Update app.py

app.py

@@ -74,7 +74,7 @@ def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]:
         
         system_message = "사용자 질문에 대해 의약품 정보를 제공하는 전문 약학 어시스턴트입니다."
         system_prefix = """
-        반드시 한글로 답변하십시오. 출력시 markdown 형식으로 출력하라. 너의 이름은 '추론 기반 PharmAI'이다.
+        반드시 한글로 답변하십시오. 출력시 markdown 형식으로 출력하라. 너의 이름은 'PharmAI'이다.
         당신은 '의약품 지식 그래프(PharmKG) 데이터 100만 건 이상을 학습한 전문적인 의약품 정보 AI 조언자입니다.'
         입력된 질문에 대해 PharmKG 데이터셋에서 가장 관련성이 높은 정보를 찾고, 이를 바탕으로 상세하고 체계적인 답변을 제공합니다.
         답변은 다음 구조를 따르십시오:
@@ -206,94 +206,113 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="teal", secondary_hue="slate", n
                </a>""")
 
     
-    chatbot = gr.Chatbot(
-        type="messages",
-        label="Gemini2.0 'Thinking' Chatbot (Streaming Output)", #Label now indicates streaming
-        render_markdown=True,
-        scale=1,
-        avatar_images=(None,"https://lh3.googleusercontent.com/oxz0sUBF0iYoN4VvhqWTmux-cxfD1rxuYkuFEfm1SFaseXEsjjE4Je_C_V3UQPuJ87sImQK3HfQ3RXiaRnQetjaZbjJJUkiPL5jFJ1WRl5FKJZYibUA=w214-h214-n-nu")
-    )
-
-    with gr.Row(equal_height=True):
-        input_box = gr.Textbox(
-            lines=1,
-            label="Chat Message",
-            placeholder="Type your message here...",
-            scale=4
-        )
+    with gr.Tabs():
+        with gr.TabItem("Chat"):
+            chatbot = gr.Chatbot(
+                type="messages",
+                label="Gemini2.0 'Thinking' Chatbot (Streaming Output)", #Label now indicates streaming
+                render_markdown=True,
+                scale=1,
+                avatar_images=(None,"https://lh3.googleusercontent.com/oxz0sUBF0iYoN4VvhqWTmux-cxfD1rxuYkuFEfm1SFaseXEsjjE4Je_C_V3UQPuJ87sImQK3HfQ3RXiaRnQetjaZbjJJUkiPL5jFJ1WRl5FKJZYibUA=w214-h214-n-nu")
+            )
+
+            with gr.Row(equal_height=True):
+                input_box = gr.Textbox(
+                    lines=1,
+                    label="Chat Message",
+                    placeholder="Type your message here...",
+                    scale=4
+                )
+
+                clear_button = gr.Button("Clear Chat", scale=1)
+
+            # Add example prompts - removed file upload examples. Kept text focused examples.
+            example_prompts = [
+                 ["Explain the interplay between CYP450 enzymes and drug metabolism, specifically focusing on how enzyme induction or inhibition might affect the therapeutic efficacy of a drug such as warfarin."],
+                ["Compare and contrast the mechanisms of action of ACE inhibitors and ARBs in managing hypertension, considering their effects on the renin-angiotensin-aldosterone system."],
+                ["Describe the pathophysiology of type 2 diabetes and explain how metformin achieves its glucose-lowering effects, including any key considerations for patients with renal impairment."],
+                 ["Please discuss the mechanism of action and clinical significance of beta-blockers in the treatment of heart failure, with reference to specific beta-receptor subtypes and their effects on the cardiovascular system."],
+                  ["알츠하이머병의 병태생리학적 기전을 설명하고, 현재 사용되는 약물들이 작용하는 주요 타겟을 상세히 기술하십시오. 특히, 아세틸콜린에스테라제 억제제와 NMDA 수용체 길항제의 작용 방식과 임상적 의의를 비교 분석해 주십시오."],
+                ["만성 신장 질환 환자에서 빈혈 치료를 위해 사용하는 에리스로포이에틴 제제의 약동학적 및 약력학적 특성을 상세히 분석하고, 투여 용량 및 투여 간격 결정에 영향을 미치는 요인들을 설명해 주십시오.",""],
+                ["간경변 환자에서 약물 대사의 변화를 설명하고, 간 기능 저하가 약물 투여량 조절에 미치는 영향을 구체적인 약물 예시와 함께 논의해 주십시오. 특히, 간 대사 효소의 활성 변화와 그 임상적 중요성을 설명해 주십시오."]
+            ]
+
+            gr.Examples(
+                examples=example_prompts,
+                inputs=input_box,
+                label="Examples: Try these prompts to see Gemini's thinking!",
+                examples_per_page=3 # Adjust as needed
+            )
+
+
+            # Set up event handlers
+            msg_store = gr.State("")  # Store for preserving user message
+
+            input_box.submit(
+                lambda msg: (msg, msg, ""),  # Store message and clear input
+                inputs=[input_box],
+                outputs=[msg_store, input_box, input_box],
+                queue=False
+            ).then(
+                user_message,  # Add user message to chat
+                inputs=[msg_store, chatbot],
+                outputs=[input_box, chatbot],
+                queue=False
+            ).then(
+                stream_gemini_response,  # Generate and stream response
+                inputs=[msg_store, chatbot],
+                outputs=chatbot
+            )
+
+            clear_button.click(
+                lambda: ([], "", ""),
+                outputs=[chatbot, input_box, msg_store],
+                queue=False
+            )
 
-        clear_button = gr.Button("Clear Chat", scale=1)
-
-    # Add example prompts - removed file upload examples. Kept text focused examples.
-    example_prompts = [
-        ["What is the generic name for Tylenol?"],
-        ["What are the side effects of aspirin?"],
-        ["Explain the mechanism of action of Metformin."],
-        ["What are the uses of Warfarin?"],
-        ["What is a typical dosage of amoxicillin?"]
-    ]
-
-    gr.Examples(
-        examples=example_prompts,
-        inputs=input_box,
-        label="Examples: Try these prompts to see Gemini's thinking!",
-        examples_per_page=5 # Adjust as needed
-    )
-
-
-    # Set up event handlers
-    msg_store = gr.State("")  # Store for preserving user message
-
-    input_box.submit(
-        lambda msg: (msg, msg, ""),  # Store message and clear input
-        inputs=[input_box],
-        outputs=[msg_store, input_box, input_box],
-        queue=False
-    ).then(
-        user_message,  # Add user message to chat
-        inputs=[msg_store, chatbot],
-        outputs=[input_box, chatbot],
-        queue=False
-    ).then(
-        stream_gemini_response,  # Generate and stream response
-        inputs=[msg_store, chatbot],
-        outputs=chatbot
-    )
-
-    clear_button.click(
-        lambda: ([], "", ""),
-        outputs=[chatbot, input_box, msg_store],
-        queue=False
-    )
-
-    gr.Markdown(  # Description moved to the bottom - updated for text-only
-        """
-        <br><br><br>  <!-- Add some vertical space -->
-        ---
-        ### About this Chatbot
-        This chatbot demonstrates the experimental 'thinking' capability of the **Gemini 2.0 Flash** model, now acting as a specialized pharmacology assistant.
-        You can observe the model's thought process as it generates responses, displayed with the "⚙️ Thinking" prefix.
-
-        **This chatbot is enhanced with a pharmacology dataset ("PharmKG") to provide more accurate and informed answers.**
-
-        **Try out the example prompts below to see Gemini in action!**
-
-        **Key Features:**
-        *   Powered by Google's **Gemini 2.0 Flash** model.
-        *   Shows the model's **thoughts** before the final answer (experimental feature).
-        *   Supports **conversation history** for multi-turn chats.
-        *   Uses **streaming** for a more interactive experience.
-        *   Leverages a **pharmacology knowledge graph** to enhance responses.
-        **Instructions:**
-        1.  Type your message in the input box below or select an example.
-        2.  Press Enter or click Submit to send.
-        3.  Observe the chatbot's "Thinking" process followed by the final response.
-        4.  Use the "Clear Chat" button to start a new conversation.
-
-        *Please note*: The 'thinking' feature is experimental and the quality of thoughts may vary.
-        """
-    )
 
+        with gr.TabItem("Instructions"):
+             gr.Markdown(
+                """
+                ## PharmAI: Your Expert Pharmacology Assistant
+
+                Welcome to PharmAI, a specialized chatbot powered by Google's Gemini 2.0 Flash model. PharmAI is designed to provide expert-level information on pharmacology topics, leveraging a large dataset of pharmaceutical knowledge ("PharmKG").
+
+                **Key Features:**
+
+                *   **Advanced Pharmacology Insights**: PharmAI provides responses that are structured, detailed, and based on a vast knowledge graph of pharmacology.
+                *   **Inference and Reasoning**: The chatbot can handle complex, multi-faceted questions, showcasing its ability to reason and infer from available information.
+                *   **Structured Responses**: Responses are organized logically to include definitions, mechanisms of action, indications, dosages, side effects, drug interactions, pharmacokinetics, and references when applicable.
+                *   **Thinking Process Display**: You can observe the model's thought process as it generates a response (experimental feature).
+                *   **Conversation History**: PharmAI remembers the previous parts of the conversation to provide more accurate and relevant information across multiple turns.
+                *   **Streaming Output**: The chatbot streams responses for an interactive experience.
+
+                **How to Use PharmAI:**
+
+                1.  **Start a Conversation**: Type your pharmacology question into the input box under the "Chat" tab. The chatbot is specifically designed to handle complex pharmacology inquiries.
+
+                2.  **Use Example Prompts**: You can try out the example questions provided to see the model in action. These examples are formulated to challenge the chatbot to exhibit its expertise.
+                
+                3. **Example Prompt Guidance**:
+                    * **Mechanisms of Action**: Ask about how a specific drug works at the molecular level. Example: "Explain the mechanism of action of Metformin."
+                    * **Drug Metabolism**: Inquire about how the body processes drugs. Example: "Explain the interplay between CYP450 enzymes and drug metabolism..."
+                    * **Clinical Implications**: Pose questions about the clinical use of drugs in treating specific diseases. Example: "Discuss the mechanism of action and clinical significance of beta-blockers in heart failure..."
+                    * **Pathophysiology and Drug Targets**: Ask about diseases, what causes them, and how drugs can treat them. Example: "Explain the pathophysiology of type 2 diabetes and how metformin works..."
+                    * **Complex Multi-Drug Interactions**: Pose questions about how one drug can affect another drug in the body.
+
+                4. **Review Responses**: The chatbot will then present its response with a "Thinking" section that reveals its internal processing. Then it provides the more structured response, with sections including definition, mechanism of action, indications, etc.
+
+                5. **Clear Conversation**: Use the "Clear Chat" button to start a new session.
+
+                **Important Notes:**
+
+                *  The 'thinking' feature is experimental, but it shows the steps the model took when creating the response.
+                *  The quality of the response is highly dependent on the user prompt. Please be as descriptive as possible when asking questions to the best results.
+                *   This model is focused specifically on pharmacology information, so questions outside this scope may not get relevant answers.
+                *   This chatbot is intended as an informational resource and should not be used for medical diagnosis or treatment recommendations. Always consult with a healthcare professional for any medical advice.
+
+                 """
+            )
 
 # Launch the interface
 if __name__ == "__main__":