K00B404 commited on
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e47d2e4
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1 Parent(s): 0cf78ee

Update app.py

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  1. app.py +9 -37
app.py CHANGED
@@ -1,24 +1,15 @@
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- '''🔧 Prerequisites
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-
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- Install the necessary packages:
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-
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- pip install gradio transformers
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-
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- 📱 Gradio Chatbot App Code
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- '''
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  import gradio as gr
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  from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
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  import torch
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  # List of available premium models
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  premium_models = [
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- "HuggingFaceH4/zephyr-7b-beta",
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- "K00B404/BagOClownCoders-slerp-7B",
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- "Qwen/Qwen2.5-Omni-7B",
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- "Qwen/Qwen2.5-VL-7B-Instruct",
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- "deepseek-ai/Janus-Pro-7B",
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- "meta-llama/Llama-2-7b-hf",
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- "Alibaba-NLP/gte-Qwen2-7B-instruct",
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  ]
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  # Dictionary to cache loaded pipelines
@@ -72,6 +63,9 @@ with gr.Blocks() as demo:
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  with gr.Row():
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  model_choice = gr.Dropdown(label="Select Model", choices=premium_models, value=premium_models[0])
 
 
 
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  chatbot_ui = gr.Chatbot(type="messages")
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  user_input = gr.Textbox(show_label=False, placeholder="Type your message and press Enter")
@@ -83,25 +77,3 @@ with gr.Blocks() as demo:
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  clear_btn.click(lambda: ([], ""), None, [chatbot_ui, state])
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  demo.launch()
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- '''
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- ✅ Features:
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-
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- Model selection from dropdown
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-
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- Maintains chat history
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-
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- Respects a system prompt
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- Uses text-generation pipeline
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- 🧠 Optional Upgrades:
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-
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- Replace text-generation with chat-completion if models support it (like OpenChat, Mistral-instruct, etc.)
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-
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- Add streaming or token-by-token response if supported
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- Save/load chat history
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- Add support for vision models (Qwen2.5-VL-7B-Instruct) using a different UI tab
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-
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- '''
 
 
 
 
 
 
 
 
 
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  import gradio as gr
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  from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
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  import torch
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  # List of available premium models
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  premium_models = [
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+ "Qwen/Qwen2-0.5B",
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+ "Qwen/Qwen2-0.5B-Instruct",
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+ "Qwen/Qwen2-0.5B-Coder",
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+ "Qwen/Qwen2-1.5B",
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+ "Qwen/Qwen2-1.5B-Instruct",
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+ "Qwen/Qwen2-1.5B-Coder",
 
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  ]
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  # Dictionary to cache loaded pipelines
 
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  with gr.Row():
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  model_choice = gr.Dropdown(label="Select Model", choices=premium_models, value=premium_models[0])
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+
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+ with gr.Row():
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+ model_choice = gr.Textbox(label="System Prompt", choices=premium_models, value=default_system_prompt)
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  chatbot_ui = gr.Chatbot(type="messages")
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  user_input = gr.Textbox(show_label=False, placeholder="Type your message and press Enter")
 
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  clear_btn.click(lambda: ([], ""), None, [chatbot_ui, state])
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  demo.launch()