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| from langchain.chat_models import ChatOpenAI | |
| from langchain.schema import AIMessage, HumanMessage | |
| import openai | |
| import gradio as gr | |
| import os | |
| os.environ["OPENAI_API_KEY"] = "sk-..." # Replace with your key | |
| llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613') | |
| def predict(message, history): | |
| history_langchain_format = [] | |
| for human, ai in history: | |
| history_langchain_format.append(HumanMessage(content=human)) | |
| history_langchain_format.append(AIMessage(content=ai)) | |
| history_langchain_format.append(HumanMessage(content=message)) | |
| # gpt_response = llm(history_langchain_format) | |
| # return gpt_response.content | |
| return "yes" | |
| gr.ChatInterface(predict).launch() | |
| # https://www.gradio.app/guides/creating-a-chatbot-fast |