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MiroFlow Agent

For comprehensive documentation, installation guide, and tool configuration, see the main README.

Prerequisites

Before running the agent, ensure you have:

  1. Installed dependencies: Run uv sync in this directory
  2. Configured environment variables: Copy .env.example to .env and fill in your API keys 
    cp .env.example .env
# Edit .env with your actual API keys (SERPER_API_KEY, JINA_API_KEY, E2B_API_KEY, etc.)
  3. Started your model server (for MiroThinker models): See the Serve the MiroThinker Model section

Quick Start

Run a Single Task

The simplest way to test the agent is running main.py directly. It will execute a default task: "What is the title of today's arxiv paper in computer science?"

# Using MiroThinker models (requires your own model server)
uv run python main.py llm=qwen-3 agent=mirothinker_v1.5_keep5_max200 llm.base_url=http://localhost:61002/v1

# Using Claude (requires ANTHROPIC_API_KEY in .env)
uv run python main.py llm=claude-3-7 agent=single_agent_keep5

# Using GPT-5 (requires OPENAI_API_KEY in .env)
uv run python main.py llm=gpt-5 agent=single_agent_keep5

Customize Your Task

To ask a different question, edit main.py line 32:

task_description = "Your custom question here"

Then run the agent again. It will search the web, execute code, and provide an answer.

Run Benchmark Evaluation

For systematic evaluation on standard benchmarks, add the benchmark= parameter:

# Run on debug benchmark (quick test)
uv run python main.py llm=qwen-3 agent=mirothinker_v1.5_keep5_max200 benchmark=debug llm.base_url=http://localhost:61002/v1

# Run on specific benchmarks
uv run python main.py llm=qwen-3 agent=mirothinker_v1.5_keep5_max200 benchmark=gaia-validation-text-103 llm.base_url=http://localhost:61002/v1

Available Configurations

LLM Models

Model Config Name Requirements
MiroThinker (self-hosted) qwen-3 Model server + llm.base_url
Claude 3.7 Sonnet claude-3-7 ANTHROPIC_API_KEY in .env
GPT-5 gpt-5 OPENAI_API_KEY in .env

Agent Configurations

MiroThinker v1.5:

  • mirothinker_v1.5_keep5_max200 ⭐ (recommended) - context management, up to 200 turns
  • mirothinker_v1.5_keep5_max400 - context management, up to 400 turns (for BrowseComp)
  • mirothinker_v1.5 - no context management, up to 600 turns

MiroThinker v1.0:

  • mirothinker_v1.0_keep5 (recommended) - context management, up to 600 turns
  • mirothinker_v1.0 - no context management, up to 600 turns

General (for closed-source models like Claude, GPT-5):

  • single_agent_keep5 (recommended) - single agent with context management
  • single_agent - single agent without context management

Multi-Agent (Legacy for v0.1/v0.2):

  • multi_agent - multi-agent with commercial tools
  • multi_agent_os - multi-agent with open-source tools

Benchmark Configs

debug, browsecomp, browsecomp_zh, hle, hle-text-2158, hle-text-500, gaia-validation-text-103, gaia-validation, frames, xbench_deepsearch, futurex, seal-0, aime2025, deepsearchqa, webwalkerqa

Output

The agent will:

  1. Execute the task using available tools (search, code execution, etc.)
  2. Generate a final summary and boxed answer
  3. Save detailed logs to ../../logs/ directory
  4. Display the results in the terminal

Troubleshooting

Problem Solution
API key errors Check .env file has correct keys
Model connection failed Verify llm.base_url is accessible
Tool execution errors Check E2B/Serper/Jina API keys and quotas
Out of memory Use mirothinker_v1.5_keep5_max200 config

For detailed logs, check the logs/ directory.