- **Description:** change to do the batch embedding server side and not
client side
- **Twitter handle:** @wildagsx
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Description:
This fixes an issue that mistakenly created in
https://github.com/langchain-ai/langchain/pull/27253. The issue
currently exists only in `langchain-community==0.3.4`.
Test cases were added to prevent this issue in the future.
Co-authored-by: Erick Friis <erick@langchain.dev>
### Description:
This PR sets a default value of `output_token_limit = 4000` for the
`PowerBIToolkit` to fix the unintentionally validation error.
### Problem:
When attempting to run a code snippet from [Langchain's PowerBI toolkit
documentation](https://python.langchain.com/v0.1/docs/integrations/toolkits/powerbi/)
to interact with a `PowerBIDataset`, the following error occurs:
```
pydantic.v1.error_wrappers.ValidationError: 1 validation error for QueryPowerBITool
output_token_limit
none is not an allowed value (type=type_error.none.not_allowed)
```
### Root Cause:
The issue arises because when creating a `QueryPowerBITool`, the
`output_token_limit` parameter is unintentionally set to `None`, which
is the current default for `PowerBIToolkit`. However, `QueryPowerBITool`
expects a default value of `4000` for `output_token_limit`. This
unintended override causes the error.
17659ca2cd/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py (L63)17659ca2cd/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py (L72-L79)17659ca2cd/libs/community/langchain_community/tools/powerbi/tool.py (L39)
### Solution:
To resolve this, the default value of `output_token_limit` is now
explicitly set to `4000` in `PowerBIToolkit` to prevent the accidental
assignment of `None`.
Co-authored-by: ccurme <chester.curme@gmail.com>
**Description:**
This PR addresses an issue in the CSVLoader example where data is not
defined, causing a NameError. The line `data = loader.load()` is added
to correctly assign the output of loader.load() to the data variable.
- **Description:**
Currently CommaSeparatedListOutputParser can't handle strings that may
contain commas within a column. It would parse any commas as the
delimiter.
Ex.
"foo, foo2", "bar", "baz"
It will create 4 columns: "foo", "foo2", "bar", "baz"
This should be 3 columns:
"foo, foo2", "bar", "baz"
- **Dependencies:**
Added 2 additional imports, but they are built in python packages.
import csv
from io import StringIO
- **Twitter handle:** @jkyamog
- [ ] **Add tests and docs**:
1. added simple unit test test_multiple_items_with_comma
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Thank you for contributing to LangChain!
Update references in Databricks integration page to reference our new
partner package databricks-langchain
https://github.com/databricks/databricks-ai-bridge/tree/main/integrations/langchain
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: Prithvi Kannan <prithvi.kannan@databricks.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "core: use friendlier names for duplicated nodes in
mermaid output"
- **Description:** When generating the Mermaid visualization of a chain,
if the chain had multiple nodes of the same type, the reid function
would replace their names with the UUID node_id. This made the generated
graph difficult to understand. This change deduplicates the nodes in a
chain by appending an index to their names.
- **Issue:** None
- **Discussion:**
https://github.com/langchain-ai/langchain/discussions/27714
- **Dependencies:** None
- [ ] **Add tests and docs**:
- Currently this functionality is not covered by unit tests, happy to
add tests if you'd like
- [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.
# Example Code:
```python
from langchain_core.runnables import RunnablePassthrough
def fake_llm(prompt: str) -> str: # Fake LLM for the example
return "completion"
runnable = {
'llm1': fake_llm,
'llm2': fake_llm,
} | RunnablePassthrough.assign(
total_chars=lambda inputs: len(inputs['llm1'] + inputs['llm2'])
)
print(runnable.get_graph().draw_mermaid(with_styles=False))
```
# Before
```mermaid
graph TD;
Parallel_llm1_llm2_Input --> 0b01139db5ed4587ad37964e3a40c0ec;
0b01139db5ed4587ad37964e3a40c0ec --> Parallel_llm1_llm2_Output;
Parallel_llm1_llm2_Input --> a98d4b56bd294156a651230b9293347f;
a98d4b56bd294156a651230b9293347f --> Parallel_llm1_llm2_Output;
Parallel_total_chars_Input --> Lambda;
Lambda --> Parallel_total_chars_Output;
Parallel_total_chars_Input --> Passthrough;
Passthrough --> Parallel_total_chars_Output;
Parallel_llm1_llm2_Output --> Parallel_total_chars_Input;
```
# After
```mermaid
graph TD;
Parallel_llm1_llm2_Input --> fake_llm_1;
fake_llm_1 --> Parallel_llm1_llm2_Output;
Parallel_llm1_llm2_Input --> fake_llm_2;
fake_llm_2 --> Parallel_llm1_llm2_Output;
Parallel_total_chars_Input --> Lambda;
Lambda --> Parallel_total_chars_Output;
Parallel_total_chars_Input --> Passthrough;
Passthrough --> Parallel_total_chars_Output;
Parallel_llm1_llm2_Output --> Parallel_total_chars_Input;
```
PR title: “langchain: add batch request support for text-embedding-v3
model”
PR message:
• Description: This PR introduces batch request support for the
text-embedding-v3 model within LangChain. The new functionality allows
users to process multiple text inputs in a single request, improving
efficiency and performance for high-volume applications.
• Issue: This PR addresses #<issue_number> (if applicable).
• Dependencies: No new external dependencies are required for this
change.
• Twitter handle: If announced on Twitter, please mention me at
@yourhandle.
Add tests and docs:
1. Added unit tests to cover the batch request functionality, ensuring
it operates without requiring network access.
2. Included an example notebook demonstrating the batch request feature,
located in docs/docs/integrations.
Lint and test: All required formatting and linting checks have been
performed using make format and make lint. The changes have been
verified with make test to ensure compatibility.
Additional notes:
• The changes are fully backwards compatible.
• No modifications were made to pyproject.toml, ensuring no new
dependencies were added.
• The update only affects the langchain package and does not involve
other packages.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
…ING} {code: Neo.ClientNotification.Statement.FeatureDeprecationWarning}
{category: DEPRECATION} {title: This feature is deprecated and will be
removed in future versions.} {description: CALL subquery without a
variable scope clause is now deprecated." this warning
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
- [ ] **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: putao520 <putao520@putao282.com>
The metadata["source"] value for the web paths was being set to
temporary path (/tmp).
Fixed it by creating a new variable self.original_file_path, which will
store the original path.
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
- Example: "community: add foobar LLM"
- [ ] **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.
I will keep this PR as small as the changes made.
**Description:** fixes a fatal bug syntax error in
AzureCosmosDBNoSqlVectorSearch
**Issue:** #27269#25468
**Description:**
Update the wrapper to support the Polygon API if not you get an error. I
keeped `STOCKBUSINESS` for retro-compatbility with older endpoints /
other uses
Old Code:
```
if status not in ("OK", "STOCKBUSINESS"):
raise ValueError(f"API Error: {data}")
```
API Respond:
```
API Error: {'results': {'P': 0.22, 'S': 0, 'T': 'ZOM', 'X': 5, 'p': 0.123, 'q': 0, 's': 200, 't': 1729614422813395456, 'x': 1, 'z': 1}, 'status': 'STOCKSBUSINESS', 'request_id': 'XXXXXX'}
```
- **Issue:** N/A Polygon API update
- **Dependencies:** N/A
- **Twitter handle:** @wgcv
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
- **Description:** add missing tool_calls kwargs of delta message in
openai adapter, then tool call will work correctly via adapter's stream
chat completion
- **Issue:** Fixes
https://github.com/langchain-ai/langchain/issues/25436
- **Dependencies:** None
- **Description:** Change `MoonshotCommon.client` type from
`_MoonshotClient` to `Any`.
- **Issue:** Fix the issue #27058
- **Dependencies:** No
- **Twitter handle:** TaoWang2218
In PR #17100, the implementation for Moonshot was added, which defined
two classes:
- `MoonshotChat(MoonshotCommon, ChatOpenAI)` in
`langchain_community.chat_models.moonshot`;
- Here, `validate_environment()` assigns **client** as
`openai.OpenAI().chat.completions`
- Note that **client** here is actually a member variable defined in
`ChatOpenAI`;
- `MoonshotCommon` in `langchain_community.llms.moonshot`;
- And here, `validate_environment()` assigns **_client** as
`_MoonshotClient`;
- Note that this is the underscored **_client**, which is defined within
`MoonshotCommon` itself;
At this time, there was no conflict between the two, one being `client`
and the other `_client`.
However, in PR #25878 which fixed#24390, `_client` in `MoonshotCommon`
was changed to `client`. Since then, a conflict in the definition of
`client` has arisen between `MoonshotCommon` and `MoonshotChat`, which
caused `pydantic` validation error.
To fix this issue, the type of `client` in `MoonshotCommon` should be
changed to `Any`.
Signed-off-by: Tao Wang <twang2218@gmail.com>
