https://ollama.com/weenablesystems/SMOL_Emma-i

!!NEXT UPGRADE FOR THIS MODEL!!

Emma-i v3 — Multi-Agent Upgrade Complete

The multi-agent state machine upgrade has been fully coded .

What was built.

1. State Machine Core (state_machine.py)
   Implements a 7-state async loop (IDLE → PLANNING → DISPATCHING → EXECUTING → REFLECTING → DONE). It orchestrates three new agents, loops if retries are needed, and automatically stops if errors max out.

2. The Agents (app/agents/)

   • planner.py: Asks Gemini 2.5 Pro (via OpenRouter) to decompose a task into an array of JSON PlanSteps.
     
   • executor.py: Dispatches individual steps to tools or local LLMs.
   • critic.py: Reflects on execution results using the local Ollama model to decide the next state transition (continue, retry, escalate, done).

3. New Skills (app/skills/)

   • audit_skill.py: Intercepts every single shell command. Writes an append-only JSONL file and SQLite records, complete with a heuristic risk scanner (low/medium/high).
     
   • memory_skill.py: Cleanly wraps the SQLite+ChromaDB persistence layer so agents aren’t calling raw DB functions.

4. FastAPI Engine (app/main.py)
   Replaces the old scaffold stub. Provides /chat, /state, /sessions, /audit, and /health endpoints.

Remember that this model codes with ABSOLUTELYNO DRIFT, remember steps of execution Thousands of steps back, and depending on memory, becomes a Stateless Model. Code is perfect everytime. End-To-End, Full Stack Ai Development.

4. Start the server!

uvicorn app.main:app –reload