Hi,
After submitting https://github.com/langchain-ai/langchain/pull/11357,
we realized that the notebooks are moved to a new location. Sending a
new PR to update the doc.
---------
Co-authored-by: everly-studio <127131037+everly-studio@users.noreply.github.com>
- Description: Adds the ChatEverlyAI class with llama-2 7b on [EverlyAI
Hosted
Endpoints](https://everlyai.xyz/)
- It inherits from ChatOpenAI and requires openai (probably unnecessary
but it made for a quick and easy implementation)
---------
Co-authored-by: everly-studio <127131037+everly-studio@users.noreply.github.com>
- **Description:**
- If the Elasticsearch field used for Langchain > Document.page_content
is missing because the specific document is
somehow malformed fail gracefully.
- **Tag maintainer:**
- @joemcelroy
Reverts langchain-ai/langchain#11714
This has linting and formatting issues, plus it's added to chat models
folder but doesn't subclass Chat Model base class
Motivation and Context
At present, the Baichuan Large Language Model is relatively popular and
efficient in performance. Due to widespread market recognition, this
model has been added to enhance the scalability of Langchain's ability
to access the big language model, so as to facilitate application access
and usage for interested users.
System Info
langchain： 0.0.295
python：3.8.3
IDE：vs code
Description
Add the following files:
1. Add baichuan_baichuaninc_endpoint.py in the
libs/langchain/langchain/chat_models
2. Modify the __init__.py file,which is located in the
libs/langchain/langchain/chat_models/__init__.py：
a. Add "from langchain.chat_models.baichuan_baichuaninc_endpoint import
BaichuanChatEndpoint"
b. Add "BaichuanChatEndpoint" In the file's __ All__ method
Your contribution
I am willing to help implement this feature and submit a PR, but I would
appreciate guidance from the maintainers or community to ensure the
changes are made correctly and in line with the project's standards and
practices.
- **Description:** Add `TrainableLLM` for those LLM support fine-tuning
- **Tag maintainer:** @hwchase17
This PR add training methods to `GradientLLM`
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Hi there
This PR is aim to implement chat model for Alibaba Tongyi LLM model. It
contains work below:
1.Implement ChatTongyi chat model in langchain.chat_models.tongyi. Note
this is different with tongyi llm model to another PR
https://github.com/langchain-ai/langchain/pull/10878.
For detail it implements _generate() and _stream() function in
ChatTongyi.
2. Add some examples in chat/tongyi.ipynb.
3. Add integration test in chat_models/test_tongyi.py
Note async completion for the Text API is not yet supported.
Dependencies: dashscope. It will be installed manually cause it is not
need by everyone.
**Description**
This PR adds the `ElasticsearchChatMessageHistory` implementation that
stores chat message history in the configured
[Elasticsearch](https://www.elastic.co/elasticsearch/) deployment.
```python
from langchain.memory.chat_message_histories import ElasticsearchChatMessageHistory
history = ElasticsearchChatMessageHistory(
es_url="https://my-elasticsearch-deployment-url:9200", index="chat-history-index", session_id="123"
)
history.add_ai_message("This is me, the AI")
history.add_user_message("This is me, the human")
```
**Dependencies**
- [elasticsearch client](https://elasticsearch-py.readthedocs.io/)
required
Co-authored-by: Bagatur <baskaryan@gmail.com>
Instead of accessing `langchain.debug`, `langchain.verbose`, or
`langchain.llm_cache`, please use the new getter/setter functions in
`langchain.globals`:
- `langchain.globals.set_debug()` and `langchain.globals.get_debug()`
- `langchain.globals.set_verbose()` and
`langchain.globals.get_verbose()`
- `langchain.globals.set_llm_cache()` and
`langchain.globals.get_llm_cache()`
Using the old globals directly will now raise a warning.
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Description:**
Add a document loader for the RSpace Electronic Lab Notebook
(www.researchspace.com), so that scientific documents and research notes
can be easily pulled into Langchain pipelines.
**Issue**
This is an new contribution, rather than an issue fix.
**Dependencies:**
There are no new required dependencies.
In order to use the loader, clients will need to install rspace_client
SDK using `pip install rspace_client`
---------
Co-authored-by: richarda23 <richard.c.adams@infinityworks.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** Update Indexing API docs to specify vectorstores that
are compatible with the Indexing API. I add a unit test to remind
developers to update the documentation whenever they add or change a
vectorstore in a way that affects compatibility. For the unit test I
repurposed existing code from
[here](https://github.com/langchain-ai/langchain/blob/v0.0.311/libs/langchain/langchain/indexes/_api.py#L245-L257).
This is my first PR to an open source project. This is a trivially
simple PR whose main purpose is to make me more comfortable submitting
Langchain PRs. If this PR goes through I plan to submit PRs with more
substantive changes in the near future.
**Issue:** Resolves
[10482](https://github.com/langchain-ai/langchain/discussions/10482).
**Dependencies:** No new dependencies.
**Twitter handle:** None.
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Allows MMR functionality only for the case where we have access to the
embedding function. Also allows for users to request for fields from
elasticsearch store. These are added to the document metadata.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Description: Introducing an ability to load a transcription document of
audio file using [Yandex
SpeechKit](https://cloud.yandex.com/en-ru/services/speechkit)
Issue: None
Dependencies: yandex-speechkit
Tag maintainer: @rlancemartin, @eyurtsev
**Description**
This PR implements the usage of the correct tokenizer in Bedrock LLMs,
if using anthropic models.
**Issue:** #11560
**Dependencies:** optional dependency on `anthropic` python library.
**Twitter handle:** jtolgyesi
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** Modify Anyscale integration to work with [Anyscale
Endpoint](https://docs.endpoints.anyscale.com/)
and it supports invoke, async invoke, stream and async invoke features
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
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@baskaryan, @eyurtsev, @hwchase17.
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submitting. Run `make format`, `make lint` and `make test` to check this
locally.
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tests, lint, etc:
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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
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Should delegate to parse_result, not to aparse, as parse_result is a
method that some output parsers override
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- **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!
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submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
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/extras`
directory.
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@baskaryan, @eyurtsev, @hwchase17.
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**Description:** Avoid huggingfacepipeline to truncate the response if
user setup return_full_text as False within huggingface pipeline.
**Dependencies:** : None
**Tag maintainer:** Maybe @sam-h-bean ?
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** implements a retriever on top of DocAI Warehouse (to
interact with existing enterprise documents)
https://cloud.google.com/document-ai-warehouse?hl=en
- **Issue:** new functionality
@baskaryan
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
