create app.py

app.py

@@ -0,0 +1,167 @@
+import gradio as gr
+import os
+import time
+import json
+from together import Together
+
+# Set environment variables
+# Note: For Hugging Face Spaces, you'll set these in the Secrets tab
+# os.environ["TOGETHER_API_KEY"] = "your-api-key-here"
+
+# Model options for dropdown
+TOGETHER_MODELS = [
+    "Qwen/Qwen2.5-Coder-32B-Instruct",
+    "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
+    "deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
+    "meta-llama/Llama-3.3-70B-Instruct-Turbo-Free"
+]
+
+# Initialize Together client
+def get_together_client():
+    api_key = os.environ.get("TOGETHER_API_KEY")
+    if not api_key:
+        raise ValueError("TOGETHER_API_KEY not found. Please set it in the environment variables.")
+    return Together(api_key=api_key)
+
+# Function to call LLM
+def call_llm(model, prompt, temperature=0.7, max_tokens=1500):
+    client = get_together_client()
+    
+    # System message for Salesforce expertise
+    system_message = "You are a Salesforce development expert specializing in B2B Commerce migrations, CloudCraze to B2B Lightning Experience conversions, and Apex code optimization. Provide clear, step-by-step guidance and corrected code."
+    
+    start_time = time.time()
+    
+    try:
+        response = client.chat.completions.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": system_message},
+                {"role": "user", "content": prompt}
+            ],
+            temperature=temperature,
+            max_tokens=max_tokens,
+            top_p=0.9
+        )
+        
+        completion_text = response.choices[0].message.content
+        
+        end_time = time.time()
+        duration = end_time - start_time
+        
+        # Add duration to the completion text if needed
+        # completion_text += f"\n\nResponse time: {duration:.2f} seconds"
+        
+        return completion_text
+        
+    except Exception as e:
+        return f"Error calling API: {str(e)}"
+
+# For Apex Trigger correction
+def correct_apex_trigger(model, trigger_code):
+    if not trigger_code.strip():
+        return "Please provide Apex Trigger code to correct."
+    
+    prompt = f"""
+Please analyze and correct the following Apex Trigger code for migration from CloudCraze to B2B Lightning Experience.
+Identify any issues, optimize it according to best practices, and provide the corrected code.
+
+```apex
+{trigger_code}
+```
+
+Please return the corrected code with explanations of what was changed and why.
+"""
+    
+    return call_llm(model, prompt)
+
+# For CloudCraze Object conversion
+def convert_cc_object(model, cc_object_code):
+    if not cc_object_code.strip():
+        return "Please provide CloudCraze Object code to convert."
+    
+    prompt = f"""
+Please convert the following CloudCraze Object code to B2B Lightning Experience format.
+Identify the appropriate B2B LEx system object that corresponds to this CloudCraze object,
+map the fields correctly, and provide the complete definition for the B2B LEx version.
+
+```
+{cc_object_code}
+```
+
+Please return:
+1. The equivalent B2B LEx system object name
+2. Field mapping between CloudCraze and B2B LEx
+3. The complete definition for the B2B LEx implementation
+4. Any additional steps needed for proper migration
+"""
+    
+    return call_llm(model, prompt)
+
+# Gradio Interface
+with gr.Blocks(title="Salesforce B2B Commerce Migration Assistant") as app:
+    gr.Markdown("# Salesforce B2B Commerce Migration Assistant")
+    gr.Markdown("This tool helps with migrating from CloudCraze to B2B Lightning Experience")
+    
+    model_dropdown = gr.Dropdown(
+        choices=TOGETHER_MODELS,
+        value=TOGETHER_MODELS[0],
+        label="Select AI Model"
+    )
+    
+    with gr.Tab("Apex Trigger Correction"):
+        gr.Markdown("### Apex Trigger Correction")
+        gr.Markdown("Paste your Apex Trigger code below to correct issues for B2B LEx compatibility")
+        
+        trigger_input = gr.Textbox(
+            lines=15,
+            placeholder="Paste your Apex Trigger code here...",
+            label="Apex Trigger Code"
+        )
+        
+        trigger_output = gr.Textbox(
+            lines=20,
+            label="Corrected Apex Trigger"
+        )
+        
+        trigger_button = gr.Button("Correct Apex Trigger")
+        trigger_button.click(
+            fn=correct_apex_trigger,
+            inputs=[model_dropdown, trigger_input],
+            outputs=trigger_output
+        )
+    
+    with gr.Tab("CloudCraze Object Conversion"):
+        gr.Markdown("### CloudCraze to B2B LEx Object Conversion")
+        gr.Markdown("Paste your CloudCraze Object code to convert it to B2B Lightning Experience format")
+        
+        object_input = gr.Textbox(
+            lines=15,
+            placeholder="Paste your CloudCraze Object code here...",
+            label="CloudCraze Object Code"
+        )
+        
+        object_output = gr.Textbox(
+            lines=20,
+            label="Converted B2B LEx Object"
+        )
+        
+        object_button = gr.Button("Convert Object")
+        object_button.click(
+            fn=convert_cc_object,
+            inputs=[model_dropdown, object_input],
+            outputs=object_output
+        )
+    
+    gr.Markdown("### About This Tool")
+    gr.Markdown("""
+    This tool uses advanced AI models to assist with Salesforce B2B Commerce migrations.
+    - The Apex Trigger Correction tool helps fix trigger code for B2B Lightning Experience compatibility
+    - The CloudCraze Object Conversion tool maps CC objects to their B2B LEx equivalents
+    
+    **Note**: Always review AI-generated output before implementing in production environments.
+    """)
+
+# Launch the app
+if __name__ == "__main__":
+    app.launch()