langchain

Commit Graph

Author	SHA1	Message	Date
Navanit Dubey	3e6cea46e2	Guide import readable json (#9291 )	1 year ago
axiangcoding	63601551b1	fix(llms): improve the ernie chat model (#9289 ) - Description: improve the ernie chat model. - fix missing kwargs to payload - new test cases - add some debug level log - improve description - Issue: None - Dependencies: None - Tag maintainer: @baskaryan	1 year ago
Daniel Chalef	1d55141c50	zep/new ZepVectorStore (#9159 ) - new ZepVectorStore class - ZepVectorStore unit tests - ZepVectorStore demo notebook - update zep-python to ~1.0.2 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	b9ca5cc5ea	update guide import (#9279 )	1 year ago
Bagatur	afba2be3dc	update openai functions docs (#9278 )	1 year ago
Bagatur	9abf60acb6	Bagatur/vectara regression (#9276 ) Co-authored-by: Ofer Mendelevitch <ofer@vectara.com> Co-authored-by: Ofer Mendelevitch <ofermend@gmail.com>	1 year ago
Xiaoyu Xee	b30f449dae	Add dashvector vectorstore (#9163 ) ## Description Add `Dashvector` vectorstore for langchain - [dashvector quick start](https://help.aliyun.com/document_detail/2510223.html) - [dashvector package description](https://pypi.org/project/dashvector/) ## How to use ```python from langchain.vectorstores.dashvector import DashVector dashvector = DashVector.from_documents(docs, embeddings) ``` --------- Co-authored-by: smallrain.xuxy <smallrain.xuxy@alibaba-inc.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	bfbb97b74c	Bagatur/deeplake docs fixes (#9275 ) Co-authored-by: adilkhan <adilkhan.sarsen@nu.edu.kz>	1 year ago
Kunj-2206	1b3942ba74	Added BittensorLLM (#9250 ) Description: Adding NIBittensorLLM via Validator Endpoint to langchain llms Tag maintainer: @Kunj-2206 Maintainer responsibilities: Models / Prompts: @hwchase17, @baskaryan --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Toshish Jawale	852722ea45	Improvements in Nebula LLM (#9226 ) - Description: Added improvements in Nebula LLM to perform auto-retry; more generation parameters supported. Conversation is no longer required to be passed in the LLM object. Examples are updated. - Issue: N/A - Dependencies: N/A - Tag maintainer: @baskaryan - Twitter handle: symbldotai --------- Co-authored-by: toshishjawale <toshish@symbl.ai>	1 year ago
Bagatur	1aae77f26f	fix context nb (#9267 )	1 year ago
Alex Gamble	cf17c58b47	Update documentation for the Context integration with new URL and features (#9259 ) Update documentation and URLs for the Langchain Context integration. We've moved from getcontext.ai to context.ai \o/ Thanks in advance for the review!	1 year ago
Joseph McElroy	5e9687a196	Elasticsearch self-query retriever (#9248 ) Now with ElasticsearchStore VectorStore merged, i've added support for the self-query retriever. I've added a notebook also to demonstrate capability. I've also added unit tests. Credit @elastic and @phoey1 on twitter.	1 year ago
Anthony Mahanna	0a04e63811	docs: Update ArangoDB Links (#9251 ) ready for review - mdx link update - colab link update	1 year ago
Hech	4b505060bd	fix: max_marginal_relevance_search and docs in Dingo (#9244 )	1 year ago
axiangcoding	664ff28cba	feat(llms): support ernie chat (#9114 ) Description: support ernie (文心一言) chat model Related issue: #7990 Dependencies: None Tag maintainer: @baskaryan	1 year ago
fanyou-wbd	5e43768f61	docs: update LlamaCpp max_tokens args (#9238 ) This PR updates documentations only, `max_length` should be `max_tokens` according to latest LlamaCpp API doc: https://api.python.langchain.com/en/latest/llms/langchain.llms.llamacpp.LlamaCpp.html	1 year ago
Bagatur	a8aa1aba1c	nit (#9243 )	1 year ago
Bagatur	68d8f73698	consolidate redirects (#9242 )	1 year ago
Joshua Sundance Bailey	ef0664728e	ArcGISLoader update (#9240 ) Small bug fixes and added metadata based on user feedback. This PR is from the author of https://github.com/langchain-ai/langchain/pull/8873 .	1 year ago
Joseph McElroy	eac4ddb4bb	Elasticsearch Store Improvements (#8636 ) Todo: - [x] Connection options (cloud, localhost url, es_connection) support - [x] Logging support - [x] Customisable field support - [x] Distance Similarity support - [x] Metadata support - [x] Metadata Filter support - [x] Retrieval Strategies - [x] Approx - [x] Approx with Hybrid - [x] Exact - [x] Custom - [x] ELSER (excluding hybrid as we are working on RRF support) - [x] integration tests - [x] Documentation 👋 this is a contribution to improve Elasticsearch integration with Langchain. Its based loosely on the changes that are in master but with some notable changes: ## Package name & design improvements The import name is now `ElasticsearchStore`, to aid discoverability of the VectorStore. ```py ## Before from langchain.vectorstores.elastic_vector_search import ElasticVectorSearch, ElasticKnnSearch ## Now from langchain.vectorstores.elasticsearch import ElasticsearchStore ``` ## Retrieval Strategy support Before we had a number of classes, depending on the strategy you wanted. `ElasticKnnSearch` for approx, `ElasticVectorSearch` for exact / brute force. With `ElasticsearchStore` we have retrieval strategies: ### Approx Example Default strategy for the vast majority of developers who use Elasticsearch will be inferring the embeddings from outside of Elasticsearch. Uses KNN functionality of _search. ```py texts = ["foo", "bar", "baz"] docsearch = ElasticsearchStore.from_texts( texts, FakeEmbeddings(), es_url="http://localhost:9200", index_name="sample-index" ) output = docsearch.similarity_search("foo", k=1) ``` ### Approx, with hybrid Developers who want to search, using both the embedding and the text bm25 match. Its simple to enable. ```py texts = ["foo", "bar", "baz"] docsearch = ElasticsearchStore.from_texts( texts, FakeEmbeddings(), es_url="http://localhost:9200", index_name="sample-index", strategy=ElasticsearchStore.ApproxRetrievalStrategy(hybrid=True) ) output = docsearch.similarity_search("foo", k=1) ``` ### Approx, with `query_model_id` Developers who want to infer within Elasticsearch, using the model loaded in the ml node. This relies on the developer to setup the pipeline and index if they wish to embed the text in Elasticsearch. Example of this in the test. ```py texts = ["foo", "bar", "baz"] docsearch = ElasticsearchStore.from_texts( texts, FakeEmbeddings(), es_url="http://localhost:9200", index_name="sample-index", strategy=ElasticsearchStore.ApproxRetrievalStrategy( query_model_id="sentence-transformers__all-minilm-l6-v2" ), ) output = docsearch.similarity_search("foo", k=1) ``` ### I want to provide my own custom Elasticsearch Query You might want to have more control over the query, to perform multi-phase retrieval such as LTR, linearly boosting on document parameters like recently updated or geo-distance. You can do this with `custom_query_fn` ```py def my_custom_query(query_body: dict, query: str) -> dict: return {"query": {"match": {"text": {"query": "bar"}}}} texts = ["foo", "bar", "baz"] docsearch = ElasticsearchStore.from_texts( texts, FakeEmbeddings(), **elasticsearch_connection, index_name=index_name ) docsearch.similarity_search("foo", k=1, custom_query=my_custom_query) ``` ### Exact Example Developers who have a small dataset in Elasticsearch, dont want the cost of indexing the dims vs tradeoff on cost at query time. Uses script_score. ```py texts = ["foo", "bar", "baz"] docsearch = ElasticsearchStore.from_texts( texts, FakeEmbeddings(), es_url="http://localhost:9200", index_name="sample-index", strategy=ElasticsearchStore.ExactRetrievalStrategy(), ) output = docsearch.similarity_search("foo", k=1) ``` ### ELSER Example Elastic provides its own sparse vector model called ELSER. With these changes, its really easy to use. The vector store creates a pipeline and index thats setup for ELSER. All the developer needs to do is configure, ingest and query via langchain tooling. ```py texts = ["foo", "bar", "baz"] docsearch = ElasticsearchStore.from_texts( texts, FakeEmbeddings(), es_url="http://localhost:9200", index_name="sample-index", strategy=ElasticsearchStore.SparseVectorStrategy(), ) output = docsearch.similarity_search("foo", k=1) ``` ## Architecture In future, we can introduce new strategies and allow us to not break bwc as we evolve the index / query strategy. ## Credit On release, could you credit @elastic and @phoey1 please? Thank you! --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Harrison Chase	71d5b7c9bf	Harrison/fallbacks (#9233 ) Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Lance Martin	41279a3ae1	Move self-check use case to "more" section (#9137 ) Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Lance Martin	22858d99b5	Move code-writing use case to "more" section (#9134 ) Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	249d7d06a2	adapter doc nit (#9234 )	1 year ago
Lance Martin	969e1683de	Move graph use case to "more" section (#8997 ) Clean `use_cases` by moving the `GraphDB` to `integrations`. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Lance Martin	d0a0d560ad	Minor formatting on Web Research Use Case (#9221 )	1 year ago
Lance Martin	17ae2998e7	Update Ollama docs (#9220 ) Based on discussion w/ team.	1 year ago
Krish Dholakia	49f1d8477c	Adding ChatLiteLLM model (#9020 ) Description: Adding a langchain integration for the LiteLLM library Tag maintainer: @hwchase17, @baskaryan Twitter handle: @krrish_dh / @Berri_AI --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Emmanuel Gautier	f11e5442d6	docs: update LlamaCpp input args (#9173 ) This PR only updates the LlamaCpp args documentation. The input arg has been flattened.	1 year ago
Massimiliano Pronesti	d95eeaedbe	feat(llms): support vLLM's OpenAI-compatible server (#9179 ) This PR aims at supporting [vLLM's OpenAI-compatible server feature](https://vllm.readthedocs.io/en/latest/getting_started/quickstart.html#openai-compatible-server), i.e. allowing to call vLLM's LLMs like if they were OpenAI's. I've also udpated the related notebook providing an example usage. At the moment, vLLM only supports the `Completion` API.	1 year ago
Michael Goin	621da3c164	Adds DeepSparse as an LLM (#9184 ) Adds [DeepSparse](https://github.com/neuralmagic/deepsparse) as an LLM backend. DeepSparse supports running various open-source sparsified models hosted on [SparseZoo](https://sparsezoo.neuralmagic.com/) for performance gains on CPUs. Twitter handles: @mgoin_ @neuralmagic --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	0fa69d8988	Bagatur/zep python 1.0 (#9186 ) Co-authored-by: Daniel Chalef <131175+danielchalef@users.noreply.github.com>	1 year ago
Harrison Chase	8d69dacdf3	multiple retreival in parralel (#9174 )	1 year ago
Eugene Yurtsev	aca8cb5fba	API Reference: Do not document private modules (#9042 ) This PR prevents documentation of private modules in the API reference	1 year ago
UmerHA	8aab39e3ce	Added SmartGPT workflow (issue #4463 ) (#4816 ) # Added SmartGPT workflow by providing SmartLLM wrapper around LLMs Edit: As @hwchase17 suggested, this should be a chain, not an LLM. I have adapted the PR. It is used like this: ``` from langchain.prompts import PromptTemplate from langchain.chains import SmartLLMChain from langchain.chat_models import ChatOpenAI hard_question = "I have a 12 liter jug and a 6 liter jug. I want to measure 6 liters. How do I do it?" hard_question_prompt = PromptTemplate.from_template(hard_question) llm = ChatOpenAI(model_name="gpt-4") prompt = PromptTemplate.from_template(hard_question) chain = SmartLLMChain(llm=llm, prompt=prompt, verbose=True) chain.run({}) ``` Original text: Added SmartLLM wrapper around LLMs to allow for SmartGPT workflow (as in https://youtu.be/wVzuvf9D9BU). SmartLLM can be used wherever LLM can be used. E.g: ``` smart_llm = SmartLLM(llm=OpenAI()) smart_llm("What would be a good company name for a company that makes colorful socks?") ``` or ``` smart_llm = SmartLLM(llm=OpenAI()) prompt = PromptTemplate( input_variables=["product"], template="What is a good name for a company that makes {product}?", ) chain = LLMChain(llm=smart_llm, prompt=prompt) chain.run("colorful socks") ``` SmartGPT consists of 3 steps: 1. Ideate - generate n possible solutions ("ideas") to user prompt 2. Critique - find flaws in every idea & select best one 3. Resolve - improve upon best idea & return it Fixes #4463 ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested: - @hwchase17 - @agola11 Twitter: [@UmerHAdil](https://twitter.com/@UmerHAdil) \| Discord: RicChilligerDude#7589 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Bagatur	45741bcc1b	Bagatur/vectara nit (#9140 ) Co-authored-by: Ofer Mendelevitch <ofer@vectara.com>	1 year ago
Dominick DEV	9b64932e55	Add LangChain utility for real-time crypto exchange prices (#4501 ) This commit adds the LangChain utility which allows for the real-time retrieval of cryptocurrency exchange prices. With LangChain, users can easily access up-to-date pricing information by running the command ".run(from_currency, to_currency)". This new feature provides a convenient way to stay informed on the latest exchange rates and make informed decisions when trading crypto. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Joshua Sundance Bailey	eaa505fb09	Create ArcGISLoader & example notebook (#8873 ) - Description: Adds the ArcGISLoader class to `langchain.document_loaders` - Allows users to load data from ArcGIS Online, Portal, and similar - Users can authenticate with `arcgis.gis.GIS` or retrieve public data anonymously - Uses the `arcgis.features.FeatureLayer` class to retrieve the data - Defines the most relevant keywords arguments and accepts `**kwargs` - Dependencies: Using this class requires `arcgis` and, optionally, `bs4.BeautifulSoup`. Tagging maintainers: - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Aashish Saini	0aabded97f	Updating interactive walkthrough link in index.md to resolve 404 error (#9063 ) Updated interactive walkthrough link in index.md to resolve 404 error. Also, expressing deep gratitude to LangChain library developers for their exceptional efforts 🥇 . --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	1 year ago
Hai The Dude	e4418d1b7e	Added new use case docs for Web Scraping, Chromium loader, BS4 transformer (#8732 ) - Description: Added a new use case category called "Web Scraping", and a tutorial to scrape websites using OpenAI Functions Extraction chain to the docs. - Tag maintainer:@baskaryan @hwchase17 , - Twitter handle: https://www.linkedin.com/in/haiphunghiem/ (I'm on LinkedIn mostly) --------- Co-authored-by: Lance Martin <lance@langchain.dev>	1 year ago
niklub	16af5f8690	Add LabelStudio integration (#8880 ) This PR introduces [Label Studio](https://labelstud.io/) integration with LangChain via `LabelStudioCallbackHandler`: - sending data to the Label Studio instance - labeling dataset for supervised LLM finetuning - rating model responses - tracking and displaying chat history - support for custom data labeling workflow ### Example ``` chat_llm = ChatOpenAI(callbacks=[LabelStudioCallbackHandler(mode="chat")]) chat_llm([ SystemMessage(content="Always use emojis in your responses."), HumanMessage(content="Hey AI, how's your day going?"), AIMessage(content="🤖 I don't have feelings, but I'm running smoothly! How can I help you today?"), HumanMessage(content="I'm feeling a bit down. Any advice?"), AIMessage(content="🤗 I'm sorry to hear that. Remember, it's okay to seek help or talk to someone if you need to. 💬"), HumanMessage(content="Can you tell me a joke to lighten the mood?"), AIMessage(content="Of course! 🎭 Why did the scarecrow win an award? Because he was outstanding in his field! 🌾"), HumanMessage(content="Haha, that was a good one! Thanks for cheering me up."), AIMessage(content="Always here to help! 😊 If you need anything else, just let me know."), HumanMessage(content="Will do! By the way, can you recommend a good movie?"), ]) ``` <img width="906" alt="image" src="https://github.com/langchain-ai/langchain/assets/6087484/0a1cf559-0bd3-4250-ad96-6e71dbb1d2f3"> ### Dependencies - [label-studio](https://pypi.org/project/label-studio/) - [label-studio-sdk](https://pypi.org/project/label-studio-sdk/) https://twitter.com/labelstudiohq --------- Co-authored-by: nik <nik@heartex.net>	1 year ago
Bagatur	8cb2594562	Bagatur/dingo (#9079 ) Co-authored-by: gary <1625721671@qq.com>	1 year ago
Manuel Soria	31cfc00845	Code understanding use case (#8801 ) Code understanding docs --------- Co-authored-by: Manuel Soria <manuel.soria@greyscaleai.com> Co-authored-by: Lance Martin <lance@langchain.dev>	1 year ago
Alvaro Bartolome	f7ae183f40	`ArgillaCallbackHandler` to properly use default values for `api_url` and `api_key` (#9113 ) As of the recent PR at #9043, after some testing we've realised that the default values were not being used for `api_key` and `api_url`. Besides that, the default for `api_key` was set to `argilla.apikey`, but since the default values are intended for people using the Argilla Quickstart (easy to run and setup), the defaults should be instead `owner.apikey` if using Argilla 1.11.0 or higher, or `admin.apikey` if using a lower version of Argilla. Additionally, we've removed the f-string replacements from the docstrings. --------- Co-authored-by: Gabriel Martin <gabriel@argilla.io>	1 year ago
Bagatur	0e5d09d0da	dalle nb fix (#9125 )	1 year ago
Francisco Ingham	9249d305af	tagging docs refactor (#8722 ) refactor of tagging use case according to new format --------- Co-authored-by: Lance Martin <lance@langchain.dev>	1 year ago
Aayush Shah	a429145420	Minor grammatical error (#9102 ) Have corrected a grammatical error in: https://python.langchain.com/docs/modules/model_io/models/llms/ document 😄	1 year ago
Ashutosh Sanzgiri	991b448dfc	minor edits (#9093 ) Description: Minor edit to PR#845 Thanks!	1 year ago
Chenyu Zhao	c0acbdca1b	Update Fireworks model names (#9085 )	1 year ago

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1726 Commits (3e6cea46e25e9d13b3da14cd90e21b99be2e7ba0)