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Update app.py
Browse files
app.py
CHANGED
@@ -1,13 +1,13 @@
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import streamlit as st
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import requests
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# Hugging Face API URL
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API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
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# Function to query the Hugging Face API
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def query(payload):
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headers = {"Authorization": f"Bearer {st.secrets['HF_TOKEN']}"}
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response = requests.post(
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return response.json()
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# Page configuration
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@@ -26,6 +26,14 @@ with st.sidebar:
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st.header("Model Configuration")
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st.markdown("[Get HuggingFace Token](https://huggingface.co/settings/tokens)")
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system_message = st.text_area(
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"System Message",
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value="You are a friendly Chatbot created by ruslanmv.com",
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@@ -76,15 +84,15 @@ if prompt := st.chat_input("Type your message..."):
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}
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}
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# Query the Hugging Face API
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output = query(payload)
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# Handle API response
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if isinstance(output, list) and len(output) > 0 and 'generated_text' in output[0]:
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assistant_response = output[0]['generated_text']
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else:
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st.error("Error: Unable to generate a response. Please try again.")
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with st.chat_message("assistant"):
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st.markdown(assistant_response)
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import streamlit as st
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import requests
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# Hugging Face API URL (default model)
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API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
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# Function to query the Hugging Face API
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def query(payload, api_url):
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headers = {"Authorization": f"Bearer {st.secrets['HF_TOKEN']}"}
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response = requests.post(api_url, headers=headers, json=payload)
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return response.json()
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# Page configuration
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st.header("Model Configuration")
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st.markdown("[Get HuggingFace Token](https://huggingface.co/settings/tokens)")
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# Dropdown to select model
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model_options = [
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"deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
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"deepseek-ai/DeepSeek-R1",
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"deepseek-ai/DeepSeek-R1-Zero"
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]
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selected_model = st.selectbox("Select Model", model_options, index=0)
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system_message = st.text_area(
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"System Message",
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value="You are a friendly Chatbot created by ruslanmv.com",
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}
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}
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# Query the Hugging Face API using the selected model
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output = query(payload, f"https://api-inference.huggingface.co/models/{selected_model}")
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# Handle API response
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if isinstance(output, list) and len(output) > 0 and 'generated_text' in output[0]:
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assistant_response = output[0]['generated_text']
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else:
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st.error("Error: Unable to generate a response. Please try again.")
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continue # Skip further execution for this iteration
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with st.chat_message("assistant"):
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st.markdown(assistant_response)
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