Create agent_engine.py

agent_engine.py

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+import os
+import logging
+import requests
+from time import perf_counter, sleep
+from .memory_manager import embed_and_store, retrieve_relevant
+
+# Agent prompts
+PROMPTS = {
+    "Initiator": "You are the Discussion Initiator...",
+    "Responder": "You are the Critical Responder...",
+    "Guardian": "You are the Depth Guardian...",
+    "Provocateur": "You are the Cross-Disciplinary Provocateur...",
+    "Cultural": "You are the Cultural Perspective...",
+    "Judge": "You are the Impartial Judge..."
+}
+
+CHAT_MODEL = os.environ.get("CHAT_MODEL", "HuggingFaceH4/zephyr-7b-beta")
+HF_API_TOKEN = os.environ.get("HF_API_TOKEN", "")
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")
+
+
+def safe_chat(system_prompt: str, history: list, temperature: float = 0.7) -> str:
+    """Call HF inference API with timing and error handling."""
+    start = perf_counter()
+    payload = {
+        "inputs": [{"role": "system", "content": system_prompt}] + history,
+        "parameters": {"max_new_tokens": 300, "temperature": temperature}
+    }
+    headers = {"Authorization": f"Bearer {HF_API_TOKEN}"} if HF_API_TOKEN else {}
+    try:
+        resp = requests.post(
+            f"https://api-inference.huggingface.co/models/{CHAT_MODEL}",
+            json=payload,
+            headers=headers,
+            timeout=60
+        )
+        if resp.status_code == 200:
+            data = resp.json()
+            text = data[0].get('generated_text', '').strip()
+        elif resp.status_code == 503:
+            logging.warning("Model loading, retrying...")
+            sleep(15)
+            return safe_chat(system_prompt, history, temperature)
+        else:
+            logging.error(f"HF error {resp.status_code}: {resp.text}")
+            text = f"⚠️ API Error {resp.status_code}"
+    except Exception as e:
+        logging.error(f"safe_chat exception: {e}")
+        text = f"⚠️ System Error: {e}"
+    elapsed = perf_counter() - start
+    logging.info(f"safe_chat: {elapsed:.3f}s for '{system_prompt[:30]}...'")
+    return text
+
+
+def step_turn(conversation: list, turn: int, topic: str, params: dict) -> list:
+    """Advance one turn of the multi-agent conversation."""
+    # Choose agent by sequence
+    sequence = ["Initiator", "Responder", "Guardian", "Provocateur", "Cultural"]
+    agent = sequence[turn % len(sequence)]
+    prompt = PROMPTS.get(agent, "")
+    # Prepare history
+    history = [{"role": "user", "content": msg['text']} for msg in conversation[-5:]]
+    response = safe_chat(prompt, history, temperature=params[agent]['creativity'])
+    embed_and_store(response, agent, topic)
+    conversation.append({"agent": agent, "text": response, "turn": turn + 1})
+    return conversation