41 Commits (9b3a025f9c806a6f8a00030c7058c689536ae5a0)

Author	SHA1	Message	Date
Eugene Yurtsev	05d31a2f00	community[patch]: Add missing type annotations (#22758) ... Add missing type annotations to objects in community. These missing type annotations will raise type errors in pydantic 2.	3 months ago
Eugene Yurtsev	25fbe356b4	community[patch]: upgrade to recent version of mypy (#21616) ... This PR upgrades community to a recent version of mypy. It inserts type: ignore on all existing failures.	4 months ago
Jorge Piedrahita Ortiz	40b2e2916b	community[minor]: Sambanova llm integration (#20955) ... - **Description:** Added [Sambanova systems](https://sambanova.ai/) integration, including sambaverse and sambastudio LLMs - **Dependencies:** sseclient-py (optional) --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Shengsheng Huang	fd1061e7bf	community[patch]: add more data types support to ipex-llm llm integration (#20833) ... - **Description**: - **add support for more data types**: by default `IpexLLM` will load the model in int4 format. This PR adds more data types support such as `sym_in5`, `sym_int8`, etc. Data formats like NF3, NF4, FP4 and FP8 are only supported on GPU and will be added in future PR. - Fix a small issue in saving/loading, update api docs - **Dependencies**: `ipex-llm` library - **Document**: In `docs/docs/integrations/llms/ipex_llm.ipynb`, added instructions for saving/loading low-bit model. - **Tests**: added new test cases to `libs/community/tests/integration_tests/llms/test_ipex_llm.py`, added config params. - **Contribution maintainer**: @shane-huang	5 months ago
ccurme	481d3855dc	patch: remove usage of llm, chat model __call__ (#20788) ... - `llm(prompt)` -> `llm.invoke(prompt)` - `llm(prompt=prompt` -> `llm.invoke(prompt)` (same with `messages=`) - `llm(prompt, callbacks=callbacks)` -> `llm.invoke(prompt, config={"callbacks": callbacks})` - `llm(prompt, **kwargs)` -> `llm.invoke(prompt, **kwargs)`	5 months ago
pjb157	479be3cc91	community[minor]: Unify Titan Takeoff Integrations and Adding Embedding Support (#18775) ... **Community: Unify Titan Takeoff Integrations and Adding Embedding Support** **Description:** Titan Takeoff no longer reflects this either of the integrations in the community folder. The two integrations (TitanTakeoffPro and TitanTakeoff) where causing confusion with clients, so have moved code into one place and created an alias for backwards compatibility. Added Takeoff Client python package to do the bulk of the work with the requests, this is because this package is actively updated with new versions of Takeoff. So this integration will be far more robust and will not degrade as badly over time. **Issue:** Fixes bugs in the old Titan integrations and unified the code with added unit test converge to avoid future problems. **Dependencies:** Added optional dependency takeoff-client, all imports still work without dependency including the Titan Takeoff classes but just will fail on initialisation if not pip installed takeoff-client **Twitter** @MeryemArik9 Thanks all :) --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
Sevin F. Varoglu	54d388d898	community[patch]: update OctoAI endpoint to subclass BaseOpenAI (#19757) ... This PR updates OctoAIEndpoint LLM to subclass BaseOpenAI as OctoAI is an OpenAI-compatible service. The documentation and tests have also been updated.	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>	6 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>	6 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>	6 months ago
Jamsheed Mistri	4f70bc119d	community[minor]: add Layerup Security integration (#19787) ... **Description:** adds integration with [Layerup Security](https://uselayerup.com). Docs can be found [here](https://docs.uselayerup.com). Integrates directly with our Python SDK. **Dependencies:** [LayerupSecurity](https://pypi.org/project/LayerupSecurity/) **Note**: all methods for our product require a paid API key, so I only included 1 test which checks for an invalid API key response. I have tested extensively locally. **Twitter handle**: [@layerup_](https://twitter.com/layerup_) --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Alex Sherstinsky	a9bc212bf2	community[minor]: fix failing Predibase integration (#19776) ... - [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` --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
wulixuan	b7c8bc8268	community[patch]: fix yuan2 errors in LLMs (#19004) ... 1. fix yuan2 errors while invoke Yuan2. 2. update tests.	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
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	7 months ago
Arun Sathiya	4adac20d7b	community[patch]: Make cohere_api_key a SecretStr (#12188) ... This PR makes `cohere_api_key` in `llms/cohere` a SecretStr, so that the API Key is not leaked when `Cohere.cohere_api_key` is represented as a string. --------- Signed-off-by: Arun <arun@arun.blog> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	7 months ago
Shengsheng Huang	ae471a7dcb	community[minor]: add BigDL-LLM integrations (#17953) ... - **Description**: [`bigdl-llm`](https://github.com/intel-analytics/BigDL) is a library for running LLM on Intel XPU (from Laptop to GPU to Cloud) using INT4/FP4/INT8/FP8 with very low latency (for any PyTorch model). This PR adds bigdl-llm integrations to langchain. - **Issue**: NA - **Dependencies**: `bigdl-llm` library - **Contribution maintainer**: @shane-huang Examples added: - docs/docs/integrations/llms/bigdl.ipynb	7 months ago
Ethan Yang	f61cb8d407	community[minor]: Add openvino backend support (#11591) ... - **Description:** add openvino backend support by HuggingFace Optimum Intel, - **Dependencies:** “optimum[openvino]”, --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Guangdong Liu	47b1b7092d	community[minor]: Add SparkLLM to community (#17702)	7 months ago
Aymeric Roucher	0d294760e7	Community: Fuse HuggingFace Endpoint-related classes into one (#17254) ... ## Description Fuse HuggingFace Endpoint-related classes into one: - [HuggingFaceHub](5ceaf784f3/libs/community/langchain_community/llms/huggingface_hub.py) - [HuggingFaceTextGenInference](5ceaf784f3/libs/community/langchain_community/llms/huggingface_text_gen_inference.py) - and [HuggingFaceEndpoint](5ceaf784f3/libs/community/langchain_community/llms/huggingface_endpoint.py) Are fused into - HuggingFaceEndpoint ## Issue The deduplication of classes was creating a lack of clarity, and additional effort to develop classes leads to issues like [this hack](5ceaf784f3/libs/community/langchain_community/llms/huggingface_endpoint.py (L159)). ## Dependancies None, this removes dependancies. ## Twitter handle If you want to post about this: @AymericRoucher --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	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	8 months ago
Armin Stepanyan	641efcf41c	community: add runtime kwargs to HuggingFacePipeline (#17005) ... This PR enables changing the behaviour of huggingface pipeline between different calls. For example, before this PR there's no way of changing maximum generation length between different invocations of the chain. This is desirable in cases, such as when we want to scale the maximum output size depending on a dynamic prompt size. Usage example: ```python from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline model_id = "gpt2" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) pipe = pipeline("text-generation", model=model, tokenizer=tokenizer) hf = HuggingFacePipeline(pipeline=pipe) hf("Say foo:", pipeline_kwargs={"max_new_tokens": 42}) ``` --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	8 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>	8 months ago
baichuan-assistant	f8f2649f12	community: Add Baichuan LLM to community (#16724) ... Replace this entire comment with: - **Description:** Add Baichuan LLM to integration/llm, also updated related docs. Co-authored-by: BaiChuanHelper <wintergyc@WinterGYCs-MacBook-Pro.local>	8 months ago
Harel Gal	a91181fe6d	community[minor]: add support for Guardrails for Amazon Bedrock (#15099) ... Added support for optionally supplying 'Guardrails for Amazon Bedrock' on both types of model invocations (batch/regular and streaming) and for all models supported by the Amazon Bedrock service. @baskaryan @hwchase17 ```python llm = Bedrock(model_id="<model_id>", client=bedrock, model_kwargs={}, guardrails={"id": " <guardrail_id>", "version": "<guardrail_version>", "trace": True}, callbacks=[BedrockAsyncCallbackHandler()]) class BedrockAsyncCallbackHandler(AsyncCallbackHandler): """Async callback handler that can be used to handle callbacks from langchain.""" async def on_llm_error( self, error: BaseException, **kwargs: Any, ) -> Any: reason = kwargs.get("reason") if reason == "GUARDRAIL_INTERVENED": # kwargs contains additional trace information sent by 'Guardrails for Bedrock' service. print(f"""Guardrails: {kwargs}""") # streaming llm = Bedrock(model_id="<model_id>", client=bedrock, model_kwargs={}, streaming=True, guardrails={"id": "<guardrail_id>", "version": "<guardrail_version>"}) ``` --------- 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
Facundo Santiago	92e6a641fd	feat: adding paygo api support for Azure ML / Azure AI Studio (#14560) ... - **Description:** Introducing support for LLMs and Chat models running in Azure AI studio and Azure ML using the new deployment mode pay-as-you-go (model as a service). - **Issue:** NA - **Dependencies:** None. - **Tag maintainer:** @prakharg-msft @gdyre - **Twitter handle:** @santiagofacundo Examples added: * [docs/docs/integrations/llms/azure_ml.ipynb](https://github.com/santiagxf/langchain/blob/santiagxf/azureml-endpoints-paygo-community/docs/docs/integrations/chat/azureml_endpoint.ipynb) * [docs/docs/integrations/chat/azureml_chat_endpoint.ipynb](https://github.com/santiagxf/langchain/blob/santiagxf/azureml-endpoints-paygo-community/docs/docs/integrations/chat/azureml_chat_endpoint.ipynb) --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	8 months ago
Iskren Ivov Chernev	fc196cab12	community[minor]: DeepInfra support for chat models (#16380) ... Add deepinfra chat models support. This is https://github.com/langchain-ai/langchain/pull/14234 re-opened from my branch (so maintainers can edit).	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	9 months ago
Bagatur	baeac236b6	langchain[patch], experimental[patch]: update utilities imports (#15438)	9 months ago
NuODaniel	7773943a51	community:qianfan endpoint support init params & remove useless params definietion (#15381) ... - **Description:** - support custom kwargs in object initialization. For instantance, QPS differs from multiple object(chat/completion/embedding with diverse models), for which global env is not a good choice for configuration. - **Issue:** no - **Dependencies:** no - **Twitter handle:** no @baskaryan PTAL	9 months ago
chyroc	1abcf441ae	Refactor: use SecretStr for Predibase llms (#15119)	9 months ago
chyroc	674fde87d2	Refactor: use SecretStr for VolcEngineMaas llms (#15117)	9 months ago
chyroc	3cc1da2b38	Refactor: use SecretStr for Petals llms (#15121)	9 months ago
Philip Kiely - Baseten	6342da333a	community: refactor Baseten integration with new API endpoints & docs (#15017) ... - **Description:** In response to user feedback, this PR refactors the Baseten integration with updated model endpoints, as well as updates relevant documentation. This PR has been tested by end users in production and works as expected. - **Issue:** N/A - **Dependencies:** This PR actually removes the dependency on the `baseten` package! - **Twitter handle:** https://twitter.com/basetenco	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
Leonid Kuligin	7f42811e14	google-genai[patch], community[patch]: Added support for new Google GenerativeAI models (#14530) ... Replace this entire comment with: - **Description:** added support for new Google GenerativeAI models - **Twitter handle:** lkuligin --------- Co-authored-by: Erick Friis <erick@langchain.dev>	9 months ago
William FH	75b8891399	Update Vertex AI to include Gemini (#14670) ... h/t to @lkuligin - **Description:** added new models on VertexAI - **Twitter handle:** @lkuligin --------- Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	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	10 months ago