local LLM support

src/physcom/llm/providers/ollama.py

@@ -0,0 +1,73 @@
+"""Ollama LLM provider — local models via the Ollama HTTP API."""
+
+from __future__ import annotations
+
+import json
+import re
+import urllib.error
+import urllib.request
+
+from physcom.llm.base import LLMProvider
+from physcom.llm.prompts import PHYSICS_ESTIMATION_PROMPT, PLAUSIBILITY_REVIEW_PROMPT
+
+
+class OllamaLLMProvider(LLMProvider):
+    """LLM provider backed by a local Ollama server (see `ollama serve`)."""
+
+    def __init__(self, model: str = "qwen2.5:7b", host: str = "http://localhost:11434") -> None:
+        self._model = model
+        self._host = host.rstrip("/")
+
+    def estimate_physics(
+        self, combination_description: str, metrics: list[str]
+    ) -> dict[str, float]:
+        prompt = PHYSICS_ESTIMATION_PROMPT.format(
+            description=combination_description,
+            metrics=", ".join(metrics),
+        )
+        text = self._generate(prompt, json_mode=True)
+        return self._parse_json(text, metrics)
+
+    def review_plausibility(
+        self, combination_description: str, scores: dict[str, float]
+    ) -> tuple[str, bool]:
+        scores_str = "\n".join(f"- {k}: {v:.3f}" for k, v in scores.items())
+        prompt = PLAUSIBILITY_REVIEW_PROMPT.format(
+            description=combination_description,
+            scores=scores_str,
+        )
+        text = self._generate(prompt, json_mode=False).strip()
+        return (text, self._parse_verdict(text))
+
+    def _generate(self, prompt: str, json_mode: bool) -> str:
+        payload = {"model": self._model, "prompt": prompt, "stream": False}
+        if json_mode:
+            payload["format"] = "json"
+        req = urllib.request.Request(
+            f"{self._host}/api/generate",
+            data=json.dumps(payload).encode("utf-8"),
+            headers={"Content-Type": "application/json"},
+        )
+        try:
+            with urllib.request.urlopen(req, timeout=120) as resp:
+                return json.loads(resp.read())["response"]
+        except urllib.error.URLError as exc:
+            raise ConnectionError(
+                f"Could not reach Ollama at {self._host} (is `ollama serve` running?)"
+            ) from exc
+
+    def _parse_verdict(self, text: str) -> bool:
+        """Extract VERDICT: PLAUSIBLE/IMPLAUSIBLE from response; default to True."""
+        m = re.search(r"VERDICT:\s*(PLAUSIBLE|IMPLAUSIBLE)", text, re.IGNORECASE)
+        if m:
+            return m.group(1).upper() == "PLAUSIBLE"
+        return True
+
+    def _parse_json(self, text: str, metrics: list[str]) -> dict[str, float]:
+        """Strip markdown fences and parse JSON; fall back to 0.5 per metric on error."""
+        text = re.sub(r"```(?:json)?\s*", "", text).strip().rstrip("`").strip()
+        try:
+            data = json.loads(text)
+            return {k: float(v) for k, v in data.items() if k in metrics}
+        except (json.JSONDecodeError, ValueError, TypeError):
+            return {m: 0.5 for m in metrics}

src/physcom/llm/registry.py

@@ -10,9 +10,11 @@ from physcom.llm.base import LLMProvider
 def build_llm_provider() -> LLMProvider | None:
     """Return an LLMProvider based on env vars, or None if not configured.
 
-    LLM_PROVIDER   — provider name ('gemini'; more can be added)
+    LLM_PROVIDER   — provider name ('gemini', 'ollama'; more can be added)
     GEMINI_API_KEY — required when LLM_PROVIDER=gemini
     GEMINI_MODEL   — optional Gemini model name (default: gemini-2.0-flash)
+    OLLAMA_MODEL   — optional Ollama model name (default: qwen2.5:7b)
+    OLLAMA_HOST    — optional Ollama server URL (default: http://localhost:11434)
     """
     provider = os.environ.get("LLM_PROVIDER", "").lower().strip()
 
@@ -27,4 +29,10 @@ def build_llm_provider() -> LLMProvider | None:
         from physcom.llm.providers.gemini import GeminiLLMProvider
         return GeminiLLMProvider(api_key=api_key, model=model)
 
-    raise ValueError(f"Unknown LLM_PROVIDER: {provider!r}. Supported: gemini")
+    if provider == "ollama":
+        model = os.environ.get("OLLAMA_MODEL", "qwen2.5:7b")
+        host = os.environ.get("OLLAMA_HOST", "http://localhost:11434")
+        from physcom.llm.providers.ollama import OllamaLLMProvider
+        return OllamaLLMProvider(model=model, host=host)
+
+    raise ValueError(f"Unknown LLM_PROVIDER: {provider!r}. Supported: gemini, ollama")