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| import os | |
| from tools import FindResearchDirectionsTool, JudgeNoveltyTool, FindReferencesTool | |
| from langchain.chat_models import ChatOpenAI | |
| from langchain.agents import initialize_agent | |
| from langchain.agents import AgentType | |
| import openai | |
| from langchain.schema import SystemMessage | |
| from langchain.memory import ConversationBufferMemory | |
| openai.api_key = os.getenv("OPENAI_API_KEY") | |
| print(os.getenv("OPENAI_API_KEY")) | |
| default_model = os.getenv("DEFAULT_MODEL") | |
| if default_model is None: | |
| default_model = "gpt-3.5-turbo-16k" | |
| import chainlit as cl | |
| agent_kwargs = { | |
| "system_message": SystemMessage(content="You are a mighty cyber professor. " | |
| "Your task is to assist your student to find an idea of research including:" | |
| "1. Search related references." | |
| "2. Propose potential research directions." | |
| "3. Evaluate the novelty of any research direction." | |
| "Follow the following instructions: " | |
| "1. You always response in the same language as your student." | |
| "2. Ask your student for further information if necessary to provide more assistance. ") | |
| } | |
| memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True) | |
| def main(): | |
| tools = [FindResearchDirectionsTool(), JudgeNoveltyTool(), FindReferencesTool()] | |
| llm = ChatOpenAI(temperature=0.9, model=default_model, streaming=True) | |
| open_ai_agent = initialize_agent(tools, | |
| llm, | |
| agent=AgentType.OPENAI_FUNCTIONS, | |
| verbose=True, | |
| agent_kwargs=agent_kwargs, | |
| memory=memory) | |
| return open_ai_agent | |
| async def run(agent, input_str): | |
| res = await cl.make_async(agent)(input_str, callbacks=[cl.LangchainCallbackHandler()]) | |
| print(res) | |
| await cl.Message(content=res["output"]).send() |