ai-local-agents

The code primarily uses well-established libraries (requests, BeautifulSoup, PyPDF2, LangChain, Streamlit) for parsing and data handling, reducing the risk of direct command injection. There are no explicit uses of 'eval()' or 'exec()', nor hardcoded API keys/secrets for external services. However, several components process arbitrary user-provided URLs (web scraper) or uploaded PDF files (PDF bot) and pass this content to a local LLM. This introduces a potential, albeit mitigated, risk of prompt injection or resource exhaustion if very large or malicious content is fed to the LLM or if the scraping/parsing process encounters malformed inputs. Content limits (e.g., '[:2000]', '[:3000]', '[:5000]') are in place to mitigate large input issues. The 'speech_recognition' library by default uses Google's speech recognition API, which sends audio data externally; users concerned about privacy should configure a local STT engine or be aware of this. Given that LLMs are run locally (Ollama), the direct network exposure is minimized. The primary risks are more at the application logic level (LLM interaction, potentially malformed input handling) rather than critical code execution vulnerabilities.