Update app.py

app.py

@@ -12,97 +12,34 @@ OPENAI_API_KEY=os.environ.get("OPENAI_API_KEY")
 PINECONE_API_KEY=os.environ.get("PINECONE_API_KEY")
 PINECONE_ENV=os.environ.get("PINECONE_ENV")
 
-pointing_pinecone_index=pinecone.Index("sethgodin")
-vectorstore=GPTPineconeIndex([],pinecone_index=pointing_pinecone_index)
-
-def set_openai_api_key(api_key: str):
-    """Set the api key and return chain.
-    If no api_key, then None is returned.
-    """
-    if api_key:
-        os.environ["OPENAI_API_KEY"] = api_key
-        chain = get_chain(vectorstore)
-        os.environ["OPENAI_API_KEY"] = ""
-        return chain
-
-
-class ChatWrapper:
-
-    def __init__(self):
-        self.lock = Lock()
-    def __call__(
-        self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain
-    ):
-        """Execute the chat functionality."""
-        self.lock.acquire()
-        try:
-            history = history or []
-            # If chain is None, that is because no API key was provided.
-            if chain is None:
-                history.append((inp, "Please paste your OpenAI key to use"))
-                return history, history
-            # Set OpenAI key
-            import openai
-            openai.api_key = api_key
-            # Run chain and append input.
-            output = chain({"question": inp, "chat_history": history})["answer"]
-            history.append((inp, output))
-        except Exception as e:
-            raise e
-        finally:
-            self.lock.release()
-        return history, history
-
-chat = ChatWrapper()
-
-block = gr.Blocks(css=".gradio-container {background-color: lightgray}")
-
-with block:
-    with gr.Row():
-        gr.Markdown("<h3><center>Chat-Your-Data (State-of-the-Union)</center></h3>")
-
-        openai_api_key_textbox = gr.Textbox(
-            placeholder="Paste your OpenAI API key (sk-...)",
-            show_label=False,
-            lines=1,
-            type="password",
-        )
-
+pindex=pinecone.Index("sethgodin")
+pinedex=GPTPineconeIndex([], pinecone_index=pindex)
+
+tools = [
+    Tool(
+        name = "GPT Index",
+        func=lambda q: str(pinedex.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 = ConversationBufferMemory(memory_key="chat_history")
+llm=OpenAI(temperature=0)
+agent_chain = initialize_agent(tools, llm, agent="conversational-react-description", memory=memory)
+
+def predict(input, history=[]):
+    # generate a response 
+    history = agent_chain.run(input=input)
+    response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)]  # convert to tuples of list
+    return response, history
+
+with gr.Blocks() as demo:
     chatbot = gr.Chatbot()
+    state = gr.State([])
 
     with gr.Row():
-        message = gr.Textbox(
-            label="What's your question?",
-            placeholder="Ask questions about the most recent state of the union",
-            lines=1,
-        )
-        submit = gr.Button(value="Send", variant="secondary").style(full_width=False)
-
-    gr.Examples(
-        examples=[
-            "What did the president say about Kentaji Brown Jackson",
-            "Did he mention Stephen Breyer?",
-            "What was his stance on Ukraine",
-        ],
-        inputs=message,
-    )
-
-    gr.HTML("Demo application of a LangChain chain.")
-
-    gr.HTML(
-        "<center>Powered by <a href='https://github.com/hwchase17/langchain'>LangChain 🦜️🔗</a></center>"
-    )
-
-    state = gr.State()
-    agent_state = gr.State()
-
-    submit.click(chat, inputs=[openai_api_key_textbox, message, state, agent_state], outputs=[chatbot, state])
-    message.submit(chat, inputs=[openai_api_key_textbox, message, state, agent_state], outputs=[chatbot, state])
+        txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
 
-    openai_api_key_textbox.change(
-        set_openai_api_key,
-        inputs=[openai_api_key_textbox],
-        outputs=[agent_state],
-    )
+    txt.submit(predict, [txt, state], [chatbot, state])
 
-block.launch(debug=True)
+demo.launch()