Add basic version: SemIf decision engine, urgency queue, skill tree, skill loop, decision log, dream pass, CLI

semif_agent/llm.py

@@ -0,0 +1,86 @@
+"""Self-assessment LLM client.
+
+Talks to a local OpenAI-compatible server (e.g. ollama, llama.cpp server) for
+the observe -> assess phase of the skill loop. Real, not mocked; the endpoint
+must be reachable. Uses only the stdlib HTTP client so the core stays
+dependency-free.
+"""
+
+from __future__ import annotations
+
+import json
+import urllib.error
+import urllib.request
+from dataclasses import dataclass, field
+from typing import Any
+
+
+@dataclass
+class Assessment:
+    success: bool
+    summary: str
+    updated_request: str | None = None
+    extra: dict[str, Any] = field(default_factory=dict)
+
+
+class LLMClient:
+    def __init__(self, base_url: str, model: str, timeout: float = 120.0):
+        self.base_url = base_url.rstrip("/")
+        self.model = model
+        self.timeout = timeout
+
+    def _chat(self, messages: list[dict], temperature: float = 0.0) -> str:
+        url = f"{self.base_url}/chat/completions"
+        body = json.dumps(
+            {"model": self.model, "messages": messages, "temperature": temperature}
+        ).encode("utf-8")
+        request = urllib.request.Request(
+            url, data=body, headers={"Content-Type": "application/json"}
+        )
+        try:
+            with urllib.request.urlopen(request, timeout=self.timeout) as response:
+                payload = json.loads(response.read().decode("utf-8"))
+        except urllib.error.URLError as exc:
+            raise RuntimeError(
+                f"LLM endpoint unreachable at {url}: {exc}. Is your local server running?"
+            ) from exc
+        return payload["choices"][0]["message"]["content"]
+
+    def assess(self, skill: str, request_text: str, action_log: str) -> Assessment:
+        system = (
+            "You are the self-assessment step of an agent skill run. Decide whether "
+            "the skill achieved its goal. Reply with JSON only: "
+            '{"success": true|false, "summary": "<brief>", "updated_request": '
+            '"<requeued request text or null>"}. success is true only if the goal was met.'
+        )
+        user = (
+            f"Skill: {skill}\n"
+            f"Goal request: {request_text}\n"
+            f"What was done:\n{action_log}\n"
+        )
+        try:
+            raw = self._chat(
+                [
+                    {"role": "system", "content": system},
+                    {"role": "user", "content": user},
+                ]
+            )
+            parsed = self._parse_json(raw)
+        except Exception as exc:
+            return Assessment(success=False, summary=f"assessment failed: {exc}")
+        success = bool(parsed.get("success"))
+        summary = str(parsed.get("summary", ""))
+        updated = parsed.get("updated_request")
+        return Assessment(
+            success=success,
+            summary=summary,
+            updated_request=None if updated is None else str(updated),
+        )
+
+    @staticmethod
+    def _parse_json(raw: str) -> dict:
+        text = raw.strip()
+        start, end = text.find("{"), text.rfind("}")
+        if start != -1 and end != -1:
+            text = text[start : end + 1]
+        return json.loads(text)