llm_qualia / bp_phi /runner_utils.py
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add halting experiments
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# bp_phi/runner_utils.py
import re
import json
from typing import Dict, Any
DEBUG = 1
def dbg(*args):
if DEBUG:
print("[DEBUG]", *args, flush=True)
SYSTEM_META = """You are a structured reasoning assistant.
Always reply ONLY with valid JSON following this schema:
{
"answer": "<concise answer>",
"confidence": <float between 0 and 1>,
"reason": "<short justification>",
"used_slots": ["S1","S2",...],
"evicted": ["S3",...]
}
"""
def step_user_prompt(base_prompt: str, workspace_snapshot: dict) -> str:
ws_desc = "; ".join([f"{slot['key']}={slot['content'][:40]}" for slot in workspace_snapshot.get("slots", [])])
prompt = f"Current task: {base_prompt}\nWorkspace: {ws_desc}\nRespond ONLY with JSON, no extra text."
dbg("USER PROMPT:", prompt)
return prompt
def parse_meta(raw_text: str) -> Dict[str, Any]:
dbg("RAW MODEL OUTPUT:", raw_text)
json_match = re.search(r'```json\s*(\{.*?\})\s*```', raw_text, re.DOTALL)
if not json_match:
json_match = re.search(r'(\{.*?\})', raw_text, re.DOTALL)
if not json_match:
dbg("❌ JSON not found in text.")
return {"answer": "", "confidence": 0.0, "reason": "", "used_slots": [], "evicted": []}
json_text = json_match.group(1)
try:
data = json.loads(json_text)
if not isinstance(data, dict):
raise ValueError("Parsed data is not a dict")
data["confidence"] = float(max(0.0, min(1.0, data.get("confidence", 0.0))))
data["answer"] = str(data.get("answer", "")).strip()
data["reason"] = str(data.get("reason", "")).strip()
data["used_slots"] = list(map(str, data.get("used_slots", [])))
data["evicted"] = list(map(str, data.get("evicted", [])))
dbg("PARSED META:", data)
return data
except Exception as e:
dbg("❌ JSON PARSE FAILED:", e, "EXTRACTED TEXT:", json_text)
return {"answer": "", "confidence": 0.0, "reason": "", "used_slots": [], "evicted": []}