Simplify Dockerfile and app.py configuration

- Remove commented-out HuggingFace and environment-related code
- Add user creation in Dockerfile for improved security
- Update base image to standard Python 3.9
- Modify file copying to use chown for better permissions
- Adjust CMD to use port 7860 consistently

Dockerfile

@@ -1,15 +1,16 @@
-FROM python:3.9-slim
+FROM python:3.9
 
+RUN useradd -m -u 1000 user
 WORKDIR /app
 
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
 
-COPY . .
+COPY --chown=user . /app
 
-EXPOSE 8000
+# EXPOSE 8000
 
-RUN --mount=type=secret,id=HUGGINGFACE_TOKEN,mode=0444,required=true \
-    test -f /run/secrets/HUGGINGFACE_TOKEN && echo "Secret exists!"
+# RUN --mount=type=secret,id=HUGGINGFACE_TOKEN,mode=0444,required=true \
+#     test -f /run/secrets/HUGGINGFACE_TOKEN && echo "Secret exists!"
 
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -1,17 +1,17 @@
 from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-from huggingface_hub import InferenceClient
+# from pydantic import BaseModel
+# from huggingface_hub import InferenceClient
 
-from langchain_core.messages import HumanMessage, AIMessage
-from langgraph.checkpoint.memory import MemorySaver
-from langgraph.graph import START, MessagesState, StateGraph
+# from langchain_core.messages import HumanMessage, AIMessage
+# from langgraph.checkpoint.memory import MemorySaver
+# from langgraph.graph import START, MessagesState, StateGraph
 
-import os
-from dotenv import load_dotenv
-load_dotenv()
+# import os
+# from dotenv import load_dotenv
+# load_dotenv()
 
-HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN", os.getenv("HUGGINGFACE_TOKEN"))
-print(HUGGINGFACE_TOKEN)
+# HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN", os.getenv("HUGGINGFACE_TOKEN"))
+# print(HUGGINGFACE_TOKEN)
 
 # Initialize the HuggingFace model
 # model = InferenceClient(
@@ -109,6 +109,6 @@ async def api_home():
 #     except Exception as e:
 #         raise HTTPException(status_code=500, detail=f"Error al generar texto: {str(e)}")
 
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+# if __name__ == "__main__":
+#     import uvicorn
+#     uvicorn.run(app, host="0.0.0.0", port=7860)