887c913bcd
- engine/llm.py: Ollama /api/chat client with OpenAI-style tool schema
- engine/reasoning.py: LLM path with 4-tier validation:
1. tool exists in registry
2. tool passes location-gating
3. args parse cleanly
4. otherwise fall back to rule-based engine
- env vars: EMERGENCE_LLM_{URL,MODEL,TIMEOUT,ENABLED}
- Default model: llama3.2:3b (best speed/quality tradeoff for tool use)
- 11 new mock tests in tests/test_llm.py (no network)
- smoke_test_llm.py: live smoke against real Ollama
- README: 'LLM Integration' section with model table + setup
Live-verified: 4/4 decisions via llama3.2:3b in 1-3s, character-consistent
('facilitate honest debate', 'work together', 'urgency and collaboration').
79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
#!/usr/bin/env python3
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"""Live smoke test against a real Ollama instance.
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This is NOT part of the regular pytest suite — it is slow (10-30s per turn
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because llama3.2:3b has to think) and requires a running Ollama server with
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at least one chat-capable model pulled.
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Usage:
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python3 smoke_test_llm.py # uses default model
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EMERGENCE_LLM_MODEL=qwen2.5-coder:7b python3 smoke_test_llm.py
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"""
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import os
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import sys
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import time
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent
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sys.path.insert(0, str(ROOT))
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# fresh DB
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db_file = ROOT / "emergence_llm_smoke.db"
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if db_file.exists():
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db_file.unlink()
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os.environ["EMERGENCE_LLM_ENABLED"] = "1"
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from engine import db, world, agents as agents_mod, tools, llm as llm_mod
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from engine import reasoning
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OK = "\033[92m✓\033[0m"
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FAIL = "\033[91m✗\033[0m"
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WARN = "\033[93m!\033[0m"
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def main():
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print("=== Emergence-Mini · Live LLM Smoke Test ===\n")
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print(f"Model: {llm_mod.DEFAULT_MODEL}")
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print(f"URL: {llm_mod.URL}")
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print(f"Timeout:{llm_mod.TIMEOUT}s\n")
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if not llm_mod.is_available():
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print(f"{FAIL} Ollama nicht erreichbar unter {llm_mod.URL}")
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print("Starte Ollama: ollama serve")
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print(f"Ziehe das Modell: ollama pull {llm_mod.DEFAULT_MODEL}")
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sys.exit(1)
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print(f"{OK} Ollama erreichbar\n")
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db.init_db()
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db.set_world_state("landmarks_seeded", False)
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db.set_world_state("agents_seeded", False)
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world.bootstrap()
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agents_mod.bootstrap()
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tools.bootstrap()
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print(f"{OK} Welt + 4 Agenten gebootet\n")
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print("--- 4 Decisions ---\n")
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successes = 0
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for aid in ("anchor", "flora", "lovely", "spark"):
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a = agents_mod.get(aid)
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print(f" [{a['name']:8s}] @ ({a['x']:3d},{a['y']:3d}) E={a['energy']:.0f} K={a['knowledge']:.0f} I={a['influence']:.0f} {a['credits']:.0f}CC")
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t0 = time.time()
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name, args, rat = reasoning.decide(a)
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dt = time.time() - t0
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mode = reasoning.get_last_decision()
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marker = OK if mode["mode"] == "llm" else WARN
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print(f" {marker} tool={name!r:30s} args={args!r:30s}")
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print(f" mode={mode['mode']:18s} latency={dt:.1f}s")
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print(f" rationale: {rat}\n")
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if mode["mode"] == "llm":
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successes += 1
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print(f"\n=== Resultat: {successes}/4 LLM-Decisions erfolgreich ===")
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if successes >= 3:
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print(f"{OK} Live-LLM-Integration funktioniert")
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else:
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print(f"{FAIL} Zu viele Fallbacks — Modell oder Schema pruefen")
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if __name__ == "__main__":
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main()
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