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--- |
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title: cluas_huginn |
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emoji: 💬 |
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colorFrom: yellow |
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colorTo: purple |
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sdk: docker |
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pinned: false |
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hf_oauth: true |
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hf_oauth_scopes: |
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- inference-api |
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license: apache-2.0 |
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short_description: A gathering of guides, a council of counsels |
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--- |
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An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index). |
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the above is just a template readme they gave me when I created this space on hugging face, feel free to ignore it. |
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# 🐦⬛ Cluas |
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*A gathering of guides, a council of counsels* |
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> **Clúas** (Gaelic: "ear") — a dialectic research tool where AI experts collaborate, remember, and build knowledge over time. |
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## What it Does |
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Corvid Council is a multi-agent MCP system that enables dialectic research |
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through collaborative AI agents. Present a question to the council and watch |
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as four specialized experts research, debate, and synthesize knowledge—building |
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on past discussions through shared memory. |
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### Modes |
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- **Collaborative Mode**: Ask a question and receive synthesized research with sources |
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- **Active Mode**: Join the discussion, steer research, challenge claims |
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### Dialectic Process |
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1. **Thesis**: Characters present initial findings using specialized tools |
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2. **Antithesis**: Characters challenge, verify, and provide counter-evidence |
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3. **Synthesis**: Council builds consensus and adds to collective memory |
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4. **Evolution**: Future discussions build on accumulated knowledge |
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### Why It Matters |
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Most AI assistants are stateless. cluas_huginn Council remembers, learns, and builds knowledge over time. |
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### Characters |
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- Corvus: 🐦⬛ (black bird) |
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- Magpie: 🪶 (feather, playful) |
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- Raven: 🦅 (eagle, serious) |
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- Crow: 🕊️ (dove, peaceful observer) |
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### Taglines |
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- "A gathering of guides, a council of counsels" |
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- "Research that remembers, knowledge that accumulates" |
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- "Multi-agent MCP research collective" |
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v2: |
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# Cluas Huginn: Multi-Agent Dialectic System |
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## What It Does |
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Four AI agents with distinct roles debate questions using structured dialectic. |
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## Architecture |
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- **Corvus**: Academic verifier (literature search) |
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- **Raven**: Accountability enforcer (news verification) |
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- **Magpie**: Trend explorer (pattern connector) |
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- **Crow**: Grounded observer (environmental data) |
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## Key Innovations |
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1. Unified inheritance architecture |
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2. Shared epistemic principles with character differentiation |
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3. Tool-use heuristics per character |
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4. Steelmanning and collaborative disagreement built-in |
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## Tech Stack |
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- Base: Python, Gradio |
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- LLMs: Groq/Nebius (Qwen 3) |
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- Tools: Academic search, news verification, web exploration |
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- Memory: Persistent character memories |
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## What Makes This Different |
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- Not just multiple LLMs - distinct epistemic roles |
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- Structured dialectic (thesis/antithesis/synthesis) |
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- Tool usage guided by character personality |
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- Collaborative, not adversarial |
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## Hackathon Track Entries |
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- "building-mcp-track-enterprise" → Track 1 |
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- "building-mcp-track-consumer" → Track 1 |
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- "building-mcp-track-creative" → Track 1 |
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- "mcp-in-action-track-enterprise" → Track 2 |
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- "mcp-in-action-track-consumer" → Track 2 |
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- "mcp-in-action-track-creative" → Track 2 |
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--- |
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This project is licensed under the [Apache 2.0 License](LICENSE). |
