Update app.py

app.py

@@ -65,7 +65,7 @@ tokenizer = AutoTokenizer.from_pretrained("FlawedLLM/Bhashini_gemma16")
 model = AutoModelForCausalLM.from_pretrained("FlawedLLM/Bhashini_gemma16", load_in_4bit=True)
 
 @spaces.GPU(duration=300)
-def chunk_it(input_command):
+def chunk_it(input_command, item_list):
     alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
     
     ### Instruction:
@@ -76,6 +76,8 @@ def chunk_it(input_command):
     
     ### Response:
     {}"""
+    if item_list is not None:
+        item_list="The ItemName should be STRICTLY chosen from the given list of ItemNames : " + item_list
     inputs = tokenizer(
     [
         alpaca_prompt.format(
@@ -118,7 +120,7 @@ def chunk_it(input_command):
                 Duration (integer: number of days, default: 6)
                 ReportType (string: "profit", "revenue", "inventory", or Null for all reports)
             
-            ALWAYS provide output in a JSON format.''', # instruction
+            ALWAYS provide output in a JSON format.''' + item_list, # instruction
             input_command, # input
             "", # output - leave this blank for generation!
         )
@@ -139,6 +141,7 @@ def chunk_it(input_command):
 
 iface=gr.Interface(fn=chunk_it,
                   inputs="text",
+                  inputs="text"
                   outputs="text",
                   title="Formatter_Pro",
                   )