Rafay17 commited on
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cea2d18
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1 Parent(s): a3af99d

Update app.py

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Files changed (1) hide show
  1. app.py +6 -36
app.py CHANGED
@@ -3,7 +3,7 @@ from unsloth import FastLanguageModel
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  import torch
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  # Load the model and tokenizer
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- model_name = "Rafay17/Llama3.2_1b_customModle2" # Use your specific model name
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  model = FastLanguageModel.from_pretrained(
@@ -18,38 +18,7 @@ FastLanguageModel.for_inference(model) # Call this immediately after loading th
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  # Function to generate a response
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  def generate_response(input_text):
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  # Prepare the labeled prompt for the model
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- labeled_prompt = (
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- "Please provide the response with the following labels:\n"
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- "Speaker: [SPEAKER]\n"
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- "Text: [TEXT]\n"
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- "Sentiment: [SENTIMENT]\n"
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- "Emotion: [EMOTION]\n"
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- "Intent: [INTENT]\n"
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- "Tone: [TONE]\n"
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- "Confidence Level: [CONFIDENCE]\n"
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- "Frustration Level: [FRUSTRATION]\n"
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- "Response Length: [LENGTH]\n"
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- "Action Required: [ACTION]\n"
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- "Interruption: [INTERRUPTION]\n"
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- "Cooperation Level: [COOPERATION]\n"
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- "Clarity: [CLARITY]\n"
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- "Objective: [OBJECTIVE]\n"
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- "Timeline: [TIMELINE]\n"
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- "Motivation: [MOTIVATION]\n"
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- "Conversation Stage: [STAGE]\n"
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- "Resolution: [RESOLUTION]\n"
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- "Context: [CONTEXT]\n"
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- "Urgency: [URGENCY]\n"
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- "Problem Type: [PROBLEM]\n"
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- "Key Words: [KEYWORDS]\n"
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- "Expected Detail: [DETAIL]\n"
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- "Time Gap: [TIME]\n"
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- "Client Expectation: [EXPECTATION]\n"
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- "Channel: [CHANNEL]\n"
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- "Power Relationship: [POWER]\n\n"
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- f"User Input: {input_text}\n"
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- "Response:"
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- )
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  # Prepare the input for the model
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  inputs = tokenizer(
@@ -75,12 +44,13 @@ def generate_response(input_text):
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  # Function to take user input and generate output
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  def user_interaction():
 
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  while True:
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- user_input = input("Enter conversation details (or type 'exit' to quit): ")
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  if user_input.lower() == 'exit':
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- print("Exiting the program.")
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  break
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- print("Generating response for input:")
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  generate_response(user_input)
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  # Start the user interaction
 
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  import torch
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  # Load the model and tokenizer
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+ model_name = "Rafay17/Llama3.2_1b_customModle2" # Your model name
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  model = FastLanguageModel.from_pretrained(
 
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  # Function to generate a response
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  def generate_response(input_text):
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  # Prepare the labeled prompt for the model
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+ labeled_prompt = f"User Input: {input_text}\nResponse:"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Prepare the input for the model
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  inputs = tokenizer(
 
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  # Function to take user input and generate output
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  def user_interaction():
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+ print("Welcome to the Chatbot! Type 'exit' to quit.")
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  while True:
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+ user_input = input("You: ")
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  if user_input.lower() == 'exit':
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+ print("Exiting the chatbot. Goodbye!")
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  break
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+ print("Chatbot is generating a response...")
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  generate_response(user_input)
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  # Start the user interaction