Update app.py

app.py

@@ -35,10 +35,15 @@ def query_huggingface(prompt, temperature=0.5, max_tokens=100, top_k=50, top_p=0
         response = requests.post(API_URL, headers=headers, json=payload)
         response.raise_for_status()
         result = response.json()
-        return result[0]['generated_text'] if isinstance(result, list) and len(result) > 0 else result.get('generated_text', 'No response generated.')
+        if isinstance(result, list) and len(result) > 0 and 'generated_text' in result[0]:
+            return result[0]['generated_text']
+        elif 'generated_text' in result:
+            return result['generated_text']
+        else:
+            return "No response generated."
     except requests.exceptions.RequestException as e:
         logger.error(f"Error querying the API: {e}")
-        return {"error": str(e)}
+        return f"Error: {str(e)}"
 
 # Initialize the Discord bot with a default prefix
 intents = discord.Intents.default()
@@ -53,31 +58,27 @@ async def on_ready():
 
 @bot.command(name='ask')
 @commands.cooldown(rate=1, per=10, type=commands.BucketType.user)
-async def ask(ctx, question: str, temperature: float = 0.8, max_tokens: int = 1000, top_k: int = 70, top_p: float = 0.4):
+async def ask(ctx, *question):
     """
     Command to ask a question to the Hugging Face model with an instructive prompt.
     """
-    try:
-        # Convert parameters to their respective types
-        temperature = float(temperature)
-        max_tokens = int(max_tokens)
-        top_k = int(top_k)
-        top_p = float(top_p)
-    except ValueError:
-        await ctx.send("Invalid input for one of the parameters. Please provide valid numbers.")
+    if not question:
+        await ctx.send("You need to ask a question.")
         return
 
-    # Create a structured prompt
-    prompt = f"Answer the following question accurately and concisely: {question}"
-    response = query_huggingface(prompt, temperature, max_tokens, top_k, top_p)
-    
-    # Extract and clean the response
-    if 'error' in response:
-        clean_response = f"Error: {response['error']}"
-    else:
+    question = " ".join(question)
+    try:
+        # Create a structured prompt
+        prompt = f"Answer the following question accurately and concisely: {question}"
+        response = query_huggingface(prompt, temperature=0.8, max_tokens=1000, top_k=70, top_p=0.4)
+        
+        # Extract and clean the response
         clean_response = response.replace(prompt, '').strip()
-    
-    await ctx.send(clean_response)
+        
+        await ctx.send(clean_response)
+    except Exception as e:
+        logger.error(f"Error processing the ask command: {e}")
+        await ctx.send("An error occurred while processing your request.")
 
 @ask.error
 async def ask_error(ctx, error):
@@ -97,12 +98,7 @@ async def set_prefix(ctx, prefix: str):
 async def help_custom(ctx):
     help_text = (
         "Here are the commands you can use:\n"
-        "!ask <question> [temperature] [max_tokens] [top_k] [top_p] - Ask a question to the AI model.\n"
-        "Optional parameters:\n"
-        "  temperature (default=0.5) - Controls the randomness of the response.\n"
-        "  max_tokens (default=100) - Limits the length of the response.\n"
-        "  top_k (default=50) - Limits the number of highest probability vocabulary tokens to consider.\n"
-        "  top_p (default=0.9) - Limits the cumulative probability of the highest probability vocabulary tokens.\n"
+        "!ask <question> - Ask a question to the AI model.\n"
         "!setprefix <prefix> - Change the command prefix (admin only).\n"
         "!help_custom - Display this help message."
     )