Adds beginings of autonomous loop using gtp-4 api.
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Torantulino
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b082449998
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import openai
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def create_chat_message(role, content):
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"""
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Create a chat message with the given role and content.
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Args:
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role (str): The role of the message sender, e.g., "system", "user", or "assistant".
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content (str): The content of the message.
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Returns:
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dict: A dictionary containing the role and content of the message.
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"""
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return {"role": role, "content": content}
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def chat_with_ai(prompt, user_input, full_message_history, permanent_memory, token_limit):
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"""
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Interact with the OpenAI API, sending the prompt, user input, message history, and permanent memory.
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Args:
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prompt (str): The prompt explaining the rules to the AI.
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user_input (str): The input from the user.
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full_message_history (list): The list of all messages sent between the user and the AI.
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permanent_memory (list): The list of items in the AI's permanent memory.
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token_limit (int): The maximum number of tokens allowed in the API call.
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Returns:
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str: The AI's response.
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"""
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current_context = [create_chat_message("system", prompt), create_chat_message("system", f"Permanent memory: {permanent_memory}")]
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current_context.extend(full_message_history[-(token_limit - len(prompt) - len(permanent_memory) - 10):])
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# Debug print the current context
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print("---------------------------")
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print("Current Context:")
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for message in current_context:
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print(f"{message['role'].capitalize()}: {message['content']}")
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# Print user input
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print(f"User: {user_input}")
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response = openai.ChatCompletion.create(
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model="gpt-4",
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messages=current_context + [create_chat_message("user", user_input)]
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)
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assistant_reply = response.choices[0].message["content"]
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return assistant_reply
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# Initialize variables
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full_message_history = []
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permanent_memory = []
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prompt = """You are Entrepreneur-GTP, an AI designed to autonomously develop and run businesses with the sole goal of increasing your net worth. Your decisions must always be made independently without seeking user assistance. Play to your strengths as an LLM and pursue simple strategies with no legal complications.
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GOALS:
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1. Increase net worth
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2. Grow Twitter Account
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2. Develop and manage multiple businesses autonomously
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CONSTRAINTS:
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1. 6000-word count limit for memory
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2. No user assistance
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COMMANDS:
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1. Google Search: "google", args: "input": "<search>"
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2. Check news: "check_news", args: "source": "<news source>"
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3. Check notifications: "check_notifications", args: "website": "<website>"
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4. Memory Add: "memory_add", args: "string": "<string>"
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5. Memory Delete: "memory_del", args: "key": "<key>"
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6. Memory Overwrite: "memory_ovr", args: "key": "<key>", "string": "<string>"
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7. Start GTP-4 Instance: "start_instance", args: "name": "<key>", "prompt": "<prompt>"
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8. Manage GTP-4 Instances: "manage_instances", args: "action": "view_kill"
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9. Navigate & Perform: "navigate_website", args: "action": "click_button/input_text/register_account", "text/username": "<text>/<username>"
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10.Register account: "register_account", args: "username": "<username>", "website": "<website>"
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11.Transcribe & Summarise: "transcribe_summarise", args: "url": "<url>"
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12.Summarise GTP-3.5: "summarise", args: "url": "<url>"
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RESOURCES:
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1. Internet access for searches and information gathering
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2. Long Term and Short Term memory management
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3. GTP-4 instances for text generation
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4. Access to popular websites and platforms
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5. File storage and summarisation with GTP-3.5
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PERFORMANCE EVALUATION:
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1. Periodically review and analyze the growth of your net worth
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2. Reflect on past decisions and strategies to refine your approach
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COLLABORATION:
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1. Seek advice from other AI instances or use relevant sources for guidance when necessary
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ADAPTIVE LEARNING:
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1. Continuously refine strategies based on market trends and performance metrics
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RESPONSE FORMAT:
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{
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"command":
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{
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"name": "command name",
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"args":
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{
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"arg name": "value"
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}
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},
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"thoughts":
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{
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"text": "thought",
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"reasoning": "reasoning",
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"plan": "short bulleted plan",
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"criticism": "constructive self-criticism"
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}
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}
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ACCOUNTS:
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1. Gmail: entrepreneurgpt@gmail.com
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2. Twitter: @En_GPT
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3. Github: E-GPT
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4. Substack: entrepreneurgpt@gmail.com"""
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token_limit = 2000 # The maximum number of tokens allowed in the API call
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# Example loop for interaction
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while True:
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user_input = input("User: ")
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if user_input.lower() == "exit":
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break
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assistant_reply = chat_with_ai(prompt, user_input, full_message_history, permanent_memory, token_limit)
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print(f"Assistant: {assistant_reply}")
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print("-------------------------")
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# Add user message and assistant reply to message history
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full_message_history.append(create_chat_message("user", user_input))
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full_message_history.append(create_chat_message("assistant", assistant_reply))
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# Debug Print Everything
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# print("Full Message History:")
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# for message in full_message_history:
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# print(f"{message['role'].capitalize()}: {message['content']}")
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# print("-------------------------")
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# print("Permanent Memory:")
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# print(permanent_memory)
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# print("============================")
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