deleted multion plugin

backend/utils/plugins.py

@@ -56,7 +56,8 @@ def get_plugins_data(uid: str, include_reviews: bool = False) -> List[Plugin]:
 
 def trigger_external_integrations(uid: str, memory: Memory) -> list:
     plugins: List[Plugin] = get_plugins_data(uid, include_reviews=False)
-    filtered_plugins = [plugin for plugin in plugins if plugin.triggers_on_memory_creation() and plugin.enabled]
+    filtered_plugins = [plugin for plugin in plugins if
+                        plugin.triggers_on_memory_creation() and plugin.enabled and not plugin.deleted]
     if not filtered_plugins:
         return []
 
@@ -131,6 +132,8 @@ def _single(plugin: Plugin):
                 return
 
             response_data = response.json()
+            if not response_data:
+                return
             message = response_data.get('message', '')
             print('Plugin', plugin.id, 'response:', message)
             if message and len(message) > 5:

community-plugins.json

@@ -703,6 +703,6 @@
       "setup_completed_url": "https://based-hardware--plugins-api.modal.run/multion/check_setup_completion",
       "setup_instructions_file_path": "/plugins/instructions/multion-amazon/README.md"
     },
-    "deleted": false
+    "deleted": true
   }
 ]

plugins/example/_multion/router.py

@@ -27,13 +27,17 @@ class BooksToBuy(BaseModel):
 
 
 def retrieve_books_to_buy(transcript: str) -> List[str]:
-    chat = ChatGroq(temperature=0, model="llama-3.1-8b-instant").with_structured_output(BooksToBuy)
+    chat = ChatGroq(temperature=0, model="llama3-groq-8b-8192-tool-use-preview").with_structured_output(BooksToBuy)
 
-    response: BooksToBuy = chat.invoke(f'''The following is the transcript of a conversation.
+    response: BooksToBuy = chat.invoke(f'''
+    The following is the transcript of a conversation:
+    ```
     {transcript}
-
-    Your task is to determine first if the speakers talked or mentioned books to each other \
-    at some point during the conversation, and provide the titles of those.''')
+    ```
+    Your task is to identify the titles of the books mentioned in the conversation, if any.
+    Make sure to find clear mentions of book titles, and not just random conversations.
+    Make sure to only include the titles of the books, and not any other information.
+    ''')
 
     print('Books to buy:', response.books)
     return response.books
@@ -162,24 +166,26 @@ async def initiate_process_transcript(data: RealtimePluginRequest, uid: str = Qu
     if not user_id:
         raise HTTPException(status_code=400, detail="Invalid UID or USERID not found.")
 
-    # session_id = 'multion-' + data.session_id
-    # db.clean_all_transcripts_except(uid, session_id)
-    # transcript: List[TranscriptSegment] = db.append_segment_to_transcript(uid, session_id, data.segments)
-    transcript = data.segments
+    session_id = 'multion-' + data.session_id
+    db.clean_all_transcripts_except(uid, session_id)
+    transcript: List[TranscriptSegment] = db.append_segment_to_transcript(uid, session_id, data.segments)
+    transcript_str = TranscriptSegment.segments_as_string(transcript)
+    if len(transcript_str) > 100:
+        transcript_str = transcript_str[-100:]
 
     try:
-        books = retrieve_books_to_buy(transcript)
+        books = retrieve_books_to_buy(transcript_str)
         if not books:
             return {'message': ''}
-        # else:
-        #     db.remove_transcript(uid, data.session_id)
-
+        db.remove_transcript(uid, data.session_id)
         result = await asyncio.wait_for(call_multion(books, user_id), timeout=120)
     except asyncio.TimeoutError:
         print("Timeout error occurred")
+        db.remove_transcript(uid, data.session_id)
         return
     except Exception as e:
         print(f"Error calling Multion API: {str(e)}")
+        db.remove_transcript(uid, data.session_id)
         return
 
     if isinstance(result, bytes):

plugins/example/advanced/realtime.py

@@ -3,19 +3,19 @@
 from fastapi import APIRouter
 from langchain_community.tools.asknews import AskNewsSearch
 from langchain_core.pydantic_v1 import BaseModel, Field
+from langchain_groq import ChatGroq
 from langchain_openai import ChatOpenAI
 
 from db import clean_all_transcripts_except, append_segment_to_transcript, remove_transcript
 from models import RealtimePluginRequest, EndpointResponse, TranscriptSegment
-from langchain_groq import ChatGroq
 
 router = APIRouter()
 chat = ChatOpenAI(model='gpt-4o', temperature=0)
 
 chat_groq_8b = ChatGroq(
     temperature=0,
     # model="llama-3.1-70b-versatile",
-    model="llama-3.1-8b-instant",
+    model="llama3-70b-8192",
     # model='llama3-groq-8b-8192-tool-use-preview',
 )
 
@@ -28,9 +28,10 @@ def news_checker(conversation: List[TranscriptSegment]) -> str:
     chat_with_parser = chat_groq_8b.with_structured_output(NewsCheck)
     conversation_str = TranscriptSegment.segments_as_string(conversation)
     result: NewsCheck = chat_with_parser.invoke(f'''
-    You will be given a segment of an ongoing conversation.
+    You will be given the last few transcript words of an ongoing conversation.
 
     Your task is to determine if the conversation specifically discusses facts that appear conspiratorial, unscientific, or super biased.
+    Historic events, that seem to contradict logic and common sense should also be considered.
     Only if the topic is of significant importance and urgency for the user to be aware of, provide a question to be asked to a news search engine, in order to debunk the conversation in process.
     Otherwise, output an empty question.
 
@@ -64,13 +65,14 @@ def news_checker(conversation: List[TranscriptSegment]) -> str:
 def news_checker_endpoint(uid: str, data: RealtimePluginRequest):
     # return {'message': ''}
     print('news_checker_endpoint', uid)
-    clean_all_transcripts_except(uid, data.session_id)
-    transcript: List[TranscriptSegment] = append_segment_to_transcript(uid, data.session_id, data.segments)
+    session_id = 'news-checker-' + data.session_id
+    clean_all_transcripts_except(uid, session_id)
+    transcript: List[TranscriptSegment] = append_segment_to_transcript(uid, session_id, data.segments)
     message = news_checker(transcript)
 
     if message:
         # so that in the next call with already triggered stuff, it doesn't trigger again
-        remove_transcript(uid, data.session_id)
+        remove_transcript(uid, session_id)
 
     return {'message': message}
 
@@ -102,12 +104,13 @@ def emotional_support(segments: list[TranscriptSegment]) -> str:
 @router.post('/emotional-support', tags=['advanced', 'realtime'], response_model=EndpointResponse)
 def emotional_support_plugin(uid: str, data: RealtimePluginRequest):
     # return {'message': ''}
-    clean_all_transcripts_except(uid, data.session_id)
-    transcript: List[TranscriptSegment] = append_segment_to_transcript(uid, data.session_id, data.segments)
+    session_id = 'emotional-support-' + data.session_id
+    clean_all_transcripts_except(uid, session_id)
+    transcript: List[TranscriptSegment] = append_segment_to_transcript(uid, session_id, data.segments)
     message = emotional_support(transcript)
 
     if message:
         # so that in the next call with already triggered stuff, it doesn't trigger again
-        remove_transcript(uid, data.session_id)
+        remove_transcript(uid, session_id)
 
     return {'message': message}