- **Description:** This is a **one line change**. the
`self.async_client.with_raw_response.create(**payload)` call is not
properly awaited within the `_astream` method. In `_agenerate` this is
done already, but likely forgotten in the other method.
- **Issue:** Not applicable
- **Dependencies:** No dependencies required.
(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>
Thank you for contributing to LangChain!
**Description:**
Similar to other packages (`langchain_openai`, `langchain_anthropic`) it
would be beneficial if that `ChatMistralAI` model could fetch the API
base URL from the environment.
This PR allows this via the following order:
- provided value
- then whatever `MISTRAL_API_URL` is set to
- then whatever `MISTRAL_BASE_URL` is set to
- if `None`, then default is ` "https://api.mistral.com/v1"`
- [x] **Add tests and docs**:
Added unit tests, docs I feel are unnecessary, as this is just aligning
with other packages that do the same?
- [x] **Lint and test**:
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
Milvus (and `pymilvus`) recently added the option to use [sparse
vectors](https://milvus.io/docs/sparse_vector.md#Sparse-Vector) with
appropriate search methods (e.g., `SPARSE_INVERTED_INDEX`) and
embeddings (e.g., `BM25`, `SPLADE`).
This PR allow creating a vector store using langchain's `Milvus` class,
setting the matching vector field type to `DataType.SPARSE_FLOAT_VECTOR`
and the default index type to `SPARSE_INVERTED_INDEX`.
It is only extending functionality, and backward compatible.
## Note
I also interested in extending the Milvus class further to support multi
vector search (aka hybrid search). Will be happy to discuss that. See
[here](https://github.com/langchain-ai/langchain/discussions/19955),
[here](https://github.com/langchain-ai/langchain/pull/20375), and
[here](https://github.com/langchain-ai/langchain/discussions/22886)
similar needs.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
## Description
In `langchain_prompty`, messages are templated by Prompty. However, a
call to `ChatPromptTemplate` was initiating a second templating. We now
convert parsed messages to `Message` objects before calling
`ChatPromptTemplate`, signifying clearly that they are already
templated.
We also revert #25739 , which applied to this second templating, which
we now avoid, and did not fix the original issue.
## Issue
Closes#25703
Add array data type for milvus vector store collection create
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**: ***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!
- [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.
---------
Signed-off-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Rohit Gupta <rohit.gupta2@walmart.com>
Co-authored-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
This pull request introduces support for the AI21 tools calling feature,
available by the Jamba-1.5 models. When Jamba-1.5 detects the necessity
to invoke a provided tool, as indicated by the 'tools' parameter passed
to the model:
```
class ToolDefinition(TypedDict, total=False):
type: Required[Literal["function"]]
function: Required[FunctionToolDefinition]
class FunctionToolDefinition(TypedDict, total=False):
name: Required[str]
description: str
parameters: ToolParameters
class ToolParameters(TypedDict, total=False):
type: Literal["object"]
properties: Required[Dict[str, Any]]
required: List[str]
```
It will respond with a list of tool calls structured as follows:
```
class ToolCall(AI21BaseModel):
id: str
function: ToolFunction
type: Literal["function"] = "function"
class ToolFunction(AI21BaseModel):
name: str
arguments: str
```
This pull request incorporates the necessary modifications to integrate
this functionality into the ai21-langchain library.
---------
Co-authored-by: asafg <asafg@ai21.com>
Co-authored-by: pazshalev <111360591+pazshalev@users.noreply.github.com>
Co-authored-by: Paz Shalev <pazs@ai21.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
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"
- "libs: langchain_milvus: add db name to milvus connection check"
- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** add db name to milvus connection check
- **Issue:** https://github.com/langchain-ai/langchain/issues/25277
- [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>
- **Description:** Added a `template_format` parameter to
`create_chat_prompt` to allow `.prompty` files to handle variables in
different template formats.
- **Issue:** #25703
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
* Removed `ruff check --select I` as `I` is already selected and checked
in the main `ruff check` command
* Added checks for non-empty `PYTHON_FILES`
* Run `ruff check` only on `PYTHON_FILES`
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Fix the validation error for `endpoint_url` for
HuggingFaceEndpoint. I have given a descriptive detail of the isse in
the issue that I have created.
- **Issue:** #24742
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
### Summary
Add `DatabricksVectorSearch` and `DatabricksEmbeddings` classes to the
`langchain-databricks` partner packages. Core functionality is
unchanged, but the vector search class is largely refactored for
readability and maintainability.
This PR does not add integration tests yet. This will be added once the
Databricks test workspace is ready.
Tagging @efriis as POC
### Tracker
[✅] Create a package and imgrate ChatDatabricks
[✍️] Migrate DatabricksVectorSearch, DatabricksEmbeddings, and their
docs
~[ ] Migrate UCFunctionToolkit and its doc~
[ ] Add provider document and update README.md
[ ] Add integration tests and set up secrets (after moved to an external
package)
[ ] Add deprecation note to the community implementations.
---------
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- [ ] **PR message**:
- **Description:** Compatible with other llm (eg: deepseek-chat, glm-4)
usage meta data
- **Issue:** N/A
- **Dependencies:** no new dependencies added
- [ ] **Add tests and docs**:
libs/partners/openai/tests/unit_tests/chat_models/test_base.py
```shell
cd libs/partners/openai
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_openai_astream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_openai_stream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_deepseek_astream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_deepseek_stream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_glm4_astream
poetry run pytest tests/unit_tests/chat_models/test_base.py::test_glm4_stream
```
---------
Co-authored-by: hyman <hyman@xiaozancloud.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Be more explicit in the docs about creating an instance of the
UnstructuredClient if you want to customize it versus using sdk
parameters with the UnstructuredLoader.
Bump the unstructured-client dependency as discussed
[here](https://github.com/langchain-ai/langchain/discussions/25328#discussioncomment-10350949)
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Hello.
First of all, thank you for maintaining such a great project.
## Description
In https://github.com/langchain-ai/langchain/pull/25123, support for
structured_output is added. However, `"additionalProperties": false`
needs to be included at all levels when a nested object is generated.
error from current code:
https://gist.github.com/fufufukakaka/e9b475300e6934853d119428e390f204
```
BadRequestError: Error code: 400 - {'error': {'message': "Invalid schema for response_format 'JokeWithEvaluation': In context=('properties', 'self_evaluation'), 'additionalProperties' is required to be supplied and to be false", 'type': 'invalid_request_error', 'param': 'response_format', 'code': None}}
```
Reference: [Introducing Structured Outputs in the
API](https://openai.com/index/introducing-structured-outputs-in-the-api/)
```json
{
"model": "gpt-4o-2024-08-06",
"messages": [
{
"role": "system",
"content": "You are a helpful math tutor."
},
{
"role": "user",
"content": "solve 8x + 31 = 2"
}
],
"response_format": {
"type": "json_schema",
"json_schema": {
"name": "math_response",
"strict": true,
"schema": {
"type": "object",
"properties": {
"steps": {
"type": "array",
"items": {
"type": "object",
"properties": {
"explanation": {
"type": "string"
},
"output": {
"type": "string"
}
},
"required": ["explanation", "output"],
"additionalProperties": false
}
},
"final_answer": {
"type": "string"
}
},
"required": ["steps", "final_answer"],
"additionalProperties": false
}
}
}
}
```
In the current code, `"additionalProperties": false` is only added at
the last level.
This PR introduces the `_add_additional_properties_key` function, which
recursively adds `"additionalProperties": false` to the entire JSON
schema for the request.
Twitter handle: `@fukkaa1225`
Thank you!
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** This change adds the ID field that's required in
Pinecone to the result documents of the similarity search method.
- **Issue:** Lack of document metadata namely the ID field
- [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: Chester Curme <chester.curme@gmail.com>
limit the most recent documents to fetch from MongoDB database.
Thank you for contributing to LangChain!
- [ ] **limit the most recent documents to fetch from MongoDB
database.**: "langchain_mongodb: limit the most recent documents to
fetch from MongoDB database."
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** Added a doc_limit parameter which enables the limit
for the documents to fetch from MongoDB database
- **Issue:**
- **Dependencies:** None
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
### Summary
Create `langchain-databricks` as a new partner packages. This PR does
not migrate all existing Databricks integration, but the package will
eventually contain:
* `ChatDatabricks` (implemented in this PR)
* `DatabricksVectorSearch`
* `DatabricksEmbeddings`
* ~`UCFunctionToolkit`~ (will be done after UC SDK work which
drastically simplify implementation)
Also, this PR does not add integration tests yet. This will be added
once the Databricks test workspace is ready.
Tagging @efriis as POC
### Tracker
[✍️] Create a package and imgrate ChatDatabricks
[ ] Migrate DatabricksVectorSearch, DatabricksEmbeddings, and their docs
~[ ] Migrate UCFunctionToolkit and its doc~
[ ] Add provider document and update README.md
[ ] Add integration tests and set up secrets (after moved to an external
package)
[ ] Add deprecation note to the community implementations.
---------
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
**Description:** Adding `BoxRetriever` for langchain_box. This retriever
handles two use cases:
* Retrieve all documents that match a full-text search
* Retrieve the answer to a Box AI prompt as a Document
**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>
Thank you for contributing to LangChain!
-Description: Adding new package: `langchain-box`:
* `langchain_box.document_loaders.BoxLoader` — DocumentLoader
functionality
* `langchain_box.utilities.BoxAPIWrapper` — Box-specific code
* `langchain_box.utilities.BoxAuth` — Helper class for Box
authentication
* `langchain_box.utilities.BoxAuthType` — enum used by BoxAuth class
- 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 <erickfriis@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
also remove some unused dependencies (fastapi) and unused test/lint/dev
dependencies (community, openai, textsplitters)
chromadb 0.5.4 introduced usage of `model_fields` which is pydantic v2
specific. also released in 0.5.5
Here we allow standard tests to specify a value for `tool_choice` via a
`tool_choice_value` property, which defaults to None.
Chat models [available in
Together](https://docs.together.ai/docs/chat-models) have issues passing
standard tool calling tests:
- llama 3.1 models currently [appear to rely on user-side
parsing](https://docs.together.ai/docs/llama-3-function-calling) in
Together;
- Mixtral-8x7B and Mistral-7B (currently tested) consistently do not
call tools in some tests.
Specifying tool_choice also lets us remove an existing `xfail` and use a
smaller model in Groq tests.
Remove the period after the hyperlink in the docstring of
BaseChatOpenAI.with_structured_output.
I have repeatedly copied the extra period at the end of the hyperlink,
which results in a "Page not found" page when pasted into the browser.
Backwards compatible change that converts pydantic extras to literals
which is consistent with pydantic 2 usage.
- fireworks
- voyage ai
- mistralai
- mistral ai
- together ai
- huggigng face
- pinecone
- Description: As described in the related issue: There is an error
occuring when using langchain-openai>=0.1.17 which can be attributed to
the following PR: #23691
Here, the parameter logprobs is added to requests per default.
However, AzureOpenAI takes issue with this parameter as stated here:
https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/chatgpt?tabs=python-new&pivots=programming-language-chat-completions
-> "If you set any of these parameters, you get an error."
Therefore, this PR changes the default value of logprobs parameter to
None instead of False. This results in it being filtered before the
request is sent.
- Issue: #24880
- Dependencies: /
Co-authored-by: blaufink <sebastian.brueckner@outlook.de>
## Description
This pull-request extends the existing vector search strategies of
MongoDBAtlasVectorSearch to include Hybrid (Reciprocal Rank Fusion) and
Full-text via new Retrievers.
There is a small breaking change in the form of the `prefilter` kwarg to
search. For this, and because we have now added a great deal of
features, including programmatic Index creation/deletion since 0.1.0, we
plan to bump the version to 0.2.0.
### Checklist
* Unit tests have been extended
* formatting has been applied
* One mypy error remains which will either go away in CI or be
simplified.
---------
Signed-off-by: Casey Clements <casey.clements@mongodb.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Among integration packages in libs/partners, Groq is an exception in
that it errors on warnings.
Following https://github.com/langchain-ai/langchain/pull/25084, Groq
fails with
> pydantic.warnings.PydanticDeprecatedSince20: The `__fields__`
attribute is deprecated, use `model_fields` instead. Deprecated in
Pydantic V2.0 to be removed in V3.0.
Here we update the behavior to no longer fail on warning, which is
consistent with the rest of the packages in libs/partners.
**Description:**
This PR fixes a bug where if `enable_dynamic_field` and
`partition_key_field` are enabled at the same time, a pymilvus error
occurs.
Milvus requires the partition key field to be a full schema defined
field, and not a dynamic one, so it will throw the error "the specified
partition key field {field} not exist" when creating the collection.
When `enabled_dynamic_field` is set to `True`, all schema field creation
based on `metadatas` is skipped. This code now checks if
`partition_key_field` is set, and creates the field.
Integration test added.
**Twitter handle:** StuartMarshUK
---------
Co-authored-by: Stuart Marsh <stuart.marsh@qumata.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Hardens index commands with try/except for free clusters and optional
waits for syncing and tests.
[efriis](https://github.com/efriis) These are the upgrades to the search
index commands (CRUD) that I mentioned.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
supports following UX
```python
class SubTool(TypedDict):
"""Subtool docstring"""
args: Annotated[Dict[str, Any], {}, "this does bar"]
class Tool(TypedDict):
"""Docstring
Args:
arg1: foo
"""
arg1: str
arg2: Union[int, str]
arg3: Optional[List[SubTool]]
arg4: Annotated[Literal["bar", "baz"], ..., "this does foo"]
arg5: Annotated[Optional[float], None]
```
- can parse google style docstring
- can use Annotated to specify default value (second arg)
- can use Annotated to specify arg description (third arg)
- can have nested complex types
Anthropic models (including via Bedrock and other cloud platforms)
accept a status/is_error attribute on tool messages/results
(specifically in `tool_result` content blocks for Anthropic API). Adding
a ToolMessage.status attribute so that users can set this attribute when
using those models
**Description:** Add empty string default for api_key and change
`server_url` to `url` to match existing loaders.
- [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.
- Mixtral with Groq has started consistently failing tool calling tests.
Here we restrict testing to llama 3.1.
- `.schema` is deprecated in pydantic proper in favor of
`.model_json_schema`.
- [ ] **PR title**: "langchain-openai: openai proxy added to base
embeddings"
- [ ] **PR message**:
- **Description:**
Dear langchain developers,
You've already supported proxy for ChatOpenAI implementation in your
package. At the same time, if somebody needed to use proxy for chat, it
also could be necessary to be able to use it for OpenAIEmbeddings.
That's why I think it's important to add proxy support for OpenAI
embeddings. That's what I've done in this PR.
@baskaryan
---------
Co-authored-by: karpov <karpov@dohod.ru>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:**
In the `ChatFireworks` class definition, the Field() call for the "stop"
("stop_sequences") parameter is missing the "default" keyword.
**Issue:**
Type checker reports "stop_sequences" as a missing arg (not recognizing
the default value is None)
**Dependencies:**
None
**Twitter handle:**
None
Mistral appears to have added validation for the format of its tool call
IDs:
`{"object":"error","message":"Tool call id was abc123 but must be a-z,
A-Z, 0-9, with a length of
9.","type":"invalid_request_error","param":null,"code":null}`
This breaks compatibility of messages from other providers. Here we add
a function that converts any string to a Mistral-valid tool call ID, and
apply it to incoming messages.
#### Update (2):
A single `UnstructuredLoader` is added to handle both local and api
partitioning. This loader also handles single or multiple documents.
#### Changes in `community`:
Changes here do not affect users. In the initial process of using the
SDK for the API Loaders, the Loaders in community were refactored.
Other changes include:
The `UnstructuredBaseLoader` has a new check to see if both
`mode="paged"` and `chunking_strategy="by_page"`. It also now has
`Element.element_id` added to the `Document.metadata`.
`UnstructuredAPIFileLoader` and `UnstructuredAPIFileIOLoader`. As such,
now both directly inherit from `UnstructuredBaseLoader` and initialize
their `file_path`/`file` attributes respectively and implement their own
`_post_process_elements` methods.
--------
#### Update:
New SDK Loaders in a [partner
package](https://python.langchain.com/v0.1/docs/contributing/integrations/#partner-package-in-langchain-repo)
are introduced to prevent breaking changes for users (see discussion
below).
##### TODO:
- [x] Test docstring examples
--------
- **Description:** UnstructuredAPIFileIOLoader and
UnstructuredAPIFileLoader calls to the unstructured api are now made
using the unstructured-client sdk.
- **New Dependencies:** unstructured-client
- [x] **Add tests and docs**: If you're adding a new integration, please
include
- [x] a test for the integration, preferably unit tests that do not rely
on network access,
- [x] update the description in
`docs/docs/integrations/providers/unstructured.mdx`
- [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.
TODO:
- [x] Update
https://python.langchain.com/v0.1/docs/integrations/document_loaders/unstructured_file/#unstructured-api
-
`langchain/docs/docs/integrations/document_loaders/unstructured_file.ipynb`
- The description here needs to indicate that users should install
`unstructured-client` instead of `unstructured`. Read over closely to
look for any other changes that need to be made.
- [x] Update the `lazy_load` method in `UnstructuredBaseLoader` to
handle json responses from the API instead of just lists of elements.
- This method may need to be overwritten by the API loaders instead of
changing it in the `UnstructuredBaseLoader`.
- [x] Update the documentation links in the class docstrings (the
Unstructured documents have moved)
- [x] Update Document.metadata to include `element_id` (see thread
[here](https://unstructuredw-kbe4326.slack.com/archives/C044N0YV08G/p1718187499818419))
---------
Signed-off-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com>
Co-authored-by: ChengZi <chen.zhang@zilliz.com>
add dynamic field feature to langchain_milvus
more unittest, more robustic
plan to deprecate the `metadata_field` in the future, because it's
function is the same as `enable_dynamic_field`, but the latter one is a
more advanced concept in milvus
Signed-off-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description**
Add support for Pinecone hosted embedding models as
`PineconeEmbeddings`. Replacement for #22890
**Dependencies**
Add `aiohttp` to support async embeddings call against REST directly
- [x] **Add tests and docs**: If you're adding a new integration, please
include
Added `docs/docs/integrations/text_embedding/pinecone.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/
Twitter: `gdjdg17`
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** Fixes an issue where the chat message history was not
returned in order. Fixed it now by returning based on timestamps.
- [x] **Add tests and docs**: Updated the tests to check the order
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>
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.
**Description:** : Add support for chat message history using Couchbase
- [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>
## Description
This pull-request improves the treatment of document IDs in
`MongoDBAtlasVectorSearch`.
Class method signatures of add_documents, add_texts, delete, and
from_texts
now include an `ids:Optional[List[str]]` keyword argument permitting the
user
greater control.
Note that, as before, IDs may also be inferred from
`Document.metadata['_id']`
if present, but this is no longer required,
IDs can also optionally be returned from searches.
This PR closes the following JIRA issues.
* [PYTHON-4446](https://jira.mongodb.org/browse/PYTHON-4446)
MongoDBVectorSearch delete / add_texts function rework
* [PYTHON-4435](https://jira.mongodb.org/browse/PYTHON-4435) Add support
for "Indexing"
* [PYTHON-4534](https://jira.mongodb.org/browse/PYTHON-4534) Ensure
datetimes are json-serializable
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** This pull request introduces two new methods to the
Langchain Chroma partner package that enable similarity search based on
image embeddings. These methods enhance the package's functionality by
allowing users to search for images similar to a given image URI. Also
introduces a notebook to demonstrate it's use.
- **Issue:** N/A
- **Dependencies:** None
- **Twitter handle:** @mrugank9009
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
## Description
This PR adds integration tests to follow up on #24164.
By default, the tests use an in-memory instance.
To run the full suite of tests, with both in-memory and Qdrant server:
```
$ docker run -p 6333:6333 qdrant/qdrant
$ make test
$ make integration_test
```
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** Explicitly add parameters from openai API
- [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>
Added missed docstrings. Format docstrings to the consistent format
(used in the API Reference)
---------
Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com>
Co-authored-by: isaac hershenson <ihershenson@hmc.edu>
Co-authored-by: Erick Friis <erick@langchain.dev>
I stumbled upon a bug that led to different similarity scores between
the async and sync similarity searches with relevance scores in Qdrant.
The reason being is that _asimilarity_search_with_relevance_scores is
missing, this makes langchain_qdrant use the method of the vectorstore
baseclass leading to drastically different results.
To illustrate the magnitude here are the results running an identical
search in a test vectorstore.
Output of asimilarity_search_with_relevance_scores:
[0.9902903374601824, 0.9472135924938804, 0.8535534011299859]
Output of similarity_search_with_relevance_scores:
[0.9805806749203648, 0.8944271849877607, 0.7071068022599718]
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
**Description:** Add support for caching (standard + semantic) LLM
responses using Couchbase
- [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: Nithish Raghunandanan <nithishr@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
