Fix Gradio TypeError and improve stability

.git.bfg-report/2025-06-23/16-51-48/cache-stats.txt

@@ -0,0 +1,4 @@
+(apply,CacheStats{hitCount=28, missCount=33, loadSuccessCount=33, loadExceptionCount=0, totalLoadTime=47715790, evictionCount=0})
+(tree,CacheStats{hitCount=42, missCount=31, loadSuccessCount=26, loadExceptionCount=0, totalLoadTime=35716500, evictionCount=0})
+(commit,CacheStats{hitCount=16, missCount=17, loadSuccessCount=17, loadExceptionCount=0, totalLoadTime=23264831, evictionCount=0})
+(tag,CacheStats{hitCount=0, missCount=0, loadSuccessCount=0, loadExceptionCount=0, totalLoadTime=0, evictionCount=0})

.git.bfg-report/2025-06-23/16-51-48/deleted-files.txt

@@ -0,0 +1,19 @@
+b464e0844c71e081ff52a56c9e0185fae1e7f091 13499 20241128Target.csv
+12fd4bc63187592eaf8774619ed93039bc22b0b8 1675002 JRCT20241128Cancer.csv
+75193609202daad74bf20574efa2998d033f2525 1970586 JRCT20241129Cancer.csv
+fddba4eb2ea34774796ea8b29fe2d3c5e9ca29d7 170866 JRCT20241129sarcoma.csv
+38ddf366adc69aaa790a1fd518b34a4184bca2e7 2145242 JRCT20241130Cancer.csv
+b0a38d3d7fab4c7f875e63fc8e61fd2e883923a8 7812338 JRCT20241202Cancer.csv
+516fa4643149c94329bbc483b5a10902c2d8bb50 6089937 JRCT20241215Cancer.csv
+f50413b6c21e28436c8a2a98d53126f3c3dd9d6f 16738554 JRCT20241215CancerPost.csv
+5d19c61671ad4a07c27a9c26f36a622615b7d267 5954 filtered_data.csv
+730debd9e9ba9dc2ac5626ca140b8e6c9df0cd47 17860 filtered_data.csv
+b75b1891e46b333a806998ed0670f72990ab87fa 7047 filtered_data.csv
+521959385eee36afaa7154e0de234a4b4cc8903f 82505 full_data.csv
+8fdf03175b47be64ae2ed2ebe5b4ae1992d536b6 18116 full_data.csv
+f3358b9c5f9982181fbeaa76338f565d514bb204 554548 gabage.csv
+12fd4bc63187592eaf8774619ed93039bc22b0b8 1675002 gabage2.csv
+7b67b253c4ff1c46aefc8e1fe077f60a305aaa8a 14676 jrct_study_details.csv
+fb703460324947bd463cd2f65cac708120958cdf 14676 jrct_study_details_sorted.csv
+de2d3993c2cd54737d31957c415453da81487643 232783 search_results.csv
+337e17ce3d67969cdd60ad5e93a85e7463bff8a6 56852 search_results_by_disease.csv

.git.bfg-report/2025-06-23/16-51-48/object-id-map.old-new.txt

@@ -0,0 +1,36 @@
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app.py

@@ -135,21 +135,10 @@ def generate_dataframe(age, sex, tumor_type, GeneMutation, Meseable, Biopsiable)
         traceback.print_exc()
         return pd.DataFrame(), pd.DataFrame()
 
-# 特定のAgentGrade（yes, no, unclear）に基づいて行をフィルタリングする関数
-def filter_rows_by_grade(original_df, grade):
-    try:
-        if original_df is None or original_df.empty:
-            return pd.DataFrame(), pd.DataFrame()
-        df_filtered = original_df[original_df['AgentGrade'] == grade]
-        return df_filtered, df_filtered
-    except Exception as e:
-        print(f"フィルタリングエラー: {e}")
-        return pd.DataFrame(), pd.DataFrame()
-
 # CSVとして保存しダウンロードする関数
 def download_filtered_csv(df):
     try:
-        if df is None or df.empty:
+        if df is None or len(df) == 0:
             return None
         file_path = "filtered_data.csv"
         df.to_csv(file_path, index=False)
@@ -161,7 +150,7 @@ def download_filtered_csv(df):
 # 全体結果をCSVとして保存しダウンロードする関数
 def download_full_csv(df):
     try:
-        if df is None or df.empty:
+        if df is None or len(df) == 0:
             return None
         file_path = "full_data.csv"
         df.to_csv(file_path, index=False)
@@ -171,69 +160,110 @@ def download_full_csv(df):
         return None
 
 # Gradioインターフェースの作成
-with gr.Blocks() as demo:
+with gr.Blocks(title="臨床試験適格性評価", theme=gr.themes.Soft()) as demo:
     gr.Markdown("## 臨床試験適格性評価インターフェース")
     gr.Markdown("⚠️ **注意**: サーバーエラーが発生する場合があります。エラーが続く場合は少し時間をおいてから再試行してください。")
 
     # 各種入力フィールド
-    age_input = gr.Textbox(label="Age", placeholder="例: 65")
-    sex_input = gr.Dropdown(choices=["男性", "女性"], label="Sex")
-    tumor_type_input = gr.Textbox(label="Tumor Type", placeholder="例: gastric cancer, 日本でも良いですが英語の方が精度が高いです。")
-    gene_mutation_input = gr.Textbox(label="Gene Mutation", placeholder="例: HER2")
-    measurable_input = gr.Dropdown(choices=["有り", "無し", "不明"], label="Measurable Tumor")
-    biopsiable_input = gr.Dropdown(choices=["有り", "無し", "不明"], label="Biopsiable Tumor")
+    with gr.Row():
+        with gr.Column():
+            age_input = gr.Textbox(label="Age", placeholder="例: 65", value="")
+            sex_input = gr.Dropdown(choices=["男性", "女性"], label="Sex", value=None)
+            tumor_type_input = gr.Textbox(label="Tumor Type", placeholder="例: gastric cancer", value="")
+        
+        with gr.Column():
+            gene_mutation_input = gr.Textbox(label="Gene Mutation", placeholder="例: HER2", value="")
+            measurable_input = gr.Dropdown(choices=["有り", "無し", "不明"], label="Measurable Tumor", value=None)
+            biopsiable_input = gr.Dropdown(choices=["有り", "無し", "不明"], label="Biopsiable Tumor", value=None)
 
     # データフレーム表示エリア
-    dataframe_output = gr.DataFrame()
-    original_df = gr.State()
-    filtered_df = gr.State()
-
-    # データフレーム生成ボタン
-    generate_button = gr.Button("Generate Clinical Trials Data")
+    dataframe_output = gr.DataFrame(
+        headers=["NCTID", "AgentGrade", "Title", "AgentJudgment", "Status"],
+        datatype=["str", "str", "str", "str", "str"],
+        value=None
+    )
+    
+    # 内部状態用の非表示コンポーネント
+    original_df_state = gr.State(value=None)
+    filtered_df_state = gr.State(value=None)
 
-    # フィルタリングボタン
-    yes_button = gr.Button("Show Eligible Trials")
-    no_button = gr.Button("Show Ineligible Trials")
-    unclear_button = gr.Button("Show Unclear Trials")
+    # ボタン類
+    with gr.Row():
+        generate_button = gr.Button("Generate Clinical Trials Data", variant="primary")
+    
+    with gr.Row():
+        yes_button = gr.Button("Show Eligible Trials", variant="secondary")
+        no_button = gr.Button("Show Ineligible Trials", variant="secondary")
+        unclear_button = gr.Button("Show Unclear Trials", variant="secondary")
     
-    # ダウンロードボタン
-    download_filtered_button = gr.Button("Download Filtered Data")
-    download_filtered_output = gr.File(label="Download Filtered Data")
+    with gr.Row():
+        download_filtered_button = gr.Button("Download Filtered Data")
+        download_full_button = gr.Button("Download Full Data")
+    
+    # ダウンロードファイル
+    download_filtered_output = gr.File(label="Download Filtered Data", visible=False)
+    download_full_output = gr.File(label="Download Full Data", visible=False)
+
+    # イベントハンドリング
+    def update_dataframe_and_state(age, sex, tumor_type, gene_mutation, measurable, biopsiable):
+        """データフレーム生成と状態更新"""
+        df, _ = generate_dataframe(age, sex, tumor_type, gene_mutation, measurable, biopsiable)
+        return df, df, df
 
-    download_full_button = gr.Button("Download Full Data")
-    download_full_output = gr.File(label="Download Full Data")
+    def filter_and_update(original_df, grade):
+        """フィルタリングと表示更新"""
+        if original_df is None or len(original_df) == 0:
+            return original_df, original_df
+        
+        try:
+            df_filtered = original_df[original_df['AgentGrade'] == grade]
+            return df_filtered, df_filtered
+        except Exception as e:
+            print(f"フィルタリングエラー: {e}")
+            return original_df, original_df
 
     # ボタン動作の設定
     generate_button.click(
-        fn=generate_dataframe, 
-        inputs=[age_input, sex_input, tumor_type_input, gene_mutation_input, measurable_input, biopsiable_input], 
-        outputs=[dataframe_output, original_df]
+        fn=update_dataframe_and_state,
+        inputs=[age_input, sex_input, tumor_type_input, gene_mutation_input, measurable_input, biopsiable_input],
+        outputs=[dataframe_output, original_df_state, filtered_df_state]
     )
+    
     yes_button.click(
-        fn=filter_rows_by_grade, 
-        inputs=[original_df, gr.State("yes")], 
-        outputs=[dataframe_output, filtered_df]
+        fn=lambda df: filter_and_update(df, "yes"),
+        inputs=[original_df_state],
+        outputs=[dataframe_output, filtered_df_state]
     )
+    
     no_button.click(
-        fn=filter_rows_by_grade, 
-        inputs=[original_df, gr.State("no")], 
-        outputs=[dataframe_output, filtered_df]
+        fn=lambda df: filter_and_update(df, "no"),
+        inputs=[original_df_state],
+        outputs=[dataframe_output, filtered_df_state]
     )
+    
     unclear_button.click(
-        fn=filter_rows_by_grade, 
-        inputs=[original_df, gr.State("unclear")], 
-        outputs=[dataframe_output, filtered_df]
+        fn=lambda df: filter_and_update(df, "unclear"),
+        inputs=[original_df_state],
+        outputs=[dataframe_output, filtered_df_state]
     )
+    
     download_filtered_button.click(
-        fn=download_filtered_csv, 
-        inputs=filtered_df, 
-        outputs=download_filtered_output
+        fn=download_filtered_csv,
+        inputs=[filtered_df_state],
+        outputs=[download_filtered_output]
     )
+    
     download_full_button.click(
-        fn=download_full_csv, 
-        inputs=original_df, 
-        outputs=download_full_output
+        fn=download_full_csv,
+        inputs=[original_df_state],
+        outputs=[download_full_output]
     )
     
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        debug=False,
+        show_error=True
+    )

requirements.txt

@@ -1,42 +1,40 @@
-# Core web framework
-gradio>=4.0.0
+# Core web framework (固定バージョンで安定性確保)
+gradio==4.44.0
 
 # Data processing
 pandas>=1.5.0
 numpy>=1.21.0
 requests>=2.25.0
 
-# LangChain ecosystem (compatible versions)
-langchain>=0.3.0,<0.4.0
-langchain-community>=0.3.0,<0.4.0
-langchain-core>=0.3.0,<0.4.0
-langchain-openai>=0.2.0,<0.3.0
-langchain-groq>=0.2.0,<0.3.0
-langchain-text-splitters>=0.3.0,<0.4.0
+# LangChain ecosystem (安定バージョンに固定)
+langchain==0.3.2
+langchain-community==0.3.1
+langchain-core==0.3.9
+langchain-openai==0.2.2
+langchain-groq==0.2.0
+langchain-text-splitters==0.3.0
 
 # LLM providers
 openai>=1.0.0
 groq>=0.4.0
 
-# Vector databases and embeddings
-chromadb>=0.4.0
-sentence-transformers>=2.2.0
-
 # Database utilities
 SQLAlchemy>=2.0.0,<3.0.0
 
-# Pydantic (for compatibility)
+# Pydantic (Gradio互換性のため)
 pydantic>=2.0.0,<3.0.0
 
-# Text processing
+# Text processing (軽量化)
 tiktoken>=0.4.0
-tokenizers>=0.19.0
-transformers>=4.40.0
 
 # Utilities
 tenacity>=8.0.0
 packaging>=23.0.0
-setuptools>=70.0.0
+
+# Optional: Vector databases (必要な場合のみ)
+# chromadb>=0.4.0
+# sentence-transformers>=2.2.0
+# transformers>=4.40.0
 
 # Optional: Bio-related libraries (if needed for your specific use case)
 # Uncomment the following lines if bio-processing is required