**Description**: PR fixes some formatting errors in deprecation message
in the `langchain_community.vectorstores.pgvector` module, where it was
missing spaces between a few words, and one word was misspelled.
**Issue**: n/a
**Dependencies**: n/a
Signed-off-by: mpeveler@timescale.com
Co-authored-by: Erick Friis <erick@langchain.dev>
PR message:
Description:
This PR refactors the Arxiv API wrapper by extracting the Arxiv search
logic into a helper function (_fetch_results) to reduce code duplication
and improve maintainability. The helper function is used in methods like
get_summaries_as_docs, run, and lazy_load, streamlining the code and
making it easier to maintain in the future.
Issue:
This is a minor refactor, so no specific issue is being fixed.
Dependencies:
No new dependencies are introduced with this change.
Add tests and docs:
No new integrations were added, so no additional tests or docs are
necessary for this PR.
Lint and test:
I have run make format, make lint, and make test to ensure all checks
pass successfully.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR updates the integration with OCI data science model deployment
service.
- Update LLM to support streaming and async calls.
- Added chat model.
- Updated tests and docs.
- Updated `libs/community/scripts/check_pydantic.sh` since the use of
`@pre_init` is removed from existing integration.
- Updated `libs/community/extended_testing_deps.txt` as this integration
requires `langchain_openai`.
---------
Co-authored-by: MING KANG <ming.kang@oracle.com>
Co-authored-by: Dmitrii Cherkasov <dmitrii.cherkasov@oracle.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR updates the Firecrawl Document Loader to use the recently
released V1 API of Firecrawl.
**Key Updates:**
**Firecrawl V1 Integration:** Updated the document loader to leverage
the new Firecrawl V1 API for improved performance, reliability, and
developer experience.
**Map Functionality Added:** Introduced the map mode for more flexible
document loading options.
These updates enhance the integration and provide access to the latest
features of Firecrawl.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
Updated
- [ ] **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!
twitter: @MaxHTran
- [ ] **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.
Not needed due to small change
- [ ] **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.
---------
Co-authored-by: Max Tran <maxtra@amazon.com>
**Description:** Deprecated version of Chroma >=0.5.5 <0.5.12 due to a
serious correctness issue that caused some embeddings for deployments
with multiple collections to be lost (read more on the issue in Chroma
repo)
**Issue:** chroma-core/chroma#2922 (fixed by chroma-core/chroma##2923
and released in
[0.5.13](https://github.com/chroma-core/chroma/releases/tag/0.5.13))
**Dependencies:** N/A
**Twitter handle:** `@t_azarov`
Starting with Clickhouse version 24.8, a different type of configuration
has been introduced in the vectorized data ingestion, and if this
configuration occurs, an error occurs when generating the table. As can
be seen below:
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**:
this PR enable VectorStore TLS and authentication (digest, basic) with
HTTP/2 for Infinispan server.
Based on httpx.
Added docker-compose facilities for testing
Added documentation
**Dependencies:**
requires `pip install httpx[http2]` if HTTP2 is needed
**Twitter handle:**
https://twitter.com/infinispan
**Description:** this PR adds a set of methods to deal with metadata
associated to the vector store entries. These, while essential to the
Graph-related extension of the `Cassandra` vector store, are also useful
in themselves. These are (all come in their sync+async versions):
- `[a]delete_by_metadata_filter`
- `[a]replace_metadata`
- `[a]get_by_document_id`
- `[a]metadata_search`
Additionally, a `[a]similarity_search_with_embedding_id_by_vector`
method is introduced to better serve the store's internal working (esp.
related to reranking logic).
**Issue:** no issue number, but now all Document's returned bear their
`.id` consistently (as a consequence of a slight refactoring in how the
raw entries read from DB are made back into `Document` instances).
**Dependencies:** (no new deps: packaging comes through langchain-core
already; `cassio` is now required to be version 0.1.10+)
**Add tests and docs**
Added integration tests for the relevant newly-introduced methods.
(Docs will be updated in a separate PR).
**Lint and test** Lint and (updated) test all pass.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Add timeout at client side for UCFunctionToolkit and add retry logic.
Users could specify environment variable
`UC_TOOL_CLIENT_EXECUTION_TIMEOUT` to increase the timeout value for
retrying to get the execution response if the status is pending. Default
timeout value is 120s.
- [ ] **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.
Tested in Databricks:
<img width="1200" alt="image"
src="https://github.com/user-attachments/assets/54ab5dfc-5e57-4941-b7d9-bfe3f8ad3f62">
- [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, ccurme, vbarda, hwchase17.
---------
Signed-off-by: serena-ruan <serena.rxy@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Example updated for vectorstore ChromaDB.
If we want to apply multiple filters then ChromaDB supports filters like
this:
Reference: [ChromaDB
filters](https://cookbook.chromadb.dev/core/filters/)
Thank you.
- [ ] **PR title**: docs: fix typo in SQLStore import path
- [ ] **PR message**:
- **Description:** This PR corrects a typo in the docstrings for the
class SQLStore(BaseStore[str, bytes]). The import path in the docstring
currently reads from langchain_rag.storage import SQLStore, which should
be changed to langchain_community.storage import SQLStore. This typo is
also reflected in the official documentation.
- **Issue:** N/A
- **Dependencies:** None
- **Twitter handle:** N/A
Co-authored-by: Erick Friis <erick@langchain.dev>
## Description
This PR fixes the context loss issue in `AsyncCallbackManager`,
specifically in `on_llm_start` and `on_chat_model_start` methods. It
properly honors the `run_inline` attribute of callback handlers,
preventing race conditions and ordering issues.
Key changes:
1. Separate handlers into inline and non-inline groups.
2. Execute inline handlers sequentially for each prompt.
3. Execute non-inline handlers concurrently across all prompts.
4. Preserve context for stateful handlers.
5. Maintain performance benefits for non-inline handlers.
**These changes are implemented in `AsyncCallbackManager` rather than
`ahandle_event` because the issue occurs at the prompt and message_list
levels, not within individual events.**
## Testing
- Test case implemented in #26857 now passes, verifying execution order
for inline handlers.
## Related Issues
- Fixes issue discussed in #23909
## Dependencies
No new dependencies are required.
---
@eyurtsev: This PR implements the discussed changes to respect
`run_inline` in `AsyncCallbackManager`. Please review and advise on any
needed changes.
Twitter handle: @parambharat
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Added `**kwargs` parameters to the `index` and `aindex` functions in
`libs/core/langchain_core/indexing/api.py`. This allows users to pass
additional arguments to the `add_documents` and `aadd_documents`
methods, enabling the specification of a custom `vector_field`. For
example, users can now use `vector_field="embedding"` when indexing
documents in `OpenSearchVectorStore`
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
This commit addresses a typographical error in the documentation for the
async astream_events method. The word 'evens' was incorrectly used in
the introductory sentence for the reference table, which could lead to
confusion for users.\n\n### Changes Made:\n- Corrected 'Below is a table
that illustrates some evens that might be emitted by various chains.' to
'Below is a table that illustrates some events that might be emitted by
various chains.'\n\nThis enhancement improves the clarity of the
documentation and ensures accurate terminology is used throughout the
reference material.\n\nIssue Reference: #27107
Thank you for contributing to LangChain!
**Description:** Box AI can return responses, but it can also be
configured to return citations. This change allows the developer to
decide if they want the answer, the citations, or both. Regardless of
the combination, this is returned as a single List[Document] object.
**Dependencies:** Updated to the latest Box Python SDK, v1.5.1
**Twitter handle:** BoxPlatform
- [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, ccurme, vbarda, hwchase17.
Co-authored-by: Erick Friis <erick@langchain.dev>
Given the current erroring behavior, every time we've moved a kwarg from
model_kwargs and made it its own field that was a breaking change.
Updating this behavior to support the old instantiations /
serializations.
Assuming build_extra_kwargs was not something that itself is being used
externally and needs to be kept backwards compatible
This adds support for inject tool args that are arbitrary types when
used with pydantic 2.
We'll need to add similar logic on the v1 path, and potentially mirror
the config from the original model when we're doing the subset.
- **Description:** prevent index function to re-index entire source
document even if nothing has changed.
- **Issue:** #22135
I worked on a solution to this issue that is a compromise between being
cheap and being fast.
In the previous code, when batch_size is greater than the number of docs
from a certain source almost the entire source is deleted (all documents
from that source except for the documents in the first batch)
My solution deletes documents from vector store and record manager only
if at least one document has changed for that source.
Hope this can help!
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
* [chore]: Agent Observation should be casted to string to avoid errors
* Merge branch 'master' into fix_observation_type_streaming
* [chore]: Using Json.dumps
* [chore]: Exact same logic as when casting agent oobservation to string
template_format is an init argument on ChatPromptTemplate but not an
attribute on the object so was getting shoved into
StructuredPrompt.structured_ouptut_kwargs
These allow converting linked documents (such as those used with
GraphVectorStore) to networkx for rendering and/or in-memory graph
algorithms such as community detection.
This PR updates the documentation examples that used
RunnableWithMessageHistory to show how to achieve the same
implementation with langgraph memory.
Some of the underlying PRs (not all of them):
- docs[patch]: update chatbot tutorial and migration guide (#26780)
- docs[patch]: update chatbot memory how-to (#26790)
- docs[patch]: update chatbot tools how-to (#26816)
- docs: update chat history in rag how-to (#26821)
- docs: update trim messages notebook (#26793)
- docs: clean up imports in how to guide for rag qa with chat history
(#26825)
- docs[patch]: update conversational rag tutorial (#26814)
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Co-authored-by: Vadym Barda <vadym@langchain.dev>
Co-authored-by: mercyspirit <ziying.qiu@gmail.com>
Co-authored-by: aqiu7 <aqiu7@gatech.edu>
Co-authored-by: John <43506685+Coniferish@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: William FH <13333726+hinthornw@users.noreply.github.com>
Co-authored-by: Subhrajyoty Roy <subhrajyotyroy@gmail.com>
Co-authored-by: Rajendra Kadam <raj.725@outlook.com>
Co-authored-by: Christophe Bornet <cbornet@hotmail.com>
Co-authored-by: Devin Gaffney <itsme@devingaffney.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** Moves callback to before yield for `_stream` and
`_astream` function for the textgen model in the community llm package
**Issue:** #16913
**Description**:
Adds a vector store integration with
[sqlite-vec](https://alexgarcia.xyz/sqlite-vec/), the successor to
sqlite-vss that is a single C file with no external dependencies.
Pretty straightforward, just copy-pasted the sqlite-vss integration and
made a few tweaks and added integration tests. Only question is whether
all documentation should be directed away from sqlite-vss if it is
defacto deprecated (cc @asg017).
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: philippe-oger <philippe.oger@adevinta.com>
**Description:** Moves yield to after callback for `_stream` and
`_astream` function for the gigachat model in the community llm package
**Issue:** #16913
This prevents `trim_messages` from raising an `IndexError` when invoked
with `include_system=True`, `strategy="last"`, and an empty message
list.
Fixes#26895
Dependencies: none
security scanners can't distinguish monorepo sources from each other.
this will resolve issues for folks trying to use e.g. langchain-core but
getting security issues from experimental flagged!
- **Description:** This pull request addresses the validation error in
`SettingsConfigDict` due to extra fields in the `.env` file. The issue
is prevalent across multiple Langchain modules. This fix ensures that
extra fields in the `.env` file are ignored, preventing validation
errors.
**Changes include:**
- Applied fixes to modules using `SettingsConfigDict`.
- **Issue:** NA, similar
https://github.com/langchain-ai/langchain/issues/26850
- **Dependencies:** NA
- **Description:** The flag is named `anonymize_snippets`. When set to
true, the Pebblo server will anonymize snippets by redacting all
personally identifiable information (PII) from the snippets going into
VectorDB and the generated reports
- **Issue:** NA
- **Dependencies:** NA
- **docs**: Updated
Description: Resolve CVE-2024-46946 by switching out sympify with
parse_expr with a very specific allowed set of operations.
https://nvd.nist.gov/vuln/detail/cve-2024-46946
Sympify uses eval which makes it vulnerable to code execution.
parse_expr is limited to specific expressions.
Bandit results
---------
Co-authored-by: aqiu7 <aqiu7@gatech.edu>
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
**Description:** Moves yield to after callback for `_stream` and
`_astream` function for the deepsparse model in the community package
**Issue:** #16913
- this flag ensures the tracer always runs in the same thread as the run
being traced for both sync and async runs
- pro: less chance for ordering bugs and other oddities
- blocking the event loop is not a concern given all code in the tracer
holds the GIL anyway
- **Description:** This PR fixes the response parsing logic for
`ChatDeepInfra`, more specifially `_convert_delta_to_message_chunk()`,
which is invoked when streaming via `ChatDeepInfra`.
- **Issue:** Streaming from DeepInfra via `ChatDeepInfra` is currently
broken because the response parsing logic doesn't handle that
`tool_calls` can be `None`. (There is no GitHub issue for this problem
yet.)
- **Dependencies:** –
- **Twitter handle:** –
Keeping this here as a reminder:
> If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
**Description:** Moves yield to after callback for
`_prepare_input_and_invoke_stream` and
`_aprepare_input_and_invoke_stream` for bedrock llm in community
package.
**Issue:** #16913
without this `model_config` importing this package produces warnings
about "model_name" having conflicts with protected namespace "model_".
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.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:**
When PR body is empty `get_pull_request` method fails with bellow
exception.
**Issue:**
```
TypeError('expected string or buffer')Traceback (most recent call last):
File ".../.venv/lib/python3.9/site-packages/langchain_core/tools/base.py", line 661, in run
response = context.run(self._run, *tool_args, **tool_kwargs)
File ".../.venv/lib/python3.9/site-packages/langchain_community/tools/github/tool.py", line 52, in _run
return self.api_wrapper.run(self.mode, query)
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 816, in run
return json.dumps(self.get_pull_request(int(query)))
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 495, in get_pull_request
add_to_dict(response_dict, "body", pull.body)
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 487, in add_to_dict
tokens = get_tokens(value)
File ".../.venv/lib/python3.9/site-packages/langchain_community/utilities/github.py", line 483, in get_tokens
return len(tiktoken.get_encoding("cl100k_base").encode(text))
File "....venv/lib/python3.9/site-packages/tiktoken/core.py", line 116, in encode
if match := _special_token_regex(disallowed_special).search(text):
TypeError: expected string or buffer
```
**Twitter:** __gorros__
Chunking of the input array controlled by `self.chunk_size` is being
ignored when `self.check_embedding_ctx_length` is disabled. Effectively,
the chunk size is assumed to be equal 1 in such a case. This is
suprising.
The PR takes into account `self.chunk_size` passed by the user.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** Add support to delete documents automatically from the
caches & chat message history by adding a new optional parameter, `ttl`.
- [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/
---------
Co-authored-by: Nithish Raghunandanan <nithishr@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
In the previous implementation, `skip_count` was counting all the
documents in the collection. Instead, we want to filter the documents by
`session_id` and calculate `skip_count` by subtracting `history_size`
from the filtered count.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- **Description:** fix "template" not allowed as prompt param
- **Issue:** #26058
- **Dependencies:** none
- [ ] **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.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
## Description
By default, `HuggingFaceEndpoint` instantiates both the
`InferenceClient` and the `AsyncInferenceClient` with the
`"server_kwargs"` passed as input. This is an issue as both clients
might not support exactly the same kwargs. This has been highlighted in
https://github.com/huggingface/huggingface_hub/issues/2522 by
@morgandiverrez with the `trust_env` parameter. In order to make
`langchain` integration future-proof, I do think it's wiser to forward
only the supported parameters to each client. Parameters that are not
supported are simply ignored with a warning to the user. From a
`huggingface_hub` maintenance perspective, this allows us much more
flexibility as we are not constrained to support the exact same kwargs
in both clients.
## Issue
https://github.com/huggingface/huggingface_hub/issues/2522
## Dependencies
None
## Twitter
https://x.com/Wauplin
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
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.
`unstructured.partition.auto.partition` supports a `url` kwarg, but
`url` in `UnstructuredLoader.__init__` is reserved for the server URL.
Here we add a `web_url` kwarg that is passed to the partition kwargs:
```python
self.unstructured_kwargs["url"] = web_url
```
Thank you for contributing to LangChain!
Fix error like
<img width="1167" alt="image"
src="https://github.com/user-attachments/assets/2e219b26-ec7e-48ef-8111-e0ff2f5ac4c0">
After the fix:
<img width="584" alt="image"
src="https://github.com/user-attachments/assets/48f36fe7-628c-48b6-81b2-7fe741e4ca85">
- [ ] **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.
---------
Signed-off-by: serena-ruan <serena.rxy@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Added PebbloTextLoader for loading text in
PebbloSafeLoader.
- Since PebbloSafeLoader wraps document loaders, this new loader enables
direct loading of text into Documents using PebbloSafeLoader.
- **Issue:** NA
- **Dependencies:** NA
- [x] **Tests**: Added/Updated tests
# Description
[Vector store base
class](4cdaca67dc/libs/core/langchain_core/vectorstores/base.py (L65))
currently expects `ids` to be passed in and that is what it passes along
to the AzureSearch vector store when attempting to `add_texts()`.
However AzureSearch expects `keys` to be passed in. When they are not
present, AzureSearch `add_embeddings()` makes up new uuids. This is a
problem when trying to run indexing. [Indexing code
expects](b297af5482/libs/core/langchain_core/indexing/api.py (L371))
the documents to be uploaded using provided ids. Currently AzureSearch
ignores `ids` passed from `indexing` and makes up new ones. Later when
`indexer` attempts to delete removed file, it uses the `id` it had
stored when uploading the document, however it was uploaded under
different `id`.
**Twitter handle: @martintriska1**
Page content sometimes is empty when PyMuPDF can not find text on pages.
For example, this can happen when the text of the PDF is not copyable
"by hand". Then an OCR solution is need - which is not integrated here.
This warning should accurately warn the user that some pages are lost
during this process.
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.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Fixes#26212: replaced the raw string with backslashes. Alternative:
raw-stringif the full docstring.
---------
Co-authored-by: Erick Friis <erickfriis@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"
Added search options for BoxRetriever and added documentation to
demonstrate how to use BoxRetriever as an agent tool - @BoxPlatform
- [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, ccurme, vbarda, hwchase17.
Ruff doesn't know about the python version in
`[tool.poetry.dependencies]`. It can get it from
`project.requires-python`.
Notes:
* poetry seems to have issues getting the python constraints from
`requires-python` and using `python` in per dependency constraints. So I
had to duplicate the info. I will open an issue on poetry.
* `inspect.isclass()` doesn't work correctly with `GenericAlias`
(`list[...]`, `dict[..., ...]`) on Python <3.11 so I added some `not
isinstance(type, GenericAlias)` checks:
Python 3.11
```pycon
>>> import inspect
>>> inspect.isclass(list)
True
>>> inspect.isclass(list[str])
False
```
Python 3.9
```pycon
>>> import inspect
>>> inspect.isclass(list)
True
>>> inspect.isclass(list[str])
True
```
Co-authored-by: Eugene Yurtsev <eyurtsev@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, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
### Description:
This pull request significantly enhances the MongodbLoader class in the
LangChain community package by adding robust metadata customization and
improved field extraction capabilities. The updated class now allows
users to specify additional metadata fields through the metadata_names
parameter, enabling the extraction of both top-level and deeply nested
document attributes as metadata. This flexibility is crucial for users
who need to include detailed contextual information without altering the
database schema.
Moreover, the include_db_collection_in_metadata flag offers optional
inclusion of database and collection names in the metadata, allowing for
even greater customization depending on the user's needs.
The loader's field extraction logic has been refined to handle missing
or nested fields more gracefully. It now employs a safe access mechanism
that avoids the KeyError previously encountered when a specified nested
field was absent in a document. This update ensures that the loader can
handle diverse and complex data structures without failure, making it
more resilient and user-friendly.
### Issue:
This pull request addresses a critical issue where the MongodbLoader
class in the LangChain community package could throw a KeyError when
attempting to access nested fields that may not exist in some documents.
The previous implementation did not handle the absence of specified
nested fields gracefully, leading to runtime errors and interruptions in
data processing workflows.
This enhancement ensures robust error handling by safely accessing
nested document fields, using default values for missing data, thus
preventing KeyError and ensuring smoother operation across various data
structures in MongoDB. This improvement is crucial for users working
with diverse and complex data sets, ensuring the loader can adapt to
documents with varying structures without failing.
### Dependencies:
Requires motor for asynchronous MongoDB interaction.
### Twitter handle:
N/A
### Add tests and docs
Tests: Unit tests have been added to verify that the metadata inclusion
toggle works as expected and that the field extraction correctly handles
nested fields.
Docs: An example notebook demonstrating the use of the enhanced
MongodbLoader is included in the docs/docs/integrations directory. This
notebook includes setup instructions, example usage, and outputs.
(Here is the notebook link : [colab
link](https://colab.research.google.com/drive/1tp7nyUnzZa3dxEFF4Kc3KS7ACuNF6jzH?usp=sharing))
Lint and test
Before submitting, I ran make format, make lint, and make test as per
the contribution guidelines. All tests pass, and the code style adheres
to the LangChain standards.
```python
import unittest
from unittest.mock import patch, MagicMock
import asyncio
from langchain_community.document_loaders.mongodb import MongodbLoader
class TestMongodbLoader(unittest.TestCase):
def setUp(self):
"""Setup the MongodbLoader test environment by mocking the motor client
and database collection interactions."""
# Mocking the AsyncIOMotorClient
self.mock_client = MagicMock()
self.mock_db = MagicMock()
self.mock_collection = MagicMock()
self.mock_client.get_database.return_value = self.mock_db
self.mock_db.get_collection.return_value = self.mock_collection
# Initialize the MongodbLoader with test data
self.loader = MongodbLoader(
connection_string="mongodb://localhost:27017",
db_name="testdb",
collection_name="testcol"
)
@patch('langchain_community.document_loaders.mongodb.AsyncIOMotorClient', return_value=MagicMock())
def test_constructor(self, mock_motor_client):
"""Test if the constructor properly initializes with the correct database and collection names."""
loader = MongodbLoader(
connection_string="mongodb://localhost:27017",
db_name="testdb",
collection_name="testcol"
)
self.assertEqual(loader.db_name, "testdb")
self.assertEqual(loader.collection_name, "testcol")
def test_aload(self):
"""Test the aload method to ensure it correctly queries and processes documents."""
# Setup mock data and responses for the database operations
self.mock_collection.count_documents.return_value = asyncio.Future()
self.mock_collection.count_documents.return_value.set_result(1)
self.mock_collection.find.return_value = [
{"_id": "1", "content": "Test document content"}
]
# Run the aload method and check responses
loop = asyncio.get_event_loop()
results = loop.run_until_complete(self.loader.aload())
self.assertEqual(len(results), 1)
self.assertEqual(results[0].page_content, "Test document content")
def test_construct_projection(self):
"""Verify that the projection dictionary is constructed correctly based on field names."""
self.loader.field_names = ['content', 'author']
self.loader.metadata_names = ['timestamp']
expected_projection = {'content': 1, 'author': 1, 'timestamp': 1}
projection = self.loader._construct_projection()
self.assertEqual(projection, expected_projection)
if __name__ == '__main__':
unittest.main()
```
### Additional Example for Documentation
Sample Data:
```json
[
{
"_id": "1",
"title": "Artificial Intelligence in Medicine",
"content": "AI is transforming the medical industry by providing personalized medicine solutions.",
"author": {
"name": "John Doe",
"email": "john.doe@example.com"
},
"tags": ["AI", "Healthcare", "Innovation"]
},
{
"_id": "2",
"title": "Data Science in Sports",
"content": "Data science provides insights into player performance and strategic planning in sports.",
"author": {
"name": "Jane Smith",
"email": "jane.smith@example.com"
},
"tags": ["Data Science", "Sports", "Analytics"]
}
]
```
Example Code:
```python
loader = MongodbLoader(
connection_string="mongodb://localhost:27017",
db_name="example_db",
collection_name="articles",
filter_criteria={"tags": "AI"},
field_names=["title", "content"],
metadata_names=["author.name", "author.email"],
include_db_collection_in_metadata=True
)
documents = loader.load()
for doc in documents:
print("Page Content:", doc.page_content)
print("Metadata:", doc.metadata)
```
Expected Output:
```
Page Content: Artificial Intelligence in Medicine AI is transforming the medical industry by providing personalized medicine solutions.
Metadata: {'author_name': 'John Doe', 'author_email': 'john.doe@example.com', 'database': 'example_db', 'collection': 'articles'}
```
Thank you.
---
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.
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
