Create app.py

app.py

@@ -0,0 +1,30 @@
+import os
+import gradio as gr
+from langchain.chat_models import ChatLiteLLM
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    AIMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+)
+from langchain.schema import AIMessage, HumanMessage, SystemMessage
+
+os.environ['PALM_API_KEY'] = "AIzaSyBcSZ82EePKjrgZphWXMpKP3u3Kcfz_8AU"  # Replace with your key
+
+chat = ChatLiteLLM(model="palm/chat-bison")
+
+def predict(message, history):
+    history_langchain_format = []
+    for human, ai in history:
+        history_langchain_format.append(HumanMessage(content=human))
+        history_langchain_format.append(AIMessage(content=ai))
+    history_langchain_format.append(HumanMessage(content=message))
+
+    try:
+        gpt_response = chat(history_langchain_format)
+        return gpt_response.content
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        return "Sorry, I couldn't process that message."
+
+gr.Interface(predict, inputs=["text", "state"], outputs="text").launch()