= qa_chain({"question": user_input})result    Fetching pages: 100%|###################################################################################################################################| 1/1 [00:00<00:00,  3.33it/s]    {'question': 'How do LLM Powered Autonomous Agents work?',     'answer': "LLM Powered Autonomous Agents work by using LLM (large language model) as the core controller of the agent's brain. It is complemented by several key components, including planning, memory, and tool use. The agent system is designed to be a powerful general problem solver. \n",     'sources': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}Run with logging‚ÄãHere, we use get_relevant_documents method to return docs.# Runimport logginglogging.basicConfig()logging.getLogger("langchain.retrievers.web_research").setLevel(logging.INFO)user_input = "What is Task Decomposition in LLM Powered Autonomous Agents?"docs = web_research_retriever.get_relevant_documents(user_input)    INFO:langchain.retrievers.web_research:Generating questions for Google Search ...    INFO:langchain.retrievers.web_research:Questions for Google Search (raw): {'question': 'What is Task Decomposition in LLM Powered Autonomous Agents?', 'text': LineList(lines=['1. How do LLM powered autonomous agents utilize task decomposition?\n', '2. Can you explain the concept of task decomposition in LLM powered autonomous agents?\n', '3. What role does task decomposition play in the functioning of LLM powered autonomous agents?\n', '4. Why is task decomposition important for LLM powered autonomous agents?\n'])}    INFO:langchain.retrievers.web_research:Questions for Google Search: ['1. How do LLM powered autonomous agents utilize task decomposition?\n', '2. Can you explain the concept of task decomposition in LLM powered autonomous agents?\n', '3. What role does task decomposition play in the functioning of LLM powered autonomous agents?\n', '4. Why is task decomposition important for LLM powered
Given a query, this retriever will:
Given a query, this retriever will: ->: = qa_chain({"question": user_input})result    Fetching pages: 100%|###################################################################################################################################| 1/1 [00:00<00:00,  3.33it/s]    {'question': 'How do LLM Powered Autonomous Agents work?',     'answer': "LLM Powered Autonomous Agents work by using LLM (large language model) as the core controller of the agent's brain. It is complemented by several key components, including planning, memory, and tool use. The agent system is designed to be a powerful general problem solver. \n",     'sources': 'https://lilianweng.github.io/posts/2023-06-23-agent/'}Run with logging‚ÄãHere, we use get_relevant_documents method to return docs.# Runimport logginglogging.basicConfig()logging.getLogger("langchain.retrievers.web_research").setLevel(logging.INFO)user_input = "What is Task Decomposition in LLM Powered Autonomous Agents?"docs = web_research_retriever.get_relevant_documents(user_input)    INFO:langchain.retrievers.web_research:Generating questions for Google Search ...    INFO:langchain.retrievers.web_research:Questions for Google Search (raw): {'question': 'What is Task Decomposition in LLM Powered Autonomous Agents?', 'text': LineList(lines=['1. How do LLM powered autonomous agents utilize task decomposition?\n', '2. Can you explain the concept of task decomposition in LLM powered autonomous agents?\n', '3. What role does task decomposition play in the functioning of LLM powered autonomous agents?\n', '4. Why is task decomposition important for LLM powered autonomous agents?\n'])}    INFO:langchain.retrievers.web_research:Questions for Google Search: ['1. How do LLM powered autonomous agents utilize task decomposition?\n', '2. Can you explain the concept of task decomposition in LLM powered autonomous agents?\n', '3. What role does task decomposition play in the functioning of LLM powered autonomous agents?\n', '4. Why is task decomposition important for LLM powered