Update app.py

app.py

@@ -2,46 +2,45 @@ import os
 import json
 import gradio as gr
 
-# Path to the dataset folder
-DATASET_FOLDER = "dataset/"
-
+# Load Dataset Function
 def load_dataset(folder_path):
-    """Load all JSON files from the dataset folder."""
+    """Loads all JSON files from a folder and subfolders into a single dataset."""
     data = []
-    for file_name in os.listdir(folder_path):
-        if file_name.endswith(".json"):
-            file_path = os.path.join(folder_path, file_name)
-            with open(file_path, "r") as f:
+    for root, dirs, files in os.walk(folder_path):
+        for file_name in files:
+            if file_name.endswith(".json"):
+                file_path = os.path.join(root, file_name)
                 try:
-                    file_data = json.load(f)
-                    data.append(file_data)
-                except json.JSONDecodeError:
-                    print(f"Error decoding {file_path}. Skipping.")
+                    with open(file_path, "r") as f:
+                        file_data = json.load(f)
+                        data.append(file_data)
+                except Exception as e:
+                    print(f"Error loading {file_name}: {e}")
     return data
 
-# Load the dataset
-dataset = load_dataset(DATASET_FOLDER)
+# Initialize Dataset
+DATASET_PATH = os.path.join(os.path.dirname(__file__), "dataset")
+dataset = load_dataset(DATASET_PATH)
 
-# Define your chatbot logic
+# Chatbot Response Function
 def chatbot_response(user_input):
-    # Example: Search dataset for relevant information
-    responses = []
-    for item in dataset:
-        if user_input.lower() in json.dumps(item).lower():
-            responses.append(item)
-    if responses:
-        return f"Found {len(responses)} matching records.", responses
-    return "No relevant information found.", []
+    """Generate a response based on user input and the dataset."""
+    for entry in dataset:
+        if "question" in entry and "answer" in entry:
+            if user_input.lower() in entry["question"].lower():
+                return entry["answer"]
+    return "I'm sorry, I couldn't find relevant information. Please provide more details."
 
 # Gradio Interface
 interface = gr.Interface(
     fn=chatbot_response,
     inputs="text",
-    outputs=["text", "json"],
+    outputs="text",
     title="Education Consultant Chatbot",
-    description="A chatbot for education consultancy."
+    description="Ask questions about study programs, visas, and more!",
+    theme="compact"
 )
 
-# Launch the app
+# Run App
 if __name__ == "__main__":
     interface.launch()