Update app.py

app.py

@@ -1,3 +1,4 @@
+```python
 import gradio as gr
 import logging
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
@@ -25,6 +26,7 @@ logger = logging.getLogger(__name__)
 # Salesforce connection
 def get_salesforce_connection():
     try:
+        logger.info("Attempting to connect to Salesforce")
         sf = Salesforce(
             username=os.getenv("SF_USERNAME"),
             password=os.getenv("SF_PASSWORD"),
@@ -72,7 +74,7 @@ app = FastAPI()
 @app.post("/generate")
 async def generate_checklist(data: ChecklistInput):
     try:
-        logger.info(f"Generating checklist for project_id_sf: {data.project_id_sf}, record_id: {data.record_id}")
+        logger.info(f"API request to /generate for project_id_sf: {data.project_id_sf}, record_id: {data.record_id}")
         inputs = f"Role: {data.role} Project: {data.project_id} ({data.project_name}) Milestones: {data.milestones}"
         logger.info(f"Input for model: {inputs[:100]}...")
         input_ids = tokenizer(inputs, return_tensors="pt", max_length=128, truncation=True).input_ids
@@ -96,6 +98,7 @@ async def generate_checklist(data: ChecklistInput):
                     'Daily_Checklist__c': '',
                     'Suggested_Tips__c': ''
                 })
+                logger.info(f"Fetched record {data.record_id}: {existing_record}")
                 update_data = {
                     'Daily_Checklist__c': checklist,
                     'Suggested_Tips__c': tips,
@@ -117,7 +120,7 @@ async def generate_checklist(data: ChecklistInput):
             "kpi_flag": kpi_flag
         }
     except Exception as e:
-        logger.error(f"Error generating checklist: {str(e)}")
+        logger.error(f"Error in /generate endpoint: {str(e)}")
         return {"error": str(e)}
 
 # Login and display records
@@ -169,6 +172,7 @@ def gradio_generate_checklist(record_id, role="Supervisor", project_id="Unknown"
             'Daily_Checklist__c': '',
             'Suggested_Tips__c': ''
         })
+        logger.info(f"Fetched record {record_id}: {existing_record}")
         inputs = f"Role: {role} Project: {project_id} ({project_name}) Milestones: {milestones}"
         logger.info(f"Model input: {inputs[:100]}...")
         input_ids = tokenizer(inputs, return_tensors="pt", max_length=128, truncation=True).input_ids
@@ -200,7 +204,9 @@ def gradio_generate_checklist(record_id, role="Supervisor", project_id="Unknown"
 def get_logs():
     try:
         with open('app.log', 'r') as f:
-            return f.read()
+            logs = f.read()
+            logger.info("Retrieved logs from app.log")
+            return logs
     except Exception as e:
         logger.error(f"Error reading logs: {str(e)}")
         return "No logs available."
@@ -226,7 +232,7 @@ with gr.Blocks() as iface:
         role = gr.Textbox(label="Role", value="Supervisor")
         project_id = gr.Textbox(label="Project ID", value="P001")
         project_name = gr.Textbox(label="Project Name", value="Building A")
-        milestones = gr.Textbox(label="Milestones", value="Complete foundation by 5/15")
+        milestones = gr.Textbox(label="Project ID (Salesforce Project__c ID, optional)", value="")
         supervisor_id = gr.Textbox(label="Supervisor ID (Salesforce User ID, optional)", value="")
         project_id_sf = gr.Textbox(label="Project ID (Salesforce Project__c ID, optional)", value="")
         reflection_log = gr.Textbox(label="Reflection Log (optional)", value="")
@@ -253,3 +259,4 @@ if __name__ == "__main__":
     except Exception as e:
         logger.error(f"Failed to launch Gradio interface: {str(e)}")
         raise e
+```