Change models

drb-c2-core/app/internal/intelligence.py

@@ -106,7 +106,7 @@ def _sync_extract(transcript: str, talkgroup_name: Optional[str]) -> dict:
 
     genai.configure(api_key=settings.gemini_api_key)
     model = genai.GenerativeModel(
-        "gemini-1.5-flash",
+        "gemini-2.5-flash-lite",
         generation_config={"response_mime_type": "application/json"},
     )
 
@@ -127,21 +127,20 @@ def _sync_extract(transcript: str, talkgroup_name: Optional[str]) -> dict:
 
 
 def _sync_embed(text: str) -> Optional[list[float]]:
-    """Generate a text-embedding-004 vector for semantic similarity."""
+    """Generate a text-embedding-3-small vector for semantic similarity."""
     from app.config import settings
-    import google.generativeai as genai
+    from openai import OpenAI
 
-    if not settings.gemini_api_key:
+    if not settings.openai_api_key:
         return None
 
-    genai.configure(api_key=settings.gemini_api_key)
     try:
-        result = genai.embed_content(
+        client = OpenAI(api_key=settings.openai_api_key)
-            model="models/text-embedding-004",
+        result = client.embeddings.create(
-            content=text,
+            model="text-embedding-3-small",
-            task_type="SEMANTIC_SIMILARITY",
+            input=text,
         )
-        return result["embedding"]
+        return result.data[0].embedding
     except Exception as e:
         logger.warning(f"Embedding generation failed: {e}")
         return None

drb-c2-core/app/internal/summarizer.py

@@ -82,7 +82,7 @@ def _sync_summarize(inc: dict, transcripts: list[str]) -> Optional[str]:
         return None
 
     genai.configure(api_key=settings.gemini_api_key)
-    model = genai.GenerativeModel("gemini-1.5-flash")
+    model = genai.GenerativeModel("gemini-2.5-flash-lite")
 
     inc_type = inc.get("type", "unknown")
     location = inc.get("location") or "unknown location"