langchain

Commit Graph

Author	SHA1	Message	Date
T Cramer	540ebf35a9	community[patch]: Add explicit error message to Bedrock error output. (#17328 ) - Description: Propagate Bedrock errors into Langchain explicitly. Use-case: unset region error is hidden behind 'Could not load credentials...' message - Issue: [17654](https://github.com/langchain-ai/langchain/issues/17654) - Dependencies: None --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Davide Menini	f7042321f1	community[patch]: gather token usage info in BedrockChat during generation (#19127 ) This PR allows to calculate token usage for prompts and completion directly in the generation method of BedrockChat. The token usage details are then returned together with the generations, so that other downstream tasks can access them easily. This allows to define a callback for tokens tracking and cost calculation, similarly to what happens with OpenAI (see [OpenAICallbackHandler](https://api.python.langchain.com/en/latest/_modules/langchain_community/callbacks/openai_info.html#OpenAICallbackHandler). I plan on adding a BedrockCallbackHandler later. Right now keeping track of tokens in the callback is already possible, but it requires passing the llm, as done here: https://how.wtf/how-to-count-amazon-bedrock-anthropic-tokens-with-langchain.html. However, I find the approach of this PR cleaner. Thanks for your reviews. FYI @baskaryan, @hwchase17 --------- Co-authored-by: taamedag <Davide.Menini@swisscom.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Anis ZAKARI	37e89ba5b1	community[patch]: Bedrock add support for mistral models (#18756 ) Description*: My previous [PR](https://github.com/langchain-ai/langchain/pull/18521) was mistakenly closed, so I am reopening this one. Context: AWS released two Mistral models on Bedrock last Friday (March 1, 2024). This PR includes some code adjustments to ensure their compatibility with the Bedrock class. --------- Co-authored-by: Anis ZAKARI <anis.zakari@hymaia.com> Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Piyush Jain	2b234a4d96	Support for claude v3 models. (#18630 ) Fixes #18513. ## Description This PR attempts to fix the support for Anthropic Claude v3 models in BedrockChat LLM. The changes here has updated the payload to use the `messages` format instead of the formatted text prompt for all models; `messages` API is backwards compatible with all models in Anthropic, so this should not break the experience for any models. ## Notes The PR in the current form does not support the v3 models for the non-chat Bedrock LLM. This means, that with these changes, users won't be able to able to use the v3 models with the Bedrock LLM. I can open a separate PR to tackle this use-case, the intent here was to get this out quickly, so users can start using and test the chat LLM. The Bedrock LLM classes have also grown complex with a lot of conditions to support various providers and models, and is ripe for a refactor to make future changes more palatable. This refactor is likely to take longer, and requires more thorough testing from the community. Credit to PRs [18579](https://github.com/langchain-ai/langchain/pull/18579) and [18548](https://github.com/langchain-ai/langchain/pull/18548) for some of the code here. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Nat Noordanus	8a3b74fe1f	community[patch]: Fix pydantic ForwardRef error in BedrockBase (#17416 ) - Description: Fixes a type annotation issue in the definition of BedrockBase. This issue was that the annotation for the `config` attribute includes a ForwardRef to `botocore.client.Config` which is only imported when `TYPE_CHECKING`. This can cause pydantic to raise an error like `pydantic.errors.ConfigError: field "config" not yet prepared so type is still a ForwardRef, ...`. - Issue: N/A - Dependencies: N/A - Twitter handle: `@__nat_n__`	7 months ago
Supreet Takkar	ae33979813	community[patch]: Allow adding ARNs as model_id to support Amazon Bedrock custom models (#16800 ) - Description: Adds an additional class variable to `BedrockBase` called `provider` that allows sending a model provider such as amazon, cohere, ai21, etc. Up until now, the model provider is extracted from the `model_id` using the first part before the `.`, such as `amazon` for `amazon.titan-text-express-v1` (see [supported list of Bedrock model IDs here](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html)). But for custom Bedrock models where the ARN of the provisioned throughput must be supplied, the `model_id` is like `arn:aws:bedrock:...` so the `model_id` cannot be extracted from this. A model `provider` is required by the LangChain Bedrock class to perform model-based processing. To allow the same processing to be performed for custom-models of a specific base model type, passing this `provider` argument can help solve the issues. The alternative considered here was the use of `provider.arn:aws:bedrock:...` which then requires ARN to be extracted and passed separately when invoking the model. The proposed solution here is simpler and also does not cause issues for current models already using the Bedrock class. - Issue: N/A - Dependencies: N/A --------- Co-authored-by: Piyush Jain <piyushjain@duck.com>	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
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
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
Guillem Orellana Trullols	aad2aa7188	community[patch]: BedrockChat -> Support Titan express as chat model (#15408 ) Titan Express model was not supported as a chat model because LangChain messages were not "translated" to a text prompt. Co-authored-by: Guillem Orellana Trullols <guillem.orellana_trullols@siemens.com>	8 months ago
JuR-0	4dab37741a	Fix Bedrock broad error catching (#14398 ) Fixes #14347 <!-- Thank you for contributing to LangChain! Replace this entire comment with: - Description: Added the traceback of the previous error to keep the initial error type, - Issue: #14347 , - Dependencies: None, - Tag maintainer: 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. --> --------- Co-authored-by: Julien Raffy <julien.raffy@emeria.eu> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	8 months ago
Blane Honeycutt	3fc1b3553b	Community: Adds ability to pass a Config to the boto3 client used by Bedrock (#15029 ) # Description This PR adds the ability to pass a `botocore.config.Config` instance to the boto3 client instantiated by the Bedrock LLM. Currently, the Bedrock LLM doesn't support a way to pass a Config, which means that some settings (e.g., timeouts and retry configuration) require instantiating a new boto3 client with a Config and then replacing the LLM's client: ```python llm = Bedrock( region_name='us-west-2', model_id="anthropic.claude-v2", model_kwargs={'max_tokens_to_sample': 4096, 'temperature': 0}, ) llm.client = boto_client('bedrock-runtime', region_name='us-west-2', config=Config({'read_timeout': 300})) ``` # Issue N/A # Dependencies N/A	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

13 Commits (f1248f8d9a9ff3de02566b7b64019c82d03872de)