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import os |
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import gradio as gr |
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from openai import OpenAI |
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API_KEY = os.getenv("API_KEY") |
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client = OpenAI( |
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base_url="https://integrate.api.nvidia.com/v1", |
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api_key=API_KEY |
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) |
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history = [] |
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files_contents = [] |
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def chat_with_model(message, file=None): |
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global history, files_contents |
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content = message |
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if file: |
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try: |
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file_content = file.read().decode() |
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except Exception: |
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file_content = "<تعذر قراءة الملف>" |
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files_contents.append(f"# محتوى الملف {file.name}:\n{file_content}") |
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if files_contents: |
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content += "\n\n".join(files_contents) |
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history.append({"role": "user", "content": content}) |
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completion = client.chat.completions.create( |
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model="qwen/qwen3-coder-480b-instruct", |
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messages=history, |
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temperature=0, |
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top_p=0.61, |
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max_tokens=16384, |
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stream=True |
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) |
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response_text = "" |
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for chunk in completion: |
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if chunk.choices[0].delta.content is not None: |
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response_text += chunk.choices[0].delta.content |
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print(chunk.choices[0].delta.content, end="") |
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history.append({"role": "assistant", "content": response_text}) |
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files_contents.clear() |
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return response_text, history |
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with gr.Blocks() as demo: |
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gr.Markdown("# NVIDIA Qwen3 Chat (ملفات متعددة، رسالة واحدة للنموذج)") |
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chatbot = gr.Chatbot(type="messages") |
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msg = gr.Textbox(label="اكتب رسالتك هنا") |
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file_input = gr.File( |
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label="ارفع ملف Python أو نصي (يمكن رفع أكثر من مرة)", |
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file_types=[".py", ".txt"] |
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) |
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send = gr.Button("إرسال") |
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def handle_submit(message, file): |
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answer, history = chat_with_model(message, file) |
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return gr.update(value=history), "", None |
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send.click(handle_submit, [msg, file_input], [chatbot, msg, file_input]) |
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demo.launch() |
