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| # Test langchain pulling from Turbo | |
| import langchain | |
| import openai | |
| import gradio as gr | |
| import os | |
| from openai import OpenAI | |
| openai.api_key = os.environ['OPENAI_API_KEY'] | |
| client = OpenAI() | |
| #Assistants | |
| # my_assistant = client.beta.assistants.retrieve("asst_9msH6Qr6Sb6JCQRwW3aqFDUi") | |
| # print(my_assistant) | |
| from langchain.chat_models import ChatOpenAI | |
| from langchain.schema import AIMessage, HumanMessage | |
| llm = ChatOpenAI(temperature=1.0, model='gpt-4-1106-preview') | |
| 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 | |
| gr.ChatInterface(predict).launch(share=True) | |