Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
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@@ -1,19 +1,16 @@
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import os
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import gradio as gr
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from huggingface_hub import login
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from huggingface_hub import InferenceClient
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import spaces
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# Authenticate with Hugging Face API
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api_key = os.getenv("
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login(api_key)
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# Initialize clients for different models
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llama_client = InferenceClient("meta-llama/Llama-3.1-70B-Instruct")
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gpt_client = InferenceClient("openai/gpt-4")
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# Define the response function
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@spaces.GPU
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def respond(
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message,
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history: list[dict],
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@@ -23,11 +20,9 @@ def respond(
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top_p,
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selected_models,
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):
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# Prepare input messages
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messages = [{"role": "system", "content": system_message}] + history
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messages.append({"role": "user", "content": message})
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# Collect responses from selected models
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responses = {}
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if "Llama" in selected_models:
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@@ -50,7 +45,7 @@ def respond(
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return responses
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# Build
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def create_demo():
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return gr.Blocks().add(
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gr.Markdown("# AI Model Comparison Tool 🌟"),
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import os
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import gradio as gr
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from huggingface_hub import login, InferenceClient
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# Authenticate with Hugging Face API
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api_key = os.getenv("TOKEN")
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login(api_key)
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# Initialize clients for different models
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llama_client = InferenceClient("meta-llama/Llama-3.1-70B-Instruct")
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gpt_client = InferenceClient("openai/gpt-4")
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# Define the response function
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def respond(
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message,
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history: list[dict],
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top_p,
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selected_models,
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):
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messages = [{"role": "system", "content": system_message}] + history
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messages.append({"role": "user", "content": message})
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responses = {}
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if "Llama" in selected_models:
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return responses
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# Build Gradio app
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def create_demo():
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return gr.Blocks().add(
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gr.Markdown("# AI Model Comparison Tool 🌟"),
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