Update llm.py

llm.py

@@ -1,39 +1,39 @@
 import os
-from typing import List
-from summarize import mmr_summarize
+from openai import OpenAI
 
-def _join(ctxs: List[str], max_chars=4000) -> str:
-    out, used = [], 0
-    for c in (ctxs or []):
-        c = (c or "").strip()
-        if not c: continue
-        if used + len(c) > max_chars: break
-        out.append(c); used += len(c)
-    return "\n\n".join(out) if out else "(no context)"
+_client = None
 
-def local_answer(question: str, contexts: List[str]) -> str:
-    ctx = _join(contexts, 3000)
-    if not ctx or ctx == "(no context)":
-        return "I don't have enough information yet."
-    return mmr_summarize(ctx, max_sentences=4)
 
-def openai_answer(question: str, contexts: List[str]) -> str:
-    try:
-        from openai import OpenAI
-        client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-        model = os.getenv("OPENAI_MODEL","gpt-4o-mini")
-        system = "You are MnemoSense. Answer using ONLY the provided context. If insufficient, say you don't know."
-        user = f"Context:\n{_join(contexts)}\n\nQuestion: {question}"
-        resp = client.chat.completions.create(
-            model=model,
-            messages=[{"role":"system","content":system},{"role":"user","content":user}],
-            temperature=0.2,
-        )
-        return resp.choices[0].message.content.strip()
-    except Exception:
-        return "(local) " + local_answer(question, contexts)
+def _get_client():
+    global _client
+    if _client is None:
+        api_key = os.getenv("OPENAI_API_KEY")
+        if not api_key:
+            raise RuntimeError("OPENAI_API_KEY is not set in the environment.")
+        _client = OpenAI(api_key=api_key)
+    return _client
 
-def answer(question: str, contexts: List[str]) -> str:
-    if os.getenv("OPENAI_API_KEY"):
-        return openai_answer(question, contexts)
-    return local_answer(question, contexts)
+
+def generate_answer(question: str, contexts):
+    contexts = contexts or []
+    context_block = "\n".join(f"- {c}" for c in contexts) or "No stored memories yet."
+
+    system = (
+        "You are MnemoSense, an external memory assistant. "
+        "Answer questions **only** using the provided memories. "
+        "If the answer is not present, say you don't know."
+    )
+
+    client = _get_client()
+    resp = client.chat.completions.create(
+        model=os.getenv("OPENAI_MODEL", "gpt-4o-mini"),
+        messages=[
+            {"role": "system", "content": system},
+            {
+                "role": "user",
+                "content": f"Memories:\n{context_block}\n\nQuestion: {question}",
+            },
+        ],
+        temperature=0.3,
+    )
+    return resp.choices[0].message.content.strip()