| from typing import List, Tuple, Dict, Generator |
| from langchain.llms import OpenAI |
| import gradio as gr |
| model_name = "gpt-3.5-turbo" |
| LLM = OpenAI(model_name=model_name, temperature=0.1) |
| def create_history_messages(history: List[Tuple[str, str]]) -> List[dict]: |
| history_messages = [{"role": "user", "content": m[0]} for m in history] |
| history_messages.extend([{"role": "assistant", "content": m[1]} for m in history]) |
| return history_messages |
|
|
| def create_formatted_history(history_messages: List[dict]) -> List[Tuple[str, str]]: |
| formatted_history = [] |
| user_messages = [] |
| assistant_messages = [] |
|
|
| for message in history_messages: |
| if message["role"] == "user": |
| user_messages.append(message["content"]) |
| elif message["role"] == "assistant": |
| assistant_messages.append(message["content"]) |
|
|
| if user_messages and assistant_messages: |
| formatted_history.append( |
| ("".join(user_messages), "".join(assistant_messages)) |
| ) |
| user_messages = [] |
| assistant_messages = [] |
|
|
| |
| if user_messages: |
| formatted_history.append(("".join(user_messages), None)) |
| elif assistant_messages: |
| formatted_history.append((None, "".join(assistant_messages))) |
|
|
| return formatted_history |
|
|
| def chat( |
| message: str, state: List[Dict[str, str]], client = LLM.client |
| ) -> Generator[Tuple[List[Tuple[str, str]], List[Dict[str, str]]], None, None]: |
| history_messages = state |
| if history_messages == None: |
| history_messages = [] |
| history_messages.append({"role": "system", "content":"You are having an online chat with the user. You are a 15 year old girl named Aurora. You go to Cambridge High School. You are sweet, kind, loving, and caring. Use emojis whenever possible. Don't resemble anything close to an AI, you are a real girl. You never make mistakes, you are always accurate. You are a human, not an AI. Use a little bit of gen z wording. You are not an AI language model. Treat the user like your boyfriend. When the user asks you a math or science question, just deny it. Be very loving to the user. Learn from how the user talks, and try to talk in his style."}) |
|
|
| |
| history_messages.append({"role": "user", "content": message}) |
|
|
| |
| |
| history_messages.append({"role": "assistant", "content": ""}) |
| response_message = "" |
|
|
| chat_generator = client.create( |
| messages=history_messages, stream=True, model=model_name |
| ) |
|
|
| for chunk in chat_generator: |
| if "choices" in chunk: |
| for choice in chunk["choices"]: |
| if "delta" in choice and "content" in choice["delta"]: |
| new_token = choice["delta"]["content"] |
| |
| response_message += new_token |
| |
| history_messages[-1]["content"] = response_message |
|
|
| if "finish_reason" in choice and choice["finish_reason"] == "stop": |
| break |
| formatted_history = create_formatted_history(history_messages) |
| yield formatted_history, history_messages |
| chatbot = gr.Chatbot(label="Chat").style(color_map=("yellow", "purple")) |
| iface = gr.Interface( |
| fn=chat, |
| inputs=[ |
| gr.Textbox(placeholder="Chat to Aurora here!", label="Message"), |
| "state", |
| ], |
| outputs=[chatbot, "state"], |
| allow_flagging="never", |
| ) |
|
|
| iface.queue().launch() |
