Webscout is a comprehensive Python toolkit designed for web scraping, AI model interaction, and various digital utilities. It targets developers and power users seeking a unified interface for diverse search engines, numerous AI providers (including OpenAI-compatible and local LLMs), and media/developer tools, simplifying complex workflows into a single library.

How It Works

Webscout offers three primary compatibility modes for AI interaction: a native API for direct provider access, OpenAI-compatible interfaces for seamless integration with existing tools, and support for local LLMs via the standalone inferno-llm package. This multi-faceted approach ensures flexibility, allowing users to leverage cloud-based AI services or self-hosted models with a consistent API structure. The library also integrates multiple search engines (Google, DuckDuckGo, Yep.com) and provides specialized modules for tasks like YouTube transcript analysis and text-to-speech conversion.

Quick Start & Requirements

• Installation: pip install -U webscout or uv install webscout. For API server: pip install -U "webscout[api]". Docker: docker pull oevortex/webscout:latest.
• Prerequisites: Python 3.x. GPU acceleration recommended for local LLMs via inferno-llm.
• Resources: Local LLM usage requires significant RAM (e.g., 8GB+ for 7B models).
• Docs: Webscout GitHub, Inferno GitHub.

Highlighted Details

• Supports over 90 AI providers, including OpenAI, Gemini, Meta, GROQ, and HuggingFaceChat.
• Includes an OpenAI-compatible API server for seamless integration with OpenAI-dependent applications.
• Features a YouTube toolkit for video and transcript management with multi-language support.
• Provides developer utilities like GitAPI for GitHub data extraction and LitAgent for undetectable user requests.

Maintenance & Community

• Active development is indicated by frequent updates and a comprehensive feature set.
• Community engagement channels are not explicitly listed in the README, but contributions are welcomed via pull requests.

Licensing & Compatibility

• The README does not explicitly state a license. Compatibility for commercial use or closed-source linking is undetermined without a specified license.

Limitations & Caveats

• The absence of a clear license is a significant adoption blocker. Some features, like Meta AI integration, may require user credentials. Hardware requirements for local LLMs are substantial.