Update app.py

app.py

@@ -1,20 +1,34 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-from datasets import load_dataset  # Import datasets library
+from datasets import load_dataset
 
-# Load the PleIAs/common_corpus dataset
-common_corpus = load_dataset("PleIAs/common_corpus")
+# Load the PleIAs/common_corpus dataset with error handling
+def load_common_corpus():
+    try:
+        return load_dataset("PleIAs/common_corpus")
+    except Exception as e:
+        print(f"Error loading dataset: {e}")
+        return None
 
-# Function to retrieve an example from the dataset
+common_corpus = load_common_corpus()
+
+# Retrieve an example from the dataset safely
 def get_example_from_corpus(dataset, index):
-    if "train" in dataset:
-        example = dataset["train"][index]
-        return example
+    if dataset and "train" in dataset:
+        try:
+            return dataset["train"][index]
+        except IndexError:
+            print("Index out of range for dataset")
+            return {"text": "No example available"}
     else:
-        raise ValueError("Dataset does not have a 'train' split.")
+        return {"text": "Dataset not loaded correctly"}
 
-# Initialize inference client
-client = InferenceClient("unsloth/Llama-3.2-1B-Instruct")
+# Initialize the Inference Client with error handling
+try:
+    client = InferenceClient("unsloth/Llama-3.2-1B-Instruct")
+except Exception as e:
+    print(f"Error initializing inference client: {e}")
+    client = None
 
 def respond(
     message,
@@ -24,33 +38,37 @@ def respond(
     temperature,
     top_p,
 ):
+    if not client:
+        return "Error: Inference client not initialized."
+
     messages = [{"role": "system", "content": system_message}]
 
-    # Add historical interactions
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
-    # Add user's message
     messages.append({"role": "user", "content": message})
 
-    # Get response from model
-    response = client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        temperature=temperature,
-        top_p=top_p,
-    ).choices[0].message.content
-
+    try:
+        response = client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            temperature=temperature,
+            top_p=top_p,
+        ).choices[0].message.content
+    except Exception as e:
+        print(f"Error during inference: {e}")
+        response = "An error occurred while generating a response."
+    
     return response
 
-# Example usage of the dataset
-example_data = get_example_from_corpus(common_corpus, index=0)
+# Example: Retrieve an entry from the dataset to demonstrate integration
+example_data = get_example_from_corpus(common_corpus, 0)
 print("Example from PleIAs/common_corpus:", example_data)
 
-# Gradio ChatInterface
+# Gradio interface with proper error handling
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -68,4 +86,7 @@ demo = gr.ChatInterface(
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    try:
+        demo.launch()
+    except Exception as e:
+        print(f"Error launching Gradio app: {e}")