ddd

app.py

@@ -26,7 +26,7 @@ from langchain.tools import AIPluginTool
 # Example system message : system = SystemMessage(content = "You are a helpful AI assistant")
 
 # driver
-def predict(user_input, chatbot):
+def predict_old(user_input, chatbot):
 
     chat = ChatOpenAI(temperature=1.0, streaming=True, model='gpt-3.5-turbo-0613')
     messages=[]
@@ -43,14 +43,41 @@ def predict(user_input, chatbot):
     gpt_response = chat(messages)
     return gpt_response.content
 
+def predict(inputs, chatbot):
 
+    print(f'inputs is - {inputs}')
+    print(f'chatbot is - {chatbot}')
+    messages = []
+    for conv in chatbot:
+        user = conv[0]
+        assistant = conv[1]
+        messages.append({"role": "user", "content":user })
+        messages.append({"role": "assistant", "content":assistant})
+    messages.append({"role": "user", "content":inputs})
+    print(f'messages is - {messages}')
+
+    # a ChatCompletion request
+    response = openai.ChatCompletion.create(
+        model='gpt-3.5-turbo',
+        messages= messages, # [{'role': 'user', 'content': "What is life? Answer in three words."}],
+        temperature=1.0,
+        stream=True  # for streaming the output to chatbot
+    )
+    print(f'response is - {response}')
+
+    partial_message = ""
+    for chunk in response:
+        if len(chunk['choices'][0]['delta']) != 0:
+          print(chunk['choices'][0]['delta']['content'])
+          yield chunk['choices'][0]['delta']['content']
+        #time.sleep(0.5)
 
 def echo_stream(message, history):
     for i in range(len(message)):
         time.sleep(0.3)
         yield message[:i]
 
-ChatInterface(echo_stream).queue().launch(debug=True)
+ChatInterface(predict).queue().launch(debug=True)
 
 #chatbot = gr.Chatbot()
 #gr.ChatInterface(predict, delete_last_btn="del").queue().launch(share=False, debug=True) #examples=["How are you?", "What's up?"],