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add huggingface working version
Browse files- app.py +3 -0
- app_huggingface.py +11 -4
app.py
CHANGED
@@ -1,5 +1,6 @@
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import gradio as gr
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from app_playai import demo as demo_playai
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from app_allenai import demo as demo_allenai
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from app_claude import demo as demo_claude
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@@ -22,6 +23,8 @@ from app_xai import demo as demo_grok
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from app_showui import demo as demo_showui
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with gr.Blocks(fill_height=True) as demo:
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with gr.Tab("Fal"):
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demo_fal.render()
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gr.Markdown("This app is built with gradio, check out gradio github and star: <a href='https://github.com/gradio-app/gradio'>Gradio <img src='https://img.shields.io/github/stars/gradio-app/gradio'></a>.")
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import gradio as gr
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from app_huggingface import demo as demo_huggingface
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from app_playai import demo as demo_playai
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from app_allenai import demo as demo_allenai
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from app_claude import demo as demo_claude
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from app_showui import demo as demo_showui
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with gr.Blocks(fill_height=True) as demo:
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with gr.Tab("Huggingface"):
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demo_huggingface.render()
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with gr.Tab("Fal"):
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demo_fal.render()
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gr.Markdown("This app is built with gradio, check out gradio github and star: <a href='https://github.com/gradio-app/gradio'>Gradio <img src='https://img.shields.io/github/stars/gradio-app/gradio'></a>.")
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app_huggingface.py
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@@ -1,4 +1,4 @@
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from gradio_client import Client
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import gradio as gr
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import os
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@@ -8,9 +8,16 @@ MODELS = {
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}
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def create_chat_fn(client):
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def chat(message, history
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response = client.predict(
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message={"text":
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system_prompt="You are a helpful AI assistant.",
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temperature=0.7,
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max_new_tokens=1024,
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@@ -71,5 +78,5 @@ with gr.Blocks() as demo:
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outputs=[client]
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)
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demo
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from gradio_client import Client, handle_file
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import gradio as gr
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import os
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}
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def create_chat_fn(client):
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def chat(message, history):
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# Extract text and files from the message
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text = message.get("text", "")
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files = message.get("files", [])
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# Handle file uploads if present
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processed_files = [handle_file(f) for f in files]
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response = client.predict(
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message={"text": text, "files": processed_files},
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system_prompt="You are a helpful AI assistant.",
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temperature=0.7,
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max_new_tokens=1024,
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outputs=[client]
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)
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demo.launch()
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