Update app.py

app.py

@@ -0,0 +1,48 @@
+import os
+import gradio as gr
+import pinecone
+from gpt_index import GPTIndexMemory, GPTPineconeIndex
+from langchain.agents import Tool
+from langchain.chains.conversation.memory import ConversationBufferMemory
+from langchain import OpenAI
+from langchain.agents import initialize_agent
+
+OPENAI_API_KEY=os.environ["OPENAI_API_KEY"]
+PINECONE_API_KEY=os.environ["PINECONE_API_KEY"]
+
+pinecone.init(api_key=PINECONE_API_KEY, environment="us-east1-gcp")
+
+pindex=pinecone.Index("sejarah")
+indexed_pinecone=GPTPineconeIndex([], pinecone_index=pindex)
+
+tools = [
+    Tool(
+        name = "GPT Index",
+        func=lambda q: str(indexed_pinecone.query(q)),
+        description="useful for when you want to answer questions about the author. The input to this tool should be a complete english sentence.",
+        return_direct=True
+    )
+]
+memory = GPTIndexMemory(index=indexed_pinecone, memory_key="chat_history", query_kwargs={"response_mode": "compact"})
+llm=LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo"))
+agent_chain = initialize_agent(tools, llm, agent="conversational-react-description", memory=memory, verbose=True)
+
+def predict(input, history=[]):
+    response = agent_chain.run(input)
+    history = history + [(input, response)]
+    response = history
+    # response = [response] 
+    # return response, response
+    return response, response
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    state = gr.State([])
+
+    with gr.Row():
+        txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
+
+    txt.submit(predict, [txt, state], [chatbot, state])
+    # txt.submit(agent_executor.run, [txt, state], [chatbot, state])
+
+demo.launch()