Replace this comment with:
- Description: Improved query of BGE embeddings after talking with the
devs of BGE embeddings ,
- Dependencies: any dependencies required for this change,
- Tag maintainer: @hwchase17 ,
- Twitter handle: @ManabChetia3
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
- Description: added filter to query methods in VectorStoreIndexWrapper
for filtering by metadata (i.e. search_kwargs)
- Tag maintainer: @rlancemartin, @eyurtsev
Updated the doc snippet on this topic as well. It took me a long while
to figure out how to filter the vectorstore by filename, so this might
help someone else out.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
This addresses some issues with introducing the Nebula LLM to LangChain
in this PR:
https://github.com/langchain-ai/langchain/pull/8876
This fixes the following:
- Removes `SYMBLAI` from variable names
- Fixes bug with `Bearer` for the API KEY
Thanks again in advance for your help!
cc: @hwchase17, @baskaryan
---------
Co-authored-by: dvonthenen <david.vonthenen@gmail.com>
### Description
Now, we can pass information like a JWT token using user_context:
```python
self.retriever = AmazonKendraRetriever(index_id=kendraIndexId, user_context={"Token": jwt_token})
```
- [x] `make lint`
- [x] `make format`
- [x] `make test`
Also tested by pip installing in my own project, and it allows access
through the token.
### Maintainers
@rlancemartin, @eyurtsev
### My twitter handle
[girlknowstech](https://twitter.com/girlknowstech)
- Description: The API doc passed to LLM only included the content of
responses but did not include the content of requestBody, causing the
agent to be unable to construct the correct request parameters based on
the requestBody information. Add two lines of code fixed the bug,
- Issue: the issue # it fixes (if applicable),
- Dependencies: any dependencies required for this change,
- Tag maintainer: @hinthornw ,
- 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!
Adds Ollama as an LLM. Ollama can run various open source models locally
e.g. Llama 2 and Vicuna, automatically configuring and GPU-optimizing
them.
@rlancemartin @hwchase17
---------
Co-authored-by: Lance Martin <lance@langchain.dev>
## Description
I am excited to propose an integration with USearch, a lightweight
vector-search engine available for both Python and JavaScript, among
other languages.
## Dependencies
It introduces a new PyPi dependency - `usearch`. I am unsure if it must
be added to the Poetry file, as this would make the PR too clunky.
Please let me know.
## Profiles
- Maintainers: @ashvardanian @davvard
- Twitter handles: @ashvardanian @unum_cloud
---------
Co-authored-by: Davit Vardanyan <78792753+davvard@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Update to #8528
Newlines and other special characters within markdown code blocks
returned as `action_input` should be handled correctly (in particular,
unescaped `"` => `\"` and `\n` => `\\n`) so they don't break JSON
parsing.
@baskaryan
when e.g. downloading a sitemap with a malformed url (e.g.
"ttp://example.com/index.html" with the h omitted at the beginning of
the url), this will ensure that the sitemap download does not crash, but
just emits a warning. (maybe should be optional with e.g. a
`skip_faulty_urls:bool=True` parameter, but this was the most
straightforward fix)
@rlancemartin, @eyurtsev
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Added async parsing functions for RetryOutputParser,
RetryWithErrorOutputParser and OutputFixingParser.
The async parse functions call the arun methods of the used LLMChains.
Fix for #7989
---------
Co-authored-by: Benjamin May <benjamin.may94@gmail.com>
- Description: Adds the ChatAnyscale class with llama-2 7b, llama-2 13b,
and llama-2 70b on [Anyscale
Endpoints](https://app.endpoints.anyscale.com/)
- It inherits from ChatOpenAI and requires openai (probably unnecessary
but it made for a quick and easy implementation)
- Inspired by https://github.com/langchain-ai/langchain/pull/8434
(@kylehh and @baskaryan )
## Description
This PR adds Nebula to the available LLMs in LangChain.
Nebula is an LLM focused on conversation understanding and enables users
to extract conversation insights from video, audio, text, and chat-based
conversations. These conversations can occur between any mix of human or
AI participants.
Examples of some questions you could ask Nebula from a given
conversation are:
- What could be the customer’s pain points based on the conversation?
- What sales opportunities can be identified from this conversation?
- What best practices can be derived from this conversation for future
customer interactions?
You can read more about Nebula here:
https://symbl.ai/blog/extract-insights-symbl-ai-generative-ai-recall-ai-meetings/
#### Integration Test
An integration test is added, but it requires network access. Since
Nebula is fully managed like OpenAI, network access is required to
exercise the integration test.
#### Linting
- [x] make lint
- [x] make test (TODO: there seems to be a failure in another
non-related test??? Need to check on this.)
- [x] make format
### Dependencies
No new dependencies were introduced.
### Twitter handle
[@symbldotai](https://twitter.com/symbldotai)
[@dvonthenen](https://twitter.com/dvonthenen)
If you have any questions, please let me know.
cc: @hwchase17, @baskaryan
---------
Co-authored-by: dvonthenen <david.vonthenen@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
# What
- fix evaluation parse test
<!-- Thank you for contributing to LangChain!
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- Description: Fix evaluation parse test
- Issue: None
- Dependencies: None
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Please make sure you're PR is passing linting and testing before
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<!-- Thank you for contributing to LangChain!
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- Description: Fix/abstract add message
- Issue: None
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-->
Long-term, would be better to use the lower-level batch() method(s) but
it may take me a bit longer to clean up. This unblocks in the meantime,
though it may fail when the evaluated chain raises a
`NotImplementedError` for a corresponding async method
This adds support for [Xata](https://xata.io) (data platform based on
Postgres) as a vector store. We have recently added [Xata to
Langchain.js](https://github.com/hwchase17/langchainjs/pull/2125) and
would love to have the equivalent in the Python project as well.
The PR includes integration tests and a Jupyter notebook as docs. Please
let me know if anything else would be needed or helpful.
I have added the xata python SDK as an optional dependency.
## To run the integration tests
You will need to create a DB in xata (see the docs), then run something
like:
```
OPENAI_API_KEY=sk-... XATA_API_KEY=xau_... XATA_DB_URL='https://....xata.sh/db/langchain' poetry run pytest tests/integration_tests/vectorstores/test_xata.py
```
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- Description: a description of the change,
- Issue: the issue # it fixes (if applicable),
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(see below),
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2. an example notebook showing its use.
Maintainer responsibilities:
- General / Misc / if you don't know who to tag: @baskaryan
- DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
- Models / Prompts: @hwchase17, @baskaryan
- Memory: @hwchase17
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- Tracing / Callbacks: @agola11
- Async: @agola11
If no one reviews your PR within a few days, feel free to @-mention the
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-->
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Philip Krauss <35487337+philkra@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
#7469
since 1.29.0, Vertex SDK supports a chat history provided to a codey
chat model.
Co-authored-by: Leonid Kuligin <kuligin@google.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Hello langchain maintainers,
this PR aims at integrating
[vllm](https://vllm.readthedocs.io/en/latest/#) into langchain. This PR
closes#8729.
This feature clearly depends on `vllm`, but I've seen other models
supported here depend on packages that are not included in the
pyproject.toml (e.g. `gpt4all`, `text-generation`) so I thought it was
the case for this as well.
@hwchase17, @baskaryan
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
<!-- Thank you for contributing to LangChain!
Replace this comment with:
- Description: a description of the change,
- Issue: the issue # it fixes (if applicable),
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(see below),
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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
tests, lint, etc:
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-->
@hwchase17, @baskaryan
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Nuno Campos <nuno@boringbits.io>
- Updated to use newer better function interaction
- Previous version had only one callback
- @hinthornw @hwchase17 Can you look into this
- Shout out to @MultiON_AI @DivGarg9 on twitter
---------
Co-authored-by: Naman Garg <ngarg3@binghamton.edu>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
<!-- Thank you for contributing to LangChain!
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- Description: a description of the change,
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(see below),
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Description: The lines I have changed looks like incorrectly escaped for
regex. In python 3.11, I receive DeprecationWarning for these lines.
You don't see any warnings unless you explicitly run python with `-W
always::DeprecationWarning` flag. So, this is my attempt to fix it.
Here are the warnings from log files:
```
/usr/local/lib/python3.11/site-packages/langchain/text_splitter.py:919: DeprecationWarning: invalid escape sequence '\s'
/usr/local/lib/python3.11/site-packages/langchain/text_splitter.py:918: DeprecationWarning: invalid escape sequence '\s'
/usr/local/lib/python3.11/site-packages/langchain/text_splitter.py:917: DeprecationWarning: invalid escape sequence '\s'
/usr/local/lib/python3.11/site-packages/langchain/text_splitter.py:916: DeprecationWarning: invalid escape sequence '\c'
/usr/local/lib/python3.11/site-packages/langchain/text_splitter.py:903: DeprecationWarning: invalid escape sequence '\*'
/usr/local/lib/python3.11/site-packages/langchain/text_splitter.py:804: DeprecationWarning: invalid escape sequence '\*'
/usr/local/lib/python3.11/site-packages/langchain/text_splitter.py:804: DeprecationWarning: invalid escape sequence '\*'
```
cc @baskaryan
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Description: This PR improves the function of recursive_url_loader, such
as limiting the depth of the access, and customizable extractors(from
the raw webpage to the text of the Document object), so that users can
use other tools to extract the webpage. This PR also includes the
document and test for the new loader.
Old PR closed due to project structure change. #7756
Because socket requests are not allowed, the old unit test was removed.
Issue: N/A
Dependencies: asyncio, aiohttp
Tag maintainer: @rlancemartin
Twitter handle: @ Zend_Nihility
---------
Co-authored-by: Lance Martin <lance@langchain.dev>
<!-- Thank you for contributing to LangChain!
Replace this comment with:
- Description: docstore had two main method: add and search, however,
dealing with docstore sometimes requires deleting an entry from
docstore. So I have added a simple delete method that deletes items from
docstore. Additionally, I have added the delete method to faiss
vectorstore for the very same reason.
- Issue: NA
- Dependencies: NA
- Tag maintainer: @rlancemartin, @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!
Please make sure you're PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
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.
Maintainer responsibilities:
- General / Misc / if you don't know who to tag: @baskaryan
- 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
tests, lint, etc:
https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md
-->
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Fix Issue #7616 with a simpler approach to extract function names (use
`__name__` attribute)
@hwchase17
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Fixes for #8786 @agola11
- Description: The flow of callback is breaking till the last chain, as
callbacks are missed in between chain along nested path. This will help
get full trace and correlate parent child relationship in all nested
chains.
- Issue: the issue #8786
- Dependencies: NA
- Tag maintainer: @agola11
- Twitter handle: Agarwal_Ankur
Description: When using a ReAct Agent with tools and no tool is found,
the InvalidTool gets called. Previously it just asked for a different
action, but I've found that if you list the available actions it
improves the chances of getting a valid action in the next round. I've
added a UnitTest for it also.
@hinthornw
# What
- Add missing test for retrievers self_query
- Add missing import validation
<!-- Thank you for contributing to LangChain!
Replace this comment with:
- Description: Add missing test for retrievers self_query
- Issue: None
- Dependencies: None
- Tag maintainer: @rlancemartin, @eyurtsev
- Twitter handle: @MlopsJ
Please make sure you're PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
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- Tracing / Callbacks: @agola11
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If no one reviews your PR within a few days, feel free to @-mention the
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-->
- Description: we expose Kendra result item id and document id as
document metadata.
- Tag maintainer: @3coins @baskaryan
- Twitter handle: wilsonleao
**Why**
The result item id and document id might be used to keep track of the
retrieved resources.
Added a couple of "integration tests" for these that I ran.
Main design point of feedback: at this point, would it just be better to
have separate arguments for each type? Little confusing what is or isn't
supported and what is the intended usage at this point since I try to
wrap the function as runnable or pack or unpack chains/llms.
```
run_on_dataset(
...
llm_or_chain_factory = None,
llm = None,
chain = NOne,
runnable=None,
function=None
):
# raise error if none set
```
Downside with runnables and arbitrary function support is that you get
much less helpful validation and error messages, but I don't think we
should block you from this, at least.
Description: Adding support for [Amazon
Textract](https://aws.amazon.com/textract/) as a PDF document loader
---------
Co-authored-by: schadem <45048633+schadem@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
