Python中llama_index与llama_parse导入无法解析问题求助
问题描述(中文翻译)
我正在开发一个多LLM代理Python程序,参考Tech with Tim的教程视频完成了环境配置:创建并激活了虚拟环境(venv),安装了llama_index、llama_parse等所需依赖。但运行代码时,所有llama_index相关导入及llama_parse导入均提示“Import 'xxx' could not be resolved”,我的Python版本为3.11.8,相关代码如下:
from llama_index.llms.ollama import Ollama from llama_parse import LlamaParse from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, PromptTemplate from llama_index.core.embeddings import resolve_embed_model from llama_index.core.tools import QueryEngineTool, ToolMetadata from llama_index.core.agent import ReActAgent from pydantic import BaseModel from llama_index.core.output_parsers import PydanticOutputParser from llama_index.core.query_pipeline import QueryPipeline from prompts import context, code_parser_template from code_reader import code_reader from dotenv import load_dotenv import os import ast load_dotenv() llm = Ollama(model="mistral", request_timeout=30.0) parser = LlamaParse(result_type="markdown") file_extractor = {".pdf": parser} documents = SimpleDirectoryReader("./data", file_extractor=file_extractor).load_data() embed_model = resolve_embed_model("local:BAAI/bge-m3") vector_index = VectorStoreIndex.from_documents(documents, embed_model=embed_model) query_engine = vector_index.as_query_engine(llm=llm) tools = [ QueryEngineTool( query_engine=query_engine, metadata=ToolMetadata( name="api_documentation", description="this gives documentation about code for an API. Use this for reading docs for the API", ), ), code_reader, ] code_llm = Ollama(model="codellama") agent = ReActAgent.from_tools(tools, llm=code_llm, verbose=True, context=context) class CodeOutput(BaseModel): code: str description: str filename: str parser = PydanticOutputParser(CodeOutput) json_prompt_str = parser.format(code_parser_template) json_prompt_tmpl = PromptTemplate(json_prompt_str) output_pipeline = QueryPipeline(chain=[json_prompt_tmpl, llm]) while (prompt := input("Enter a prompt (q to quit): ")) != "q": retries = 0 while retries < 3: try: result = agent.query(prompt) next_result = output_pipeline.run(response=result) cleaned_json = ast.literal_eval(str(next_result).replace("assistant:", "")) break except Exception as e: retries += 1 print(f"Error occured, retry #{retries}:", e) if retries >= 3: print("Unable to process request, try again...") continue print("Code generated") print(cleaned_json["code"]) print("\n\nDesciption:", cleaned_json["description"]) filename = cleaned_json["filename"] try: with open(os.path.join("output", filename), "w") as f: f.write(cleaned_json["code"]) print("Saved file", filename) except: print("Error saving file...")
请问我哪里操作出错了?
问题排查与解决方法
确认虚拟环境激活状态
运行代码前必须确保venv已正确激活:- Windows系统:执行
venv\Scripts\activate - macOS/Linux系统:执行
source venv/bin/activate
激活成功后终端会显示(venv)前缀,此时再运行代码。
- Windows系统:执行
检查依赖是否安装在虚拟环境中
激活venv后执行pip list,查看输出是否包含llama-index、llama-parse、pydantic、python-dotenv这些包。如果缺失,重新安装:pip install llama-index llama-parse pydantic python-dotenv注意:PyPI上的包名是
llama-index(带连字符),如果之前用llama_index(下划线)安装会失败。校准IDE的Python解释器
如果用VS Code或PyCharm,需确保IDE使用的是虚拟环境内的Python解释器:- VS Code:按
Ctrl+Shift+P(Windows)/Cmd+Shift+P(macOS),输入Python: Select Interpreter,选择venv目录下的Python程序。 - PyCharm:依次点击
File → Settings → Project: [项目名] → Python Interpreter,选择对应的venv解释器。
- VS Code:按
终端验证导入有效性
激活venv后打开Python交互环境(输入python),手动执行导入语句:from llama_index.llms.ollama import Ollama from llama_parse import LlamaParse如果终端能成功导入,说明是IDE配置问题;如果终端也报错,卸载重装依赖:
pip uninstall -y llama-index llama-parse pip install llama-index llama-parse确认虚拟环境Python版本
激活venv后执行python --version,确保版本为3.11.8,避免误用到系统全局的其他Python版本。
内容的提问来源于stack exchange,提问作者Joshie
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