chatagent-root
Verified Safeby PolecatWorks
Overview
Build and deploy an AI-powered conversational bot for Microsoft Teams, leveraging LangChain/LangGraph for LLM interaction and tool execution.
Installation
poetry run chatbot start --config <path/to/config.yaml> --secrets <path/to/secrets_dir>Environment Variables
- GCP_LLM_KEY
- AZURE_API_KEY
- GITHUB_API_KEY
- CLIENTID
- CLIENTSECRET
- TENANTID
- GHCR_USERNAME
- GHCR_TOKEN
Security Notes
The project uses Pydantic's SecretStr for API keys and integrates with Kubernetes secrets for deployment, which are good practices. There are no obvious hardcoded secrets or direct uses of 'eval' or 'exec' on user input. The primary security consideration for this type of LLM agent is the inherent risk of prompt injection leading to unintended tool execution. Tools like 'delete_record_by_id' (even if mocked in the provided code) highlight the need for robust access control and careful sandboxing of real-world tool implementations. The 'interactivedebugger' in CLI is opt-in and primarily for development.
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