Add application file

app.py

@@ -1,15 +1,57 @@
 import gradio as gr
-from transformers import pipeline
+import os, openai
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
-def predict(image):
-    predictions = pipeline(image)
-    return {p["label"]: p["score"] for p in predictions}
+conversation = []
 
-gr.Interface(
-    predict,
-    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
-    outputs=gr.outputs.Label(num_top_classes=2),
-    title="Hot Dog? Or Not?",
-).launch(server_name='127.0.0.1',server_port=7788)
+class ChatGPT:  
+    
+
+    def __init__(self):
+        self.api_key = ""
+        self.messages = conversation
+        self.model = os.getenv("OPENAI_MODEL", default = "gpt-3.5-turbo")
+
+    def save_api_key(self, user_input0):
+        self.api_key = user_input0
+
+    def get_response(self, user_input):
+        openai.api_key = self.api_key
+        conversation.append({"role": "user", "content": user_input})
+        
+
+        response = openai.ChatCompletion.create(
+	            model=self.model,
+                messages = self.messages
+
+                )
+
+        conversation.append({"role": "assistant", "content": response['choices'][0]['message']['content']})
+        
+        print("AI回答內容：")        
+        print(response['choices'][0]['message']['content'].strip())
+
+
+        
+        return response['choices'][0]['message']['content'].strip()
+
+
+chatgpt = ChatGPT()
+
+
+def greet(prompt, api_key):
+    chatgpt.save_api_key(api_key)
+    
+    reply_text = chatgpt.get_response(prompt)
+
+    greeting = f"{reply_text}"
+
+    return greeting
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=["text", "text"],
+    outputs=["text"],
+)
+
+demo.launch()

requirements.txt

@@ -1,3 +1,2 @@
 gradio
-transformers
-torch
+openai==0.27.0