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| import os | |
| from typing import Optional, Tuple | |
| import gradio as gr | |
| import pickle | |
| from query_data import get_chain | |
| from threading import Lock | |
| with open("vectorstore.pkl", "rb") as f: | |
| vectorstore = pickle.load(f) | |
| 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 (H2 Economics)</center></h3>") | |
| openai_api_key_textbox = gr.Textbox( | |
| placeholder="Paste your OpenAI API key (sk-...)", | |
| show_label=False, | |
| lines=1, | |
| type="password", | |
| ) | |
| chatbot = gr.Chatbot() | |
| with gr.Row(): | |
| message = gr.Textbox( | |
| label="What's your question?", | |
| placeholder="Ask questions about anything covered in the H2 Economics syllabus", | |
| lines=1, | |
| ) | |
| submit = gr.Button(value="Send", variant="secondary").style(full_width=False) | |
| gr.Examples( | |
| examples=[ | |
| "Explain real wealth effect.", | |
| "Use the real wealth effect to explain the negative gradient of the AD curve.", | |
| "Explain the multiplier process.", | |
| ], | |
| inputs=message, | |
| ) | |
| gr.HTML("Demo application of a LangChain chain, built on H2 Economics Data. Many thanks to Jean Chua for giving her notes for this project.") | |
| 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]) | |
| openai_api_key_textbox.change( | |
| set_openai_api_key, | |
| inputs=[openai_api_key_textbox], | |
| outputs=[agent_state], | |
| ) | |
| block.launch(debug=True) |