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chore(docker): increased number of replicas
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3c11e03764
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@ -313,8 +313,6 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
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# Combine all response tokens to form the final assistant message
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assistant = "".join(response_tokens)
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logger.info("💋💋💋💋")
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logger.info(streamed_chat_history)
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try:
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if save_answer:
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@ -246,7 +246,6 @@ class HeadlessQA(BaseModel, QAInterface):
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)
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async for token in callback.aiter():
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logger.info("Token: %s", token)
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response_tokens.append(token)
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streamed_chat_history.assistant = token
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yield f"data: {json.dumps(streamed_chat_history.dict())}"
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@ -66,22 +66,14 @@ class BrainfulChat(ChatInterface):
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supabase_client, embeddings, table_name="vectors"
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)
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# Get the first question from the chat_question
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logger.info(f"Finding brain closest to {chat_question}")
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logger.info("🔥🔥🔥🔥🔥")
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question = chat_question.question
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logger.info(f"Question is {question}")
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history = chat_service.get_chat_history(chat_id)
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if history:
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question = history[0].user_message
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logger.info(f"Question is {question}")
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brain_id_to_use = vector_store.find_brain_closest_query(question)
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logger.info(f"Found brain {brain_id_to_use}")
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logger.info("🧠🧠🧠")
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brain = brain_service.get_brain_by_id(brain_id_to_use)
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logger.info(f"Brain type: {brain.brain_type}")
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logger.info(f"Id is {brain.brain_id}")
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logger.info(f"Type of brain_id is {type(brain.brain_id)}")
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if (
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brain
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and brain.brain_type == BrainType.DOC
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@ -43,9 +43,6 @@ class CustomSupabaseVectorStore(SupabaseVectorStore):
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).execute()
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# Get the brain_id of the brain that is most similar to the query
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logger.info(f"Found {len(res.data)} brains")
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logger.info(res.data)
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logger.info("🔥🔥🔥🔥🔥")
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brain_id = res.data[0].get("id", None)
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if not brain_id:
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return None
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@ -23,7 +23,7 @@ services:
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- "--port"
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- "5050"
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- "--workers"
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- "2"
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- "6"
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restart: always
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ports:
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@ -41,7 +41,7 @@ services:
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- "--port"
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- "5050"
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- "--workers"
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- "1"
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- "6"
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restart: always
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volumes:
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- ./backend/:/code/
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