when running AsyncCallbackManagerForChainRun (from
langchain.callbacks.manager import AsyncCallbackManagerForChainRun),
provided default values for tags and inheritable_tages of empty lists in
manager.py BaseRunManager.
- Description: In manager.py, `BaseRunManager`, default values were
provided for the `__init__` args `tags` and `inheritable_tags`. They
default to empty lists (`[]`).
- Issue: When trying to use Nvidia NeMo Guardrails with LangChain, the
following exception was raised:
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#### Add streaming only final async iterator of agent
This callback returns an async iterator and only streams the final
output of an agent.
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Added parentheses to ensure the division operation is performed before
multiplication. This now correctly calculates the cost by dividing the
number of tokens by 1000 first (to get the cost per token), and then
multiplies it with the model's cost per 1k tokens @agola11
- Description: Bug Fix - Added a step variable to keep track of prompts
- Issue: Bug from internal Arize testing - The prompts and responses
that are ingested were not mapped correctly
- Dependencies: N/A
Since this model name is not there in the list MODEL_COST_PER_1K_TOKENS,
when we use get_openai_callback(), for gpt 3.5 model in Azure AI, we do
not get the cost of the tokens. This will fix this issue
#### Who can review?
@hwchase17
@agola11
Co-authored-by: rajib76 <rajib76@yahoo.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
This PR targets the `API Reference` documentation.
- Several classes and functions missed `docstrings`. These docstrings
were created.
- In several places this
```
except ImportError:
raise ValueError(
```
was replaced to
```
except ImportError:
raise ImportError(
```
A new implementation of `StreamlitCallbackHandler`. It formats Agent
thoughts into Streamlit expanders.
You can see the handler in action here:
https://langchain-mrkl.streamlit.app/
Per a discussion with Harrison, we'll be adding a
`StreamlitCallbackHandler` implementation to an upcoming
[Streamlit](https://github.com/streamlit/streamlit) release as well, and
will be updating it as we add new LLM- and LangChain-specific features
to Streamlit.
The idea with this PR is that the LangChain `StreamlitCallbackHandler`
will "auto-update" in a way that keeps it forward- (and backward-)
compatible with Streamlit. If the user has an older Streamlit version
installed, the LangChain `StreamlitCallbackHandler` will be used; if
they have a newer Streamlit version that has an updated
`StreamlitCallbackHandler`, that implementation will be used instead.
(I'm opening this as a draft to get the conversation going and make sure
we're on the same page. We're really excited to land this into
LangChain!)
#### Who can review?
@agola11, @hwchase17
### Integration of Infino with LangChain for Enhanced Observability
This PR aims to integrate [Infino](https://github.com/infinohq/infino),
an open source observability platform written in rust for storing
metrics and logs at scale, with LangChain, providing users with a
streamlined and efficient method of tracking and recording LangChain
experiments. By incorporating Infino into LangChain, users will be able
to gain valuable insights and easily analyze the behavior of their
language models.
#### Please refer to the following files related to integration:
- `InfinoCallbackHandler`: A [callback
handler](https://github.com/naman-modi/langchain/blob/feature/infino-integration/langchain/callbacks/infino_callback.py)
specifically designed for storing chain responses within Infino.
- Example `infino.ipynb` file: A comprehensive notebook named
[infino.ipynb](https://github.com/naman-modi/langchain/blob/feature/infino-integration/docs/extras/modules/callbacks/integrations/infino.ipynb)
has been included to guide users on effectively leveraging Infino for
tracking LangChain requests.
- [Integration
Doc](https://github.com/naman-modi/langchain/blob/feature/infino-integration/docs/extras/ecosystem/integrations/infino.mdx)
for Infino integration.
By integrating Infino, LangChain users will gain access to powerful
visualization and debugging capabilities. Infino enables easy tracking
of inputs, outputs, token usage, execution time of LLMs. This
comprehensive observability ensures a deeper understanding of individual
executions and facilitates effective debugging.
Co-authors: @vinaykakade @savannahar68
---------
Co-authored-by: Vinay Kakade <vinaykakade@gmail.com>
Arize released a new Generative LLM Model Type, adjusting the callback
function to new logging.
Added arize imports, please delete if not necessary.
Specifically, this change makes sure that the prompt and response pairs
from LangChain agents are logged into Arize as a Generative LLM model,
instead of our previous categorical model. In order to do this, the
callback functions collects the necessary data and passes the data into
Arize using Python Pandas SDK.
Arize library, specifically pandas.logger is an additional dependency.
Notebook For Test:
https://docs.arize.com/arize/resources/integrations/langchain
Who can review?
Tag maintainers/contributors who might be interested:
@hwchase17 - project lead
Tracing / Callbacks
@agola11
@agola11
Issue
#6193
I added the new pricing for the new models.
Also, now gpt-3.5-turbo got split into "input" and "output" pricing. It
currently does not support that.
In LangChain, all module classes are enumerated in the `__init__.py`
file of the correspondent module. But some classes were missed and were
not included in the module `__init__.py`
This PR:
- added the missed classes to the module `__init__.py` files
- `__init__.py:__all_` variable value (a list of the class names) was
sorted
- `langchain.tools.sql_database.tool.QueryCheckerTool` was renamed into
the `QuerySQLCheckerTool` because it conflicted with
`langchain.tools.spark_sql.tool.QueryCheckerTool`
- changes to `pyproject.toml`:
- added `pgvector` to `pyproject.toml:extended_testing`
- added `pandas` to
`pyproject.toml:[tool.poetry.group.test.dependencies]`
- commented out the `streamlit` from `collbacks/__init__.py`, It is
because now the `streamlit` requires Python >=3.7, !=3.9.7
- fixed duplicate names in `tools`
- fixed correspondent ut-s
#### Who can review?
@hwchase17
@dev2049
Hi again @agola11! 🤗
## What's in this PR?
After playing around with different chains we noticed that some chains
were using different `output_key`s and we were just handling some, so
we've extended the support to any output, either if it's a Python list
or a string.
Kudos to @dvsrepo for spotting this!
---------
Co-authored-by: Daniel Vila Suero <daniel@argilla.io>
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Fixes # (issue)
#### Before submitting
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Obey `handler.raise_error` in `_ahandle_event_for_handler`
Exceptions for async callbacks were only logged as warnings, also when
`raise_error = True`
#### Who can review?
@hwchase17
@agola11
# like
[StdoutCallbackHandler](https://github.com/hwchase17/langchain/blob/master/langchain/callbacks/stdout.py),
but writes to a file
When running experiments I have found myself wanting to log the outputs
of my chains in a more lightweight way than using WandB tracing. This PR
contributes a callback handler that writes to file what
`StdoutCallbackHandler` would print.
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## Example Notebook
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See the included `filecallbackhandler.ipynb` notebook for usage. Would
it be better to include this notebook under `modules/callbacks` or under
`integrations/`?
## Who can review?
Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:
@agola11
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# Make FinalStreamingStdOutCallbackHandler more robust by ignoring new
lines & white spaces
`FinalStreamingStdOutCallbackHandler` doesn't work out of the box with
`ChatOpenAI`, as it tokenized slightly differently than `OpenAI`. The
response of `OpenAI` contains the tokens `["\nFinal", " Answer", ":"]`
while `ChatOpenAI` contains `["Final", " Answer", ":"]`.
This PR make `FinalStreamingStdOutCallbackHandler` more robust by
ignoring new lines & white spaces when determining if the answer prefix
has been reached.
Fixes#5433
## Who can review?
Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:
Tracing / Callbacks
- @agola11
Twitter: [@UmerHAdil](https://twitter.com/@UmerHAdil) | Discord:
RicChilligerDude#7589
William FH