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…14125) - **Description:** to support not only publicly available Hugging Face endpoints, but also protected ones (created with "Inference Endpoints" Hugging Face feature), I have added ability to specify custom api_url. But if not specified, default behaviour won't change - **Issue:** langchain-ai#9181, - **Dependencies:** no extra dependencies
Add option to override input_type for cohere's v3 embeddings models --------- Co-authored-by: Bagatur <[email protected]>
### Description Starting from [openai version 1.0.0](https://github.com/openai/openai-python/tree/17ac6779958b2b74999c634c4ea4c7b74906027a#module-level-client), the camel case form of `openai.ChatCompletion` is no longer supported and has been changed to lowercase `openai.chat.completions`. In addition, the returned object only accepts attribute access instead of index access: ```python import openai # optional; defaults to `os.environ['OPENAI_API_KEY']` openai.api_key = '...' # all client options can be configured just like the `OpenAI` instantiation counterpart openai.base_url = "https://..." openai.default_headers = {"x-foo": "true"} completion = openai.chat.completions.create( model="gpt-4", messages=[ { "role": "user", "content": "How do I output all files in a directory using Python?", }, ], ) print(completion.choices[0].message.content) ``` So I implemented a compatible adapter that supports both attribute access and index access: ```python In [1]: from langchain.adapters import openai as lc_openai ...: messages = [{"role": "user", "content": "hi"}] In [2]: result = lc_openai.chat.completions.create( ...: messages=messages, model="gpt-3.5-turbo", temperature=0 ...: ) In [3]: result.choices[0].message Out[3]: {'role': 'assistant', 'content': 'Hello! How can I assist you today?'} In [4]: result["choices"][0]["message"] Out[4]: {'role': 'assistant', 'content': 'Hello! How can I assist you today?'} In [5]: result = await lc_openai.chat.completions.acreate( ...: messages=messages, model="gpt-3.5-turbo", temperature=0 ...: ) In [6]: result.choices[0].message Out[6]: {'role': 'assistant', 'content': 'Hello! How can I assist you today?'} In [7]: result["choices"][0]["message"] Out[7]: {'role': 'assistant', 'content': 'Hello! How can I assist you today?'} In [8]: for rs in lc_openai.chat.completions.create( ...: messages=messages, model="gpt-3.5-turbo", temperature=0, stream=True ...: ): ...: print(rs.choices[0].delta) ...: print(rs["choices"][0]["delta"]) ...: {'role': 'assistant', 'content': ''} {'role': 'assistant', 'content': ''} {'content': 'Hello'} {'content': 'Hello'} {'content': '!'} {'content': '!'} In [20]: async for rs in await lc_openai.chat.completions.acreate( ...: messages=messages, model="gpt-3.5-turbo", temperature=0, stream=True ...: ): ...: print(rs.choices[0].delta) ...: print(rs["choices"][0]["delta"]) ...: {'role': 'assistant', 'content': ''} {'role': 'assistant', 'content': ''} {'content': 'Hello'} {'content': 'Hello'} {'content': '!'} {'content': '!'} ... ``` ### Twitter handle [lin_bob57617](https://twitter.com/lin_bob57617)
- **Description:** Our PR is an integration of a Steam API Tool that makes recommendations on steam games based on user's Steam profile and provides information on games based on user provided queries. - **Issue:** the issue # our PR implements: langchain-ai#12120 - **Dependencies:** python-steam-api library, steamspypi library and decouple library - **Tag maintainer:** @baskaryan, @hwchase17 - **Twitter handle:** N/A Hello langchain Maintainers, We are a team of 4 University of Toronto students contributing to langchain as part of our course [CSCD01 (link to course page)](https://cscd01.com/work/open-source-project). We hope our changes help the community. We have run make format, make lint and make test locally before submitting the PR. To our knowledge, our changes do not introduce any new errors. Our PR integrates the python-steam-api, steamspypi and decouple packages. We have added integration tests to test our python API integration into langchain and an example notebook is also provided. Our amazing team that contributed to this PR: @JohnY2002, @shenceyang, @andrewqian2001 and @muntaqamahmood Thank you in advance to all the maintainers for reviewing our PR! --------- Co-authored-by: Shence <[email protected]> Co-authored-by: JohnY2002 <[email protected]> Co-authored-by: Andrew Qian <[email protected]> Co-authored-by: Harrison Chase <[email protected]> Co-authored-by: JohnY <[email protected]>
…ain-ai#13966) ### **Description** Hi, I just started learning the source code of `langchain` and hope to contribute code. However, according to the instructions in the [CONTRIBUTING.md](https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md) document, I could not run the test command `make test` to run normally. I found that many modules did not exist after [splitting `langchain_core`](langchain-ai#13823), so I updated the document. ### **Twitter handle** lin_bob57617
**Description:** Adds the document loader for [Couchbase](http://couchbase.com/), a distributed NoSQL database. **Dependencies:** Added the Couchbase SDK as an optional dependency. **Twitter handle:** nithishr --------- Co-authored-by: Bagatur <[email protected]>
Switches to a more maintained solution for building ipynb -> md files (`quarto`) Also bumps us down to python3.8 because it's significantly faster in the vercel build step. Uses default openssl version instead of upgrading as well.
- **Description:** Obsidian templates can include [variables](https://help.obsidian.md/Plugins/Templates#Template+variables) using double curly braces. `ObsidianLoader` uses PyYaml to parse the frontmatter of documents. This parsing throws an error when encountering variables' curly braces. This is avoided by temporarily substituting safe strings before parsing. - **Issue:** langchain-ai#13887 - **Tag maintainer:** @hwchase17
…n-ai#13695) <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** The existing version hardcoded search.windows.net in the base url. This is not compatible with the gov cloud. I am allowing the user to override the default for gov cloud support., - **Issue:** N/A, did not write up in an issue, - **Dependencies:** None Please make sure your PR is passing linting and testing before 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Nicholas Ceccarelli <[email protected]> Co-authored-by: Harrison Chase <[email protected]>
Co-authored-by: Jacob Matias <[email protected]> Co-authored-by: Karam Daid <[email protected]> Co-authored-by: Jumana <[email protected]> Co-authored-by: KaramDaid <[email protected]> Co-authored-by: Anna Chester <[email protected]> Co-authored-by: Jumana <[email protected]>
langchain-ai#14201) If we are not going to make the existing Docstore class also implement `BaseStore[str, Document]`, IMO all base store implementations should always be `[str, bytes]` so that they are more interchangeable. CC @rlancemartin @eyurtsev
…le (langchain-ai#14230) **Description:** When a RunnableLambda only receives a synchronous callback, this callback is wrapped into an async one since langchain-ai#13408. However, this wrapping with `(*args, **kwargs)` causes the `accepts_config` check at [/libs/core/langchain_core/runnables/config.py#L342](https://github.com/langchain-ai/langchain/blob/ee94ef55ee6ab064da08340817955f821dfa6261/libs/core/langchain_core/runnables/config.py#L342) to fail, as this checks for the presence of a "config" argument in the method signature. Adding a `functools.wraps` around it, resolves it.
…hain-ai#14202) Allow users to pass a generic `BaseStore[str, bytes]` to MultiVectorRetriever, removing the need to use the `create_kv_docstore` method. This encoding will now happen internally. @rlancemartin @eyurtsev --------- Co-authored-by: Eugene Yurtsev <[email protected]>
The `/docs/integrations/toolkits/vectorstore` page is not the Integration page. The best place is in `/docs/modules/agents/how_to/` - Moved the file - Rerouted the page URL
# Dependencies None # Twitter handle @HKydlicek --------- Co-authored-by: Erick Friis <[email protected]>
…ts (langchain-ai#9027) The Github utilities are fantastic, so I'm adding support for deeper interaction with pull requests. Agents should read "regular" comments and review comments, and the content of PR files (with summarization or `ctags` abbreviations). Progress: - [x] Add functions to read pull requests and the full content of modified files. - [x] Function to use Github's built in code / issues search. Out of scope: - Smarter summarization of file contents of large pull requests (`tree` output, or ctags). - Smarter functions to checkout PRs and edit the files incrementally before bulk committing all changes. - Docs example for creating two agents: - One watches issues: For every new issue, open a PR with your best attempt at fixing it. - The other watches PRs: For every new PR && every new comment on a PR, check the status and try to finish the job. <!-- Thank you for contributing to LangChain! 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 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: Erick Friis <[email protected]>
Running a large number of requests to Embaas' servers (or any server) can result in intermittent network failures (both from local and external network/service issues). This PR implements exponential backoff retries to help mitigate this issue.
- **Description:** fixed the transform_input method in the example., - **Issue:** example didn't work, - **Dependencies:** None, - **Tag maintainer:** @baskaryan, - **Twitter handle:** @Ravidhu87
Co-authored-by: SebastjanPrachovskij <[email protected]>
Hi! I'm Alex, Python SDK Team Lead from [Comet](https://www.comet.com/site/). This PR contains our new integration between langchain and Comet - `CometTracer` class which uses new `comet_llm` python package for submitting data to Comet. No additional dependencies for the langchain package are required directly, but if the user wants to use `CometTracer`, `comet-llm>=2.0.0` should be installed. Otherwise an exception will be raised from `CometTracer.__init__`. A test for the feature is included. There is also an already existing callback (and .ipynb file with example) which ideally should be deprecated in favor of a new tracer. I wasn't sure how exactly you'd prefer to do it. For example we could open a separate PR for that. I'm open to your ideas :)
- **Description:** Bugfix duckduckgo_search news search - **Issue:** langchain-ai#13648 - **Dependencies:** None - **Tag maintainer:** @baskaryan --------- Co-authored-by: Harrison Chase <[email protected]>
…chain-ai#13619) **Description** Implements `max_marginal_relevance_search` and `max_marginal_relevance_search_by_vector` for the Momento Vector Index vectorstore. Additionally bumps the `momento` dependency in the lock file and adds logging to the implementation. **Dependencies** ✅ updates `momento` dependency in lock file **Tag maintainer** @baskaryan **Twitter handle** Please tag @momentohq for Momento Vector Index and @mloml for the contribution 🙇 <!-- Thank you for contributing to LangChain! 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, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **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` 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->
delete code that could never be reached
- npm - search config - custom
Add [Text Embeddings by Cloudflare Workers AI](https://developers.cloudflare.com/workers-ai/models/text-embeddings/). It's a new integration. Trying to align it with its langchain-js version counterpart [here](https://api.js.langchain.com/classes/embeddings_cloudflare_workersai.CloudflareWorkersAIEmbeddings.html). - Dependencies: N/A - Done `make format` `make lint` `make spell_check` `make integration_tests` and all my changes was passed
Co-authored-by: stvhu-bookend <[email protected]>
here it is validating shapely.geometry.point.Point: if not
isinstance(data_frame[page_content_column].iloc[0], gpd.GeoSeries):
raise ValueError(
f"Expected data_frame[{page_content_column}] to be a GeoSeries" you need
it to validate the geoSeries and not the shapely.geometry.point.Point
if not isinstance(data_frame[page_content_column], gpd.GeoSeries):
raise ValueError(
f"Expected data_frame[{page_content_column}] to be a GeoSeries"
<!-- Thank you for contributing to LangChain!
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,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **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` 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.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
Description: There's a copy-paste typo where on_llm_error() calls _on_chain_error() instead of _on_llm_error(). Issue: langchain-ai#13580 Dependencies: None Tag maintainer: @hwchase17 Twitter handle: @jwatte "Run `make format`, `make lint` and `make test` to check this locally." The test scripts don't work in a plain Ubuntu LTS 20.04 system. It looks like the dev container pulling is stuck. Or maybe the internet is just ornery today. --------- Co-authored-by: jwatte <[email protected]> Co-authored-by: Harrison Chase <[email protected]>
…-ai#14823) ... variable, accompanied by a quote Co-authored-by: Yacine Bouakkaz <[email protected]>
[ScaNN](https://python.langchain.com/docs/integrations/providers/scann) and [DynamoDB](https://python.langchain.com/docs/integrations/platforms/aws#aws-dynamodb) pages in `providers` are redundant because we have those references in the Google and AWS platform pages. It is confusing. - I removed unnecessary pages, redirected files to new nams;
Corrected path reference from package/pirate-speak to packages/pirate-speak
Now that it's supported again for OAI chat models . Shame this wouldn't include it in the `.invoke()` output though (it's not included in the message itself). Would need to do a follow-up for that to be the case
…ndpoints` (langchain-ai#14827) This page doesn't exist: - https://python.langchain.com/docs/integrations/text_embeddings/nvidia_ai_endpoints but this one does: - https://python.langchain.com/docs/integrations/text_embedding/nvidia_ai_endpoints
Description: Fixes minor typo to documentation
**Description:** fixing a broken link to the extraction doc page
…xAIEmbeddings (langchain-ai#13999) - **Description:** VertexAIEmbeddings performance improvements - **Twitter handle:** @vladkol ## Improvements - Dynamic batch size, starting from 250, lowering down to 5. Batch size varies across regions. Some regions support larger batches, and it significantly improves performance. When running large batches of texts in `us-central1`, performance gain can be up to 3.5x. The dynamic batching also makes sure every batch is below 20K token limit. - New model parameter `embeddings_type` that translates to `task_type` parameter of the API. Newer model versions support [different embeddings task types](https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings#api_changes_to_models_released_on_or_after_august_2023).
Gpt-3.5 sometimes calls with empty string arguments instead of `{}`
I'd assume it's because the typescript representation on their backend
makes it a bit ambiguous.
…#14830) Tool outputs have to be strings apparently. Ensure they are formatted correctly before passing as intermediate steps. ``` BadRequestError: Error code: 400 - {'error': {'message': '1 validation error for Request\nbody -> tool_outputs -> 0 -> output\n str type expected (type=type_error.str)', 'type': 'invalid_request_error', 'param': None, 'code': None}} ```
<img width="1305" alt="Screenshot 2023-12-18 at 9 54 01 PM" src="https://github.com/langchain-ai/langchain/assets/10000925/c943fd81-cd48-46eb-8dff-4680424d9ba9"> The current model is no longer available.
- **Description:** Modification of descriptions for marketing purposes and transitioning towards `platforms` directory if possible. - **Issue:** Some marketing opportunities, lodging PR and awaiting later discussions. - This PR is intended to be merged when decisions settle/hopefully after further considerations. Submitting as Draft for now. Nobody @'d yet. --------- Co-authored-by: Bagatur <[email protected]>
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Downmerge version 0.0.351 of langchain to skypoint-langchain
All these changes are from version 0.0.351 release of langchain