Upload app.py

app.py

@@ -1,4 +1,20 @@
+import os
 import gradio as gr
+import openai
+# 如需使用 Claude，請先安裝 "anthropic" 套件： pip install anthropic
+from typing import Optional
+
+try:
+    from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT
+except ImportError:
+    Anthropic = None
+    HUMAN_PROMPT = ""
+    AI_PROMPT = ""
+
+# 從環境變數中取得金鑰
+openai.api_key = os.environ.get("gptkey", "")
+
+claude_api_key = os.environ.get("claudekey", "")
 
 # 定義每個類型的句子
 achievement_statements = [
@@ -44,10 +60,16 @@ status_statements = [
     "比起和他人待在一起，我更喜歡獨處",
 ]
 
-# 定義一個函數來處理選擇並生成提示
 
-def generate_prompt(achievement, emotion, information, possession, power, status):
-    # 對應的資料結構
+############################################
+# 產生 Prompt
+############################################
+
+def generate_prompt(achievement: str, emotion: str, information: str,
+                    possession: str, power: str, status: str) -> str:
+    """
+    根據使用者針對六個類型選擇「正」或「負」，產生對應的 Prompt。
+    """
     category_map = {
         '成就型': achievement_statements,
         '情感型': emotion_statements,
@@ -87,26 +109,140 @@ def generate_prompt(achievement, emotion, information, possession, power, status
 
     return prompt
 
-# 使用 Gradio 建立介面
-with gr.Blocks() as demo:
-    gr.Markdown("## Prompt 產生器")
+############################################
+# 呼叫模型 API (OpenAI / Claude)
+############################################
+
+def call_openai_api(prompt: str, model_name: str = "gpt-3.5-turbo") -> str:
+    """呼叫 OpenAI API"""
+    if not openai.api_key:
+        return "[OpenAI API Key 未設定，無法呼叫 API]"
+
+    try:
+        response = openai.ChatCompletion.create(
+            model=model_name,
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.7,
+            max_tokens=1024
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"[OpenAI API 呼叫失敗]: {str(e)}"
+
+
+def call_claude_api(prompt: str) -> str:
+    """呼叫 Claude API"""
+    if not claude_api_key or not Anthropic:
+        return "[Claude API Key 未設定或未安裝 anthropic 套件，無法呼叫 API]"
+    
+    try:
+        client = Anthropic(api_key=claude_api_key)
+        conversation = client.completions.create(
+            prompt=f"{HUMAN_PROMPT} {prompt}{AI_PROMPT}",
+            model="claude-v1.3",  # 這裡可調整對應的 Claude 模型
+            max_tokens_to_sample=1024,
+            temperature=0.7,
+        )
+        return conversation.completion.strip()
+    except Exception as e:
+        return f"[Claude API 呼叫失敗]: {str(e)}"
+
+
+def get_model_answer(model_choice: str, final_prompt: str, question: str) -> str:
+    """
+    根據 model_choice 呼叫對應的 API。
+    """
+    # 最終送出給模型的內容
+    content_to_send = final_prompt + "\n\n" + question
+
+    if model_choice == "ChatGPT 4o":
+        return call_openai_api(content_to_send, model_name="gpt-4")
+    elif model_choice == "ChatGPT o1":
+        return call_openai_api(content_to_send, model_name="gpt-3.5-turbo")
+    elif model_choice == "Claude 3.5 Sonnet":
+        return call_claude_api(content_to_send)
+    else:
+        return "[錯誤] 未知的模型選擇"
+
+
+############################################
+# Gradio 介面
+############################################
+
+def main():
+    # 預設問題
+    predefined_questions = {
+        "請介紹你自己": "請介紹你自己，讓我們了解你是什麼樣的人。你可以分享你的經歷、興趣、價值觀，以及未來規劃。特別說明一下，當你遇到挑戰時，你通常會如何面對？",
+        "如何分配意外收入": "如果你突然收到一筆意外收入，你會如何分配這筆錢來購物？請列出前三項想購買的東西，並說明購買原因。",
+        "新專案團隊問題": "假設你被指派帶領一個新專案，但發現團隊成員能力參差不齊，預算有限，且截止日期緊迫，你會如何處理？",
+        "自訂提問": ""
+    }
 
-    with gr.Row():
-        achievement = gr.Radio(["正", "負"], label="成就型", value="正")
-        emotion = gr.Radio(["正", "負"], label="情感型", value="正")
-        information = gr.Radio(["正", "負"], label="資訊型", value="正")
-        possession = gr.Radio(["正", "負"], label="佔有型", value="正")
-        power = gr.Radio(["正", "負"], label="權力型", value="正")
-        status = gr.Radio(["正", "負"], label="地位型", value="正")
+    with gr.Blocks() as demo:
+        gr.Markdown("## Prompt 產生器")
+
+        with gr.Row():
+            achievement = gr.Radio(["正", "負"], label="成就型", value="正")
+            emotion = gr.Radio(["正", "負"], label="情感型", value="正")
+            information = gr.Radio(["正", "負"], label="資訊型", value="正")
+            possession = gr.Radio(["正", "負"], label="佔有型", value="正")
+            power = gr.Radio(["正", "負"], label="權力型", value="正")
+            status = gr.Radio(["正", "負"], label="地位型", value="正")
+
+        prompt_output = gr.Textbox(label="生成的 Prompt", lines=10)
+        generate_button = gr.Button("生成 Prompt")
+
+        # 下方選擇模型
+        model_choice = gr.Radio(
+            ["ChatGPT 4o", "ChatGPT o1", "Claude 3.5 Sonnet"],
+            label="選擇模型",
+            value="ChatGPT 4o"
+        )
+
+        # 選擇問題或自訂
+        question_choice = gr.Radio(
+            list(predefined_questions.keys()),
+            label="選擇一個提問",
+            value="請介紹你自己"
+        )
+        custom_question = gr.Textbox(
+            label="自訂提問 (若選擇 '自訂提問' 時才使用)",
+            lines=2,
+            placeholder="若上面選擇了 '自訂提問'，請在此輸入問題"
+        )
+
+        answer_output = gr.Textbox(label="模型回應", lines=10)
+        ask_button = gr.Button("送出問題並取得回答")
+
+        def on_generate_prompt(a, e, i, p, pow_, s):
+            return generate_prompt(a, e, i, p, pow_, s)
+
+        generate_button.click(
+            fn=on_generate_prompt,
+            inputs=[achievement, emotion, information, possession, power, status],
+            outputs=prompt_output
+        )
+
+        def on_ask_question(m_choice, p_output, q_choice, c_question):
+            if q_choice == "自訂提問":
+                if not c_question.strip():
+                    return "[錯誤] 你選擇了自訂提問，但沒有輸入內容"
+                question = c_question.strip()
+            else:
+                question = predefined_questions[q_choice]
+
+            # 呼叫對應的模型
+            answer = get_model_answer(m_choice, p_output, question)
+            return answer
+
+        ask_button.click(
+            fn=on_ask_question,
+            inputs=[model_choice, prompt_output, question_choice, custom_question],
+            outputs=answer_output
+        )
 
-    prompt_output = gr.Textbox(label="生成的 Prompt", lines=20)
-    generate_button = gr.Button("生成 Prompt")
+    demo.launch()
 
-    generate_button.click(
-        fn=generate_prompt,
-        inputs=[achievement, emotion, information, possession, power, status],
-        outputs=prompt_output
-    )
 
 if __name__ == "__main__":
-    demo.launch()
+    main()