Thank you for contributing to LangChain!
- [x] **PR title**: community: Add Zep Cloud components + docs +
examples
- [x] **PR message**:
We have recently released our new zep-cloud sdks that are compatible
with Zep Cloud (not Zep Open Source). We have also maintained our Cloud
version of langchain components (ChatMessageHistory, VectorStore) as
part of our sdks. This PRs goal is to port these components to langchain
community repo, and close the gap with the existing Zep Open Source
components already present in community repo (added
ZepCloudMemory,ZepCloudVectorStore,ZepCloudRetriever).
Also added a ZepCloudChatMessageHistory components together with an
expression language example ported from our repo. We have left the
original open source components intact on purpose as to not introduce
any breaking changes.
- **Issue:** -
- **Dependencies:** Added optional dependency of our new cloud sdk
`zep-cloud`
- **Twitter handle:** @paulpaliychuk51
- [x] **Add tests and docs**
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
3 fixes of DuckDB vector store:
- unify defaults in constructor and from_texts (users no longer have to
specify `vector_key`).
- include search similarity into output metadata (fixes#20969)
- significantly improve performance of `from_documents`
Dependencies: added Pandas to speed up `from_documents`.
I was thinking about CSV and JSON options, but I expect trouble loading
JSON values this way and also CSV and JSON options require storing data
to disk.
Anyway, the poetry file for langchain-community already contains a
dependency on Pandas.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
Thank you for contributing to LangChain!
- [X] **PR title**: community: Updated langchain-community PremAI
documentation
- [X] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
- **Description:** I've added a tab on embedding text with LangChain
using Hugging Face models to here:
https://python.langchain.com/v0.2/docs/how_to/embed_text/. HF was
mentioned in the running text, but not in the tabs, which I thought was
odd.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** No need, this is tiny :)
Also, I had a ton of issues with the poetry docs/lint install, so I
haven't linted this. Apologies for that.
cc @Jofthomas
- Tom Aarsen
**PR message**:
Update `hub.pull("rlm/map-prompt")` to `hub.pull("rlm/reduce-prompt")`
in summarization.ipynb
**Description:**
Fix typo in prompt hub link from `reduce_prompt =
hub.pull("rlm/map-prompt")` to `reduce_prompt =
hub.pull("rlm/reduce-prompt")` following next issue
**Issue:** #22014
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
This PR is opinionated.
Issue: the `API Reference` sections in the examples hold too much
vertical space and make us scroll the page too much. See an
[example](https://python.langchain.com/docs/get_started/quickstart/#conversation-retrieval-chain).
These sections are **important**. So, the compacting should not make
these sections less noticeable.
Change: compacting the `API Reference` sections. See the [same example
after change
applied](https://langchain-j6nya46lf-langchain.vercel.app/docs/get_started/quickstart/#conversation-retrieval-chain).
It is more compact and now looks like references (footnotes).
Note: I would also change the section style, so it would be more
noticeable (maybe to look like the footnotes. Smaller wider font?)
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
We dont really have any abstractions around multi-modal... so add a
section explaining we dont have any abstrations and then how to guides
for openai and anthropic (probably need to add for more)
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Tomaz Bratanic <bratanic.tomaz@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: junefish <junefish@users.noreply.github.com>
Co-authored-by: William Fu-Hinthorn <13333726+hinthornw@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Added [Scrapfly](https://scrapfly.io/) Web Loader integration. Scrapfly
is a web scraping API that allows extracting web page data into
accessible markdown or text datasets.
- __Description__: Added Scrapfly web loader for retrieving web page
data as markdown or text.
- Dependencies: scrapfly-sdk
- Twitter: @thealchemi1st
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** Backwards compatible extension of the initialisation
interface of HanaDB to allow the user to specify
specific_metadata_columns that are used for metadata storage of selected
keys which yields increased filter performance. Any not-mentioned
metadata remains in the general metadata column as part of a JSON
string. Furthermore switched to executemany for batch inserts into
HanaDB.
**Issue:** N/A
**Dependencies:** no new dependencies added
**Twitter handle:** @sapopensource
---------
Co-authored-by: Martin Kolb <martin.kolb@sap.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Integrate RankLLM reranker (https://github.com/castorini/rank_llm) into
LangChain
An example notebook is given in
`docs/docs/integrations/retrievers/rankllm-reranker.ipynb`
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "update IBM WatsonxLLM docs with deprecated
LLMChain"
- [x] **PR message**:
- **Description:** update IBM WatsonxLLM docs with deprecated LLMChain
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
- Updated docs to have an example to use Jamba instead of J2
---------
Co-authored-by: Asaf Gardin <asafg@ai21.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Tongyi uses different client for chat model and
vision model. This PR chooses proper client based on model name to
support both chat model and vision model. Reference [tongyi
document](https://help.aliyun.com/zh/dashscope/developer-reference/tongyi-qianwen-vl-plus-api?spm=a2c4g.11186623.0.0.27404c9a7upm11)
for details.
```
from langchain_core.messages import HumanMessage
from langchain_community.chat_models import ChatTongyi
llm = ChatTongyi(model_name='qwen-vl-max')
image_message = {
"image": "https://lilianweng.github.io/posts/2023-06-23-agent/agent-overview.png"
}
text_message = {
"text": "summarize this picture",
}
message = HumanMessage(content=[text_message, image_message])
llm.invoke([message])
```
- **Issue:** None
- **Dependencies:** None
- **Twitter handle:** None
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
- `llm_chain` becomes `Union[LLMChain, Runnable]`
- `.from_llm` creates a runnable
tested by verifying that docs/how_to/MultiQueryRetriever.ipynb runs
unchanged with sync/async invoke (and that it runs if we specifically
instantiate with LLMChain).
We add a tool and retriever for the [AskNews](https://asknews.app)
platform with example notebooks.
The retriever can be invoked with:
```py
from langchain_community.retrievers import AskNewsRetriever
retriever = AskNewsRetriever(k=3)
retriever.invoke("impact of fed policy on the tech sector")
```
To retrieve 3 documents in then news related to fed policy impacts on
the tech sector. The included notebook also includes deeper details
about controlling filters such as category and time, as well as
including the retriever in a chain.
The tool is quite interesting, as it allows the agent to decide how to
obtain the news by forming a query and deciding how far back in time to
look for the news:
```py
from langchain_community.tools.asknews import AskNewsSearch
from langchain import hub
from langchain.agents import AgentExecutor, create_openai_functions_agent
from langchain_openai import ChatOpenAI
tool = AskNewsSearch()
instructions = """You are an assistant."""
base_prompt = hub.pull("langchain-ai/openai-functions-template")
prompt = base_prompt.partial(instructions=instructions)
llm = ChatOpenAI(temperature=0)
asknews_tool = AskNewsSearch()
tools = [asknews_tool]
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(
agent=agent,
tools=tools,
verbose=True,
)
agent_executor.invoke({"input": "How is the tech sector being affected by fed policy?"})
```
---------
Co-authored-by: Emre <e@emre.pm>
Please let me know if you see any possible areas of improvement. I would
very much appreciate your constructive criticism if time allows.
**Description:**
- Added a aerospike vector store integration that utilizes
[Aerospike-Vector-Search](https://aerospike.com/products/vector-database-search-llm/)
add-on.
- Added both unit tests and integration tests
- Added a docker compose file for spinning up a test environment
- Added a notebook
**Dependencies:** any dependencies required for this change
- aerospike-vector-search
**Twitter handle:**
- No twitter, you can use my GitHub handle or LinkedIn if you'd like
Thanks!
---------
Co-authored-by: Jesse Schumacher <jschumacher@aerospike.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Closes#20561
This PR fixes MLX LLM stream `AttributeError`.
Recently, `mlx-lm` changed the token decoding logic, which affected the
LC+MLX integration.
Additionally, I made minor fixes such as: docs example broken link and
enforcing pipeline arguments (max_tokens, temp and etc) for invoke.
- **Issue:** #20561
- **Twitter handle:** @Prince_Canuma
UpTrain has a new dashboard now that makes it easier to view projects
and evaluations. Using this requires specifying both project_name and
evaluation_name when performing evaluations. I have updated the code to
support it.
The Diffbot DocumentLoader page doesn't actually run for a number of
reasons. This PR fixes it along with some light details on the Graph
Transformer and Provider pages.
## Full Changelog
[Document Loader
Page](https://python.langchain.com/v0.1/docs/integrations/document_loaders/diffbot/)
* Fixed the notebook so that it actually runs (missing required modules,
env variables, etc..)
* Added "open in colab" button like the Graph Transformer page
[Graph Transformer
Page](https://python.langchain.com/v0.2/docs/integrations/graphs/diffbot/)
* Fixed broken colab link
* Moved "open in colab" button to below description so the description
in the [Graphs category
page](https://python.langchain.com/v0.2/docs/integrations/graphs/) shows
up correctly
[Provider
Page](https://python.langchain.com/v0.2/docs/integrations/providers/diffbot/)
* Clarified explanations of Diffbot products
* Added section and link to LangChain Graph Transformer page
---------
Co-authored-by: jeromechoo <hello@jeromechoo.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** Add `Origin/langchain` to Apify's client's user-agent
to attribute API activity to LangChain (at Apify, we aim to monitor our
integrations to evaluate whether we should invest more in the LangChain
integration regarding functionality and content)
**Issue:** None
**Dependencies:** None
**Twitter handle:** None
Fixed Documentation for HuggingFaceEndpoint as per the issue #21903
---------
Co-authored-by: keenborder786 <mohammad.mohtashim78@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "docs: update notebook for latest Pinecone API +
serverless"
- [x] **PR message**: Published notebook is incompatible with latest
`pinecone-client` and not runnable. Updated for use with latest Pinecone
Python SDK. Also updated to be compatible with serverless indexes (only
index type available on Pinecone free tier).
- [x] **Add tests and docs**: N/A (tested in Colab)
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---
- To see the specific tasks where the Asana app for GitHub is being
used, see below:
- https://app.asana.com/0/0/1207328087952499
Thank you for contributing to LangChain!
- [x] **PR title**: "docs: update notebook for new Pinecone API +
serverless"
- [x] **PR message**: The published notebook is not runnable after
`pinecone-client` v2, which is deprecated. `langchain-pinecone` is not
compatible with the latest `pinecone-client` (v4), so I hardcoded it to
the last v3. Also updated for serverless indexes (only index type
available on Pinecone free plan).
- [x] **Add tests and docs**: N/A (tested in Colab)
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---
- To see the specific tasks where the Asana app for GitHub is being
used, see below:
- https://app.asana.com/0/0/1207328087952500
- bind_tools interface is a better alternative.
- openai doesn't use functions but tools in its API now.
- the underlying content appears in some redirects, so will need to
investigate if we can remove.
Update tool calling using prompts.
- Add required concepts
- Update names of tool invoking function.
- Add doc-string to function, and add information about `config` (which
users often forget)
- Remove steps that show how to use single function only. This makes the
how-to guide a bit shorter and more to the point.
- Add diagram from another how-to guide that shows how the thing works
overall.
Since the LangChain based on many research papers, the LC documentation
has several references to the arXiv papers. It would be beneficial to
create a single page with all referenced papers.
PR:
1. Developed code to search the arXiv references in the LangChain
Documentation and the LangChain code base. Those references are included
in a newly generated documentation page.
2. Page is linked to the Docs menu.
Controversial:
1. The `arxiv_references` page is automatically generated. But this
generation now started only manually. It is not included in the doc
generation scripts. The reason for this is simple. I don't want to
mangle into the current documentation refactoring. If you think, we need
to regenerate this page in each build, let me know. Note: This script
has a dependency on the `arxiv` package.
2. The link for this page in the menu is not obvious.
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
There are 2 issues fixed here:
* In the notebook pandas dataframes are formatted as HTML in the cells.
On the documentation site the renderer that converts notebooks
incorrectly displays the raw HTML. I can't find any examples of where
this is working and so I am formatting the dataframes as text.
* Some incorrect table names were referenced resulting in errors.
The only change is replacing the word "operators" with "operates," to
make the sentence grammatically correct.
Thank you for contributing to LangChain!
- [x] **PR title**: "docs: Made a grammatical correction in
streaming.ipynb to use the word "operates" instead of the word
"operators""
- [x] **PR message**:
- **Description:** The use of the word "operators" was incorrect, given
the context and grammar of the sentence. This PR updates the
documentation to use the word "operates" instead of the word
"operators".
- **Issue:** Makes the documentation more easily understandable.
- **Dependencies:** -no dependencies-
- **Twitter handle:** --
- [x] **Add tests and docs**: Since no new integration is being made, no
new tests/example notebooks are required.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
- **No formatting changes made to the documentation**
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
- Remove double implementations of functions. The single input is just
taking up space.
- Added tool specific information for `async + showing invoke vs.
ainvoke.
- Added more general information about about `async` (this should live
in a different place eventually since it's not specific to tools).
- Changed ordering of custom tools (StructuredTool is simpler and should
appear before the inheritance)
- Improved the error handling section (not convinced it should be here
though)
- Add information about naitve tool calling capabilities
- Add information about standard langchain interface for tool calling
- Update description for tools
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
This PR improves on the `CassandraCache` and `CassandraSemanticCache`
classes, mainly in the constructor signature, and also introduces
several minor improvements around these classes.
### Init signature
A (sigh) breaking change is tentatively introduced to the constructor.
To me, the advantages outweigh the possible discomfort: the new syntax
places the DB-connection objects `session` and `keyspace` later in the
param list, so that they can be given a default value. This is what
enables the pattern of _not_ specifying them, provided one has
previously initialized the Cassandra connection through the versatile
utility method `cassio.init(...)`.
In this way, a much less unwieldy instantiation can be done, such as
`CassandraCache()` and `CassandraSemanticCache(embedding=xyz)`,
everything else falling back to defaults.
A downside is that, compared to the earlier signature, this might turn
out to be breaking for those doing positional instantiation. As a way to
mitigate this problem, this PR typechecks its first argument trying to
detect the legacy usage.
(And to make this point less tricky in the future, most arguments are
left to be keyword-only).
If this is considered too harsh, I'd like guidance on how to further
smoothen this transition. **Our plan is to make the pattern of optional
session/keyspace a standard across all Cassandra classes**, so that a
repeatable strategy would be ideal. A possibility would be to keep
positional arguments for legacy reasons but issue a deprecation warning
if any of them is actually used, to later remove them with 0.2 - please
advise on this point.
### Other changes
- class docstrings: enriched, completely moved to class level, added
note on `cassio.init(...)` pattern, added tiny sample usage code.
- semantic cache: revised terminology to never mention "distance" (it is
in fact a similarity!). Kept the legacy constructor param with a
deprecation warning if used.
- `llm_caching` notebook: uniform flow with the Cassandra and Astra DB
separate cases; better and Cassandra-first description; all imports made
explicit and from community where appropriate.
- cache integration tests moved to community (incl. the imported tools),
env var bugfix for `CASSANDRA_CONTACT_POINTS`.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [x] **PR title**: "community: updated Browserbase loader"
- [x] **PR message**:
Updates the Browserbase loader with more options and improved docs.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
## Description
This PR introduces the new `langchain-qdrant` partner package, intending
to deprecate the community package.
## Changes
- Moved the Qdrant vector store implementation `/libs/partners/qdrant`
with integration tests.
- The conditional imports of the client library are now regular with
minor implementation improvements.
- Added a deprecation warning to
`langchain_community.vectorstores.qdrant.Qdrant`.
- Replaced references/imports from `langchain_community` with either
`langchain_core` or by moving the definitions to the `langchain_qdrant`
package itself.
- Updated the Qdrant vector store documentation to reflect the changes.
## Testing
- `QDRANT_URL` and
[`QDRANT_API_KEY`](583e36bf6b)
env values need to be set to [run integration
tests](d608c93d1f)
in the [cloud](https://cloud.qdrant.tech).
- If a Qdrant instance is running at `http://localhost:6333`, the
integration tests will use it too.
- By default, tests use an
[`in-memory`](https://github.com/qdrant/qdrant-client?tab=readme-ov-file#local-mode)
instance(Not comprehensive).
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Erick Friis <erickfriis@gmail.com>
This PR makes some small updates for `KuzuQAChain` for graph QA.
- Updated Cypher generation prompt (we now support `WHERE EXISTS`) and
generalize it more
- Support different LLMs for Cypher generation and QA
- Update docs and examples
- Adds Techniques section
- Moves function calling, retrieval types to Techniques
- Removes Installation section (not conceptual)
- Reorders a few things (chat models before llms, package descriptions
before diagram)
- Add text splitter types to Techniques
First Pr for the langchain_huggingface partner Package
- Moved some of the hugging face related class from `community` to the
new `partner package`
Still needed :
- Documentation
- Tests
- Support for the new apply_chat_template in `ChatHuggingFace`
- Confirm choice of class to support for embeddings witht he
sentence-transformer team.
cc : @efriis
---------
Co-authored-by: Cyril Kondratenko <kkn1993@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- Make sure the left nav bar is horizontally scrollable
- Make sure the navigation dropdown is vertically scrollable and height
capped at 80% of viewport height
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
- Added new document_transformer: MarkdonifyTransformer, that uses
`markdonify` package with customizable options to convert HTML to
Markdown. It's similar to Html2TextTransformer, but has more flexible
options and also I've noticed that sometimes MarkdownifyTransformer
performs better than html2text one, so that's why I use markdownify on
my project.
- Added docs and tests
- Usage:
```python
from langchain_community.document_transformers import MarkdownifyTransformer
markdownify = MarkdownifyTransformer()
docs_transform = markdownify.transform_documents(docs)
```
- Example of better performance on simple task, that I've noticed:
```
<html>
<head><title>Reports on product movement</title></head>
<body>
<p data-block-key="2wst7">The reports on product movement will be useful for forming supplier orders and controlling outcomes.</p>
</body>
```
**Html2TextTransformer**:
```python
[Document(page_content='The reports on product movement will be useful for forming supplier orders and\ncontrolling outcomes.\n\n')]
# Here we can see 'and\ncontrolling', which has extra '\n' in it
```
**MarkdownifyTranformer**:
```python
[Document(page_content='Reports on product movement\n\nThe reports on product movement will be useful for forming supplier orders and controlling outcomes.')]
```
---------
Co-authored-by: Sokolov Fedor <f.sokolov@sokolov-macbook.bbrouter>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Sokolov Fedor <f.sokolov@sokolov-macbook.local>
Co-authored-by: Sokolov Fedor <f.sokolov@192.168.1.6>
Description: We are merging UPSTAGE_DOCUMENT_AI_API_KEY and
UPSTAGE_API_KEY into one, and only UPSTAGE_API_KEY will be used going
forward. And we changed the base class of ChatUpstage to BaseChatOpenAI.
---------
Co-authored-by: Sean <chosh0615@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- Added Together docs in chat models section
- Update Together provider docs to match the LLM & chat models sections
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This is a doc update. It fixes up formatting and product name
references. The example code is updated to use a local built-in text
file.
@mmhangami Please take a look
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Description:** Updated the together integration docs by leading with
the streaming example, explicitly specifying a model to show users how
to do that, and updating the sections to more closely match other
integrations.
**Description:** Adding chat completions to the Together AI package,
which is our most popular API. Also staying backwards compatible with
the old API so folks can continue to use the completions API as well.
Also moved the embedding API to use the OpenAI library to standardize it
further.
**Twitter handle:** @nutlope
- [x] **Add tests and docs**: If you're adding a new integration, please
include
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** Update LarkSuite loader doc to give an example for
loading data from LarkSuite wiki.
**Issue:** None
**Dependencies:** None
**Twitter handle:** None
Thank you for contributing to LangChain!
- Oracle AI Vector Search
Oracle AI Vector Search is designed for Artificial Intelligence (AI)
workloads that allows you to query data based on semantics, rather than
keywords. One of the biggest benefit of Oracle AI Vector Search is that
semantic search on unstructured data can be combined with relational
search on business data in one single system. This is not only powerful
but also significantly more effective because you don't need to add a
specialized vector database, eliminating the pain of data fragmentation
between multiple systems.
- Oracle AI Vector Search is designed for Artificial Intelligence (AI)
workloads that allows you to query data based on semantics, rather than
keywords. One of the biggest benefit of Oracle AI Vector Search is that
semantic search on unstructured data can be combined with relational
search on business data in one single system. This is not only powerful
but also significantly more effective because you don't need to add a
specialized vector database, eliminating the pain of data fragmentation
between multiple systems.
This Pull Requests Adds the following functionalities
Oracle AI Vector Search : Vector Store
Oracle AI Vector Search : Document Loader
Oracle AI Vector Search : Document Splitter
Oracle AI Vector Search : Summary
Oracle AI Vector Search : Oracle Embeddings
- We have added unit tests and have our own local unit test suite which
verifies all the code is correct. We have made sure to add guides for
each of the components and one end to end guide that shows how the
entire thing runs.
- We have made sure that make format and make lint run clean.
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---------
Co-authored-by: skmishraoracle <shailendra.mishra@oracle.com>
Co-authored-by: hroyofc <harichandan.roy@oracle.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Description:Added documentation on Anthropic models on Vertex
@lkuligin for review
---------
Co-authored-by: adityarane@google.com <adityarane@google.com>
Refactors the docs build in order to:
- run the same `make build` command in both vercel and local build
- incrementally build artifacts in 2 distinct steps, instead of building
all docs in-place (in vercel) or in a _dist dir (locally)
Highlights:
- introduces `make build` in order to build the docs
- collects and generates all files for the build in
`docs/build/intermediate`
- renders those jupyter notebook + markdown files into
`docs/build/outputs`
And now the outputs to host are in `docs/build/outputs`, which will need
a vercel settings change.
Todo:
- [ ] figure out how to point the right directory (right now deleting
and moving docs dir in vercel_build.sh isn't great)
**Description:**
This pull request introduces a new feature for LangChain: the
integration with the Rememberizer API through a custom retriever.
This enables LangChain applications to allow users to load and sync
their data from Dropbox, Google Drive, Slack, their hard drive into a
vector database that LangChain can query. Queries involve sending text
chunks generated within LangChain and retrieving a collection of
semantically relevant user data for inclusion in LLM prompts.
User knowledge dramatically improved AI applications.
The Rememberizer integration will also allow users to access general
purpose vectorized data such as Reddit channel discussions and US
patents.
**Issue:**
N/A
**Dependencies:**
N/A
**Twitter handle:**
https://twitter.com/Rememberizer
Vertex DIY RAG APIs helps to build complex RAG systems and provide more
granular control, and are suited for custom use cases.
The Ranking API takes in a list of documents and reranks those documents
based on how relevant the documents are to a given query. Compared to
embeddings that look purely at the semantic similarity of a document and
a query, the ranking API can give you a more precise score for how well
a document answers a given query.
[Reference](https://cloud.google.com/generative-ai-app-builder/docs/ranking)
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description**
This pull request updates the Bagel Network package name from
"betabageldb" to "bagelML" to align with the latest changes made by the
Bagel Network team.
The following modifications have been made:
- Updated all references to the old package name ("betabageldb") with
the new package name ("bagelML") throughout the codebase.
- Modified the documentation, and any relevant scripts to reflect the
package name change.
- Tested the changes to ensure that the functionality remains intact and
no breaking changes were introduced.
By merging this pull request, our project will stay up to date with the
latest Bagel Network package naming convention, ensuring compatibility
and smooth integration with their updated library.
Please review the changes and provide any feedback or suggestions. Thank
you!
**Description:** Update UpstageLayoutAnalysisParser and Loader and add
upstage loader example in pdf section
**Dependencies:** langchain_community
**Twitter handle:** [@upstageai](https://twitter.com/upstageai)
- [x] **Add tests and docs**: 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/docs/integrations` directory.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
**Issue:**
Currently `AzureSearch` vector store does not implement `delete` method.
This PR implements it. This also makes it compatible with LangChain
indexer.
**Dependencies:**
None
**Twitter handle:**
@martintriska1
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
## Description
Adding `UpstashVectorStore` to utilize [Upstash
Vector](https://upstash.com/docs/vector/overall/getstarted)!
#17012 was opened to add Upstash Vector to langchain but was closed to
wait for filtering. Now filtering is added to Upstash vector and we open
a new PR. Additionally, [embedding
feature](https://upstash.com/docs/vector/features/embeddingmodels) was
added and we add this to our vectorstore aswell.
## Dependencies
[upstash-vector](https://pypi.org/project/upstash-vector/) should be
installed to use `UpstashVectorStore`. Didn't update dependencies
because of [this comment in the previous
PR](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1876522450).
## Tests
Tests are added and they pass. Tests are naturally network bound since
Upstash Vector is offered through an API.
There was [a discussion in the previous PR about mocking the
unittests](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1891820567).
We didn't make changes to this end yet. We can update the tests if you
can explain how the tests should be mocked.
---------
Co-authored-by: ytkimirti <yusuftaha9@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description**: ToolKit and Tools for accessing data in a Cassandra
Database primarily for Agent integration. Initially, this includes the
following tools:
- `cassandra_db_schema` Gathers all schema information for the connected
database or a specific schema. Critical for the agent when determining
actions.
- `cassandra_db_select_table_data` Selects data from a specific keyspace
and table. The agent can pass paramaters for a predicate and limits on
the number of returned records.
- `cassandra_db_query` Expiriemental alternative to
`cassandra_db_select_table_data` which takes a query string completely
formed by the agent instead of parameters. May be removed in future
versions.
Includes unit test and two notebooks to demonstrate usage.
**Dependencies**: cassio
**Twitter handle**: @PatrickMcFadin
---------
Co-authored-by: Phil Miesle <phil.miesle@datastax.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** This pull request introduces a new feature to community
tools, enhancing its search capabilities by integrating the Mojeek
search engine
**Dependencies:** None
---------
Co-authored-by: Igor Brai <igor@mojeek.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
Document: Updated google_drive,ipynb for loading following extended
metadata.
- full_path - Full path of the file/s in google drive.
- owner - owner of the file/s.
- size - size of the file/s.
Code changes:
[langchain-google/pull/179.](https://github.com/langchain-ai/langchain-google/pull/179)
Signed-off-by: Rahul Tripathi <rauhl.psit.ec@gmail.com>
Co-authored-by: Rahul Tripathi <rauhl.psit.ec@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "docs: switched GCSLoaders docs to
langchain-google-community"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** switched GCSLoaders docs to
langchain-google-community
Implemented bind_tools for OllamaFunctions.
Made OllamaFunctions sub class of ChatOllama.
Implemented with_structured_output for OllamaFunctions.
integration unit test has been updated.
notebook has been updated.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Added langchainhub package in import statement which is required for
"from langchain import hub" to work.
Added sample code to add OpenAI key
Co-authored-by: Chi Yan Tang <100466443+poochiekittie@users.noreply.github.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
MindsDB integrates with LangChain, enabling users to deploy, serve, and
fine-tune models available via LangChain within MindsDB, making them
accessible to numerous data sources.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
* Groundedness Check takes `str` or `list[Document]` as input.
* Deprecate `GroundednessCheck` due to its naming.
* Added `UpstageGroundednessCheck`.
* Hotfix for Groundedness Check parameter.
The name `query` was misleading and it should be `answer` instead.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- [ ] **Kinetica Document Loader**: "community: a class to load
Documents from Kinetica"
- [ ] **Kinetica Document Loader**:
- **Description:** implemented KineticaLoader in `kinetica_loader.py`
- **Dependencies:** install the Kinetica API using `pip install
gpudb==7.2.0.1 `
- **Description**:
- **add support for more data types**: by default `IpexLLM` will load
the model in int4 format. This PR adds more data types support such as
`sym_in5`, `sym_int8`, etc. Data formats like NF3, NF4, FP4 and FP8 are
only supported on GPU and will be added in future PR.
- Fix a small issue in saving/loading, update api docs
- **Dependencies**: `ipex-llm` library
- **Document**: In `docs/docs/integrations/llms/ipex_llm.ipynb`, added
instructions for saving/loading low-bit model.
- **Tests**: added new test cases to
`libs/community/tests/integration_tests/llms/test_ipex_llm.py`, added
config params.
- **Contribution maintainer**: @shane-huang
Description: Add support for Semantic topics and entities.
Classification done by pebblo-server is not used to enhance metadata of
Documents loaded by document loaders.
Dependencies: None
Documentation: Updated.
Signed-off-by: Rahul Tripathi <rauhl.psit.ec@gmail.com>
Co-authored-by: Rahul Tripathi <rauhl.psit.ec@gmail.com>
**Description:**
This PR removes an unnecessary code snippet from the documentation. The
snippet in question is not relevant to the content and does not
contribute to the overall understanding of the topic. It contained
redundant imports and unused code, potentially causing confusion for
readers.
**Issue:**
There is no specific issue number associated with this change.
**Dependencies:**
No additional dependencies are required for this change.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
**Description:** In VoyageAI text-embedding examples use voyage-law-2
model
- [x] **Add tests and docs**: 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/docs/integrations` directory.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
Thank you for contributing to LangChain!
- [x] **PR title**: Fix misplaced zep cloud example links
- [x] **PR message**:
- **Description:** Fixes misplaced links for vector store and memory zep
cloud examples
- [x] **Add tests and docs**: 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/docs/integrations` directory.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
- **Description:** Adapt JinaEmbeddings to run with the new Jina AI
Rerank API
- **Twitter handle:** https://twitter.com/JinaAI_
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
* Updating the provider docs page.
The RAG example was meant to be moved to cookbook, but was merged by
mistake.
* Fix bug in Groundedness Check
---------
Co-authored-by: JuHyung-Son <sonju0427@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Description :
- added functionalities - delete, index creation, using existing
connection object etc.
- updated usage
- Added LaceDB cloud OSS support
make lint_diff , make test checks done
**Description:** Adds the command to install packages required before
using _Unstructured_ and _PDFMiner_ from `langchain.community`
**Documentation Page Being Updated:** [LangChain > Retrieval > Document
loaders > PDF > Using
Unstructured](https://python.langchain.com/docs/modules/data_connection/document_loaders/pdf/#using-unstructured)
**Issue:** #20719
**Dependencies:** no dependencies
**Twitter handle:** SalikaDave
<!--
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17. -->
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Implemented the ability to enable full-text search within the
SingleStore vector store, offering users a versatile range of search
strategies. This enhancement allows users to seamlessly combine
full-text search with vector search, enabling the following search
strategies:
* Search solely by vector similarity.
* Conduct searches exclusively based on text similarity, utilizing
Lucene internally.
* Filter search results by text similarity score, with the option to
specify a threshold, followed by a search based on vector similarity.
* Filter results by vector similarity score before conducting a search
based on text similarity.
* Perform searches using a weighted sum of vector and text similarity
scores.
Additionally, integration tests have been added to comprehensively cover
all scenarios.
Updated notebook with examples.
CC: @baskaryan, @hwchase17
---------
Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- added guard on the `pyTigerGraph` import
- added a missed example page in the `docs/integrations/graphs/`
- formatted the `docs/integrations/providers/` page to the consistent
format. Added links.
- **Description:**
This PR adds support for advanced filtering to the integration of HANA
Vector Engine.
The newly supported filtering operators are: $eq, $ne, $gt, $gte, $lt,
$lte, $between, $in, $nin, $like, $and, $or
- **Issue:** N/A
- **Dependencies:** no new dependencies added
Added integration tests to:
`libs/community/tests/integration_tests/vectorstores/test_hanavector.py`
Description of the new capabilities in notebook:
`docs/docs/integrations/vectorstores/hanavector.ipynb`
Thank you for contributing to LangChain!
- [x] **PR title**: docs: Update Zep Messaging, add links to Zep Cloud
Docs
- [x] **PR message**:
- **Description:** This PR updates Zep messaging in the docs + links to
Langchain Zep Cloud examples in our documentation
- **Twitter handle:** @paulpaliychuk51
- [x] **Add tests and docs**: 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/docs/integrations` directory.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
- **Description:** In January, Laiyer.ai became part of ProtectAI, which
means the model became owned by ProtectAI. In addition to that,
yesterday, we released a new version of the model addressing issues the
Langchain's community and others mentioned to us about false-positives.
The new model has a better accuracy compared to the previous version,
and we thought the Langchain community would benefit from using the
[latest version of the
model](https://huggingface.co/protectai/deberta-v3-base-prompt-injection-v2).
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** @alex_yaremchuk
Fixed an error in the sample code to ensure that the code can run
directly.
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
langchain_community.document_loaders depricated
new langchain_google_community
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
Thank you for contributing to LangChain!
- [ ] **PR title**: "docs: added a description of differences
langchain_google_genai vs langchain_google_vertexai"
- [ ]
- **Description:** added a description of differences
langchain_google_genai vs langchain_google_vertexai
**Description:** implemented GraphStore class for Apache Age graph db
**Dependencies:** depends on psycopg2
Unit and integration tests included. Formatting and linting have been
run.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** This pull request removes a duplicated `--quiet` flag
in the pip install command found in the LangSmith Walkthrough section of
the documentation.
**Issue:** N/A
**Dependencies:** None
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: docs"
- [ ] **PR message**:
- **Description:** Updated Tutorials for Vertex Vector Search
- **Issue:** NA
- **Dependencies:** NA
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
@lkuligin for review
---------
Co-authored-by: adityarane@google.com <adityarane@google.com>
Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Description: you don't need to pass a version for Replicate official
models. That was broken on LangChain until now!
You can now run:
```
llm = Replicate(
model="meta/meta-llama-3-8b-instruct",
model_kwargs={"temperature": 0.75, "max_length": 500, "top_p": 1},
)
prompt = """
User: Answer the following yes/no question by reasoning step by step. Can a dog drive a car?
Assistant:
"""
llm(prompt)
```
I've updated the replicate.ipynb to reflect that.
twitter: @charliebholtz
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
VSDX data contains EMF files. Some of these apparently can contain
exploits with some Adobe tools.
This is likely a false positive from antivirus software, but we
can remove it nonetheless.
Hey @eyurtsev, I noticed that the notebook isn't displaying the outputs
properly. I've gone ahead and rerun the cells to ensure that readers can
easily understand the functionality without having to run the code
themselves.
fix timeout issue
fix zhipuai usecase notebookbook
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
Thank you for contributing to LangChain!
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
**Community: Unify Titan Takeoff Integrations and Adding Embedding
Support**
**Description:**
Titan Takeoff no longer reflects this either of the integrations in the
community folder. The two integrations (TitanTakeoffPro and
TitanTakeoff) where causing confusion with clients, so have moved code
into one place and created an alias for backwards compatibility. Added
Takeoff Client python package to do the bulk of the work with the
requests, this is because this package is actively updated with new
versions of Takeoff. So this integration will be far more robust and
will not degrade as badly over time.
**Issue:**
Fixes bugs in the old Titan integrations and unified the code with added
unit test converge to avoid future problems.
**Dependencies:**
Added optional dependency takeoff-client, all imports still work without
dependency including the Titan Takeoff classes but just will fail on
initialisation if not pip installed takeoff-client
**Twitter**
@MeryemArik9
Thanks all :)
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
## Description:
The PR introduces 3 changes:
1. added `recursive` property to `O365BaseLoader`. (To keep the behavior
unchanged, by default is set to `False`). When `recursive=True`,
`_load_from_folder()` also recursively loads all nested folders.
2. added `folder_id` to SharePointLoader.(similar to (this
PR)[https://github.com/langchain-ai/langchain/pull/10780] ) This
provides an alternative to `folder_path` that doesn't seem to reliably
work.
3. when none of `document_ids`, `folder_id`, `folder_path` is provided,
the loader fetches documets from root folder. Combined with
`recursive=True` this provides an easy way of loading all compatible
documents from SharePoint.
The PR contains the same logic as [this stale
PR](https://github.com/langchain-ai/langchain/pull/10780) by
@WaleedAlfaris. I'd like to ask his blessing for moving forward with
this one.
## Issue:
- As described in https://github.com/langchain-ai/langchain/issues/19938
and https://github.com/langchain-ai/langchain/pull/10780 the sharepoint
loader often does not seem to work with folder_path.
- Recursive loading of subfolders is a missing functionality
## Dependecies: None
Twitter handle:
@martintriska1 @WRhetoric
This is my first PR here, please be gentle :-)
Please review @baskaryan
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
This PR updates OctoAIEndpoint LLM to subclass BaseOpenAI as OctoAI is
an OpenAI-compatible service. The documentation and tests have also been
updated.
**Description:** Adds ThirdAI NeuralDB retriever integration. NeuralDB
is a CPU-friendly and fine-tunable text retrieval engine. We previously
added a vector store integration but we think that it will be easier for
our customers if they can also find us under under
langchain-community/retrievers.
---------
Co-authored-by: kartikTAI <129414343+kartikTAI@users.noreply.github.com>
Co-authored-by: Kartik Sarangmath <kartik@thirdai.com>
- **Description:**
This PR adds a callback handler for UpTrain. It performs evaluations in
the RAG pipeline to check the quality of retrieved documents, generated
queries and responses.
- **Dependencies:**
- The UpTrainCallbackHandler requires the uptrain package
---------
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
- **Description:**Add Google Firestore Vector store docs
- **Issue:** NA
- **Dependencies:** NA
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
Description: fixes LangChainDeprecationWarning: The class
`langchain_community.embeddings.cohere.CohereEmbeddings` was deprecated
in langchain-community 0.0.30 and will be removed in 0.2.0. An updated
version of the class exists in the langchain-cohere package and should
be used instead. To use it run `pip install -U langchain-cohere` and
import as `from langchain_cohere import CohereEmbeddings`.
Dependencies : langchain_cohere
Twitter handle: @Mo_Noumaan
**Description:** Updates the documentation for Portkey and Langchain.
Also updates the notebook. The current documentation is fairly old and
is non-functional.
**Twitter handle:** @portkeyai
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description**: The pydantic schema fields are supposed to be
optional but the use of `...` makes them required. This causes a
`ValidationError` when running the example code. I replaced `...` with
`default=None` to make the fields optional as intended. I also
standardized the format for all fields.
- **Issue**: n/a
- **Dependencies**: none
- **Twitter handle**: https://twitter.com/m_atoms
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
spelling error fixed
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
Added the [FireCrawl](https://firecrawl.dev) document loader. Firecrawl
crawls and convert any website into LLM-ready data. It crawls all
accessible subpages and give you clean markdown for each.
- **Description:** Adds FireCrawl data loader
- **Dependencies:** firecrawl-py
- **Twitter handle:** @mendableai
ccing contributors: (@ericciarla @nickscamara)
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
- **Description:** Added cross-links for easy access of api
documentation of each output parser class from it's description page.
- **Issue:** related to issue #19969
Co-authored-by: Haris Ali <haris.ali@formulatrix.com>
avaliable -> available
- **Description:** fixed typo
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- make Tencent Cloud VectorDB support metadata filtering.
- implement delete function for Tencent Cloud VectorDB.
- support both Langchain Embedding model and Tencent Cloud VDB embedding
model.
- Tencent Cloud VectorDB support filter search keyword, compatible with
langchain filtering syntax.
- add Tencent Cloud VectorDB TranslationVisitor, now work with self
query retriever.
- more documentations.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
- **Description:** In this PR I fixed the links which points to the API
docs for classes in OpenAI functions and OpenAI tools section of output
parsers.
- **Issue:** It fixed the issue #19969
Co-authored-by: Haris Ali <haris.ali@formulatrix.com>
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** Langchain-Predibase integration was failing, because
it was not current with the Predibase SDK; in addition, Predibase
integration tests were instantiating the Langchain Community `Predibase`
class with one required argument (`model`) missing. This change updates
the Predibase SDK usage and fixes the integration tests.
- **Twitter handle:** `@alexsherstinsky`
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Last year Microsoft [changed the
name](https://learn.microsoft.com/en-us/azure/search/search-what-is-azure-search)
of Azure Cognitive Search to Azure AI Search. This PR updates the
Langchain Azure Retriever API and it's associated docs to reflect this
change. It may be confusing for users to see the name Cognitive here and
AI in the Microsoft documentation which is why this is needed. I've also
added a more detailed example to the Azure retriever doc page.
There are more places that need a similar update but I'm breaking it up
so the PRs are not too big 😄 Fixing my errors from the previous PR.
Twitter: @marlene_zw
Two new tests added to test backward compatibility in
`libs/community/tests/integration_tests/retrievers/test_azure_cognitive_search.py`
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- Added missed providers
- Added links, descriptions in related examples
- Formatted in a consistent format
Co-authored-by: Erick Friis <erick@langchain.dev>
Updated a page with existing document loaders with links to examples.
Fixed formatting of one example.
Co-authored-by: Erick Friis <erick@langchain.dev>
Issue: The `graph` code was moved into the `community` package a long
ago. But the related documentation is still in the
[use_cases](https://python.langchain.com/docs/use_cases/graph/integrations/diffbot_graphtransformer)
section and not in the `integrations`.
Changes:
- moved the `use_cases/graph/integrations` notebooks into the
`integrations/graphs`
- renamed files and changed titles to follow the consistent format
- redirected old page URLs to new URLs in `vercel.json` and in several
other pages
- added descriptions and links when necessary
- formatted into the consistent format
Should hopefully avoid weird broken link edge cases.
Relative links now trip up the Docusaurus broken link checker, so this
PR also removes them.
Also snuck in a small addition about asyncio
- **Description:** In order to use index and aindex in
libs/langchain/langchain/indexes/_api.py, I implemented delete method
and all async methods in opensearch_vector_search
- **Dependencies:** No changes
**Description:** Update of Cohere documentation (main provider page)
**Issue:** After addition of the Cohere partner package, the
documentation was out of date
**Dependencies:** None
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [x] **PR message**:
- **Description:** mention not-caching methods in CacheBackedEmbeddings
- **Issue:** n/a I almost created one until I read the code
- **Dependencies:** n/a
- **Twitter handle:** `tarsylia`
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
cohere: update imports and installs to langchain_cohere
---------
Co-authored-by: Harry M <127103098+harry-cohere@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** adds integration with [Layerup
Security](https://uselayerup.com). Docs can be found
[here](https://docs.uselayerup.com). Integrates directly with our Python
SDK.
**Dependencies:**
[LayerupSecurity](https://pypi.org/project/LayerupSecurity/)
**Note**: all methods for our product require a paid API key, so I only
included 1 test which checks for an invalid API key response. I have
tested extensively locally.
**Twitter handle**: [@layerup_](https://twitter.com/layerup_)
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** the layout of html pages can be variant based on the
bootstrap framework or the styles of the pages. So we need to have a
splitter to transform the html tags to a proper layout and then split
the html content based on the provided list of tags to determine its
html sections. We are using BS4 library along with xslt structure to
split the html content using an section aware approach.
- **Dependencies:** No new dependencies
- **Twitter handle:** @m_setayesh
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` from the root
of the package you've modified to check this locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc: https://python.langchain.com/docs/contributing/
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/docs/integrations` directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
[Dria](https://dria.co/) is a hub of public RAG models for developers to
both contribute and utilize a shared embedding lake. This PR adds a
retriever that can retrieve documents from Dria.
Description: Update `ChatZhipuAI` to support the latest `glm-4` model.
Issue: N/A
Dependencies: httpx, httpx-sse, PyJWT
The previous `ChatZhipuAI` implementation requires the `zhipuai`
package, and cannot call the latest GLM model. This is because
- The old version `zhipuai==1.*` doesn't support the latest model.
- `zhipuai==2.*` requires `pydantic V2`, which is incompatible with
'langchain-community'.
This re-implementation invokes the GLM model by sending HTTP requests to
[open.bigmodel.cn](https://open.bigmodel.cn/dev/api) via the `httpx`
package, and uses the `httpx-sse` package to handle stream events.
---------
Co-authored-by: zR <2448370773@qq.com>
**Description:** An additional `U` argument was added for the
instructions to install the pip packages for the MediaWiki Dump Document
loader which was leading to error in installing the package. Removing
the argument fixed the command to install.
**Issue:** #19820
**Dependencies:** No dependency change requierd
**Twitter handle:** [@vardhaman722](https://twitter.com/vardhaman722)
- **Description:** Support reranking based on cross encoder models
available from HuggingFace.
- Added `CrossEncoder` schema
- Implemented `HuggingFaceCrossEncoder` and
`SagemakerEndpointCrossEncoder`
- Implemented `CrossEncoderReranker` that performs similar functionality
to `CohereRerank`
- Added `cross-encoder-reranker.ipynb` to demonstrate how to use it.
Please let me know if anything else needs to be done to make it visible
on the table-of-contents navigation bar on the left, or on the card list
on [retrievers documentation
page](https://python.langchain.com/docs/integrations/retrievers).
- **Issue:** N/A
- **Dependencies:** None other than the existing ones.
---------
Co-authored-by: Kenny Choe <kchoe@amazon.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
### Description
This implementation adds functionality from the AlphaVantage API,
renowned for its comprehensive financial data. The class encapsulates
various methods, each dedicated to fetching specific types of financial
information from the API.
### Implemented Functions
- **`search_symbols`**:
- Searches the AlphaVantage API for financial symbols using the provided
keywords.
- **`_get_market_news_sentiment`**:
- Retrieves market news sentiment for a specified stock symbol from the
AlphaVantage API.
- **`_get_time_series_daily`**:
- Fetches daily time series data for a specific symbol from the
AlphaVantage API.
- **`_get_quote_endpoint`**:
- Obtains the latest price and volume information for a given symbol
from the AlphaVantage API.
- **`_get_time_series_weekly`**:
- Gathers weekly time series data for a particular symbol from the
AlphaVantage API.
- **`_get_top_gainers_losers`**:
- Provides details on top gainers, losers, and most actively traded
tickers in the US market from the AlphaVantage API.
### Issue:
- #11994
### Dependencies:
- 'requests' library for HTTP requests. (import requests)
- 'pytest' library for testing. (import pytest)
---------
Co-authored-by: Adam Badar <94140103+adam-badar@users.noreply.github.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Code written by following, the official documentation
of [Google Drive
Loader](https://python.langchain.com/docs/integrations/document_loaders/google_drive),
gives errors. I have opened an issue regarding this. See #14725. This is
a pull request for modifying the documentation to use an approach that
makes the code work. Basically, the change is that we need to always set
the GOOGLE_APPLICATION_CREDENTIALS env var to an emtpy string, rather
than only in case of RefreshError. Also, rewrote 2 paragraphs to make
the instructions more clear.
- **Issue:** See this related [issue #
14725](https://github.com/langchain-ai/langchain/issues/14725)
- **Dependencies:** NA
- **Tag maintainer:** @baskaryan
- **Twitter handle:** NA
Co-authored-by: Snehil <snehil@example.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "community: added support for llmsherpa library"
- [x] **Add tests and docs**:
1. Integration test:
'docs/docs/integrations/document_loaders/test_llmsherpa.py'.
2. an example notebook:
`docs/docs/integrations/document_loaders/llmsherpa.ipynb`.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
this pr also drops the community added action for checking broken links
in mdx. It does not work well for our use case, throwing errors for
local paths, plus the rest of the errors our in house solution had.
- **Description:** Haskell language support added in text_splitter
module
- **Dependencies:** No
- **Twitter handle:** @nisargtr
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:**
1. Fix the BiliBiliLoader that can receive cookie parameters, it
requires 3 other parameters to run. The change is backward compatible.
2. Add test;
3. Add example in docs
- **Issue:** [#14213]
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** A few grammatical changes to improve readability of the
LCEL .ipynb and tidy some null characters.
**Issue:** N/A
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
- [x] **PR title**: "community: Support streaming in Azure ML and few
naming changes"
- [x] **PR message**:
- **Description:** Added support for streaming for azureml_endpoint.
Also, renamed and AzureMLEndpointApiType.realtime to
AzureMLEndpointApiType.dedicated. Also, added new classes
CustomOpenAIChatContentFormatter and CustomOpenAIContentFormatter and
updated the classes LlamaChatContentFormatter and LlamaContentFormatter
to now show a deprecated warning message when instantiated.
---------
Co-authored-by: Sachin Paryani <saparan@microsoft.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Previous markdown code was not working as intended, new code should add
green box around the tip so it is highlighted
Co-authored-by: Hershenson, Isaac (Extern) <isaac.hershenson.extern@bayer04.de>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Add our solar chat models, available model choices:
* solar-1-mini-chat
* solar-1-mini-translate-enko
* solar-1-mini-translate-koen
More documents and pricing can be found at
https://console.upstage.ai/services/solar.
The references to our solar model can be found at
* https://arxiv.org/abs/2402.17032
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
This is a follow up to #18371. These are the changes:
- New **Azure AI Services** toolkit and tools to replace those of
**Azure Cognitive Services**.
- Updated documentation for Microsoft platform.
- The image analysis tool has been rewritten to use the new package
`azure-ai-vision-imageanalysis`, doing a proper replacement of
`azure-ai-vision`.
These changes:
- Update outdated naming from "Azure Cognitive Services" to "Azure AI
Services".
- Update documentation to use non-deprecated methods to create and use
agents.
- Removes need to depend on yanked python package (`azure-ai-vision`)
There is one new dependency that is needed as a replacement to
`azure-ai-vision`:
- `azure-ai-vision-imageanalysis`. This is optional and declared within
a function.
There is a new `azure_ai_services.ipynb` notebook showing usage; Changes
have been linted and formatted.
I am leaving the actions of adding deprecation notices and future
removal of Azure Cognitive Services up to the LangChain team, as I am
not sure what the current practice around this is.
---
If this PR makes it, my handle is @galo@mastodon.social
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
- **Description**: `bigdl-llm` library has been renamed to
[`ipex-llm`](https://github.com/intel-analytics/ipex-llm). This PR
migrates the `bigdl-llm` integration to `ipex-llm` .
- **Issue**: N/A. The original PR of `bigdl-llm` is
https://github.com/langchain-ai/langchain/pull/17953
- **Dependencies**: `ipex-llm` library
- **Contribution maintainer**: @shane-huang
Updated doc: docs/docs/integrations/llms/ipex_llm.ipynb
Updated test:
libs/community/tests/integration_tests/llms/test_ipex_llm.py
- **Description:** Add support for Intel Lab's [Visual Data Management
System (VDMS)](https://github.com/IntelLabs/vdms) as a vector store
- **Dependencies:** `vdms` library which requires protobuf = "4.24.2".
There is a conflict with dashvector in `langchain` package but conflict
is resolved in `community`.
- **Contribution maintainer:** [@cwlacewe](https://github.com/cwlacewe)
- **Added tests:**
libs/community/tests/integration_tests/vectorstores/test_vdms.py
- **Added docs:** docs/docs/integrations/vectorstores/vdms.ipynb
- **Added cookbook:** cookbook/multi_modal_RAG_vdms.ipynb
---------
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Updates Meilisearch vectorstore for compatibility
with v1.6 and above. Adds embedders settings and embedder_name which are
now required.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** I've made a fix to a ParseError call in the
XMLOutputParser documentation.
- **Issue:** None
- **Dependencies:** None
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Introduction
[Intel® Extension for
Transformers](https://github.com/intel/intel-extension-for-transformers)
is an innovative toolkit designed to accelerate GenAI/LLM everywhere
with the optimal performance of Transformer-based models on various
Intel platforms
Description
adding ITREX runtime embeddings using intel-extension-for-transformers.
added mdx documentation and example notebooks
added embedding import testing.
---------
Signed-off-by: yuwenzho <yuwen.zhou@intel.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Update Azure Document Intelligence implementation by
Microsoft team and RAG cookbook with Azure AI Search
---------
Co-authored-by: Lu Zhang (AI) <luzhan@microsoft.com>
Co-authored-by: Yateng Hong <yatengh@microsoft.com>
Co-authored-by: teethache <hongyateng2006@126.com>
Co-authored-by: Lu Zhang <44625949+luzhang06@users.noreply.github.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
- **Description:** Implemented try-except block for
`GCSDirectoryLoader`. Reason: Users processing large number of
unstructured files in a folder may experience many different errors. A
try-exception block is added to capture these errors. A new argument
`use_try_except=True` is added to enable *silent failure* so that error
caused by processing one file does not break the whole function.
- **Issue:** N/A
- **Dependencies:** no new dependencies
- **Twitter handle:** timothywong731
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** Adding oracle autonomous database document loader
integration. This will allow users to connect to oracle autonomous
database through connection string or TNS configuration.
https://www.oracle.com/autonomous-database/
- **Issue:** None
- **Dependencies:** oracledb python package
https://pypi.org/project/oracledb/
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
Unit test and doc are added.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:**
Update to correctly import Document class -
from langchain_core.documents import Document
- **Issue:**
Fixes the notebook and the hosted documentation
[here](https://python.langchain.com/docs/integrations/tools/apify)
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Fixing some issues for AzureCosmosDBSemanticCache
- Added the entry for "AzureCosmosDBSemanticCache" which was missing in
langchain/cache.py
- Added application name when creating the MongoClient for the
AzureCosmosDBVectorSearch, for tracking purposes.
@baskaryan, can you please review this PR, we need this to go in asap.
These are just small fixes which we found today in our testing.
Description: Added support for AI21 Labs model - Segmentation, as a Text
Splitter
Dependencies: ai21, langchain-text-splitter
Twitter handle: https://github.com/AI21Labs
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
### Prem SDK integration in LangChain
This PR adds the integration with [PremAI's](https://www.premai.io/)
prem-sdk with langchain. User can now access to deployed models
(llms/embeddings) and use it with langchain's ecosystem. This PR adds
the following:
### This PR adds the following:
- [x] Add chat support
- [X] Adding embedding support
- [X] writing integration tests
- [X] writing tests for chat
- [X] writing tests for embedding
- [X] writing unit tests
- [X] writing tests for chat
- [X] writing tests for embedding
- [X] Adding documentation
- [X] writing documentation for chat
- [X] writing documentation for embedding
- [X] run `make test`
- [X] run `make lint`, `make lint_diff`
- [X] Final checks (spell check, lint, format and overall testing)
---------
Co-authored-by: Anindyadeep Sannigrahi <anindyadeepsannigrahi@Anindyadeeps-MacBook-Pro.local>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
The existing default list of separators for the `RecursiveTextSplitter`
assumes spaces are word boundaries. Some languages [don't use spaces
between
words](https://en.wikipedia.org/wiki/Category:Writing_systems_without_word_boundaries)
(Chinese, Japanese, Thai, Burmese).
This PR extends the documentation to explain how to cater for those
languages by adding additional punctuation to the separators and
zero-width spaces which are used by some typesetters and will assist the
splitter to not split in words.
Ideally, **these separators could be a constant in the module** but for
now, defining them in the documentation is a start.
This PR aims to enhance the documentation for TiDB integration, driven
by feedback from our users. It provides detailed introductions to key
features, ensuring developers can fully leverage TiDB for AI application
development.
Corrected a broken link within the semantic-chunker.ipynb notebook,
ensuring that users can access the referenced resource.
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
- **Description:** Since the implicit `__call__` has been deprecated in
favor of `invoke`, the local_llms article also needed to be updated.
This article was my introduction to Lanchain, and as it was helpful in
getting me setup with running LLMs locally, it is nice to not have any
warnings when running the example code. With this change, the warnings
go away when running the example code.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** clarkerican
Description: adds support for langchain_cohere
---------
Co-authored-by: Harry M <127103098+harry-cohere@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:**
This PR adds [Dappier](https://dappier.com/) for the chat model. It
supports generate, async generate, and batch functionalities. We added
unit and integration tests as well as a notebook with more details about
our chat model.
**Dependencies:**
No extra dependencies are needed.
DuckDB has a cosine similarity function along list and array data types,
which can be used as a vector store.
- **Description:** The latest version of DuckDB features a cosine
similarity function, which can be used with its support for list or
array column types. This PR surfaces this functionality to langchain.
- **Dependencies:** duckdb 0.10.0
- **Twitter handle:** @igocrite
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Looking at tokens / page of our docs, we see a few outliers:
<img width="761" alt="image"
src="https://github.com/langchain-ai/langchain/assets/122662504/677aa2d6-0a29-45e4-882a-db2bbf46d02b">
It is due to non-rendering images in one case, and output spamming.
Clean these, along with other cases of excessing output spamming in
docs.
All get sucked into chat-langchain for retrieval.
Thank you for contributing to LangChain!
bilibili-api-python use https://github.com/Nemo2011/bilibili-api repo.
Change to the correct address.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
**Description:** Update module imports for Fireworks documentation
**Issue:** Module imports not present or in incorrect location
**Dependencies:** None
**Description:** Update import paths and move to lcel for llama.cpp
examples
**Issue:** Update import paths to reflect package refactoring and move
chains to LCEL in examples
**Dependencies:** None
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** Moving FireworksEmbeddings documentation to the
location docs/integration/text_embedding/ from langchain_fireworks/docs/
**Issue:** FireworksEmbeddings documentation was not in the correct
location
**Dependencies:** None
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:**
Currently, `CacheBackedEmbeddings` computes vectors for *all* uncached
documents before updating the store. This pull request updates the
embedding computation loop to compute embeddings in batches, updating
the store after each batch.
I noticed this when I tried `CacheBackedEmbeddings` on our 30k document
set and the cache directory hadn't appeared on disk after 30 minutes.
The motivation is to minimize compute/data loss when problems occur:
* If there is a transient embedding failure (e.g. a network outage at
the embedding endpoint triggers an exception), at least the completed
vectors are written to the store instead of being discarded.
* If there is an issue with the store (e.g. no write permissions), the
condition is detected early without computing (and discarding!) all the
vectors.
**Issue:**
Implements enhancement #18026.
**Testing:**
I was unable to run unit tests; details in [this
post](https://github.com/langchain-ai/langchain/discussions/15019#discussioncomment-8576684).
---------
Signed-off-by: chrispy <chrispy@synopsys.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
The `retryFailed` option will retry all failed links, once at a time
with the goal of not triggering bot protection
`microsoft.com` is now hard coded into the whitelist
Thank you for contributing to LangChain!
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- **PR message**:
- **Description:** Update the slack toolkit doc to use an agent that
support multiple inputs. Using ReAct agent will cause a ValidationError
when invoking the slack tools. This is because the agent return a string
like `'{"channel": "C05LDF54S21", "message": "Hello, world!"}'` but the
ReAct agent does not support multiple inputs.
- **Issue:** This is related to this
[Discussion#18083](https://github.com/langchain-ai/langchain/discussions/18083)
- **Dependencies:** No dependencies required
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description**:
this PR enable VectorStore autoconfiguration for Infinispan: if
metadatas are only of basic types, protobuf
config will be automatically generated for the user.
**Description**
This PR adds some missing details from the "Split by tokens" page in the
documentation. Specifically:
- The `.from_tiktoken_encoder()` class methods for both the
`CharacterTextSplitter` and `RecursiveCharacterTextSplitter` default to
the old `gpt-2` encoding. I've added a comment to suggest specifying
`model_name` or `encoding`
- The docs didn't mention that the `from_tiktoken_encoder()` class
method passes additional kwargs down to the constructor of the splitter.
I only discovered this by reading the source code
- Added an example of using the `.from_tiktoken_encoder()` class method
with `RecursiveCharacterTextSplitter` which is the recommended approach
for most scenarios above `CharacterTextSplitter`
- Added a warning that `TokenTextSplitter` can split characters which
have multiple tokens (e.g. 猫 has 3 cl100k_base tokens) between multiple
chunks which creates malformed Unicode strings and should not be used in
these situations.
Side note: I think the default argument of `gpt2` for
`.from_tiktoken_encoder()` should be updated?
**Twitter handle** anthonypjshaw
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** Fixes the import paths for the `FlashrankRerank`
example notebook.
**Issue:** #19139
**Dependencies:** None
**Twitter handle:** n/a
---------
Co-authored-by: Simon Stone <simon.stone@dartmouth.edu>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "Updating format of pip install in two files of
docs/cookbook"
- pip install is not reflecting properly in some of the files in
cookbook
- Example:
[docs/expression_language/cookbook/sql_db](https://python.langchain.com/docs/expression_language/cookbook/sql_db)
- [x] **PR message**: Updating format of pip install in two files of
docs/cookbook
- **Description:** a description of the change
- **Issue:** #19197
- Note - let's do squash merge for the PR
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
Thank you for contributing to LangChain!
- [x] **PR title**: "community: deprecate DocugamiLoader"
- [x] **PR message**: Deprecate the langchain_community and use the
docugami_langchain DocugamiLoader
---------
Co-authored-by: Kenzie Mihardja <kenzie28@cs.washington.edu>
I think that cell type for pip command may be 'code'.
Please check, thank you :)
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
Line `from langchain_openai import ChatOpenAI` is put twice in Get
Started / Serving with LangServe section.
Imports on lines 559 and 566 are identical
Co-authored-by: Vitalii <vitalii@localhost>
**Description:** Update stales link in Together AI documentation
**Issue:** Some links pointed to legacy webpages on the Together AI
website
**Dependencies:** None
**Lint and test**: `make format`, `make lint` were run
- [ ] **PR title**: "docs: correction in
"https://github.com/langchain-ai/langchain/blob/master/docs/docs/get_started/quickstart.mdx",
line 289".
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**:
- Corrected the spelling mistake
- #18981
Fixed Grammar in Considerations of Model I/O Concepts documentation page
- Update concepts.mdx
Page Link:
https://python.langchain.com/docs/modules/model_io/concepts#considerations
- **Description:** Fixed Grammar in Considerations of Model I/O
Documentation Page
- **Issue:** "to work well with the model are you using" # "to work well
with the model you are using"
- **Dependencies:** None
- **Twitter handle:** @Anubhav_Madhav
(https://twitter.com/Anubhav_Madhav)
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
## Description
This PR addresses a documentation issue in the
[Indexing](https://python.langchain.com/docs/modules/data_connection/indexing)
page. Specifically, it corrects the execution results of the Jupyter
notebook under the
[Source](https://python.langchain.com/docs/modules/data_connection/indexing#source)
section, which were broken as detailed below.
## Problem
The execution results following the statement, `This should delete the
old versions of documents associated with doggy.txt source and replace
them with the new versions.`, appear to be incorrect, as described
below.
### Current Behavior
- For some reason, the `index` function fails to add the new content of
`doggy.txt`. Although it deletes the document objects associated with
the `doggy.txt` source, it does not add the objects in
`changed_doggy_docs`. Consequently, the execution result displays
`num_added: 0`.
- This unexpected behavior also impacts the results of
`vectorstore.similarity_search("dog", k=30)`, showing only the contents
of `kitty.txt`. It appears as though the contents of `doggy.txt` have
been completely removed from the index:
```
Document(page_content='tty kitty', metadata={'source': 'kitty.txt'}),
Document(page_content='tty kitty ki', metadata={'source': 'kitty.txt'}),
Document(page_content='kitty kit', metadata={'source': 'kitty.txt'})]
```
### Expected Behavior
- The `index` function should successfully add the objects in
`changed_doggy_docs` after removing the old content of `doggy.txt`. The
anticipated execution result is `num_added: 2`.
- Subsequently, the modified content of `doggy.txt` should appear in the
results of `vectorstore.similarity_search("dog", k=30)` as follows:
```
[Document(page_content='woof woof', metadata={'source': 'doggy.txt'}),
Document(page_content='woof woof woof', metadata={'source': 'doggy.txt'}),
Document(page_content='tty kitty', metadata={'source': 'kitty.txt'}),
Document(page_content='tty kitty ki', metadata={'source': 'kitty.txt'}),
Document(page_content='kitty kit', metadata={'source': 'kitty.txt'})]
```
## Fix
I reran `docs/docs/modules/data_connection/indexing.ipynb` and have
included the diff in this PR.
Docs fix: replace column name search with source.
The Xata integration expects metadata column named "source".
The docs suggest the name "search", which if used, yields the following
error:
```
File "/usr/local/lib/python3.11/site-packages/langchain_community/vectorstores/xata.py", line 95, in _add_vectors
raise Exception(f"Error adding vectors to Xata: {r.status_code} {r}")
Exception: Error adding vectors to Xata: 400 {'errors': [{'status': 400, 'message': 'invalid record: column [source]: column not found'}]}
```
poetry can't reliably handle resolving the number of optional "extended
test" dependencies we have. If we instead just rely on pip to install
extended test deps in CI, this isn't an issue.
Fixed typo in line 661 - from 'mimimize' to 'minimize
- [ ] **PR message**:
- **Description:** Fixed typo in streaming document - change 'mimimize'
to 'minimize
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
**Description:**
Updates to LangChain-MongoDB documentation: updates to the Atlas vector
search index definition
**Issue:**
NA
**Dependencies:**
NA
**Twitter handle:**
iprakul
Add documentation notebook for `ElasticsearchRetriever`.
## Dependencies
- [ ] Release new `langchain-elasticsearch` version 0.2.0 that includes
`ElasticsearchRetriever`
**Description:** Refactor code of FAISS vectorcstore and update the
related documentation.
Details:
- replace `.format()` with f-strings for strings formatting;
- refactor definition of a filtering function to make code more readable
and more flexible;
- slightly improve efficiency of
`max_marginal_relevance_search_with_score_by_vector` method by removing
unnecessary looping over the same elements;
- slightly improve efficiency of `delete` method by using set data
structure for checking if the element was already deleted;
**Issue:** fix small inconsistency in the documentation (the old example
was incorrect and unappliable to faiss vectorstore)
**Dependencies:** basic langchain-community dependencies and `faiss`
(for CPU or for GPU)
**Twitter handle:** antonenkodev
Added deps:
- `@supabase/supabase-js` - for sending inserts
- `supabase` - dev dep, for generating types via cli
- `dotenv` for loading env vars
Added script:
- `yarn gen` - will auto generate the database schema types using the
supabase CLI. Not necessary for development, but is useful. Requires
authing with the supabase CLI (will error out w/ instructions if you're
not authed).
Added functionality:
- pulls users IP address (using a free endpoint: `https://api.ipify.org`
so we can filter out abuse down the line)
TODO:
- [x] add env vars to vercel
community: fix - change sparkllm spark_app_url to spark_api_url
- **Description:**
- Change the variable name from `sparkllm spark_app_url` to
`spark_api_url` in the community package.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:**
Variable name was `openai_poem` but it didn't pass in the `"prompt":
"poem"` config, so the examples were showing a joke being returned from
a variable called `*_poem`.
We could have gone one of two ways:
1. Updating the config line and the output line, or
2. Updating the variable name
The latter seemed simpler, so that's what I went with. But I'd be glad
to re-do this PR if you prefer the former.
Thanks for everything, y'all. You rock 🤘
**Issue:** N/A
**Dependencies:** N/A
**Twitter handle:** `conroywhitney`
This PR updates the on_tool_end handlers to return the raw output from the tool instead of casting it to a string.
This is technically a breaking change, though it's impact is expected to be somewhat minimal. It will fix behavior in `astream_events` as well.
Fixes the following issue #18760 raised by @eyurtsev
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
**Description:** Update callbacks documentation
**Issue:** Change some module imports and a method invocation to reflect
the current LangChainAPI
**Dependencies:** None
Created the `facebook` page from `facebook_faiss` and `facebook_chat`
pages. Added another Facebook integrations into this page.
Updated `discord` page.
- **Description:** Adding an optional parameter `linearization_config`
to the `AmazonTextractPDFLoader` so the caller can define how the output
will be linearized, instead of forcing a predefined set of linearization
configs. It will still have a default configuration as this will be an
optional parameter.
- **Issue:** #17457
- **Dependencies:** The same ones that already exist for
`AmazonTextractPDFLoader`
- **Twitter handle:** [@lvieirajr19](https://twitter.com/lvieirajr19)
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** Fix lists display issues in **Docs > Use Cases > Q&A
with RAG > Quickstart**.
In essence, this PR changes:
```markdown
Some paragraph.
- Item a.
- Item b.
```
to:
```markdown
Some paragraph.
- Item a.
- Item b.
```
There needs an extra empty line to make the list rendered properly.
FYI, the old version is displayed not properly as:
<img width="856" alt="image"
src="https://github.com/langchain-ai/langchain/assets/22856433/65202577-8ea2-47c6-b310-39bf42796fac">
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Co-authored-by: Bagatur <baskaryan@gmail.com>
## Add Passio Nutrition AI Food Search Tool to Community Package
### Description
We propose adding a new tool to the `community` package, enabling
integration with Passio Nutrition AI for food search functionality. This
tool will provide a simple interface for retrieving nutrition facts
through the Passio Nutrition AI API, simplifying user access to
nutrition data based on food search queries.
### Implementation Details
- **Class Structure:** Implement `NutritionAI`, extending `BaseTool`. It
includes an `_run` method that accepts a query string and, optionally, a
`CallbackManagerForToolRun`.
- **API Integration:** Use `NutritionAIAPI` for the API wrapper,
encapsulating all interactions with the Passio Nutrition AI and
providing a clean API interface.
- **Error Handling:** Implement comprehensive error handling for API
request failures.
### Expected Outcome
- **User Benefits:** Enable easy querying of nutrition facts from Passio
Nutrition AI, enhancing the utility of the `langchain_community` package
for nutrition-related projects.
- **Functionality:** Provide a straightforward method for integrating
nutrition information retrieval into users' applications.
### Dependencies
- `langchain_core` for base tooling support
- `pydantic` for data validation and settings management
- Consider `requests` or another HTTP client library if not covered by
`NutritionAIAPI`.
### Tests and Documentation
- **Unit Tests:** Include tests that mock network interactions to ensure
tool reliability without external API dependency.
- **Documentation:** Create an example notebook in
`docs/docs/integrations/tools/passio_nutrition_ai.ipynb` showing usage,
setup, and example queries.
### Contribution Guidelines Compliance
- Adhere to the project's linting and formatting standards (`make
format`, `make lint`, `make test`).
- Ensure compliance with LangChain's contribution guidelines,
particularly around dependency management and package modifications.
### Additional Notes
- Aim for the tool to be a lightweight, focused addition, not
introducing significant new dependencies or complexity.
- Potential future enhancements could include caching for common queries
to improve performance.
### Twitter Handle
- Here is our Passio AI [twitter handle](https://twitter.com/@passio_ai)
where we announce our products.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
**Description:** Minor update to Anthropic documentation
**Issue:** Not applicable
**Dependencies:** None
**Lint and test**: `make format` and `make lint` was done
Fixing a minor typo in the package name.
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: 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/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
- [ ] **PR title:** docs: Fix link to HF TEI in
text_embeddings_inference.ipynb
- [ ] **PR message:**
- **Description:** Fix the link to [Hugging Face Text Embeddings
Inference
(TEI)](https://huggingface.co/docs/text-embeddings-inference/index) in
text_embeddings_inference.ipynb
- **Issue:** Fix#18576
## Description
- Add [Friendli](https://friendli.ai/) integration for `Friendli` LLM
and `ChatFriendli` chat model.
- Unit tests and integration tests corresponding to this change are
added.
- Documentations corresponding to this change are added.
## Dependencies
- Optional dependency
[`friendli-client`](https://pypi.org/project/friendli-client/) package
is added only for those who use `Frienldi` or `ChatFriendli` model.
## Twitter handle
- https://twitter.com/friendliai
This pull request introduces initial support for the TiDB vector store.
The current version is basic, laying the foundation for the vector store
integration. While this implementation provides the essential features,
we plan to expand and improve the TiDB vector store support with
additional enhancements in future updates.
Upcoming Enhancements:
* Support for Vector Index Creation: To enhance the efficiency and
performance of the vector store.
* Support for max marginal relevance search.
* Customized Table Structure Support: Recognizing the need for
flexibility, we plan for more tailored and efficient data store
solutions.
Simple use case exmaple
```python
from typing import List, Tuple
from langchain.docstore.document import Document
from langchain_community.vectorstores import TiDBVectorStore
from langchain_openai import OpenAIEmbeddings
db = TiDBVectorStore.from_texts(
embedding=embeddings,
texts=['Andrew like eating oranges', 'Alexandra is from England', 'Ketanji Brown Jackson is a judge'],
table_name="tidb_vector_langchain",
connection_string=tidb_connection_url,
distance_strategy="cosine",
)
query = "Can you tell me about Alexandra?"
docs_with_score: List[Tuple[Document, float]] = db.similarity_search_with_score(query)
for doc, score in docs_with_score:
print("-" * 80)
print("Score: ", score)
print(doc.page_content)
print("-" * 80)
```
**Description:**
This integrates Infinispan as a vectorstore.
Infinispan is an open-source key-value data grid, it can work as single
node as well as distributed.
Vector search is supported since release 15.x
For more: [Infinispan Home](https://infinispan.org)
Integration tests are provided as well as a demo notebook
Follow up on https://github.com/langchain-ai/langchain/pull/17467.
- Update all references to the Elasticsearch classes to use the partners
package.
- Deprecate community classes.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** Update to the streaming tutorial notebook in the LCEL
documentation
**Issue:** Fixed an import and (minor) changes in documentation language
**Dependencies:** None
- **Description:** Fixed some typos and copy errors in the Beta
Structured Output docs
- **Issue:** N/A
- **Dependencies:** Docs only
- **Twitter handle:** @psvann
Co-authored-by: P.S. Vann <psvann@yahoo.com>
Description:
This pull request addresses two key improvements to the langchain
repository:
**Fix for Crash in Flight Search Interface**:
Previously, the code would crash when encountering a failure scenario in
the flight ticket search interface. This PR resolves this issue by
implementing a fix to handle such scenarios gracefully. Now, the code
handles failures in the flight search interface without crashing,
ensuring smoother operation.
**Documentation Update for Amadeus Toolkit**:
Prior to this update, examples provided in the documentation for the
Amadeus Toolkit were unable to run correctly due to outdated
information. This PR includes an update to the documentation, ensuring
that all examples can now be executed successfully. With this update,
users can effectively utilize the Amadeus Toolkit with accurate and
functioning examples.
These changes aim to enhance the reliability and usability of the
langchain repository by addressing issues related to error handling and
ensuring that documentation remains up-to-date and actionable.
Issue: https://github.com/langchain-ai/langchain/issues/17375
Twitter Handle: SingletonYxx
### Description
Changed the value specified for `content_key` in JSONLoader from a
single key to a value based on jq schema.
I created [similar
PR](https://github.com/langchain-ai/langchain/pull/11255) before, but it
has several conflicts because of the architectural change associated
stable version release, so I re-create this PR to fit new architecture.
### Why
For json data like the following, specify `.data[].attributes.message`
for page_content and `.data[].attributes.id` or
`.data[].attributes.attributes. tags`, etc., the `content_key` must also
parse the json structure.
<details>
<summary>sample json data</summary>
```json
{
"data": [
{
"attributes": {
"message": "message1",
"tags": [
"tag1"
]
},
"id": "1"
},
{
"attributes": {
"message": "message2",
"tags": [
"tag2"
]
},
"id": "2"
}
]
}
```
</details>
<details>
<summary>sample code</summary>
```python
def metadata_func(record: dict, metadata: dict) -> dict:
metadata["source"] = None
metadata["id"] = record.get("id")
metadata["tags"] = record["attributes"].get("tags")
return metadata
sample_file = "sample1.json"
loader = JSONLoader(
file_path=sample_file,
jq_schema=".data[]",
content_key=".attributes.message", ## content_key is parsable into jq schema
is_content_key_jq_parsable=True, ## this is added parameter
metadata_func=metadata_func
)
data = loader.load()
data
```
</details>
### Dependencies
none
### Twitter handle
[kzk_maeda](https://twitter.com/kzk_maeda)
**Description:**
modified the user_name to username to conform with the expected inputs
to TelegramChatApiLoader
**Issue:**
Current code fails in langchain-community 0.0.24
<loader = TelegramChatApiLoader(
chat_entity="<CHAT_URL>", # recommended to use Entity here
api_hash="<API HASH >",
api_id="<API_ID>",
user_name="", # needed only for caching the session.
)>
## **Description**
Migrate the `MongoDBChatMessageHistory` to the managed
`langchain-mongodb` partner-package
## **Dependencies**
None
## **Twitter handle**
@mongodb
## **tests and docs**
- [x] Migrate existing integration test
- [x ]~ Convert existing integration test to a unit test~ Creation is
out of scope for this ticket
- [x ] ~Considering delaying work until #17470 merges to leverage the
`MockCollection` object. ~
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
# Description
- **Description:** Adding MongoDB LLM Caching Layer abstraction
- **Issue:** N/A
- **Dependencies:** None
- **Twitter handle:** @mongodb
Checklist:
- [x] PR title: Please title your PR "package: description", where
"package" is whichever of langchain, community, core, experimental, etc.
is being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
- [x] PR Message (above)
- [x] Pass lint and test: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified to check that you're
passing lint and testing. See contribution guidelines for more
information on how to write/run tests, lint, etc:
https://python.langchain.com/docs/contributing/
- [ ] Add tests and docs: 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/docs/integrations` directory.
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @efriis, @eyurtsev, @hwchase17.
---------
Co-authored-by: Jib <jib@byblack.us>
- **Description:**
This PR fixes some issues in the Jupyter notebook for the VectorStore
"SAP HANA Cloud Vector Engine":
* Slight textual adaptations
* Fix of wrong column name VEC_META (was: VEC_METADATA)
- **Issue:** N/A
- **Dependencies:** no new dependecies added
- **Twitter handle:** @sapopensource
path to notebook:
`docs/docs/integrations/vectorstores/hanavector.ipynb`
## PR title
Docs: Updated callbacks/index.mdx adding example on runnable methods
## PR message
- **Description:** Updated callbacks/index.mdx adding an example on how
to pass callbacks to the runnable methods (invoke, batch, ...)
- **Issue:** #16379
- **Dependencies:** None
- **Description:** finishes adding the you.com functionality including:
- add async functions to utility and retriever
- add the You.com Tool
- add async testing for utility, retriever, and tool
- add a tool integration notebook page
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** @scottnath
Description:
This pull request introduces several enhancements for Azure Cosmos
Vector DB, primarily focused on improving caching and search
capabilities using Azure Cosmos MongoDB vCore Vector DB. Here's a
summary of the changes:
- **AzureCosmosDBSemanticCache**: Added a new cache implementation
called AzureCosmosDBSemanticCache, which utilizes Azure Cosmos MongoDB
vCore Vector DB for efficient caching of semantic data. Added
comprehensive test cases for AzureCosmosDBSemanticCache to ensure its
correctness and robustness. These tests cover various scenarios and edge
cases to validate the cache's behavior.
- **HNSW Vector Search**: Added HNSW vector search functionality in the
CosmosDB Vector Search module. This enhancement enables more efficient
and accurate vector searches by utilizing the HNSW (Hierarchical
Navigable Small World) algorithm. Added corresponding test cases to
validate the HNSW vector search functionality in both
AzureCosmosDBSemanticCache and AzureCosmosDBVectorSearch. These tests
ensure the correctness and performance of the HNSW search algorithm.
- **LLM Caching Notebook** - The notebook now includes a comprehensive
example showcasing the usage of the AzureCosmosDBSemanticCache. This
example highlights how the cache can be employed to efficiently store
and retrieve semantic data. Additionally, the example provides default
values for all parameters used within the AzureCosmosDBSemanticCache,
ensuring clarity and ease of understanding for users who are new to the
cache implementation.
@hwchase17,@baskaryan, @eyurtsev,
* **Description:** adds `LlamafileEmbeddings` class implementation for
generating embeddings using
[llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models.
Includes related unit tests and notebook showing example usage.
* **Issue:** N/A
* **Dependencies:** N/A
**Description:**
(a) Update to the module import path to reflect the splitting up of
langchain into separate packages
(b) Update to the documentation to include the new calling method
(invoke)
**Description:**
The URL of the data to index, specified to `WebBaseLoader` to import is
incorrect, causing the `langsmith_search` retriever to return a `404:
NOT_FOUND`.
Incorrect URL: https://docs.smith.langchain.com/overview
Correct URL: https://docs.smith.langchain.com
**Issue:**
This commit corrects the URL and prevents the LangServe Playground from
returning an error from its inability to use the retriever when
inquiring, "how can langsmith help with testing?".
**Dependencies:**
None.
**Twitter Handle:**
@ryanmeinzer
In this commit we update the documentation for Google El Carro for Oracle Workloads. We amend the documentation in the Google Providers page to use the correct name which is El Carro for Oracle Workloads. We also add changes to the document_loaders and memory pages to reflect changes we made in our repo.
- **Description**:
[`bigdl-llm`](https://github.com/intel-analytics/BigDL) is a library for
running LLM on Intel XPU (from Laptop to GPU to Cloud) using
INT4/FP4/INT8/FP8 with very low latency (for any PyTorch model). This PR
adds bigdl-llm integrations to langchain.
- **Issue**: NA
- **Dependencies**: `bigdl-llm` library
- **Contribution maintainer**: @shane-huang
Examples added:
- docs/docs/integrations/llms/bigdl.ipynb
Nvidia provider page is missing a Triton Inference Server package
reference.
Changes:
- added the Triton Inference Server reference
- copied the example notebook from the package into the doc files.
- added the Triton Inference Server description and links, the link to
the above example notebook
- formatted page to the consistent format
NOTE:
It seems that the [example
notebook](https://github.com/langchain-ai/langchain/blob/master/libs/partners/nvidia-trt/docs/llms.ipynb)
was originally created in wrong place. It should be in the LangChain
docs
[here](https://github.com/langchain-ai/langchain/tree/master/docs/docs/integrations/llms).
So, I've created a copy of this example. The original example is still
in the nvidia-trt package.
This PR migrates the existing MongoDBAtlasVectorSearch abstraction from
the `langchain_community` section to the partners package section of the
codebase.
- [x] Run the partner package script as advised in the partner-packages
documentation.
- [x] Add Unit Tests
- [x] Migrate Integration Tests
- [x] Refactor `MongoDBAtlasVectorStore` (autogenerated) to
`MongoDBAtlasVectorSearch`
- [x] ~Remove~ deprecate the old `langchain_community` VectorStore
references.
## Additional Callouts
- Implemented the `delete` method
- Included any missing async function implementations
- `amax_marginal_relevance_search_by_vector`
- `adelete`
- Added new Unit Tests that test for functionality of
`MongoDBVectorSearch` methods
- Removed [`del
res[self._embedding_key]`](e0c81e1cb0/libs/community/langchain_community/vectorstores/mongodb_atlas.py (L218))
in `_similarity_search_with_score` function as it would make the
`maximal_marginal_relevance` function fail otherwise. The `Document`
needs to store the embedding key in metadata to work.
Checklist:
- [x] PR title: Please title your PR "package: description", where
"package" is whichever of langchain, community, core, experimental, etc.
is being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
- [x] PR message
- [x] Pass lint and test: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified to check that you're
passing lint and testing. See contribution guidelines for more
information on how to write/run tests, lint, etc:
https://python.langchain.com/docs/contributing/
- [x] Add tests and docs: If you're adding a new integration, please
include
1. Existing tests supplied in docs/docs do not change. Updated
docstrings for new functions like `delete`
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory. (This already exists)
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
---------
Co-authored-by: Steven Silvester <steven.silvester@ieee.org>
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR adds links to some more free resources for people to get
acquainted with Langhchain without having to configure their system.
<!-- If no one reviews your PR within a few days, please @-mention one
of baskaryan, efriis, eyurtsev, hwchase17. -->
Co-authored-by: Filip Schouwenaars <filipsch@users.noreply.github.com>
**Description:**
In this PR, I am adding a `PolygonFinancials` tool, which can be used to
get financials data for a given ticker. The financials data is the
fundamental data that is found in income statements, balance sheets, and
cash flow statements of public US companies.
**Twitter**:
[@virattt](https://twitter.com/virattt)
Several URL-s were broken (in the yesterday PR). Like
[Integrations/platforms/google/Document
Loaders](https://python.langchain.com/docs/integrations/platforms/google#document-loaders)
page, Example link to "Document Loaders / Cloud SQL for PostgreSQL" and
most of the new example links in the Document Loaders, Vectorstores,
Memory sections.
- fixed URL-s (manually verified all example links)
- sorted sections in page to follow the "integrations/components" menu
item order.
- fixed several page titles to fix Navbar item order
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** Update to the list of partner packages in the list of
providers
**Issue:** Google & Nvidia had two entries each, both pointing to the
same page
**Dependencies:** None
- **Description:** A generic document loader adapter for SQLAlchemy on
top of LangChain's `SQLDatabaseLoader`.
- **Needed by:** https://github.com/crate-workbench/langchain/pull/1
- **Depends on:** GH-16655
- **Addressed to:** @baskaryan, @cbornet, @eyurtsev
Hi from CrateDB again,
in the same spirit like GH-16243 and GH-16244, this patch breaks out
another commit from https://github.com/crate-workbench/langchain/pull/1,
in order to reduce the size of this patch before submitting it, and to
separate concerns.
To accompany the SQLAlchemy adapter implementation, the patch includes
integration tests for both SQLite and PostgreSQL. Let me know if
corresponding utility resources should be added at different spots.
With kind regards,
Andreas.
### Software Tests
```console
docker compose --file libs/community/tests/integration_tests/document_loaders/docker-compose/postgresql.yml up
```
```console
cd libs/community
pip install psycopg2-binary
pytest -vvv tests/integration_tests -k sqldatabase
```
```
14 passed
```
---------
Co-authored-by: Andreas Motl <andreas.motl@crate.io>
**Description**: This PR adds support for using the [LLMLingua project
](https://github.com/microsoft/LLMLingua) especially the LongLLMLingua
(Enhancing Large Language Model Inference via Prompt Compression) as a
document compressor / transformer.
The LLMLingua project is an interesting project that can greatly improve
RAG system by compressing prompts and contexts while keeping their
semantic relevance.
**Issue**: https://github.com/microsoft/LLMLingua/issues/31
**Dependencies**: [llmlingua](https://pypi.org/project/llmlingua/)
@baskaryan
---------
Co-authored-by: Ayodeji Ayibiowu <ayodeji.ayibiowu@getinge.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
### Description
This PR moves the Elasticsearch classes to a partners package.
Note that we will not move (and later remove) `ElasticKnnSearch`. It
were previously deprecated.
`ElasticVectorSearch` is going to stay in the community package since it
is used quite a lot still.
Also note that I left the `ElasticsearchTranslator` for self query
untouched because it resides in main `langchain` package.
### Dependencies
There will be another PR that updates the notebooks (potentially pulling
them into the partners package) and templates and removes the classes
from the community package, see
https://github.com/langchain-ai/langchain/pull/17468
#### Open question
How to make the transition smooth for users? Do we move the import
aliases and require people to install `langchain-elasticsearch`? Or do
we remove the import aliases from the `langchain` package all together?
What has worked well for other partner packages?
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**
Adding different threshold types to the semantic chunker. I’ve had much
better and predictable performance when using standard deviations
instead of percentiles.
For all the documents I’ve tried, the distribution of distances look
similar to the above: positively skewed normal distribution. All skews
I’ve seen are less than 1 so that explains why standard deviations
perform well, but I’ve included IQR if anyone wants something more
robust.
Also, using the percentile method backwards, you can declare the number
of clusters and use semantic chunking to get an ‘optimal’ splitting.
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Description:** Update the example fiddler notebook to use community
path, instead of langchain.callback
**Dependencies:** None
**Twitter handle:** @bhalder
Co-authored-by: Barun Halder <barun@fiddler.ai>
I tried to configure MongoDBChatMessageHistory using the code from the
original documentation to store messages based on the passed session_id
in MongoDB. However, this configuration did not take effect, and the
session id in the database remained as 'test_session'. To resolve this
issue, I found that when configuring MongoDBChatMessageHistory, it is
necessary to set session_id=session_id instead of
session_id=test_session.
Issue: DOC: Ineffective Configuration of MongoDBChatMessageHistory for
Custom session_id Storage
previous code：
```python
chain_with_history = RunnableWithMessageHistory(
chain,
lambda session_id: MongoDBChatMessageHistory(
session_id="test_session",
connection_string="mongodb://root:Y181491117cLj@123.56.224.232:27017",
database_name="my_db",
collection_name="chat_histories",
),
input_messages_key="question",
history_messages_key="history",
)
config = {"configurable": {"session_id": "mmm"}}
chain_with_history.invoke({"question": "Hi! I'm bob"}, config)
```
Modified code:
```python
chain_with_history = RunnableWithMessageHistory(
chain,
lambda session_id: MongoDBChatMessageHistory(
session_id=session_id, # here is my modify code
connection_string="mongodb://root:Y181491117cLj@123.56.224.232:27017",
database_name="my_db",
collection_name="chat_histories",
),
input_messages_key="question",
history_messages_key="history",
)
config = {"configurable": {"session_id": "mmm"}}
chain_with_history.invoke({"question": "Hi! I'm bob"}, config)
```
Effect after modification (it works)：
**Description:** Update the azure search notebook to have more
descriptive comments, and an option to choose between OpenAI and
AzureOpenAI Embeddings
---------
Co-authored-by: Matt Gotteiner <[email protected]>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** Callback handler to integrate fiddler with langchain.
This PR adds the following -
1. `FiddlerCallbackHandler` implementation into langchain/community
2. Example notebook `fiddler.ipynb` for usage documentation
[Internal Tracker : FDL-14305]
**Issue:**
NA
**Dependencies:**
- Installation of langchain-community is unaffected.
- Usage of FiddlerCallbackHandler requires installation of latest
fiddler-client (2.5+)
**Twitter handle:** @fiddlerlabs @behalder
Co-authored-by: Barun Halder <barun@fiddler.ai>
- **Description:** Added the `return_sparql_query` feature to the
`GraphSparqlQAChain` class, allowing users to get the formatted SPARQL
query along with the chain's result.
- **Issue:** NA
- **Dependencies:** None
Note: I've ensured that the PR passes linting and testing by running
make format, make lint, and make test locally.
I have added a test for the integration (which relies on network access)
and I have added an example to the notebook showing its use.
https://github.com/langchain-ai/langchain/issues/17657
Thank you for contributing to LangChain!
Checklist:
- [ ] PR title: Please title your PR "package: description", where
"package" is whichever of langchain, community, core, experimental, etc.
is being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
- [ ] PR message: **Delete this entire template message** and replace it
with the following bulleted list
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] Pass lint and test: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified to check that you're
passing lint and testing. See contribution guidelines for more
information on how to write/run tests, lint, etc:
https://python.langchain.com/docs/contributing/
- [ ] Add tests and docs: 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/docs/integrations` directory.
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
**Description:** Initial pull request for Kinetica LLM wrapper
**Issue:** N/A
**Dependencies:** No new dependencies for unit tests. Integration tests
require gpudb, typeguard, and faker
**Twitter handle:** @chad_juliano
Note: There is another pull request for Kinetica vectorstore. Ultimately
we would like to make a partner package but we are starting with a
community contribution.
- **Description:** Update the Azure Search vector store notebook for the
latest version of the SDK
---------
Co-authored-by: Matt Gotteiner <[email protected]>
**Description:** Clean up Google product names and fix document loader
section
**Issue:** NA
**Dependencies:** None
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Update IBM watsonx.ai docs and add IBM as a provider
docs
- **Dependencies:**
[ibm-watsonx-ai](https://pypi.org/project/ibm-watsonx-ai/),
- **Tag maintainer:** :
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally. ✅
**Description:** This PR changes the module import path for SQLDatabase
in the documentation
**Issue:** Updates the documentation to reflect the move of integrations
to langchain-community
- **Description:** The URL in the tigris tutorial was htttps instead of
https, leading to a bad link.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** Speucey
In this pull request, we introduce the add_images method to the
SingleStoreDB vector store class, expanding its capabilities to handle
multi-modal embeddings seamlessly. This method facilitates the
incorporation of image data into the vector store by associating each
image's URI with corresponding document content, metadata, and either
pre-generated embeddings or embeddings computed using the embed_image
method of the provided embedding object.
the change includes integration tests, validating the behavior of the
add_images. Additionally, we provide a notebook showcasing the usage of
this new method.
---------
Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Issue in the API Reference:
If the `Classes` of `Functions` section is empty, it still shown in API
Reference. Here is an
[example](https://api.python.langchain.com/en/latest/core_api_reference.html#module-langchain_core.agents)
where `Functions` table is empty but still presented.
It happens only if this section has only the "private" members (with
names started with '_'). Those members are not shown but the whole
member section (empty) is shown.
This way we can document APIs in methods signature only where they are
checked by the typing system and we get them also in the param
description without having to duplicate in the docstrings (where they
are unchecked).
Twitter: @cbornet_
Description:
In this PR, I am adding a PolygonTickerNews Tool, which can be used to
get the latest news for a given ticker / stock.
Twitter handle: [@virattt](https://twitter.com/virattt)
**Description**: CogniSwitch focusses on making GenAI usage more
reliable. It abstracts out the complexity & decision making required for
tuning processing, storage & retrieval. Using simple APIs documents /
URLs can be processed into a Knowledge Graph that can then be used to
answer questions.
**Dependencies**: No dependencies. Just network calls & API key required
**Tag maintainer**: @hwchase17
**Twitter handle**: https://github.com/CogniSwitch
**Documentation**: Please check
`docs/docs/integrations/toolkits/cogniswitch.ipynb`
**Tests**: The usual tool & toolkits tests using `test_imports.py`
PR has passed linting and testing before this submission.
---------
Co-authored-by: Saicharan Sridhara <145636106+saiCogniswitch@users.noreply.github.com>
Hi, I'm from the LanceDB team.
Improves LanceDB integration by making it easier to use - now you aren't
required to create tables manually and pass them in the constructor,
although that is still backward compatible.
Bug fix - pandas was being used even though it's not a dependency for
LanceDB or langchain
PS - this issue was raised a few months ago but lost traction. It is a
feature improvement for our users kindly review this , Thanks !
This PR replaces the imports of the Astra DB vector store with the
newly-released partner package, in compliance with the deprecation
notice now attached to the community "legacy" store.
- **Description:** Update documentation for RunnableWithMessageHistory
- **Issue:** https://github.com/langchain-ai/langchain/issues/16642
I don't have access to an Anthropic API key so I updated things to use
OpenAI. Let me know if you'd prefer another provider.
**Description:** This PR introduces a new "Astra DB" Partner Package.
So far only the vector store class is _duplicated_ there, all others
following once this is validated and established.
Along with the move to separate package, incidentally, the class name
will change `AstraDB` => `AstraDBVectorStore`.
The strategy has been to duplicate the module (with prospected removal
from community at LangChain 0.2). Until then, the code will be kept in
sync with minimal, known differences (there is a makefile target to
automate drift control. Out of convenience with this check, the
community package has a class `AstraDBVectorStore` aliased to `AstraDB`
at the end of the module).
With this PR several bugfixes and improvement come to the vector store,
as well as a reshuffling of the doc pages/notebooks (Astra and
Cassandra) to align with the move to a separate package.
**Dependencies:** A brand new pyproject.toml in the new package, no
changes otherwise.
**Twitter handle:** `@rsprrs`
---------
Co-authored-by: Christophe Bornet <cbornet@hotmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
A few minor changes for contribution:
1) Updating link to say "Contributing" rather than "Developer's guide"
2) Minor changes after going through the contributing documentation
page.
This PR is adding support for NVIDIA NeMo embeddings issue #16095.
---------
Co-authored-by: Praveen Nakshatrala <pnakshatrala@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
1. integrate with
[`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md)
2. update `langchain.llms`
3. add a new doc for [Yuan2.0
integration](docs/docs/integrations/llms/yuan2.ipynb)
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
This pull request introduces support for various Approximate Nearest
Neighbor (ANN) vector index algorithms in the VectorStore class,
starting from version 8.5 of SingleStore DB. Leveraging this enhancement
enables users to harness the power of vector indexing, significantly
boosting search speed, particularly when handling large sets of vectors.
---------
Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:**
1. Added _clear_edges()_ and _get_number_of_nodes()_ functions in
NetworkxEntityGraph class.
2. Added the above two function in graph_networkx_qa.ipynb
documentation.
Thank you for contributing to LangChain!
Checklist:
- **PR title**: docs: add & update docs for Oracle Cloud Infrastructure
(OCI) integrations
- **Description**: adding and updating documentation for two
integrations - OCI Generative AI & OCI Data Science
(1) adding integration page for OCI Generative AI embeddings (@baskaryan
request,
docs/docs/integrations/text_embedding/oci_generative_ai.ipynb)
(2) updating integration page for OCI Generative AI llms
(docs/docs/integrations/llms/oci_generative_ai.ipynb)
(3) adding platform documentation for OCI (@baskaryan request,
docs/docs/integrations/platforms/oci.mdx). this combines the
integrations of OCI Generative AI & OCI Data Science
(4) if possible, requesting to be added to 'Featured Community
Providers' so supplying a modified
docs/docs/integrations/platforms/index.mdx to reflect the addition
- **Issue:** none
- **Dependencies:** no new dependencies
- **Twitter handle:**
---------
Co-authored-by: MING KANG <ming.kang@oracle.com>
1. integrate chat models with
[`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md)
2. add a new doc for [Yuan2.0
integration](docs/docs/integrations/llms/yuan2.ipynb)
Yuan2.0 is a new generation Fundamental Large Language Model developed
by IEIT System. We have published all three models, Yuan 2.0-102B, Yuan
2.0-51B, and Yuan 2.0-2B.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
## Description
I am submitting this for a school project as part of a team of 5. Other
team members are @LeilaChr, @maazh10, @Megabear137, @jelalalamy. This PR
also has contributions from community members @Harrolee and @Mario928.
Initial context is in the issue we opened (#11229).
This pull request adds:
- Generic framework for expanding the languages that `LanguageParser`
can handle, using the
[tree-sitter](https://github.com/tree-sitter/py-tree-sitter#py-tree-sitter)
parsing library and existing language-specific parsers written for it
- Support for the following additional languages in `LanguageParser`:
- C
- C++
- C#
- Go
- Java (contributed by @Mario928
https://github.com/ThatsJustCheesy/langchain/pull/2)
- Kotlin
- Lua
- Perl
- Ruby
- Rust
- Scala
- TypeScript (contributed by @Harrolee
https://github.com/ThatsJustCheesy/langchain/pull/1)
Here is the [design
document](https://docs.google.com/document/d/17dB14cKCWAaiTeSeBtxHpoVPGKrsPye8W0o_WClz2kk)
if curious, but no need to read it.
## Issues
- Closes#11229
- Closes#10996
- Closes#8405
## Dependencies
`tree_sitter` and `tree_sitter_languages` on PyPI. We have tried to add
these as optional dependencies.
## Documentation
We have updated the list of supported languages, and also added a
section to `source_code.ipynb` detailing how to add support for
additional languages using our framework.
## Maintainer
- @hwchase17 (previously reviewed
https://github.com/langchain-ai/langchain/pull/6486)
Thanks!!
## Git commits
We will gladly squash any/all of our commits (esp merge commits) if
necessary. Let us know if this is desirable, or if you will be
squash-merging anyway.
<!-- 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
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Please make sure your PR is passing linting and testing before
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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: Maaz Hashmi <mhashmi373@gmail.com>
Co-authored-by: LeilaChr <87657694+LeilaChr@users.noreply.github.com>
Co-authored-by: Jeremy La <jeremylai511@gmail.com>
Co-authored-by: Megabear137 <zubair.alnoor27@gmail.com>
Co-authored-by: Lee Harrold <lhharrold@sep.com>
Co-authored-by: Mario928 <88029051+Mario928@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
- **Description:** Pebblo opensource project enables developers to
safely load data to their Gen AI apps. It identifies semantic topics and
entities found in the loaded data and summarizes them in a
developer-friendly report.
- **Dependencies:** none
- **Twitter handle:** srics
@hwchase17
**Description**: This PR adds a chain for Amazon Neptune graph database
RDF format. It complements the existing Neptune Cypher chain. The PR
also includes a Neptune RDF graph class to connect to, introspect, and
query a Neptune RDF graph database from the chain. A sample notebook is
provided under docs that demonstrates the overall effect: invoking the
chain to make natural language queries against Neptune using an LLM.
**Issue**: This is a new feature
**Dependencies**: The RDF graph class depends on the AWS boto3 library
if using IAM authentication to connect to the Neptune database.
---------
Co-authored-by: Piyush Jain <piyushjain@duck.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** This PR adds support for
[flashrank](https://github.com/PrithivirajDamodaran/FlashRank) for
reranking as alternative to Cohere.
I'm not sure `libs/langchain` is the right place for this change. At
first, I wanted to put it under `libs/community`. All the compressors
were under `libs/langchain/retrievers/document_compressors` though. Hope
this makes sense!
- **Description:** This adds a delete method so that rocksetdb can be
used with `RecordManager`.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** `@_morgan_adams_`
---------
Co-authored-by: Rockset API Bot <admin@rockset.io>
- Reordered sections
- Applied consistent formatting
- Fixed headers (there were 2 H1 headers; this breaks CoT)
- Added `Settings` header and moved all related sections under it
Description: Updated doc for integrations/chat/anthropic_functions with
new functions: invoke. Changed structure of the document to match the
required one.
Issue: https://github.com/langchain-ai/langchain/issues/15664
Dependencies: None
Twitter handle: None
---------
Co-authored-by: NaveenMaltesh <naveen@onmeta.in>
- **Description:** Adds the document loader for [AWS
Athena](https://aws.amazon.com/athena/), a serverless and interactive
analytics service.
- **Dependencies:** Added boto3 as a dependency
This PR updates the `TF-IDF.ipynb` documentation to reflect the new
import path for TFIDFRetriever in the langchain-community package. The
previous path, `from langchain.retrievers import TFIDFRetriever`, has
been updated to `from langchain_community.retrievers import
TFIDFRetriever` to align with the latest changes in the langchain
library.
according to https://youtu.be/rZus0JtRqXE?si=aFo1JTDnu5kSEiEN&t=678 by
@efriis
- **Description:** Seems the requirements for tool names have changed
and spaces are no longer allowed. Changed the tool name from Google
Search to google_search in the notebook
- **Issue:** n/a
- **Dependencies:** none
- **Twitter handle:** @mesirii
**Description**
Make some functions work with Milvus:
1. get_ids: Get primary keys by field in the metadata
2. delete: Delete one or more entities by ids
3. upsert: Update/Insert one or more entities
**Issue**
None
**Dependencies**
None
**Tag maintainer:**
@hwchase17
**Twitter handle:**
None
---------
Co-authored-by: HoaNQ9 <hoanq.1811@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
## Summary
This PR upgrades LangChain's Ruff configuration in preparation for
Ruff's v0.2.0 release. (The changes are compatible with Ruff v0.1.5,
which LangChain uses today.) Specifically, we're now warning when
linter-only options are specified under `[tool.ruff]` instead of
`[tool.ruff.lint]`.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Issue:** Issue with model argument support (been there for a while
actually):
- Non-specially-handled arguments like temperature don't work when
passed through constructor.
- Such arguments DO work quite well with `bind`, but also do not abide
by field requirements.
- Since initial push, server-side error messages have gotten better and
v0.0.2 raises better exceptions. So maybe it's better to let server-side
handle such issues?
- **Description:**
- Removed ChatNVIDIA's argument fields in favor of
`model_kwargs`/`model_kws` arguments which aggregates constructor kwargs
(from constructor pathway) and merges them with call kwargs (bind
pathway).
- Shuffled a few functions from `_NVIDIAClient` to `ChatNVIDIA` to
streamline construction for future integrations.
- Minor/Optional: Old services didn't have stop support, so client-side
stopping was implemented. Now do both.
- **Any Breaking Changes:** Minor breaking changes if you strongly rely
on chat_model.temperature, etc. This is captured by
chat_model.model_kwargs.
PR passes tests and example notebooks and example testing. Still gonna
chat with some people, so leaving as draft for now.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
The Integrations `Toolkits` menu was named as [`Agents and
toolkits`](https://python.langchain.com/docs/integrations/toolkits).
This name has a historical reason that is not correct anymore. Now this
menu is all about community `Toolkits`. There is a separate menu for
[Agents](https://python.langchain.com/docs/modules/agents/). Also Agents
are officially not part of Integrations (Community package) but part of
LangChain package.
<!-- Thank you for contributing to LangChain!
Please title your PR "<package>: <description>", where <package> is
whichever of langchain, community, core, experimental, etc. is being
modified.
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,
- **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` from the root
of the package you've modified to check this locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc: https://python.langchain.com/docs/contributing/
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/docs/integrations` directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
- **Description: changes to you.com files**
- general cleanup
- adds community/utilities/you.py, moving bulk of code from retriever ->
utility
- removes `snippet` as endpoint
- adds `news` as endpoint
- adds more tests
<s>**Description: update community MAKE file**
- adds `integration_tests`
- adds `coverage`</s>
- **Issue:** the issue # it fixes if applicable,
- [For New Contributors: Update Integration
Documentation](https://github.com/langchain-ai/langchain/issues/15664#issuecomment-1920099868)
- **Dependencies:** n/a
- **Twitter handle:** @scottnath
- **Mastodon handle:** scottnath@mastodon.social
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** This adds a recursive json splitter class to the
existing text_splitters as well as unit tests
- **Issue:** splitting text from structured data can cause issues if you
have a large nested json object and you split it as regular text you may
end up losing the structure of the json. To mitigate against this you
can split the nested json into large chunks and overlap them, but this
causes unnecessary text processing and there will still be times where
the nested json is so big that the chunks get separated from the parent
keys.
As an example you wouldn't want the following to be split in half:
```shell
{'val0': 'DFWeNdWhapbR',
'val1': {'val10': 'QdJo',
'val11': 'FWSDVFHClW',
'val12': 'bkVnXMMlTiQh',
'val13': 'tdDMKRrOY',
'val14': 'zybPALvL',
'val15': 'JMzGMNH',
'val16': {'val160': 'qLuLKusFw',
'val161': 'DGuotLh',
'val162': 'KztlcSBropT',
-----------------------------------------------------------------------split-----
'val163': 'YlHHDrN',
'val164': 'CtzsxlGBZKf',
'val165': 'bXzhcrWLmBFp',
'val166': 'zZAqC',
'val167': 'ZtyWno',
'val168': 'nQQZRsLnaBhb',
'val169': 'gSpMbJwA'},
'val17': 'JhgiyF',
'val18': 'aJaqjUSFFrI',
'val19': 'glqNSvoyxdg'}}
```
Any llm processing the second chunk of text may not have the context of
val1, and val16 reducing accuracy. Embeddings will also lack this
context and this makes retrieval less accurate.
Instead you want it to be split into chunks that retain the json
structure.
```shell
{'val0': 'DFWeNdWhapbR',
'val1': {'val10': 'QdJo',
'val11': 'FWSDVFHClW',
'val12': 'bkVnXMMlTiQh',
'val13': 'tdDMKRrOY',
'val14': 'zybPALvL',
'val15': 'JMzGMNH',
'val16': {'val160': 'qLuLKusFw',
'val161': 'DGuotLh',
'val162': 'KztlcSBropT',
'val163': 'YlHHDrN',
'val164': 'CtzsxlGBZKf'}}}
```
and
```shell
{'val1':{'val16':{
'val165': 'bXzhcrWLmBFp',
'val166': 'zZAqC',
'val167': 'ZtyWno',
'val168': 'nQQZRsLnaBhb',
'val169': 'gSpMbJwA'},
'val17': 'JhgiyF',
'val18': 'aJaqjUSFFrI',
'val19': 'glqNSvoyxdg'}}
```
This recursive json text splitter does this. Values that contain a list
can be converted to dict first by using split(... convert_lists=True)
otherwise long lists will not be split and you may end up with chunks
larger than the max chunk.
In my testing large json objects could be split into small chunks with
✅ Increased question answering accuracy
✅ The ability to split into smaller chunks meant retrieval queries can
use fewer tokens
- **Dependencies:** json import added to text_splitter.py, and random
added to the unit test
- **Twitter handle:** @joelsprunger
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Description:**: Fix 422 error in example with LangServe client code
httpx.HTTPStatusError: Client error '422 Unprocessable Entity' for url
'http://localhost:8000/agent/invoke'
- **Description:** Fixes in the Ontotext GraphDB Graph and QA Chain
related to the error handling in case of invalid SPARQL queries, for
which `prepareQuery` doesn't throw an exception, but the server returns
400 and the query is indeed invalid
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** @OntotextGraphDB
Ran
```python
import glob
import re
def update_prompt(x):
return re.sub(
r"(?P<start>\b)PromptTemplate\(template=(?P<template>.*), input_variables=(?:.*)\)",
"\g<start>PromptTemplate.from_template(\g<template>)",
x
)
for fn in glob.glob("docs/**/*", recursive=True):
try:
content = open(fn).readlines()
except:
continue
content = [update_prompt(l) for l in content]
with open(fn, "w") as f:
f.write("".join(content))
```
Replace this entire comment with:
- **Description:** Added missing link for Quickstart in Model IO
documentation,
- **Issue:** N/A,
- **Dependencies:** N/A,
- **Twitter handle:** N/A
<!--
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Several notebooks have Title != file name. That results in corrupted
sorting in Navbar (ToC).
- Fixed titles and file names.
- Changed text formats to the consistent form
- Redirected renamed files in the `Vercel.json`
This PR is opinionated.
- Moved `Embedding models` item to place after `LLMs` and `Chat model`,
so all items with models are together.
- Renamed `Text embedding models` to `Embedding models`. Now, it is
shorter and easier to read. `Text` is obvious from context. The same as
the `Text LLMs` vs. `LLMs` (we also have multi-modal LLMs).
