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Zaious commited on
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eb0ade0
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1 Parent(s): 7fb15d2

Update app.py

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Files changed (1) hide show
  1. app.py +51 -48
app.py CHANGED
@@ -15,53 +15,55 @@ MAX_TOKENS = 1024
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  # ---------- ❷ JSON Schema ----------
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  product_schema = {
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  "name": "RetailPriceTagSchema",
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- "description": "A list of products extracted from retail price-tag photos.",
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- "strict": True, # 讓模型一定要符合 schema，否則自動重試
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  "schema": {
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- "type": "array",
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- "items": {
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- "type": "object",
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- "properties": {
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- "name": {
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- "type": "string",
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- "description": "商品完整名稱；若無或無法辨識請輸出『無法辨識』"
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- },
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- "list_price": {
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- "type": "string",
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- "description": "標價上標示的原價 (未折扣)；若無或無法辨識請輸出『無法辨識』"
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- },
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- "promo_price": {
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- "type": "string",
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- "description": "促銷／特價；若無或無法辨識請輸出『無法辨識』"
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- },
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- "weight": {
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- "type": "string",
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- "description": "總重量 (g / kg 等)；若無或無法辨識請輸出『無法辨識』"
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- },
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- "volume": {
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- "type": "string",
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- "description": "總量 (ml / L / pcs 等)；若無或無法辨識請輸出『無法辨識』"
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- },
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- "barcode": {
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- "type": "string",
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- "description": "EAN／UPC／13 碼條碼；若無或無法辨識請輸出『無法辨識』"
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- },
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- "item_code": {
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- "type": "string",
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- "description": "通路自用貨號／PLU；若無或無法辨識請輸出『無法辨識』"
 
 
 
 
 
 
 
 
 
 
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  }
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- },
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- "required": [
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- "name",
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- "list_price",
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- "promo_price",
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- "weight",
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- "volume",
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- "barcode",
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- "item_code"
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- ],
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- "additionalProperties": False
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- }
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  }
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  }
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@@ -106,13 +108,14 @@ def call_gpt4o(image_paths):
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  def process(images):
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  paths = [img.name for img in images]
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- all_items = call_gpt4o(paths)
 
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  # (1) JSON pretty print
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- json_str = json.dumps(all_items, ensure_ascii=False, indent=2)
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  # (2) to Excel
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- df = pd.DataFrame(all_items)
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  bio = io.BytesIO()
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  df.to_excel(bio, index=False, engine="openpyxl")
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  bio.seek(0)
 
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  # ---------- ❷ JSON Schema ----------
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  product_schema = {
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  "name": "RetailPriceTagSchema",
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+ "description": "Products extracted from retail price-tag photos.",
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+ "strict": True,
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  "schema": {
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+ "type": "object",
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+ "properties": {
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+ "products": {
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+ "type": "array",
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+ "items": {
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+ "type": "object",
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+ "properties": {
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+ "name": {
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+ "type": "string",
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+ "description": "完整商品名稱；若無或無法辨識請輸出『無法辨識』"
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+ },
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+ "list_price": {
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+ "type": "string",
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+ "description": "原價；若無或無法辨識請輸出『無法辨識』"
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+ },
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+ "promo_price": {
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+ "type": "string",
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+ "description": "促銷／特價；若無或無法辨識請輸出『無法辨識』"
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+ },
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+ "weight": {
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+ "type": "string",
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+ "description": "總重量；若無或無法辨識請輸出『無法辨識』"
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+ },
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+ "volume": {
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+ "type": "string",
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+ "description": "總量；若無或無法辨識請輸出『無法辨識』"
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+ },
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+ "barcode": {
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+ "type": "string",
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+ "description": "條碼號；若無或無法辨識請輸出『無法辨識』"
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+ },
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+ "item_code": {
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+ "type": "string",
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+ "description": "通路自用貨號／PLU；若無或無法辨識請輸出『無法辨識』"
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+ }
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+ },
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+ "required": [
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+ "name", "list_price", "promo_price",
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+ "weight", "volume", "barcode", "item_code"
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+ ],
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+ "additionalProperties": False
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  }
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+ }
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+ },
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+ "required": ["products"],
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+ "additionalProperties": False
 
 
 
 
 
 
 
 
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  }
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  }
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  def process(images):
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  paths = [img.name for img in images]
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+ payload = call_gpt4o(paths) # payload 是 {"products":[ {...}, ... ]}
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+ items = payload.get("products", [])
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  # (1) JSON pretty print
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+ json_str = json.dumps(items, ensure_ascii=False, indent=2)
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  # (2) to Excel
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+ df = pd.DataFrame(items)
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  bio = io.BytesIO()
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  df.to_excel(bio, index=False, engine="openpyxl")
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  bio.seek(0)