Deepagent-research-context-engineering
by XXXaber
Overview
Develop and manage smart multi-agent systems for AI research, supporting recursive reasoning, tool integration, and context-aware workflows.
Installation
cd deepagents_sourcecode/libs/acp && python -m deepagents_acp.serverEnvironment Variables
- OLLAMA_MODEL
- OLLAMA_API_BASE_URL
- TEMPERATURE
- MAX_SEARCH_RESULTS
- RUST_LOG
- TAVILY_API_KEY
- OPENAI_MODEL
- ANTHROPIC_MODEL
- GOOGLE_MODEL
- OPENAI_API_KEY
- ANTHROPIC_API_KEY
- GOOGLE_API_KEY
- LANGSMITH_API_KEY
Security Notes
CRITICAL: The `rig-rlm` component explicitly allows for arbitrary Python code execution (`pyo3` executor) as stated in its AGENTS.md, posing a direct Remote Code Execution (RCE) vulnerability. Similarly, the `deepagents-cli` and `deepagents_harbor` libraries provide `shell_tool` and `execute` functionalities that run arbitrary shell commands via `subprocess.run` or `shlex.split`. While acknowledged in the documentation as a 'prototype' or requiring 'sandboxing for production,' this makes the system inherently unsafe for untrusted inputs without external sandboxing solutions (e.g., WASM, Firecracker, gVisor) which are not implemented in the provided code. Running this server as-is with LLM-generated code poses a significant security risk to the host system.
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