Commit Graph

173 Commits

Author SHA1 Message Date
Lakshay Kansal
a8c916955f
Updates to Nomic Atlas and GPT4All documentation (#9414)
Description: Updates for Nomic AI Atlas and GPT4All integrations
documentation.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-08-23 17:49:44 -07:00
Keras Conv3d
cbaea8d63b
tair fix distance_type error, and add hybrid search (#9531)
- fix: distance_type error, 
- feature: Tair add hybrid search

---------

Co-authored-by: thw <hanwen.thw@alibaba-inc.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-08-23 16:38:31 -07:00
Jacob Lee
278ef0bdcf
Adds ChatOllama (#9628)
@rlancemartin

---------

Co-authored-by: Adilkhan Sarsen <54854336+adolkhan@users.noreply.github.com>
Co-authored-by: Kim Minjong <make.dirty.code@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-08-23 13:02:26 -07:00
Bagatur
a40c12bb88
Update the nlpcloud connector after some changes on the NLP Cloud API (#9586)
- Description: remove some text generation deprecated parameters and
update the embeddings doc,
- Tag maintainer: @rlancemartin
2023-08-23 11:35:08 -07:00
Bagatur
e2e582f1f6
Fixed source key name for docugami loader (#8598)
The Docugami loader was not returning the source metadata key. This was
triggering this exception when used with retrievers, per
https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/schema/prompt_template.py#L193C1-L195C41

The fix is simple and just updates the metadata key name for the
document each chunk is sourced from, from "name" to "source" as
expected.

I tested by running the python notebook that has an end to end scenario
in it.

Tagging DataLoader maintainers @rlancemartin @eyurtsev
2023-08-23 11:24:55 -07:00
Zizhong Zhang
8a03836160
docs: fix PromptGuard docs (#9659)
Fix PromptGuard docs. Noticed several trivial issues on the docs when
integrating the new class.
cc @baskaryan
2023-08-23 10:04:53 -07:00
Yong woo Song
f0ae10a20e
Fix typo in tigris (#9637)
The link has a **typo** in [tigirs
docs](https://python.langchain.com/docs/integrations/providers/tigris),
so I couldn't access it. So, I have corrected it.
Thanks! ☺️
2023-08-23 07:15:18 -07:00
Joseph McElroy
2a06e7b216
ElasticsearchStore: improve error logging for adding documents (#9648)
Not obvious what the error is when you cannot index. This pr adds the
ability to log the first errors reason, to help the user diagnose the
issue.

Also added some more documentation for when you want to use the
vectorstore with an embedding model deployed in elasticsearch.

Credit: @elastic and @phoey1
2023-08-23 07:04:09 -07:00
Julien Salinas
f1072cc31f
Merge branch 'master' into master 2023-08-23 14:42:40 +02:00
Leonid Ganeline
e1f4f9ac3e
docs: integrations/providers (#9631)
Added missed pages for `integrations/providers` from `vectorstores`.
Updated several `vectorstores` notebooks.
2023-08-22 20:28:11 -07:00
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>
2023-08-22 23:18:10 -04:00
Jacob Lee
632a83c48e
Update ChatOpenAI docs with fine-tuning example (#9632) 2023-08-22 16:56:53 -07:00
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.
2023-08-22 15:12:24 -07:00
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>
2023-08-22 08:03:33 -07:00
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>
2023-08-22 07:36:24 -07:00
Julien Salinas
4d0b7bb8e1 Remove Dolphin and GPT-J from the embeddings docs.
These models are not proposed anymore.
2023-08-22 09:28:22 +02:00
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>
2023-08-21 14:59:36 -07:00
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
2023-08-21 12:53:36 -07:00
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>
2023-08-21 12:51:15 -07:00
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>
2023-08-21 07:52:25 -07:00
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>
2023-08-21 07:49:07 -07:00
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"
2023-08-21 07:39:14 -07:00
Leonid Ganeline
fdbeb52756
Qwen model example (#9516)
added an example for `Qwen-7B` model on `HugginfFaceHub` 🤗
2023-08-20 17:21:45 -07:00
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>
2023-08-20 16:40:15 -07:00
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.
2023-08-20 16:25:19 -07:00
bsenst
a956b69720
fix typo in huggingface_hub.ipynb (#9499) 2023-08-19 14:50:05 -07:00
Taqi Jaffri
069c0a041f comment update for poetry install 2023-08-19 13:50:16 -07:00
Taqi Jaffri
5cd244e9b7 CR feedback 2023-08-19 13:48:15 -07:00
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.
2023-08-18 18:54:28 -07:00
Leonid Ganeline
99e5eaa9b1
InternLM example (#9465)
Added `InternML` model example to the HubbingFace Hub notebook
2023-08-18 11:17:17 -07:00
William FH
d4f790fd40
Fix imports in notebook (#9458) 2023-08-18 10:08:47 -07:00
Angel Luis
2e8733cf54
Fix typo in huggingface_textgen_inference.ipynb (#9313)
Replaced incorrect `stream` parameter by `streaming` on Integrations
docs.
2023-08-16 16:22:21 -07:00
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
2023-08-16 00:48:42 -07:00
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>
2023-08-16 00:23:07 -07:00
Bagatur
9abf60acb6
Bagatur/vectara regression (#9276)
Co-authored-by: Ofer Mendelevitch <ofer@vectara.com>
Co-authored-by: Ofer Mendelevitch <ofermend@gmail.com>
2023-08-15 16:19:46 -07:00
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>
2023-08-15 16:19:30 -07:00
Bagatur
bfbb97b74c
Bagatur/deeplake docs fixes (#9275)
Co-authored-by: adilkhan <adilkhan.sarsen@nu.edu.kz>
2023-08-15 15:56:36 -07:00
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>
2023-08-15 15:40:52 -07:00
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>
2023-08-15 15:33:07 -07:00
Bagatur
1aae77f26f
fix context nb (#9267) 2023-08-15 12:53:37 -07:00
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!
2023-08-15 11:38:34 -07:00
Anthony Mahanna
0a04e63811
docs: Update ArangoDB Links (#9251)
ready for review 

- mdx link update
- colab link update
2023-08-15 07:43:47 -07:00
Hech
4b505060bd
fix: max_marginal_relevance_search and docs in Dingo (#9244) 2023-08-15 01:06:06 -07:00
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
2023-08-15 01:05:46 -07:00
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
2023-08-15 00:50:20 -07:00
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 .
2023-08-14 23:44:29 -07:00
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>
2023-08-14 23:42:35 -07:00
Lance Martin
17ae2998e7
Update Ollama docs (#9220)
Based on discussion w/ team.
2023-08-14 13:56:16 -07:00
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>
2023-08-14 07:43:40 -07:00
Emmanuel Gautier
f11e5442d6
docs: update LlamaCpp input args (#9173)
This PR only updates the LlamaCpp args documentation. The input arg has
been flattened.
2023-08-14 07:42:03 -07:00