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1# 1. Install dependencies
2pip install -r requirements.txt
3
4# 2. Ensure Ollama is running with a model (e.g., llama3.1)
5ollama pull llama3.1
6
7# 3. Run
8python main.py| Step | Name | MVP Status |
|---|---|---|
| 1 | State Reader | ✅ Implemented |
| 2 | Contract Classifier | ✅ Implemented |
| 3 | Dial Setting | ✅ Implemented |
| 4 | Archetype Blender | ✅ Implemented |
| 5 | J.A.R.V.I.S. Persona Injection | ✅ Implemented |
| 6 | Council of Three | ✅ Implemented |
| 7 | Self-Scoring Agent | ⏳ Stub (disabled in config) |
| 8 | Mirror Check (Drift Guard) | ⏳ Stub (disabled in config) |
| 9 | [ANCHOR] Gate | ⏳ Stub (disabled in config) |
| 10 | Memory Writer | ✅ Implemented |
| 11 | Proactive Loop Detector | ⏳ Stub (disabled in config) |
| 12 | Response Delivery | ✅ Implemented |
config.yaml or set env vars:1llm:
2 provider: ollama # or openai / anthropic
3 model: llama3.1
4 base_url: http://localhost:11434/v1JARVIS_LLM_PROVIDERJARVIS_LLM_MODELJARVIS_LLM_API_KEYJARVIS_LLM_BASE_URLjarvis/
__init__.py
config.py # YAML/JSON config dataclasses
llm.py # Pluggable LLM backends
memory.py # SQLite + ChromaDB unified memory
pipeline.py # 12-step Alvin OS pipeline
ui.py # Rich terminal interface
main.py # Entry point
config.yaml # Default configuration
requirements.txt # Dependencies