add more to can select model

app.py

@@ -28,14 +28,26 @@ TABLE_NAME = "Feedback_search"
 api = Api(AIRTABLE_API_KEY)
 table = api.table(BASE_ID, TABLE_NAME)
 
-# Load model
-model = SentenceTransformer('e5_finetuned')
-collection_name = "product_E5_finetune"
-
 # Load whitelist
 with open("keyword_whitelist.pkl", "rb") as f:
     keyword_whitelist = pickle.load(f)
 
+# Preload Models
+models = {
+    "E5 Finetuned": {
+        "model": SentenceTransformer("e5_finetuned"),
+        "collection": "product_E5_finetune",
+        "threshold": 0.8,
+        "prefix": "query: "
+    },
+    "BGE M3": {
+        "model": SentenceTransformer("BAAI/bge-m3"),
+        "collection": "product_bge-m3",
+        "threshold": 0.5,
+        "prefix": ""
+    }
+}
+
 # Utils
 def is_non_thai(text):
     return re.match(r'^[A-Za-z0-9&\-\s]+$', text) is not None
@@ -83,12 +95,19 @@ def correct_query_merge_phrases(query: str, whitelist, threshold=80, max_ngram=3
 # Global state
 latest_query_result = {"query": "", "result": "", "raw_query": "", "time": ""}
 
-# Main Search
-def search_product(query):
+# Search Function
+def search_product(query, model_choice):
     start_time = time.time()
     latest_query_result["raw_query"] = query
+
+    selected = models[model_choice]
+    model = selected["model"]
+    collection_name = selected["collection"]
+    threshold = selected["threshold"]
+    prefix = selected["prefix"]
+
     corrected_query = correct_query_merge_phrases(query, keyword_whitelist)
-    query_embed = model.encode("query: " + corrected_query)
+    query_embed = model.encode(prefix + corrected_query)
 
     try:
         result = qdrant_client.query_points(
@@ -107,10 +126,10 @@ def search_product(query):
         html_output += f"<p>🔧 แก้คำค้นจาก: <code>{query}</code> → <code>{corrected_query}</code></p>"
 
     html_output += '<div style="display: grid; grid-template-columns: repeat(auto-fill, minmax(220px, 1fr)); gap: 20px;">'
-
     result_summary, found = "", False
+
     for res in result:
-        if res.score > 0.8:
+        if res.score >= threshold:
             found = True
             name = res.payload.get("name", "ไม่ทราบชื่อสินค้า")
             score = f"{res.score:.4f}"
@@ -145,12 +164,12 @@ def search_product(query):
 
     return html_output
 
-# Feedback logging
-def log_feedback(feedback):
+# Feedback Function
+def log_feedback(feedback, model_choice):
     try:
         now = datetime.now().strftime("%Y-%m-%d")
         table.create({
-            "model": "E5 (intfloat/multilingual-e5-small)",
+            "model": model_choice,
             "timestamp": now,
             "raw_query": latest_query_result["raw_query"],
             "query": latest_query_result["query"],
@@ -166,7 +185,10 @@ def log_feedback(feedback):
 with gr.Blocks() as demo:
     gr.Markdown("## 🔎 Product Semantic Search (Vector Search + Qdrant)")
 
-    query_input = gr.Textbox(label="พิมพ์คำค้นหา")
+    with gr.Row():
+        model_selector = gr.Dropdown(label="🔍 เลือกโมเดล", choices=list(models.keys()), value="E5 Finetuned")
+        query_input = gr.Textbox(label="พิมพ์คำค้นหา")
+
     result_output = gr.HTML(label="📋 ผลลัพธ์")
 
     with gr.Row():
@@ -175,9 +197,8 @@ with gr.Blocks() as demo:
 
     feedback_status = gr.Textbox(label="📬 สถานะ Feedback")
 
-    query_input.submit(search_product, inputs=[query_input], outputs=result_output)
-    match_btn.click(lambda: log_feedback("match"), outputs=feedback_status)
-    not_match_btn.click(lambda: log_feedback("not_match"), outputs=feedback_status)
+    query_input.submit(search_product, inputs=[query_input, model_selector], outputs=result_output)
+    match_btn.click(fn=lambda model: log_feedback("match", model), inputs=model_selector, outputs=feedback_status)
+    not_match_btn.click(fn=lambda model: log_feedback("not_match", model), inputs=model_selector, outputs=feedback_status)
 
-# Run
 demo.launch(share=True)