121 lines
4.5 KiB
Python
121 lines
4.5 KiB
Python
import json
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import logging
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import openai
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import time
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from jarvis.db import db_utils
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chat_messages = {}
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def setup_messages(uuid):
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prompt = open("jarvis/utils/gpt_prompt_v3.txt", "r").read()
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chat_messages[uuid] = [{"role": "system", "content": prompt}]
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def chatgpt_recognise(text, uuid):
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# If the chat history is empty, create it
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if uuid not in chat_messages:
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setup_messages(uuid)
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# Add the user message to the chat history
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chat_messages[uuid].append({"role": "user", "content": text})
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# Call ChatGPT API
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start_time = time.time()
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=chat_messages.get(uuid),
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)
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end_time = time.time()
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logging.info("GPT-3 response in " + str(round(end_time - start_time, ndigits=2)) + " seconds")
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try:
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# Parse the response
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query_json = json.loads(str(response.choices[0].message.content))
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# Check if the response looks like a "valid" JSON
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if 'simplified_sentence' in query_json and 'response' in query_json:
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response = query_json['response']
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simplified_sentence = query_json['simplified_sentence']
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# Add the response to the chat history
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chat_messages[uuid].append({"role": "assistant", "content": response})
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# Add to local database
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db_utils.add_query(text, simplified_sentence, response)
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# Return the response
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return query_json
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except Exception as e:
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# If the response is not a JSON, it's probably a plaintext response
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logging.error("Error while parsing ChatGPT response, probably not JSON: " + str(response.choices))
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logging.error(str(e))
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# TODO: repeat query if it's not a JSON response
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return None
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def clear_chat(uuid):
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"""Clear the chat history for a given uuid"""
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logging.info("Cleared chat for uuid " + uuid)
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chat_messages[uuid] = []
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# def get_answer_from_response(response):
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# if 'action' not in response:
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# # Fix for when it responds in plaintext to follow-up questions
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# # In that case the response is an OpenAIObject not a JSON
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# return response.choices[0].message.content
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# else:
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# if response['action'] == 'clarify':
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# return response['question']
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# elif response['action'] == 'command':
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# return response['comment']
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# elif response['action'] == 'query':
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# return response['device_description']
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# elif response['action'] == 'answer':
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# return response['answer']
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# elif response['action'] == 'calculate':
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# return response['calculation']
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# else:
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# return "I don't know how to respond to that..."
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# def get_conversation_as_one_message(uuid):
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# """
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# Prepare the messages to send to OpenAI API
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# We don't use OpenAI way of using an array of messages because it doesn't work well with the prompt and chatgpt
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# breaks out of character.
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# So instead, we add the history to the system prompt and create a new conversation each time.
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# It should not cost more tokens, but I am not sure at 100%.
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# """
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#
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# # Load the prompt
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# prompt = open("/home/mathieu/PycharmProjects/jarvis-server-v2/jarvis/utils/chatgpt_prompt_2_smaller.txt", "r").read()
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#
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# # Replace the variables in the prompt
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# prompt = prompt.replace("{{timestamp}}", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()))
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# prompt = prompt.replace("{{location}}", "Lausanne in the canton Vaud of Switzerland")
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#
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# # Check if the user has already asked a question (to keep context)
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# if len(chat_messages[uuid]) > 1:
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# history = ""
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#
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# # Add the last 4 messages from the user to the prompt
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# # we don't give the whole history because it adds a lot of tokens.
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# history += "\nFor context, last discussion you had with user:\n"
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# for message in chat_messages[uuid][-4:]:
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# if message['role'] == "user":
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# history += "U: " + message['content'] + "\n"
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# elif message['role'] == "assistant":
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# history += "Y: " + message['content'] + "\n"
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#
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# # Replace the {{history}} variable in the prompt with the history
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# prompt = prompt.replace("{{history}}", history)
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# else:
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# # If the user hasn't asked a question yet, remove the history part of the prompt
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# prompt = prompt.replace("{{history}}", "")
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#
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# return [{"role": "system", "content": prompt}]
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