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| import gradio as gr | |
| from datetime import date | |
| from langchain.agents import AgentType, initialize_agent, tool | |
| from langchain.chat_models import ChatOpenAI | |
| config = { | |
| "max_tokens": 1000, | |
| "model_name": "gpt-4", | |
| "temperature": 0, | |
| } | |
| def time(text: str) -> str: | |
| """Returns todays date, use this for any \ | |
| questions related to knowing todays date. \ | |
| The input should always be an empty string, \ | |
| and this function will always return todays \ | |
| date - any date mathmatics should occur \ | |
| outside this function.""" | |
| return str(date.today()) | |
| def invoke(openai_api_key, prompt): | |
| if (openai_api_key == ""): | |
| raise gr.Error("OpenAI API Key is required.") | |
| if (prompt == ""): | |
| raise gr.Error("Prompt is required.") | |
| output = "" | |
| try: | |
| llm = ChatOpenAI(model_name = config["model_name"], | |
| openai_api_key = openai_api_key, | |
| temperature = config["temperature"]) | |
| agent = initialize_agent([time], | |
| llm, | |
| agent = AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION, | |
| handle_parsing_errors = True, | |
| verbose = True) | |
| completion = agent(prompt) | |
| output = completion.output | |
| except Exception as e: | |
| err_msg = e | |
| raise gr.Error(e) | |
| return output | |
| description = """<a href='https://www.gradio.app/'>Gradio</a> UI using the <a href='https://openai.com/'>OpenAI</a> API | |
| with <a href='https://openai.com/research/gpt-4'>gpt-4</a> model.""" | |
| gr.close_all() | |
| demo = gr.Interface(fn = invoke, | |
| inputs = [gr.Textbox(label = "OpenAI API Key", type = "password", lines = 1), | |
| gr.Textbox(label = "Prompt", lines = 1, value = "What is today's date?")], | |
| outputs = [gr.Textbox(label = "Completion", lines = 1)], | |
| title = "Generative AI - LLM & Agent", | |
| description = description) | |
| demo.launch() |