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Adding Tavily Search API as a tool. I will be the maintainer and
assaf_elovic is the twitter handler.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Current ChatTongyi is not compatible with DashScope API, which will
cause error when passing api key to chat model directly.
- **Description:** Update tongyi.py to be compatible with DashScope API.
Specifically, update parameter name "dashscope_api_key" to "api_key".
- **Issue:** None.
- **Dependencies:** Nothing new, Tongyi would require DashScope as
before.
- **Description:**
- Replace Telegram with Whatsapp in whatsapp.ipynb
- Add # to mark the telegram as heading in telegram.ipynb
- **Issue:** None
- **Dependencies:** None
- **Description:** Implementing the Google Scholar Tool as requested in
PR #11505. The tool will be using the [serpapi python
package](https://serpapi.com/integrations/python#search-google-scholar).
The main idea of the tool will be to return the results from a Google
Scholar search given a query as an input to the tool.
- **Tag maintainer:** @baskaryan, @eyurtsev, @hwchase17
Replace this entire comment with:
- **Description:** Fix superfluous [Auto-fixing
parser](https://python.langchain.com/docs/modules/model_io/output_parsers/output_fixing_parser)
docs. Also switching to `langchain.pydantic_v1` from the direct
reference to `pydantic`,
- **Issue:** N/A,
- **Dependencies:** N/A,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** @dosuken123
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- Fixes error:
```
ValueError: "GoogleVertexAISearchRetriever" object has no field "_serving_config"
```
Introduced in #11736
@baskaryan, @eyurtsev, @hwchase17 if you could review and merge quickly,
that would be appreciated :)
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- **Description:** The return info in the documentation for
similarity_search_by_vector and similarity_search_with_relevance_scores
is wrong
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This reverts commit a46eef64a7.
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- **Description:** Provide a way to use different text for embedding.
- For example, if you are ingesting stack-overflow Q&As for RAG, you
would want to embed the questions and return the answer(s) for the hits.
With this change, the consumer of langchain can implement that easily.
- I noticed the similar function is added on faiss.py with #1912 which
was for performance reason, but I see the same function can be used to
achieve what I thought. So instead of changing Document class to have
embedding_content, I mimicked the implementation of faiss.py.
- The test should provide some guidance on how to use it. It would be
more intuitive if I just pass texts and embedding_texts as separate
arguments, but I chose to use `zip`-ed object for the consistency with
faiss.py implementation.
- I plan to make similar pull request for OpenSearch.
- **Issue:** N/A
- **Dependencies:** None other than the existing ones.
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Adding Pydantic v2 support for OpenAPI Specs
- **Issue:**
- OpenAPI spec support was disabled because `openapi-schema-pydantic`
doesn't support Pydantic v2:
#9205
- Caused errors in `get_openapi_chain`
- This may be the cause of #9520.
- **Tag maintainer:** @eyurtsev
- **Twitter handle:** kreneskyp
The root cause was that `openapi-schema-pydantic` hasn't been updated in
some time but
[openapi-pydantic](https://github.com/mike-oakley/openapi-pydantic)
forked and updated the project.
Added a notebook with examples of the creation of a retriever from the
SingleStoreDB vector store, and further usage.
Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Updated the elasticsearch self query retriever to use the match clause
for LIKE operator instead of the non-analyzed fuzzy search clause.
Other small updates include:
- fixing the stack inference integration test where the index's default
pipeline didn't use the inference pipeline created
- adding a user-agent to the old implementation to track usage
- improved the documentation for ElasticsearchStore filters
