Spaces:
Running
Running
Change to Gradio
Browse files- Dockerfile +15 -2
- app.py +31 -6
- requirements.txt +6 -3
Dockerfile
CHANGED
@@ -13,5 +13,18 @@ RUN pip install -r requirements.txt
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# 公开 Gradio 默认的端口 7860
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EXPOSE 7860
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#
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# 公开 Gradio 默认的端口 7860
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EXPOSE 7860
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# Set up a new user named "user" with user ID 1000
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RUN useradd -m -u 1000 user
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# Switch to the "user" user
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USER user
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# Set home to the user's home directory
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ENV HOME=/home/user \
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PATH=/home/user/.local/bin:$PATH
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# Set the working directory to the user's home directory
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WORKDIR $HOME/app
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# Copy the current directory contents into the container at $HOME/app setting the owner to the user
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COPY --chown=user . $HOME/app
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]
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app.py
CHANGED
@@ -3,6 +3,9 @@ from fastapi import FastAPI
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from pydantic import BaseModel
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from fastapi.middleware.wsgi import WSGIMiddleware
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app = FastAPI() # 创建 FastAPI 应用
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# 定义请求模型
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@@ -11,7 +14,20 @@ class TextRequest(BaseModel):
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# 定义两个 API 路由处理函数
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@app.post("/api/aaa")
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async def
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result = request.text + 'aaa'
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return {"result": result}
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@@ -20,12 +36,21 @@ async def api_bbb(request: TextRequest):
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result = request.text + 'bbb'
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return {"result": result}
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@app.get("/")
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async def root():
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return {"message": "Welcome to the API. Use /api/aaa or /api/bbb for processing."}
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# 启动应用,使用环境变量指定的端口
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if __name__ == "__main__":
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import uvicorn
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port = int(os.getenv("PORT", 7860)) # 获取 PORT 环境变量
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uvicorn.run(app, host="0.0.0.0", port=port)
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from pydantic import BaseModel
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from fastapi.middleware.wsgi import WSGIMiddleware
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from transformers import pipeline
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app = FastAPI() # 创建 FastAPI 应用
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# 定义请求模型
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# 定义两个 API 路由处理函数
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@app.post("/api/aaa")
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async def api_aaa_post(request: TextRequest):
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result = request.text + 'aaa'
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return {"result": result}
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# 定义两个 API 路由处理函数
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@app.post("/aaa")
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async def aaa(request: TextRequest):
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result = request.text + 'aaa'
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return {"result": result}
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# 定义两个 API 路由处理函数
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@app.get("/aaa")
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async def api_aaa_get(request: TextRequest):
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result = request.text + 'aaa'
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return {"result": result}
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result = request.text + 'bbb'
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return {"result": result}
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pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")
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@app.get("/infer_t5")
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def t5_get(input):
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output = pipe_flan(input)
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return {"output": output[0]["generated_text"]}
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@app.post("/infer_t5")
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def t5_post(input):
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output = pipe_flan(input)
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return {"output": output[0]["generated_text"]}
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@app.get("/")
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async def root():
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return {"message": "Welcome to the API. Use /api/aaa or /api/bbb for processing."}
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requirements.txt
CHANGED
@@ -1,4 +1,3 @@
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gradio
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transformers
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akshare
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blis==0.7.11
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@@ -6,5 +5,9 @@ spacy==3.7.5
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gensim
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numpy
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gensim
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fastapi
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transformers
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akshare
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blis==0.7.11
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gensim
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numpy
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gensim
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fastapi==0.74.*
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requests==2.27.*
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sentencepiece==0.1.*
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torch==1.11.*
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transformers==4.*
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uvicorn[standard]==0.17.*
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