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A highly flexible multi-agent ReAct framework powered by Google Gemini with advanced Memory, RAG, and Network resilience

Project description

🐝 Swarm Intelligence Framework

PyPI version License: MIT GitHub stars

Swarm is a professional, production-ready, highly flexible multi-agent intelligence framework powered by Google's Gemini models (including the latest gemini-3.5-flash). It allows an arbitrary number of autonomous agents to collaborate, use system tools, execute code, perform web searches, and index local data in a shared environmental context with robust transaction safety and memory management.

🚀 Key Features

  • N-Agent Support: Run as many agents as your tasks require.
  • Autonomous Toolchain: Modular, isolated tools returning unified ToolResult wrappers.
  • Dynamic Layered Configuration: Configures any parameter (name, model, temperature, system prompt) via CLI flags, JSON configuration files, or saved session states with hierarchical merging (Defaults ➔ Session Config ➔ CLI Args).
  • Handover Logic: Agents can autonomously pass control to specific peers using the pass_turn tool.
  • Shared Environment: Tool execution outputs are shared with all agents via automatic System Reports.
  • Files API Integration: Agents can upload and analyze local files (PDFs, images, logs) on the fly.
  • Smart Sandboxing: Per-agent regex blacklists for terminal commands and file system paths.
  • Persistent & Secure Sessions: Save and load complete Swarm states. Protected against race conditions and file corruption via SessionLockManager (thread-safe RLock and atomic temp-file swaps).
  • Advanced Memory Hierarchy & Robustness:
    • Integrated MemoryManager with sliding window history truncation to prevent context window overflow while preserving key interaction states.
    • Self-Healing Alternation Filter: An automated history cleaning and merging pipeline that prevents consecutive same-role turns (user-user or model-model), ensuring 100% compliance with Gemini's strict conversational API constraints.
  • Flexible Message Injection: Manually inject messages globally (to the current active agent) or directly to specific targeted agent(s) by ID or Name. Highly configurable through CLI parameters, environment variables, or the interactive Command Center.
  • Built-in RAG (Retrieval-Augmented Generation): Dynamic indexing and querying of local documents via LocalFileRetriever and RAGTool with token-aware truncation.
  • Network Resilience:
    • 429 (Too Many Requests): Automatic API key rotation.
    • 503 (Service Unavailable) / 500: Automatic backoff and retry.

🛠 Installation

pip install swarmai

Requires Python 3.9+ and a Google Gemini API Key.

💻 Quick Start

Basic Two-Agent Discussion

swarm --keys YOUR_API_KEY --agents_count 2

Autonomous Developer & Auditor

swarm --keys YOUR_API_KEY \
      --first_msg "Write a secure Python data scraper" \
      --ai1_name "Dev" --ai1_sys "You are a senior coder." \
      --ai2_name "Security" --ai2_sys "You look for vulnerabilities."

⚙️ Advanced CLI Configuration

Swarm uses a dynamic argument system. You can prefix any standard parameter with aiN_ to target a specific agent:

  • --ai1_model "gemini-3.5-flash" (Use the latest Gemini model for the lead agent)
  • --ai2_temp 0.1 (Make the auditor more deterministic)
  • --ai3_name "Researcher" (Set a custom name for the 3rd agent)
  • --cmd_blacklist "rm" "sudo" (Global security policy)

Global Parameters:

  • --agents_count: Number of agents in session (default: 2).
  • --log_level: DEBUG, INFO, or WARNING.
  • --no_pause: Disable "Press Enter" delays for fully autonomous runs.
  • --config: Path to a JSON file containing all these parameters.
  • --inject_msg: A message to inject into the session upon startup.
  • --inject_targets: Targeted agent(s) (Names or IDs, comma-separated) to receive the injected message.

Environment Variables:

  • SWARM_INJECT_MSG: Default startup message to inject if CLI parameter is not set.
  • SWARM_INJECT_TARGETS: Target agent(s) (Names or IDs, comma-separated) for the environment-injected message.

⌨️ Command Center (Ctrl+C)

Press Ctrl+C during execution to pause the Swarm and access the interactive menu:

  1. Rotate Keys: Rotate or update API keys on the fly.
  2. Toggle Pauses: Switch between manual and autonomous modes.
  3. Save State: Export the entire session to a JSON file (including the active config layer!).
  4. Inject Message: Direct a message globally or target specific agent(s) (by ID or Name), instantly switching focus.
  5. Log Level: Adjust verbosity without restarting.
  6. List Agents & Status: Show details of all agents, active models, descriptions, and history turn lengths.
  7. Switch Current Agent: Manually change the active agent.
  8. View Agent History: Browse the full dialogue and turn history of any agent.
  9. Shutdown: Gracefully exit the session.

📄 Tool Documentation

  • web_search: Browses the web for real-time data using DuckDuckGo.
  • shell_exec: Runs bash commands. Supports complex multi-line scripts.
  • upload_file: Uploads local assets to the Google Gemini Files API.
  • rag_query: Queries indexed local documents for relevant context snippets.
  • pass_turn: Moves the turn to a specific agent by name.

🤝 Contributing

Swarm is maintained by ProgVM.

Feel free to open issues or submit pull requests for new features!

License: MIT

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