FileResponse¶ Asynchronously streams a file as the response. Takes a different set of arguments to instantiate than the other response types: path- The file path to the file to stream. headers- Any custom headers to include, as a dictionary. ...
from typing import Annotated from fastapi import FastAPI, File, UploadFile from fastapi.responses import HTMLResponse app = FastAPI() @app.post("/files/") async def create_files(files: Annotated[list[bytes], File()]): return {"file_sizes": [len(file) for file in files]} @app.post("/...
from fastapi.responses import JSONResponse, HTMLResponse, FileResponse app = FastAPI() #创建访问路径 @app.get("/user") def user(): return JSONResponse( content = { "msg": "get user" }, status_code = 202, headers = { "a": "b" }) # 给返回的header增加新的key:a @app.get("/")...
from pydantic import BaseModel import ollama app = FastAPI( title="AI Service API", description="基于 Ollama + FastAPI 的 AI 服务", version="1.0.0" ) class RequestModel(BaseModel): prompt: str temperature: float = 0.7 max_tokens: int = 256 class ResponseModel(BaseModel): response: str...
db_url="sqlite://:memory:", modules={"models": [__name__]}, generate_schemas=True, ):await_initial_users() add_pagination(app)yieldapp = FastAPI(title="Tortoise ORM Pagination example", lifespan=lifespan) fastapi_cdn_host.patch_docs(app)@app.post("/users", response_model=UserOut)as...
#无量化,最低显存占用约16.5GBllm=LLM(model="qwen/Qwen-7B-Chat",trust_remote_code=True)#int4量化,最低显存占用约7GB# llm = LLM(model="qwen/Qwen-7B-Chat-int4", trust_remote_code=True,gpu_memory_utilization=0.35) 值得注意的是如果显存不够大,需要自行调整gpu_memory_utilization参数到一个合适...
return FileResponse("server_monitor_frontend/index.html") @app.get("/stats") async def get_server_stats(): # Your server stats logic here return {"cpu_percent": 50, "memory_percent": 60, "disk_percent": 70} if __name__ == "__main__": ...
File 是直接从 Form 继承的类。 But remember that when you import Query, Path, File and others from fastapi, those are actually functions that return special classes. 但是请记住,当您从 fastapi 中导入 Query、Path、File 和其他文件时,这些实际上是返回特殊类的函数。
from fastapi import FastAPI, Response import shutil import os app = FastAPI() @app.get("/download/{filename}") async def download_file(filename: str): file_path = f"./files/{filename}" if not os.path.exists(file_path): return Response(content="File not found", status_code=404) r...
image.save("image.png")returnFileResponse("image.png") @app.get("/generate-memory")defgenerate_image_memory( prompt: str,*, seed: int| None =None, num_inference_steps: int= 50, guidance_scale: float= 7.5): image=obtain_image(