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This PR replaces the previous `Intent` check with the new `Prompt
Safety` check. The logic and steps to enable chain moderation via the
Amazon Comprehend service, allowing you to detect and redact PII, Toxic,
and Prompt Safety information in the LLM prompt or answer remains
unchanged.
This implementation updates the code and configuration types with
respect to `Prompt Safety`.
### Usage sample
```python
from langchain_experimental.comprehend_moderation import (BaseModerationConfig,
ModerationPromptSafetyConfig,
ModerationPiiConfig,
ModerationToxicityConfig
)
pii_config = ModerationPiiConfig(
labels=["SSN"],
redact=True,
mask_character="X"
)
toxicity_config = ModerationToxicityConfig(
threshold=0.5
)
prompt_safety_config = ModerationPromptSafetyConfig(
threshold=0.5
)
moderation_config = BaseModerationConfig(
filters=[pii_config, toxicity_config, prompt_safety_config]
)
comp_moderation_with_config = AmazonComprehendModerationChain(
moderation_config=moderation_config, #specify the configuration
client=comprehend_client, #optionally pass the Boto3 Client
verbose=True
)
template = """Question: {question}
Answer:"""
prompt = PromptTemplate(template=template, input_variables=["question"])
responses = [
"Final Answer: A credit card number looks like 1289-2321-1123-2387. A fake SSN number looks like 323-22-9980. John Doe's phone number is (999)253-9876.",
"Final Answer: This is a really shitty way of constructing a birdhouse. This is fucking insane to think that any birds would actually create their motherfucking nests here."
]
llm = FakeListLLM(responses=responses)
llm_chain = LLMChain(prompt=prompt, llm=llm)
chain = (
prompt
| comp_moderation_with_config
| {llm_chain.input_keys[0]: lambda x: x['output'] }
| llm_chain
| { "input": lambda x: x['text'] }
| comp_moderation_with_config
)
try:
response = chain.invoke({"question": "A sample SSN number looks like this 123-456-7890. Can you give me some more samples?"})
except Exception as e:
print(str(e))
else:
print(response['output'])
```
### Output
```python
> Entering new AmazonComprehendModerationChain chain...
Running AmazonComprehendModerationChain...
Running pii Validation...
Running toxicity Validation...
Running prompt safety Validation...
> Finished chain.
> Entering new AmazonComprehendModerationChain chain...
Running AmazonComprehendModerationChain...
Running pii Validation...
Running toxicity Validation...
Running prompt safety Validation...
> Finished chain.
Final Answer: A credit card number looks like 1289-2321-1123-2387. A fake SSN number looks like XXXXXXXXXXXX John Doe's phone number is (999)253-9876.
```
---------
Co-authored-by: Jha <nikjha@amazon.com>
Co-authored-by: Anjan Biswas <anjanavb@amazon.com>
Co-authored-by: Anjan Biswas <84933469+anjanvb@users.noreply.github.com>
**Description:**
This PR adds support for the [Pro version of Titan Takeoff
Server](https://docs.titanml.co/docs/category/pro-features). Users of
the Pro version will have to import the TitanTakeoffPro model, which is
different from TitanTakeoff.
**Issue:**
Also minor fixes to docs for Titan Takeoff (Community version)
**Dependencies:**
No additional dependencies
**Twitter handle:** @becoming_blake
@baskaryan @hwchase17
- **Description:** Super simple fix for colab link on
code_understanding.ipynb,
- **Issue:** not applicable
- **Dependencies:** none,
- **Tag maintainer:** ,
- **Twitter handle:** @kengoodridge
- **Description:**
This PR adds `allowd_operators` property to `QdrantTranslator` to fix
the `TypeError: can only join an iterable` bug. This property is
required in `get_query_constructor_prompt` in
`query_constructor\base.py`:
```
allowed_operators=" | ".join(allowed_operators),
```
- **Issue:**
#12061
---------
Co-authored-by: XIE Qihui <qihui.xie@bopufund.com>
Problem statement:
In the `integrations/llms` and `integrations/chat` pages, we have a
sidebar with ToC, and we also have a ToC at the end of the page.
The ToC at the end of the page is not necessary, and it is confusing
when we mix the index page styles; moreover, it requires manual work.
So, I removed ToC at the end of the page (it was discussed with and
approved by @baskaryan)
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
If user function is wrapped as a traceable function, this will help hand
off the trace between the two.
Also update handling fields to reflect optional values
- **Description**: Fix for the SPARQL QA chain: fixed SPARQL queries for
retrieving information about relations in the graph to create a textual
description of the schema for the language model. This should resolve
#8907
- **Issue**: #8907
- **Dependencies**: None
- **Tag maintainer**: @baskaryan, @hwchase17
**Description:** When llms output leading or trailing whitespace for xml
(when using XMLOutputParser) the parser would raise a `ValueError: Could
not parse output: ...`. However, leading or trailing whitespace are
"ignorable" in the sense of XML standard.
**Issue:** I did not find an issue related.
**Dependencies:** None
**Tag maintainer:**
**Twitter handle:** donatoaz
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
Done, updated unit test and ran `make docker_test`.
- **Description:** Response parser for arcee retriever,
- **Issue:** follow-up pr on #11578 and
[discussion](https://github.com/arcee-ai/arcee-python/issues/15#issuecomment-1759874053),
- **Dependencies:** NA
This pr implements a parser for the response from ArceeRetreiver to
convert to langchain `Document`. This closes the loop of generation and
retrieval for Arcee DALMs in langchain.
The reference for the response parser is
[api-docs:retrieve](https://api.arcee.ai/docs#/v2/retrieve_model)
Attaching screenshot of working implementation:
<img width="1984" alt="Screenshot 2023-10-25 at 7 42 34 PM"
src="https://github.com/langchain-ai/langchain/assets/65639964/026987b9-34b2-4e4b-b87d-69fcd0c6641a">
\*api key deleted
---
Successful tests, lints, etc.
```shell
Re-run pytest with --snapshot-update to delete unused snapshots.
==================================================================================================================== slowest 5 durations =====================================================================================================================
1.56s call tests/unit_tests/schema/runnable/test_runnable.py::test_retrying
0.63s call tests/unit_tests/schema/runnable/test_runnable.py::test_map_astream
0.33s call tests/unit_tests/schema/runnable/test_runnable.py::test_map_stream_iterator_input
0.30s call tests/unit_tests/schema/runnable/test_runnable.py::test_map_astream_iterator_input
0.20s call tests/unit_tests/indexes/test_indexing.py::test_cleanup_with_different_batchsize
======================================================================================================= 1265 passed, 270 skipped, 32 warnings in 6.55s =======================================================================================================
[ "." = "" ] || poetry run black .
All done! ✨🍰✨
1871 files left unchanged.
[ "." = "" ] || poetry run ruff --select I --fix .
./scripts/check_pydantic.sh .
./scripts/check_imports.sh
poetry run ruff .
[ "." = "" ] || poetry run black . --check
All done! ✨🍰✨
1871 files would be left unchanged.
[ "." = "" ] || poetry run mypy .
Success: no issues found in 1868 source files
poetry run codespell --toml pyproject.toml
poetry run codespell --toml pyproject.toml -w
```
Co-authored-by: Shubham Kushwaha <shwu@Shubhams-MacBook-Pro.local>
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tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
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/extras`
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If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
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<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
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maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
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/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
**Description:**
Documents further usage of RetrievalQAWithSourcesChain in an existing
test. I'd not found much documented usage of RetrievalQAWithSourcesChain
and how to get the sources out. This additional code will hopefully be
useful to other potential users of this retriever.
**Issue:** No raised issue
**Dependencies:** No new dependencies needed to run the test (it already
needs `open-ai`, `faiss-cpu` and `unstructured`).
Note - `make lint` showed 8 linting errors in unrelated files
---------
Co-authored-by: richarda23 <richard.c.adams@infinityworks.com>
If I go traceable -> runnable when the project is manually specified,
the runnable wont be logged. This makes sure the session/project is
threaded through appropriately.
This PR adds a data [E2B's](https://e2b.dev/) analysis/code interpreter
sandbox as a tool
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Jakub Novak <jakub@e2b.dev>
- Move Document AI provider to the Google provider page
- Change Vertex AI Matching Engine to Vector Search
- Change references from GCP to Google Cloud
- Add Gmail chat loader to Google provider page
- Change Serper page title to "Serper - Google Search API" since it is
not a Google product.
