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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

Run Command
cd deepagents_sourcecode/libs/acp && python -m deepagents_acp.server

Environment 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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Stats

Interest Score0
Security Score2
Cost ClassHigh
Avg Tokens10000
Stars0
Forks0
Last Update2026-01-19

Tags

Multi-AgentAI ResearchContext ManagementLLMTools