Add LogicBench integration tab (UI and placeholder logic)

app.py

@@ -2,6 +2,7 @@
 Gradio application for SFOSR (Semantic Formal Ontology Structure Representation) System.
 
 Provides an interface to analyze, verify, and construct proofs using the SFOSR framework.
+Includes a tab for integrating with LogicBench tasks (requires LLM for text-to-SFOSR conversion).
 """
 
 import gradio as gr
@@ -40,9 +41,10 @@ else:
 
 # --- Helper Functions for Gradio ---
 
-def handle_system_unavailable():
-    """Returns an error message if the SFOSR system isn't ready."""
-    return "SFOSR System is not available. Please check server logs.", "", "", ""
+def handle_system_unavailable(num_outputs=4):
+    """Returns error messages if the SFOSR system isn't ready."""
+    error_msg = "SFOSR System is not available. Please check server logs."
+    return [error_msg] + ["" for _ in range(num_outputs - 1)]
 
 def process_input_json(json_string):
     """Safely parse input JSON string."""
@@ -64,7 +66,7 @@ def process_input_json(json_string):
 def run_analysis_verification(input_json_str):
     """Gradio function to run analysis and verification."""
     if sfosr_instance is None:
-        return handle_system_unavailable()
+        return handle_system_unavailable(num_outputs=4)
 
     input_data, error = process_input_json(input_json_str)
     if error:
@@ -91,13 +93,14 @@ def run_analysis_verification(input_json_str):
         return analysis_summary, verification_summary, vector_details, graph_output
 
     except Exception as e:
-        print(f"Error during SFOSR processing: {e}") # Log for debugging
-        return f"An error occurred: {e}", "", "", ""
+        error_trace = traceback.format_exc()
+        print(f"Error during SFOSR processing: {e}\n{error_trace}") # Log for debugging
+        return f"An error occurred: {e}", "", vector_details, graph_output # Return partial results if possible
 
 def run_proof_construction(input_json_str, source_concept, target_concept):
     """Gradio function to run proof construction."""
     if sfosr_instance is None:
-        return handle_system_unavailable()[:1] + ("",) # Only return one value for proof status
+        return handle_system_unavailable(num_outputs=2)
 
     input_data, error = process_input_json(input_json_str)
     if error:
@@ -120,7 +123,7 @@ def run_proof_construction(input_json_str, source_concept, target_concept):
 
         if not proof_result:
              # This might happen if the process function structure changes or proof wasn't run
-             return "Proof was not attempted or failed silently.", ""
+             return "Proof was not attempted or failed silently (check input vectors and concepts).", ""
 
         proof_status = f"**Proof Status:** {proof_result.get('status', 'N/A')}\n" \
                        f"**Is Valid:** {proof_result.get('is_valid', 'N/A')}"
@@ -132,9 +135,75 @@ def run_proof_construction(input_json_str, source_concept, target_concept):
         return proof_status, proof_details
 
     except Exception as e:
-        print(f"Error during SFOSR proof: {e}") # Log for debugging
+        error_trace = traceback.format_exc()
+        print(f"Error during SFOSR proof: {e}\n{error_trace}") # Log for debugging
         return f"An error occurred: {e}", ""
 
+# --- Placeholder for LogicBench Integration --- 
+def run_logicbench_task(logicbench_context, logicbench_question):
+    """Placeholder function for LogicBench task processing."""
+    print(f"Received LogicBench Context: {logicbench_context[:100]}...")
+    print(f"Received LogicBench Question: {logicbench_question}")
+
+    # --- Stage 1: Text-to-SFOSR Conversion (using LLM - TO BE IMPLEMENTED) ---
+    generated_sfosr_json = {
+        "text": logicbench_context,
+        "vectors": [
+            {"id": "placeholder", "source": "PlaceholderSource", "target": "PlaceholderTarget", 
+             "type": "PlaceholderType", "axis": "placeholder", "justification": "LLM Step Not Implemented"}
+        ]
+    }
+    generated_sfosr_str = json.dumps(generated_sfosr_json, indent=2, ensure_ascii=False)
+
+    # --- Stage 2: SFOSR Processing (using the generated JSON) ---
+    if sfosr_instance is None:
+        final_answer = "Error: SFOSR System not available."
+        sfosr_proof_status = ""
+        sfosr_proof_details = ""
+    else:
+        try:
+            # Determine source/target for proof based on the question (requires logic)
+            # For now, let's use placeholder source/target from the generated JSON
+            # This part needs significant refinement based on how questions are mapped
+            source_concept_lb = generated_sfosr_json["vectors"][0]["source"]
+            target_concept_lb = generated_sfosr_json["vectors"][0]["target"]
+            
+            logicbench_input_data = generated_sfosr_json
+            logicbench_input_data["proof_query"] = {
+                "source": source_concept_lb,
+                "target": target_concept_lb 
+            }
+            
+            # Call the main process method
+            sfosr_result = sfosr_instance.process(logicbench_input_data)
+            sfosr_proof_result = sfosr_result.get("proof")
+
+            # --- Stage 3: Interpret SFOSR Result as LogicBench Answer (TO BE IMPLEMENTED) ---
+            if sfosr_proof_result and sfosr_proof_result.get("is_valid"):
+                final_answer = "Answer: Yes (Placeholder - based on successful SFOSR proof)"
+            else:
+                final_answer = "Answer: No/Unknown (Placeholder - SFOSR proof failed or invalid)"
+            
+            # Format proof output for display
+            if sfosr_proof_result:
+                 sfosr_proof_status = f"**Proof Status:** {sfosr_proof_result.get('status', 'N/A')}\n" \
+                                      f"**Is Valid:** {sfosr_proof_result.get('is_valid', 'N/A')}"
+                 if sfosr_proof_result.get('reason'):
+                      sfosr_proof_status += f"\n**Reason:** {sfosr_proof_result.get('reason')}"
+                 sfosr_proof_details = sfosr_proof_result
+            else:
+                sfosr_proof_status = "SFOSR Proof was not generated or failed."
+                sfosr_proof_details = {}
+                
+        except Exception as e:
+            error_trace = traceback.format_exc()
+            print(f"Error during LogicBench task processing: {e}\n{error_trace}")
+            final_answer = f"Error processing task: {e}"
+            sfosr_proof_status = "Error during processing"
+            sfosr_proof_details = {}
+
+    return final_answer, generated_sfosr_str, sfosr_proof_status, sfosr_proof_details
+
 
 # --- Example Input Formats ---
 example_verify_json = '''{
@@ -180,6 +249,10 @@ example_proof_json = '''{
   ]
 }'''
 
+# Example for LogicBench (replace with actual examples)
+example_logicbench_context = "If it rains, the ground gets wet. The ground is not wet."
+example_logicbench_question = "Did it rain?"
+
 # --- Gradio Interface Definition ---
 
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
@@ -250,7 +323,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                     gr.Markdown("### Детали Проверки Векторов")
                     vector_details_output = gr.JSON(label="Детали по Векторам")
                     gr.Markdown("### Граф Концептов")
-                    graph_placeholder_output = gr.Textbox(label="Информация о Графе")
+                    graph_placeholder_output = gr.Textbox(label="Информация о Графе") # Placeholder
 
             gr.Examples(
                 examples=[
@@ -310,7 +383,60 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                 inputs=[input_json_p, source_concept_input, target_concept_input],
                 label="Пример построения доказательства"
             )
-            
+
+        with gr.TabItem("Интеграция с LogicBench"):
+             gr.Markdown(
+                """
+                ### Решение Задач LogicBench (Экспериментально)
+                
+                Эта вкладка демонстрирует гибридный подход: 
+                1. **LLM** преобразует текстовую задачу из LogicBench в структурированные SFOSR векторы (JSON).
+                2. **SFOSR** система анализирует и пытается доказать ответ на вопрос задачи, используя сгенерированные векторы.
+                
+                **Внимание:** Шаг 1 (LLM преобразование) еще не реализован. Сейчас используется placeholder.
+                
+                #### Как пользоваться (когда будет реализовано):
+                1. Вставьте **Контекст/Посылки** из задачи LogicBench.
+                2. Вставьте **Вопрос** из задачи LogicBench.
+                3. Нажмите кнопку "Решить Задачу LogicBench".
+                4. Посмотрите **Финальный Ответ** и детали работы SFOSR.
+                """
+            )
+             with gr.Row():
+                with gr.Column(scale=1):
+                    gr.Markdown("### Входные данные из LogicBench")
+                    lb_context_input = gr.Textbox(
+                        lines=10,
+                        label="Контекст / Посылки",
+                        info="Вставьте текст контекста или посылок из задачи LogicBench",
+                        placeholder="Пример: Если идет дождь, трава мокрая. Трава сухая."
+                    )
+                    lb_question_input = gr.Textbox(
+                        lines=2,
+                        label="Вопрос",
+                        info="Вставьте вопрос из задачи LogicBench",
+                        placeholder="Пример: Идет ли дождь?"
+                    )
+                    lb_button = gr.Button("Решить Задачу LogicBench", variant="primary")
+                
+                with gr.Column(scale=1):
+                    gr.Markdown("### Результат Решения")
+                    lb_final_answer_output = gr.Markdown(label="Финальный Ответ")
+                    with gr.Accordion("Детали Обработки SFOSR", open=False):
+                        gr.Markdown("#### Сгенерированный SFOSR JSON (LLM Шаг - Placeholder)")
+                        lb_sfosr_json_output = gr.Code(language="json", label="SFOSR JSON")
+                        gr.Markdown("#### Результат Доказательства SFOSR")
+                        lb_proof_status_output = gr.Markdown(label="Статус Доказательства SFOSR")
+                        lb_proof_details_output = gr.JSON(label="Структура Доказательства SFOSR")
+
+             gr.Examples(
+                 examples=[
+                     [example_logicbench_context, example_logicbench_question]
+                 ],
+                 inputs=[lb_context_input, lb_question_input],
+                 label="Пример Задачи LogicBench"
+            )
+
         with gr.TabItem("Справка"):
             gr.Markdown(
                 """
@@ -364,17 +490,27 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     
     # --- Event Handlers ---
     if sfosr_instance: # Only wire up buttons if the system initialized
+        # Analyze & Verify Tab
         av_button.click(
             fn=run_analysis_verification,
             inputs=[input_json_av],
             outputs=[analysis_output, verification_output, vector_details_output, graph_placeholder_output]
         )
-
+        
+        # Construct Proof Tab
         p_button.click(
             fn=run_proof_construction,
             inputs=[input_json_p, source_concept_input, target_concept_input],
             outputs=[proof_status_output, proof_details_output]
         )
+        
+        # LogicBench Integration Tab
+        lb_button.click(
+            fn=run_logicbench_task, 
+            inputs=[lb_context_input, lb_question_input],
+            outputs=[lb_final_answer_output, lb_sfosr_json_output, lb_proof_status_output, lb_proof_details_output]
+        )
+        
     else:
          # Display a persistent error if the system couldn't load
          gr.Markdown(