Spaces:
Running
on
T4
Running
on
T4
Commit
•
d6cc295
1
Parent(s):
e201c60
Update app.py
Browse files
app.py
CHANGED
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@@ -4,6 +4,8 @@ from gradio_webrtc import WebRTC, ReplyOnPause, AdditionalOutputs
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import numpy as np
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import os
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from twilio.rest import Client
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account_sid = os.environ.get("TWILIO_ACCOUNT_SID")
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auth_token = os.environ.get("TWILIO_AUTH_TOKEN")
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@@ -33,6 +35,34 @@ whisper = pipeline(
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system_prompt = "You are an AI coding assistant. Your task is to write single-file HTML applications based on a user's request. You may also be asked to edit your original response. Only return the code needed to fulfill the request."
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user_prompt = "Please write a single-file HTML application to fulfill the following request. Only return the necessary code. Include all necessary imports and styles.\nThe message:{user_message}\nCurrent code you have written:{code}"
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def generate(user_message: tuple[int, np.ndarray],
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@@ -48,17 +78,20 @@ def generate(user_message: tuple[int, np.ndarray],
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history.append({"role": "user", "content": user_msg_formatted})
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input_text = tokenizer.apply_chat_template(history, tokenize=False)
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inputs = tokenizer.encode(input_text, return_tensors="pt").to(device)
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outputs = model.generate(inputs, max_new_tokens=
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response = tokenizer.decode(outputs[0])
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output = response[response.rindex("<|im_start|>assistant\n") + len("<|im_start|>assistant\n"):]
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history.append({"role": "assistant", "content": output})
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yield AdditionalOutputs(history,
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with gr.Blocks() as demo:
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history = gr.State([{"role": "system", "content": system_prompt}])
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with gr.Row():
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code = gr.Code(language="html")
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sandbox = gr.HTML("")
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with gr.Row():
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webrtc = WebRTC(rtc_configuration=rtc_configuration, mode="send", modality="audio")
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@@ -67,6 +100,7 @@ with gr.Blocks() as demo:
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outputs=[webrtc], time_limit=90)
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webrtc.on_additional_outputs(lambda history, code: (history, code),
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outputs=[history, code])
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if __name__ == "__main__":
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demo.launch()
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import numpy as np
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import os
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from twilio.rest import Client
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import base64
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account_sid = os.environ.get("TWILIO_ACCOUNT_SID")
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auth_token = os.environ.get("TWILIO_AUTH_TOKEN")
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system_prompt = "You are an AI coding assistant. Your task is to write single-file HTML applications based on a user's request. You may also be asked to edit your original response. Only return the code needed to fulfill the request."
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user_prompt = "Please write a single-file HTML application to fulfill the following request. Only return the necessary code. Include all necessary imports and styles.\nThe message:{user_message}\nCurrent code you have written:{code}"
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def extract_html_content(text):
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"""
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Extract content including HTML tags.
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"""
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try:
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start_tag = "<html>"
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end_tag = "</html>"
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# Find positions of start and end tags
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start_pos = text.find(start_tag)
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end_pos = text.find(end_tag)
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# Check if both tags exist and are in correct order
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if start_pos == -1 or end_pos == -1 or start_pos > end_pos:
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return None
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# Extract content including tags
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return text[start_pos:end_pos + len(end_tag)]
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except Exception as e:
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print(f"Error processing string: {e}")
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return None
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def display_in_sandbox(code):
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encoded_html = base64.b64encode(code.encode('utf-8')).decode('utf-8')
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data_uri = f"data:text/html;charset=utf-8;base64,{encoded_html}"
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return f"<iframe src=\"{data_uri}\" width=\"100%\" height=\"920px\"></iframe>"
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def generate(user_message: tuple[int, np.ndarray],
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history.append({"role": "user", "content": user_msg_formatted})
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input_text = tokenizer.apply_chat_template(history, tokenize=False)
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inputs = tokenizer.encode(input_text, return_tensors="pt").to(device)
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outputs = model.generate(inputs, max_new_tokens=2048, temperature=0.2, top_p=0.9, do_sample=True)
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response = tokenizer.decode(outputs[0])
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print("response", response)
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output = response[response.rindex("<|im_start|>assistant\n") + len("<|im_start|>assistant\n"):]
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html_code = extract_html_content(output)
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history.append({"role": "assistant", "content": output})
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yield AdditionalOutputs(history, html_code)
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with gr.Blocks() as demo:
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history = gr.State([{"role": "system", "content": system_prompt}])
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with gr.Row():
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code = gr.Code(language="html", interactive=False)
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sandbox = gr.HTML("")
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with gr.Row():
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webrtc = WebRTC(rtc_configuration=rtc_configuration, mode="send", modality="audio")
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outputs=[webrtc], time_limit=90)
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webrtc.on_additional_outputs(lambda history, code: (history, code),
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outputs=[history, code])
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code.change(display_in_sandbox, code, html, queue=False)
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if __name__ == "__main__":
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demo.launch()
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