Commit Graph

156 Commits (b2d9970fc1ae93610ab4e3d07d1796f8174fdf43)

Author SHA1 Message Date
anifort 900c1f3e8d
Add support for structured data sources with google enterprise search (#9037)
<!-- Thank you for contributing to LangChain!

Replace this comment with:
- Description: Added the capability to handles structured data from
google enterprise search,
- Issue: Retriever failed when underline search engine was integrated
with structured data,
  - Dependencies: google-api-core
  - Tag maintainer: @jarokaz
  - Twitter handle: anifort

Please make sure you're PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.

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.

Maintainer responsibilities:
  - General / Misc / if you don't know who to tag: @baskaryan
  - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
  - Models / Prompts: @hwchase17, @baskaryan
  - Memory: @hwchase17
  - Agents / Tools / Toolkits: @hinthornw
  - Tracing / Callbacks: @agola11
  - Async: @agola11

If no one reviews your PR within a few days, feel free to @-mention the
same people again.

See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md
 -->

---------

Co-authored-by: Christos Aniftos <aniftos@google.com>
Co-authored-by: Holt Skinner <13262395+holtskinner@users.noreply.github.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
1 year ago
Jacob Lee 632a83c48e
Update ChatOpenAI docs with fine-tuning example (#9632) 1 year ago
Adilkhan Sarsen f29312eb84
Fixing deeplake.mdx file as it uses outdates links (#9602)
deeplake.mdx was using old links and was not working properly, in the PR
we fix the issue.
1 year ago
klae01 b868ef23bc
Add AINetwork blockchain toolkit integration (#9527)
# Description
This PR introduces a new toolkit for interacting with the AINetwork
blockchain. The toolkit provides a set of tools for performing various
operations on the AINetwork blockchain, such as transferring AIN,
reading and writing values to the blockchain database, managing apps,
setting rules and owners.

# Dependencies
[ain-py](https://github.com/ainblockchain/ain-py) >= 1.0.2

# Misc
The example notebook
(langchain/docs/extras/integrations/toolkits/ainetwork.ipynb) is in the
PR

---------

Co-authored-by: kriii <kriii@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
toddkim95 fba29f203a
Add to support polars (#9610)
### Description
Polars is a DataFrame interface on top of an OLAP Query Engine
implemented in Rust.
Polars is faster to read than pandas, so I'm looking forward to seeing
it added to the document loader.

### Dependencies
polars (https://pola-rs.github.io/polars-book/user-guide/)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Zizhong Zhang 00eff8c4a7
feat: Add PromptGuard integration (#9481)
Add PromptGuard integration
-------
There are two approaches to integrate PromptGuard with a LangChain
application.

1. PromptGuardLLMWrapper
2. functions that can be used in LangChain expression.

-----
- Dependencies
`promptguard` python package, which is a runtime requirement if you'd
try out the demo.

- @baskaryan @hwchase17 Thanks for the ideas and suggestions along the
development process.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Matthew Zeiler 949b2cf177
Improvements to the Clarifai integration (#9290)
- Improved docs
- Improved performance in multiple ways through batching, threading,
etc.
 - fixed error message 
 - Added support for metadata filtering during similarity search.

@baskaryan PTAL
1 year ago
ricki-epsilla 66a47d9a61
add Epsilla vectorstore (#9239)
[Epsilla](https://github.com/epsilla-cloud/vectordb) vectordb is an
open-source vector database that leverages the advanced academic
parallel graph traversal techniques for vector indexing.
This PR adds basic integration with
[pyepsilla](https://github.com/epsilla-cloud/epsilla-python-client)(Epsilla
vectordb python client) as a vectorstore.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
axiangcoding 05aa02005b
feat(llms): support ERNIE Embedding-V1 (#9370)
- Description: support [ERNIE
Embedding-V1](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/alj562vvu),
which is part of ERNIE ecology
- Issue: None
- Dependencies: None
- Tag maintainer: @baskaryan

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
José Ferraz Neto f116e10d53
Add SharePoint Loader (#4284)
- Added a loader (`SharePointLoader`) that can pull documents (`pdf`,
`docx`, `doc`) from the [SharePoint Document
Library](https://support.microsoft.com/en-us/office/what-is-a-document-library-3b5976dd-65cf-4c9e-bf5a-713c10ca2872).
- Added a Base Loader (`O365BaseLoader`) to be used for all Loaders that
use [O365](https://github.com/O365/python-o365) Package
- Code refactoring on `OneDriveLoader` to use the new `O365BaseLoader`.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Utku Ege Tuluk bb4f7936f9
feat(llms): add streaming support to textgen (#9295)
- Description: Added streaming support to the textgen component in the
llms module.
  - Dependencies: websocket-client = "^1.6.1"
1 year ago
Leonid Ganeline fdbeb52756
`Qwen` model example (#9516)
added an example for `Qwen-7B` model on `HugginfFaceHub` 🤗
1 year ago
Martin Schade 0c8a88b3fa
AmazonTextractPDFLoader documentation updates (#9415)
Description: Updating documentation to add AmazonTextractPDFLoader
according to
[comment](https://github.com/langchain-ai/langchain/pull/8661#issuecomment-1666572992)
from [baskaryan](https://github.com/baskaryan)

Adding one notebook and instructions to the
modules/data_connection/document_loaders/pdf.mdx

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
Asif Ahmad 08feed3332
Changed the NIBittensorLLM API URL to the correct one (#9419)
Changed https://api.neuralinterent.ai/ to https://api.neuralinternet.ai/
which is the valid URL for the API of NIBittensorLLM.
1 year ago
bsenst a956b69720
fix typo in huggingface_hub.ipynb (#9499) 1 year ago
Matt Robinson 83d2a871eb
fix: apply unstructured preprocess functions (#9473)
### Summary

Fixes a bug from #7850 where post processing functions in Unstructured
loaders were not apply. Adds a assertion to the test to verify the post
processing function was applied and also updates the explanation in the
example notebook.
1 year ago
Leonid Ganeline 99e5eaa9b1
`InternLM` example (#9465)
Added `InternML` model example to the HubbingFace Hub notebook
1 year ago
William FH d4f790fd40
Fix imports in notebook (#9458) 1 year ago
Angel Luis 2e8733cf54
Fix typo in huggingface_textgen_inference.ipynb (#9313)
Replaced incorrect `stream` parameter by `streaming` on Integrations
docs.
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 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
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
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
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
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
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
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
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