Chatbot Engine

This package largely implements a local chatbot, but review and proceed cautiously: - Missing declared env vars: The LLM adapter will read env vars like OPENAI_API_KEY or ANTHROPIC_API_KEY if you initialize with those providers; these were not listed as required. Do not install or run the skill with sensitive API keys in your environment unless you trust it. - Missing dependencies: The code imports sentence_transformers and fuzzywuzzy, but requirements.txt does not list them. Either add those to requirements.txt or run in 'mock' or 'local' mode to avoid installing them. Unexpected manual dependency installation increases risk if you copy commands from third-party sources. - Network calls and data flow: If you configure provider='openai' or 'anthropic' the adapter will use the respective client libraries to call external APIs and send prompts/context. That means user messages and context can be transmitted to those services — expected for a chatbot but important to know for sensitive data. - Run in a sandbox first: Execute unit tests and examples in an isolated environment (virtualenv/container) and try provider='mock' to observe behavior without network calls. - If you need to use production LLMs, explicitly set and scope API keys and audit network usage; consider adding explicit declarations to requirements and SKILL.md documenting env var names and what will be transmitted. - If you want to be stricter: update requirements.txt to include sentence_transformers and fuzzywuzzy (or modify code to optionally import them), and document the env vars the adapter will read. If you cannot verify these, treat the package as untrusted code and do not provide real API keys or sensitive data.