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| """A Simple chatbot that uses the LangChain and Gradio UI to answer questions about wandb documentation.""" | |
| import os | |
| from types import SimpleNamespace | |
| import gradio as gr | |
| import wandb | |
| from chain import get_answer, load_chain, load_vector_store | |
| from config import default_config | |
| class Chat: | |
| """A chatbot interface that persists the vectorstore and chain between calls.""" | |
| def __init__( | |
| self, | |
| config: SimpleNamespace, | |
| ): | |
| """Initialize the chatbot. | |
| Args: | |
| config (SimpleNamespace): The configuration. | |
| """ | |
| self.config = config | |
| self.wandb_run = wandb.init( | |
| project=self.config.project, | |
| entity=self.config.entity, | |
| job_type=self.config.job_type, | |
| config=self.config, | |
| ) | |
| self.vector_store = None | |
| self.chain = None | |
| def __call__( | |
| self, | |
| question: str, | |
| history: list[tuple[str, str]] | None = None, | |
| openai_api_key: str = None, | |
| ): | |
| """Answer a question about MASSA documentation using the LangChain QA chain and vector store retriever. | |
| Args: | |
| question (str): The question to answer. | |
| history (list[tuple[str, str]] | None, optional): The chat history. Defaults to None. | |
| openai_api_key (str, optional): The OpenAI API key. Defaults to None. | |
| Returns: | |
| list[tuple[str, str]], list[tuple[str, str]]: The chat history before and after the question is answered. | |
| """ | |
| if openai_api_key is not None: | |
| openai_key = openai_api_key | |
| elif os.environ["OPENAI_API_KEY"]: | |
| openai_key = os.environ["OPENAI_API_KEY"] | |
| else: | |
| raise ValueError( | |
| "Please provide your OpenAI API key as an argument or set the OPENAI_API_KEY environment variable" | |
| ) | |
| if self.vector_store is None: | |
| self.vector_store = load_vector_store( | |
| wandb_run=self.wandb_run, openai_api_key=openai_key | |
| ) | |
| if self.chain is None: | |
| self.chain = load_chain( | |
| self.wandb_run, self.vector_store, openai_api_key=openai_key | |
| ) | |
| history = history or [] | |
| question = question.lower() | |
| response = get_answer( | |
| chain=self.chain, | |
| question=question, | |
| chat_history=history, | |
| ) | |
| history.append((question, response)) | |
| return history, history | |
| with gr.Blocks() as demo: | |
| gr.HTML( | |
| """<div style="text-align: center; max-width: 700px; margin: 0 auto;"> | |
| <div | |
| style=" | |
| display: inline-flex; | |
| align-items: center; | |
| gap: 0.8rem; | |
| font-size: 1.75rem; | |
| " | |
| > | |
| <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;"> | |
| Massa QandA Bot | |
| </h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%"> | |
| Hi, I'm a massa documentaion Q and A bot, start by typing in your OpenAI API key, questions/issues you have related to massa usage and then press enter.<br> | |
| Built using <a href="https://langchain.readthedocs.io/en/latest/" target="_blank">LangChain</a> and <a href="https://github.com/gradio-app/gradio" target="_blank">Gradio Github repo</a> | |
| </p> | |
| </div>""" | |
| ) | |
| with gr.Row(): | |
| question = gr.Textbox( | |
| label="Type in your questions about massa net here and press Enter!", | |
| placeholder="How do I write smart contract with massa ?", | |
| ) | |
| openai_api_key = gr.Textbox( | |
| type="password", | |
| label="Enter your OpenAI API key here", | |
| ) | |
| state = gr.State() | |
| chatbot = gr.Chatbot() | |
| question.submit( | |
| Chat( | |
| config=default_config, | |
| ), | |
| [question, state, openai_api_key], | |
| [chatbot, state], | |
| ) | |
| if __name__ == "__main__": | |
| demo.queue().launch( | |
| share=False, server_name="0.0.0.0", server_port=8884, show_error=True | |
| ) | |