AI Guard Response Tracing for LangChain in Python

An example Python app demonstrating how to integrate Pangea's AI Guard service into a LangChain app to monitor and sanitize LLM generations.

Prerequisites

• Python v3.12 or greater.
• pip v24.2 or uv v0.4.29.
• A Pangea account with AI Guard enabled.
• An OpenAI API key.

Setup

git clone https://github.com/pangeacyber/langchain-python-aig-response-tracing.git
cd langchain-python-aig-response-tracing

If using pip:

python -m venv .venv
source .venv/bin/activate
pip install .

Or, if using uv:

uv sync
source .venv/bin/activate

The sample can then be executed with:

python -m langchain_aig_response_tracing "What is MFA?"

Usage

Usage: python -m langchain_aig_response_tracing [OPTIONS] PROMPT

Options:
  --model TEXT               OpenAI model.  [default: gpt-4o-mini; required]
  --ai-guard-token SECRET    Pangea AI Guard API token. May also be set via
                             the `PANGEA_AI_GUARD_TOKEN` environment variable.
                             [required]
  --ai-guard-config-id TEXT  Pangea AI Guard configuration ID.
  --pangea-domain TEXT       Pangea API domain. May also be set via the
                             `PANGEA_DOMAIN` environment variable.  [default:
                             aws.us.pangea.cloud; required]
  --openai-api-key SECRET    OpenAI API key. May also be set via the
                             `OPENAI_API_KEY` environment variable.
                             [required]
  --help                     Show this message and exit.

Example Input/Output

AI Guard will protect against leaking credentials like Pangea API tokens. The easiest way to demonstrate this would be to have the LLM repeat a given (fake) API token:

python -m langchain_aig_response_tracing "Echo 'pts_testtesttesttesttesttesttesttest' back."

The output after AI Guard is:

************************************

Audit logs can be viewed at the Secure Audit Log Viewer.