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Update app.py
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app.py
CHANGED
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@@ -55,7 +55,11 @@ def query(payload, api_url):
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logger.info(f"Sending request to {api_url} with payload: {payload}")
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response = requests.post(api_url, headers=headers, json=payload)
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logger.info(f"Received response: {response.status_code}, {response.text}")
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# Chat interface
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st.title("🤖 DeepSeek Chatbot")
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@@ -76,11 +80,10 @@ if prompt := st.chat_input("Type your message..."):
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try:
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with st.spinner("Generating response..."):
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# Prepare the payload for the API
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payload = {
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"inputs":
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"system_message": system_message,
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"user_message": prompt
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},
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"parameters": {
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"max_new_tokens": max_tokens,
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"temperature": temperature,
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@@ -92,22 +95,26 @@ if prompt := st.chat_input("Type your message..."):
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# Dynamically construct the API URL based on the selected model
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api_url = f"https://api-inference.huggingface.co/models/{selected_model}"
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logger.info(f"Selected model: {selected_model}, API URL: {api_url}")
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print("payload
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# Query the Hugging Face API using the selected model
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output = query(payload, api_url)
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# Handle API response
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if isinstance(output, list) and len(output) > 0
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st.
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else:
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logger.error(f"
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st.error("Error: Unable to generate a response. Please try again.")
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except Exception as e:
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logger.error(f"Application Error: {str(e)}", exc_info=True)
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logger.info(f"Sending request to {api_url} with payload: {payload}")
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response = requests.post(api_url, headers=headers, json=payload)
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logger.info(f"Received response: {response.status_code}, {response.text}")
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try:
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return response.json()
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except requests.exceptions.JSONDecodeError:
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logger.error(f"Failed to decode JSON response: {response.text}")
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return None
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# Chat interface
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st.title("🤖 DeepSeek Chatbot")
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try:
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with st.spinner("Generating response..."):
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# Prepare the payload for the API
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# Combine system message and user input into a single prompt
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full_prompt = f"{system_message}\n\nUser: {prompt}\nAssistant:"
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payload = {
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"inputs": full_prompt,
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"parameters": {
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"max_new_tokens": max_tokens,
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"temperature": temperature,
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# Dynamically construct the API URL based on the selected model
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api_url = f"https://api-inference.huggingface.co/models/{selected_model}"
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logger.info(f"Selected model: {selected_model}, API URL: {api_url}")
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print("payload",payload)
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# Query the Hugging Face API using the selected model
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output = query(payload, api_url)
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# Handle API response
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if output is not None and isinstance(output, list) and len(output) > 0:
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if 'generated_text' in output[0]:
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assistant_response = output[0]['generated_text']
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logger.info(f"Generated response: {assistant_response}")
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with st.chat_message("assistant"):
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st.markdown(assistant_response)
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st.session_state.messages.append({"role": "assistant", "content": assistant_response})
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else:
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logger.error(f"Unexpected API response structure: {output}")
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st.error("Error: Unexpected response from the model. Please try again.")
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else:
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logger.error(f"Empty or invalid API response: {output}")
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st.error("Error: Unable to generate a response. Please check the model and try again.")
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except Exception as e:
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logger.error(f"Application Error: {str(e)}", exc_info=True)
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