chunk_extraction uses gpt-4o-mini

backend/utils/llm.py

@@ -381,6 +381,8 @@ class SummaryOutput(BaseModel):
 
 
 def chunk_extraction(segments: List[TranscriptSegment], topics: List[str]) -> str:
+    _chat = ChatOpenAI(model="gpt-4o-mini")
+
     content = TranscriptSegment.segments_as_string(segments)
     prompt = f'''
     You are an experienced detective, your task is to extract the key points of the conversation related to the topics you were provided.
@@ -394,7 +396,7 @@ def chunk_extraction(segments: List[TranscriptSegment], topics: List[str]) -> st
 
     Topics: {topics}
     '''
-    with_parser = llm.with_structured_output(SummaryOutput)
+    with_parser = _chat.with_structured_output(SummaryOutput)
     response: SummaryOutput = with_parser.invoke(prompt)
     return response.summary
 

backend/utils/plugins.py

@@ -108,7 +108,8 @@ def _single(plugin: Plugin):
 
 def trigger_realtime_integrations(uid: str, token: str, segments: List[dict]) -> dict:
     plugins: List[Plugin] = get_plugins_data(uid, include_reviews=False)
-    filtered_plugins = [plugin for plugin in plugins if plugin.triggers_realtime() and plugin.enabled]
+    filtered_plugins = [plugin for plugin in plugins if
+                        plugin.triggers_realtime() and plugin.enabled and not plugin.deleted]
     if not filtered_plugins:
         return {}