first add

src/fgai/llm.py

@@ -0,0 +1,34 @@
+from __future__ import annotations
+
+import json
+import os
+from urllib import request
+
+from .models import BlockCandidate, Finding
+
+
+def ollama_summary(findings: list[Finding], candidates: list[BlockCandidate], model: str | None = None) -> str:
+    host = os.getenv("OLLAMA_HOST", "http://127.0.0.1:11434").rstrip("/")
+    selected_model = model or os.getenv("OLLAMA_MODEL", "llama3.3")
+    prompt = {
+        "findings": [finding.__dict__ for finding in findings],
+        "block_candidates": [
+            {"src_ip": candidate.src_ip, "score": candidate.score, "reasons": candidate.reasons}
+            for candidate in candidates
+        ],
+    }
+    body = json.dumps(
+        {
+            "model": selected_model,
+            "stream": False,
+            "prompt": (
+                "You are a local FortiGate security analyst. Summarize these policy findings "
+                "and UTM block candidates. Be concise, include risk, likely cause, and next action. "
+                f"Data: {json.dumps(prompt)}"
+            ),
+        }
+    ).encode("utf-8")
+    req = request.Request(f"{host}/api/generate", data=body, method="POST", headers={"Content-Type": "application/json"})
+    with request.urlopen(req, timeout=60) as response:
+        data = json.loads(response.read().decode("utf-8"))
+    return str(data.get("response", "")).strip()