When using AzureChatOpenAI the openai_api_type defaults to "azure". The
utils' get_from_dict_or_env() function triggered by the root validator
does not look for user provided values from environment variables
OPENAI_API_TYPE, so other values like "azure_ad" are replaced with
"azure". This does not allow the use of token-based auth.
By removing the "default" value, this allows environment variables to be
pulled at runtime for the openai_api_type and thus enables the other
api_types which are expected to work.
This fixes#6650
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- Description: updates to Vectara documentation with more details on how
to get started.
- Issue: NA
- Dependencies: NA
- Tag maintainer: @rlancemartin, @eyurtsev
- Twitter handle: @vectara, @ofermend
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
This lets you pass callbacks when you create the summarize chain:
```
summarize = load_summarize_chain(llm, chain_type="map_reduce", callbacks=[my_callbacks])
summary = summarize(documents)
```
See #5572 for a similar surgical fix.
tagging @hwchase17 for callbacks work
<!-- Thank you for contributing to LangChain!
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- Issue: the issue # it fixes (if applicable),
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- DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
- Models / Prompts: @hwchase17, @baskaryan
- Memory: @hwchase17
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- Async: @agola11
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-->
This is another case, similar to #5572 and #7565 where the callbacks are
getting dropped during construction of the chains.
tagging @hwchase17 and @agola11 for callbacks propagation
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Replace this comment with:
- Description: a description of the change,
- Issue: the issue # it fixes (if applicable),
- Dependencies: any dependencies required for this change,
- Tag maintainer: for a quicker response, tag the relevant maintainer
(see below),
- Twitter handle: we announce bigger features on Twitter. If your PR
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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,
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Maintainer responsibilities:
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- DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
- Models / Prompts: @hwchase17, @baskaryan
- Memory: @hwchase17
- Agents / Tools / Toolkits: @hinthornw
- Tracing / Callbacks: @agola11
- Async: @agola11
If no one reviews your PR within a few days, feel free to @-mention the
same people again.
See contribution guidelines for more information on how to write/run
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-->
Description: I have added two methods serializer and deserializer
methods. There was method called save local but it saves the to the
local disk. I wanted the vectorstore in the format using which i can
push it to the sql database's blob field. I have used this while i was
working on something
@rlancemartin, @eyurtsev
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
It fails currently because the event loop is already running.
The `retry` decorator alraedy infers an `AsyncRetrying` handler for
coroutines (see [tenacity
line](aa6f8f0a24/tenacity/__init__.py (L535)))
However before_sleep always gets called synchronously (see [tenacity
line](aa6f8f0a24/tenacity/__init__.py (L338))).
Instead, check for a running loop and use that it exists. Of course,
it's running an async method synchronously which is not _nice_. Given
how important LLMs are, it may make sense to have a task list or
something but I'd want to chat with @nfcampos on where that would live.
This PR also fixes the unit tests to check the handler is called and to
make sure the async test is run (it looks like it's just been being
skipped). It would have failed prior to the proposed fixes but passes
now.
Replace this comment with:
- Description: added a document loader for a list of RSS feeds or OPML.
It iterates through the list and uses NewsURLLoader to load each
article.
- Issue: N/A
- Dependencies: feedparser, listparser
- Tag maintainer: @rlancemartin, @eyurtsev
- Twitter handle: @ruze
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Solves #8644
This embedding models output identical random embedding vectors, given
the input texts are identical.
Useful when used in unittest.
@baskaryan
### Description
Fixes a grammar issue I noticed when reading through the documentation.
### Maintainers
@baskaryan
Co-authored-by: mmillerick <mmillerick@blend.com>
## Description:
1)Map reduce example in docs is missing an important import statement.
Figured other people would benefit from being able to copy 🍝 the code.
2)RefineDocumentsChain example also broken.
## Issue:
None
## Dependencies:
None. One liner.
## Tag maintainer:
@baskaryan
## Twitter handle:
I mean, it's a one line fix lol. But @will_thompson_k is my twitter
handle.
This small PR introduces new parameters into Qdrant (`on_disk`), fixes
some tests and changes the error message to be more clear.
Tagging: @baskaryan, @rlancemartin, @eyurtsev
- Description: run the poetry dependencies
- Issue: #7329
- Dependencies: any dependencies required for this change,
- Tag maintainer: @rlancemartin
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
### Description
OpenSearch supports validation using both Master Credentials (Username
and password) and IAM. For Master Credentials users will not pass the
argument `service` in `http_auth` and the existing code will break. To
fix this, I have updated the condition to check if service attribute is
present in http_auth before accessing it.
### Maintainers
@baskaryan @navneet1v
Signed-off-by: Naveen Tatikonda <navtat@amazon.com>
Description - Integrates Fireworks within Langchain LLMs to allow users
to use Fireworks models with Langchain, mainly for summarization.
Issue - Not applicable
Dependencies - None
Tag maintainer - @rlancemartin
---------
Co-authored-by: Raj Janardhan <rajjanardhan@Rajs-Laptop.attlocal.net>
Existing implementation requires that you install `firebase-admin`
package, and prevents you from using an existing Firestore client
instance if available.
This adds optional `firestore_client` param to
`FirestoreChatMessageHistory`, so users can just use their existing
client/settings. If not passed, existing logic executes to initialize a
`firestore_client`.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Add a StreamlitChatMessageHistory class that stores chat messages in
[Streamlit's Session
State](https://docs.streamlit.io/library/api-reference/session-state).
Note: The integration test uses a currently-experimental Streamlit
testing framework to simulate the execution of a Streamlit app. Marking
this PR as draft until I confirm with the Streamlit team that we're
comfortable supporting it.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
### Summary
Updates the `unstructured` install instructions. For
`unstructured>=0.9.0`, dependencies are broken out by document type and
the base `unstructured` package includes fewer dependencies. `pip
install "unstructured[local-inference]"` has been replace by `pip
install "unstructured[all-docs]"`, though the `local-inference` extra is
still supported for the time being.
### Reviewers
- @rlancemartin
- @eyurtsev
- @hwchase17
- Description: added memgraph_graph.py which defines the MemgraphGraph
class, subclassing off the existing Neo4jGraph class. This lets you
query the Memgraph graph database using natural language. It leverages
the Neo4j drivers and the bolt protocol.
- Dependencies: since it is a subclass off of Neo4jGraph, it is
dependent on it and the GraphCypherQA Chain implementations. It is
dependent on the Neo4j drivers being present. It is dependent on having
a running Memgraph instance to connect to.
- Tag maintainer: @baskaryan
- Twitter handle: @villageideate
- example usage can be seen in this repo
https://github.com/brettdbrewer/MemgraphGraph/
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
## Description
This PR implements a callback handler for SageMaker Experiments which is
similar to that of mlflow.
* When creating the callback handler, it takes the experiment's run
object as an argument. All the callback outputs are then logged to the
run object.
* The output of each callback action (e.g., `on_llm_start`) is saved to
S3 bucket as json file.
* Optionally, you can also log additional information such as the LLM
hyper-parameters to the same run object.
* Once the callback object is no more needed, you will need to call the
`flush_tracker()` method. This makes sure that any intermediate files
are deleted.
* A separate notebook example is provided to show how the callback is
used.
@3coins @agola11
---------
Co-authored-by: Tesfagabir Meharizghi <mehariz@amazon.com>
Description: Made Chroma constructor more robust when client_settings is
provided. Otherwise, existing embeddings will not be loaded correctly
from Chroma.
Issue: #7804
Dependencies: None
Tag maintainer: @rlancemartin, @eyurtsev
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Description:
This PR adds support for loading documents from Huawei OBS (Object
Storage Service) in Langchain. OBS is a cloud-based object storage
service provided by Huawei Cloud. With this enhancement, Langchain users
can now easily access and load documents stored in Huawei OBS directly
into the system.
Key Changes:
- Added a new document loader module specifically for Huawei OBS
integration.
- Implemented the necessary logic to authenticate and connect to Huawei
OBS using access credentials.
- Enabled the loading of individual documents from a specified bucket
and object key in Huawei OBS.
- Provided the option to specify custom authentication information or
obtain security tokens from Huawei Cloud ECS for easy access.
How to Test:
1. Ensure the required package "esdk-obs-python" is installed.
2. Configure the endpoint, access key, secret key, and bucket details
for Huawei OBS in the Langchain settings.
3. Load documents from Huawei OBS using the updated document loader
module.
4. Verify that documents are successfully retrieved and loaded into
Langchain for further processing.
Please review this PR and let us know if any further improvements are
needed. Your feedback is highly appreciated!
@rlancemartin, @eyurtsev
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
