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| import interpreter | |
| import gradio as gr | |
| import os | |
| import io | |
| import contextlib | |
| # Use environ variables for saving and using OpenAI API key as below or use from a textbox in gradio UI | |
| # interpreter.api_key = os.environ.get('openai_api_key') | |
| interpreter.auto_run = True | |
| def chat_with_interpreter(message, history, openai_api_key): | |
| interpreter.api_key = openai_api_key | |
| if message == 'reset': | |
| interpreter.reset() | |
| # Redirect stdout to capture the streamed output | |
| new_stdout = io.StringIO() | |
| with contextlib.redirect_stdout(new_stdout): | |
| interpreter.chat(message) | |
| output = new_stdout.getvalue() | |
| # Return this output so Gradio's ChatInterface can display it | |
| return output | |
| openai_api_key = gr.Textbox(label='OpenAI API Key', intercative=True) | |
| additional_inputs = [openai_api_key] | |
| examples=[["what is 2+2?"], | |
| ["Can you solve for x: 10x -65=0?"], | |
| ["What are top 10 headlines from BBC from last week?"] | |
| ], | |
| demo = gr.ChatInterface(fn=chat_with_interpreter, | |
| title="Open-Interpreter Gradio ChatInterface", | |
| description="Open Interpreter lets LLMs run code (Python, Javascript, Shell, and more) locally", | |
| clear_btn=None, | |
| retry_btn=None, | |
| undo_btn=None, | |
| #examples=examples, | |
| additional_inputs=additional_inputs, | |
| additional_inputs_accordion_name = "OpenAI API Key", | |
| ).queue() | |
| demo.launch(debug=True) | |