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Update app.py
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app.py
CHANGED
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@@ -9,15 +9,14 @@ import base64
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from concurrent.futures import ThreadPoolExecutor
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from PIL import Image, ImageOps
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from fastapi import FastAPI, UploadFile, File, Form, HTTPException
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from fastapi.staticfiles import StaticFiles
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from fastapi.middleware.cors import CORSMiddleware
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import rarfile
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import zipfile
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# --- MIGRATION: New SDK Imports ---
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from google import genai
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from google.genai import types
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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@@ -52,112 +51,49 @@ def parse_filename_to_ms(filename):
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return (h * 3600000) + (m * 60000) + (s * 1000) + ms
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def parse_srt(content: str):
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Robust State Machine Parser for SRT (Backend Version).
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Matches Frontend logic to handle blank subtitles correctly.
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"""
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content = content.replace('\r\n', '\n').replace('\r', '\n')
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parsed = []
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if state == 'SEARCH_ID':
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if line.isdigit():
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current_item["id"] = line
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state = 'SEARCH_TIME'
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elif state == 'SEARCH_TIME':
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if '-->' in line:
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current_item["time"] = line
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state = 'READ_TEXT'
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# EDGE CASE: Immediate Blank Subtitle
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# If next line is a number (start of new ID), current block is blank
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if next_line and next_line.isdigit():
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# Check 2 lines ahead to confirm it's really an ID (followed by timestamp)
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line_after_next = lines[i+2].strip() if i + 2 < len(lines) else None
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if line_after_next and '-->' in line_after_next:
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# Close current blank block
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start_ms = parse_srt_time_to_ms(current_item["time"].split('-->')[0].strip())
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parsed.append({
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"id": current_item["id"],
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"time": current_item["time"],
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"startTimeMs": start_ms,
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"text": ""
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})
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current_item = {"id": None, "time": None, "text_lines": []}
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state = 'SEARCH_ID'
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elif line.isdigit():
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# Recover from missing timestamp
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current_item["id"] = line
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next_line and next_line.isdigit() and
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(i + 2 < len(lines) and '-->' in lines[i+2])
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)
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if is_new_block_start:
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# Missing blank separator, force close
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text = "\n".join(current_item["text_lines"]).strip() or ""
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start_ms = parse_srt_time_to_ms(current_item["time"].split('-->')[0].strip())
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parsed.append({
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"id": current_item["id"],
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"time": current_item["time"],
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"startTimeMs": start_ms,
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"text": text
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})
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current_item = {"id": line, "time": None, "text_lines": []}
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state = 'SEARCH_TIME'
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"text": text
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})
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current_item = {"id": None, "time": None, "text_lines": []}
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state = 'SEARCH_ID'
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else:
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if line:
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current_item["text_lines"].append(line)
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# Push last item
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if current_item["id"] and current_item["time"]:
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text = " ".join(current_item["text_lines"]).strip() or "[BLANK SUBTITLE]"
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start_ms = parse_srt_time_to_ms(current_item["time"].split('-->')[0].strip())
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parsed.append({
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"id": current_item["id"],
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"time": current_item["time"],
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"startTimeMs": start_ms,
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"text": text
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})
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return parsed
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def compress_image(image_bytes, max_width=800, quality=80):
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"""
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Compresses an image to WebP (best) or optimized JPEG.
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"""
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try:
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img = Image.open(io.BytesIO(image_bytes))
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@@ -168,6 +104,7 @@ def compress_image(image_bytes, max_width=800, quality=80):
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buffer = io.BytesIO()
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# 2. Try WebP first (Best quality/size ratio)
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use_webp = True
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if use_webp:
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@@ -199,14 +136,14 @@ def compress_image(image_bytes, max_width=800, quality=80):
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except Exception as e:
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logger.error(f"Image compression failed: {e}")
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return None
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# --- MIGRATION: Updated Gemini Processing Function ---
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def process_batch_gemini(api_key, items, model_name):
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try:
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client = genai.Client(api_key=api_key)
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prompt_parts = [
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"You are a Subtitle Quality Control (QC) bot.",
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@@ -221,18 +158,13 @@ def process_batch_gemini(api_key, items, model_name):
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prompt_parts.append(f"Index: {item['index']}")
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prompt_parts.append(f"Expected Text: \"{item['expected_text']}\"")
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prompt_parts.append(f"Image:")
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# The new SDK handles PIL images directly in the contents list just like the old one
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img = Image.open(io.BytesIO(item['image_data']))
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prompt_parts.append(img)
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#
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response =
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config=types.GenerateContentConfig(
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response_mime_type="application/json"
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)
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text = response.text.replace("```json", "").replace("```", "").strip()
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@@ -241,6 +173,7 @@ def process_batch_gemini(api_key, items, model_name):
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return json.loads(text)
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except json.JSONDecodeError as e:
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# Handle Truncated JSON (Output Token Limit Exceeded)
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logger.warning(f"JSON Parse Error (likely truncated response): {e}. Attempting repair...")
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# Repair Strategy: Find the last closing brace '}', discard everything after, and close the array ']'
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@@ -268,7 +201,7 @@ async def analyze_subtitles(
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media_files: list[UploadFile] = File(...),
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api_keys: str = Form(...),
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batch_size: int = Form(20),
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model_name: str = Form("gemini-
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compression_quality: float = Form(0.7)
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):
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temp_dir = tempfile.mkdtemp()
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from concurrent.futures import ThreadPoolExecutor
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from PIL import Image, ImageOps
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from fastapi import FastAPI, UploadFile, File, Form, HTTPException
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from fastapi.staticfiles import StaticFiles
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from fastapi.middleware.cors import CORSMiddleware
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from PIL import Image
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import rarfile
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import zipfile
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import google.generativeai as genai
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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return (h * 3600000) + (m * 60000) + (s * 1000) + ms
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def parse_srt(content: str):
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# Normalize line endings
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content = content.replace('\r\n', '\n').replace('\r', '\n')
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# Split by double newline (standard SRT block separator)
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blocks = re.split(r'\n\n+', content.strip())
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parsed = []
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for block in blocks:
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lines = [l.strip() for l in block.split('\n') if l.strip()]
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if len(lines) < 2:
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continue
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srt_id = lines[0]
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time_range = lines[1]
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# Check if there is actually text after the timestamp
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# If there are lines after index 1, join them; otherwise, it's a blank sub
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if len(lines) > 2:
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text = "\n".join(lines[2:])
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else:
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text = "" # Explicitly blank
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try:
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start_time_str = time_range.split('-->')[0].strip()
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start_ms = parse_srt_time_to_ms(start_time_str)
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parsed.append({
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"id": srt_id,
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"time": time_range,
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"startTimeMs": start_ms,
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"text": text
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})
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except Exception as e:
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logger.warning(f"Skipping malformed SRT block: {block[:50]}... Error: {e}")
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return parsed
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logger = logging.getLogger(__name__)
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def compress_image(image_bytes, max_width=800, quality=80):
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"""
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Compresses an image to WebP (best) or optimized JPEG.
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Renamed back to 'compress_image' to fix your error.
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"""
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try:
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img = Image.open(io.BytesIO(image_bytes))
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buffer = io.BytesIO()
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# 2. Try WebP first (Best quality/size ratio)
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# If you strictly need JPEG, change use_webp to False
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use_webp = True
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if use_webp:
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except Exception as e:
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logger.error(f"Image compression failed: {e}")
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# If logging isn't setup, print the error so you can see it
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print(f"Error: {e}")
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return None
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def process_batch_gemini(api_key, items, model_name):
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try:
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genai.configure(api_key=api_key)
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model = genai.GenerativeModel(model_name)
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prompt_parts = [
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"You are a Subtitle Quality Control (QC) bot.",
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prompt_parts.append(f"Index: {item['index']}")
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prompt_parts.append(f"Expected Text: \"{item['expected_text']}\"")
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prompt_parts.append(f"Image:")
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img = Image.open(io.BytesIO(item['image_data']))
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prompt_parts.append(img)
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# Enforce JSON mode
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response = model.generate_content(
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prompt_parts,
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generation_config={"response_mime_type": "application/json"}
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)
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text = response.text.replace("```json", "").replace("```", "").strip()
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return json.loads(text)
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except json.JSONDecodeError as e:
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# Handle Truncated JSON (Output Token Limit Exceeded)
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# This happens if the batch size is too large for the model's output window
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logger.warning(f"JSON Parse Error (likely truncated response): {e}. Attempting repair...")
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# Repair Strategy: Find the last closing brace '}', discard everything after, and close the array ']'
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media_files: list[UploadFile] = File(...),
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api_keys: str = Form(...),
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batch_size: int = Form(20),
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model_name: str = Form("gemini-3-flash-preview"),
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compression_quality: float = Form(0.7)
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):
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temp_dir = tempfile.mkdtemp()
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