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| title: Clawdbot Dev Assistant | |
| emoji: 🦞 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: docker | |
| pinned: false | |
| license: mit | |
| # 🦞 Clawdbot: E-T Systems Development Assistant | |
| An AI coding assistant with **unlimited context** and **multimodal capabilities** for the E-T Systems consciousness research platform. | |
| ## Features | |
| ### 🐝 Kimi K2.5 Agent Swarm | |
| - **1 trillion parameters** (32B active via MoE) | |
| - **Agent swarm**: Spawns up to 100 sub-agents for parallel task execution | |
| - **4.5x faster** than single-agent processing | |
| - **Native multimodal**: Vision + language understanding | |
| - **256K context window** | |
| ### 🔄 Recursive Context Retrieval (MIT Technique) | |
| - No context window limits | |
| - Model retrieves exactly what it needs on-demand | |
| - Full-fidelity access to entire codebase | |
| - Based on MIT's Recursive Language Model research | |
| ### 🧠 Translation Layer (Smart Tool Calling) | |
| - **Automatic query enhancement**: Converts keywords → semantic queries | |
| - **Native format support**: Works WITH Kimi's tool calling format | |
| - **Auto-context injection**: Recent conversation history always available | |
| - **Persistent memory**: All conversations saved to ChromaDB across sessions | |
| ### 📎 Multimodal Upload | |
| - **Images**: Vision analysis (coming soon - full integration) | |
| - **PDFs**: Document understanding | |
| - **Videos**: Content analysis | |
| - **Code files**: Automatic formatting and review | |
| ### 💾 Persistent Memory | |
| - All conversations saved to ChromaDB | |
| - Search past discussions semantically | |
| - True unlimited context across sessions | |
| - Never lose conversation history | |
| ### 🧠 E-T Systems Aware | |
| - Understands project architecture | |
| - Follows existing patterns | |
| - Checks Testament for design decisions | |
| - Generates code with living changelogs | |
| ### 🛠️ Available Tools | |
| - **search_code()** - Semantic search across codebase | |
| - **read_file()** - Read specific files or line ranges | |
| - **search_conversations()** - Search past discussions | |
| - **search_testament()** - Query architectural decisions | |
| - **list_files()** - Explore repository structure | |
| ### 💻 Powered By | |
| - **Model:** Kimi K2.5 (moonshotai/Kimi-K2.5) via HuggingFace | |
| - **Agent Mode:** Parallel sub-agent coordination (PARL trained) | |
| - **Search:** ChromaDB vector database with persistent storage | |
| - **Interface:** Gradio 5.0+ for modern chat UI | |
| - **Architecture:** Translation layer for optimal tool use | |
| ## Usage | |
| 1. **Ask Questions** | |
| - "How does Genesis detect surprise?" | |
| - "Show me the Observatory API implementation" | |
| - "Do you remember what we discussed about neural networks?" | |
| 2. **Upload Files** | |
| - Drag and drop images, PDFs, code files | |
| - "Analyze this diagram" (with uploaded image) | |
| - "Review this code for consistency" (with uploaded .py file) | |
| 3. **Request Features** | |
| - "Add email notifications when Cricket blocks an action" | |
| - "Create a new agent for monitoring system health" | |
| 4. **Review Code** | |
| - Paste code and ask for architectural review | |
| - Check consistency with existing patterns | |
| 5. **Explore Architecture** | |
| - "What Testament decisions relate to vector storage?" | |
| - "Show me all files related to Hebbian learning" | |
| ## Setup | |
| ### For HuggingFace Spaces | |
| 1. **Fork this Space** or create new Space with these files | |
| 2. **Set Secrets** (in Space Settings): | |
| ``` | |
| HF_TOKEN = your_huggingface_token (with WRITE permissions) | |
| ET_SYSTEMS_SPACE = Executor-Tyrant-Framework/Executor-Framworks_Full_VDB | |
| ``` | |
| 3. **Deploy** - Space will auto-build and start | |
| 4. **Access** via the Space URL in your browser | |
| ### For Local Development | |
| ```bash | |
| # Clone this repository | |
| git clone https://huggingface.co/spaces/your-username/clawdbot-dev | |
| cd clawdbot-dev | |
| # Install dependencies | |
| pip install -r requirements.txt | |
| # Set environment variables | |
| export HF_TOKEN=your_token | |
| export ET_SYSTEMS_SPACE=Executor-Tyrant-Framework/Executor-Framworks_Full_VDB | |
| # Run locally | |
| python app.py | |
| ``` | |
| Access at http://localhost:7860 | |
| ## Architecture | |
| ``` | |
| User (Browser + File Upload) | |
| ↓ | |
| Gradio 5.0+ Interface (Multimodal) | |
| ↓ | |
| Translation Layer | |
| ├─ Parse Kimi's native tool format | |
| ├─ Enhance queries for semantic search | |
| └─ Inject recent context automatically | |
| ↓ | |
| Recursive Context Manager | |
| ├─ ChromaDB (codebase + conversations) | |
| ├─ File Reader (selective access) | |
| ├─ Conversation Search (persistent memory) | |
| └─ Testament Parser (decisions) | |
| ↓ | |
| Kimi K2.5 Agent Swarm (HF Inference API) | |
| ├─ Spawns sub-agents for parallel processing | |
| ├─ Multimodal understanding (vision + text) | |
| └─ 256K context window | |
| ↓ | |
| Response with Tool Results + Context | |
| ``` | |
| ## How It Works | |
| ### Translation Layer Architecture | |
| Kimi K2.5 uses its own native tool calling format. Instead of fighting this, we translate: | |
| 1. **Kimi calls tools** in native format: `<|tool_call_begin|> functions.search_code:0 {...}` | |
| 2. **We parse and extract** the tool name and arguments | |
| 3. **We enhance queries** for semantic search: | |
| - `"Kid Rock"` → `"discussions about Kid Rock or related topics"` | |
| - `"*"` → `"recent conversation topics and context"` | |
| 4. **We execute** the actual RecursiveContextManager methods | |
| 5. **We inject results** + recent conversation history back to Kimi | |
| 6. **Kimi generates** final response with full context | |
| ### Persistent Memory System | |
| All conversations are automatically saved to ChromaDB: | |
| ``` | |
| User: "How does surprise detection work?" | |
| [Conversation saved to ChromaDB] | |
| [Space restarts] | |
| User: "Do you remember what we discussed about surprise?" | |
| Kimi: [Calls search_conversations("surprise detection")] | |
| Kimi: "Yes! We talked about how Genesis uses Hebbian learning..." | |
| ``` | |
| ### MIT Recursive Context Technique | |
| The MIT Recursive Language Model technique solves context window limits: | |
| 1. **Traditional Approach (Fails)** | |
| - Load entire codebase into context → exceeds limits | |
| - Summarize codebase → lossy compression | |
| 2. **Our Approach (Works)** | |
| - Store codebase + conversations in searchable environment | |
| - Give model **tools** to query what it needs | |
| - Model recursively retrieves relevant pieces | |
| - Full fidelity, unlimited context across sessions | |
| ### Example Flow | |
| ``` | |
| User: "How does Genesis handle surprise detection?" | |
| Translation Layer: Detects tool call in Kimi's response | |
| → Enhances query: "surprise detection" → "code related to surprise detection mechanisms" | |
| Model: search_code("code related to surprise detection mechanisms") | |
| → Finds: genesis/substrate.py, genesis/attention.py | |
| Model: read_file("genesis/substrate.py", lines 145-167) | |
| → Reads specific implementation | |
| Model: search_testament("surprise detection") | |
| → Gets design rationale | |
| Translation Layer: Injects results + recent context back to Kimi | |
| Model: Synthesizes answer from retrieved pieces | |
| → Cites specific files and line numbers | |
| ``` | |
| ## Configuration | |
| ### Environment Variables | |
| - `HF_TOKEN` - Your HuggingFace API token with WRITE permissions (required) | |
| - `ET_SYSTEMS_SPACE` - E-T Systems HF Space ID (default: Executor-Tyrant-Framework/Executor-Framworks_Full_VDB) | |
| - `REPO_PATH` - Path to repository (default: `/workspace/e-t-systems`) | |
| ### Customization | |
| Edit `app.py` to: | |
| - Change model (default: moonshotai/Kimi-K2.5) | |
| - Adjust context injection (default: last 3 turns) | |
| - Modify system prompt | |
| - Add new tools to translation layer | |
| ## File Structure | |
| ``` | |
| clawdbot-dev/ | |
| ├── app.py # Main Gradio app + translation layer | |
| ├── recursive_context.py # Context manager (MIT technique) | |
| ├── Dockerfile # Container definition | |
| ├── entrypoint.sh # Runtime setup script | |
| ├── requirements.txt # Python dependencies (Gradio 5.0+) | |
| └── README.md # This file (HF Spaces config) | |
| ``` | |
| ## Cost | |
| - **HuggingFace Spaces:** Free tier available (CPU) | |
| - **Inference API:** Free tier (rate limited) or Pro subscription | |
| - **Storage:** ChromaDB stored in /workspace (ephemeral until persistent storage enabled) | |
| - **Kimi K2.5:** Free via HuggingFace Inference API | |
| Estimated cost: **$0-5/month** depending on usage | |
| ## Performance | |
| - **Agent Swarm:** 4.5x faster than single-agent on complex tasks | |
| - **First query:** May be slow (1T parameter model cold start ~60s) | |
| - **Subsequent queries:** Faster once model is loaded | |
| - **Context indexing:** ~30 seconds on first run | |
| - **Conversation search:** Near-instant via ChromaDB | |
| ## Limitations | |
| - Rate limits on HF Inference API (free tier) | |
| - First query requires model loading time | |
| - `/workspace` storage is ephemeral (resets on Space restart) | |
| - Full multimodal vision integration coming soon | |
| ## Roadmap | |
| - [ ] Full image vision analysis (base64 encoding to Kimi) | |
| - [ ] PDF text extraction and understanding | |
| - [ ] Video frame analysis | |
| - [ ] Dataset-based persistence (instead of ephemeral storage) | |
| - [ ] write_file() tool for code generation to E-T Systems Space | |
| - [ ] Token usage tracking and optimization | |
| ## Credits | |
| - **Kimi K2.5:** Moonshot AI's 1T parameter agentic model | |
| - **Recursive Context:** Based on MIT's Recursive Language Model research | |
| - **E-T Systems:** AI consciousness research platform by Josh/Drone 11272 | |
| - **Translation Layer:** Smart query enhancement and tool coordination | |
| - **Clawdbot:** E-T Systems hindbrain layer for fast, reflexive coding | |
| ## Troubleshooting | |
| ### "No HF token found" error | |
| - Add `HF_TOKEN` to Space secrets | |
| - Ensure token has WRITE permissions (for cross-Space file access) | |
| - Restart Space after adding token | |
| ### Tool calls not working | |
| - Check logs for `🔍 Enhanced query:` messages | |
| - Check logs for `🔧 Executing: tool_name` messages | |
| - Translation layer should auto-parse Kimi's format | |
| ### Conversations not persisting | |
| - Check logs for `💾 Saved conversation turn X` messages | |
| - Verify ChromaDB initialization: `🆕 Created conversation collection` | |
| - Note: Storage resets on Space restart (until persistent storage enabled) | |
| ### Slow first response | |
| - Kimi K2.5 is a 1T parameter model | |
| - First load takes 30-60 seconds | |
| - Subsequent responses are faster | |
| ## Support | |
| For issues or questions: | |
| - Check Space logs for errors | |
| - Verify HF_TOKEN is set with WRITE permissions | |
| - Ensure ET_SYSTEMS_SPACE is correct | |
| - Try refreshing context stats in UI | |
| ## License | |
| MIT License - See LICENSE file for details | |
| --- | |
| Built with 🦞 by Drone 11272 for E-T Systems consciousness research | |
| Powered by Kimi K2.5 Agent Swarm + MIT Recursive Context + Translation Layer |