Update app.py

app.py

@@ -2,12 +2,10 @@
 Visiting Card & Letterhead OCR API
 ===================================
 Two-step pipeline: nemoretriever-ocr-v1 → nvidia-nemotron-nano-9b-v2
-
 Deploy on Hugging Face Spaces (Docker or Python SDK):
   - Set secret  NVIDIA_API_KEY  in Space settings → Variables and secrets
   - The app serves the HTML frontend at  /  and the API at  /extract-card
   - HF Spaces exposes port 7860 by default (set via HF_PORT env var)
-
 Local usage:
   pip install fastapi uvicorn requests python-multipart
   NVIDIA_API_KEY=nvapi-xxx python visiting_card_api.py
@@ -57,7 +55,6 @@ CARD_SYSTEM_PROMPT = """You are a business card and letterhead data extraction a
 You will receive raw OCR text extracted from a visiting card, business card, or the header/footer of a business letter.
 Parse it carefully and return ONLY a valid JSON object.
 No markdown fences, no explanation, no preamble — just the raw JSON object.
-
 JSON schema (return exactly this structure):
 {
   "company_name": "full name of the company or firm (string)",
@@ -75,7 +72,6 @@ JSON schema (return exactly this structure):
   "website": "website URL if present (string)",
   "fax": "fax number if present (string)"
 }
-
 Rules:
 - company_name: usually the largest text or the text near a logo
 - contact_person: individual's personal name distinct from company name
@@ -102,10 +98,19 @@ async def run_ocr(file: UploadFile) -> str:
     content = await file.read()
     image_b64 = base64.b64encode(content).decode()
 
-    if len(image_b64) >= 500_000:
-        raise HTTPException(413, "Image too large. Resize and retry.")
+    # Matches reference: base64 must be < 180,000 characters
+    if len(image_b64) >= 180_000:
+        raise HTTPException(413, "Image too large (base64 must be < 180,000 chars). Resize and retry.")
 
-    payload = {"input": [{"type": "image_url", "url": f"data:image/png;base64,{image_b64}"}]}
+    # Payload structure matches the official reference exactly
+    payload = {
+        "input": [
+            {
+                "type": "image_url",
+                "url": f"data:image/png;base64,{image_b64}",
+            }
+        ]
+    }
 
     try:
         r = requests.post(OCR_URL, headers=OCR_HEADERS, json=payload, timeout=30)
@@ -260,4 +265,4 @@ async def serve_ui():
 if __name__ == "__main__":
     import uvicorn
     port = int(os.environ.get("HF_PORT", 7860))
-    uvicorn.run("app:app", host="0.0.0.0", port=port, reload=False)
+    uvicorn.run("app:app", host="0.0.0.0", port=port, reload=False)