## 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>
- allow overriding run_type in on_chain_start
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from my understanding, the `check_repeated_memory_variable` validator
will raise an error if any of the variables in the `memories` list are
repeated. However, the `load_memory_variables` method does not check for
repeated variables. This means that it is possible for the
`CombinedMemory` instance to return a dictionary of memory variables
that contains duplicate values. This code will check for repeated
variables in the `data` dictionary returned by the
`load_memory_variables` method of each sub-memory. If a repeated
variable is found, an error will be raised.
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---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
- Description: Adds an optional buffer arg to the memory's
from_messages() method. If provided the existing memory will be loaded
instead of regenerating a summary from the loaded messages.
Why? If we have past messages to load from, it is likely we also have an
existing summary. This is particularly helpful in cases where the chat
is ephemeral and/or is backed by serverless where the chat history is
not stored but where the updated chat history is passed back and forth
between a backend/frontend.
Eg: Take a stateless qa backend implementation that loads messages on
every request and generates a response — without this addition, each
time the messages are loaded via from_messages, the summaries are
recomputed even though they may have just been computed during the
previous response. With this, the previously computed summary can be
passed in and avoid:
1) spending extra $$$ on tokens, and
2) increased response time by avoiding regenerating previously generated
summary.
Tag maintainer: @hwchase17
Twitter handle: https://twitter.com/ShantanuNair
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
- Description: updated BabyAGI examples to append the iteration to the
result id to fix error storing data to vectorstore.
- Issue: 7445
- Dependencies: no
- Tag maintainer: @eyurtsev
- 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!
This fix worked for me locally. Happy to take some feedback and iterate
on a better solution. I was considering appending a uuid instead but
didnt want to over complicate the example.
…call, it needs retry
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Co-authored-by: yangdihang <yangdihang@bytedance.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Works just like the GenericLoader but concurrently for those who choose
to optimize their workflow.
@rlancemartin @eyurtsev
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Description: Using Azure Cognitive Search as a VectorStore. Calling the
`add_texts` method throws an error if there is no metadata property
specified. The `additional_fields` field is set in an `if` statement and
then is used later outside the if statement. This PR just moves the
declaration of `additional_fields` below and puts the usage of it in
context.
Issue: https://github.com/langchain-ai/langchain/issues/8544
Tagging @rlancemartin, @eyurtsev as this is related to Vector stores.
`make format`, `make lint`, `make spellcheck`, and `make test` have been
run
- Description: Follow up of #8478
- Issue: #8477
- Dependencies: None
- Tag maintainer: @baskaryan
- Twitter handle: [@BharatR123](twitter.com/BharatR123)
The links were still broken after #8478 and sadly the issue was not
caught with either the Vercel app build and `make docs_linkcheck`
- Description: This pull request (PR) includes two minor changes:
1. Updated the default prompt for SQL Query Checker: The current prompt
does not clearly specify the final response that the LLM (Language
Model) should provide when checking for the query if `use_query_checker`
is enabled in SQLDatabase Chain. As a result, the LLM adds extra words
like "Here is your updated query" to the response. However, this causes
a syntax error when executing the SQL command in SQLDatabaseChain, as
these additional words are also included in the SQL query.
2. Moved the query's execution part into a separate method for
SQLDatabase: The purpose of this change is to provide users with more
flexibility when obtaining the result of an SQL query in the original
form returned by sqlalchemy. In the previous implementation, the run
method returned the results as a string. By creating a distinct method
for execution, users can now receive the results in original format,
which proves helpful in various scenarios. For example, during the
development of a tool, I found it advantageous to obtain results in
original format rather than a string, as currently done by the run
method.
- Tag maintainer: @hinthornw
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
This PR makes minor improvements to our python notebook, and adds
support for `Rockset` workspaces in our vectorstore client.
@rlancemartin, @eyurtsev
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description: a description of the change**
In this pull request, GitLoader has been updated to handle multiple load
calls, provided the same repository is being cloned. Previously, calling
`load` multiple times would raise an error if a clone URL was provided.
Additionally, a check has been added to raise a ValueError when
attempting to clone a different repository into an existing path.
New tests have also been introduced to verify the correct behavior of
the GitLoader class when `load` is called multiple times.
Lastly, the GitPython package, a dependency for the GitLoader class, has
been added to the project dependencies (pyproject.toml and poetry.lock).
**Issue: the issue # it fixes (if applicable)**
None
**Dependencies: any dependencies required for this change**
GitPython
**Tag maintainer: for a quicker response, tag the relevant maintainer
(see below)**
- DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
## Description
This PR handles modifying the Chroma DB integration's documentation.
It modifies the **Docker container** example to fix the instructions
mentioned in the documentation.
In the current documentation, the below `client.reset()` line causes a
runtime error:
```py
...
client = chromadb.HttpClient(settings=Settings(allow_reset=True))
client.reset() # resets the database
collection = client.create_collection("my_collection")
...
```
`Exception: {"error":"ValueError('Resetting is not allowed by this
configuration')"}`
This is due to the Chroma DB server needing to have the `allow_reset`
flag set to `true` there as well.
This is fixed by adding the `ALLOW_RESET=TRUE` to the `docker-compose`
file environment variable to the docker container before spinning it
## Issue
This fixes the runtime error that occurs when running the docker
container example code
## Tag Maintainer
@rlancemartin, @eyurtsev
## Description
The imports for `NeptuneOpenCypherQAChain` are failing. This PR adds the
chain class to the `__init__.py` file to fix this issue.
## Maintainers
@dev2049
@krlawrence
Docs for from_documents() were outdated as seen in
https://github.com/langchain-ai/langchain/issues/8457 .
fixes#8457
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- Async: @agola11
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-->
### Description
In the LangChain Documentation and Comments, I've Noticed that `pip
install faiss` was mentioned, instead of `pip install faiss-gpu`, since
installing `pip install faiss` results in an error. I've gone ahead and
updated the Documentation, and `faiss.ipynb`. This Change will ensure
ease of use for the end user, trying to install `faiss-gpu`.
### Issue:
Documentation / Comments Related.
### Dependencies:
No Dependencies we're changed only updated the files with the wrong
reference.
### Tag maintainer:
@rlancemartin, @eyurtsev (Thank You for your contributions 😄 )
# What
- add test to ensure values in time weighted retriever are updated
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- Description: add test to ensure values in time weighted retriever are
updated
- Issue: None
- Dependencies: None
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- Twitter handle: @MlopsJ
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-->
