langchain

Commit Graph

Author	SHA1	Message	Date
Eugene Yurtsev	5cfa72a130	Bibtex integration for document loader and retriever (#5137 ) # Bibtex integration Wrap bibtexparser to retrieve a list of docs from a bibtex file. * Get the metadata from the bibtex entries * `page_content` get from the local pdf referenced in the `file` field of the bibtex entry using `pymupdf` * If no valid pdf file, `page_content` set to the `abstract` field of the bibtex entry * Support Zotero flavour using regex to get the file path * Added usage example in `docs/modules/indexes/document_loaders/examples/bibtex.ipynb` --------- Co-authored-by: Sébastien M. Popoff <sebastien.popoff@espci.fr> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Harrison Chase	a775aa6389	Harrison/vertex (#5049 ) Co-authored-by: Leonid Kuligin <kuligin@google.com> Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru> Co-authored-by: sasha-gitg <44654632+sasha-gitg@users.noreply.github.com> Co-authored-by: Justin Flick <Justinjayflick@gmail.com> Co-authored-by: Justin Flick <jflick@homesite.com>	1 year ago
Zander Chase	e76e68b211	Add Delete Session Method (#5193 )	1 year ago
Alon Diament	44abe925df	Add Joplin document loader (#5153 ) # Add Joplin document loader [Joplin](https://joplinapp.org/) is an open source note-taking app. Joplin has a [REST API](https://joplinapp.org/api/references/rest_api/) for accessing its local database. The proposed `JoplinLoader` uses the API to retrieve all notes in the database and their metadata. Joplin needs to be installed and running locally, and an access token is required. - The PR includes an integration test. - The PR includes an example notebook. --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
ByronHsu	f0730c6489	Allow readthedoc loader to pass custom html tag (#5175 ) ## Description The html structure of readthedocs can differ. Currently, the html tag is hardcoded in the reader, and unable to fit into some cases. This pr includes the following changes: 1. Replace `find_all` with `find` because we just want one tag. 2. Provide `custom_html_tag` to the loader. 3. Add tests for readthedoc loader 4. Refactor code ## Issues See more in https://github.com/hwchase17/langchain/pull/2609. The problem was not completely fixed in that pr. --------- Signed-off-by: byhsu <byhsu@linkedin.com> Co-authored-by: byhsu <byhsu@linkedin.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Tommaso De Lorenzo	52714cedd4	fixing total cost finetuned model giving zero (#5144 ) # OpanAI finetuned model giving zero tokens cost Very simple fix to the previously committed solution to allowing finetuned Openai models. Improves #5127 --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Harrison Chase	94cf391ef1	standardize json parsing (#5168 ) Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Davis Chase	2b2176a3c1	tfidf retriever (#5114 ) Co-authored-by: vempaliakhil96 <vempaliakhil96@gmail.com>	1 year ago
Harrison Chase	11c26ebb55	Harrison/modelscope (#5156 ) Co-authored-by: thomas-yanxin <yx20001210@163.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	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
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
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
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
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
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
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
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
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
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	b0431c672b	Harrison/psychic (#5063 ) Co-authored-by: Ayan Bandyopadhyay <ayanb9440@gmail.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Davis Chase	3bc0bf0079	fix prompt saving (#4987 ) will add unit tests	1 year ago
Davis Chase	080eb1b3fc	Fix graphql tool (#4984 ) Fix construction and add unit test.	1 year ago
Mike McGarry	ddd595fe81	feature/4493 Improve Evernote Document Loader (#4577 ) # Improve Evernote Document Loader When exporting from Evernote you may export more than one note. Currently the Evernote loader concatenates the content of all notes in the export into a single document and only attaches the name of the export file as metadata on the document. This change ensures that each note is loaded as an independent document and all available metadata on the note e.g. author, title, created, updated are added as metadata on each document. It also uses an existing optional dependency of `html2text` instead of `pypandoc` to remove the need to download the pandoc application via `download_pandoc()` to be able to use the `pypandoc` python bindings. Fixes #4493 Co-authored-by: Mike McGarry <mike.mcgarry@finbourne.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Eugene Yurtsev	0ff59569dc	Adds 'IN' metadata filter for pgvector for checking set presence (#4982 ) # Adds "IN" metadata filter for pgvector to all checking for set presence PGVector currently supports metadata filters of the form: ``` {"filter": {"key": "value"}} ``` which will return documents where the "key" metadata field is equal to "value". This PR adds support for metadata filters of the form: ``` {"filter": {"key": { "IN" : ["list", "of", "values"]}}} ``` Other vector stores support this via an "$in" syntax. I chose to use "IN" to match postgres' syntax, though happy to switch. Tested locally with PGVector and ChatVectorDBChain. @dev2049 --------- Co-authored-by: jade@spanninglabs.com <jade@spanninglabs.com>	1 year ago
Eugene Yurtsev	06e524416c	power bi api wrapper integration tests & bug fix (#4983 ) # Powerbi API wrapper bug fix + integration tests - Bug fix by removing `TYPE_CHECKING` in in utilities/powerbi.py - Added integration test for power bi api in utilities/test_powerbi_api.py - Added integration test for power bi agent in agent/test_powerbi_agent.py - Edited .env.examples to help set up power bi related environment variables - Updated demo notebook with working code in docs../examples/powerbi.ipynb - AzureOpenAI -> ChatOpenAI Notes: Chat models (gpt3.5, gpt4) are much more capable than davinci at writing DAX queries, so that is important to getting the agent to work properly. Interestingly, gpt3.5-turbo needed the examples=DEFAULT_FEWSHOT_EXAMPLES to write consistent DAX queries, so gpt4 seems necessary as the smart llm. Fixes #4325 ## Before submitting Azure-core and Azure-identity are necessary dependencies check integration tests with the following: `pytest tests/integration_tests/utilities/test_powerbi_api.py` `pytest tests/integration_tests/agent/test_powerbi_agent.py` You will need a power bi account with a dataset id + table name in order to test. See .env.examples for details. ## Who can review? @hwchase17 @vowelparrot --------- Co-authored-by: aditya-pethe <adityapethe1@gmail.com>	1 year ago
Harrison Chase	88a3a56c1a	Add Spark SQL support (#4602 ) (#4956 ) # Add Spark SQL support * Add Spark SQL support. It can connect to Spark via building a local/remote SparkSession. * Include a notebook example I tried some complicated queries (window function, table joins), and the tool works well. Compared to the [Spark Dataframe agent](https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html), this tool is able to generate queries across multiple tables. --------- # Your PR Title (What it does) <!-- 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 # (issue) ## 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: Gengliang Wang <gengliang@apache.org> Co-authored-by: Mike W <62768671+skcoirz@users.noreply.github.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: UmerHA <40663591+UmerHA@users.noreply.github.com> Co-authored-by: 张城铭 <z@hyperf.io> Co-authored-by: assert <zhangchengming@kkguan.com> Co-authored-by: blob42 <spike@w530> Co-authored-by: Yuekai Zhang <zhangyuekai@foxmail.com> Co-authored-by: Richard He <he.yucheng@outlook.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com> Co-authored-by: Leonid Ganeline <leo.gan.57@gmail.com> Co-authored-by: Alexey Nominas <60900649+Chae4ek@users.noreply.github.com> Co-authored-by: elBarkey <elbarkey@gmail.com> Co-authored-by: Davis Chase <130488702+dev2049@users.noreply.github.com> Co-authored-by: Jeffrey D <1289344+verygoodsoftwarenotvirus@users.noreply.github.com> Co-authored-by: so2liu <yangliu35@outlook.com> Co-authored-by: Viswanadh Rayavarapu <44315599+vishwa-rn@users.noreply.github.com> Co-authored-by: Chakib Ben Ziane <contact@blob42.xyz> Co-authored-by: Daniel Chalef <131175+danielchalef@users.noreply.github.com> Co-authored-by: Daniel Chalef <daniel.chalef@private.org> Co-authored-by: Jari Bakken <jari.bakken@gmail.com> Co-authored-by: escafati <scafatieugenio@gmail.com>	1 year ago
Daniel Chalef	c8c2276ccb	Zep Retriever - Vector Search Over Chat History (#4533 ) # Zep Retriever - Vector Search Over Chat History with the Zep Long-term Memory Service More on Zep: https://github.com/getzep/zep Note: This PR is related to and relies on https://github.com/hwchase17/langchain/pull/4834. I did not want to modify the `pyproject.toml` file to add the `zep-python` dependency a second time. Co-authored-by: Daniel Chalef <daniel.chalef@private.org>	1 year ago
Davis Chase	55baa0d153	Update redis integration tests (#4937 )	1 year ago
Harrison Chase	c9a362e482	add alias for model (#4553 ) Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Eugene Yurtsev	e46202829f	feat #4479 : TextLoader auto detect encoding and improved exceptions (#4927 ) # TextLoader auto detect encoding and enhanced exception handling - Add an option to enable encoding detection on `TextLoader`. - The detection is done using `chardet` - The loading is done by trying all detected encodings by order of confidence or raise an exception otherwise. ### New Dependencies: - `chardet` Fixes #4479 ## 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: - @eyurtsev --------- Co-authored-by: blob42 <spike@w530>	1 year ago
Harrison Chase	9e2227ba11	Harrison/serper api bug (#4902 ) Co-authored-by: Jerry Luan <xmaswillyou@gmail.com>	1 year ago
Davis Chase	8966f61ca5	Zep memory (#4898 ) Co-authored-by: Daniel Chalef <daniel.chalef@private.org> Co-authored-by: Daniel Chalef <131175+danielchalef@users.noreply.github.com>	1 year ago
Davis Chase	e28bdf4453	Cadlabs/python tool sanitization (#4754 ) Co-authored-by: BenSchZA <BenSchZA@users.noreply.github.com>	1 year ago
Eugene Yurtsev	0dc304ca80	Add html parsers (#4874 ) # Add bs4 html parser * Some minor refactors * Extract the bs4 html parsing code from the bs html loader * Move some tests from integration tests to unit tests	1 year ago
Eugene Yurtsev	8e41143bf5	Add a generic document loader (#4875 ) # Add generic document loader * This PR adds a generic document loader which can assemble a loader from a blob loader and a parser * Adds a registry for parsers * Populate registry with a default mimetype based parser ## Expected changes - Parsing involves loading content via IO so can be sped up via: * Threading in sync * Async - The actual parsing logic may be computatinoally involved: may need to figure out to add multi-processing support - May want to add suffix based parser since suffixes are easier to specify in comparison to mime types ## Before submitting No notebooks yet, we first need to get a few of the basic parsers up (prior to advertising the interface)	1 year ago
yujiosaka	2f8eb95a91	Remove unnecessary comment (#4845 ) # Remove unnecessary comment Remove unnecessary comment accidentally included in #4800 ## Before submitting - no test - no document ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested:	1 year ago
Zander Chase	8dcad0f272	Add Support for Flexible Input Format for LLM and Chat Model Runs (#4805 ) Previously, the client expected a strict 'prompt' or 'messages' format and wouldn't permit running a chat model or llm on prompts or messages (respectively). Since many datasets may want to specify custom key: string , relax this requirement. Also, add support for running a chat model on raw prompts and LLM on chat messages through their respective fallbacks.	1 year ago
Ankush Gola	aa73a888fa	Some notebook and client fixes (add retries, clean up docs, etc) (#4820 ) # Your PR Title (What it does) <!-- 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 # (issue) ## 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 -->	1 year ago
charosen	75fe9d3555	Add from_file method to message prompt template (#4713 ) Feature: This PR adds `from_template_file` class method to BaseStringMessagePromptTemplate. This is useful to help user to create message prompt templates directly from template files, including `ChatMessagePromptTemplate`, `HumanMessagePromptTemplate`, `AIMessagePromptTemplate` & `SystemMessagePromptTemplate`. Tests: Unit tests have been added in this PR. Co-authored-by: charosen <charosen@bupt.cn> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
yujiosaka	6561efebb7	Accept uuids kwargs for weaviate (#4800 ) # Accept uuids kwargs for weaviate Fixes #4791	1 year ago
Adam Quigley	e78c9be312	Add Confluence Loader unit tests (#3333 ) Adds some basic unit tests for the ConfluenceLoader that can be extended later. Ports this [PR from llama-hub](https://github.com/emptycrown/llama-hub/pull/208) and adapts it to `langchain`. @Jflick58 and @zywilliamli adding you here as potential reviewers --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago
Magnus Friberg	d126276693	Specify which data to return from chromadb (#4393 ) # Improve the Chroma get() method by adding the optional "include" parameter. The Chroma get() method excludes embeddings by default. You can customize the response by specifying the "include" parameter to selectively retrieve the desired data from the collection. --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>	1 year ago

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