INFERENCE — sovereign LLM execution

Hugging Chat / the HF router is fine for prototyping, but the critical path is an endpoint you control that the harness hits programmatically. Two paths, both OpenAI-compatible — no code changes, only env:

export FREESTREAM_AGENT=llm
export FREESTREAM_LLM_BASE_URL=<endpoint>/v1
export FREESTREAM_LLM_API_KEY=<key or "local">
export FREESTREAM_LLM_MODEL=local          # llama.cpp/MLX serve any model name
export FREESTREAM_CHARACTER_CARD=identity/characters/vera-steel.json

A. Dedicated HF Space (shipped — freestream-llm)

Docker Space running llama.cpp server (Qwen2.5-7B-Instruct Q4_K_M, auto-downloaded on boot). Endpoint:

https://lovelogicai-freestream-llm.hf.space/v1/chat/completions

Setup once: Space settings → upgrade hardware to CPU Upgrade (8 vCPU) → add the LLM_API_KEY secret → optionally enable persistent storage (/data) so the 4.7GB model survives restarts. Pause the Space when idle — a 24/7 CPU-upgrade Space bills continuously, and sovereignty shouldn't mean a standing bill.

Measured throughput will be reported in docs/LATENCY.md after the probe job.

B. Mac mini (recommended primary — your hardware, no standing bill)

cd freestream
./scripts/serve_local_llm.sh mlx    # MLX, fastest on Apple Silicon
#   or: ./scripts/serve_local_llm.sh cpp
export FREESTREAM_LLM_BASE_URL=http://localhost:8080/v1
export FREESTREAM_LLM_MODEL=local
export FREESTREAM_LLM_API_KEY=local
python tests/e2e_roleplay.py        # the harness hits localhost programmatically

MLX: pip install mlx-lm, serves mlx-community/Qwen2.5-7B-Instruct-4bit via python -m mlx_lm.server (OpenAI-compatible).
llama.cpp: brew install llama.cpp, llama-server -hf <gguf> — same API.

The 4s assistant-profile win condition stays a cloud-burst feature (router/GPU); sovereign local inference is the roleplay/agentic profile (gates 20s/30s) — measure your mini's tok/s and record it in LATENCY.md.

Harness wiring (both paths)

Every e2e harness reads the same env; nothing is hardcoded to the router. load_agent accepts keyless local endpoints (localhost / *.local) without falling back to the rule stub — set FREESTREAM_LLM_API_KEY=local for hosts that ignore auth headers.

Endpoint contract

CharacterAgent needs exactly one route: POST {base}/chat/completions with {"model", "messages", "max_tokens", "temperature"} → choices[0].message.content. Any OpenAI-compatible server satisfies it (llama-server, mlx_lm.server, vLLM, Ollama with base=/v1).