initial commit

Dockerfile

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+FROM python:3.10
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+RUN pip install llama-cpp-python
+
+COPY . .
+
+CMD ["python", "app.py"]

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+import os
+
+# Khởi tạo client
+client = InferenceClient(
+    "TheBloke/OpenHermes-2.5-Mistral-7B-GGUF",
+)
+
+def generate_text(prompt, system_prompt="", max_new_tokens=512, temperature=0.7, top_p=0.95):
+    # Chuẩn bị prompt theo định dạng mà mô hình yêu cầu
+    if system_prompt:
+        formatted_prompt = f"<|im_start|>system\n{system_prompt}<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
+    else:
+        formatted_prompt = f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
+    
+    # Gọi API inference
+    response = client.text_generation(
+        formatted_prompt,
+        max_new_tokens=max_new_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        stopping_words=["<|im_end|>"]
+    )
+    
+    return response
+
+# Tạo Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# OpenHermes-2.5-Mistral-7B API")
+    
+    with gr.Row():
+        with gr.Column():
+            system_prompt = gr.Textbox(label="System Prompt (optional)", lines=2)
+            prompt = gr.Textbox(label="User Prompt", lines=4)
+            
+            with gr.Row():
+                max_tokens = gr.Slider(minimum=64, maximum=2048, value=512, step=64, label="Max New Tokens")
+                temp = gr.Slider(minimum=0.1, maximum=1.5, value=0.7, step=0.1, label="Temperature")
+                top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p")
+            
+            submit_btn = gr.Button("Generate")
+        
+        with gr.Column():
+            output = gr.Textbox(label="Generated Output", lines=10)
+    
+    submit_btn.click(
+        generate_text,
+        inputs=[prompt, system_prompt, max_tokens, temp, top_p],
+        outputs=output
+    )
+
+# Thêm API endpoint
+demo.queue().launch(share=True)

requirements.txt

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+gradio>=3.50.2
+huggingface_hub
+transformers