File size: 2,029 Bytes
b25b8f2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | from fastapi import FastAPI, UploadFile, File, Form, HTTPException
from pydantic import BaseModel
from typing import Optional, Dict
import uvicorn
app = FastAPI(title="Input Receiver Service", description="Accepts and routes math problems in text or image format.")
class TextInputRequest(BaseModel):
text: str
metadata: Optional[Dict] = {}
@app.get("/health")
async def health_check():
"""Returns the health status of the Input Receiver service."""
return {"status": "healthy", "service": "input-receiver"}
@app.post("/receive/text")
async def receive_text(request: TextInputRequest):
"""
Accepts a math problem in text format and returns it in a standardized JSON payload.
This payload will subsequently be sent to the Preprocessing Service.
"""
if not request.text.strip():
raise HTTPException(status_code=400, detail="Text cannot be empty.")
return {
"status": "success",
"input_type": "text",
"data": request.text,
"metadata": request.metadata
}
@app.post("/receive/image")
async def receive_image(
file: UploadFile = File(...),
metadata: Optional[str] = Form("{}")
):
"""
Accepts a math problem as an image upload and returns a confirmation JSON payload.
The image bytes will subsequently be sent to the OCR Service.
"""
if file.content_type not in ["image/jpeg", "image/png"]:
raise HTTPException(status_code=400, detail="Invalid image format. Use JPEG or PNG.")
# In a real microservice, we might save this to an S3 bucket or shared volume and pass the URL/path.
# For MVP, we return a success format. The actual forwarding will be handled by the API Gateway.
return {
"status": "success",
"input_type": "image",
"filename": file.filename,
"content_type": file.content_type,
"metadata": metadata
}
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=8000)
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