106 Commits (f79bec12eb0704a7b6092e1bd1c54d7ae9b488e8)

Author	SHA1	Message	Date
David Křístek	a010f29013	fix: call correct stream method in ollama (#15104) ... Co-authored-by: David Kristek <david@David--MacBook-Pro.local>	9 months ago
Christian Janiake	be578f32be	community:Lazy load wikipedia dump file (#15111) ... **Description:** the MWDumpLoader implementation currently does not support the lazy_load method, and the files are usually very large. We are proposing refactoring the load function, extracting two private functions with the functionality of loading the dump file and parsing a single page, to reuse the code in the lazy_load implementation.	9 months ago
chyroc	a4ae4bc361	feat: mask api_key for konko (#14010) ... for https://github.com/langchain-ai/langchain/issues/12165	9 months ago
joel-teratis	62d32bd214	fix(minor): added missing **kwargs parameter to chroma query function (#14919) ... **Description:** This PR adds the `**kwargs` parameter to six calls in the `chroma.py` package. All functions already were able to receive `kwargs` but they were discarded before. **Issue:** When passing `kwargs` to functions in the `chroma.py` package they are being ignored. For example: ``` chroma_instance.similarity_search_with_score( query, k=100, include=["metadatas", "documents", "distances", "embeddings"], # this parameter gets ignored ) ``` The `include` parameter does not get passed on to the next function and does not have any effect. **Dependencies:** None	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
Nuno Campos	99000c612e	Propagate context vars in all classes/methods (#15329) ... - Any direct usage of ThreadPoolExecutor or asyncio.run_in_executor needs manual handling of context vars <!-- 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:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **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. 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	9 months ago
Ankush Gola	7eec8f2487	Delete V1 tracer and refactor tracer tests to core (#15326)	9 months ago
chyroc	7ce338201c	Patch: improve check openai version (#15301)	9 months ago
Nuno Campos	eb5e250188	Propagate context vars in all classes/methods ... - Any direct usage of ThreadPoolExecutor or asyncio.run_in_executor needs manual handling of context vars	9 months ago
Shuai Liu	4b53440e70	Upgrades the Tongyi LLM and ChatTongyi Model (#14793) ... - **Description:** fixes and upgrades for the Tongyi LLM and ChatTongyi Model - Fixed typos; it should be `Tongyi`, not `OpenAI`. - Fixed a bug in `stream_generate_with_retry`; it's a real stream generator now. - Fixed a bug in `validate_environment`; the `dashscope_api_key` should be properly handled when set by environment variables or initialization parameters. - Changed the `dashscope` response to incremental output by setting the parameter `incremental_output`, which eliminates the need for the prefix-removal trick. - Removed some unused parameters, like `n`, `prefix_messages`. - Added `_stream` method. - Added async methods support, such as `_astream`, `_agenerate`, `_abatch`. - **Dependencies:** No new dependencies. - **Tag maintainer:** @hwchase17 > PS: Some may be confused about the terms `dashscope`, `tongyi`, and `Qwen`: > - `dashscope`: A platform to deploy LLMs and provide APIs to invoke the LLM. > - `tongyi`: A brand name or overall term about Alibaba Cloud's LLM/AI. > - `Qwen`: An LLM that is open-sourced and deployed in `dashscope`. > > We use the `dashscope` SDK to interact with the `tongyi`-`Qwen` LLM. --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	9 months ago
Bagatur	8bfac1a319	community[patch]: Release 0.0.7 (#15320)	9 months ago
Diego Rani Mazine	ec72225265	refactor: enable connection pool usage in PGVector (#11514) ... - **Description:** `PGVector` refactored to use connection pool. - **Issue:** #11433, - **Tag maintainer:** @hwchase17 @eyurtsev, --------- Co-authored-by: Diego Rani Mazine <diego.mazine@mercadolivre.com> Co-authored-by: Nuno Campos <nuno@langchain.dev>	9 months ago
joshy-deshaw	bf5385592e	core, community: propagate context between threads (#15171) ... While using `chain.batch`, the default implementation uses a `ThreadPoolExecutor` and run the chains in separate threads. An issue with this approach is that that [the token counting callback](https://python.langchain.com/docs/modules/callbacks/token_counting) fails to work as a consequence of the context not being propagated between threads. This PR adds context propagation to the new threads and adds some thread synchronization in the OpenAI callback. With this change, the token counting callback works as intended. Having the context propagation change would be highly beneficial for those implementing custom callbacks for similar functionalities as well. --------- Co-authored-by: Nuno Campos <nuno@langchain.dev>	9 months ago
shroominic	694bbb14cd	community: fix typo in async ollama chat (#15276) ... Made a stupid typo in the last PR which got already merged😅	9 months ago
triThirty	fea4888e72	community: Enhance Github error prompt (#15248) ... - **Description:** The Github error prompt is confused because of JWT enctrypt to somebody not familiar with Github connection method. This PR is to add some useful error prompt to help users troubleshooting. - **Issue:** https://github.com/langchain-ai/langchain/issues/14550#issuecomment-1867445049 - **Dependencies:** None, - **Twitter handle:** None	9 months ago
Bob Lin	a464eb4394	community: Make doctran synchronous (#15264) ... ### Description I found that the methods in [the doctran library](https://github.com/psychic-api/doctran) have been restructured into [synchronized versions](14944a59f7), And [the example ipynb](https://github.com/psychic-api/doctran/blob/main/examples.ipynb) also shows that the code is synchronized, but the README has not been updated yet. so we need to modify the code and update the documentation. ### Issue https://github.com/langchain-ai/langchain/issues/14645	9 months ago
chyroc	6fb3cc6f27	Fix: Use `Union` instead of `|` to improve compatibility, fix #15244 (#15245)	9 months ago
chyroc	1abcf441ae	Refactor: use SecretStr for Predibase llms (#15119)	9 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
chyroc	674fde87d2	Refactor: use SecretStr for VolcEngineMaas llms (#15117)	9 months ago
chyroc	3cc1da2b38	Refactor: use SecretStr for Petals llms (#15121)	9 months ago
shroominic	e6f0cee896	community: Async Ollama + ChatOllama (#15169) ... **Description:** Adding async methods to booth OllamaLLM and ChatOllama to enable async streaming and async .on_llm_new_token callbacks. **Issue:** ChatOllama is not working in combination with an AsyncCallbackManager because the .on_llm_new_token method is not awaited.	9 months ago
Phill Zarfos	35896faab7	community: correct spelling mistakes of "Suffle" and "reporoducibility" (#15172) ... - **Description:** Correct spelling mistakes of "Suffle" and "reporoducibility" in `DirectoryLoader` class - **Issue:** N/A - **Dependencies:** N/A - **Twitter handle:** N/A	9 months ago
chyroc	3a3f880e5a	Patch: improve ollama 404 api error message, fix #15147 (#15156) ... Make this issue more clearly exposed to developers	9 months ago
Ivan	59d4b80a92	[community]: Elasticsearch chat history encoding (#15055) ... - Added ensure_ascii property to ElasticsearchChatMessageHistory <!-- 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:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **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. 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Ivan Chetverikov <ivan.chetverikov@raftds.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	9 months ago
Corey Brown	9e492620d4	Don't reassign chunk_type (#14923) ... **Description**: The parameter chunk_type was being hard coded to "extractive_answers", so that when "snippet" was being passed, it was being ignored. This change simply doesn't do that.	9 months ago
Takuya Igei	6da2246215	Add support Vertex AI Gemini uses a public image URL (#14949) ... ## What Since `langchain_google_genai.ChatGoogleGenerativeAI` supported A public image URL, we add to support it in `langchain.chat_models.ChatVertexAI` as well. ### Example ```py from langchain.chat_models.vertexai import ChatVertexAI from langchain_core.messages import HumanMessage llm = ChatVertexAI(model_name="gemini-pro-vision") image_message = { "type": "image_url", "image_url": { "url": "https://python.langchain.com/assets/images/cell-18-output-1-0c7fb8b94ff032d51bfe1880d8370104.png", }, } text_message = { "type": "text", "text": "What is shown in this image?", } message = HumanMessage(content=[text_message, image_message]) output = llm([message]) print(output.content) ``` ## Refs - https://python.langchain.com/docs/integrations/llms/google_vertex_ai_palm - https://python.langchain.com/docs/integrations/chat/google_generative_ai	9 months ago
Archan Ghosh	affa3e755a	Update arxiv.py with get_summaries_as_docs inside of Arxivloader (#14953) ... Added the call function get_summaries_as_docs inside of Arxivloader - **Description:** Added a function that returns the documents from get_summaries_as_docs, as the call signature is present in the parent file but never used from Arxivloader, this can be used from Arxivloader itself just like .load() as both the signatures are same. - **Issue:** Reduces time to load papers as no pdf is processed only metadata is pulled from Arxiv allowing users for faster load times on bulk loads. Users can then choose one or more paper and use ID directly with .load() to load pdf thereby loading all the contents of the paper.	9 months ago
ccurme	f2782f4c86	community: add args_schema to GmailSendMessage (#14973) ... - **Description:** `tools.gmail.send_message` implements a `SendMessageSchema` that is not used anywhere. `GmailSendMessage` also does not have an `args_schema` attribute (this led to issues when invoking the tool with an OpenAI functions agent, at least for me). Here we add the missing attribute and a minimal test for the tool. - **Issue:** N/A - **Dependencies:** N/A - **Twitter handle:** N/A --------- Co-authored-by: Chester Curme <chestercurme@microsoft.com>	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
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
Grzegorz Sajko	dc71fcfabf	corrected outdated link (#15053) ... <!-- 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:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **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. 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	9 months ago
Ran	c3f8733aef	fix: correct spelling mistakes of "seperate, intialise, pre-defined" (#14647) ... fix spellings **seperate -> separate**: found more occurrences, see https://github.com/langchain-ai/langchain/pull/14602 **initialise -> intialize**: the latter is more common in the repo **pre-defined > predefined**: adding a comma after a prefix is a delicate matter, but this is a generally accepted word also, another word that appears in the repo is "fs" (stands for filesystem), e.g., in `libs/core/langchain_core/prompts/loading.py` ` """Unified method for loading a prompt from LangChainHub or local fs."""` Isn't "filesystem" better?	9 months ago
Harrison Chase	2e159931ac	add defaults for tavily (#15075)	9 months ago
chyroc	4440ec5ab3	Refactor: use SecretStr for minimax embeddings (#15067)	9 months ago
chyroc	aa19ca9723	Refactor: use SecretStr for jina embeddings (#15068) ... <!-- 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:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **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. 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	9 months ago
Michael Goin	501cc8311d	community[patch]: Fix generation_config not setting properly for DeepSparse (#15036) ... - **Description:** Tiny but important bugfix to use a more stable interface for specifying generation_config parameters for DeepSparse LLM	9 months ago
QIAN Zifei	2460f977c5	community[minor]: Azure DocumentIntelligenceLoader/Parser support update with latest SDK (#14389) ... - **Description:** Add DocumentIntelligenceLoader & DocumentIntelligenceParser implementation using the latest Azure Document Intelligence SDK with markdown support. The core logic resides in DocumentIntelligenceParser and DocumentIntelligenceLoader is a mere wrapper of the parser. The parser will takes api_endpoint and api_key and creates DocumentIntelligenceClient for the user. 4 parsing modes are supported: 1. Markdown (default) 2. Single 3. Page 4. Object UT and notebook are also updated accordingly. - **Dependencies:** Azure Document Intelligence SDK: azure-ai-documentintelligence [azure-sdk-for-python/sdk/documentintelligence/azure-ai-documentintelligence at 7c42462ac662522a6fd21b17d2a20f4cd40d0356 · Azure/azure-sdk-for-python (github.com)](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FAzure%2Fazure-sdk-for-python%2Ftree%2F7c42462ac662522a6fd21b17d2a20f4cd40d0356%2Fsdk%2Fdocumentintelligence%2Fazure-ai-documentintelligence&data=05%7C01%7CZifei.Qian%40microsoft.com%7C298225aa3e31468a863108dbf07374ff%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638368150928704292%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=oE0Sl4HERnMKdbkV9KgBV46Z2xytcQAShdTWf7ZNl%2Bs%3D&reserved=0). --------- Co-authored-by: Erick Friis <erick@langchain.dev>	9 months ago
Ran	129a929d69	infra: Fix test filesystem paths incompatible with windows (#14388) ... - **Description:** This PR fixes test failures on Windows caused by path handling differences and unescaped special characters in regex. The failing tests are: ``` FAILED tests/unit_tests/storage/test_filesystem.py::test_yield_keys - AssertionError: assert ['key1', 'subdir\\key2'] == ['key1', 'subdir/key2'] FAILED tests/unit_tests/test_imports.py::test_importable_all - ModuleNotFoundError: No module named 'langchain_community.langchain_community\\adapters' FAILED tests/unit_tests/tools/file_management/test_utils.py::test_get_validated_relative_path_errs_on_absolute - re.error: incomplete escape \U at position 53 FAILED tests/unit_tests/tools/file_management/test_utils.py::test_get_validated_relative_path_errs_on_parent_dir - re.error: incomplete escape \U at position 69 FAILED tests/unit_tests/tools/file_management/test_utils.py::test_get_validated_relative_path_errs_for_symlink_outside_root - re.error: incomplete escape \U at position 64 ``` - **Issue:** fixes https://github.com/langchain-ai/langchain/issues/11775 (partially) - **Dependencies:** none	9 months ago
Bagatur	40f42b8947	community[patch]: Release 0.0.6 (#15023)	9 months ago
Jacob Lee	1b01ee0e3c	community[minor]: add hf chat wrapper (#14736) ... Builds on #14040 with community refactor merged and notebook updated. Note that with this refactor, models will be imported from `langchain_community.chat_models.huggingface` rather than the main `langchain` repo. --------- Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> Signed-off-by: ugm2 <unaigaraymaestre@gmail.com> Signed-off-by: Yuchen Liang <yuchenl3@andrew.cmu.edu> Co-authored-by: Andrew Reed <andrew.reed.r@gmail.com> Co-authored-by: Andrew Reed <areed1242@gmail.com> Co-authored-by: A-Roucher <aymeric.roucher@gmail.com> Co-authored-by: Aymeric Roucher <69208727+A-Roucher@users.noreply.github.com>	9 months ago
Leonid Kuligin	b99274c9d8	community[patch]: changed default for VertexAIEmbeddings (#14614) ... Replace this entire comment with: - **Description:** @kurtisvg has raised a point that it's a good idea to have a fixed version for embeddings (since otherwise a user might run a query with one version vs a vectorstore where another version was used). In order to avoid breaking changes, I'd suggest to give users a warning, and make a `model_name` a required argument in 1.5 months.	9 months ago
Karim Lalani	228ddabc3b	community: fix for surrealdb client 0.3.2 update + store and retrieve metadata (#14997) ... Surrealdb client changes from 0.3.1 to 0.3.2 broke the surrealdb vectore integration. This PR updates the code to work with the updated client. The change is backwards compatible with previous versions of surrealdb client. Also expanded the vector store implementation to store and retrieve metadata that's included with the document object.	9 months ago
JaguarDB	ca0a75e1fc	community[patch]: JaguarHttpClient conditional import (#14985) ... - **Description:** Fixed jaguar.py to import JaguarHttpClient with try and catch - **Issue:** the issue # Unable to use the JaguarHttpClient at run time - **Dependencies:** It requires "pip install -U jaguardb-http-client" - **Twitter handle:** workbot --------- Co-authored-by: JY <jyjy@jaguardb> Co-authored-by: Bagatur <baskaryan@gmail.com>	9 months ago
Michael Landis	1c934fff0e	community[patch]: support momento vector index filter expressions (#14978) ... **Description** For the Momento Vector Index (MVI) vector store implementation, pass through `filter_expression` kwarg to the MVI client, if specified. This change will enable the MVI self query implementation in a future PR. Also fixes some integration tests.	9 months ago
Yacine	300c1cbf92	community[patch]: Fix typo in class Docstring (#14982) ... - **Description:** Fix typo in class Docstring to replace AZURE_OPENAI_API_ENDPOINT by AZURE_OPENAI_ENDPOINT - **Issue:** the issue #14901 - **Dependencies:** NA - **Twitter handle:** Co-authored-by: Yacine Bouakkaz <Yacine.Bouakkaz@evokegroup.com>	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
Erick Friis	75ba22793f	community: Vectara summarization (#14970) ... Description: Adding Summarization to Vectara, to reflect it provides not only vector-store type functionality but also can return a summary. Also added: MMR capability (in the Vectara platform side) Updated templates Updated documentation and IPYNB examples Tag maintainer: @baskaryan Twitter handle: @ofermend --------- Co-authored-by: Ofer Mendelevitch <ofermend@gmail.com>	9 months ago
Liang Zhang	6479aab74f	community[patch]: Add param "task" to Databricks LLM to work around serialization of transform_output_fn (#14933) ... **What is the reproduce code?** ```python from langchain.chains import LLMChain, load_chain from langchain.llms import Databricks from langchain.prompts import PromptTemplate def transform_output(response): # Extract the answer from the responses. return str(response["candidates"][0]["text"]) def transform_input(**request): full_prompt = f"""{request["prompt"]} Be Concise. """ request["prompt"] = full_prompt return request chat_model = Databricks( endpoint_name="llama2-13B-chat-Brambles", transform_input_fn=transform_input, transform_output_fn=transform_output, verbose=True, ) print(f"Test chat model: {chat_model('What is Apache Spark')}") # This works llm_chain = LLMChain(llm=chat_model, prompt=PromptTemplate.from_template("{chat_input}")) llm_chain("colorful socks") # this works llm_chain.save("databricks_llm_chain.yaml") # transform_input_fn and transform_output_fn are not serialized into the model yaml file loaded_chain = load_chain("databricks_llm_chain.yaml") # The Databricks LLM is recreated with transform_input_fn=None, transform_output_fn=None. loaded_chain("colorful socks") # Thus this errors. The transform_output_fn is needed to produce the correct output ``` Error: ``` File "/local_disk0/.ephemeral_nfs/envs/pythonEnv-6c34afab-3473-421d-877f-1ef18930ef4d/lib/python3.10/site-packages/pydantic/v1/main.py", line 341, in __init__ raise validation_error pydantic.v1.error_wrappers.ValidationError: 1 validation error for Generation text str type expected (type=type_error.str) request payload: {'query': 'What is a databricks notebook?'}'} ``` **What does the error mean?** When the LLM generates an answer, represented by a Generation data object. The Generation data object takes a str field called text, e.g. Generation(text=”blah”). However, the Databricks LLM tried to put a non-str to text, e.g. Generation(text={“candidates”:[{“text”: “blah”}]}) Thus, pydantic errors. **Why the output format becomes incorrect after saving and loading the Databricks LLM?** Databrick LLM does not support serializing transform_input_fn and transform_output_fn, so they are not serialized into the model yaml file. When the Databricks LLM is loaded, it is recreated with transform_input_fn=None, transform_output_fn=None. Without transform_output_fn, the output text is not unwrapped, thus errors. Missing transform_output_fn causes this error. Missing transform_input_fn causes the additional prompt “Be Concise.” to be lost after saving and loading. <!-- 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://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/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	9 months ago