Update app.py

app.py

@@ -136,23 +136,24 @@
 
 
 # new code
+from langchain.chat_models import ChatOpenAI
+from langchain.schema import AIMessage, HumanMessage
+import openai
 import gradio as gr
-import time
 
-def echo(message, history, system_prompt, tokens):
-    response = f"System prompt: {system_prompt}\n Message: {message}."
-    for i in range(min(len(response), int(tokens))):
-        time.sleep(0.05)
-        yield response[: i + 1]
+os.environ["OPENAI_API_KEY"] = "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"  # Replace with your key
 
-demo = gr.ChatInterface(
-    echo,
-    
-    additional_inputs=[
-        gr.Textbox("You are helpful AI.", label="System Prompt"),
-        gr.Slider(10, 100),
-    ],
-)
+llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')
 
-demo.launch()
+def predict(message, history):
+    history_langchain_format = []
+    for msg in history:
+        if msg['role'] == "user":
+            history_langchain_format.append(HumanMessage(content=msg['content']))
+        elif msg['role'] == "assistant":
+            history_langchain_format.append(AIMessage(content=msg['content']))
+    history_langchain_format.append(HumanMessage(content=message))
+    gpt_response = llm(history_langchain_format)
+    return gpt_response.content
 
+gr.ChatInterface(predict).launch()