Update app.py

app.py

@@ -16,9 +16,16 @@ API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Inst
 headers = {"Authorization": f"Bearer {HF_API_KEY}"}
 
 # Function to query the Hugging Face model with a structured prompt
-def query_huggingface(prompt):
+def query_huggingface(prompt, temperature=0.5, max_tokens=100):
+    payload = {
+        "inputs": prompt,
+        "parameters": {
+            "temperature": temperature,
+            "max_new_tokens": max_tokens
+        }
+    }
     try:
-        response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
+        response = requests.post(API_URL, headers=headers, json=payload)
         response.raise_for_status()
         return response.json()
     except requests.exceptions.RequestException as e:
@@ -37,13 +44,13 @@ async def on_ready():
     print(f'Bot is ready. Logged in as {bot.user}')
 
 @bot.command(name='ask')
-async def ask(ctx, *, question: str):
+async def ask(ctx, question: str, temperature: float = 0.5, max_tokens: int = 100):
     """
     Command to ask a question to the Hugging Face model with an instructive prompt.
     """
     # Create a structured prompt
-    prompt = f"Answer the following question as accurately and concisely as possible: {question}"
-    response = query_huggingface(prompt)
+    prompt = f"Do not under any circumstance, finish or add to the input. Excluded input correction or finishing at all times. Answer the following question as accurately and concisely as possible: {question}"
+    response = query_huggingface(prompt, temperature, max_tokens)
     
     # Extract and clean the response
     if isinstance(response, dict) and 'generated_text' in response: