Commit Graph

308 Commits

Author SHA1 Message Date
Liu Ming
24f889f2bc
Change with_history option to False for ChatGLM by default (#8076)
ChatGLM LLM integration will by default accumulate conversation
history(with_history=True) to ChatGLM backend api, which is not expected
in most cases. This PR set with_history=False by default, user should
explicitly set llm.with_history=True to turn this feature on. Related
PR: #8048 #7774

---------

Co-authored-by: mlot <limpo2000@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-07-24 15:46:02 -07:00
Anthony Mahanna
76102971c0
ArangoDB/AQL support for Graph QA Chain (#7880)
**Description**: Serves as an introduction to LangChain's support for
[ArangoDB](https://github.com/arangodb/arangodb), similar to
https://github.com/hwchase17/langchain/pull/7165 and
https://github.com/hwchase17/langchain/pull/4881

**Issue**: No issue has been created for this feature

**Dependencies**: `python-arango` has been added as an optional
dependency via the `CONTRIBUTING.md` guidelines
 
**Twitter handle**: [at]arangodb

- Integration test has been added
- Notebook has been added:
[graph_arangodb_qa.ipynb](https://github.com/amahanna/langchain/blob/master/docs/extras/modules/chains/additional/graph_arangodb_qa.ipynb)

[![Open In
Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/amahanna/langchain/blob/master/docs/extras/modules/chains/additional/graph_arangodb_qa.ipynb)

```
docker run -p 8529:8529 -e ARANGO_ROOT_PASSWORD= arangodb/arangodb
```

```
pip install git+https://github.com/amahanna/langchain.git
```

```python
from arango import ArangoClient

from langchain.chat_models import ChatOpenAI
from langchain.graphs import ArangoGraph
from langchain.chains import ArangoGraphQAChain

db = ArangoClient(hosts="localhost:8529").db(name="_system", username="root", password="", verify=True)

graph = ArangoGraph(db)

chain = ArangoGraphQAChain.from_llm(ChatOpenAI(temperature=0), graph=graph)

chain.run("Is Ned Stark alive?")
```

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-07-24 15:16:52 -07:00
Juan José Torres
1cc7d4c9eb
Update SageMaker Endpoint Embeddings docs to be up to date with current requirements (#8103)
- **Description:** Simple change of the Class that ContentHandler
inherits from. To create an object of type SagemakerEndpointEmbeddings,
the property content_handler must be of type EmbeddingsContentHandler
not ContentHandlerBase anymore,
  - **Twitter handle:** @Juanjo_Torres11

Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-07-24 13:35:06 -07:00
Bagatur
1a7d8667c8
Bagatur/gateway chat (#8198)
Signed-off-by: dbczumar <corey.zumar@databricks.com>
Co-authored-by: dbczumar <corey.zumar@databricks.com>
2023-07-24 12:17:00 -07:00
Ettore Di Giacinto
ae28568e2a
Add embeddings for LocalAI (#8134)
Description:

This PR adds embeddings for LocalAI (
https://github.com/go-skynet/LocalAI ), a self-hosted OpenAI drop-in
replacement. As LocalAI can re-use OpenAI clients it is mostly following
the lines of the OpenAI embeddings, however when embedding documents, it
just uses string instead of sending tokens as sending tokens is
best-effort depending on the model being used in LocalAI. Sending tokens
is also tricky as token id's can mismatch with the model - so it's safer
to just send strings in this case.

Partly related to: https://github.com/hwchase17/langchain/issues/5256

Dependencies: No new dependencies

Twitter: @mudler_it
---------

Signed-off-by: mudler <mudler@localai.io>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-07-24 12:16:49 -07:00
Mike Nitsenko
d983046f90
Extend Cube Semantic Loader functionality (#8186)
**PR Description:**

This pull request introduces several enhancements and new features to
the `CubeSemanticLoader`. The changes include the following:

1. Added imports for the `json` and `time` modules.
2. Added new constructor parameters: `load_dimension_values`,
`dimension_values_limit`, `dimension_values_max_retries`, and
`dimension_values_retry_delay`.
3. Updated the class documentation with descriptions for the new
constructor parameters.
4. Added a new private method `_get_dimension_values()` to retrieve
dimension values from Cube's REST API.
5. Modified the `load()` method to load dimension values for string
dimensions if `load_dimension_values` is set to `True`.
6. Updated the API endpoint in the `load()` method from the base URL to
the metadata endpoint.
7. Refactored the code to retrieve metadata from the response JSON.
8. Added the `column_member_type` field to the metadata dictionary to
indicate if a column is a measure or a dimension.
9. Added the `column_values` field to the metadata dictionary to store
the dimension values retrieved from Cube's API.
10. Modified the `page_content` construction to include the column title
and description instead of the table name, column name, data type,
title, and description.

These changes improve the functionality and flexibility of the
`CubeSemanticLoader` class by allowing the loading of dimension values
and providing more detailed metadata for each document.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-07-24 12:11:58 -07:00
Bagatur
c8c8635dc9
mv module integrations docs (#8101) 2023-07-23 23:23:16 -07:00
Bagatur
58f65fcf12
use top nav docs (#8090) 2023-07-21 13:52:03 -07:00