langchain

Commit Graph

Author	SHA1	Message	Date
Jeff Vestal	cf19a2a59f	example usage (#5182 ) Adding example usage for elasticsearch knn embeddings [per](https://github.com/hwchase17/langchain/pull/3401#issuecomment-1548518389) https://github.com/hwchase17/langchain/blob/master/langchain/embeddings/elasticsearch.py	1 year ago
Ikko Eltociear Ashimine	fff21a0b35	Update rellm_experimental.ipynb (#5189 ) # Your PR Title (What it does) HuggingFace -> Hugging Face	1 year ago
Nolan Tremelling	faa26650c9	Beam (#4996 ) # Beam Calls the Beam API wrapper to deploy and make subsequent calls to an instance of the gpt2 LLM in a cloud deployment. Requires installation of the Beam library and registration of Beam Client ID and Client Secret. Additional calls can then be made through the instance of the large language model in your code or by calling the Beam API. --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Ofer Mendelevitch	c81fb88035	Vectara (#5069 ) # Vectara Integration This PR provides integration with Vectara. Implemented here are: * langchain/vectorstore/vectara.py * tests/integration_tests/vectorstores/test_vectara.py * langchain/retrievers/vectara_retriever.py And two IPYNB notebooks to do more testing: * docs/modules/chains/index_examples/vectara_text_generation.ipynb * docs/modules/indexes/vectorstores/examples/vectara.ipynb --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Jason Bosco	9c4b43b494	Add Typesense vector store (#1674 ) Closes #931. --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Leonid Ganeline	33929489b9	docs: added missed `document_loaders` examples (#5150 ) # DOCS added missed document_loader examples Added missed examples: `JSON`, `Open Document Format (ODT)`, `Wikipedia`, `tomarkdown`. Updated them to a consistent format. ## Who can review? @hwchase17 @dev2049	1 year ago
Daniel Quinteros	c111134a55	Clarification of the reference to the "get_text_legth" function in ge… (#5154 ) # Clarification of the reference to the "get_text_legth" function in getting_started.md Reference to the function "get_text_legth" in the documentation did not make sense. Comment added for clarification. @hwchase17	1 year ago
Daniel Quinteros	de4ef24f75	Docs: updated getting_started.md (#5151 ) # Docs: updated getting_started.md Just accommodating some unnecessary spaces in the example of "pass few shot examples to a prompt template". @vowelparrot	1 year ago
mbchang	b1b7f3541c	fix: fix current_time=Now bug for aadd_documents in TimeWeightedRetriever (#5155 ) # Same as PR #5045, but for async <!-- Thank you for contributing to LangChain! Your PR will appear in our next release under the title you set. Please make sure it highlights your valuable contribution. Replace this with a description of the change, the issue it fixes (if applicable), and relevant context. List any dependencies required for this change. After you're done, someone will review your PR. They may suggest improvements. If no one reviews your PR within a few days, feel free to @-mention the same people again, as notifications can get lost. --> <!-- Remove if not applicable --> Fixes #4825 I had forgotten to update the asynchronous counterpart `aadd_documents` with the bug fix from PR #5045, so this PR also fixes `aadd_documents` too. ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested: @dev2049 <!-- For a quicker response, figure out the right person to tag with @ @hwchase17 - project lead Tracing / Callbacks - @agola11 Async - @agola11 DataLoaders - @eyurtsev Models - @hwchase17 - @agola11 Agents / Tools / Toolkits - @vowelparrot VectorStores / Retrievers / Memory - @dev2049 -->	1 year ago
Jeremiah Lowin	925dd3e59e	Add async versions of predict() and predict_messages() (#4867 ) # Add async versions of predict() and predict_messages() #4615 introduced a unifying interface for "base" and "chat" LLM models via the new `predict()` and `predict_messages()` methods that allow both types of models to operate on string and message-based inputs, respectively. This PR adds async versions of the same (`apredict()` and `apredict_messages()`) that are identical except for their use of `agenerate()` in place of `generate()`, which means they repurpose all existing work on the async backend. ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested: @hwchase17 (follows his work on #4615) @agola11 (async) --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Junlin Zhou	9242998db1	Empty check before pop (#4929 ) # Check whether 'other' is empty before popping This PR could fix a potential 'popping empty set' error. Co-authored-by: Junlin Zhou <jlzhou@zjuici.com>	1 year ago
Daniel King	de6e6c764e	Add MosaicML inference endpoints (#4607 ) # Add MosaicML inference endpoints This PR adds support in langchain for MosaicML inference endpoints. We both serve a select few open source models, and allow customers to deploy their own models using our inference service. Docs are here (https://docs.mosaicml.com/en/latest/inference.html), and sign up form is here (https://forms.mosaicml.com/demo?utm_source=langchain). I'm not intimately familiar with the details of langchain, or the contribution process, so please let me know if there is anything that needs fixing or this is the wrong way to submit a new integration, thanks! I'm also not sure what the procedure is for integration tests. I have tested locally with my api key. ## Who can review? @hwchase17 --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Adheeban Manoharan	68f0d45485	Adding Weather Loader (#5056 ) Co-authored-by: Tyler Hutcherson <tyler.hutcherson@redis.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Jeff Vestal	0b542a9706	Add ElasticsearchEmbeddings class for generating embeddings using Elasticsearch models (#3401 ) This PR introduces a new module, `elasticsearch_embeddings.py`, which provides a wrapper around Elasticsearch embedding models. The new ElasticsearchEmbeddings class allows users to generate embeddings for documents and query texts using a [model deployed in an Elasticsearch cluster](https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-model-ref.html#ml-nlp-model-ref-text-embedding). ### Main features: 1. The ElasticsearchEmbeddings class initializes with an Elasticsearch connection object and a model_id, providing an interface to interact with the Elasticsearch ML client through [infer_trained_model](https://elasticsearch-py.readthedocs.io/en/v8.7.0/api.html?highlight=trained%20model%20infer#elasticsearch.client.MlClient.infer_trained_model) . 2. The `embed_documents()` method generates embeddings for a list of documents, and the `embed_query()` method generates an embedding for a single query text. 3. The class supports custom input text field names in case the deployed model expects a different field name than the default `text_field`. 4. The implementation is compatible with any model deployed in Elasticsearch that generates embeddings as output. ### Benefits: 1. Simplifies the process of generating embeddings using Elasticsearch models. 2. Provides a clean and intuitive interface to interact with the Elasticsearch ML client. 3. Allows users to easily integrate Elasticsearch-generated embeddings. Related issue https://github.com/hwchase17/langchain/issues/3400 --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Theodore Rolle	754b5133e9	Improve PlanningOutputParser whitespace handling (#5143 ) Some LLM's will produce numbered lists with leading whitespace, i.e. in response to "What is the sum of 2 and 3?": ``` Plan: 1. Add 2 and 3. 2. Given the above steps taken, please respond to the users original question. ``` This commit updates the PlanningOutputParser regex to ignore leading whitespace before the step number, enabling it to correctly parse this format.	1 year ago
Tommaso De Lorenzo	5002f3ae35	solving #2887 (#5127 ) # Allowing openAI fine-tuned models Very simple fix that checks whether a openAI `model_name` is a fine-tuned model when loading `context_size` and when computing call's cost in the `openai_callback`. Fixes #2887 --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Myeongseop Kim	7a75bb2121	docs: fix minor typo + add wikipedia package installation part in human_input_llm.ipynb (#5118 ) # Fix typo + add wikipedia package installation part in human_input_llm.ipynb This PR 1. Fixes typo ("the the human input LLM"), 2. Addes wikipedia package installation part (in accordance with `WikipediaQueryRun` [documentation](https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html)) in `human_input_llm.ipynb` (`docs/modules/models/llms/examples/human_input_llm.ipynb`)	1 year ago
Davis Chase	753f4cfc26	bump 178 (#5130 )	1 year ago
Ayan Bandyopadhyay	5c87dbf5a8	Add link to Psychic from document loaders documentation page (#5115 ) # Add link to Psychic from document loaders documentation page In my previous PR I forgot to update `document_loaders.rst` to link to `psychic.ipynb` to make it discoverable from the main documentation.	1 year ago
Tian Wei	d7f807b71f	Add AzureCognitiveServicesToolkit to call Azure Cognitive Services API (#5012 ) # Add AzureCognitiveServicesToolkit to call Azure Cognitive Services API: achieve some multimodal capabilities This PR adds a toolkit named AzureCognitiveServicesToolkit which bundles the following tools: - AzureCogsImageAnalysisTool: calls Azure Cognitive Services image analysis API to extract caption, objects, tags, and text from images. - AzureCogsFormRecognizerTool: calls Azure Cognitive Services form recognizer API to extract text, tables, and key-value pairs from documents. - AzureCogsSpeech2TextTool: calls Azure Cognitive Services speech to text API to transcribe speech to text. - AzureCogsText2SpeechTool: calls Azure Cognitive Services text to speech API to synthesize text to speech. This toolkit can be used to process image, document, and audio inputs. --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Jamie Broomall	d4fd589638	WhyLabs callback (#4906 ) # Add a WhyLabs callback handler * Adds a simple WhyLabsCallbackHandler * Add required dependencies as optional * protect against missing modules with imports * Add docs/ecosystem basic example based on initial prototype from @andrewelizondo > this integration gathers privacy preserving telemetry on text with whylogs and sends stastical profiles to WhyLabs platform to monitoring these metrics over time. For more information on what WhyLabs is see: https://whylabs.ai After you run the notebook (if you have env variables set for the API Keys, org_id and dataset_id) you get something like this in WhyLabs: ![Screenshot (443)](https://github.com/hwchase17/langchain/assets/88007022/6bdb3e1c-4243-4ae8-b974-23a8bb12edac) Co-authored-by: Andre Elizondo <andre@whylabs.ai> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Eugene Yurtsev	d56313acba	Improve effeciency of TextSplitter.split_documents, iterate once (#5111 ) # Improve TextSplitter.split_documents, collect page_content and metadata in one iteration ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested: @eyurtsev In the case where documents is a generator that can only be iterated once making this change is a huge help. Otherwise a silent issue happens where metadata is empty for all documents when documents is a generator. So we expand the argument from `List[Document]` to `Union[Iterable[Document], Sequence[Document]]` --------- Co-authored-by: Steven Tartakovsky <tartakovsky.developer@gmail.com>	1 year ago
Jettro Coenradie	b950022894	Fixes issue #5072 - adds additional support to Weaviate (#5085 ) Implementation is similar to search_distance and where_filter # adds 'additional' support to Weaviate queries Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Zander Chase	87bba2e8d3	Pass Dataset Name by Name not Position (#5108 ) Pass dataset name by name	1 year ago
Matt Rickard	de6a401a22	Add OpenLM LLM multi-provider (#4993 ) OpenLM is a zero-dependency OpenAI-compatible LLM provider that can call different inference endpoints directly via HTTP. It implements the OpenAI Completion class so that it can be used as a drop-in replacement for the OpenAI API. This changeset utilizes BaseOpenAI for minimal added code. --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Gergely Imreh	69de33e024	Add Mastodon toots loader (#5036 ) # Add Mastodon toots loader. Loader works either with public toots, or Mastodon app credentials. Toot text and user info is loaded. I've also added integration test for this new loader as it works with public data, and a notebook with example output run now. --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
mbchang	e173e032bc	fix: assign current_time to datetime.now() if current_time is None (#5045 ) # Assign `current_time` to `datetime.now()` if it `current_time is None` in `time_weighted_retriever` Fixes #4825 As implemented, `add_documents` in `TimeWeightedVectorStoreRetriever` assigns `doc.metadata["last_accessed_at"]` and `doc.metadata["created_at"]` to `datetime.datetime.now()` if `current_time` is not in `kwargs`. ```python def add_documents(self, documents: List[Document], kwargs: Any) -> List[str]: """Add documents to vectorstore.""" current_time = kwargs.get("current_time", datetime.datetime.now()) # Avoid mutating input documents dup_docs = [deepcopy(d) for d in documents] for i, doc in enumerate(dup_docs): if "last_accessed_at" not in doc.metadata: doc.metadata["last_accessed_at"] = current_time if "created_at" not in doc.metadata: doc.metadata["created_at"] = current_time doc.metadata["buffer_idx"] = len(self.memory_stream) + i self.memory_stream.extend(dup_docs) return self.vectorstore.add_documents(dup_docs, kwargs) ``` However, from the way `add_documents` is being called from `GenerativeAgentMemory`, `current_time` is set as a `kwarg`, but it is given a value of `None`: ```python def add_memory( self, memory_content: str, now: Optional[datetime] = None ) -> List[str]: """Add an observation or memory to the agent's memory.""" importance_score = self._score_memory_importance(memory_content) self.aggregate_importance += importance_score document = Document( page_content=memory_content, metadata={"importance": importance_score} ) result = self.memory_retriever.add_documents([document], current_time=now) ``` The default of `now` was set in #4658 to be None. The proposed fix is the following: ```python def add_documents(self, documents: List[Document], **kwargs: Any) -> List[str]: """Add documents to vectorstore.""" current_time = kwargs.get("current_time", datetime.datetime.now()) # `current_time` may exist in kwargs, but may still have the value of None. if current_time is None: current_time = datetime.datetime.now() ``` Alternatively, we could just set the default of `now` to be `datetime.datetime.now()` everywhere instead. Thoughts @hwchase17? If we still want to keep the default to be `None`, then this PR should fix the above issue. If we want to set the default to be `datetime.datetime.now()` instead, I can update this PR with that alternative fix. EDIT: seems like from #5018 it looks like we would prefer to keep the default to be `None`, in which case this PR should fix the error.	1 year ago
Leonid Ganeline	c28cc0f1ac	changed ValueError to ImportError (#5103 ) # changed ValueError to ImportError Code cleaning. Fixed inconsistencies in ImportError handling. Sometimes it raises ImportError and sometime ValueError. I've changed all cases to the `raise ImportError` Also: - added installation instruction in the error message, where it missed; - fixed several installation instructions in the error message; - fixed several error handling in regards to the ImportError	1 year ago
venetisgr	5e47c648ed	Update serpapi.py (#4947 ) Added link option in _process_response <!-- In _process_respons "snippet" provided non working links for the case that "links" had the correct answer. Thus added an elif statement before snippet --> <!-- Remove if not applicable --> Fixes # (issue) In _process_response link provided correct answers while the snippet reply provided non working links @vowelparrot ## Before submitting <!-- If you're adding a new integration, include an integration test and an example notebook showing its use! --> ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested: <!-- For a quicker response, figure out the right person to tag with @ @hwchase17 - project lead Tracing / Callbacks - @agola11 Async - @agola11 DataLoaders - @eyurtsev Models - @hwchase17 - @agola11 Agents / Tools / Toolkits - @vowelparrot VectorStores / Retrievers / Memory - @dev2049 --> --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Ankit Arya	5b2b436fab	Fixed import error for AutoGPT e.g. from langchain.experimental.auton… (#5101 ) `from langchain.experimental.autonomous_agents.autogpt.agent import AutoGPT` results in an import error as AutoGPT is not defined in the __init__.py file https://python.langchain.com/en/latest/use_cases/autonomous_agents/marathon_times.html An Alternate, way would be to be directly update the import statement to be `from langchain.experimental import AutoGPT` Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Ankush Gola	467ca6f025	update langchainplus client and docker file to reflect port changes (#5005 ) # Currently, only the dev images are updated	1 year ago
Shawn91	9e649462ce	fix: add_texts method of Weaviate vector store creats wrong embeddings (#4933 ) # fix a bug in the add_texts method of Weaviate vector store that creats wrong embeddings The following is the original code in the `add_texts` method of the Weaviate vector store, from line 131 to 153, which contains a bug. The code here includes some extra explanations in the form of comments and some omissions. ```python for i, doc in enumerate(texts): # some code omitted if self._embedding is not None: # variable texts is a list of string and doc here is just a string. # list(doc) actually breaks up the string into characters. # so, embeddings[0] is just the embedding of the first character embeddings = self._embedding.embed_documents(list(doc)) batch.add_data_object( data_object=data_properties, class_name=self._index_name, uuid=_id, vector=embeddings[0], ) ``` To fix this bug, I pulled the embedding operation out of the for loop and embed all texts at once. Co-authored-by: Shawn91 <zyx199199@qq.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Eduard van Valkenburg	1cb04f2b26	PowerBI major refinement in working of tool and tweaks in the rest (#5090 ) # PowerBI major refinement in working of tool and tweaks in the rest I've gained some experience with more complex sets and the earlier implementation had too many tries by the agent to create DAX, so refactored the code to run the LLM to create dax based on a question and then immediately run the same against the dataset, with retries and a prompt that includes the error for the retry. This works much better! Also did some other refactoring of the inner workings, making things clearer, more concise and faster.	1 year ago
hwaking	e57ebf3922	add get_top_k_cosine_similarity method to get max top k score and index (#5059 ) # Row-wise cosine similarity between two equal-width matrices and return the max top_k score and index, the score all greater than threshold_score. Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Donger	039f8f1abb	Add the usage of SSL certificates for Elasticsearch and user password authentication (#5058 ) Enhance the code to support SSL authentication for Elasticsearch when using the VectorStore module, as previous versions did not provide this capability. @dev2049 --------- Co-authored-by: caidong <zhucaidong1992@gmail.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Andreas Liebschner	44dc959584	Improve pinecone hybrid search retriever adding metadata support (#5098 ) # Improve pinecone hybrid search retriever adding metadata support I simply remove the hardwiring of metadata to the existing implementation allowing one to pass `metadatas` attribute to the constructors and in `get_relevant_documents`. I also add one missing pip install to the accompanying notebook (I am not adding dependencies, they were pre-existing). First contribution, just hoping to help, feel free to critique :) my twitter username is `@andreliebschner` While looking at hybrid search I noticed #3043 and #1743. I think the former can be closed as following the example right now (even prior to my improvements) works just fine, the latter I think can be also closed safely, maybe pointing out the relevant classes and example. Should I reply those issues mentioning someone? @dev2049, @hwchase17 --------- Co-authored-by: Andreas Liebschner <a.liebschner@shopfully.com>	1 year ago
Deepak S V	5cd12102be	Improving Resilience of MRKL Agent (#5014 ) This is a highly optimized update to the pull request https://github.com/hwchase17/langchain/pull/3269 Summary: 1) Added ability to MRKL agent to self solve the ValueError(f"Could not parse LLM output: `{llm_output}`") error, whenever llm (especially gpt-3.5-turbo) does not follow the format of MRKL Agent, while returning "Action:" & "Action Input:". 2) The way I am solving this error is by responding back to the llm with the messages "Invalid Format: Missing 'Action:' after 'Thought:'" & "Invalid Format: Missing 'Action Input:' after 'Action:'" whenever Action: and Action Input: are not present in the llm output respectively. For a detailed explanation, look at the previous pull request. New Updates: 1) Since @hwchase17 , requested in the previous PR to communicate the self correction (error) message, using the OutputParserException, I have added new ability to the OutputParserException class to store the observation & previous llm_output in order to communicate it to the next Agent's prompt. This is done, without breaking/modifying any of the functionality OutputParserException previously performs (i.e. OutputParserException can be used in the same way as before, without passing any observation & previous llm_output too). --------- Co-authored-by: Deepak S V <svdeepak99@users.noreply.github.com>	1 year ago
Michael Landis	6eacd88ae7	fix: revert docarray explicit transitive dependencies and use extras instead (#5015 ) tldr: The docarray [integration PR](https://github.com/hwchase17/langchain/pull/4483) introduced a pinned dependency to protobuf. This is a docarray dependency, not a langchain dependency. Since this is handled by the docarray dependencies, it is unnecessary here. Further, as a pinned dependency, this quickly leads to incompatibilities with application code that consumes the library. Much less with a heavily used library like protobuf. Detail: as we see in the [docarray integration](https://github.com/hwchase17/langchain/pull/4483/files#diff-50c86b7ed8ac2cf95bd48334961bf0530cdc77b5a56f852c5c61b89d735fd711R81-R83), the transitive dependencies of docarray were also listed as langchain dependencies. This is unnecessary as the docarray project has an appropriate [extras](`a01a05542d/pyproject.toml (L70)`). The docarray project also does not require this _pinned_ version of protobuf, rather [a minimum version](`a01a05542d/pyproject.toml (L41)`). So this pinned version was likely in error. To fix this, this PR reverts the explicit hnswlib and protobuf dependencies and adds the hnswlib extras install for docarray (which installs hnswlib and protobuf, as originally intended). Because version `0.32.0` of the docarray hnswlib extras added protobuf, we bump the docarray dependency from `^0.31.0` to `^0.32.0`. # revert docarray explicit transitive dependencies and use extras instead ## Who can review? @dev2049 -- reviewed the original PR @eyurtsev -- bumped the pinned protobuf dependency a few days ago --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Davis Chase	fcd88bccb3	Bump 177 (#5095 )	1 year ago
Harrison Chase	10ba201d05	Harrison/neo4j (#5078 ) Co-authored-by: Tomaz Bratanic <bratanic.tomaz@gmail.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Deepak S V	49ca02711e	Improved query, print & exception handling in REPL Tool (#4997 ) Update to pull request https://github.com/hwchase17/langchain/pull/3215 Summary: 1) Improved the sanitization of query (using regex), by removing python command (since gpt-3.5-turbo sometimes assumes python console as a terminal, and runs python command first which causes error). Also sometimes 1 line python codes contain single backticks. 2) Added 7 new test cases. For more details, view the previous pull request. --------- Co-authored-by: Deepak S V <svdeepak99@users.noreply.github.com>	1 year ago
Zander Chase	785502edb3	Add 'get_token_ids' method (#4784 ) Let user inspect the token ids in addition to getting th enumber of tokens --------- Co-authored-by: Zach Schillaci <40636930+zachschillaci27@users.noreply.github.com>	1 year ago
Zander Chase	ef7d015be5	Separate Runner Functions from Client (#5079 ) Extract the methods specific to running an LLM or Chain on a dataset to separate utility functions. This simplifies the client a bit and lets us separate concerns of LCP details from running examples (e.g., for evals)	1 year ago
Leonid Ganeline	443ebe22f4	docs: `Deployments` page moved into `Ecosystem/` (#4949 ) # docs: `deployments` page moved into `ecosystem/` The `Deployments` page moved into the `Ecosystem/` group Small fixes: - `index` page: fixed order of items in the `Modules` list, in the `Use Cases` list - item `References/Installation` was lost in the `index` page (not on the Navbar!). Restored it. - added `\|` marker in several places. NOTE: I also thought about moving the `Additional Resources/Gallery` page into the `Ecosystem` group but decided to leave it unchanged. Please, advise on this. ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested: @dev2049	1 year ago
Hans van Dam	a395ff7c90	preserve language in conversation retrieval (#4969 ) Without the addition of 'in its original language', the condensing response, more often than not, outputs the rephrased question in English, even when the conversation is in another language. This question in English then transfers to the question in the retrieval prompt and the chatbot is stuck in English. I'm sometimes surprised that this does not happen more often, but apparently the GPT models are smart enough to understand that when the template contains Question: .... Answer: then the answer should be in in the language of the question.	1 year ago
Matt Robinson	bf3f554357	feat: batch multiple files in a single Unstructured API request (#4525 ) ### Submit Multiple Files to the Unstructured API Enables batching multiple files into a single Unstructured API requests. Support for requests with multiple files was added to both `UnstructuredAPIFileLoader` and `UnstructuredAPIFileIOLoader`. Note that if you submit multiple files in "single" mode, the result will be concatenated into a single document. We recommend using this feature in "elements" mode. ### Testing The following should load both documents, using two of the example docs from the integration tests folder. ```python from langchain.document_loaders import UnstructuredAPIFileLoader file_paths = ["examples/layout-parser-paper.pdf", "examples/whatsapp_chat.txt"] loader = UnstructuredAPIFileLoader( file_paths=file_paths, api_key="FAKE_API_KEY", strategy="fast", mode="elements", ) docs = loader.load() ```	1 year ago
Harrison Chase	0c3de0a0b3	Merge branch 'master' of github.com:hwchase17/langchain	1 year ago
Harrison Chase	224f73e978	move docs	1 year ago
Harrison Chase	6c25f860fd	bump to 176 (#5064 )	1 year ago
Harrison Chase	b0431c672b	Harrison/psychic (#5063 ) Co-authored-by: Ayan Bandyopadhyay <ayanb9440@gmail.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago

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