Commit Graph

154 Commits (d2cf0d16b3e814e2bc86472e309c7ad81bf36cdb)

Author SHA1 Message Date
William FH 4789c99bc2
Add String Distance and Embedding Evaluators (#7123)
Add a string evaluator and pairwise string evaluator implementation for:
- Embedding distance
- String distance

Update docs
1 year ago
ljeagle fb6e63dc36
Upgrade the AwaDB from 0.3.5 to 0.3.6 (#7363) 1 year ago
OwenElliott 3074306ae1
Marqo Vector Store Examples & Type Hints (#7326)
This PR improves the example notebook for the Marqo vectorstore
implementation by adding a new RetrievalQAWithSourcesChain example. The
`embedding` parameter in `from_documents` has its type updated to
`Union[Embeddings, None]` and a default parameter of None because this
is ignored in Marqo.

This PR also upgrades the Marqo version to 0.11.0 to remove the device
parameter after a breaking change to the API.

Related to #7068 @tomhamer @hwchase17

---------

Co-authored-by: Tom Hamer <tom@marqo.ai>
1 year ago
Bagatur a9c5b4bcea
Bagatur/clarifai update (#7324)
This PR improves upon the Clarifai LangChain integration with improved docs, errors, args and the addition of embedding model support in LancChain for Clarifai's embedding models and an overview of the various ways you can integrate with Clarifai added to the docs.

---------

Co-authored-by: Matthew Zeiler <zeiler@clarifai.com>
1 year ago
Harrison Chase 52b016920c
Harrison/update anthropic (#7237)
Co-authored-by: William Fu-Hinthorn <13333726+hinthornw@users.noreply.github.com>
1 year ago
Tom e533da8bf2
Adding Marqo to vectorstore ecosystem (#7068)
This PR brings in a vectorstore interface for
[Marqo](https://www.marqo.ai/).

The Marqo vectorstore exposes some of Marqo's functionality in addition
the the VectorStore base class. The Marqo vectorstore also makes the
embedding parameter optional because inference for embeddings is an
inherent part of Marqo.

Docs, notebook examples and integration tests included.

Related PR:
https://github.com/hwchase17/langchain/pull/2807

---------

Co-authored-by: Tom Hamer <tom@marqo.ai>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
felixocker db98c44f8f
Support for SPARQL (#7165)
# [SPARQL](https://www.w3.org/TR/rdf-sparql-query/) for
[LangChain](https://github.com/hwchase17/langchain)

## Description
LangChain support for knowledge graphs relying on W3C standards using
RDFlib: SPARQL/ RDF(S)/ OWL with special focus on RDF \
* Works with local files, files from the web, and SPARQL endpoints
* Supports both SELECT and UPDATE queries
* Includes both a Jupyter notebook with an example and integration tests

## Contribution compared to related PRs and discussions
* [Wikibase agent](https://github.com/hwchase17/langchain/pull/2690) -
uses SPARQL, but specifically for wikibase querying
* [Cypher qa](https://github.com/hwchase17/langchain/pull/5078) - graph
DB question answering for Neo4J via Cypher
* [PR 6050](https://github.com/hwchase17/langchain/pull/6050) - tries
something similar, but does not cover UPDATE queries and supports only
RDF
* Discussions on [w3c mailing list](mailto:semantic-web@w3.org) related
to the combination of LLMs (specifically ChatGPT) and knowledge graphs

## Dependencies
* [RDFlib](https://github.com/RDFLib/rdflib)

## Tag maintainer
Graph database related to memory -> @hwchase17
1 year ago
Simon Cheung 81eebc4070
Add HugeGraphQAChain to support gremlin generating chain (#7132)
[Apache HugeGraph](https://github.com/apache/incubator-hugegraph) is a
convenient, efficient, and adaptable graph database, compatible with the
Apache TinkerPop3 framework and the Gremlin query language.

In this PR, the HugeGraph and HugeGraphQAChain provide the same
functionality as the existing integration with Neo4j and enables query
generation and question answering over HugeGraph database. The
difference is that the graph query language supported by HugeGraph is
not cypher but another very popular graph query language
[Gremlin](https://tinkerpop.apache.org/gremlin.html).

A notebook example and a simple test case have also been added.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
William FH dfa48dc3b5
Update sdk version (#7109) 1 year ago
Stefano Lottini 8d2281a8ca
Second Attempt - Add concurrent insertion of vector rows in the Cassandra Vector Store (#7017)
Retrying with the same improvements as in #6772, this time trying not to
mess up with branches.

@rlancemartin doing a fresh new PR from a branch with a new name. This
should do. Thank you for your help!

---------

Co-authored-by: Jonathan Ellis <jbellis@datastax.com>
Co-authored-by: rlm <pexpresss31@gmail.com>
1 year ago
Zander Chase b0859c9b18
Add New Retriever Interface with Callbacks (#5962)
Handle the new retriever events in a way that (I think) is entirely
backwards compatible? Needs more testing for some of the chain changes
and all.

This creates an entire new run type, however. We could also just treat
this as an event within a chain run presumably (same with memory)

Adds a subclass initializer that upgrades old retriever implementations
to the new schema, along with tests to ensure they work.

First commit doesn't upgrade any of our retriever implementations (to
show that we can pass the tests along with additional ones testing the
upgrade logic).

Second commit upgrades the known universe of retrievers in langchain.

- [X] Add callback handling methods for retriever start/end/error (open
to renaming to 'retrieval' if you want that)
- [X] Update BaseRetriever schema to support callbacks
- [X] Tests for upgrading old "v1" retrievers for backwards
compatibility
- [X] Update existing retriever implementations to implement the new
interface
- [X] Update calls within chains to .{a]get_relevant_documents to pass
the child callback manager
- [X] Update the notebooks/docs to reflect the new interface
- [X] Test notebooks thoroughly


Not handled:
- Memory pass throughs: retrieval memory doesn't have a parent callback
manager passed through the method

---------

Co-authored-by: Nuno Campos <nuno@boringbits.io>
Co-authored-by: William Fu-Hinthorn <13333726+hinthornw@users.noreply.github.com>
1 year ago
Daniel Chalef b26cca8008
Zep Authentication (#6728)
## Description: Add Zep API Key argument to ZepChatMessageHistory and
ZepRetriever
- correct docs site links
- add zep api_key auth to constructors

ZepChatMessageHistory: @hwchase17, 
ZepRetriever: @rlancemartin, @eyurtsev
1 year ago
William FH 13c62cf6b1
Arthur Callback (#6972)
Co-authored-by: Max Cembalest <115359769+arthuractivemodeling@users.noreply.github.com>
1 year ago
Bagatur 60b0d6ea35
Bagatur/openllm ensure available (#6960)
Signed-off-by: Aaron <29749331+aarnphm@users.noreply.github.com>
Co-authored-by: Aaron <29749331+aarnphm@users.noreply.github.com>
1 year ago
Stefano Lottini 75fb9d2fdc
Cassandra support for chat history using CassIO library (#6771)
### Overview

This PR aims at building on #4378, expanding the capabilities and
building on top of the `cassIO` library to interface with the database
(as opposed to using the core drivers directly).

Usage of `cassIO` (a library abstracting Cassandra access for
ML/GenAI-specific purposes) is already established since #6426 was
merged, so no new dependencies are introduced.

In the same spirit, we try to uniform the interface for using Cassandra
instances throughout LangChain: all our appreciation of the work by
@jj701 notwithstanding, who paved the way for this incremental work
(thank you!), we identified a few reasons for changing the way a
`CassandraChatMessageHistory` is instantiated. Advocating a syntax
change is something we don't take lighthearted way, so we add some
explanations about this below.

Additionally, this PR expands on integration testing, enables use of
Cassandra's native Time-to-Live (TTL) features and improves the phrasing
around the notebook example and the short "integrations" documentation
paragraph.

We would kindly request @hwchase to review (since this is an elaboration
and proposed improvement of #4378 who had the same reviewer).

### About the __init__ breaking changes

There are
[many](https://docs.datastax.com/en/developer/python-driver/3.28/api/cassandra/cluster/)
options when creating the `Cluster` object, and new ones might be added
at any time. Choosing some of them and exposing them as `__init__`
parameters `CassandraChatMessageHistory` will prove to be insufficient
for at least some users.

On the other hand, working through `kwargs` or adding a long, long list
of arguments to `__init__` is not a desirable option either. For this
reason, (as done in #6426), we propose that whoever instantiates the
Chat Message History class provide a Cassandra `Session` object, ready
to use. This also enables easier injection of mocks and usage of
Cassandra-compatible connections (such as those to the cloud database
DataStax Astra DB, obtained with a different set of init parameters than
`contact_points` and `port`).

We feel that a breaking change might still be acceptable since LangChain
is at `0.*`. However, while maintaining that the approach we propose
will be more flexible in the future, room could be made for a
"compatibility layer" that respects the current init method. Honestly,
we would to that only if there are strong reasons for it, as that would
entail an additional maintenance burden.

### Other changes

We propose to remove the keyspace creation from the class code for two
reasons: first, production Cassandra instances often employ RBAC so that
the database user reading/writing from tables does not necessarily (and
generally shouldn't) have permission to create keyspaces, and second
that programmatic keyspace creation is not a best practice (it should be
done more or less manually, with extra care about schema mismatched
among nodes, etc). Removing this (usually unnecessary) operation from
the `__init__` path would also improve initialization performance
(shorter time).

We suggest, likewise, to remove the `__del__` method (which would close
the database connection), for the following reason: it is the
recommended best practice to create a single Cassandra `Session` object
throughout an application (it is a resource-heavy object capable to
handle concurrency internally), so in case Cassandra is used in other
ways by the app there is the risk of truncating the connection for all
usages when the history instance is destroyed. Moreover, the `Session`
object, in typical applications, is best left to garbage-collect itself
automatically.

As mentioned above, we defer the actual database I/O to the `cassIO`
library, which is designed to encode practices optimized for LLM
applications (among other) without the need to expose LangChain
developers to the internals of CQL (Cassandra Query Language). CassIO is
already employed by the LangChain's Vector Store support for Cassandra.

We added a few more connection options in the companion notebook example
(most notably, Astra DB) to encourage usage by anyone who cannot run
their own Cassandra cluster.

We surface the `ttl_seconds` option for automatic handling of an
expiration time to chat history messages, a likely useful feature given
that very old messages generally may lose their importance.

We elaborated a bit more on the integration testing (Time-to-live,
separation of "session ids", ...).

### Remarks from linter & co.

We reinstated `cassio` as a dependency both in the "optional" group and
in the "integration testing" group of `pyproject.toml`. This might not
be the right thing do to, in which case the author of this PR offer his
apologies (lack of confidence with Poetry - happy to be pointed in the
right direction, though!).

During linter tests, we were hit by some errors which appear unrelated
to the code in the PR. We left them here and report on them here for
awareness:

```
langchain/vectorstores/mongodb_atlas.py:137: error: Argument 1 to "insert_many" of "Collection" has incompatible type "List[Dict[str, Sequence[object]]]"; expected "Iterable[Union[MongoDBDocumentType, RawBSONDocument]]"  [arg-type]
langchain/vectorstores/mongodb_atlas.py:186: error: Argument 1 to "aggregate" of "Collection" has incompatible type "List[object]"; expected "Sequence[Mapping[str, Any]]"  [arg-type]

langchain/vectorstores/qdrant.py:16: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:19: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:20: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:22: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:23: error: Name "grpc" is not defined  [name-defined]
```

In the same spirit, we observe that to even get `import langchain` run,
it seems that a `pip install bs4` is missing from the minimal package
installation path.

Thank you!
1 year ago
Harrison Chase 3ac08c3de4
Harrison/octo ml (#6897)
Co-authored-by: Bassem Yacoube <125713079+AI-Bassem@users.noreply.github.com>
Co-authored-by: Shotaro Kohama <khmshtr28@gmail.com>
Co-authored-by: Rian Dolphin <34861538+rian-dolphin@users.noreply.github.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Shashank Deshpande <shashankdeshpande18@gmail.com>
1 year ago
Ayan Bandyopadhyay f92ccf70fd
Update to the latest Psychic python library version (#6804)
Update the Psychic document loader to use the latest `psychicapi` python
library version: `0.8.0`
1 year ago
Cristóbal Carnero Liñán e494b0a09f
feat (documents): add a source code loader based on AST manipulation (#6486)
#### Summary

A new approach to loading source code is implemented:

Each top-level function and class in the code is loaded into separate
documents. Then, an additional document is created with the top-level
code, but without the already loaded functions and classes.

This could improve the accuracy of QA chains over source code.

For instance, having this script:

```
class MyClass:
    def __init__(self, name):
        self.name = name

    def greet(self):
        print(f"Hello, {self.name}!")

def main():
    name = input("Enter your name: ")
    obj = MyClass(name)
    obj.greet()

if __name__ == '__main__':
    main()
```

The loader will create three documents with this content:

First document:
```
class MyClass:
    def __init__(self, name):
        self.name = name

    def greet(self):
        print(f"Hello, {self.name}!")
```

Second document:
```
def main():
    name = input("Enter your name: ")
    obj = MyClass(name)
    obj.greet()
```

Third document:
```
# Code for: class MyClass:

# Code for: def main():

if __name__ == '__main__':
    main()
```

A threshold parameter is added to control whether small scripts are
split in this way or not.

At this moment, only Python and JavaScript are supported. The
appropriate parser is determined by examining the file extension.

#### Tests

This PR adds:

- Unit tests
- Integration tests

#### Dependencies

Only one dependency was added as optional (needed for the JavaScript
parser).

#### Documentation

A notebook is added showing how the loader can be used.

#### Who can review?

@eyurtsev @hwchase17

---------

Co-authored-by: rlm <pexpresss31@gmail.com>
1 year ago
Zander Chase b4fe7f3a09
Session to project (#6249)
Sessions are being renamed to projects in the tracer
1 year ago
Tim Conkling c28990d871
StreamlitCallbackHandler (#6315)
A new implementation of `StreamlitCallbackHandler`. It formats Agent
thoughts into Streamlit expanders.

You can see the handler in action here:
https://langchain-mrkl.streamlit.app/

Per a discussion with Harrison, we'll be adding a
`StreamlitCallbackHandler` implementation to an upcoming
[Streamlit](https://github.com/streamlit/streamlit) release as well, and
will be updating it as we add new LLM- and LangChain-specific features
to Streamlit.

The idea with this PR is that the LangChain `StreamlitCallbackHandler`
will "auto-update" in a way that keeps it forward- (and backward-)
compatible with Streamlit. If the user has an older Streamlit version
installed, the LangChain `StreamlitCallbackHandler` will be used; if
they have a newer Streamlit version that has an updated
`StreamlitCallbackHandler`, that implementation will be used instead.

(I'm opening this as a draft to get the conversation going and make sure
we're on the same page. We're really excited to land this into
LangChain!)

#### Who can review?

@agola11, @hwchase17
1 year ago
minhajul-clarifai 6e57306a13
Clarifai integration (#5954)
# Changes
This PR adds [Clarifai](https://www.clarifai.com/) integration to
Langchain. Clarifai is an end-to-end AI Platform. Clarifai offers user
the ability to use many types of LLM (OpenAI, cohere, ect and other open
source models). As well, a clarifai app can be treated as a vector
database to upload and retrieve data. The integrations includes:
- Clarifai LLM integration: Clarifai supports many types of language
model that users can utilize for their application
- Clarifai VectorDB: A Clarifai application can hold data and
embeddings. You can run semantic search with the embeddings

#### Before submitting
- [x] Added integration test for LLM 
- [x] Added integration test for VectorDB 
- [x] Added notebook for LLM 
- [x] Added notebook for VectorDB 

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Davis Chase 4fabd02d25
Add OpenLLM wrapper(#6578)
LLM wrapper for models served with OpenLLM

---------

Signed-off-by: Aaron <29749331+aarnphm@users.noreply.github.com>
Authored-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>
Co-authored-by: Chaoyu <paranoyang@gmail.com>
1 year ago
ljeagle ca24dc2d5f
Upgrade the version of AwaDB and add some new interfaces (#6565)
1. upgrade the version of AwaDB
2. add some new interfaces
3. fix bug of packing page content error

@dev2049  please review, thanks!

---------

Co-authored-by: vincent <awadb.vincent@gmail.com>
1 year ago
囧囧 0fce8ef178
Add KuzuQAChain (#6454)
This PR adds `KuzuGraph` and `KuzuQAChain` for interacting with [Kùzu
database](https://github.com/kuzudb/kuzu). Kùzu is an in-process
property graph database management system (GDBMS) built for query speed
and scalability. The `KuzuGraph` and `KuzuQAChain` provide the same
functionality as the existing integration with NebulaGraph and Neo4j and
enables query generation and question answering over Kùzu database.

A notebook example and a simple test case have also been added.

---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Zeeland 8a604b93ab
feat: use latest duckduckgo_search API to call (#6409)
# Provider the latest duckduckgo_search API

The Git commit contents involve two files related to some DuckDuckGo
query operations, and an upgrade of the DuckDuckGo module to version
3.8.3. A suitable commit message could be "Upgrade DuckDuckGo module to
version 3.8.3, including query operations". Specifically, in the
duckduckgo_search.py file, a DDGS() class instance is newly added to
replace the previous ddg() function, and the time parameter name in the
get_snippets() and results() methods is changed from "time" to
"timelimit" to accommodate recent changes. In the pyproject.toml file,
the duckduckgo-search module is upgraded to version 3.8.3.

[duckduckgo_search readme
attention](https://github.com/deedy5/duckduckgo_search): Versions before
v2.9.4 no longer work as of May 12, 2023

## Who can review?

@vowelparrot

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
volodymyr-memsql d2e9b621ab
Update SinglStoreDB vectorstore (#6423)
1. Introduced new distance strategies support: **DOT_PRODUCT** and
**EUCLIDEAN_DISTANCE** for enhanced flexibility.
2. Implemented a feature to filter results based on metadata fields.
3. Incorporated connection attributes specifying "langchain python sdk"
usage for enhanced traceability and debugging.
4. Expanded the suite of integration tests for improved code
reliability.
5. Updated the existing notebook with the usage example

@dev2049

---------

Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
Zander Chase 00f276d23f
Run eval in eval mode (#6447)
For the `run_on_dataset` sessions
1 year ago
Leonid Ganeline c7ca350cd3
Fix class promotion (#6187)
In LangChain, all module classes are enumerated in the `__init__.py`
file of the correspondent module. But some classes were missed and were
not included in the module `__init__.py`

This PR:
- added the missed classes to the module `__init__.py` files
- `__init__.py:__all_` variable value (a list of the class names) was
sorted
- `langchain.tools.sql_database.tool.QueryCheckerTool` was renamed into
the `QuerySQLCheckerTool` because it conflicted with
`langchain.tools.spark_sql.tool.QueryCheckerTool`
- changes to `pyproject.toml`:
  - added `pgvector` to `pyproject.toml:extended_testing`
- added `pandas` to
`pyproject.toml:[tool.poetry.group.test.dependencies]`
- commented out the `streamlit` from `collbacks/__init__.py`, It is
because now the `streamlit` requires Python >=3.7, !=3.9.7
- fixed duplicate names in `tools`
- fixed correspondent ut-s

#### Who can review?
@hwchase17
@dev2049
1 year ago
Harrison Chase af18413d97
Harrison/deeplake new features (#6263)
Co-authored-by: adilkhan <adilkhan.sarsen@nu.edu.kz>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
ljeagle ad324a39ae
Improve the performance of add_texts interface and upgrade the AwaDB from 0.3.2 to 0.3.3 (#6316)
1. Changed the implementation of add_texts interface for the AwaDB
vector store in order to improve the performance
2. Upgrade the AwaDB from 0.3.2 to 0.3.3

---------

Co-authored-by: vincent <awadb.vincent@gmail.com>
1 year ago
Zander Chase 0c52275bdb
Use Run object from SDK (#6067)
Update the Run object in the tracer to extend that in the SDK to include
the parameters necessary for tracking/tracing
1 year ago
Harrison Chase d1561b74eb
Harrison/cognitive search (#6011)
Co-authored-by: Fabrizio Ruocco <ruoccofabrizio@gmail.com>
1 year ago
Nuno Campos 18af149e91
nc/load (#5733)
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
Harrison Chase 9218684759
Add a new vector store - AwaDB (#5971) (#5992)
Added AwaDB vector store, which is a wrapper over the AwaDB, that can be
used as a vector storage and has an efficient similarity search. Added
integration tests for the vector store
Added jupyter notebook with the example

Delete a unneeded empty file and resolve the
conflict(https://github.com/hwchase17/langchain/pull/5886)

Please check, Thanks!

@dev2049
@hwchase17

---------

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#### Before submitting

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#### Who can review?

Tag maintainers/contributors who might be interested:

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  Tracing / Callbacks
  - @agola11

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  - @agola11

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  - @eyurtsev

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  - @hwchase17
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---------

Co-authored-by: ljeagle <vincent_jieli@yeah.net>
Co-authored-by: vincent <awadb.vincent@gmail.com>
1 year ago
Kacper Łukawski 7cc200766e
Expose full params in Qdrant (#5947)
# Expose full params in Qdrant

There were many questions regarding supporting some additional
parameters in Qdrant integration. Qdrant supports many vector search
optimizations that were impossible to use directly in Qdrant before.
That includes:

1. Possibility to manipulate collection params while using
`Qdrant.from_texts`. The PR allows setting things such as quantization,
HNWS config, optimizers config, etc. That makes it consistent with raw
`QdrantClient`.
2. Extended options while searching. It includes HNSW options, exact
search, score threshold filtering, and read consistency in distributed
mode.

After merging that PR, #4858 might also be closed.

## Who can review?

VectorStores / Retrievers / Memory

@dev2049 @hwchase17
1 year ago
Zander Chase 77c286cf02
Use LCP Client in Tracer (#5908)
Move the LCP calls to the client.
1 year ago
Harrison Chase 893d20f735
bump version to 194 (#5866) 1 year ago
Harrison Chase 35cfd25db3
Harrison/nebula graph (#5865)
Co-authored-by: Wey Gu <weyl.gu@gmail.com>
Co-authored-by: chenweisomebody <chenweisomebody@gmail.com>
1 year ago
volodymyr-memsql a1549901ce
Added SingleStoreDB Vector Store (#5619)
- Added `SingleStoreDB` vector store, which is a wrapper over the
SingleStore DB database, that can be used as a vector storage and has an
efficient similarity search.
- Added integration tests for the vector store
- Added jupyter notebook with the example

@dev2049

---------

Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
Zander Chase d9fcc45d05
Add in the async methods and link the run id (#5810) 1 year ago
Zander Chase 217b5cc72d
Base RunEvaluator Chain (#5750)
Clean up a bit and only implement the QA and reference free
implementations from https://github.com/hwchase17/langchain/pull/5618
1 year ago
Zander Chase 204a73c1d9
Use client from LCP-SDK (#5695)
- Remove the client implementation (this breaks backwards compatibility
for existing testers. I could keep the stub in that file if we want, but
not many people are using it yet
- Add SDK as dependency
- Update the 'run_on_dataset' method to be a function that optionally
accepts a client as an argument
- Remove the langchain plus server implementation (you get it for free
with the SDK now)

We could make the SDK optional for now, but the plan is to use w/in the
tracer so it would likely become a hard dependency at some point.
1 year ago
Adil Ansari 233b52735e
feat: Support for `Tigris` Vector Database for vector search (#5703)
### Changes
- New vector store integration - [Tigris](https://tigrisdata.com)
- Adds [tigrisdb](https://pypi.org/project/tigrisdb/) optional
dependency
- Example notebook demonstrating usage

Fixes #5535 
Closes tigrisdata/tigris-client-python#40

#### Twitter handles
We'd love a shoutout on our
[@TigrisData](https://twitter.com/TigrisData) and
[@adilansari](https://twitter.com/adilansari) twitter handles

#### Who can review?
@dev2049

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Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
1 year ago
Daniel Chalef 0551bc90a5
Zep Hybrid Search (#5742)
Zep now supports persisting custom metadata with messages and hybrid
search across both message embeddings and structured metadata. This PR
implements custom metadata and enhancements to the
`ZepChatMessageHistory` and `ZepRetriever` classes to implement this
support.

Tag maintainers/contributors who might be interested:

  VectorStores / Retrievers / Memory
  - @dev2049

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Co-authored-by: Daniel Chalef <daniel.chalef@private.org>
1 year ago
Natalie 199cc700a3
Ability to specify credentials wihen using Google BigQuery as a data loader (#5466)
# Adds ability to specify credentials when using Google BigQuery as a
data loader

Fixes #5465 . Adds ability to set credentials which must be of the
`google.auth.credentials.Credentials` type. This argument is optional
and will default to `None.

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Ayan Bandyopadhyay 8181f9e362
Update psychicapi version (#5471)
Update [psychicapi](https://pypi.org/project/psychicapi/) python package
dependency to the latest version 0.5. The newest python package version
addresses breaking changes in the Psychic http api.
1 year ago
Paul-Emile Brotons a61b7f7e7c
adding MongoDBAtlasVectorSearch (#5338)
# Add MongoDBAtlasVectorSearch for the python library

Fixes #5337
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Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Harrison Chase 760632b292
Harrison/spark reader (#5405)
Co-authored-by: Rithwik Ediga Lakhamsani <rithwik.ediga@databricks.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
German Martin 0b3e0dd1d2
New Trello document loader (#4767)
# Added New Trello loader class and documentation

Simple Loader on top of py-trello wrapper. 
With a board name you can pull cards and to do some field parameter
tweaks on load operation.
I included documentation and examples.
Included unit test cases using patch and a fixture for py-trello client
class.

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Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago
Michael Landis 7047a2c1af
feat: add Momento as a standard cache and chat message history provider (#5221)
# Add Momento as a standard cache and chat message history provider

This PR adds Momento as a standard caching provider. Implements the
interface, adds integration tests, and documentation. We also add
Momento as a chat history message provider along with integration tests,
and documentation.

[Momento](https://www.gomomento.com/) is a fully serverless cache.
Similar to S3 or DynamoDB, it requires zero configuration,
infrastructure management, and is instantly available. Users sign up for
free and get 50GB of data in/out for free every month.

## Before submitting

 We have added documentation, notebooks, and integration tests
demonstrating usage.

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
1 year ago