Updated chat app with OpenAI flow using Langchain

app.py

@@ -1,7 +1,56 @@
+import os
+
 import gradio as gr
+from langchain.schema import AIMessage, HumanMessage
+from langchain_openai import ChatOpenAI
+from pydantic import BaseModel, SecretStr
+
+
+class APIKey(BaseModel):
+    api_key: SecretStr
+
+
+def set_api_key(api_key: SecretStr):
+    os.environ["OPENAI_API_KEY"] = api_key.get_secret_value()
+    llm = ChatOpenAI(temperature=1.0, model="gpt-3.5-turbo-0125")
+    return llm
+
+
+def predict(message, chat_history, api_key):
+    api_key_model = APIKey(api_key=api_key)
+    llm = set_api_key(api_key_model.api_key)
+
+    history_langchain_format = []
+    for human, ai in chat_history:
+        history_langchain_format.append(HumanMessage(content=human))
+        history_langchain_format.append(AIMessage(content=ai))
+    history_langchain_format.append(HumanMessage(content=message))
+    openai_response = llm.invoke(history_langchain_format)
+    chat_history.append((message, openai_response.content))
+    return "", chat_history
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        api_key = gr.Textbox(
+            label="Please enter your OpenAI API key",
+            type="password",
+            elem_id="lets-chat-langchain-oakey",
+        )
+
+    with gr.Row():
+        msg = gr.Textbox(label="Please enter your message")
+
+    with gr.Row():
+        chatbot = gr.Chatbot(label="OpenAI Chatbot")
+
+    with gr.Row():
+        clear = gr.ClearButton([msg, chatbot])
+
+    def respond(message, chat_history, api_key):
+        return predict(message, chat_history, api_key)
 
-def greet(name):
-    return "Hello " + name + "!!"
+    api_key.submit(respond, [msg, chatbot, api_key], [msg, chatbot])
+    msg.submit(respond, [msg, chatbot, api_key], [msg, chatbot])
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()