from pathlib import Pathfrom shutil import rmtreeimport httpxfrom phi.agent import Agentfrom phi.knowledge.llamaindex import LlamaIndexKnowledgeBasefrom llama_index.core import ( SimpleDirectoryReader, StorageContext, VectorStoreIndex,)from llama_index.core.retrievers import VectorIndexRetrieverfrom llama_index.core.node_parser import SentenceSplitterdata_dir = Path(__file__).parent.parent.parent.joinpath("wip", "data", "paul_graham")if data_dir.is_dir(): rmtree(path=data_dir, ignore_errors=True)data_dir.mkdir(parents=True, exist_ok=True)url = "https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt"file_path = data_dir.joinpath("paul_graham_essay.txt")response = httpx.get(url)if response.status_code == 200: with open(file_path, "wb") as file: file.write(response.content) print(f"File downloaded and saved as {file_path}")else: print("Failed to download the file")documents = SimpleDirectoryReader(str(data_dir)).load_data()splitter = SentenceSplitter(chunk_size=1024)nodes = splitter.get_nodes_from_documents(documents)storage_context = StorageContext.from_defaults()index = VectorStoreIndex(nodes=nodes, storage_context=storage_context)retriever = VectorIndexRetriever(index)# Create a knowledge base from the vector storeknowledge_base = LlamaIndexKnowledgeBase(retriever=retriever)# Create an agent with the knowledge baseagent = Agent(knowledge_base=knowledge_base, search_knowledge=True, debug_mode=True, show_tool_calls=True)# Use the agent to ask a question and print a response.agent.print_response("Explain what this text means: low end eats the high end", markdown=True)