langchain

Commit Graph

Author	SHA1	Message	Date
Corey Zumar	3a068b26f3	community[patch]: Databricks - fix scope of dangerous deserialization error in Databricks LLM connector (#20368 ) fix scope of dangerous deserialization error in Databricks LLM connector --------- Signed-off-by: dbczumar <corey.zumar@databricks.com>	5 months ago
Alex Sherstinsky	fad0962643	community: for Predibase -- enable both Predibase-hosted and HuggingFace-hosted fine-tuned adapter repositories (#20370 )	5 months ago
Prince Canuma	1f9f4d8742	community[minor]: Add support for MLX models (chat & llm) (#18152 ) Description: This PR adds support for MLX models both chat (i.e., instruct) and llm (i.e., pretrained) types/ Dependencies: mlx, mlx_lm, transformers Twitter handle: @Prince_Canuma --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
Alex Sherstinsky	5f563e040a	community: extend Predibase integration to support fine-tuned LLM adapters (#19979 ) - [x] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [x] PR message: *Delete this entire checklist* and replace with - Description: Langchain-Predibase integration was failing, because it was not current with the Predibase SDK; in addition, Predibase integration tests were instantiating the Langchain Community `Predibase` class with one required argument (`model`) missing. This change updates the Predibase SDK usage and fixes the integration tests. - Twitter handle: `@alexsherstinsky` - [x] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
Cheng, Penghui	cc407e8a1b	community[minor]: weight only quantization with intel-extension-for-transformers. (#14504 ) Support weight only quantization with intel-extension-for-transformers. [Intel® Extension for Transformers](https://github.com/intel/intel-extension-for-transformers) is an innovative toolkit to accelerate Transformer-based models on Intel platforms, in particular effective on 4th Intel Xeon Scalable processor [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html) (codenamed Sapphire Rapids). The toolkit provides the below key features: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime. * Optimized Transformer-based model packages. * [NeuralChat](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of plugins and SOTA optimizations. * [Inference](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/llm/runtime/graph) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels. This PR is an integration of weight only quantization feature with intel-extension-for-transformers. Unit test is in lib/langchain/tests/integration_tests/llm/test_weight_only_quantization.py The notebook is in docs/docs/integrations/llms/weight_only_quantization.ipynb. The document is in docs/docs/integrations/providers/weight_only_quantization.mdx. --------- Signed-off-by: Cheng, Penghui <penghui.cheng@intel.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Kamal Zhang	368e35c3b1	community[patch]: introduce convert_to_secret() to bananadev llm (#14283 ) - Description: Per #12165, this PR add to BananaLLM the function convert_to_secret_str() during environment variable validation. - Issue: #12165 - Tag maintainer: @eyurtsev - Twitter handle: @treewatcha75751 --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
shahrin014	f51e6a35ba	community[patch]: OllamaEmbeddings - Pass headers to post request (#16880 ) ## Feature - Set additional headers in constructor - Headers will be sent in post request This feature is useful if deploying Ollama on a cloud service such as hugging face, which requires authentication tokens to be passed in the request header. ## Tests - Test if header is passed - Test if header is not passed Similar to https://github.com/langchain-ai/langchain/pull/15881 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Jialei	f7c903e24a	community[minor]: add support for Moonshot llm and chat model (#17100 )	6 months ago
Shengsheng Huang	ac1dd8ad94	community[minor]: migrate `bigdl-llm` to `ipex-llm` (#19518 ) - Description: `bigdl-llm` library has been renamed to [`ipex-llm`](https://github.com/intel-analytics/ipex-llm). This PR migrates the `bigdl-llm` integration to `ipex-llm` . - Issue: N/A. The original PR of `bigdl-llm` is https://github.com/langchain-ai/langchain/pull/17953 - Dependencies: `ipex-llm` library - Contribution maintainer: @shane-huang Updated doc: docs/docs/integrations/llms/ipex_llm.ipynb Updated test: libs/community/tests/integration_tests/llms/test_ipex_llm.py	6 months ago
Yuki Watanabe	cfecbda48b	community[minor]: Allow passing `allow_dangerous_deserialization` when loading LLM chain (#18894 ) ### Issue Recently, the new `allow_dangerous_deserialization` flag was introduced for preventing unsafe model deserialization that relies on pickle without user's notice (#18696). Since then some LLMs like Databricks requires passing in this flag with true to instantiate the model. However, this breaks existing functionality to loading such LLMs within a chain using `load_chain` method, because the underlying loader function [load_llm_from_config](`f96dd57501/libs/langchain/langchain/chains/loading.py (L40)`) (and load_llm) ignores keyword arguments passed in. ### Solution This PR fixes this issue by propagating the `allow_dangerous_deserialization` argument to the class loader iff the LLM class has that field. --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
gonvee	b82644078e	community: Add `keep_alive` parameter to control how long the model w… (#19005 ) Add `keep_alive` parameter to control how long the model will stay loaded into memory with Ollama。 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Leonid Ganeline	7de1d9acfd	community: `llms` imports fixes (#18943 ) Classes are missed in __all__ and in different places of __init__.py - BaichuanLLM - ChatDatabricks - ChatMlflow - Llamafile - Mlflow - Together Added classes to __all__. I also sorted __all__ list. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Yunmo Koo	fee6f983ef	community[minor]: Integration for `Friendli` LLM and `ChatFriendli` ChatModel. (#17913 ) ## Description - Add [Friendli](https://friendli.ai/) integration for `Friendli` LLM and `ChatFriendli` chat model. - Unit tests and integration tests corresponding to this change are added. - Documentations corresponding to this change are added. ## Dependencies - Optional dependency [`friendli-client`](https://pypi.org/project/friendli-client/) package is added only for those who use `Frienldi` or `ChatFriendli` model. ## Twitter handle - https://twitter.com/friendliai	6 months ago
Eugene Yurtsev	4c25b49229	community[major]: breaking change in some APIs to force users to opt-in for pickling (#18696 ) This is a PR that adds a dangerous load parameter to force users to opt in to use pickle. This is a PR that's meant to raise user awareness that the pickling module is involved.	6 months ago
Liang Zhang	81985b31e6	community[patch]: Databricks SerDe uses cloudpickle instead of pickle (#18607 ) - Description: Databricks SerDe uses cloudpickle instead of pickle when serializing a user-defined function transform_input_fn since pickle does not support functions defined in `__main__`, and cloudpickle supports this. - Dependencies: cloudpickle>=2.0.0 Added a unit test.	6 months ago
Brad Erickson	ecd72d26cf	community: Bugfix - correct Ollama API path to avoid HTTP 307 (#17895 ) Sets the correct /api/generate path, without ending /, to reduce HTTP requests. Reference: https://github.com/ollama/ollama/blob/efe040f8/docs/api.md#generate-request-streaming Before: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate/ HTTP/1.1" 307 0 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None After: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None	7 months ago
Guangdong Liu	47b1b7092d	community[minor]: Add SparkLLM to community (#17702 )	7 months ago
wulixuan	c776cfc599	community[minor]: integrate with model Yuan2.0 (#15411 ) 1. integrate with [`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md) 2. update `langchain.llms` 3. add a new doc for [Yuan2.0 integration](docs/docs/integrations/llms/yuan2.ipynb) --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Kate Silverstein	0bc4a9b3fc	community[minor]: Adds Llamafile as an LLM (#17431 ) * Description: Adds a simple LLM implementation for interacting with [llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models. * Dependencies: N/A * Issue: N/A Detail [llamafile](https://github.com/Mozilla-Ocho/llamafile) lets you run LLMs locally from a single file on most computers without installing any dependencies. To use the llamafile LLM implementation, the user needs to: 1. Download a llamafile e.g. https://huggingface.co/jartine/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/TinyLlama-1.1B-Chat-v1.0.Q5_K_M.llamafile?download=true 2. Make the file executable. 3. Run the llamafile in 'server mode'. (All llamafiles come packaged with a lightweight server; by default, the server listens at `http://localhost:8080`.) ```bash wget https://url/of/model.llamafile chmod +x model.llamafile ./model.llamafile --server --nobrowser ``` Now, the user can invoke the LLM via the LangChain client: ```python from langchain_community.llms.llamafile import Llamafile llm = Llamafile() llm.invoke("Tell me a joke.") ```	7 months ago
Erick Friis	3a2eb6e12b	infra: add print rule to ruff (#16221 ) Added noqa for existing prints. Can slowly remove / will prevent more being intro'd	7 months ago
kYLe	c9999557bf	community[patch]: Modify LLMs/Anyscale work with OpenAI API v1 (#14206 ) <!-- Thank you for contributing to LangChain! Replace this entire comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> - Description: 1. Modify LLMs/Anyscale to work with OAI v1 2. Get rid of openai_ prefixed variables in Chat_model/ChatAnyscale 3. Modify `anyscale_api_base` to `anyscale_base_url` to follow OAI name convention (reverted) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Liang Zhang	7306600e2f	community[patch]: Support SerDe transform functions in Databricks LLM (#16752 ) Description: Databricks LLM does not support SerDe the transform_input_fn and transform_output_fn. After saving and loading, the LLM will be broken. This PR serialize these functions into a hex string using pickle, and saving the hex string in the yaml file. Using pickle to serialize a function can be flaky, but this is a simple workaround that unblocks many use cases. If more sophisticated SerDe is needed, we can improve it later. Test: Added a simple unit test. I did manual test on Databricks and it works well. The saved yaml looks like: ``` llm: _type: databricks cluster_driver_port: null cluster_id: null databricks_uri: databricks endpoint_name: databricks-mixtral-8x7b-instruct extra_params: {} host: e2-dogfood.staging.cloud.databricks.com max_tokens: null model_kwargs: null n: 1 stop: null task: null temperature: 0.0 transform_input_fn: 80049520000000000000008c085f5f6d61696e5f5f948c0f7472616e73666f726d5f696e7075749493942e transform_output_fn: null ``` @baskaryan ```python from langchain_community.embeddings import DatabricksEmbeddings from langchain_community.llms import Databricks from langchain.chains import RetrievalQA from langchain.document_loaders import TextLoader from langchain.text_splitter import CharacterTextSplitter from langchain.vectorstores import FAISS import mlflow embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") def transform_input(**request): request["messages"] = [ { "role": "user", "content": request["prompt"] } ] del request["prompt"] return request llm = Databricks(endpoint_name="databricks-mixtral-8x7b-instruct", transform_input_fn=transform_input) persist_dir = "faiss_databricks_embedding" # Create the vector db, persist the db to a local fs folder loader = TextLoader("state_of_the_union.txt") documents = loader.load() text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) docs = text_splitter.split_documents(documents) db = FAISS.from_documents(docs, embeddings) db.save_local(persist_dir) def load_retriever(persist_directory): embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en") vectorstore = FAISS.load_local(persist_directory, embeddings) return vectorstore.as_retriever() retriever = load_retriever(persist_dir) retrievalQA = RetrievalQA.from_llm(llm=llm, retriever=retriever) with mlflow.start_run() as run: logged_model = mlflow.langchain.log_model( retrievalQA, artifact_path="retrieval_qa", loader_fn=load_retriever, persist_dir=persist_dir, ) # Load the retrievalQA chain loaded_model = mlflow.pyfunc.load_model(logged_model.model_uri) print(loaded_model.predict([{"query": "What did the president say about Ketanji Brown Jackson"}])) ```	7 months ago
Luiz Ferreira	34d2daffb3	community[patch]: Fix chat openai unit test (#17124 ) - Description: Actually the test named `test_openai_apredict` isn't testing the apredict method from ChatOpenAI. - Twitter handle: https://twitter.com/OAlmofadas	7 months ago
Harrison Chase	4eda647fdd	infra: add -p to mkdir in lint steps (#17013 ) Previously, if this did not find a mypy cache then it wouldnt run this makes it always run adding mypy ignore comments with existing uncaught issues to unblock other prs --------- Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	7 months ago
Micah Parker	6543e585a5	community[patch]: Added support for Ollama's num_predict option in ChatOllama (#16633 ) Just a simple default addition to the options payload for a ollama generate call to support a max_new_tokens parameter. Should fix issue: https://github.com/langchain-ai/langchain/issues/14715	8 months ago
Rave Harpaz	c4e9c9ca29	community[minor]: Add OCI Generative AI integration (#16548 ) <!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - Description: Adding Oracle Cloud Infrastructure Generative AI integration. Oracle Cloud Infrastructure (OCI) Generative AI is a fully managed service that provides a set of state-of-the-art, customizable large language models (LLMs) that cover a wide range of use cases, and which is available through a single API. Using the OCI Generative AI service you can access ready-to-use pretrained models, or create and host your own fine-tuned custom models based on your own data on dedicated AI clusters. https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm - Issue: None, - Dependencies: OCI Python SDK, - Twitter handle: we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. Passed See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. we provide unit tests. However, we cannot provide integration tests due to Oracle policies that prohibit public sharing of api keys. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Arthur Cheng <arthur.cheng@oracle.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	8 months ago
Shivani Modi	4e160540ff	community[minor]: Adding Konko Completion endpoint (#15570 ) This PR introduces update to Konko Integration with LangChain. 1. New Endpoint Addition: Integration of a new endpoint to utilize completion models hosted on Konko. 2. Chat Model Updates for Backward Compatibility: We have updated the chat models to ensure backward compatibility with previous OpenAI versions. 4. Updated Documentation: Comprehensive documentation has been updated to reflect these new changes, providing clear guidance on utilizing the new features and ensuring seamless integration. Thank you to the LangChain team for their exceptional work and for considering this PR. Please let me know if any additional information is needed. --------- Co-authored-by: Shivani Modi <shivanimodi@Shivanis-MacBook-Pro.local> Co-authored-by: Shivani Modi <shivanimodi@Shivanis-MBP.lan>	8 months ago
DL	b9e7f6f38a	community[minor]: Bedrock async methods (#12477 ) Description: Added support for asynchronous streaming in the Bedrock class and corresponding tests. Primarily: async def aprepare_output_stream async def _aprepare_input_and_invoke_stream async def _astream async def _acall I've ensured that the code adheres to the project's linting and formatting standards by running make format, make lint, and make test. Issue: #12054, #11589 Dependencies: None Tag maintainer: @baskaryan Twitter handle: @dominic_lovric --------- Co-authored-by: Piyush Jain <piyushjain@duck.com>	8 months ago
shahrin014	86321a949f	community: Ollama - Parameter structure to follow official documentation (#16035 ) ## Feature - Follow parameter structure as per official documentation - top level parameters (e.g. model, system, template) will be passed as top level parameters - other parameters will be sent in options unless options is provided ![image](https://github.com/langchain-ai/langchain/assets/17451563/d14715d9-9701-4ee3-b44b-89fffea62389) ## Tests - Test if top level parameters handled properly - Test if parameters that are not top level parameters are handled as options - Test if options is provided, it will be passed as is	8 months ago
shahrin014	bdd90ae2ee	community: Ollama - Pass headers to post request (#15881 ) ## Feature - Set additional headers in constructor - Headers will be sent in post request This feature is useful if deploying Ollama on a cloud service such as hugging face, which requires authentication tokens to be passed in the request header. ## Tests - Test if header is passed - Test if header is not passed	8 months ago
Erick Friis	ebc75c5ca7	openai[minor]: implement langchain-openai package (#15503 ) Todo - [x] copy over integration tests - [x] update docs with new instructions in #15513 - [x] add linear ticket to bump core -> community, community->langchain, and core->openai deps - [ ] (optional): add `pip install langchain-openai` command to each notebook using it - [x] Update docstrings to not need `openai` install - [x] Add serialization - [x] deprecate old models Contributor steps: - [x] Add secret names to manual integrations workflow in .github/workflows/_integration_test.yml - [x] Add secrets to release workflow (for pre-release testing) in .github/workflows/_release.yml Maintainer steps (Contributors should not do these): - [x] set up pypi and test pypi projects - [x] add credential secrets to Github Actions - [ ] add package to conda-forge Functional changes to existing classes: - now relies on openai client v1 (1.6.1) via concrete dep in langchain-openai package Codebase organization - some function calling stuff moved to `langchain_core.utils.function_calling` in order to be used in both community and langchain-openai	8 months ago
chyroc	0a9a73a9c9	Refactor: use SecretStr for PipelineAI llms (#15120 )	9 months ago
chyroc	d63ceb65b3	Refactor: use SecretStr for StochasticAI llms (#15118 )	9 months ago
MING KANG	ed5e0cfe57	community: add OCI Endpoint (#14250 ) - Description: - [OCI Data Science](https://docs.oracle.com/en-us/iaas/data-science/using/home.htm) is a fully managed and serverless platform for data science teams to build, train, and manage machine learning models in the Oracle Cloud Infrastructure. This PR add integration for using LangChain with an LLM hosted on a [OCI Data Science Model Deployment](https://docs.oracle.com/en-us/iaas/data-science/using/model-dep-about.htm). To authenticate, [oracle-ads](https://accelerated-data-science.readthedocs.io/en/latest/user_guide/cli/authentication.html) has been used to automatically load credentials for invoking endpoint. - Issue: None - Dependencies: `oracle-ads` - Tag maintainer: @baskaryan - Twitter handle: None --------- Co-authored-by: Erick Friis <erick@langchain.dev>	9 months ago
AlpinDale	b0588774f1	community[minor]: Add Aphrodite Engine support (#14759 ) This PR adds support for PygmalionAI's [Aphrodite Engine](https://github.com/PygmalionAI/aphrodite-engine), based on vLLM's attention mechanism. At the moment, this PR does not include support for the API servers, but they will be added in a later PR. The only dependency as of now is `aphrodite-engine==0.4.2`. We pin the version to prevent breakage due to changes in the aphrodite-engine library. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	9 months ago
Erick Friis	5f839beab9	community: replace deprecated davinci models (#14860 ) This is technically a breaking change because it'll switch out default models from `text-davinci-003` to `gpt-3.5-turbo-instruct`, but OpenAI is shutting off those endpoints on 1/4 anyways. Feels less disruptive to switch out the default instead.	9 months ago
Bagatur	ed58eeb9c5	community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463 ) Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes	9 months ago

37 Commits (7824291252c8f99a31c416f363d6a46d7e8f63e4)