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| import os | |
| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| # Read Hugging Face token from Secrets | |
| HF_TOKEN = os.getenv("HF_TOKEN") | |
| client = InferenceClient( | |
| provider="hf-inference", | |
| api_key=HF_TOKEN, | |
| ) | |
| SYSTEM_PROMPT = """ | |
| You are an experienced Software QA Engineer. | |
| Generate a professional bug report in the following format: | |
| Bug Title: | |
| Severity: | |
| Priority: | |
| Module: | |
| Steps to Reproduce: | |
| Expected Result: | |
| Actual Result: | |
| Possible Root Cause: | |
| """ | |
| def generate_bug_report(description): | |
| try: | |
| response = client.chat.completions.create( | |
| model="Qwen/Qwen2.5-7B-Instruct", | |
| messages=[ | |
| { | |
| "role": "system", | |
| "content": SYSTEM_PROMPT | |
| }, | |
| { | |
| "role": "user", | |
| "content": description | |
| } | |
| ], | |
| max_tokens=500, | |
| ) | |
| return response.choices[0].message.content | |
| except Exception as e: | |
| return f"Error:\n\n{str(e)}" | |
| demo = gr.Interface( | |
| fn=generate_bug_report, | |
| inputs=gr.Textbox( | |
| lines=8, | |
| placeholder="Describe the software bug..." | |
| ), | |
| outputs=gr.Textbox(lines=20), | |
| title="🐞 AI Bug Report Generator", | |
| description="Enter a bug description and generate a professional QA bug report using AI." | |
| ) | |
| demo.launch() |