Add application file

app.py

@@ -0,0 +1,162 @@
+## chatGPT with Gradio 起手式
+## 在你的資料夾新增 .env 檔案，並在裡面寫入 API_KEY=你的API金鑰
+import os
+import openai
+import gradio as gr
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv()) # read local .env file
+
+API_KEY = os.environ['OPENAI_API_KEY']
+
+print (API_KEY)
+
+## AI 建議
+def get_advice(bmi,temp, API_KEY, model="gpt-3.5-turbo"):
+    openai.api_key = API_KEY
+    messages = [{"role": "system", "content": "You can provide some dietary advice based on \
+                 the user's BMI value. You can only give up to 3 suggestions"},
+                {"role": "user", "content": f'My BMI is {bmi}. What can I do to be healthier?'},]
+    response = openai.chat.completions.create(
+        model=model,
+        max_tokens=200,
+        messages=messages,
+        temperature=temp, # this is the degree of randomness of the model's output
+    )
+    return response.choices[0].message.content
+
+## 健身計畫
+def get_gym(bmi,slide, temp, API_KEY, model="gpt-3.5-turbo"):
+    openai.api_key = API_KEY
+    messages = [{"role": "system", "content": "You are a great fitness coach and \
+                 you will give users great fitness plans."},
+                {"role": "user", "content": f'My BMI is {bmi}. I want a {slide}-point weight\
+                  loss plan, from 1 to 10. The higher the number, the faster the weight loss.'},]
+    response = openai.chat.completions.create(
+        model=model,
+        max_tokens=200,
+        messages=messages,
+        temperature=temp, # this is the degree of randomness of the model's output
+    )
+    return response.choices[0].message.content
+
+def BMI(height, weight) -> int:
+    height = int(height) / 100
+    bmi = int(weight) / (height * height)
+    if bmi < 18.5:
+        return str(bmi)[:5], "過輕"
+    elif bmi < 24:
+        return str(bmi)[:5], "正常"
+    elif bmi < 27:
+        return str(bmi)[:5], "過重"
+    elif bmi < 30:
+        return str(bmi)[:5], "輕度肥胖"
+    elif bmi < 35:
+        return str(bmi)[:5], "中度肥胖"
+    else:
+        return str(bmi)[:5], "重度肥胖"
+
+
+
+# 建立 components
+height = gr.Textbox(
+    label="身高",
+    info="輸入你的身高(cm)",
+    placeholder="Type your hiegh here...")
+
+weight = gr.Textbox(
+    label="體重",
+    info="輸入你的體重(kg)",
+    placeholder="Type your weight here...",)
+
+output_bmi = gr.Textbox(
+    value="",
+    label="BMI 值",
+    info="顯示BMI 數字",
+    placeholder="BMI")
+
+output_state = gr.Textbox(
+    value="",
+    label="BMI 結果",
+    info="診斷",
+    placeholder="顯示診斷結果")
+
+advice = gr.Textbox(
+    label="AI Advice",
+    info="請選擇以下按鈕讓AI 根據你的BMI值給予的建議",
+    placeholder="Ouput Text here...",
+    lines=5,)
+
+btn = gr.Button(
+    value="計算BMI值",
+    variant="primary", scale=1)
+
+btn_advice  = gr.Button(
+    value="AI 建議",
+    variant="primary", scale=2)
+
+btn_gym = gr.Button(
+    value="AI 健身計畫",
+    variant="primary", scale=1)
+
+key_box = gr.Textbox(
+    label="Enter your API key",
+    info="You have to provide your own OPENAI_API_KEY for this app to function properly",
+    placeholder="Type OpenAI API KEY here...",
+    type="password")
+
+
+slider = gr.Slider(
+    minimum=1,
+    maximum=10,
+    step=1,
+    label="減重速度",
+    value=5,
+    info="請選擇你的減重速度，數字越大，減重越快",
+    )
+
+temperature = gr.Slider(
+    minimum=0,
+    maximum=1.0,
+    value=0.3,
+    step=0.05,
+    label="Temperature",
+    info=(
+        "Temperature controls the degree of randomness in token selection. Lower "
+        "temperatures are good for prompts that expect a true or correct response, "
+        "while higher temperatures can lead to more diverse or unexpected results. "
+    ),
+)
+
+with gr.Blocks() as demo:
+    gr.Markdown("""
+    # BMI 計算器
+    簡易測量你的BMI值
+    """)
+    with gr.Column():
+        with gr.Row():
+            height.render()  # 顯示身高輸入框
+            weight.render() # 顯示體重輸入框
+        
+        with gr.Row():
+            output_bmi.render() # 顯示BMI值結果
+            output_state.render() # 顯示BMI診斷結果
+
+        btn.render() # 顯示計算BMI值按鈕
+        btn.click(fn=BMI, 
+                     inputs=[height, weight], 
+                     outputs=[output_bmi,output_state])
+
+        advice.render() # 顯示AI建議結果的文字框
+        
+        with gr.Row(): 
+            key_box.render() # 顯示API金鑰輸入框
+            btn_advice.render() # 顯示AI建議按鈕
+            btn_advice.click(fn=get_advice, inputs=[output_bmi,temperature,key_box], outputs=advice)
+            btn_gym.render() # 顯示AI健身計畫按鈕
+            btn_gym.click(fn=get_gym, inputs=[output_bmi,slider,temperature, key_box], outputs=advice)
+    
+        with gr.Accordion("settings", open=True):
+            slider.render()
+            temperature.render()
+
+demo.launch()