Update app.py

app.py

@@ -1,7 +1,82 @@
-import gradio as gr
+import re
+from unsloth import FastLanguageModel
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+if True:
+    from unsloth import FastLanguageModel
+    model, tokenizer = FastLanguageModel.from_pretrained(
+        model_name = "FlawedLLM/BhashiniLLM", # YOUR MODEL YOU USED FOR TRAINING
+        max_seq_length = max_seq_length,
+        dtype = dtype,
+        load_in_4bit = load_in_4bit,
+    )
+    FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+
+@spaces.GPU
+def chunk_it(input_command):
+    inputs = tokenizer(
+    [
+        alpaca_prompt.format(
+            '''
+            You will receive  text input that you need to analyze to perform the following tasks:
+    
+            transaction: Record the details of an item transaction.
+            last n days transactions: Retrieve transaction records for a specified time period.
+            view risk inventory: View inventory items based on a risk category.
+            view inventory: View inventory details.
+            new items: Add new items to the inventory.
+            old items: View old items in inventory.
+            report generation: Generate various inventory reports.
+            Required Parameters:
+    
+            Each task requires specific parameters to execute correctly:
+    
+            transaction:
+                ItemName (string)
+                ItemQt (quantity - integer)
+                Flow (string: "in" or "out")
+                ShelfNo (string or integer)
+            last n days transactions:
+                ItemName (string)
+                Duration (integer: number of days, default: 30)
+            view risk inventory:
+                RiskType (string: "overstock", "understock", or Null for all risk types)
+            view inventory:
+                ItemName (string)
+                ShelfNo (string or integer)
+            new items:
+                ItemName (string)
+                SellingPrice (number)
+                CostPrice (number)
+            old items:
+                ShelfNo (string or integer)
+            report generation:
+                ItemName (string)
+                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
+            input_command, # input
+            "", # output - leave this blank for generation!
+        )
+    ], return_tensors = "pt").to("cuda")
+    
+    outputs = model.generate(**inputs, max_new_tokens = 216, use_cache = True)
+    tokenizer.batch_decode(outputs)
+    
+    reply=tokenizer.batch_decode(outputs)
+    # Regular expression pattern to match content between "### Response:" and "<|end_of_text|>"
+    pattern = r"### Response:\n(.*?)<\|end_of_text\|>"
+    # Search for the pattern in the text
+    match = re.search(pattern, reply[0], re.DOTALL)  # re.DOTALL allows '.' to match newlines
+    reply = match.group(1).strip()  # Extract and remove extra whitespace
+
+    return reply
+
+
+iface=gr.Interface(fn=chunk_it,
+                  inputs="text",
+                  outputs="text",
+                  title="Formatter_Pro",
+                  )
+iface.launch(inline=False)