Hermes Pipeline
28b0c483b8
Extracted from: https://github.com/DennisDRX/Faraday-Web-Researcher-Agent.git Score: 1.0
36 lines
2.4 KiB
JSON
36 lines
2.4 KiB
JSON
{
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"name": "autonomous-web-research-agent",
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"version": "1.0.0",
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"goal": "Autonomously research a given query on the web using multiple search tools and generate a structured report with summary, detailed sections, source tracking, and bias analysis.",
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"inputs": [
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"query (string): the research question or topic to investigate",
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"tools (list, optional): selected web search/tools to use (e.g., Tavily, Google, NewsAPI, DuckDuckGo)",
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"api_keys (dict, optional): credentials for LLM and external search APIs",
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"model_config (dict, optional): LLM provider and parameters"
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],
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"steps": [
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"1. Accept user query and optional tool selections.",
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"2. Initialize agent framework (e.g., LangGraph) with integrated tools: web search (Tavily, Google, DuckDuckGo), news API, web scraping.",
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"3. Decompose query into sub-questions if needed and iteratively call tools to gather relevant information.",
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"4. Extract and deduplicate content from retrieved sources, tracking source metadata (URL, tool used).",
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"5. Use a large language model to synthesize findings into an executive summary and detailed sections.",
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"6. Analyze potential biases or limitations of gathered sources.",
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"7. Compile a structured report object (ResearchReport) containing query, summary, sections, sources, biases.",
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"8. Optionally present report via a UI (e.g., Streamlit) or return as JSON."
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],
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"outputs": [
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"ResearchReport (JSON/dict) with fields: query (string), summary (string), sections (list of {heading, content}), sources (list of {url, tool_used, title}), potential_biases (string)",
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"Optional UI rendering of report with source badges and expandable sections"
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],
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"failure_modes": [
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"Missing or invalid API keys causing tool authentication failures",
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"Rate limits or network errors from search APIs",
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"Insufficient or low-quality search results leading to incomplete report",
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"LLM hallucination or mis-summarization despite source tracking",
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"Parsing errors in HTML/scraped content"
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],
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"confidence": 0.85,
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"explanation": "The repository implements a generic autonomous web research agent that can be reused for any topical query. The workflow of querying, multi-tool retrieval, synthesis, and structured reporting is not domain-specific and can be extracted as a reusable skill.",
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"source_repo": "https://github.com/DennisDRX/Faraday-Web-Researcher-Agent.git",
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"score": 1.0
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} |