Sqlfunc

2025, Mar 13    

Cheat Sheet: Problems, Fixes, Trigger Comparison, and Implementation Details

Problems Encountered and Fixes

Problem Symptoms Root Cause Fix Impact
JSON Parsing Issue (Operation vs. operation) Logs showed “Change missing ‘operation’ field” despite valid data. SQL trigger sent "Operation" (uppercase) while code expected "operation" (lowercase). Updated code to handle both "operation" and "Operation" using change.get("operation") or change.get("Operation"). Enabled message processing by fixing the JSON parsing mismatch.
Infinite Loop / Messages Not Processed Function appeared to wait indefinitely, processing no messages. Early exit due to JSON parsing failure prevented further execution. Ensured proper JSON parsing and added a check for empty changes_list to avoid unnecessary loops. Allowed real-time processing of new messages as they arrive.
Sender Filtering Not Working Processed messages from sender = 'assistant' and others, not just 'user'. In-code filtering (if sender != "user") wasn’t reached due to parsing issue; no database-level filter. Strengthened in-code check with strict sender != "user" and added logging to verify sender values. Ensured only sender = 'user' messages are processed.
FHIR Observation Not Sent No FHIR-related logs; mood analysis and upload never executed. Processing halted early, preventing FHIR logic execution; potential server issues. Fixed parsing to reach FHIR steps; added detailed logging and verified FHIR_SERVER_URL/TOKEN. Enabled mood analysis and FHIR upload for qualifying messages.
FHIR Server Blocking “Sorry, you have been blocked” error (Cloudflare). Incorrect FHIR_SERVER_URL (e.g., http://3.142.231.50:80) or invalid FHIR_AUTH_TOKEN. Recommended using a valid HTTPS URL and testing manually with curl. Resolved once environment variables are corrected.
Page Not Found “Not Found” error (Apache server). FHIR_SERVER_URL pointed to an invalid endpoint. Suggested verifying and updating FHIR_SERVER_URL to a working FHIR server endpoint. Ensured correct server communication.

Differences Between Timer Trigger and SQL Trigger

Aspect Timer Trigger SQL Trigger
Trigger Mechanism Executes on a scheduled interval (e.g., every 5s). Executes on changes to a specified SQL table (e.g., dbo.messages).
Event Source Time-based (cron schedule). Data-based (INSERT, UPDATE, DELETE on table).
Processing Style Polls for new data (e.g., latest unprocessed message). Reacts immediately to each change event.
Use Case Periodic tasks (e.g., checking for updates). Real-time data processing (e.g., mood analysis on new messages).
Parameter func.TimerRequest (contains schedule info). str (JSON string of changes).
Scalability Less reactive; depends on polling frequency. Highly reactive; scales with database change rate.
Complexity Simpler for periodic tasks; manual data fetch needed (e.g., get_latest_user_message). More complex due to handling multiple change events; requires JSON parsing.
  • Key Difference: The timer trigger is proactive and periodic, requiring custom logic to fetch new data (e.g., get_latest_user_message), while the SQL trigger is reactive and event-driven, processing changes as they occur. Your requirement for simultaneous processing favors the SQL trigger.

Necessary Files, Parameters, and Coding Details

Necessary Files

  1. function_app.py:
    • Main file containing the Azure Function definition.
    • Includes imports, environment variables, helper functions (analyze_patient_mood, create_fhir_observation, send_to_fhir), and the trigger function (chat_with_knowbot_sql_trigger).
    • Example Structure: 
      import azure.functions as func
# ... other imports ...
app = func.FunctionApp()
@app.sql_trigger(arg_name="changes", table_name="dbo.messages", connection_string_setting="SqlConnectionString")
def chat_with_knowbot_sql_trigger(changes: str) -> None:
    # Function logic
  2. .env or local.settings.json:
    • Stores environment variables for secure configuration.
    • Example .env: 
      AZURE_OPENAI_ENDPOINT=https://your-openai-endpoint
AZURE_OPENAI_API_KEY=your-api-key
AZURE_API_VERSION=2024-02-01
SERVER=your-server
DATABASE=your-database
USERNAME1=your-username
PASSWORD=your-password
FHIR_SERVER_URL=https://your-fhir-server/fhir
FHIR_AUTH_TOKEN=your-token
    • Example local.settings.json: 
      {
  "IsEncrypted": false,
  "Values": {
    "AzureWebJobsStorage": "UseDevelopmentStorage=true",
    "SqlConnectionString": "DRIVER={ODBC Driver 18 for SQL Server};SERVER=your-server;PORT=1433;DATABASE=your-database;UID=your-username;PWD=your-password;Encrypt=yes;TrustServerCertificate=no;Connection Timeout=30;",
    "FHIR_SERVER_URL": "https://your-fhir-server/fhir",
    "FHIR_AUTH_TOKEN": "your-token"
  }
}
  3. host.json (Optional):
    • Configures function app settings (e.g., logging, extensions).
    • Example: 
      {
  "version": "2.0",
  "logging": {
    "applicationInsights": {
      "samplingSettings": {
        "isEnabled": true
      }
    }
  },
  "extensions": {
    "sql": {
      "connectionStringSetting": "SqlConnectionString"
    }
  }
}
  4. requirements.txt:
    • Lists Python dependencies.
    • Example: 
      azure-functions==1.17.0
openai==1.14.0
requests==2.31.0
pyodbc==5.1.0
python-dotenv==1.0.0

Parameters

  • changes (str):
    • Passed to the SQL trigger function as a JSON string containing a list of change events.
    • Example from Logs: 
      [
  {
    "Operation": 0,
    "Item": {
      "id": "2820eb1c-f63c-4178-8b34-a21ebd8cb9e2",
      "user_id": "bfe7385c-e544-44b2-bb36-8463781be9e2",
      "sender": "user",
      "message": "Am tired",
      "date": "2025-03-13T00:00:00",
      "time": "1:33 PM",
      "created_at": "2025-03-13T13:33:23.389+01:00"
    }
  }
]
    • Contains Operation (e.g., 0 for INSERT) and Item (message details).
  • Environment Variables:
    • Accessed via os.getenv() (e.g., FHIR_SERVER_URL, FHIR_AUTH_TOKEN).
    • Must be set in .env or local.settings.json.

Coding Details

  • SQL Trigger Definition:
    • Use @app.sql_trigger decorator with parameters:
      • arg_name: Name of the parameter (e.g., "changes").
      • table_name: Target SQL table (e.g., "dbo.messages").
      • connection_string_setting: Name of the setting containing the SQL connection string (e.g., "SqlConnectionString").
    • Example: 
      @app.sql_trigger(arg_name="changes", table_name="dbo.messages", connection_string_setting="SqlConnectionString")
def chat_with_knowbot_sql_trigger(changes: str) -> None:
    # Logic here
  • Processing Logic:
    • Parse changes with json.loads(changes).
    • Iterate over changes_list to handle each change.
    • Check operation (e.g., == 0 for INSERT) and item fields.
    • Filter sender == "user" and process mood analysis/FHIR upload.
  • FHIR Upload:
    • Use requests.post with FHIR_SERVER_URL, headers, and JSON payload.
    • Handle exceptions with requests.exceptions.RequestException.

Why It Didn’t Work Initially

  1. "Operation" vs. "operation" Error:
    • Cause: The SQL trigger provided JSON with "Operation" (uppercase), but the code checked for "operation" (lowercase) using change.get("operation"). Since no match was found, operation was None, triggering the if not operation: condition and skipping the message.
    • Evidence: Logs showed "Change missing 'operation' field" despite valid Operation: 0.
    • Fix: Added fallback with change.get("operation") or change.get("Operation") to handle case sensitivity.
  2. Early Exit:
    • Cause: The early exit due to the JSON parsing mismatch prevented the code from reaching the sender filtering, mood analysis, and FHIR upload steps, creating the appearance of an infinite loop as the trigger kept firing without processing.
    • Evidence: No logs beyond "Change missing 'operation' field".
    • Fix: Corrected JSON parsing and ensured the loop completed for each batch.
  3. Environment Misconfiguration:
    • Cause: Potential issues with FHIR_SERVER_URL (e.g., http://3.142.231.50:80) and FHIR_AUTH_TOKEN caused FHIR failures when processing would have occurred.
    • Evidence: Documents showed “Sorry, you have been blocked” and “Page not found”.
    • Fix: Recommended verifying and updating environment variables.

Final Notes

  • Testing: Continue testing with new messages and monitor logs for FHIR success.
  • Optimization: Consider adding a database-level filter (e.g., a view with WHERE sender = 'user') if supported by your SQL trigger setup.
  • Support: Share logs or errors if further issues arise!
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