Update app.py

app.py

@@ -43,6 +43,26 @@ def get_relevant_info(query, top_k=3):
     return data.iloc[top_indices]
 
 # Function to generate response using Hugging Face Model API
+# def generate_response(input_text, relevant_info):
+#     # Concatenate the relevant information as context for the model
+#     context = "\n".join(relevant_info['combined_description'].tolist())
+#     input_with_context = f"Context: {context}\n\nUser Query: {input_text}"
+    
+#     api_url = "https://api-inference.huggingface.co/models/m42-health/Llama3-Med42-8B"
+#     headers = {"Authorization": f"Bearer {os.getenv('HUGGINGFACEHUB_API_TOKEN')}"}
+#     payload = {"inputs": input_with_context}
+
+#     try:
+#         response = requests.post(api_url, headers=headers, json=payload)
+#         response_data = response.json()
+#         if isinstance(response_data, list) and "generated_text" in response_data[0]:
+#             return response_data[0]["generated_text"]
+#         else:
+#             return "Unexpected response format from API."
+#     except Exception as e:
+#         st.error(f"Error during API request: {e}")
+#         return "Error processing your request."
+
 def generate_response(input_text, relevant_info):
     # Concatenate the relevant information as context for the model
     context = "\n".join(relevant_info['combined_description'].tolist())
@@ -55,6 +75,11 @@ def generate_response(input_text, relevant_info):
     try:
         response = requests.post(api_url, headers=headers, json=payload)
         response_data = response.json()
+        
+        # Print or display the raw response data
+        st.write("Raw API response:", response_data)
+        
+        # Check and parse the response
         if isinstance(response_data, list) and "generated_text" in response_data[0]:
             return response_data[0]["generated_text"]
         else:
@@ -63,6 +88,11 @@ def generate_response(input_text, relevant_info):
         st.error(f"Error during API request: {e}")
         return "Error processing your request."
 
+# Check and parse the response if it's a single JSON object
+if isinstance(response_data, dict) and "generated_text" in response_data:
+    return response_data["generated_text"]
+
+
 # Streamlit UI for the FAQ Chatbot
 def main():
     st.title("Medical FAQ Chatbot")