Update app.py

app.py

@@ -1,64 +1,64 @@
+# CodeSearch-ModernBERT-Owl Demo Space using CodeSearchNet Dataset
 import gradio as gr
-from huggingface_hub import InferenceClient
+import torch
+import random
+from sentence_transformers import SentenceTransformer, util
+from datasets import load_dataset
+from spaces import GPU
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# --- Load model ---
+model = SentenceTransformer("Shuu12121/CodeSearch-ModernBERT-Owl")
+model.eval()
 
+# --- Load CodeSearchNet dataset (test split only) ---
+dataset_all = load_dataset("code_search_net", split="test")
+lang_filter = ["python", "java", "javascript", "ruby", "go", "php"]
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+# --- UI for language choice ---
+def get_random_query(lang: str, seed: int = 42):
+    subset = dataset_all.filter(lambda x: x["language"] == lang)
+    random.seed(seed)
+    idx = random.randint(0, len(subset) - 1)
+    sample = subset[idx]
+    return sample["function"] or "", sample["docstring"] or ""
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+@GPU
+def code_search_demo(lang: str, seed: int):
+    code_str, doc_str = get_random_query(lang, seed)
+    query_emb = model.encode(doc_str, convert_to_tensor=True)
 
-    messages.append({"role": "user", "content": message})
+    # ランダムに取得した同一言語の10件の関数とドキュメントを比較対象として選択
+    candidates = dataset_all.filter(lambda x: x["language"] == lang).shuffle(seed=seed).select(range(10))
+    candidate_texts = [c["function"] or "" for c in candidates]
+    candidate_embeddings = model.encode(candidate_texts, convert_to_tensor=True)
 
-    response = ""
+    # 類似度計算
+    cos_scores = util.cos_sim(query_emb, candidate_embeddings)[0]
+    results = sorted(zip(candidate_texts, cos_scores), key=lambda x: x[1], reverse=True)
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    # 結果フォーマット（ランキング付き）
+    output = f"### 🔍 Query Docstring (Language: {lang})\n\n" + doc_str + "\n\n"
+    output += "## 🏆 Top Matches:\n"
+    medals = ["🥇", "🥈", "🥉"] + [f"#{i+1}" for i in range(3, len(results))]
+    for i, (code, score) in enumerate(results):
+        label = medals[i] if i < len(medals) else f"#{i+1}"
+        output += f"\n**{label}** - Similarity: {score.item():.4f}\n\n```
+{code.strip()[:1000]}
+```\n"
 
-        response += token
-        yield response
+    return output
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+# --- Gradio Interface ---
+demo = gr.Interface(
+    fn=code_search_demo,
+    inputs=[
+        gr.Dropdown(["python", "java", "javascript", "ruby", "go", "php"], label="Language", value="python"),
+        gr.Slider(0, 100000, value=42, step=1, label="Random Seed")
     ],
+    outputs=gr.Markdown(label="Search Result"),
+    title="🔎 CodeSearch-ModernBERT-Owl Demo",
+    description="コードドキュメントから関数検索を行うデモ（CodeSearchNet + CodeModernBERT-Owl）"
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()