[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>
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This PR introduces a new Mendable UI tailored to a better search
experience.
We're more closely integrating our traditional search with our AI
generation.
With this change, you won't have to tab back and forth between the
mendable bot and the keyword search. Both types of search are handled in
the same bar. This should make the docs easier to navigate. while still
letting users get code generations or AI-summarized answers if they so
wish. Also, it should reduce the cost.
Would love to hear your feedback :)
Cc: @dev2049 @hwchase17
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## Description
The type hint for `FAISS.__init__()`'s `relevance_score_fn` parameter
allowed the parameter to be set to `None`. However, a default function
is provided by the constructor. This led to an unnecessary check in the
code, as well as a test to verify this check.
**ASSUMPTION**: There's no reason to ever set `relevance_score_fn` to
`None`.
This PR changes the type hint and removes the unnecessary code.
- Description: Added a new SpacyEmbeddings class for generating
embeddings using the Spacy library.
- Issue: Sentencebert/Bert/Spacy/Doc2vec embedding support #6952
- Dependencies: This change requires the Spacy library and the
'en_core_web_sm' Spacy model.
- Tag maintainer: @dev2049
- Twitter handle: N/A
This change includes a new SpacyEmbeddings class, but does not include a
test or an example notebook.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description**:
The JSON Lines format is used by some services such as OpenAI and
HuggingFace. It's also a convenient alternative to CSV.
This PR adds JSON Lines support to `JSONLoader` and also updates related
tests.
**Tag maintainer**: @rlancemartin, @eyurtsev.
PS I was not able to build docs locally so didn't update related
section.
Update to Vectara integration
- By user request added "add_files" to take advantage of Vectara
capabilities to process files on the backend, without the need for
separate loading of documents and chunking in the chain.
- Updated vectara.ipynb example notebook to be broader and added testing
of add_file()
@hwchase17 - project lead
---------
Co-authored-by: rlm <pexpresss31@gmail.com>
### Description:
Updated the delete function in the Pinecone integration to allow for
deletion of vectors by specifying a filter condition, and to delete all
vectors in a namespace.
Made the ids parameter optional in the delete function in the base
VectorStore class and allowed for additional keyword arguments.
Updated the delete function in several classes (Redis, Chroma, Supabase,
Deeplake, Elastic, Weaviate, and Cassandra) to match the changes made in
the base VectorStore class. This involved making the ids parameter
optional and allowing for additional keyword arguments.
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>
should be no functional changes
also keep __init__ exposing a lot for backwards compat
---------
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
### Summary
Updates `UnstructuredEmailLoader` so that it can process attachments in
addition to the e-mail content. The loader will process attachments if
the `process_attachments` kwarg is passed when the loader is
instantiated.
### Testing
```python
file_path = "fake-email-attachment.eml"
loader = UnstructuredEmailLoader(
file_path, mode="elements", process_attachments=True
)
docs = loader.load()
docs[-1]
```
### Reviewers
- @rlancemartin
- @eyurtsev
- @hwchase17
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>
