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- **Description:** In Google Vertex AI, Gemini Chat models currently
doesn't have a support for SystemMessage. This PR adds support for it
only if a user provides additional convert_system_message_to_human flag
during model initialization (in this case, SystemMessage would be
prepended to the first HumanMessage). **NOTE:** The implementation is
similar to #14824
- **Twitter handle:** rajesh_thallam
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description**: Updated doc for llm/google_vertex_ai_palm with new
functions: `invoke`, `stream`... Changed structure of the document to
match the required one.
- **Issue**: #15664
- **Dependencies**: None
- **Twitter handle**: None
---------
Co-authored-by: Jorge Zaldívar <jzaldivar@google.com>
**Description:** Gemini model has quite annoying default safety_settings
settings. In addition, current VertexAI class doesn't provide a property
to override such settings.
So, this PR aims to
- add safety_settings property to VertexAI
- fix issue with incorrect LLM output parsing when LLM responds with
appropriate 'blocked' response
- fix issue with incorrect parsing LLM output when Gemini API blocks
prompt itself as inappropriate
- add safety_settings related tests
I'm not enough familiar with langchain code base and guidelines. So, any
comments and/or suggestions are very welcome.
**Issue:** it will likely fix#14841
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
* Removed some env vars not used in langchain package IT
* Added Astra DB env vars in langchain package, used for cache tests
* Added conftest.py to load env vars in langchain_community IT
* Added .env.example in langchain_community IT
<!-- Thank you for contributing to LangChain!
Please title your PR "<package>: <description>", where <package> is
whichever of langchain, community, core, experimental, etc. is being
modified.
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes if applicable,
- **Dependencies:** any dependencies required for this change,
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` from the root
of the package you've modified to check this locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc: https://python.langchain.com/docs/contributing/
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. It lives in
`docs/docs/integrations` directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
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The timeout function comes in handy when you want to kill longrunning
queries.
The value sanitization removes all lists that are larger than 128
elements. The idea here is to remove embedding properties from results.
- **Description:** As Shell tool is very versatile, while integrating it
into applications as openai functions, developers have no clue about
what command is being executed using the ShellTool. All one can see is:
![image](https://github.com/langchain-ai/langchain/assets/60742358/540e274a-debc-4564-9027-046b91424df3)
Summarising my feature request:
1. There's no visibility about what command was executed.
2. There's no mechanism to prevent a command to be executed using
ShellTool, like a y/n human input which can be accepted from user to
proceed with executing the command.,
- **Issue:** the issue #15931 it fixes if applicable,
- **Dependencies:** There isn't any dependancy,
- **Twitter handle:** @krishnashed
- **Description:** Made a small fix for the `SQLDatabase` highlighted in
an issue. The issue pertains to switching schema for different SQL
engines.
- **Issue:** #16023
@baskaryan
- **Description:** Support IN and LIKE comparators in Milvus
self-querying retriever, based on [Boolean Expression
Rules](https://milvus.io/docs/boolean.md)
- **Issue:** No
- **Dependencies:** No
- **Twitter handle:** No
Signed-off-by: ChengZi <chen.zhang@zilliz.com>
**Description**: This PR fixes an error in the documentation for Azure
Cosmos DB Integration.
**Issue**: The correct way to import `AzureCosmosDBVectorSearch` is
```python
from langchain_community.vectorstores.azure_cosmos_db import (
AzureCosmosDBVectorSearch,
)
```
While the
[documentation](https://python.langchain.com/docs/integrations/vectorstores/azure_cosmos_db)
states it to be
```python
from langchain_community.vectorstores.azure_cosmos_db_vector_search import (
AzureCosmosDBVectorSearch,
CosmosDBSimilarityType,
)
```
As you can see in
[azure_cosmos_db.py](c323742f4f/libs/langchain/langchain/vectorstores/azure_cosmos_db.py (L1C45-L2))
**Dependencies:**: None
**Twitter handle**: None
- **Description:** This handles the cohere response when documents
aren't included in the response
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** N/A
- bumps package post versions for packages without current unreleased
updates
- will bump package version in release prs associated with packages that
do have changes (mistral, vertex)