Support using additional import mapping. This allows users to override
old mappings/add new imports to the loads function.
- [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/
The object extends from
langchain_community.chat_models.openai.ChatOpenAI which doesn't have
`bind_tools` defined. I tried extending from
`langchain_openai.ChatOpenAI` in
https://github.com/langchain-ai/langchain/pull/25975 but that PR got
closed because this is not correct.
So adding our own `bind_tools` (which for now copying from ChatOpenAI is
good enough) will solve the tool calling issue we are having now.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **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>
Open source models like Llama3.1 have function calling, but it's not
that great. Therefore, we introduce the option to ignore model's
function calling and just use the prompt-based approach
Thank you for contributing to LangChain!
- [X ] **PR title**
- [X ] **PR message**:
**Description:** adds a handler for when delta choice is None
**Issue:** Fixes#25951
**Dependencies:** Not applicable
- [ X] **Add tests and docs**: Not applicable
- [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: Grande <Tom.Daniel.Grande@statsbygg.no>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:**
Change the default Neo4j username/password (when not supplied as
environment variable or in code) from `None` to `""`.
Neo4j has an option to [disable
auth](https://neo4j.com/docs/operations-manual/current/configuration/configuration-settings/#config_dbms.security.auth_enabled)
which is helpful when developing. When auth is disabled, the username /
password through the `neo4j` module should be `""` (ie an empty string).
Empty strings get marked as false in
`langchain_core.utils.env.get_from_dict_or_env` -- changing this code /
behaviour would have a wide impact and is undesirable.
In order to both _allow_ access to Neo4j with auth disabled and _not_
impact `langchain_core` this patch is presented. The downside would be
that if a user forgets to set NEO4J_USERNAME or NEO4J_PASSWORD they
would see an invalid credentials error rather than missing credentials
error. This could be mitigated but would result in a less elegant patch!
**Issue:**
Fix issue where langchain cannot communicate with Neo4j if Neo4j auth is
disabled.
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>
- **PR title**: "community: add Jina Search tool"
- **Description:** Added the Jina Search tool for querying the Jina
search API. This includes the implementation of the JinaSearchAPIWrapper
and the JinaSearch tool, along with a Jupyter notebook example
demonstrating its usage.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** [Twitter
handle](https://x.com/yashp3020?t=7wM0gQ7XjGciFoh9xaBtqA&s=09)
- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. 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 <baskaryan@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Previously, regardless of whether or not strip_whitespace was set to
true or false, the strip text method in the SpacyTextSplitter class used
`sent.text` to get the sentence. I modified this to include a ternary
such that if strip_whitespace is false, it uses `sent.text_with_ws`
I also modified the project.toml to include the spacy pipeline package
and to lock the numpy version, as higher versions break spacy.
- **Issue:** N/a
- **Dependencies:** None
Returns an array of results which is more specific and easier for later
use.
Tested locally:
```
resp = tool.invoke("what's the weather like in Shanghai?")
for item in resp:
print(item)
```
returns
```
{'snippet': '<b>Shanghai</b>, <b>Shanghai</b>, China <b>Weather</b> Forecast, with current conditions, wind, air quality, and what to expect for the next 3 days.', 'title': 'Shanghai, Shanghai, China Weather Forecast | AccuWeather', 'link': 'https://www.accuweather.com/en/cn/shanghai/106577/weather-forecast/106577'}
{'snippet': '5. 99 / 87 °F. 6. 99 / 86 °F. 7. Detailed forecast for 14 days. Need some help? Current <b>weather</b> <b>in Shanghai</b> and forecast for today, tomorrow, and next 14 days.', 'title': 'Weather for Shanghai, Shanghai Municipality, China - timeanddate.com', 'link': 'https://www.timeanddate.com/weather/china/shanghai'}
{'snippet': '<b>Shanghai</b> - <b>Weather</b> warnings issued 14-day forecast. <b>Weather</b> warnings issued. Forecast - <b>Shanghai</b>. Day by day forecast. Last updated Friday at 01:05. Tonight, ... Temperature feels <b>like</b> 34 ...', 'title': 'Shanghai - BBC Weather', 'link': 'https://www.bbc.com/weather/1796236'}
{'snippet': 'Current <b>weather</b> <b>in Shanghai</b>, <b>Shanghai</b>, China. Check current conditions <b>in Shanghai</b>, <b>Shanghai</b>, China with radar, hourly, and more.', 'title': 'Shanghai, Shanghai, China Current Weather | AccuWeather', 'link': 'https://www.accuweather.com/en/cn/shanghai/106577/current-weather/106577'}
13-Day Beijing, Xi'an, Chengdu, <b>Shanghai</b> Chinese Language and Culture Immersion Tour. <b>Shanghai</b> in September. Average daily temperature range: 23–29°C (73–84°F) Average rainy days: 10. Average sunny days: 20. September ushers in pleasant autumn <b>weather</b>, making it one of the best months to visit <b>Shanghai</b>. <b>Weather</b> in <b>Shanghai</b>: Climate, Seasons, and Average Monthly Temperature. <b>Shanghai</b> has a subtropical maritime monsoon climate, meaning high humidity and lots of rain. Hot muggy summers, cool falls, cold winters with little snow, and warm springs are the norm. Midsummer through early fall is the best time to visit <b>Shanghai</b>. <b>Shanghai</b>, <b>Shanghai</b>, China <b>Weather</b> Forecast, with current conditions, wind, air quality, and what to expect for the next 3 days. 1165. 45.9. 121. Winter, from December to February, is quite cold: the average January temperature is 5 °C (41 °F). There may be cold periods, with highs around 5 °C (41 °F) or below, and occasionally, even snow can fall. The temperature dropped to -10 °C (14 °F) in January 1977 and to -7 °C (19.5 °F) in January 2016. 5. 99 / 87 °F. 6. 99 / 86 °F. 7. Detailed forecast for 14 days. Need some help? Current <b>weather</b> in <b>Shanghai</b> and forecast for today, tomorrow, and next 14 days. Everything you need to know about today's <b>weather</b> in <b>Shanghai</b>, <b>Shanghai</b>, China. High/Low, Precipitation Chances, Sunrise/Sunset, and today's Temperature History. <b>Shanghai</b> - <b>Weather</b> warnings issued 14-day forecast. <b>Weather</b> warnings issued. Forecast - <b>Shanghai</b>. Day by day forecast. Last updated Friday at 01:05. Tonight, ... Temperature feels <b>like</b> 34 ... <b>Shanghai</b> 14 Day Extended Forecast. <b>Weather</b> Today <b>Weather</b> Hourly 14 Day Forecast Yesterday/Past <b>Weather</b> Climate (Averages) Currently: 84 °F. Passing clouds. (<b>Weather</b> station: <b>Shanghai</b> Hongqiao Airport, China). See more current <b>weather</b>. Current <b>weather</b> in <b>Shanghai</b>, <b>Shanghai</b>, China. Check current conditions in <b>Shanghai</b>, <b>Shanghai</b>, China with radar, hourly, and more. <b>Shanghai</b> <b>Weather</b> Forecasts. <b>Weather Underground</b> provides local & long-range <b>weather</b> forecasts, weatherreports, maps & tropical <b>weather</b> conditions for the <b>Shanghai</b> area.
```
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:**
Adding a new option to the CSVLoader that allows us to implicitly
specify the columns that are used for generating the Document content.
Currently these are implicitly set as "all fields not part of the
metadata_columns".
In some cases however it is useful to have a field both as a metadata
and as part of the document content.
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:** The function `_is_assistants_builtin_tool` didn't had
support for `file_search` from OpenAI. This was creating conflict and
blocking the usage of such. OpenAI Assistant changed from`retrieval` to
`file_search`.
The following code
```
agent = OpenAIAssistantV2Runnable.create_assistant(
name="Data Analysis Assistant",
instructions=prompt[0].content,
tools={'type': 'file_search'},
model=self.chat_config.connection.deployment_name,
client=llm,
as_agent=True,
tool_resources={
"file_search": {
"vector_store_ids": vector_store_id
}
}
)
```
Was throwing the following error
```
Traceback (most recent call last):
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 500, in get_response
return await super().get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 96, in get_response
response = await self.inner_chat.get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 96, in get_response
response = await self.inner_chat.get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/chat_decorators.py",
line 96, in get_response
response = await self.inner_chat.get_response(post, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[Previous line repeated 4 more times]
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/chat/azure_open_ai_chat.py",
line 147, in get_response
chain = chain_factory.get_chain(prompts, post.conversation.id,
overrides, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/Documents/codes/shellai-nlp-backend/app/llm_connections/chains.py",
line 1324, in get_chain
agent = OpenAIAssistantV2Runnable.create_assistant(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_community/agents/openai_assistant/base.py",
line 256, in create_assistant
tools=[_get_assistants_tool(tool) for tool in tools], # type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_community/agents/openai_assistant/base.py",
line 256, in <listcomp>
tools=[_get_assistants_tool(tool) for tool in tools], # type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_community/agents/openai_assistant/base.py",
line 119, in _get_assistants_tool
return convert_to_openai_tool(tool)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_core/utils/function_calling.py",
line 255, in convert_to_openai_tool
function = convert_to_openai_function(tool)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/l.guedesdossantos/anaconda3/envs/shell-e/lib/python3.11/site-packages/langchain_core/utils/function_calling.py",
line 230, in convert_to_openai_function
raise ValueError(
ValueError: Unsupported function
{'type': 'file_search'}
Functions must be passed in as Dict, pydantic.BaseModel, or Callable. If
they're a dict they must either be in OpenAI function format or valid
JSON schema with top-level 'title' and 'description' keys.
```
With the proposed changes, this is fixed and the function will have support for `file_search`.
This was the only place missing the support for `file_search`.
Reference doc
https://platform.openai.com/docs/assistants/tools/file-search
- **Twitter handle:** luizf0992
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Description:
- Add system templates and user templates in integration testing
- initialize the response id field value to request_id
- Adjust the default model to hunyuan-pro
- Remove the default values of Temperature and TopP
- Add SystemMessage
all the integration tests have passed.
1、Execute integration tests for the first time
<img width="1359" alt="71ca77a2-e9be-4af6-acdc-4d665002bd9b"
src="https://github.com/user-attachments/assets/9298dc3a-aa26-4bfa-968b-c011a4e699c9">
2、Run the integration test a second time
<img width="1501" alt="image"
src="https://github.com/user-attachments/assets/61335416-4a67-4840-bb89-090ba668e237">
Issue: None
Dependencies: None
Twitter handle: None
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:** [IPEX-LLM](https://github.com/intel-analytics/ipex-llm)
is a PyTorch library for running LLM on Intel CPU and GPU (e.g., local
PC with iGPU, discrete GPU such as Arc, Flex and Max) with very low
latency. This PR adds Intel GPU support to `ipex-llm` llm integration.
**Dependencies:** `ipex-llm`
**Contribution maintainer**: @ivy-lv11 @Oscilloscope98
**tests and docs**:
- Add: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/libs/community/tests/llms/test_ipex_llm.py
---------
Co-authored-by: ivy-lv11 <zhicunlv@gmail.com>
- **Description:**
Improve llamacpp embedding class by adding the `device` parameter so it
can be passed to the model and used with `gpu`, `cpu` or Apple metal
(`mps`).
Improve performance by making use of the bulk client api to compute
embeddings in batches.
- **Dependencies:** none
- **Tag maintainer:**
@hwchase17
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:**
Starting from Neo4j 5.23 (22 August 2024), with vector-2.0 indexes,
`vector.dimensions` is not required to be set, which will cause it the
key not exist error in index config if it's not set.
Since the existence of vector.dimensions will only ensure additional
checks, this commit turns embedding dimension check optional, and only
do checks when it exists (not None).
https://neo4j.com/release-notes/database/neo4j-5/
**Twitter handle:** @HollowM186
Signed-off-by: Hollow Man <hollowman@opensuse.org>
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Added `ref` query parameter so data is not loaded
only from the default branch but any branch passed
---------
Co-authored-by: Osama Mehdi <mehdi@hm.edu>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.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"
- [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.
## Description
- Updates the self-query retriever factory to check for the new Qdrant
vector store class. i.e. `langchain_qdrant.QdrantVectorstore`.
- Deprecates `QdrantSparseVectorRetriever`, since the vector store
implementation natively supports it now.
Resolves#25798
- **Description:** When useing LLM integration moonshot,it's occurring
error "'Moonshot' object has no attribute '_client'",it's because of the
"_client" that is private in pydantic v1.0 so that we can't use it.I
turn "_client" into "client" , the error to be resolved!
- **Issue:** the issue #24390
- **Dependencies:** none
- **Twitter handle:** @Rainsubtime
- [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: Cyue <Cyue_work2001@163.com>
- [x] **PR title - community: add neo4j query constructor for self
query**
- [x] **PR message**
- **Description:** adding a Neo4jTranslator so that the Neo4j vector
database can use SelfQueryRetriever
- **Issue:** this issue had been raised before in #19748
- **Dependencies:** none.
- **Twitter handle:** @moyi_dang
- p.s. I have not added the query constructor in BUILTIN_TRANSLATORS in
this PR, I want to make changes to only one package at a time.
- [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: Bagatur <22008038+baskaryan@users.noreply.github.com>
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:** OpenAI recently introduced a "strict" parameter for
[structured outputs in their
API](https://openai.com/index/introducing-structured-outputs-in-the-api/).
An optional `strict` parameter has been added to
`create_openai_functions_agent()` and `create_openai_tools_agent()` so
developers can use this feature in those agents.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- [ ] **PR title**: community: add tests for ChatOctoAI
- [ ] **PR message**:
Description: Added unit tests for the ChatOctoAI class in the community
package to ensure proper validation and default values. These tests
verify the correct initialization of fields, the handling of missing
required parameters, and the proper setting of aliases.
Issue: N/A
Dependencies: None
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Thank you for contributing to LangChain!
community:premai[patch]: standardize init args
- updated `temperature` with Pydantic Field, updated the unit test.
- updated `max_tokens` with Pydantic Field, updated the unit test.
- updated `max_retries` with Pydantic Field, updated the unit test.
Related to #20085
---------
Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
Description: Moves yield to after callback for _astream for gigachat in
the community package
Issue: #16913
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- [x] **PR title**: "community: Patch enable to use Amazon OpenSearch
Serverless for Semantic Cache store"
- [x] **PR message**:
- **Description:** OpenSearchSemanticCache class support Amazon
OpenSearch Serverless for Semantic Cache store, it's only required to
pass auth(http_auth) parameter to initializer
- **Dependencies:** none
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Jinoos Lee <jinoos@amazon.com>
it fixes two issues:
### YGPTs are broken #25575
```
File ....conda/lib/python3.11/site-packages/langchain_community/embeddings/yandex.py:211, in _make_request(self, texts, **kwargs)
..
--> 211 res = stub.TextEmbedding(request, metadata=self._grpc_metadata) # type: ignore[attr-defined]
AttributeError: 'YandexGPTEmbeddings' object has no attribute '_grpc_metadata'
```
My gut feeling that #23841 is the cause.
I have to drop leading underscore from `_grpc_metadata` for quickfix,
but I just don't know how to do it _pydantic_ enough.
### minor issue:
if we use `api_key`, which is not the best practice the code fails with
```
File ~/git/...../python3.11/site-packages/langchain_community/embeddings/yandex.py:119, in YandexGPTEmbeddings.validate_environment(cls, values)
...
AttributeError: 'tuple' object has no attribute 'append'
```
- Added new integration test. But it requires YGPT env available and
active account. I don't know how int tests dis\enabled in CI.
- added small unit tests with mocks. Should be fine.
---------
Co-authored-by: mikhail-khludnev <mikhail_khludnev@rntgroup.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"
Support passing extra params when executing UC functions:
The params should be a dictionary with key EXECUTE_FUNCTION_ARG_NAME,
the assumption is that the function itself doesn't use such variable
name (starting and ending with double underscores), and if it does we
raise Exception.
If invalid params passing to the execute_statement, we raise Exception
as well.
- [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: Serena Ruan <serena.rxy@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "community: optimize xinference llm import"
- [ ] **PR message**:
- **Description:** from xinferece_client import RESTfulClient when there
is no importing xinference.
- **Dependencies:** xinferece_client
- **Why do so:** the total xinference(pip install xinference[all]) is
too heavy for installing, let alone it is useless for langchain user
except RESTfulClient. The modification has maintained consistency with
the xinference embeddings
[embeddings/xinference](../blob/master/libs/community/langchain_community/embeddings/xinference.py#L89).
[This
commit](d3ca2cc8c3)
has broken the moderation chain so we've faced a crash when migrating
the LangChain from v0.1 to v0.2.
The issue appears that the class attribute the code refers to doesn't
hold the value processed in the `validate_environment` method. We had
`extras={}` in this attribute, and it was casted to `True` when it
should've been `False`. Adding a simple assignment seems to resolve the
issue, though I'm not sure it's the right way.
---
---------
Co-authored-by: Michael Rubél <mrubel@oroinc.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
## 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>
**Description:**
Adds the 'score' returned by Pinecone to the
`PineconeHybridSearchRetriever` list of returned Documents.
There is currently no way to return the score when using Pinecone hybrid
search, so in this PR I include it by default.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
### Description
adds an init method to ChatDeepInfra to set the model_name attribute
accordings to the argument
### Issue
currently, the model_name specified by the user during initialization of
the ChatDeepInfra class is never set. Therefore, it always chooses the
default model (meta-llama/Llama-2-70b-chat-hf, however probably since
this is deprecated it always uses meta-llama/Llama-3-70b-Instruct). We
stumbled across this issue and fixed it as proposed in this pull
request. Feel free to change the fix according to your coding guidelines
and style, this is just a proposal and we want to draw attention to this
problem.
### Dependencies
no additional dependencies required
Feel free to contact me or @timo282 and @finitearth if you have any
questions.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** Make the hyperlink only appear once in the
extract_hyperlinks tool output. (for some websites output contains
meaningless '#' hyperlinks multiple times which will extend the tokens
of context window without any advantage)
**Issue:** None
**Dependencies:** None
Thank you for contributing to LangChain!
- [x] **PR title**: "langchain: Chains: query_constructor: add date time
parser"
- [x] **PR message**:
- **Description:** add date time parser to langchain Chains
query_constructor
- **Issue: https://github.com/langchain-ai/langchain/issues/25526
- [ ] **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.
Added Azure Search Access Token Authentication instead of API KEY auth.
Fixes Issue: https://github.com/langchain-ai/langchain/issues/24263
Dependencies: None
Twitter: @levalencia
@baskaryan
Could you please review? First time creating a PR that fixes some code.
---------
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>
This addresses the issue mentioned in #25702
I have updated the endpoint used in validating the endpoint API type in
the AzureMLBaseEndpoint class from `/v1/completions` to `/completions`
and `/v1/chat/completions` to `/chat/completions`.
Co-authored-by: = <=>
- **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>
- **Description:** Added langchain version while calling discover API
during both ingestion and retrieval
- **Issue:** NA
- **Dependencies:** NA
- **Tests:** NA
- **Docs** NA
---------
Co-authored-by: dristy.cd <dristy@clouddefense.io>
- **Description:** Updating source path and file path in Pebblo safe
loader for SharePoint apps during loading
- **Issue:** NA
- **Dependencies:** NA
- **Tests:** NA
- **Docs** NA
---------
Co-authored-by: dristy.cd <dristy@clouddefense.io>
- **PR message**: **Fix URL construction in newer Python versions**
- **Description:**
- Update the URL construction logic to use the .value attribute for
Routes enum members.
- This adjustment resolves an issue where the code worked correctly in
Python 3.9 but failed in Python 3.11.
- Clean up unused routes.
- **Issue:** NA
- **Dependencies:** NA
* 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>
Thank you for contributing to LangChain!
- [ ] **PR title**: "langchain-core: Fix type"
- The file to modify is located in
/libs/core/langchain_core/prompts/base.py
- [ ] **PR message**:
- **Description:** The change is a type for the inner input variable,
the type go from dict to Any. This change is required since the method
_validate input expects a type that is not only a dictionary.
- **Dependencies:** There are no dependencies for this change
- [ ] **Add tests and docs**:
1. A test is not needed. This error occurs because I overrode a portion
of the _validate_input method, which is causing a 'beartype' to raise an
error.
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>
This PR introduces adjustments to ensure compatibility with the recently
released preview version of [TiDB Serverless Vector
Search](https://tidb.cloud/ai), aiming to prevent user confusion.
- TiDB Vector now supports vector indexing with cosine and l2 distance
strategies, although inner_product remains unsupported.
- Changing the distance strategy is currently not supported, so the test
cased should be adjusted.
updated stop and request_timeout so they aliased to stop_sequences, and
timeout respectively. Added test that both continue to set the same
underlying attributes.
Related to
[20085](https://github.com/langchain-ai/langchain/issues/20085)
Co-authored-by: ccurme <chester.curme@gmail.com>
Issue: the `service` optional parameter was mentioned but not used.
Fix: added this parameter.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
## Description
There is a bug in the concatenation of embeddings obtained from MLflow
that does not conform to the type hint requested by the function.
``` python
def _query(self, texts: List[str]) -> List[List[float]]:
```
It is logical to expect a **List[List[float]]** for a **List[str]**.
However, the append method encapsulates the response in a global List.
To avoid this, the extend method should be used, which will add the
embeddings of all strings at the same list level.
## Testing
I have tried using OpenAI-ADA to obtain the embeddings, and the result
of executing this snippet is as follows:
``` python
embeds = await MlflowAIGatewayEmbeddings().aembed_documents(texts=["hi", "how are you?"])
print(embeds)
```
``` python
[[[-0.03512698, -0.020624293, -0.015343423, ...], [-0.021260535, -0.011461929, -0.00033121882, ...]]]
```
When in reality, the expected result should be:
``` python
[[-0.03512698, -0.020624293, -0.015343423, ...], [-0.021260535, -0.011461929, -0.00033121882, ...]]
```
The above result complies with the expected type hint:
**List[List[float]]** . As I mentioned, we can achieve that by using the
extend method instead of the append method.
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: ccurme <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"
Description: Simply pass kwargs to allow arguments like "where" to be
propagated
Issue: Previously, db.delete(where={}) wouldn't work for chroma
vectorstores
Dependencies: N/A
Twitter handle: N/A
- [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: Send both the query and query_embedding to the Databricks
index for hybrid search.
Issue: When using hybrid search with non-Databricks managed embedding we
currently don't pass both the embedding and query_text to the index.
Hybrid search requires both of these. This change fixes this issue for
both `similarity_search` and `similarity_search_by_vector`.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
# Issue
As of late July, Perplexity [no longer supports Llama 3
models](https://docs.perplexity.ai/changelog/introducing-new-and-improved-sonar-models).
# Description
This PR updates the default model and doc examples to reflect their
latest supported model. (Mostly updating the same places changed by
#23723.)
# Twitter handle
`@acompa_` on behalf of the team at Not Diamond. Check us out
[here](https://notdiamond.ai).
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
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>
Previously the code was able to only handle a single level of nesting
for subgraphs in mermaid. This change adds support for arbitrary nesting
of subgraphs.
Fix handling of pipeline_kwargs to prioritize class attribute defaults.
#19770
Co-authored-by: jaizo <manuel.jaiczay@polygons.at>
Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com>
This PR adds tiny improvements to the `GithubFileLoader` document loader
and its code sample, addressing the following issues:
1. Currently, the `file_extension` argument of `GithubFileLoader` does
not change its behavior at all.
1. The `GithubFileLoader` sample code in
`docs/docs/integrations/document_loaders/github.ipynb` does not work as
it stands.
The respective solutions I propose are the following:
1. Remove `file_extension` argument from `GithubFileLoader`.
1. Specify the branch as `master` (not the default `main`) and rename
`documents` as `document`.
---------
Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com>
When I used the Neo4JGraph enhanced_schema=True option, I ran into an
error because a prop min_size of None was compared numerically with an
int.
The fix I applied is similar to the pattern of skipping embeddings
elsewhere in the file.
Co-authored-by: ccurme <chester.curme@gmail.com>
**Description:**
LLM will stop generating text even in the middle of a sentence if
`finish_reason` is `length` (for OpenAI) or `stop_reason` is
`max_tokens` (for Anthropic).
To obtain longer outputs from LLM, we should call the message generation
API multiple times and merge the results into the text to circumvent the
API's output token limit.
The extra line breaks forced by the `merge_message_runs` function when
seamlessly merging messages can be annoying, so I added the option to
specify the chunk separator.
**Issue:**
No corresponding issues.
**Dependencies:**
No dependencies required.
**Twitter handle:**
@hanama_chem
https://x.com/hanama_chem
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
parsed_json is expected to be a list of dictionaries, but it seems to…
be a single dictionary instead.
This is at
libs/experimental/langchain_experimental/graph_transformers/llm.py
process process_response
Thank you for contributing to LangChain!
- [ ] **Bugfix**: "experimental: bugfix"
---------
Co-authored-by: based <basir.sedighi@nris.no>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- Cause chunks are joined by space, so they can't be found in text, and
the final `start_index` is very possibility to be -1.
- The simplest way is to use the natural index of the chunk as
`start_index`.
- **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>
[langchain_core] Fix UnionType type var replacement
- Added types.UnionType to typing.Union mapping
Type replacement cause `TypeError: 'type' object is not subscriptable`
if any of union type comes as function `_py_38_safe_origin` return
`types.UnionType` instead of `typing.Union`
```python
>>> from types import UnionType
>>> from typing import Union, get_origin
>>> type_ = get_origin(str | None)
>>> type_
<class 'types.UnionType'>
>>> UnionType[(str, None)]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'type' object is not subscriptable
>>> Union[(str, None)]
typing.Optional[str]
```
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Description: DeepInfra 500 errors have useful information in the text
field that isn't being exposed to the user. I updated the error message
to fix this.
As an example, this code
```
from langchain_community.chat_models import ChatDeepInfra
from langchain_core.messages import HumanMessage
model = "meta-llama/Meta-Llama-3-70B-Instruct"
deepinfra_api_token = "..."
model = ChatDeepInfra(model=model, deepinfra_api_token=deepinfra_api_token)
messages = [HumanMessage("All work and no play makes Jack a dull boy\n" * 9000)]
response = model.invoke(messages)
```
Currently gives this error:
```
langchain_community.chat_models.deepinfra.ChatDeepInfraException: DeepInfra Server: Error 500
```
This change would give the following error:
```
langchain_community.chat_models.deepinfra.ChatDeepInfraException: DeepInfra Server error status 500: {"error":{"message":"Requested input length 99009 exceeds maximum input length 8192"}}
```
**Refactor PebbloRetrievalQA**
- Created `APIWrapper` and moved API logic into it.
- Created smaller functions/methods for better readability.
- Properly read environment variables.
- Removed unused code.
- Updated models
**Issue:** NA
**Dependencies:** NA
**tests**: NA
**Refactor PebbloSafeLoader**
- Created `APIWrapper` and moved API logic into it.
- Moved helper functions to the utility file.
- Created smaller functions and methods for better readability.
- Properly read environment variables.
- Removed unused code.
**Issue:** NA
**Dependencies:** NA
**tests**: Updated
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>
Description: The neo4j driver can raise a SessionExpired error, which is
considered a retriable error. If a query fails with a SessionExpired
error, this change retries every query once. This change will make the
neo4j integration less flaky.
Twitter handle: noahmay_
### 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>
- **Description:** Updating metadata for sharepoint loader with full
path i.e., webUrl
- **Issue:** NA
- **Dependencies:** NA
- **Tests:** NA
- **Docs** NA
Co-authored-by: dristy.cd <dristy@clouddefense.io>
Co-authored-by: ccurme <chester.curme@gmail.com>
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
This will allow complextype metadata to be returned. the current
implementation throws error when dealing with nested metadata
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, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
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.
- **Description:** The following
[line](fd546196ef/libs/community/langchain_community/document_loaders/parsers/audio.py (L117))
in `OpenAIWhisperParser` returns a text object for some odd reason
despite the official documentation saying it should return `Transcript`
Instance which should have the text attribute. But for the example given
in the issue and even when I tried running on my own, I was directly
getting the text. The small PR accounts for that.
- **Issue:** : #25218
I was able to replicate the error even without the GenericLoader as
shown below and the issue was with `OpenAIWhisperParser`
```python
parser = OpenAIWhisperParser(api_key="sk-fxxxxxxxxx",
response_format="srt",
temperature=0)
list(parser.lazy_parse(Blob.from_path('path_to_file.m4a')))
```
…he prompt in the create_stuff_documents_chain
Thank you for contributing to LangChain!
- [ ] **PR title**: "langchain:add document_variable_name in the
function _validate_prompt in create_stuff_documents_chain"
- [ ] **PR message**:
- **Description:** add document_variable_name in the function
_validate_prompt in create_stuff_documents_chain
- **Issue:** according to the description of
create_stuff_documents_chain function, the parameter
document_variable_name can be used to override the "context" in the
prompt, but in the function, _validate_prompt it still use DOCUMENTS_KEY
to check if it is a valid prompt, the value of DOCUMENTS_KEY is always
"context", so even through the user use document_variable_name to
override it, the code still tries to check if "context" is in the
prompt, and finally it reports error. so I use document_variable_name to
replace DOCUMENTS_KEY, the default value of document_variable_name is
"context" which is same as DOCUMENTS_KEY, but it can be override by
users.
- **Dependencies:** none
- **Twitter handle:** https://x.com/xjr199703
- [ ] **Add tests and docs**: none
- [ ] **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>
- [x] NatbotChain: move to community, deprecate langchain version.
Update to use `prompt | llm | output_parser` instead of LLMChain.
- [x] LLMMathChain: deprecate + add langgraph replacement example to API
ref
- [x] HypotheticalDocumentEmbedder (retriever): update to use `prompt |
llm | output_parser` instead of LLMChain
- [x] FlareChain: update to use `prompt | llm | output_parser` instead
of LLMChain
- [x] ConstitutionalChain: deprecate + add langgraph replacement example
to API ref
- [x] LLMChainExtractor (document compressor): update to use `prompt |
llm | output_parser` instead of LLMChain
- [x] LLMChainFilter (document compressor): update to use `prompt | llm
| output_parser` instead of LLMChain
- [x] RePhraseQueryRetriever (retriever): update to use `prompt | llm |
output_parser` instead of LLMChain
Within the semantic chunker, when calling `_threshold_from_clusters`
there is the possibility for a divide by 0 error if the
`number_of_chunks` is equal to the length of `distances`.
Fix simply implements a check if these values match to prevent the error
and enable chunking to continue.
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.
- **Description:**
This PR will slove error messages about `ValueError` when use model with
history.
Detail in #24660.
#22933 causes that
`langchain_core.runnables.history.RunnableWithMessageHistory._get_output_messages`
miss type check of `output_val` if `output_val` is `False`. After
running `RunnableWithMessageHistory._is_not_async`, `output` is `False`.
249945a572/libs/core/langchain_core/runnables/history.py (L323-L334)15a36dd0a2/libs/core/langchain_core/runnables/history.py (L461-L471)
~~I suggest that `_get_output_messages` return empty list when
`output_val == False`.~~
- **Issue**:
- #24660
- **Dependencies:**: No Change.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
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**
Fix the asyncronous methods to retrieve documents from AzureSearch
VectorStore. The previous changes from [this
commit](ffe6ca986e)
create a similar code for the syncronous methods and the asyncronous
ones but the asyncronous client return an asyncronous iterator
"AsyncSearchItemPaged" as said in the issue #24740.
To solve this issue, the syncronous iterators in asyncronous methods
where changed to asyncronous iterators.
@chrislrobert said in [this
comment](https://github.com/langchain-ai/langchain/issues/24740#issuecomment-2254168302)
that there was a still a flaw due to `with` blocks that close the client
after each call. I removed this `with` blocks in the `async_client`
following the same pattern as the sync `client`.
In order to close up the connections, a __del__ method is included to
gently close up clients once the vectorstore object is destroyed.
**Issue:** #24740 and #24064
**Dependencies:** No new dependencies for this change
**Example notebook:** I created a notebook just to test the changes work
and gives the same results as the syncronous methods for vector and
hybrid search. With these changes, the asyncronous methods in the
retriever work as well.
**Lint and test**: Passes the tests and the linter
This adds `args_schema` member to `SearxSearchResults` tool. This member
is already present in the `SearxSearchRun` tool in the same file.
I was having `TypeError: Type is not JSON serializable:
AsyncCallbackManagerForToolRun` being thrown in langserve playground
when I was using `SearxSearchResults` tool as a part of chain there.
This fixes the issue, so the error is not raised anymore.
This is a example langserve app that was giving me the error, but it
works properly after the proposed fix:
```python
#!/usr/bin/env python
from fastapi import FastAPI
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables import RunnablePassthrough
from langchain_openai import ChatOpenAI
from langchain_community.utilities import SearxSearchWrapper
from langchain_community.tools.searx_search.tool import SearxSearchResults
from langserve import add_routes
template = """Answer the question based only on the following context:
{context}
Question: {question}
"""
prompt = ChatPromptTemplate.from_template(template)
model = ChatOpenAI()
s = SearxSearchWrapper(searx_host="http://localhost:8080")
search = SearxSearchResults(wrapper=s)
search_chain = (
{"context": search, "question": RunnablePassthrough()}
| prompt
| model
| StrOutputParser()
)
app = FastAPI()
add_routes(
app,
search_chain,
path="/chain",
)
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="localhost", port=8000)
```
- **Description:** Standardize SparkLLM, include:
- docs, the issue #24803
- to support stream
- update api url
- model init arg names, the issue #20085
- **Description:** This PR implements the `bind_tool` functionality for
ChatZhipuAI as requested by the user. ChatZhipuAI models support tool
calling according to the `OpenAI` tool format, as outlined in their
official documentation [here](https://open.bigmodel.cn/dev/api#glm-4).
- **Issue:** ##23868
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
- In the in ` embedding-3 ` and later models of Zhipu AI, it is
supported to specify the dimensions parameter of Embedding. Ref:
https://bigmodel.cn/dev/api#text_embedding-3 .
- Add test case for `embedding-3` model by assigning dimensions.
This PR deprecates the beta upsert APIs in vectorstore.
We'll introduce them in a V2 abstraction instead to keep the existing
vectorstore implementations lighter weight.
The main problem with the existing APIs is that it's a bit more
challenging to
implement the correct behavior w/ respect to IDs since ID can be present
in
both the function signature and as an optional attribute on the document
object.
But VectorStores that pass the standard tests should have implemented
the semantics properly!
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR gets rid `root_validators(allow_reuse=True)` logic used in
EdenAI Tool in preparation for pydantic 2 upgrade.
- add another test to secret_from_env_factory
**Description:**
The get time point method in the _consume() method of
core.rate_limiters.InMemoryRateLimiter uses time.time(), which can be
affected by system time backwards. Therefore, it is recommended to use
the monotonically increasing monotonic() to obtain the time
```python
with self._consume_lock:
now = time.time() # time.time() -> time.monotonic()
# initialize on first call to avoid a burst
if self.last is None:
self.last = now
elapsed = now - self.last # when use time.time(), elapsed may be negative when system time backwards
```
Thank you for contributing to LangChain!
- [X] **PR title**: "community: fix valueerror mentions wrong argument
missing"
- 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:** when faiss.py has a None relevance_score_fn it raises
a ValueError that says a normalize_fn_score argument is needed.
Co-authored-by: ccurme <chester.curme@gmail.com>
**Description:** This minor PR aims to add `llm_extraction` to Firecrawl
loader. This feature is supported on API and PythonSDK, but the
langchain loader omits adding this to the response.
**Twitter handle:** [scalable_pizza](https://x.com/scalablepizza)
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- 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>
Change all usages of __fields__ with get_fields adapter merged into
langchain_core.
Code mod generated using the following grit pattern:
```
engine marzano(0.1)
language python
`$X.__fields__` => `get_fields($X)` where {
add_import(source="langchain_core.utils.pydantic", name="get_fields")
}
```
Migrate pydantic extra to literals
Upgrade to using a literal for specifying the extra which is the
recommended approach in pydantic 2.
This works correctly also in pydantic v1.
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel, extra="forbid"):
x: int
Foo(x=5, y=1)
```
And
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel):
x: int
class Config:
extra = "forbid"
Foo(x=5, y=1)
```
## Enum -> literal using grit pattern:
```
engine marzano(0.1)
language python
or {
`extra=Extra.allow` => `extra="allow"`,
`extra=Extra.forbid` => `extra="forbid"`,
`extra=Extra.ignore` => `extra="ignore"`
}
```
Resorted attributes in config and removed doc-string in case we will
need to deal with going back and forth between pydantic v1 and v2 during
the 0.3 release. (This will reduce merge conflicts.)
## Sort attributes in Config:
```
engine marzano(0.1)
language python
function sort($values) js {
return $values.text.split(',').sort().join("\n");
}
class_definition($name, $body) as $C where {
$name <: `Config`,
$body <: block($statements),
$values = [],
$statements <: some bubble($values) assignment() as $A where {
$values += $A
},
$body => sort($values),
}
```
Add a utility that can be used as a default factory
The goal will be to start migrating from of the pydantic models to use
`from_env` as a default factory if possible.
```python
from pydantic import Field, BaseModel
from langchain_core.utils import from_env
class Foo(BaseModel):
name: str = Field(default_factory=from_env('HELLO'))
```
Change all usages of __fields__ with get_fields adapter merged into
langchain_core.
Code mod generated using the following grit pattern:
```
engine marzano(0.1)
language python
`$X.__fields__` => `get_fields($X)` where {
add_import(source="langchain_core.utils.pydantic", name="get_fields")
}
```
Upgrade to using a literal for specifying the extra which is the
recommended approach in pydantic 2.
This works correctly also in pydantic v1.
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel, extra="forbid"):
x: int
Foo(x=5, y=1)
```
And
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel):
x: int
class Config:
extra = "forbid"
Foo(x=5, y=1)
```
## Enum -> literal using grit pattern:
```
engine marzano(0.1)
language python
or {
`extra=Extra.allow` => `extra="allow"`,
`extra=Extra.forbid` => `extra="forbid"`,
`extra=Extra.ignore` => `extra="ignore"`
}
```
Resorted attributes in config and removed doc-string in case we will
need to deal with going back and forth between pydantic v1 and v2 during
the 0.3 release. (This will reduce merge conflicts.)
## Sort attributes in Config:
```
engine marzano(0.1)
language python
function sort($values) js {
return $values.text.split(',').sort().join("\n");
}
class_definition($name, $body) as $C where {
$name <: `Config`,
$body <: block($statements),
$values = [],
$statements <: some bubble($values) assignment() as $A where {
$values += $A
},
$body => sort($values),
}
```
Upgrade to using a literal for specifying the extra which is the
recommended approach in pydantic 2.
This works correctly also in pydantic v1.
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel, extra="forbid"):
x: int
Foo(x=5, y=1)
```
And
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel):
x: int
class Config:
extra = "forbid"
Foo(x=5, y=1)
```
## Enum -> literal using grit pattern:
```
engine marzano(0.1)
language python
or {
`extra=Extra.allow` => `extra="allow"`,
`extra=Extra.forbid` => `extra="forbid"`,
`extra=Extra.ignore` => `extra="ignore"`
}
```
Resorted attributes in config and removed doc-string in case we will
need to deal with going back and forth between pydantic v1 and v2 during
the 0.3 release. (This will reduce merge conflicts.)
## Sort attributes in Config:
```
engine marzano(0.1)
language python
function sort($values) js {
return $values.text.split(',').sort().join("\n");
}
class_definition($name, $body) as $C where {
$name <: `Config`,
$body <: block($statements),
$values = [],
$statements <: some bubble($values) assignment() as $A where {
$values += $A
},
$body => sort($values),
}
```
For business subscription the status is STOCKSBUSINESS not OK
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
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>
- **Description:** Instantiating `GPT4AllEmbeddings` with no
`gpt4all_kwargs` argument raised a `ValidationError`. Root cause: #21238
added the capability to pass `gpt4all_kwargs` through to the `GPT4All`
instance via `Embed4All`, but broke code that did not specify a
`gpt4all_kwargs` argument.
- **Issue:** #25119
- **Dependencies:** None
- **Twitter handle:** [`@metadaddy`](https://twitter.com/metadaddy)
This PR does an aesthetic sort of the config object attributes. This
will make it a bit easier to go back and forth between pydantic v1 and
pydantic v2 on the 0.3.x branch
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:**
In this PR, I am adding three stock market tools from
financialdatasets.ai (my API!):
- get balance sheets
- get cash flow statements
- get income statements
Twitter handle: [@virattt](https://twitter.com/virattt)
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Example: "community: Added bedrock 3-5 sonnet cost detials for
BedrockAnthropicTokenUsageCallbackHandler"
- [ ] **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: Naval Chand <navalchand@192.168.1.36>
- description: I remove the limitation of mandatory existence of
`QIANFAN_AK` and default model name which langchain uses cause there is
already a default model nama underlying `qianfan` SDK powering langchain
component.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- community: Allow authorization to Confluence with bearer token
- **Description:** Allow authorization to Confluence with [Personal
Access
Token](https://confluence.atlassian.com/enterprise/using-personal-access-tokens-1026032365.html)
by checking for the keys `['client_id', token: ['access_token',
'token_type']]`
- **Issue:**
Currently the following error occurs when using an personal access token
for authorization.
```python
loader = ConfluenceLoader(
url=os.getenv('CONFLUENCE_URL'),
oauth2={
'token': {"access_token": os.getenv("CONFLUENCE_ACCESS_TOKEN"), "token_type": "bearer"},
'client_id': 'client_id',
},
page_ids=['12345678'],
)
```
```
ValueError: Error(s) while validating input: ["You have either omitted require keys or added extra keys to the oauth2 dictionary. key values should be `['access_token', 'access_token_secret', 'consumer_key', 'key_cert']`"]
```
With this PR the loader runs as expected.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
