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57 lines
1.6 KiB
57 lines
1.6 KiB
# Advanced Research
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An enhanced implementation of the orchestrator-worker pattern from Anthropic's paper, "How we built our multi-agent research system", built on top of the bleeding-edge multi-agent framework [swarms](https://github.com/kyegomez/swarms). Our implementation of this advanced research system leverages parallel execution, LLM-as-judge evaluation, and professional report generation with export capabilities.
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**Repository**: [AdvancedResearch](https://github.com/The-Swarm-Corporation/AdvancedResearch)
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## Installation
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```bash
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pip3 install -U advanced-research
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# uv pip install -U advanced-research
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```
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## Environment Variables
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```txt
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# Exa Search API Key (Required for web search functionality)
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EXA_API_KEY="your_exa_api_key_here"
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# Anthropic API Key (For Claude models)
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ANTHROPIC_API_KEY="your_anthropic_api_key_here"
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# OpenAI API Key (For GPT models)
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OPENAI_API_KEY="your_openai_api_key_here"
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# Worker Agent Configuration
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WORKER_MODEL_NAME="gpt-4.1"
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WORKER_MAX_TOKENS=8000
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# Exa Search Configuration
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EXA_SEARCH_NUM_RESULTS=2
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EXA_SEARCH_MAX_CHARACTERS=100
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```
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**Note**: At minimum, you need `EXA_API_KEY` for web search functionality. For LLM functionality, you need either `ANTHROPIC_API_KEY` or `OPENAI_API_KEY`.
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## Quick Start
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### Basic Usage
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```python
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from advanced_research import AdvancedResearch
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# Initialize the research system
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research_system = AdvancedResearch(
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name="AI Research Team",
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description="Specialized AI research system",
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max_loops=1,
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)
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# Run research and get results
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result = research_system.run(
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"What are the latest developments in quantum computing?"
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)
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print(result)
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``` |