynb +++ b/docs/docs/tutorials/retrievers.ipynb @@ -121,9 +121,9 @@ "\n", "## Vector stores\n", "\n", - "Vector search is a common way to store and search over unstructured data (such as unstructured text). The idea is to store numeric vectors that are associated with the text. Given a query, we can [embed](/docs/concepts#embedding-models) it as a vector of the same dimension and use vector similarity metrics to identify related data in the store.\n", + "Vector search is a common way to store and search over unstructured data (such as unstructured text). The idea is to store numeric vectors that are associated with the text. Given a query, we can [embed](/docs/concepts/embedding_models) it as a vector of the same dimension and use vector similarity metrics to identify related data in the store.\n", "\n", - "LangChain [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.VectorStore.html) objects contain methods for adding text and `Document` objects to the store, and querying them using various similarity metrics. They are often initialized with [embedding](/docs/how_to/embed_text) models, which determine how text data is translated to numeric vectors.\n", + "LangChain [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) objects contain methods for adding text and `Document` objects to the store, and querying them using various similarity metrics. They are often initialized with [embedding](/docs/how_to/embed_text) models, which determine how text data is translated to numeric vectors.\n", "\n", "LangChain includes a suite of [integrations](/docs/integrations/vectorstores) with different vector store technologies. Some vector stores are hosted by a provider (e.g., various cloud providers) and require specific credentials to use; some (such as [Postgres](/docs/integrations/vectorstores/pgvector)) run in separate infrastructure that can be run locally or via a third-party; others can run in-memory for lightweight workloads. Here we will demonstrate usage of LangChain VectorStores using [Chroma](/docs/integrations/vectorstores/chroma), which includes an in-memory implementation.\n", "\n", @@ -309,9 +309,9 @@ "\n", "## Retrievers\n", "\n", - "LangChain `VectorStore` objects do not subclass [Runnable](https://python.langchain.com/api_reference/core/index.html#module-langchain_core.runnables), and so cannot immediately be integrated into LangChain Expression Language [chains](/docs/concepts/lcel).\n", + "LangChain `VectorStore` objects do not subclass [Runnable](https://python.langchain.com/api_reference/core/index.html#langchain-core-runnables), and so cannot immediately be integrated into LangChain Expression Language [chains](/docs/concepts/lcel).\n", "\n", - "LangChain [Retrievers](https://python.langchain.com/api_reference/core/index.html#module-langchain_core.retrievers) are Runnables, so they implement a standard set of methods (e.g., synchronous and asynchronous `invoke` and `batch` operations) and are designed to be incorporated in LCEL chains.\n", + "LangChain [Retrievers](https://python.langchain.com/api_reference/core/index.html#langchain-core-retrievers) are Runnables, so they implement a standard set of methods (e.g., synchronous and asynchronous `invoke` and `batch` operations) and are designed to be incorporated in LCEL chains.\n", "\n", "We can create a simple version of this ourselves, without subclassing `Retriever`. If we choose what method we wish to use to retrieve documents, we can create a runnable easily. Below we will build one around the `similarity_search` method:" ] diff --git a/docs/docs/tutorials/sql_qa.ipynb b/docs/docs/tutorials/sql_qa.ipynb index 18a8063f8660d..3c7c8677d1fd1 100644 --- a/docs/docs/tutorials/sql_qa.ipynb +++ b/docs/docs/tutorials/sql_qa.ipynb @@ -138,7 +138,7 @@ "\n", "## Chains {#chains}\n", "\n", - "Chains (i.e., compositions of LangChain [Runnables](/docs/concepts#langchain-expression-language-lcel)) support applications whose steps are predictable. We can create a simple chain that takes a question and does the following:\n", + "Chains (i.e., compositions of LangChain [Runnables](/docs/concepts/lcel)) support applications whose steps are predictable. We can create a simple chain that takes a question and does the following:\n", "- convert the question into a SQL query;\n", "- execute the query;\n", "- use the result to answer the original question.\n", @@ -494,7 +494,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We will use a prebuilt [LangGraph](/docs/concepts/#langgraph) agent to build our agent" + "We will use a prebuilt [LangGraph](/docs/concepts/architecture/#langgraph) agent to build our agent" ] }, { diff --git a/docs/docs/versions/migrating_chains/index.ipynb b/docs/docs/versions/migrating_chains/index.ipynb index 7a46b74d67d28..9e787c0561468 100644 --- a/docs/docs/versions/migrating_chains/index.ipynb +++ b/docs/docs/versions/migrating_chains/index.ipynb @@ -34,7 +34,7 @@ ":::info Prerequisites\n", "\n", "These guides assume some familiarity with the following concepts:\n", - "- [LangChain Expression Language](/docs/concepts#langchain-expression-language-lcel)\n", + "- [LangChain Expression Language](/docs/concepts/lcel)\n", "- [LangGraph](https://langchain-ai.github.io/langgraph/)\n", ":::\n", "\n", diff --git a/docs/scripts/kv_store_feat_table.py b/docs/scripts/kv_store_feat_table.py index dd7fc1ca203a8..6730ec650d066 100644 --- a/docs/scripts/kv_store_feat_table.py +++ b/docs/scripts/kv_store_feat_table.py @@ -14,7 +14,7 @@ # Key-value stores -[Key-value stores](/docs/concepts/#key-value-stores) are used by other LangChain components to store and retrieve data. +[Key-value stores](/docs/concepts/key_value_stores) are used by other LangChain components to store and retrieve data. :::info diff --git a/docs/scripts/partner_pkg_table.py b/docs/scripts/partner_pkg_table.py index 6bc8b4badf7ac..e5b4fd0eda37c 100644 --- a/docs/scripts/partner_pkg_table.py +++ b/docs/scripts/partner_pkg_table.py @@ -76,7 +76,6 @@ CUSTOM_NAME = { "google-genai": "Google Generative AI", "aws": "AWS", - "airbyte": "Airbyte", "ibm": "IBM", } CUSTOM_PROVIDER_PAGES = { diff --git a/docs/scripts/tool_feat_table.py b/docs/scripts/tool_feat_table.py index 981fe2f706525..4585551f36e12 100644 --- a/docs/scripts/tool_feat_table.py +++ b/docs/scripts/tool_feat_table.py @@ -182,9 +182,9 @@ # Tools -[Tools](/docs/concepts/#tools) are utilities designed to be called by a model: their inputs are designed to be generated by models, and their outputs are designed to be passed back to models. +[Tools](/docs/concepts/tools) are utilities designed to be called by a model: their inputs are designed to be generated by models, and their outputs are designed to be passed back to models. -A [toolkit](/docs/concepts#toolkits) is a collection of tools meant to be used together. +A [toolkit](/docs/concepts/tools/#toolkits) is a collection of tools meant to be used together. :::info diff --git a/docs/vercel.json b/docs/vercel.json index 1f2aa98c786e8..4f368093c5aed 100644 --- a/docs/vercel.json +++ b/docs/vercel.json @@ -87,7 +87,7 @@ "destination": "/docs/integrations/providers/:path*" }, { - "source": "/docs/troubleshooting/errors/:path((?:GRAPH_RECURSION_LIMIT|INVALID_CONCURRENT_GRAPH_UPDATE|INVALID_GRAPH_NODE_RETURN_VALUE|MULTIPLE_SUBGRAPHS)/?)*", + "source": "/docs/troubleshooting/errors/:path((?:GRAPH_RECURSION_LIMIT|INVALID_CONCURRENT_GRAPH_UPDATE|INVALID_GRAPH_NODE_RETURN_VALUE|MULTIPLE_SUBGRAPHS|INVALID_CHAT_HISTORY)/?)*", "destination": "https://langchain-ai.github.io/langgraph/troubleshooting/errors/:path*" }, { diff --git a/libs/cli/langchain_cli/integration_template/pyproject.toml b/libs/cli/langchain_cli/integration_template/pyproject.toml index 5f50f0c54d066..efdcb9efeadcd 100644 --- a/libs/cli/langchain_cli/integration_template/pyproject.toml +++ b/libs/cli/langchain_cli/integration_template/pyproject.toml @@ -1,3 +1,7 @@ +[build-system] +requires = [ "poetry-core>=1.0.0",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "__package_name__" version = "0.1.0" @@ -7,82 +11,68 @@ readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/__package_name_short__" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22__package_name_short__%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" + +[tool.ruff.lint] +select = [ "E", "F", "I", "T201",] + +[tool.coverage.run] +omit = [ "tests/*",] + +[tool.pytest.ini_options] +addopts = "--strict-markers --strict-config --durations=5" +markers = [ "compile: mark placeholder test used to compile integration tests without running them",] +asyncio_mode = "auto" [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.4.3" pytest-asyncio = "^0.23.2" pytest-socket = "^0.7.0" -langchain-core = { path = "../../core", develop = true } pytest-watcher = "^0.3.4" -[tool.poetry.group.codespell] -optional = true - [tool.poetry.group.codespell.dependencies] codespell = "^2.2.6" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.5" [tool.poetry.group.typing.dependencies] mypy = "^1.10" -langchain-core = { path = "../../core", develop = true } -[tool.poetry.group.dev] -optional = true +[tool.poetry.group.test.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } +[tool.poetry.group.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -addopts = "--strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/cli/langchain_cli/package_template/pyproject.toml b/libs/cli/langchain_cli/package_template/pyproject.toml index c3e4e08acf3c0..3a6ab95f439ff 100644 --- a/libs/cli/langchain_cli/package_template/pyproject.toml +++ b/libs/cli/langchain_cli/package_template/pyproject.toml @@ -1,3 +1,7 @@ +[build-system] +requires = [ "poetry-core",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "__package_name__" version = "0.0.1" @@ -5,21 +9,16 @@ description = "" authors = [] readme = "README.md" +[tool.langserve] +export_module = "__module_name__" +export_attr = "chain" + [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" langchain-openai = ">=0.0.1" - [tool.poetry.group.dev.dependencies] langchain-cli = ">=0.0.4" fastapi = "^0.104.0" sse-starlette = "^1.6.5" - -[tool.langserve] -export_module = "__module_name__" -export_attr = "chain" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/libs/community/langchain_community/adapters/openai.py b/libs/community/langchain_community/adapters/openai.py index 8db939d5c9705..673e5fa567be8 100644 --- a/libs/community/langchain_community/adapters/openai.py +++ b/libs/community/langchain_community/adapters/openai.py @@ -180,6 +180,12 @@ def _convert_message_chunk(chunk: BaseMessageChunk, i: int) -> dict: # not missing, but None. if i == 0: _dict["content"] = None + if "tool_calls" in chunk.additional_kwargs: + _dict["tool_calls"] = chunk.additional_kwargs["tool_calls"] + # If the first chunk is tool calls, the content is not empty string, + # not missing, but None. + if i == 0: + _dict["content"] = None else: _dict["content"] = chunk.content else: diff --git a/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py b/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py index 424d967abbf1e..113ff9be53c70 100644 --- a/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py +++ b/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py @@ -51,7 +51,7 @@ class PowerBIToolkit(BaseToolkit): examples: Optional. The examples for the prompt. Default is None. max_iterations: Optional. The maximum iterations to run. Default is 5. callback_manager: Optional. The callback manager. Default is None. - output_token_limit: Optional. The output token limit. Default is None. + output_token_limit: The output token limit. Default is 4000. tiktoken_model_name: Optional. The TikToken model name. Default is None. """ @@ -60,7 +60,7 @@ class PowerBIToolkit(BaseToolkit): examples: Optional[str] = None max_iterations: int = 5 callback_manager: Optional[BaseCallbackManager] = None - output_token_limit: Optional[int] = None + output_token_limit: int = 4000 tiktoken_model_name: Optional[str] = None model_config = ConfigDict( diff --git a/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py b/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py index 741528d915288..93f32e9a83e58 100644 --- a/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py +++ b/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py @@ -68,9 +68,16 @@ def convert_message_to_dict(message: BaseMessage) -> dict: message_dict = {"role": "assistant", "content": message.content} if "function_call" in message.additional_kwargs: message_dict["function_call"] = message.additional_kwargs["function_call"] - # If function call only, content is None not empty string - if message_dict["content"] == "": - message_dict["content"] = None + elif len(message.tool_calls) != 0: + tool_call = message.tool_calls[0] + message_dict["function_call"] = { + "name": tool_call["name"], + "args": tool_call["args"], + } + + # If function call only, content is None not empty string + if "function_call" in message_dict and message_dict["content"] == "": + message_dict["content"] = None elif isinstance(message, (FunctionMessage, ToolMessage)): message_dict = { "role": "function", diff --git a/libs/community/langchain_community/document_loaders/parsers/audio.py b/libs/community/langchain_community/document_loaders/parsers/audio.py index abc08e561a578..32ced08260187 100644 --- a/libs/community/langchain_community/document_loaders/parsers/audio.py +++ b/libs/community/langchain_community/document_loaders/parsers/audio.py @@ -1,7 +1,8 @@ +import io import logging import os import time -from typing import Any, Dict, Iterator, Literal, Optional, Tuple, Union +from typing import Any, Callable, Dict, Iterator, Literal, Optional, Tuple, Union from langchain_core.documents import Document @@ -12,6 +13,218 @@ logger = logging.getLogger(__name__) +class AzureOpenAIWhisperParser(BaseBlobParser): + """ + Transcribe and parse audio files using Azure OpenAI Whisper. + + This parser integrates with the Azure OpenAI Whisper model to transcribe + audio files. It differs from the standard OpenAI Whisper parser, requiring + an Azure endpoint and credentials. The parser is limited to files under 25 MB. + + **Note**: + This parser uses the Azure OpenAI API, providing integration with the Azure + ecosystem, and making it suitable for workflows involving other Azure services. + + For files larger than 25 MB, consider using Azure AI Speech batch transcription: + https://learn.microsoft.com/azure/ai-services/speech-service/batch-transcription-create?pivots=rest-api#use-a-whisper-model + + Setup: + 1. Follow the instructions here to deploy Azure Whisper: + https://learn.microsoft.com/azure/ai-services/openai/whisper-quickstart?tabs=command-line%2Cpython-new&pivots=programming-language-python + 2. Install ``langchain`` and set the following environment variables: + + .. code-block:: bash + + pip install -U langchain langchain-community + + export AZURE_OPENAI_API_KEY="your-api-key" + export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/" + export OPENAI_API_VERSION="your-api-version" + + Example Usage: + .. code-block:: python + + from langchain.community import AzureOpenAIWhisperParser + + whisper_parser = AzureOpenAIWhisperParser( + deployment_name="your-whisper-deployment", + api_version="2024-06-01", + api_key="your-api-key", + # other params... + ) + + audio_blob = Blob(path="your-audio-file-path") + response = whisper_parser.lazy_parse(audio_blob) + + for document in response: + print(document.page_content) + + Integration with Other Loaders: + The AzureOpenAIWhisperParser can be used with video/audio loaders and + `GenericLoader` to automate retrieval and parsing. + + YoutubeAudioLoader Example: + .. code-block:: python + + from langchain_community.document_loaders.blob_loaders import ( + YoutubeAudioLoader + ) + from langchain_community.document_loaders.generic import GenericLoader + + # Must be a list + youtube_url = ["https://your-youtube-url"] + save_dir = "directory-to-download-videos" + + loader = GenericLoader( + YoutubeAudioLoader(youtube_url, save_dir), + AzureOpenAIWhisperParser(deployment_name="your-deployment-name") + ) + + docs = loader.load() + """ + + def __init__( + self, + *, + api_key: Optional[str] = None, + azure_endpoint: Optional[str] = None, + api_version: Optional[str] = None, + azure_ad_token_provider: Union[Callable[[], str], None] = None, + language: Optional[str] = None, + prompt: Optional[str] = None, + response_format: Union[ + Literal["json", "text", "srt", "verbose_json", "vtt"], None + ] = None, + temperature: Optional[float] = None, + deployment_name: str, + max_retries: int = 3, + ): + """ + Initialize the AzureOpenAIWhisperParser. + + Args: + api_key (Optional[str]): + Azure OpenAI API key. If not provided, defaults to the + `AZURE_OPENAI_API_KEY` environment variable. + azure_endpoint (Optional[str]): + Azure OpenAI service endpoint. Defaults to `AZURE_OPENAI_ENDPOINT` + environment variable if not set. + api_version (Optional[str]): + API version to use, + defaults to the `OPENAI_API_VERSION` environment variable. + azure_ad_token_provider (Union[Callable[[], str], None]): + Azure Active Directory token for authentication (if applicable). + language (Optional[str]): + Language in which the request should be processed. + prompt (Optional[str]): + Custom instructions or prompt for the Whisper model. + response_format (Union[str, None]): + The desired output format. Options: "json", "text", "srt", + "verbose_json", "vtt". + temperature (Optional[float]): + Controls the randomness of the model's output. + deployment_name (str): + The deployment name of the Whisper model. + max_retries (int): + Maximum number of retries for failed API requests. + Raises: + ImportError: + If the required package `openai` is not installed. + """ + self.api_key = api_key or os.environ.get("AZURE_OPENAI_API_KEY") + self.azure_endpoint = azure_endpoint or os.environ.get("AZURE_OPENAI_ENDPOINT") + self.api_version = api_version or os.environ.get("OPENAI_API_VERSION") + self.azure_ad_token_provider = azure_ad_token_provider + + self.language = language + self.prompt = prompt + self.response_format = response_format + self.temperature = temperature + + self.deployment_name = deployment_name + self.max_retries = max_retries + + try: + import openai + except ImportError: + raise ImportError( + "openai package not found, please install it with " + "`pip install openai`" + ) + + if is_openai_v1(): + self._client = openai.AzureOpenAI( + api_key=self.api_key, + azure_endpoint=self.azure_endpoint, + api_version=self.api_version, + max_retries=self.max_retries, + azure_ad_token=self.azure_ad_token_provider, + ) + else: + if self.api_key: + openai.api_key = self.api_key + if self.azure_endpoint: + openai.api_base = self.azure_endpoint + if self.api_version: + openai.api_version = self.api_version + openai.api_type = "azure" + self._client = openai + + @property + def _create_params(self) -> Dict[str, Any]: + params = { + "language": self.language, + "prompt": self.prompt, + "response_format": self.response_format, + "temperature": self.temperature, + } + return {k: v for k, v in params.items() if v is not None} + + def lazy_parse(self, blob: Blob) -> Iterator[Document]: + """ + Lazily parse the provided audio blob for transcription. + + Args: + blob (Blob): + The audio file in Blob format to be transcribed. + + Yields: + Document: + Parsed transcription from the audio file. + + Raises: + Exception: + If an error occurs during transcription. + """ + + file_obj = open(str(blob.path), "rb") + + # Transcribe + try: + if is_openai_v1(): + transcript = self._client.audio.transcriptions.create( + model=self.deployment_name, + file=file_obj, + **self._create_params, + ) + else: + transcript = self._client.Audio.transcribe( + model=self.deployment_name, + deployment_id=self.deployment_name, + file=file_obj, + **self._create_params, + ) + except Exception: + raise + + yield Document( + page_content=transcript.text + if not isinstance(transcript, str) + else transcript, + metadata={"source": blob.source}, + ) + + class OpenAIWhisperParser(BaseBlobParser): """Transcribe and parse audio files. @@ -19,7 +232,7 @@ class OpenAIWhisperParser(BaseBlobParser): Args: api_key: OpenAI API key - chunk_duration_threshold: minimum duration of a chunk in seconds + chunk_duration_threshold: Minimum duration of a chunk in seconds NOTE: According to the OpenAI API, the chunk duration should be at least 0.1 seconds. If the chunk duration is less or equal than the threshold, it will be skipped. @@ -61,8 +274,6 @@ def _create_params(self) -> Dict[str, Any]: def lazy_parse(self, blob: Blob) -> Iterator[Document]: """Lazily parse the blob.""" - import io - try: import openai except ImportError: @@ -85,11 +296,11 @@ def lazy_parse(self, blob: Blob) -> Iterator[Document]: if self.api_key: openai.api_key = self.api_key if self.base_url: - openai.base_url = self.base_url + openai.api_base = self.base_url # Audio file from disk - audio = AudioSegment.from_file(blob.path) + audio = AudioSegment.from_file(blob.path) # Define the duration of each chunk in minutes # Need to meet 25MB size limit for Whisper API chunk_duration = 20 @@ -240,8 +451,6 @@ def __init__( def lazy_parse(self, blob: Blob) -> Iterator[Document]: """Lazily parse the blob.""" - import io - try: from pydub import AudioSegment except ImportError: @@ -436,8 +645,6 @@ def __init__( def lazy_parse(self, blob: Blob) -> Iterator[Document]: """Lazily parse the blob.""" - import io - try: from pydub import AudioSegment except ImportError: diff --git a/libs/community/langchain_community/document_loaders/word_document.py b/libs/community/langchain_community/document_loaders/word_document.py index c7c50575cc7ef..bd2c4ae8f57f8 100644 --- a/libs/community/langchain_community/document_loaders/word_document.py +++ b/libs/community/langchain_community/document_loaders/word_document.py @@ -24,6 +24,7 @@ class Docx2txtLoader(BaseLoader, ABC): def __init__(self, file_path: Union[str, Path]): """Initialize with file path.""" self.file_path = str(file_path) + self.original_file_path = self.file_path if "~" in self.file_path: self.file_path = os.path.expanduser(self.file_path) @@ -55,7 +56,7 @@ def load(self) -> List[Document]: return [ Document( page_content=docx2txt.process(self.file_path), - metadata={"source": self.file_path}, + metadata={"source": self.original_file_path}, ) ] diff --git a/libs/community/langchain_community/embeddings/dashscope.py b/libs/community/langchain_community/embeddings/dashscope.py index 0963808635d18..3268e5de3bd02 100644 --- a/libs/community/langchain_community/embeddings/dashscope.py +++ b/libs/community/langchain_community/embeddings/dashscope.py @@ -23,6 +23,8 @@ logger = logging.getLogger(__name__) +BATCH_SIZE = {"text-embedding-v1": 25, "text-embedding-v2": 25, "text-embedding-v3": 6} + def _create_retry_decorator(embeddings: DashScopeEmbeddings) -> Callable[[Any], Any]: multiplier = 1 @@ -49,9 +51,12 @@ def _embed_with_retry(**kwargs: Any) -> Any: i = 0 input_data = kwargs["input"] input_len = len(input_data) if isinstance(input_data, list) else 1 + batch_size = BATCH_SIZE.get(kwargs["model"], 25) while i < input_len: kwargs["input"] = ( - input_data[i : i + 25] if isinstance(input_data, list) else input_data + input_data[i : i + batch_size] + if isinstance(input_data, list) + else input_data ) resp = embeddings.client.call(**kwargs) if resp.status_code == 200: @@ -67,7 +72,7 @@ def _embed_with_retry(**kwargs: Any) -> Any: f"code: {resp.code} \n message: {resp.message}", response=resp, ) - i += 25 + i += batch_size return result return _embed_with_retry(**kwargs) diff --git a/libs/community/langchain_community/llms/moonshot.py b/libs/community/langchain_community/llms/moonshot.py index 473f35fdf069b..7f204fa69d885 100644 --- a/libs/community/langchain_community/llms/moonshot.py +++ b/libs/community/langchain_community/llms/moonshot.py @@ -39,7 +39,7 @@ def completion(self, request: Any) -> Any: class MoonshotCommon(BaseModel): """Common parameters for Moonshot LLMs.""" - client: _MoonshotClient + client: Any base_url: str = MOONSHOT_SERVICE_URL_BASE moonshot_api_key: Optional[SecretStr] = Field(default=None, alias="api_key") """Moonshot API key. Get it here: https://platform.moonshot.cn/console/api-keys""" diff --git a/libs/community/langchain_community/utilities/polygon.py b/libs/community/langchain_community/utilities/polygon.py index c7ab49f405467..f14069bd4fa61 100644 --- a/libs/community/langchain_community/utilities/polygon.py +++ b/libs/community/langchain_community/utilities/polygon.py @@ -45,7 +45,7 @@ def get_financials(self, ticker: str) -> Optional[dict]: data = response.json() status = data.get("status", None) - if status not in ("OK", "STOCKBUSINESS"): + if status not in ("OK", "STOCKBUSINESS", "STOCKSBUSINESS"): raise ValueError(f"API Error: {data}") return data.get("results", None) @@ -61,7 +61,7 @@ def get_last_quote(self, ticker: str) -> Optional[dict]: data = response.json() status = data.get("status", None) - if status not in ("OK", "STOCKBUSINESS"): + if status not in ("OK", "STOCKBUSINESS", "STOCKSBUSINESS"): raise ValueError(f"API Error: {data}") return data.get("results", None) @@ -82,7 +82,7 @@ def get_ticker_news(self, ticker: str) -> Optional[dict]: data = response.json() status = data.get("status", None) - if status not in ("OK", "STOCKBUSINESS"): + if status not in ("OK", "STOCKBUSINESS", "STOCKSBUSINESS"): raise ValueError(f"API Error: {data}") return data.get("results", None) @@ -116,7 +116,7 @@ def get_aggregates(self, ticker: str, **kwargs: Any) -> Optional[dict]: data = response.json() status = data.get("status", None) - if status not in ("OK", "STOCKBUSINESS"): + if status not in ("OK", "STOCKBUSINESS", "STOCKSBUSINESS"): raise ValueError(f"API Error: {data}") return data.get("results", None) diff --git a/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py b/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py index 8a671da921ce6..2317af9da0250 100644 --- a/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py +++ b/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py @@ -274,15 +274,15 @@ def _similarity_search_with_score( query += "TOP @limit " query += ( - "c.id, c.{}, c.text, c.metadata, " - "VectorDistance(c.@embeddingKey, @embeddings) AS SimilarityScore FROM c" + "c.id, c[@embeddingKey], c.text, c.metadata, " + "VectorDistance(c[@embeddingKey], @embeddings) AS SimilarityScore FROM c" ) # Add where_clause if specified if pre_filter is not None and pre_filter.get("where_clause") is not None: query += " {}".format(pre_filter["where_clause"]) - query += " ORDER BY VectorDistance(c.@embeddingKey, @embeddings)" + query += " ORDER BY VectorDistance(c[@embeddingKey], @embeddings)" # Add limit_offset_clause if specified if pre_filter is not None and pre_filter.get("limit_offset_clause") is not None: diff --git a/libs/community/langchain_community/vectorstores/neo4j_vector.py b/libs/community/langchain_community/vectorstores/neo4j_vector.py index a17444c6907a2..7f7f3f97dd875 100644 --- a/libs/community/langchain_community/vectorstores/neo4j_vector.py +++ b/libs/community/langchain_community/vectorstores/neo4j_vector.py @@ -890,7 +890,7 @@ def add_embeddings( import_query = ( "UNWIND $data AS row " - "CALL { WITH row " + "CALL (row) { WITH row " f"MERGE (c:`{self.node_label}` {{id: row.id}}) " "WITH c, row " f"CALL db.create.setNodeVectorProperty(c, " diff --git a/libs/community/poetry.lock b/libs/community/poetry.lock index 91abf5461a03b..beeae92b1e4c9 100644 --- a/libs/community/poetry.lock +++ b/libs/community/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -356,21 +356,20 @@ lxml = ["lxml"] [[package]] name = "bleach" -version = "6.1.0" +version = "6.2.0" description = "An easy safelist-based HTML-sanitizing tool." optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "bleach-6.1.0-py3-none-any.whl", hash = "sha256:3225f354cfc436b9789c66c4ee030194bee0568fbf9cbdad3bc8b5c26c5f12b6"}, - {file = "bleach-6.1.0.tar.gz", hash = "sha256:0a31f1837963c41d46bbf1331b8778e1308ea0791db03cc4e7357b97cf42a8fe"}, + {file = "bleach-6.2.0-py3-none-any.whl", hash = "sha256:117d9c6097a7c3d22fd578fcd8d35ff1e125df6736f554da4e432fdd63f31e5e"}, + {file = "bleach-6.2.0.tar.gz", hash = "sha256:123e894118b8a599fd80d3ec1a6d4cc7ce4e5882b1317a7e1ba69b56e95f991f"}, ] [package.dependencies] -six = ">=1.9.0" webencodings = "*" [package.extras] -css = ["tinycss2 (>=1.1.0,<1.3)"] +css = ["tinycss2 (>=1.1.0,<1.5)"] [[package]] name = "certifi" @@ -1748,13 +1747,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (> [[package]] name = "jupyterlab" -version = "4.2.5" +version = "4.3.0" description = "JupyterLab computational environment" optional = false python-versions = ">=3.8" files = [ - {file = "jupyterlab-4.2.5-py3-none-any.whl", hash = "sha256:73b6e0775d41a9fee7ee756c80f58a6bed4040869ccc21411dc559818874d321"}, - {file = "jupyterlab-4.2.5.tar.gz", hash = "sha256:ae7f3a1b8cb88b4f55009ce79fa7c06f99d70cd63601ee4aa91815d054f46f75"}, + {file = "jupyterlab-4.3.0-py3-none-any.whl", hash = "sha256:f67e1095ad61ae04349024f0b40345062ab108a0c6998d9810fec6a3c1a70cd5"}, + {file = "jupyterlab-4.3.0.tar.gz", hash = "sha256:7c6835cbf8df0af0ec8a39332e85ff11693fb9a468205343b4fc0bfbc74817e5"}, ] [package.dependencies] @@ -1775,9 +1774,9 @@ tornado = ">=6.2.0" traitlets = "*" [package.extras] -dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.3.5)"] -docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"] -docs-screenshots = ["altair (==5.3.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.2)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.1.post2)", "matplotlib (==3.8.3)", "nbconvert (>=7.0.0)", "pandas (==2.2.1)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"] +dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.6.9)"] +docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<8.1.0)", "sphinx-copybutton"] +docs-screenshots = ["altair (==5.4.1)", "ipython (==8.16.1)", "ipywidgets (==8.1.5)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.2.post3)", "matplotlib (==3.9.2)", "nbconvert (>=7.0.0)", "pandas (==2.2.3)", "scipy (==1.14.1)", "vega-datasets (==0.9.0)"] test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"] upgrade-extension = ["copier (>=9,<10)", "jinja2-time (<0.3)", "pydantic (<3.0)", "pyyaml-include (<3.0)", "tomli-w (<2.0)"] @@ -1841,7 +1840,7 @@ develop = true [package.dependencies] aiohttp = "^3.8.3" async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""} -langchain-core = "^0.3.14" +langchain-core = "^0.3.15" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" numpy = [ @@ -1860,7 +1859,7 @@ url = "../langchain" [[package]] name = "langchain-core" -version = "0.3.14" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -1894,7 +1893,7 @@ develop = true [package.dependencies] httpx = "^0.27.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" pytest = ">=7,<9" syrupy = "^4" @@ -1912,7 +1911,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" [package.source] type = "directory" @@ -1920,13 +1919,13 @@ url = "../text-splitters" [[package]] name = "langsmith" -version = "0.1.137" +version = "0.1.138" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.137-py3-none-any.whl", hash = "sha256:4256d5c61133749890f7b5c88321dbb133ce0f440c621ea28e76513285859b81"}, - {file = "langsmith-0.1.137.tar.gz", hash = "sha256:56cdfcc6c74cb20a3f437d5bd144feb5bf93f54c5a2918d1e568cbd084a372d4"}, + {file = "langsmith-0.1.138-py3-none-any.whl", hash = "sha256:5c2bd5c11c75f7b3d06a0f06b115186e7326ca969fd26d66ffc65a0669012aee"}, + {file = "langsmith-0.1.138.tar.gz", hash = "sha256:1ecf613bb52f6bf17f1510e24ad8b70d4b0259bc9d3dbfd69b648c66d4644f0b"}, ] [package.dependencies] @@ -2347,26 +2346,26 @@ files = [ [[package]] name = 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-content-hash = "6a739a5552965a20315aaed5985fb53cf1954af2483c98ea6ef86c6ff823dbc0" +content-hash = "0179027f05f5159e95267551c013cac474abd3e9f137399f715835b3070d9c33" diff --git a/libs/community/pyproject.toml b/libs/community/pyproject.toml index e5da0953f1b19..822c2b7b94995 100644 --- a/libs/community/pyproject.toml +++ b/libs/community/pyproject.toml @@ -1,10 +1,10 @@ [build-system] -requires = ["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-community" -version = "0.3.4" +version = "0.3.5" description = "Community contributed LangChain integrations." authors = [] license = "MIT" @@ -12,15 +12,12 @@ readme = "README.md" repository = "https://github.com/langchain-ai/langchain" [tool.ruff] -exclude = [ - "tests/examples/non-utf8-encoding.py", - "tests/integration_tests/examples/non-utf8-encoding.py", -] +exclude = [ "tests/examples/non-utf8-encoding.py", "tests/integration_tests/examples/non-utf8-encoding.py",] [tool.mypy] ignore_missing_imports = "True" disallow_untyped_defs = "True" -exclude = ["notebooks", "examples", "example_data"] +exclude = [ "notebooks", "examples", "example_data",] [tool.codespell] skip = ".git,*.pdf,*.svg,*.pdf,*.yaml,*.ipynb,poetry.lock,*.min.js,*.css,package-lock.json,example_data,_dist,examples,*.trig" @@ -33,9 +30,9 @@ ignore-words-list = "momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogy [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.14" +langchain-core = "^0.3.15" langchain = "^0.3.6" -SQLAlchemy = ">=1.4,<3" +SQLAlchemy = ">=1.4,<2.0.36" requests = "^2" PyYAML = ">=5.3" aiohttp = "^3.8.3" @@ -44,7 +41,6 @@ dataclasses-json = ">= 0.5.7, < 0.7" pydantic-settings = "^2.4.0" langsmith = "^0.1.125" httpx-sse = "^0.4.0" - [[tool.poetry.dependencies.numpy]] version = "^1" python = "<3.12" @@ -54,24 +50,16 @@ version = "^1.26.0" python = ">=3.12" [tool.ruff.lint] -select = ["E", "F", "I", "T201"] +select = [ "E", "F", "I", "T201",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--strict-markers --strict-config --durations=5 --snapshot-warn-unused -vv" -markers = [ - "requires: mark tests as requiring a specific library", - "scheduled: mark tests to run in scheduled testing", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "scheduled: mark tests to run in scheduled testing", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" -filterwarnings = [ - "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", - "ignore::langchain_core._api.deprecation.LangChainDeprecationWarning:test", - "ignore::langchain_core._api.deprecation.LangChainPendingDeprecationWarning:test", -] +filterwarnings = [ "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", "ignore::langchain_core._api.deprecation.LangChainDeprecationWarning:test", "ignore::langchain_core._api.deprecation.LangChainPendingDeprecationWarning:test",] [tool.poetry.group.test] optional = true @@ -103,12 +91,13 @@ pytest-mock = "^3.10.0" pytest-socket = "^0.6.0" syrupy = "^4.0.2" requests-mock = "^1.11.0" -# TODO: hack to fix 3.9 builds -cffi = [ - { version = "<1.17.1", python = "<3.10" }, - { version = "*", python = ">=3.10" }, -] +[[tool.poetry.group.test.dependencies.cffi]] +version = "<1.17.1" +python = "<3.10" +[[tool.poetry.group.test.dependencies.cffi]] +version = "*" +python = ">=3.10" [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" @@ -119,12 +108,13 @@ vcrpy = "^6" [tool.poetry.group.lint.dependencies] ruff = "^0.5" -# TODO: hack to fix 3.9 builds -cffi = [ - { version = "<1.17.1", python = "<3.10" }, - { version = "*", python = ">=3.10" }, -] +[[tool.poetry.group.lint.dependencies.cffi]] +version = "<1.17.1" +python = "<3.10" +[[tool.poetry.group.lint.dependencies.cffi]] +version = "*" +python = ">=3.10" [tool.poetry.group.dev.dependencies] jupyter = "^1.0.0" diff --git a/libs/community/tests/examples/hello_world.m4a b/libs/community/tests/examples/hello_world.m4a new file mode 100644 index 0000000000000..959ddd19aa63a Binary files /dev/null and b/libs/community/tests/examples/hello_world.m4a differ diff --git a/libs/community/tests/unit_tests/document_loaders/parsers/test_azure_whisper_parser.py b/libs/community/tests/unit_tests/document_loaders/parsers/test_azure_whisper_parser.py new file mode 100644 index 0000000000000..d48970534c1db --- /dev/null +++ b/libs/community/tests/unit_tests/document_loaders/parsers/test_azure_whisper_parser.py @@ -0,0 +1,104 @@ +"""Tests for the Azure OpenAI Whisper parser.""" + +from pathlib import Path +from typing import Any +from unittest.mock import Mock, patch + +import pytest +from langchain_core.documents import Document +from langchain_core.documents.base import Blob + +from langchain_community.document_loaders.parsers.audio import AzureOpenAIWhisperParser + +_THIS_DIR = Path(__file__).parents[3] + +_EXAMPLES_DIR = _THIS_DIR / "examples" +AUDIO_M4A = _EXAMPLES_DIR / "hello_world.m4a" + + +@pytest.mark.requires("openai") +@patch("openai.AzureOpenAI") +def test_azure_openai_whisper(mock_client: Mock) -> None: + endpoint = "endpoint" + key = "key" + version = "115" + name = "model" + + parser = AzureOpenAIWhisperParser( + api_key=key, azure_endpoint=endpoint, api_version=version, deployment_name=name + ) + mock_client.assert_called_once_with( + api_key=key, + azure_endpoint=endpoint, + api_version=version, + max_retries=3, + azure_ad_token=None, + ) + assert parser._client == mock_client() + + +@pytest.mark.requires("openai") +def test_is_openai_v1_lazy_parse(mocker: Any) -> None: + endpoint = "endpoint" + key = "key" + version = "115" + name = "model" + + mock_blob = mocker.Mock(spec=Blob) + mock_blob.path = AUDIO_M4A + mock_blob.source = "test_source" + + mock_openai_client = mocker.Mock() + + mock_openai_client.audio.transcriptions.create.return_value = mocker.Mock() + mock_openai_client.audio.transcriptions.create.return_value.text = ( + "Transcribed text" + ) + + mocker.patch("langchain_community.utils.openai.is_openai_v1", return_value=True) + + parser = AzureOpenAIWhisperParser( + api_key=key, azure_endpoint=endpoint, api_version=version, deployment_name=name + ) + + parser._client = mock_openai_client + + result = list(parser.lazy_parse(mock_blob)) + + assert len(result) == 1 + assert isinstance(result[0], Document) + assert result[0].page_content == "Transcribed text" + assert result[0].metadata["source"] == "test_source" + + +@pytest.mark.requires("openai") +def test_is_not_openai_v1_lazy_parse(mocker: Any) -> None: + endpoint = "endpoint" + key = "key" + version = "115" + name = "model" + + mock_blob = mocker.Mock(spec=Blob) + mock_blob.path = AUDIO_M4A + mock_blob.source = "test_source" + + mock_openai_client = mocker.Mock() + + mock_openai_client.audio.transcriptions.create.return_value = mocker.Mock() + mock_openai_client.audio.transcriptions.create.return_value.text = ( + "Transcribed text" + ) + + mocker.patch("langchain_community.utils.openai.is_openai_v1", return_value=False) + + parser = AzureOpenAIWhisperParser( + api_key=key, azure_endpoint=endpoint, api_version=version, deployment_name=name + ) + parser._client = mock_openai_client + + result = list(parser.lazy_parse(mock_blob)) + + assert len(result) == 1 + assert isinstance(result[0], Document) + assert result[0].page_content == "Transcribed text" + assert result[0].metadata["source"] == "test_source" diff --git a/libs/core/langchain_core/callbacks/manager.py b/libs/core/langchain_core/callbacks/manager.py index 58340be1ed9a0..9a25734f9371f 100644 --- a/libs/core/langchain_core/callbacks/manager.py +++ b/libs/core/langchain_core/callbacks/manager.py @@ -2502,7 +2502,8 @@ async def foo(inputs): ): print(event) - .. warning: If using python <= 3.10 and async, you MUST + .. warning:: + If using python <= 3.10 and async, you MUST specify the `config` parameter or the function will raise an error. This is due to a limitation in asyncio for python <= 3.10 that prevents LangChain from automatically propagating the config object on the user's diff --git a/libs/core/langchain_core/indexing/api.py b/libs/core/langchain_core/indexing/api.py index ab729314cfc99..c310deb241516 100644 --- a/libs/core/langchain_core/indexing/api.py +++ b/libs/core/langchain_core/indexing/api.py @@ -484,7 +484,7 @@ async def aindex( docs_source: Data loader or iterable of documents to index. record_manager: Timestamped set to keep track of which documents were updated. - vectorstore: Vector store or Document Index to index the documents into + vector_store: VectorStore or DocumentIndex to index the documents into. batch_size: Batch size to use when indexing. Default is 100. cleanup: How to handle clean up of documents. Default is None. - Incremental: Cleans up all documents that haven't been updated AND diff --git a/libs/core/langchain_core/output_parsers/list.py b/libs/core/langchain_core/output_parsers/list.py index 858ba86c79fa2..ebaca8f8ca94f 100644 --- a/libs/core/langchain_core/output_parsers/list.py +++ b/libs/core/langchain_core/output_parsers/list.py @@ -1,9 +1,11 @@ from __future__ import annotations +import csv import re from abc import abstractmethod from collections import deque from collections.abc import AsyncIterator, Iterator +from io import StringIO from typing import Optional as Optional from typing import TypeVar, Union @@ -162,7 +164,14 @@ def parse(self, text: str) -> list[str]: Returns: A list of strings. """ - return [part.strip() for part in text.split(",")] + try: + reader = csv.reader( + StringIO(text), quotechar='"', delimiter=",", skipinitialspace=True + ) + return [item for sublist in reader for item in sublist] + except csv.Error: + # keep old logic for backup + return [part.strip() for part in text.split(",")] @property def _type(self) -> str: diff --git a/libs/core/langchain_core/prompts/image.py b/libs/core/langchain_core/prompts/image.py index 9336e20f60ac5..334e2b85aee1c 100644 --- a/libs/core/langchain_core/prompts/image.py +++ b/libs/core/langchain_core/prompts/image.py @@ -9,7 +9,6 @@ PromptTemplateFormat, ) from langchain_core.runnables import run_in_executor -from langchain_core.utils import image as image_utils class ImagePromptTemplate(BasePromptTemplate[ImageURL]): @@ -80,8 +79,8 @@ def format( A formatted string. Raises: - ValueError: If the url or path is not provided. - ValueError: If the path or url is not a string. + ValueError: If the url is not provided. + ValueError: If the url is not a string. Example: @@ -98,23 +97,24 @@ def format( else: formatted[k] = v url = kwargs.get("url") or formatted.get("url") - path = kwargs.get("path") or formatted.get("path") - detail = kwargs.get("detail") or formatted.get("detail") - if not url and not path: - msg = "Must provide either url or path." + if kwargs.get("path") or formatted.get("path"): + msg = ( + "Loading images from 'path' has been removed as of 0.3.15 for security " + "reasons. Please specify images by 'url'." + ) raise ValueError(msg) + detail = kwargs.get("detail") or formatted.get("detail") if not url: - if not isinstance(path, str): - msg = "path must be a string." - raise ValueError(msg) - url = image_utils.image_to_data_url(path) - if not isinstance(url, str): + msg = "Must provide url." + raise ValueError(msg) + elif not isinstance(url, str): msg = "url must be a string." raise ValueError(msg) - output: ImageURL = {"url": url} - if detail: - # Don't check literal values here: let the API check them - output["detail"] = detail # type: ignore[typeddict-item] + else: + output: ImageURL = {"url": url} + if detail: + # Don't check literal values here: let the API check them + output["detail"] = detail # type: ignore[typeddict-item] return output async def aformat(self, **kwargs: Any) -> ImageURL: @@ -127,7 +127,6 @@ async def aformat(self, **kwargs: Any) -> ImageURL: A formatted string. Raises: - ValueError: If the url or path is not provided. ValueError: If the path or url is not a string. """ return await run_in_executor(None, self.format, **kwargs) diff --git a/libs/core/langchain_core/runnables/graph.py b/libs/core/langchain_core/runnables/graph.py index fd2c8adb98b23..2cb57c4e0fec5 100644 --- a/libs/core/langchain_core/runnables/graph.py +++ b/libs/core/langchain_core/runnables/graph.py @@ -1,7 +1,7 @@ from __future__ import annotations import inspect -from collections import Counter +from collections import defaultdict from collections.abc import Sequence from dataclasses import dataclass, field from enum import Enum @@ -423,12 +423,19 @@ def prefixed(id: str) -> str: def reid(self) -> Graph: """Return a new graph with all nodes re-identified, using their unique, readable names where possible.""" - node_labels = {node.id: node.name for node in self.nodes.values()} - node_label_counts = Counter(node_labels.values()) + node_name_to_ids = defaultdict(list) + for node in self.nodes.values(): + node_name_to_ids[node.name].append(node.id) + + unique_labels = { + node_id: node_name if len(node_ids) == 1 else f"{node_name}_{i + 1}" + for node_name, node_ids in node_name_to_ids.items() + for i, node_id in enumerate(node_ids) + } def _get_node_id(node_id: str) -> str: - label = node_labels[node_id] - if is_uuid(node_id) and node_label_counts[label] == 1: + label = unique_labels[node_id] + if is_uuid(node_id): return label else: return node_id diff --git a/libs/core/langchain_core/utils/image.py b/libs/core/langchain_core/utils/image.py index 708f0c7fdea55..f46ee599d32c6 100644 --- a/libs/core/langchain_core/utils/image.py +++ b/libs/core/langchain_core/utils/image.py @@ -1,29 +1,13 @@ -import base64 -import mimetypes - - -def encode_image(image_path: str) -> str: - """Get base64 string from image URI. - - Args: - image_path: The path to the image. - - Returns: - The base64 string of the image. - """ - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode("utf-8") - - -def image_to_data_url(image_path: str) -> str: - """Get data URL from image URI. - - Args: - image_path: The path to the image. - - Returns: - The data URL of the image. - """ - encoding = encode_image(image_path) - mime_type = mimetypes.guess_type(image_path)[0] - return f"data:{mime_type};base64,{encoding}" +from typing import Any + + +def __getattr__(name: str) -> Any: + if name in ("encode_image", "image_to_data_url"): + msg = ( + f"'{name}' has been removed for security reasons.\n\n" + f"Usage of this utility in environments with user-input paths is a " + f"security vulnerability. Out of an abundance of caution, the utility " + f"has been removed to prevent possible misuse." + ) + raise ValueError(msg) + raise AttributeError(name) diff --git a/libs/core/pyproject.toml b/libs/core/pyproject.toml index 402ba2c237a96..3e01a13364031 100644 --- a/libs/core/pyproject.toml +++ b/libs/core/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-core" -version = "0.3.14" +version = "0.3.15" description = "Building applications with LLMs through composability" authors = [] license = "MIT" diff --git a/libs/core/tests/unit_tests/output_parsers/test_list_parser.py b/libs/core/tests/unit_tests/output_parsers/test_list_parser.py index 3f43edfa2aed8..11bd11b6a0b92 100644 --- a/libs/core/tests/unit_tests/output_parsers/test_list_parser.py +++ b/libs/core/tests/unit_tests/output_parsers/test_list_parser.py @@ -64,6 +64,25 @@ def test_multiple_items() -> None: assert list(parser.transform(iter([text]))) == [[a] for a in expected] +def test_multiple_items_with_comma() -> None: + """Test that a string with multiple comma-separated items with 1 item containing a + comma is parsed to a list.""" + parser = CommaSeparatedListOutputParser() + text = '"foo, foo2",bar,baz' + expected = ["foo, foo2", "bar", "baz"] + + assert parser.parse(text) == expected + assert add(parser.transform(t for t in text)) == expected + assert list(parser.transform(t for t in text)) == [[a] for a in expected] + assert list(parser.transform(t for t in text.splitlines(keepends=True))) == [ + [a] for a in expected + ] + assert list( + parser.transform(" " + t if i > 0 else t for i, t in enumerate(text.split(" "))) + ) == [[a] for a in expected] + assert list(parser.transform(iter([text]))) == [[a] for a in expected] + + def test_numbered_list() -> None: parser = NumberedListOutputParser() text1 = ( diff --git a/libs/core/tests/unit_tests/prompts/test_chat.py b/libs/core/tests/unit_tests/prompts/test_chat.py index eee1ac498ec47..8038281b58d2a 100644 --- a/libs/core/tests/unit_tests/prompts/test_chat.py +++ b/libs/core/tests/unit_tests/prompts/test_chat.py @@ -719,7 +719,7 @@ async def test_chat_tmpl_from_messages_multipart_image() -> None: async def test_chat_tmpl_from_messages_multipart_formatting_with_path() -> None: - """Verify that we can pass `path` for an image as a variable.""" + """Verify that we cannot pass `path` for an image as a variable.""" in_mem = "base64mem" in_file_data = "base64file01" @@ -746,35 +746,19 @@ async def test_chat_tmpl_from_messages_multipart_formatting_with_path() -> None: ), ] ) - expected = [ - SystemMessage(content="You are an AI assistant named R2D2."), - HumanMessage( - content=[ - {"type": "text", "text": "What's in this image?"}, - { - "type": "image_url", - "image_url": {"url": f"data:image/jpeg;base64,{in_mem}"}, - }, - { - "type": "image_url", - "image_url": {"url": f"data:image/jpeg;base64,{in_file_data}"}, - }, - ] - ), - ] - messages = template.format_messages( - name="R2D2", - in_mem=in_mem, - file_path=temp_file.name, - ) - assert messages == expected + with pytest.raises(ValueError): + template.format_messages( + name="R2D2", + in_mem=in_mem, + file_path=temp_file.name, + ) - messages = await template.aformat_messages( - name="R2D2", - in_mem=in_mem, - file_path=temp_file.name, - ) - assert messages == expected + with pytest.raises(ValueError): + await template.aformat_messages( + name="R2D2", + in_mem=in_mem, + file_path=temp_file.name, + ) def test_messages_placeholder() -> None: diff --git a/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr b/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr index ba9d742b37407..208bdbac45e7f 100644 --- a/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr +++ b/libs/core/tests/unit_tests/runnables/__snapshots__/test_graph.ambr @@ -26,6 +26,20 @@ ''' # --- +# name: test_graph_mermaid_duplicate_nodes[mermaid] + ''' + graph TD; + PromptInput --> PromptTemplate_1; + Parallel_llm1_llm2_Input --> FakeListLLM_1; + FakeListLLM_1 --> Parallel_llm1_llm2_Output; + Parallel_llm1_llm2_Input --> FakeListLLM_2; + FakeListLLM_2 --> Parallel_llm1_llm2_Output; + PromptTemplate_1 --> Parallel_llm1_llm2_Input; + PromptTemplate_2 --> PromptTemplateOutput; + Parallel_llm1_llm2_Output --> PromptTemplate_2; + + ''' +# --- # name: test_graph_sequence[ascii] ''' +-------------+ diff --git a/libs/core/tests/unit_tests/runnables/test_graph.py b/libs/core/tests/unit_tests/runnables/test_graph.py index 8898b64c01fae..39f2f2871a800 100644 --- a/libs/core/tests/unit_tests/runnables/test_graph.py +++ b/libs/core/tests/unit_tests/runnables/test_graph.py @@ -405,3 +405,17 @@ def test_graph_mermaid_escape_node_label() -> None: assert _escape_node_label("foo-bar") == "foo-bar" assert _escape_node_label("foo_1") == "foo_1" assert _escape_node_label("#foo*&!") == "_foo___" + + +def test_graph_mermaid_duplicate_nodes(snapshot: SnapshotAssertion) -> None: + fake_llm = FakeListLLM(responses=["foo", "bar"]) + sequence: Runnable = ( + PromptTemplate.from_template("Hello, {input}") + | { + "llm1": fake_llm, + "llm2": fake_llm, + } + | PromptTemplate.from_template("{llm1} {llm2}") + ) + graph = sequence.get_graph() + assert graph.draw_mermaid(with_styles=False) == snapshot(name="mermaid") diff --git a/libs/langchain/langchain/agents/react/agent.py b/libs/langchain/langchain/agents/react/agent.py index faf86789ce117..137263a5db973 100644 --- a/libs/langchain/langchain/agents/react/agent.py +++ b/libs/langchain/langchain/agents/react/agent.py @@ -27,6 +27,12 @@ def create_react_agent( Based on paper "ReAct: Synergizing Reasoning and Acting in Language Models" (https://arxiv.org/abs/2210.03629) + .. warning:: + This implementation is based on the foundational ReAct paper but is older and not well-suited for production applications. + For a more robust and feature-rich implementation, we recommend using the `create_react_agent` function from the LangGraph library. + See the [reference doc](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent) + for more information. + Args: llm: LLM to use as the agent. tools: Tools this agent has access to. diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index bc6600b5932e9..3ceb6d136b1bc 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -1988,7 +1988,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.14" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -2013,7 +2013,7 @@ url = "../core" [[package]] name = "langchain-openai" -version = "0.2.4" +version = "0.2.5" description = "An integration package connecting OpenAI and LangChain" optional = true python-versions = ">=3.9,<4.0" @@ -2021,7 +2021,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" openai = "^1.52.0" tiktoken = ">=0.7,<1" @@ -2058,7 +2058,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" [package.source] type = "directory" @@ -4073,14 +4073,61 @@ description = "Database Abstraction Library" optional = false python-versions = ">=3.7" files = [ + {file = 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"sha256:8fbd4be412e8a7f35f623dd61034e6380a1c8dbd0edf6e87277a3289f6e98093"}, + {file = "vcrpy-4.3.0.tar.gz", hash = "sha256:49c270ce67e826dba027d83e20d25b67a5885487697e97bca6dbdf53d750a0ac"}, +] + +[package.dependencies] +PyYAML = "*" +six = ">=1.5" +wrapt = "*" +yarl = "*" + [[package]] name = "vcrpy" version = "6.0.2" @@ -4567,10 +4590,7 @@ files = [ [package.dependencies] PyYAML = "*" -urllib3 = [ - {version = "<2", markers = "platform_python_implementation == \"PyPy\" or python_version < \"3.10\""}, - {version = "*", markers = "platform_python_implementation != \"PyPy\" and python_version >= \"3.10\""}, -] +urllib3 = {version = "*", markers = "platform_python_implementation != \"PyPy\" and python_version >= \"3.10\""} wrapt = "*" yarl = "*" @@ -4880,4 +4900,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "f426834916aac5361268adcaa2eee8ee310c3b1eb46b60b54a97334ef2c2a1da" +content-hash = "7d093bafda2acfc3eae68b365b8a9d3801ad77d6cd47aa8dd3cb8298e3168cb3" diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml index 4fe14479baeb8..79fb6cb232565 100644 --- a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain" -version = "0.3.6" +version = "0.3.7" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -33,7 +33,7 @@ langchain-server = "langchain.server:main" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.14" +langchain-core = "^0.3.15" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" pydantic = "^2.7.4" diff --git a/libs/packages.yml b/libs/packages.yml new file mode 100644 index 0000000000000..8f9a16d2f48bd --- /dev/null +++ b/libs/packages.yml @@ -0,0 +1,145 @@ +# this file is used to define the packages that are used in the project +# it is EXPERIMENTAL and may be removed in the future + +packages: + - name: langchain-core + repo: langchain-ai/langchain + path: libs/core + - name: langchain-text-splitters + repo: langchain-ai/langchain + path: libs/text-splitters + - name: langchain + repo: langchain-ai/langchain + path: libs/langchain + - name: langchain-community + repo: langchain-ai/langchain + path: libs/community + - name: langchain-experimental + repo: langchain-ai/langchain-experimental + path: libs/experimental + - name: langchain-cli + repo: langchain-ai/langchain + path: libs/cli + - name: langchain-ai21 + repo: langchain-ai/langchain-ai21 + path: libs/ai21 + - name: langchain-anthropic + repo: langchain-ai/langchain + path: libs/partners/anthropic + - name: langchain-chroma + repo: langchain-ai/langchain + path: libs/partners/chroma + - name: langchain-exa + repo: langchain-ai/langchain + path: libs/partners/exa + - name: langchain-fireworks + repo: langchain-ai/langchain + path: libs/partners/fireworks + - name: langchain-groq + repo: langchain-ai/langchain + path: libs/partners/groq + - name: langchain-huggingface + repo: langchain-ai/langchain + path: libs/partners/huggingface + - name: langchain-ibm + repo: langchain-ai/langchain + path: libs/partners/ibm + - name: langchain-milvus + repo: langchain-ai/langchain-milvus + path: libs/milvus + - name: langchain-mistralai + repo: langchain-ai/langchain + path: libs/partners/mistralai + - name: langchain-mongodb + repo: langchain-ai/langchain-mongodb + path: libs/mongodb + - name: langchain-nomic + repo: langchain-ai/langchain + path: libs/partners/nomic + - name: langchain-openai + repo: langchain-ai/langchain + path: libs/partners/openai + - name: langchain-pinecone + repo: langchain-ai/langchain + path: libs/partners/pinecone + - name: langchain-prompty + repo: langchain-ai/langchain + path: libs/partners/prompty + - name: langchain-qdrant + repo: langchain-ai/langchain + path: libs/partners/qdrant + - name: langchain-sema4 + repo: langchain-ai/langchain-sema4 + path: libs/sema4 + - name: langchain-together + repo: langchain-ai/langchain-together + path: libs/together + - name: langchain-upstage + repo: langchain-ai/langchain-upstage + path: libs/upstage + - name: langchain-voyageai + repo: langchain-ai/langchain + path: libs/partners/voyageai + - name: langchain-aws + repo: langchain-ai/langchain-aws + path: libs/aws + - name: langchain-astradb + repo: langchain-ai/langchain-datastax + path: libs/astradb + - name: langchain-google-genai + repo: langchain-ai/langchain-google + path: libs/genai + - name: langchain-google-vertexai + repo: langchain-ai/langchain-google + path: libs/vertexai + - name: langchain-google-community + repo: langchain-ai/langchain-google + path: libs/community + - name: langchain-weaviate + repo: langchain-ai/langchain-weaviate + path: libs/weaviate + - name: langchain-cohere + repo: langchain-ai/langchain-cohere + path: libs/cohere + - name: langchain-elasticsearch + repo: langchain-ai/langchain-elastic + path: libs/elasticsearch + - name: langchain-nvidia-ai-endpoints + repo: langchain-ai/langchain-nvidia + path: libs/ai-endpoints + - name: langchain-postgres + repo: langchain-ai/langchain-postgres + path: . + - name: langchain-redis + repo: langchain-ai/langchain-redis + path: libs/redis + - name: langchain-unstructured + repo: langchain-ai/langchain-unstructured + path: libs/unstructured + - name: langchain-azure-dynamic-sessions + repo: langchain-ai/langchain-azure + path: libs/azure-dynamic-sessions + - name: langchain-sqlserver + repo: langchain-ai/langchain-azure + path: libs/sqlserver + - name: langchain-cerebras + repo: langchain-ai/langchain-cerebras + path: libs/cerebras + - name: langchain-snowflake + repo: langchain-ai/langchain-snowflake + path: libs/snowflake + - name: langchain-databricks + repo: langchain-ai/langchain-databricks + path: libs/databricks + - name: langchain-ibm + repo: langchain-ai/langchain-ibm + path: libs/ibm + - name: langchain-couchbase + repo: langchain-ai/langchain + path: libs/partners/couchbase + - name: langchain-ollama + repo: langchain-ai/langchain + path: libs/partners/ollama + - name: langchain-box + repo: langchain-ai/langchain + path: libs/partners/box diff --git a/libs/partners/airbyte/.gitignore b/libs/partners/airbyte/.gitignore deleted file mode 100644 index bee8a64b79a99..0000000000000 --- a/libs/partners/airbyte/.gitignore +++ /dev/null @@ -1 +0,0 @@ -__pycache__ diff --git a/libs/partners/airbyte/LICENSE b/libs/partners/airbyte/LICENSE deleted file mode 100644 index fc0602feecdd6..0000000000000 --- a/libs/partners/airbyte/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2024 LangChain, Inc. - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/libs/partners/airbyte/Makefile b/libs/partners/airbyte/Makefile deleted file mode 100644 index 82e64b3839815..0000000000000 --- a/libs/partners/airbyte/Makefile +++ /dev/null @@ -1,59 +0,0 @@ -.PHONY: all format lint test tests integration_tests docker_tests help extended_tests - -# Default target executed when no arguments are given to make. -all: help - -# Define a variable for the test file path. -TEST_FILE ?= tests/unit_tests/ -integration_test integration_tests: TEST_FILE = tests/integration_tests/ - -test tests integration_test integration_tests: - poetry run pytest $(TEST_FILE) - -test_watch: - poetry run ptw --snapshot-update --now . -- -vv $(TEST_FILE) - - -###################### -# LINTING AND FORMATTING -###################### - -# Define a variable for Python and notebook files. -PYTHON_FILES=. -MYPY_CACHE=.mypy_cache -lint format: PYTHON_FILES=. -lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/airbyte --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$') -lint_package: PYTHON_FILES=langchain_airbyte -lint_tests: PYTHON_FILES=tests -lint_tests: MYPY_CACHE=.mypy_cache_test - -lint lint_diff lint_package lint_tests: - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff $(PYTHON_FILES) - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff - [ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE) - -format format_diff: - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I --fix $(PYTHON_FILES) - -spell_check: - poetry run codespell --toml pyproject.toml - -spell_fix: - poetry run codespell --toml pyproject.toml -w - -check_imports: $(shell find langchain_airbyte -name '*.py') - poetry run python ./scripts/check_imports.py $^ - -###################### -# HELP -###################### - -help: - @echo '----' - @echo 'check_imports - check imports' - @echo 'format - run code formatters' - @echo 'lint - run linters' - @echo 'test - run unit tests' - @echo 'tests - run unit tests' - @echo 'test TEST_FILE= - run all tests in file' diff --git a/libs/partners/airbyte/README.md b/libs/partners/airbyte/README.md deleted file mode 100644 index b5c5b5f67397d..0000000000000 --- a/libs/partners/airbyte/README.md +++ /dev/null @@ -1,27 +0,0 @@ -# langchain-airbyte - -This package contains the LangChain integration with Airbyte - -## Installation - -```bash -pip install -U langchain-airbyte -``` - -The integration package doesn't have any global environment variables that need to be -set, but some integrations (e.g. `source-github`) may need credentials passed in. - -## Document Loaders - -`AirbyteLoader` class exposes a single document loader for Airbyte sources. - -```python -from langchain_airbyte import AirbyteLoader - -loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 100}, -) -docs = loader.load() -``` diff --git a/libs/partners/airbyte/langchain_airbyte/__init__.py b/libs/partners/airbyte/langchain_airbyte/__init__.py deleted file mode 100644 index cf3c11697c025..0000000000000 --- a/libs/partners/airbyte/langchain_airbyte/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from langchain_airbyte.document_loaders import AirbyteLoader - -__all__ = ["AirbyteLoader"] diff --git a/libs/partners/airbyte/langchain_airbyte/document_loaders.py b/libs/partners/airbyte/langchain_airbyte/document_loaders.py deleted file mode 100644 index 08b1513d54cbc..0000000000000 --- a/libs/partners/airbyte/langchain_airbyte/document_loaders.py +++ /dev/null @@ -1,127 +0,0 @@ -"""Airbyte vector stores.""" - -from __future__ import annotations - -from typing import ( - TYPE_CHECKING, - Any, - AsyncIterator, - Dict, - Iterator, - List, - Mapping, - Optional, - TypeVar, -) - -import airbyte as ab -from langchain_core.documents import Document -from langchain_core.prompts import PromptTemplate -from langchain_core.runnables import run_in_executor -from langchain_core.vectorstores import VectorStore - -if TYPE_CHECKING: - from langchain_text_splitters import TextSplitter - -VST = TypeVar("VST", bound=VectorStore) - - -class AirbyteLoader: - """Airbyte Document Loader. - - Example: - .. code-block:: python - - from langchain_airbyte import AirbyteLoader - - loader = AirbyteLoader( - source="github", - stream="pull_requests", - ) - documents = loader.lazy_load() - """ - - def __init__( - self, - source: str, - stream: str, - *, - config: Optional[Dict] = None, - include_metadata: bool = True, - template: Optional[PromptTemplate] = None, - ): - self._airbyte_source = ab.get_source(source, config=config, streams=[stream]) - self._stream = stream - self._template = template - self._include_metadata = include_metadata - - def load(self) -> List[Document]: - """Load source data into Document objects.""" - return list(self.lazy_load()) - - def load_and_split( - self, text_splitter: Optional[TextSplitter] = None - ) -> List[Document]: - """Load Documents and split into chunks. Chunks are returned as Documents. - - Args: - text_splitter: TextSplitter instance to use for splitting documents. - Defaults to RecursiveCharacterTextSplitter. - - Returns: - List of Documents. - """ - - if text_splitter is None: - try: - from langchain_text_splitters import RecursiveCharacterTextSplitter - except ImportError as e: - raise ImportError( - "Unable to import from langchain_text_splitters. Please specify " - "text_splitter or install langchain_text_splitters with " - "`pip install -U langchain-text-splitters`." - ) from e - _text_splitter: TextSplitter = RecursiveCharacterTextSplitter() - else: - _text_splitter = text_splitter - docs = self.lazy_load() - return _text_splitter.split_documents(docs) - - def lazy_load(self) -> Iterator[Document]: - """A lazy loader for Documents.""" - # if no prompt template defined, use default airbyte documents - if not self._template: - for document in self._airbyte_source.get_documents(self._stream): - # convert airbyte document to langchain document - metadata = ( - {} - if not self._include_metadata - else { - **document.metadata, - "_last_modified": document.last_modified, - "_id": document.id, - } - ) - yield Document( - page_content=document.content, - metadata=metadata, - ) - else: - records: Iterator[Mapping[str, Any]] = self._airbyte_source.get_records( - self._stream - ) - for record in records: - metadata = {} if not self._include_metadata else dict(record) - 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-[tool.poetry.group.test] -optional = true - -[tool.poetry.group.test.dependencies] -pytest = "^7.4.3" -pytest-asyncio = "^0.23.2" -langchain-core = { path = "../../core", develop = true } - -[tool.poetry.group.codespell] -optional = true - -[tool.poetry.group.codespell.dependencies] -codespell = "^2.2.6" - -[tool.poetry.group.test_integration] -optional = true - -[tool.poetry.group.test_integration.dependencies] - -[tool.poetry.group.lint] -optional = true - -[tool.poetry.group.lint.dependencies] -ruff = "^0.1.8" - -[tool.poetry.group.typing.dependencies] -mypy = "^1.7.1" -langchain-core = { path = "../../core", develop = true } -langchain-text-splitters = { path = "../../text-splitters", develop = true } -langchain = { path = "../../langchain", develop = true } - -[tool.poetry.group.dev] -optional = true - -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } - -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -addopts = "--strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" diff --git a/libs/partners/airbyte/scripts/check_imports.py b/libs/partners/airbyte/scripts/check_imports.py deleted file mode 100644 index 58a460c149353..0000000000000 --- a/libs/partners/airbyte/scripts/check_imports.py +++ /dev/null @@ -1,17 +0,0 @@ -import sys -import traceback -from importlib.machinery import SourceFileLoader - -if __name__ == "__main__": - files = sys.argv[1:] - has_failure = False - for file in files: - try: - SourceFileLoader("x", file).load_module() - except Exception: - has_failure = True - print(file) # noqa: T201 - traceback.print_exc() - print() # noqa: T201 - - sys.exit(1 if has_failure else 0) diff --git a/libs/partners/airbyte/scripts/lint_imports.sh b/libs/partners/airbyte/scripts/lint_imports.sh deleted file mode 100755 index 19ccec1480c01..0000000000000 --- a/libs/partners/airbyte/scripts/lint_imports.sh +++ /dev/null @@ -1,18 +0,0 @@ -#!/bin/bash - -set -eu - -# Initialize a variable to keep track of errors -errors=0 - -# make sure not importing from langchain, langchain_experimental, or langchain_community -git --no-pager grep '^from langchain\.' . && errors=$((errors+1)) -git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1)) -git --no-pager grep '^from langchain_community\.' . && errors=$((errors+1)) - -# Decide on an exit status based on the errors -if [ "$errors" -gt 0 ]; then - exit 1 -else - exit 0 -fi diff --git a/libs/partners/airbyte/tests/__init__.py b/libs/partners/airbyte/tests/__init__.py deleted file mode 100644 index e69de29bb2d1d..0000000000000 diff --git a/libs/partners/airbyte/tests/integration_tests/__init__.py b/libs/partners/airbyte/tests/integration_tests/__init__.py deleted file mode 100644 index e69de29bb2d1d..0000000000000 diff --git a/libs/partners/airbyte/tests/integration_tests/test_compile.py b/libs/partners/airbyte/tests/integration_tests/test_compile.py deleted file mode 100644 index 33ecccdfa0fbd..0000000000000 --- a/libs/partners/airbyte/tests/integration_tests/test_compile.py +++ /dev/null @@ -1,7 +0,0 @@ -import pytest - - -@pytest.mark.compile -def test_placeholder() -> None: - """Used for compiling integration tests without running any real tests.""" - pass diff --git a/libs/partners/airbyte/tests/integration_tests/test_document_loaders.py b/libs/partners/airbyte/tests/integration_tests/test_document_loaders.py deleted file mode 100644 index 0c5008d85ea03..0000000000000 --- a/libs/partners/airbyte/tests/integration_tests/test_document_loaders.py +++ /dev/null @@ -1,28 +0,0 @@ -"""Test Airbyte embeddings.""" - -import os - -from langchain_airbyte import AirbyteLoader - -GITHUB_TOKEN = os.environ.get("GITHUB_TOKEN") - - -def test_load_github() -> None: - """Test loading from GitHub.""" - airbyte_loader = AirbyteLoader( - source="source-github", - stream="issues", - config={ - "repositories": ["airbytehq/quickstarts"], - "credentials": {"personal_access_token": GITHUB_TOKEN}, - }, - ) - documents = airbyte_loader.load() - assert len(documents) > 0 - # make sure some documents have body in metadata - found_body = False - for doc in documents: - if "body" in doc.metadata and doc.metadata["body"]: - found_body = True - break - assert found_body, "No documents with body found" diff --git a/libs/partners/airbyte/tests/unit_tests/__init__.py b/libs/partners/airbyte/tests/unit_tests/__init__.py deleted file mode 100644 index e69de29bb2d1d..0000000000000 diff --git a/libs/partners/airbyte/tests/unit_tests/test_document_loaders.py b/libs/partners/airbyte/tests/unit_tests/test_document_loaders.py deleted file mode 100644 index e97f4122685ab..0000000000000 --- a/libs/partners/airbyte/tests/unit_tests/test_document_loaders.py +++ /dev/null @@ -1,77 +0,0 @@ -from langchain_core.prompts import PromptTemplate - -from langchain_airbyte import AirbyteLoader - - -def test_initialization() -> None: - """Test integration loader initialization.""" - AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - ) - - -def test_load() -> None: - """Test loading from source.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 5}, - ) - documents = airbyte_loader.load() - assert len(documents) == 5 - - -def test_lazy_load() -> None: - """Test lazy loading from source.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - ) - documents = airbyte_loader.lazy_load() - assert len(list(documents)) == 3 - - -async def test_alazy_load() -> None: - """Test async lazy loading from source.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - ) - documents = airbyte_loader.alazy_load() - lendocs = 0 - async for _ in documents: - lendocs += 1 - assert lendocs == 3 - - -def test_load_with_template() -> None: - """Test loading from source with template.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - template=PromptTemplate.from_template("My name is {name}"), - ) - documents = airbyte_loader.load() - assert len(documents) == 3 - for doc in documents: - assert doc.page_content.startswith("My name is ") - assert doc.metadata["name"] # should have a name - - -def test_load_no_metadata() -> None: - """Test loading from source with no metadata.""" - airbyte_loader = AirbyteLoader( - source="source-faker", - stream="users", - config={"count": 3}, - include_metadata=False, - ) - documents = airbyte_loader.load() - assert len(documents) == 3 - for doc in documents: - assert doc.metadata == {} diff --git a/libs/partners/airbyte/tests/unit_tests/test_imports.py b/libs/partners/airbyte/tests/unit_tests/test_imports.py deleted file mode 100644 index 40a369414dd1b..0000000000000 --- a/libs/partners/airbyte/tests/unit_tests/test_imports.py +++ /dev/null @@ -1,9 +0,0 @@ -from langchain_airbyte import __all__ - -EXPECTED_ALL = [ - "AirbyteLoader", -] - - -def test_all_imports() -> None: - assert sorted(EXPECTED_ALL) == sorted(__all__) diff --git a/libs/partners/anthropic/langchain_anthropic/chat_models.py b/libs/partners/anthropic/langchain_anthropic/chat_models.py index c408cdc23d039..5a6ca4cc6b993 100644 --- a/libs/partners/anthropic/langchain_anthropic/chat_models.py +++ b/libs/partners/anthropic/langchain_anthropic/chat_models.py @@ -143,10 +143,12 @@ def _merge_messages( all(isinstance(m, c) for m in (curr, last)) for c in (SystemMessage, HumanMessage) ): - if isinstance(last.content, str): - new_content: List = [{"type": "text", "text": last.content}] + if isinstance(cast(BaseMessage, last).content, str): + new_content: List = [ + {"type": "text", "text": cast(BaseMessage, last).content} + ] else: - new_content = copy.copy(last.content) + new_content = copy.copy(cast(list, cast(BaseMessage, last).content)) if isinstance(curr.content, str): new_content.append({"type": "text", "text": curr.content}) else: diff --git a/libs/partners/anthropic/poetry.lock b/libs/partners/anthropic/poetry.lock index 5e783dda5a450..23fccaa9d3169 100644 --- a/libs/partners/anthropic/poetry.lock +++ b/libs/partners/anthropic/poetry.lock @@ -514,7 +514,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.9" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -530,7 +530,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -1333,4 +1333,4 @@ watchmedo = ["PyYAML (>=3.10)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "ff45241f112ccfe1ca845dfc9685f7b63d7cb0a362acffbb17d81ff4691af9d4" +content-hash = "f1cd6241802e9ee68050d69ed38775fa26182185984cc18b30f51595dba56330" diff --git a/libs/partners/anthropic/pyproject.toml b/libs/partners/anthropic/pyproject.toml index 83e32dbb03007..55c5b90e1b482 100644 --- a/libs/partners/anthropic/pyproject.toml +++ b/libs/partners/anthropic/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-anthropic" -version = "0.2.3" +version = "0.2.4" description = "An integration package connecting AnthropicMessages and LangChain" authors = [] readme = "README.md" @@ -21,7 +21,7 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" anthropic = ">=0.30.0,<1" -langchain-core = "^0.3.9" +langchain-core = "^0.3.15" pydantic = "^2.7.4" [tool.ruff.lint] diff --git a/libs/partners/box/poetry.lock b/libs/partners/box/poetry.lock index ff2f7db6dfc86..8589034ae40f9 100644 --- a/libs/partners/box/poetry.lock +++ b/libs/partners/box/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "annotated-types" @@ -459,7 +459,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.13" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -1099,4 +1099,4 @@ zstd = ["zstandard (>=0.18.0)"] [metadata] lock-version = "2.0" python-versions = ">=3.9.0,<3.13" -content-hash = "bd2a5266b1ec798a570e0e6aa5c9b5e255aa19d9d42565c9cab406326f794530" +content-hash = "c85860d3c2b38a4aeb9f1fe93aa25ee61d9a7cb7e5cda8006004d3f27ce8bdb5" diff --git a/libs/partners/box/pyproject.toml b/libs/partners/box/pyproject.toml index 8a1786cda1c89..8f454f4ee0122 100644 --- a/libs/partners/box/pyproject.toml +++ b/libs/partners/box/pyproject.toml @@ -1,93 +1,84 @@ +[build-system] +requires = [ "poetry-core>=1.0.0",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "langchain-box" -version = "0.2.2" +version = "0.2.3" description = "An integration package connecting Box and LangChain" authors = [] readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/box" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-box%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9.0,<3.13" -langchain-core = "^0.3.13" -box-sdk-gen = { extras = ["jwt"], version = "^1.5.0" } +langchain-core = "^0.3.15" pydantic = "^2" +[tool.ruff.lint] +select = [ "E", "F", "I", "T201",] + +[tool.coverage.run] +omit = [ "tests/*",] + +[tool.pytest.ini_options] +markers = [ "compile: mark placeholder test used to compile integration tests without running them",] +asyncio_mode = "auto" + +[tool.poetry.dependencies.box-sdk-gen] +extras = [ "jwt",] +version = "^1.5.0" + [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.4.3" pytest_mock = "^3.14.0" pytest-asyncio = "^0.23.2" pytest-socket = "^0.7.0" -langchain-core = { path = "../../core", develop = true } - -[tool.poetry.group.codespell] -optional = true [tool.poetry.group.codespell.dependencies] codespell = "^2.2.6" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] python-dotenv = "^1.0.1" -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.1.8" [tool.poetry.group.typing.dependencies] mypy = "^1.7.1" -langchain-core = { path = "../../core", develop = true } types-requests = "^2.32.0.20240712" -[tool.poetry.group.dev] -optional = true - -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } - -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] +[tool.poetry.group.test.dependencies.langchain-core] +path = "../../core" +develop = true -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" +[tool.poetry.group.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -# addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/partners/chroma/poetry.lock b/libs/partners/chroma/poetry.lock index 435c4533c7672..19729f51db44d 100644 --- a/libs/partners/chroma/poetry.lock +++ b/libs/partners/chroma/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "annotated-types" @@ -11,18 +11,15 @@ files = [ {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, ] -[package.dependencies] -typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""} - [[package]] name = "anyio" -version = "4.5.0" +version = "4.6.2.post1" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "anyio-4.5.0-py3-none-any.whl", hash = "sha256:fdeb095b7cc5a5563175eedd926ec4ae55413bb4be5770c424af0ba46ccb4a78"}, - {file = "anyio-4.5.0.tar.gz", hash = "sha256:c5a275fe5ca0afd788001f58fca1e69e29ce706d746e317d660e21f70c530ef9"}, + {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"}, + {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"}, ] [package.dependencies] @@ -33,7 +30,7 @@ typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} [package.extras] doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"] trio = ["trio (>=0.26.1)"] [[package]] @@ -308,13 +305,13 @@ numpy = "*" [[package]] name = "chromadb" -version = "0.5.13" +version = "0.5.17" description = "Chroma." optional = false python-versions = ">=3.8" files = [ - {file = "chromadb-0.5.13-py3-none-any.whl", hash = "sha256:090134cb8a9bd35622175a8a9bb93a7b56ace413697489e9d2f43a5299a6b7bc"}, - {file = "chromadb-0.5.13.tar.gz", hash = "sha256:fb1f44b5425976ef2bdf7403d365986ee5a224e5d8108fcd86472ff64de216a0"}, + {file = "chromadb-0.5.17-py3-none-any.whl", hash = "sha256:d1403b9f78678effdc42240759041272b4ead013ab205a16f656da923e542cae"}, + {file = "chromadb-0.5.17.tar.gz", hash = "sha256:6d744dbab036d48d83c2425d3459006022dbcbe9e428affb011c72c91af04a39"}, ] [package.dependencies] @@ -322,7 +319,6 @@ bcrypt = ">=4.0.1" build = ">=1.0.3" chroma-hnswlib = "0.7.6" fastapi = ">=0.95.2" -graphlib-backport = {version = ">=1.0.3", markers = "python_version < \"3.9\""} grpcio = ">=1.58.0" httpx = ">=0.27.0" importlib-resources = "*" @@ -451,18 +447,18 @@ test = ["pytest (>=6)"] [[package]] name = "fastapi" -version = "0.115.2" +version = "0.115.4" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" optional = false python-versions = ">=3.8" files = [ - {file = 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["pytest-mypy"] [metadata] lock-version = "2.0" -python-versions = ">=3.8.1,<4" -content-hash = "fb0291adcbf1f22fd16d20298665d5790734b3f334b4d8bbec8db24c12ba9c55" +python-versions = ">=3.9,<4" +content-hash = "2747536a10c5e463604c0ff0024055c186363e673fe755b01df356deb9800435" diff --git a/libs/partners/chroma/pyproject.toml b/libs/partners/chroma/pyproject.toml index fdde6826a455d..3fa59a97f74e3 100644 --- a/libs/partners/chroma/pyproject.toml +++ b/libs/partners/chroma/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-chroma" -version = "0.1.5" +version = "0.2.0" description = "An integration package connecting Chroma and LangChain" authors = [] readme = "README.md" @@ -19,14 +19,8 @@ disallow_untyped_defs = true "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-chroma%3D%3D0%22&expanded=true" [tool.poetry.dependencies] -python = ">=3.8.1,<4" -[[tool.poetry.dependencies.langchain-core]] 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python = ">=3.10"}] [tool.poetry.group.dev.dependencies] [[tool.poetry.group.dev.dependencies.langchain-core]] diff --git a/libs/partners/couchbase/poetry.lock b/libs/partners/couchbase/poetry.lock index 39ad5dce0b999..5931a6a913b83 100644 --- a/libs/partners/couchbase/poetry.lock +++ b/libs/partners/couchbase/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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a/libs/partners/exa/poetry.lock +++ b/libs/partners/exa/poetry.lock @@ -402,7 +402,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -411,14 +411,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -427,13 +427,13 @@ url = "../../core" [[package]] name = "langsmith" -version = "0.1.120" +version = "0.1.139" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"}, - {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"}, + {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, + {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, ] [package.dependencies] @@ -444,6 +444,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] requests = ">=2,<3" +requests-toolbelt = ">=1.0.0,<2.0.0" [[package]] name = "mypy" @@ -912,6 +913,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" 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["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-exa" -version = "0.2.0" +version = "0.2.1" description = "An integration package connecting Exa and LangChain" authors = [] readme = "README.md" @@ -20,21 +20,18 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" exa-py = "^1.0.8" [tool.ruff.lint] -select = ["E", "F", "I", "T201"] +select = [ "E", "F", "I", "T201",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" [tool.poetry.group.test] diff --git a/libs/partners/fireworks/poetry.lock b/libs/partners/fireworks/poetry.lock index 5f42499337142..33b0cdf669c5a 100644 --- a/libs/partners/fireworks/poetry.lock +++ b/libs/partners/fireworks/poetry.lock @@ -670,7 +670,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.9" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -686,7 +686,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -1716,4 +1716,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "56f279717e189244fb82561676aac12e1be0d39400d261a1587302335563a091" +content-hash = 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"langchain-pinecone" -version = "0.2.0" +version = "0.2.1" description = "An integration package connecting Pinecone and LangChain" authors = [] readme = "README.md" @@ -20,10 +20,9 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<3.13" -langchain-core = "^0.3" +langchain-core = "^0.3.15" pinecone-client = "^5.0.0" aiohttp = ">=3.9.5,<3.10" - [[tool.poetry.dependencies.numpy]] version = "^1" python = "<3.12" @@ -33,17 +32,14 @@ version = "^1.26.0" python = ">=3.12" [tool.ruff.lint] -select = ["E", "F", "I", "T201"] +select = [ "E", "F", "I", "T201",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" [tool.poetry.group.test] diff --git a/libs/partners/prompty/poetry.lock b/libs/partners/prompty/poetry.lock index 5965576a6da19..3753802ecc0df 100644 --- a/libs/partners/prompty/poetry.lock +++ b/libs/partners/prompty/poetry.lock @@ -637,7 +637,7 @@ files = [ [[package]] name = "langchain" -version = "0.3.0" +version = "0.3.6" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -647,7 +647,7 @@ develop = true [package.dependencies] aiohttp = "^3.8.3" async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""} -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" numpy = [ @@ -658,7 +658,7 @@ pydantic = "^2.7.4" PyYAML = ">=5.3" requests = "^2" SQLAlchemy = ">=1.4,<3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10" [package.source] type = "directory" @@ -666,7 +666,7 @@ url = "../../langchain" [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -675,14 +675,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -691,7 +691,7 @@ url = "../../core" [[package]] name = "langchain-text-splitters" -version = "0.3.0" +version = "0.3.1" description = "LangChain text splitting utilities" optional = false python-versions = ">=3.9,<4.0" @@ -699,7 +699,7 @@ files = [] develop = true [package.dependencies] -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" [package.source] type = "directory" @@ -707,13 +707,13 @@ url = "../../text-splitters" [[package]] name = "langsmith" -version = "0.1.120" +version = "0.1.139" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"}, - {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"}, + {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, + {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, ] [package.dependencies] @@ -724,6 +724,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] requests = ">=2,<3" +requests-toolbelt = ">=1.0.0,<2.0.0" [[package]] name = "multidict" @@ -1320,6 +1321,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"}, + {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"}, +] + +[package.dependencies] +requests = ">=2.0.1,<3.0.0" + [[package]] name = "ruff" version = "0.1.15" @@ -1377,7 +1392,9 @@ python-versions = ">=3.7" files = [ {file = "SQLAlchemy-2.0.34-cp310-cp310-macosx_10_9_x86_64.whl", hash = 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+[tool.ruff] +select = [ "E", "F", "I",] + +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/prompty" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-prompty%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" pyyaml = "^6.0.1" +[tool.coverage.run] +omit = [ "tests/*",] + +[tool.pytest.ini_options] +addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them",] +asyncio_mode = "auto" + [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.3.0" freezegun = "^1.2.2" @@ -26,71 +56,38 @@ pytest-mock = "^3.10.0" syrupy = "^4.0.2" pytest-watcher = "^0.3.4" pytest-asyncio = "^0.21.1" -langchain-core = { path = "../../core", develop = true } -langchain = { path = "../../langchain", develop = true } -langchain-text-splitters = { path = "../../text-splitters", develop = true } - -[tool.poetry.group.codespell] -optional = true [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.1.5" -[tool.poetry.group.typing.dependencies] -mypy = "^0.991" +[tool.poetry.group.dev.dependencies] types-pyyaml = "^6.0.12.20240311" -langchain-core = { path = "../../core", develop = true } - -[tool.poetry.group.dev] -optional = true -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } +[tool.poetry.group.typing.dependencies] +mypy = "^0.991" types-pyyaml = "^6.0.12.20240311" -[tool.ruff] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort -] +[tool.poetry.group.test.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.mypy] -disallow_untyped_defs = "True" +[tool.poetry.group.test.dependencies.langchain] +path = "../../langchain" +develop = true -[tool.coverage.run] -omit = ["tests/*"] +[tool.poetry.group.test.dependencies.langchain-text-splitters] +path = "../../text-splitters" +develop = true -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" +[tool.poetry.group.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/partners/voyageai/poetry.lock b/libs/partners/voyageai/poetry.lock index d807625792933..3f84762f35456 100644 --- a/libs/partners/voyageai/poetry.lock +++ b/libs/partners/voyageai/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -572,7 +572,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -581,14 +581,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -597,13 +597,13 @@ url = "../../core" [[package]] name = "langsmith" -version = "0.1.120" +version = "0.1.139" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"}, - {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"}, + {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, + {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, ] [package.dependencies] @@ -614,6 +614,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] requests = ">=2,<3" +requests-toolbelt = ">=1.0.0,<2.0.0" [[package]] name = "multidict" @@ -1207,6 +1208,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"}, + {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"}, +] + +[package.dependencies] +requests = ">=2.0.1,<3.0.0" + [[package]] name = "ruff" version = "0.1.15" @@ -1491,4 +1506,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "7743429cd1357000a4fe104cf06f7e7fd8207c318af580053965257bf858ab8e" +content-hash = "c037eee2ed1ce2ed484992fb08ee187a0db037bf8c84cf69d8715c7c62a59bfe" diff --git a/libs/partners/voyageai/pyproject.toml b/libs/partners/voyageai/pyproject.toml index 9b416f3ce5970..0193cc36d5e26 100644 --- a/libs/partners/voyageai/pyproject.toml +++ b/libs/partners/voyageai/pyproject.toml @@ -1,25 +1,55 @@ +[build-system] +requires = [ "poetry-core>=1.0.0",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "langchain-voyageai" -version = "0.1.2" +version = "0.1.3" description = "An integration package connecting VoyageAI and LangChain" authors = [] readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/voyageai" "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-voyageai%3D%3D0%22&expanded=true" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" voyageai = ">=0.2.1,<1" pydantic = ">=2,<3" +[tool.ruff.lint] +select = [ "E", "F", "I",] + +[tool.coverage.run] +omit = [ "tests/*",] + +[tool.pytest.ini_options] +addopts = "--strict-markers --strict-config --durations=5" +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them",] +asyncio_mode = "auto" + [tool.poetry.group.test] optional = true +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.dev] +optional = true + [tool.poetry.group.test.dependencies] pytest = "^7.3.0" freezegun = "^1.2.2" @@ -27,8 +57,6 @@ pytest-mock = "^3.10.0" syrupy = "^4.0.2" pytest-watcher = "^0.3.4" pytest-asyncio = "^0.21.1" -langchain-core = { path = "../../core", develop = true } - [[tool.poetry.group.test.dependencies.numpy]] version = "^1.24.0" python = "<3.12" @@ -37,65 +65,25 @@ python = "<3.12" version = "^1.26.0" python = ">=3.12" -[tool.poetry.group.codespell] -optional = true - [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" -[tool.poetry.group.test_integration] -optional = true - [tool.poetry.group.test_integration.dependencies] -[tool.poetry.group.lint] -optional = true - [tool.poetry.group.lint.dependencies] ruff = "^0.1.5" [tool.poetry.group.typing.dependencies] mypy = "^1.10" -langchain-core = { path = "../../core", develop = true } -[tool.poetry.group.dev] -optional = true +[tool.poetry.group.test.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } +[tool.poetry.group.dev.dependencies.langchain-core] +path = "../../core" +develop = true -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -addopts = "--strict-markers --strict-config --durations=5" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../../core" +develop = true diff --git a/libs/standard-tests/poetry.lock b/libs/standard-tests/poetry.lock index 67b5fee2313cb..8655b65aa7753 100644 --- a/libs/standard-tests/poetry.lock +++ b/libs/standard-tests/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "annotated-types" @@ -294,7 +294,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.0" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -303,14 +303,14 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.117" +langsmith = "^0.1.125" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] PyYAML = ">=5.3" -tenacity = "^8.1.0,!=8.4.0" +tenacity = ">=8.1.0,!=8.4.0,<10.0.0" typing-extensions = ">=4.7" [package.source] @@ -319,13 +319,13 @@ url = "../core" [[package]] name = "langsmith" -version = "0.1.120" +version = "0.1.139" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"}, - {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"}, + {file = "langsmith-0.1.139-py3-none-any.whl", hash = "sha256:2a4a541bfbd0a9727255df28a60048c85bc8c4c6a276975923785c3fd82dc879"}, + {file = "langsmith-0.1.139.tar.gz", hash = "sha256:2f9e4d32fef3ad7ef42c8506448cce3a31ad6b78bb4f3310db04ddaa1e9d744d"}, ] [package.dependencies] @@ -336,6 +336,7 @@ pydantic = [ {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, ] requests = ">=2,<3" +requests-toolbelt = ">=1.0.0,<2.0.0" [[package]] name = "mypy" @@ -737,6 +738,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"}, + {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"}, +] + +[package.dependencies] +requests = ">=2.0.1,<3.0.0" + [[package]] name = "ruff" version = "0.1.15" @@ -845,4 +860,4 @@ zstd = ["zstandard (>=0.18.0)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "ba5e8730ffc3c7a10aded2e9625abaa51299be5b5f499d946b1ccb8f78341eb7" +content-hash = "cb3804aa252eed812fd6dc0762ffb110d6b55046f7e691f3fe14080d8ab06b38" diff --git a/libs/standard-tests/pyproject.toml b/libs/standard-tests/pyproject.toml index 9c3201688a706..a3775ed9b3010 100644 --- a/libs/standard-tests/pyproject.toml +++ b/libs/standard-tests/pyproject.toml @@ -1,84 +1,70 @@ +[build-system] +requires = [ "poetry-core",] +build-backend = "poetry.core.masonry.api" + [tool.poetry] name = "langchain-standard-tests" version = "0.1.1" description = "Standard tests for LangChain implementations" -authors = ["Erick Friis "] +authors = [ "Erick Friis ",] readme = "README.md" repository = "https://github.com/langchain-ai/langchain" license = "MIT" +[tool.mypy] +disallow_untyped_defs = "True" + [tool.poetry.urls] "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/standard-tests" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.0" +langchain-core = "^0.3.15" pytest = ">=7,<9" httpx = "^0.27.0" syrupy = "^4" +[tool.ruff.lint] +select = [ "E", "F", "I", "T201",] + +[tool.coverage.run] +omit = [ "tests/*",] + +[tool.pytest.ini_options] +addopts = "--strict-markers --strict-config --durations=5 -vv" +markers = [ "requires: mark tests as requiring a specific library", "scheduled: mark tests to run in scheduled testing", "compile: mark placeholder test used to compile integration tests without running them",] +asyncio_mode = "auto" + [tool.poetry.group.test] optional = true -[tool.poetry.group.test.dependencies] -langchain-core = { path = "../core", develop = true } -pytest-asyncio = "^0.23.7" - [tool.poetry.group.test_integration] optional = true -[tool.poetry.group.test_integration.dependencies] - [tool.poetry.group.codespell] optional = true -[tool.poetry.group.codespell.dependencies] -codespell = "^2.2.0" - [tool.poetry.group.lint] optional = true +[tool.poetry.group.test.dependencies] +pytest-asyncio = "^0.23.7" + +[tool.poetry.group.test_integration.dependencies] + +[tool.poetry.group.codespell.dependencies] +codespell = "^2.2.0" + [tool.poetry.group.lint.dependencies] ruff = "^0.1.5" [tool.poetry.group.typing.dependencies] mypy = "^0.991" -langchain-core = { path = "../core", develop = true } -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort - "T201", # print -] +[tool.poetry.group.test.dependencies.langchain-core] +path = "../core" +develop = true -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.coverage.run] -omit = ["tests/*"] - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" - -[tool.pytest.ini_options] -# --strict-markers will raise errors on unknown marks. -# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks -# -# https://docs.pytest.org/en/7.1.x/reference/reference.html -# --strict-config any warnings encountered while parsing the `pytest` -# section of the configuration file raise errors. -# -# https://github.com/tophat/syrupy -# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. -addopts = "--strict-markers --strict-config --durations=5 -vv" -# Registering custom markers. -# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers -markers = [ - "requires: mark tests as requiring a specific library", - "scheduled: mark tests to run in scheduled testing", - "compile: mark placeholder test used to compile integration tests without running them", -] -asyncio_mode = "auto" +[tool.poetry.group.typing.dependencies.langchain-core] +path = "../core" +develop = true diff --git a/libs/text-splitters/poetry.lock b/libs/text-splitters/poetry.lock index 00296208416dd..ff73e1b8838ee 100644 --- a/libs/text-splitters/poetry.lock +++ b/libs/text-splitters/poetry.lock @@ -1170,7 +1170,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.13" +version = "0.3.15" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -2980,4 +2980,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "985bbcb3e82965a3b68764c90270cece172f6a3a825e5e08644d4df63049cb44" +content-hash = "1ca2ffa7cad6f306bdedb6aa3497597cd0292172c6a2a48684881cd344458598" diff --git a/libs/text-splitters/pyproject.toml b/libs/text-splitters/pyproject.toml index f880c8a74c943..c4c8a7535860e 100644 --- a/libs/text-splitters/pyproject.toml +++ b/libs/text-splitters/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-text-splitters" -version = "0.3.1" +version = "0.3.2" description = "LangChain text splitting utilities" authors = [] license = "MIT" @@ -23,7 +23,7 @@ ignore_missing_imports = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.13" +langchain-core = "^0.3.15" [tool.ruff.lint] select = [ "E", "F", "I", "T201",]