geethareddy commited on
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bfd0001
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1 Parent(s): 6fb3e39

Update app.py

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Files changed (1) hide show
  1. app.py +1 -54
app.py CHANGED
@@ -2,24 +2,6 @@ import gradio as gr
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  import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  import datetime
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- from simple_salesforce import Salesforce
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- import os
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- import uuid
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- import tempfile
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-
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- # Salesforce configuration
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- SF_USERNAME = os.getenv('SF_USERNAME', 'your_salesforce_username')
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- SF_PASSWORD = os.getenv('SF_PASSWORD', 'your_salesforce_password')
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- SF_SECURITY_TOKEN = os.getenv('SF_SECURITY_TOKEN', 'your_salesforce_security_token')
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- SF_DOMAIN = 'login' # Use 'test' for sandbox or 'login' for production
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-
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- # Initialize Salesforce connection
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- sf = Salesforce(
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- username=SF_USERNAME,
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- password=SF_PASSWORD,
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- security_token=SF_SECURITY_TOKEN,
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- domain=SF_DOMAIN
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- )
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  # Initialize model and tokenizer (preloading them for quicker response)
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  model_name = "distilgpt2"
@@ -114,41 +96,6 @@ def generate_outputs(role, project_id, milestones, reflection):
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  quote_start = generated_text.find("Quote:") + len("Quote:")
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  quote = generated_text[quote_start:].strip()
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- # Generate a file with the processed output
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- output_content = f"""Checklist:
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- {checklist}
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-
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- Suggestions:
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- {suggestions}
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-
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- Quote:
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- {quote}
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- """
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- # Create a temporary file
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- temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.txt', mode='w', encoding='utf-8')
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- temp_file.write(output_content)
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- temp_file.close()
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-
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- # Simulate a download URL (in production, upload to a file hosting service like Salesforce Content or AWS S3)
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- file_name = f"supervisor_coaching_{uuid.uuid4()}.txt"
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- download_url = f"/tmp/{file_name}" # Placeholder URL; replace with actual file hosting URL in production
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- os.rename(temp_file.name, os.path.join(tempfile.gettempdir(), file_name))
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-
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- # Save to Salesforce Supervisor_AI_Coaching__c object
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- try:
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- sf.Supervisor_AI_Coaching__c.create({
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- 'Role__c': role,
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- 'Project_ID__c': project_id,
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- 'Milestones__c': milestones,
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- 'Reflection__c': reflection,
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- 'Checklist__c': checklist,
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- 'Suggestions__c': suggestions,
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- 'Quote__c': quote,
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- 'Download_Link__c': download_url
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- })
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- except Exception as e:
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- print(f"Error saving to Salesforce: {str(e)}")
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-
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  # Return structured outputs
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  return checklist, suggestions, quote
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@@ -188,4 +135,4 @@ def create_interface():
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  if __name__ == "__main__":
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  demo = create_interface()
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- demo.launch()
 
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  import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  import datetime
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Initialize model and tokenizer (preloading them for quicker response)
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  model_name = "distilgpt2"
 
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  quote_start = generated_text.find("Quote:") + len("Quote:")
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  quote = generated_text[quote_start:].strip()
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  # Return structured outputs
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  return checklist, suggestions, quote
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  if __name__ == "__main__":
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  demo = create_interface()
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+ demo.launch()