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import argparse
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import uvicorn
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from fastapi import Body, FastAPI, HTTPException, Query
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import HTMLResponse
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from pydantic import BaseModel
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import os
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from deepsearcher.configuration import Configuration, init_config
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from deepsearcher.offline_loading import load_from_local_files, load_from_website
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from deepsearcher.online_query import query
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app = FastAPI()
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config = Configuration()
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init_config(config)
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class ProviderConfigRequest(BaseModel):
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"""
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Request model for setting provider configuration.
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Attributes:
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feature (str): The feature to configure (e.g., 'embedding', 'llm').
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provider (str): The provider name (e.g., 'openai', 'azure').
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config (Dict): Configuration parameters for the provider.
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"""
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feature: str
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provider: str
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config: dict
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@app.get("/", response_class=HTMLResponse)
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async def read_root():
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"""
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Serve the main HTML page.
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"""
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# 获取当前文件所在目录
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current_dir = os.path.dirname(os.path.abspath(__file__))
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# 构建模板文件路径 - 修复路径问题
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template_path = os.path.join(current_dir, "deepsearcher", "backend", "templates", "index.html")
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# 读取HTML文件内容
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try:
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with open(template_path, encoding="utf-8") as file:
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html_content = file.read()
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return HTMLResponse(content=html_content, status_code=200)
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except FileNotFoundError:
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# 如果找不到文件，提供一个简单的默认页面
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default_html = f"""
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<!DOCTYPE html>
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<html>
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<head>
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<title>DeepSearcher</title>
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<meta charset="utf-8">
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<style>
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body {{ font-family: Arial, sans-serif; margin: 40px; }}
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.container {{ max-width: 800px; margin: 0 auto; }}
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h1 {{ color: #333; }}
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.info {{ background: #f0f8ff; padding: 15px; border-radius: 5px; }}
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.error {{ background: #ffe4e1; padding: 15px; border-radius: 5px; color: #d00; }}
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</style>
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</head>
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<body>
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<div class="container">
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<h1>DeepSearcher</h1>
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<div class="info">
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<p>欢迎使用 DeepSearcher 智能搜索系统!</p>
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<p>系统正在运行，但未找到前端模板文件。</p>
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<p>请确认文件是否存在: {template_path}</p>
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</div>
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<div class="info">
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<h2>API 接口</h2>
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<p>您仍然可以通过以下 API 接口使用系统:</p>
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<ul>
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<li><code>POST /load-files/</code> - 加载本地文件</li>
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<li><code>POST /load-website/</code> - 加载网站内容</li>
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<li><code>GET /query/</code> - 执行查询</li>
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</ul>
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<p>有关 API 使用详情，请查看 <a href="/docs">API 文档</a></p>
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</div>
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</div>
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</body>
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</html>
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"""
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return HTMLResponse(content=default_html, status_code=200)
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@app.post("/set-provider-config/")
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def set_provider_config(request: ProviderConfigRequest):
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"""
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Set configuration for a specific provider.
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Args:
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request (ProviderConfigRequest): The request containing provider configuration.
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Returns:
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dict: A dictionary containing a success message and the updated configuration.
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Raises:
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HTTPException: If setting the provider config fails.
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"""
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try:
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config.set_provider_config(request.feature, request.provider, request.config)
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init_config(config)
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return {
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"message": "Provider config set successfully",
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"provider": request.provider,
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"config": request.config,
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Failed to set provider config: {str(e)}")
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@app.post("/load-files/")
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def load_files(
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paths: str | list[str] = Body(
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...,
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description="A list of file paths to be loaded.",
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examples=["/path/to/file1", "/path/to/file2", "/path/to/dir1"],
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),
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collection_name: str = Body(
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None,
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description="Optional name for the collection.",
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examples=["my_collection"],
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),
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collection_description: str = Body(
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None,
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description="Optional description for the collection.",
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examples=["This is a test collection."],
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),
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batch_size: int = Body(
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None,
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description="Optional batch size for the collection.",
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examples=[256],
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),
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):
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"""
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Load files into the vector database.
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Args:
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paths (Union[str, List[str]]): File paths or directories to load.
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collection_name (str, optional): Name for the collection. Defaults to None.
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collection_description (str, optional): Description for the collection. Defaults to None.
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batch_size (int, optional): Batch size for processing. Defaults to None.
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Returns:
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dict: A dictionary containing a success message.
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Raises:
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HTTPException: If loading files fails.
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"""
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try:
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# 修复batch_size为None时的问题
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load_from_local_files(
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paths_or_directory=paths,
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collection_name=collection_name,
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collection_description=collection_description,
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batch_size=batch_size if batch_size is not None else 8, # 提供默认值
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)
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return {"message": "Files loaded successfully."}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@app.post("/load-website/")
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def load_website(
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urls: str | list[str] = Body(
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...,
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description="A list of URLs of websites to be loaded.",
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examples=["https://milvus.io/docs/overview.md"],
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),
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collection_name: str = Body(
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None,
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description="Optional name for the collection.",
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examples=["my_collection"],
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),
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collection_description: str = Body(
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None,
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description="Optional description for the collection.",
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examples=["This is a test collection."],
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),
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batch_size: int = Body(
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None,
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description="Optional batch size for the collection.",
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examples=[256],
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),
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):
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"""
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Load website content into the vector database.
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Args:
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urls (Union[str, List[str]]): URLs of websites to load.
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collection_name (str, optional): Name for the collection. Defaults to None.
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collection_description (str, optional): Description for the collection. Defaults to None.
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batch_size (int, optional): Batch size for processing. Defaults to None.
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Returns:
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dict: A dictionary containing a success message.
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Raises:
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HTTPException: If loading website content fails.
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"""
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try:
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# 修复batch_size为None时的问题
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load_from_website(
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urls=urls,
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collection_name=collection_name,
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collection_description=collection_description,
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batch_size=batch_size if batch_size is not None else 256, # 提供默认值
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)
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return {"message": "Website loaded successfully."}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/query/")
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def perform_query(
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original_query: str = Query(
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...,
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description="Your question here.",
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examples=["Write a report about Milvus."],
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),
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max_iter: int = Query(
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3,
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description="The maximum number of iterations for reflection.",
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ge=1,
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examples=[3],
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),
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):
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"""
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Perform a query against the loaded data.
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Args:
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original_query (str): The user's question or query.
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max_iter (int, optional): Maximum number of iterations for reflection. Defaults to 3.
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Returns:
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dict: A dictionary containing the query result and token consumption.
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Raises:
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HTTPException: If the query fails.
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"""
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try:
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# 清除之前的进度消息
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from deepsearcher.utils.log import clear_progress_messages
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clear_progress_messages()
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result_text, _, consume_token = query(original_query, max_iter)
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# 获取进度消息
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from deepsearcher.utils.log import get_progress_messages
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progress_messages = get_progress_messages()
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return {
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"result": result_text,
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"consume_token": consume_token,
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"progress_messages": progress_messages
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="FastAPI Server")
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parser.add_argument("--host", type=str, default="0.0.0.0", help="Host to bind the server to")
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parser.add_argument("--port", type=int, default=8000, help="Port to bind the server to")
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parser.add_argument("--enable-cors", action="store_true", default=False, help="Enable CORS support")
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args = parser.parse_args()
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if args.enable_cors:
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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print("CORS is enabled.")
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else:
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print("CORS is disabled.")
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print(f"Starting server on {args.host}:{args.port}")
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uvicorn.run(app, host=args.host, port=args.port)
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