# services/report_data_handler.py import pandas as pd import logging from apis.Bubble_API_Calls import fetch_linkedin_posts_data_from_bubble, bulk_upload_to_bubble from config import ( BUBBLE_REPORT_TABLE_NAME, BUBBLE_OKR_TABLE_NAME, BUBBLE_KEY_RESULTS_TABLE_NAME, BUBBLE_TASKS_TABLE_NAME, BUBBLE_KR_UPDATE_TABLE_NAME, ) import json # For handling JSON data from typing import List, Dict, Any, Optional, Tuple # It's good practice to configure the logger at the application entry point, # but setting a default handler here prevents "No handler found" warnings. logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) def fetch_latest_agentic_analysis(org_urn: str) -> Tuple[Optional[pd.DataFrame], Optional[str]]: """ Fetches all agentic analysis data for a given org_urn from Bubble. Returns the full dataframe and any error message, or None, None. """ logger.info(f"Starting fetch_latest_agentic_analysis for org_urn: {org_urn}") if not org_urn: logger.warning("fetch_latest_agentic_analysis: org_urn is missing.") return None, "org_urn is missing." try: report_data_df, error = fetch_linkedin_posts_data_from_bubble( data_type=BUBBLE_REPORT_TABLE_NAME, org_urn=org_urn ) if error: logger.error(f"Error fetching data from Bubble for org_urn {org_urn}: {error}") return None, str(error) if report_data_df is None or report_data_df.empty: logger.info(f"No existing agentic analysis found in Bubble for org_urn {org_urn}.") return None, None logger.info(f"Successfully fetched {len(report_data_df)} records for org_urn {org_urn}") return report_data_df, None # Return full dataframe and no error except Exception as e: logger.exception(f"An unexpected error occurred in fetch_latest_agentic_analysis for org_urn {org_urn}: {e}") return None, str(e) def save_report_results( org_urn: str, report_markdown: str, quarter: int, year: int, report_type: str, ) -> Optional[str]: """Saves the agentic pipeline results to Bubble. Returns the new record ID or None.""" logger.info(f"Starting save_report_results for org_urn: {org_urn}") if not org_urn: logger.error("Cannot save agentic results: org_urn is missing.") return None try: payload = { "organization_urn": org_urn, "report_text": report_markdown if report_markdown else "N/A", "quarter": quarter, "year": year, "report_type": report_type, } logger.info(f"Attempting to save agentic analysis to Bubble for org_urn: {org_urn}") response = bulk_upload_to_bubble([payload], BUBBLE_REPORT_TABLE_NAME) # Handle API response which could be a list of dicts (for bulk) or a single dict. if response and isinstance(response, list) and len(response) > 0 and isinstance(response[0], dict) and 'id' in response[0]: record_id = response[0]['id'] # Get the ID from the first dictionary in the list logger.info(f"Successfully saved agentic analysis to Bubble. Record ID: {record_id}") return record_id elif response and isinstance(response, dict) and "id" in response: # Handle non-bulk response record_id = response["id"] logger.info(f"Successfully saved agentic analysis to Bubble. Record ID: {record_id}") return record_id else: # Catches None, False, empty lists, or other unexpected formats. logger.error(f"Failed to save agentic analysis to Bubble. Unexpected API Response: {response}") return None except Exception as e: logger.exception(f"An unexpected error occurred in save_report_results for org_urn {org_urn}: {e}") return None # --- Data Saving Functions --- def save_objectives( org_urn: str, report_id: str, objectives_data: List[Dict[str, Any]] ) -> Optional[List[str]]: """ Saves Objective records to Bubble. Returns a list of the newly created Bubble record IDs for the objectives, or None on failure. """ logger.info(f"Starting save_objectives for report_id: {report_id}") if not objectives_data: logger.info("No objectives to save.") return [] try: payloads = [ { "description": obj.get("objective_description"), "timeline": obj.get("objective_timeline"), "owner": obj.get("objective_owner"), "report": report_id, } for obj in objectives_data ] logger.info(f"Attempting to save {payloads} objectives for report_id: {report_id}") response_data = bulk_upload_to_bubble(payloads, BUBBLE_OKR_TABLE_NAME) # Validate response and extract IDs from the list of dictionaries. if not response_data or not isinstance(response_data, list): logger.error(f"Failed to save objectives. API response was not a list: {response_data}") return None try: # Extract the ID from each dictionary in the response list. extracted_ids = [item['id'] for item in response_data] except (TypeError, KeyError): logger.error(f"Failed to parse IDs from API response. Response format invalid: {response_data}", exc_info=True) return None # Check if we extracted the expected number of IDs if len(extracted_ids) != len(payloads): logger.error(f"Failed to save all objectives for report_id: {report_id}. " f"Expected {len(payloads)} IDs, but got {len(extracted_ids)} from response: {response_data}") return None logger.info(f"Successfully saved {len(extracted_ids)} objectives.") return extracted_ids except Exception as e: logger.exception(f"An unexpected error occurred in save_objectives for report_id {report_id}: {e}") return None def save_key_results( org_urn: str, objectives_with_ids: List[Tuple[Dict[str, Any], str]] ) -> Optional[List[Tuple[Dict[str, Any], str]]]: """ Saves Key Result records to Bubble, linking them to their parent objectives. Returns a list of tuples containing the original key result data and its new Bubble ID, or None on failure. """ logger.info(f"Starting save_key_results for {len(objectives_with_ids)} objectives.") key_result_payloads = [] # This list preserves the original KR data in the correct order to match the returned IDs key_results_to_process = [] if not objectives_with_ids: logger.info("No objectives provided to save_key_results.") return [] try: for objective_data, parent_objective_id in objectives_with_ids: # Defensive check to ensure the parent_objective_id is a valid-looking string. if not isinstance(parent_objective_id, str) or not parent_objective_id: logger.error(f"Invalid parent_objective_id found: '{parent_objective_id}'. Skipping KRs for this objective.") continue # Skip this loop iteration for kr in objective_data.get("key_results", []): key_results_to_process.append(kr) key_result_payloads.append({ "okr": parent_objective_id, "description": kr.get("key_result_description"), "target_metric": kr.get("target_metric"), "target_value": kr.get("target_value"), "kr_type": kr.get("key_result_type"), "data_subject": kr.get("data_subject"), }) if not key_result_payloads: logger.info("No key results to save.") return [] logger.info(f"Attempting to save {key_result_payloads} key results for org_urn: {org_urn}") response_data = bulk_upload_to_bubble(key_result_payloads, BUBBLE_KEY_RESULTS_TABLE_NAME) # Validate response and extract IDs. if not response_data or not isinstance(response_data, list): logger.error(f"Failed to save key results. API response was not a list: {response_data}") return None try: extracted_ids = [item['id'] for item in response_data] except (TypeError, KeyError): logger.error(f"Failed to parse IDs from key result API response: {response_data}", exc_info=True) return None if len(extracted_ids) != len(key_result_payloads): logger.error(f"Failed to save all key results for org_urn: {org_urn}. " f"Expected {len(key_result_payloads)} IDs, but got {len(extracted_ids)} from response: {response_data}") return None logger.info(f"Successfully saved {len(extracted_ids)} key results.") return list(zip(key_results_to_process, extracted_ids)) except Exception as e: logger.exception(f"An unexpected error occurred in save_key_results for org_urn {org_urn}: {e}") return None def save_tasks( org_urn: str, key_results_with_ids: List[Tuple[Dict[str, Any], str]] ) -> Optional[List[str]]: """ Saves Task records to Bubble, linking them to their parent key results. Returns a list of the newly created Bubble record IDs for the tasks, or None on failure. """ logger.info(f"Starting save_tasks for {len(key_results_with_ids)} key results.") if not key_results_with_ids: logger.info("No key results provided to save_tasks.") return [] try: task_payloads = [] for key_result_data, parent_key_result_id in key_results_with_ids: for task in key_result_data.get("tasks", []): task_payloads.append({ "key_result": parent_key_result_id, "description": task.get("task_description"), "objective_deliverable": task.get("objective_deliverable"), "category": task.get("task_category"), "priority": task.get("priority"), "priority_justification": task.get("priority_justification"), "effort": task.get("effort"), "timeline": task.get("timeline"), "responsible_party": task.get("responsible_party"), "success_criteria_metrics": task.get("success_criteria_metrics"), "dependencies": task.get("dependencies_prerequisites"), "why": task.get("why_proposed"), }) if not task_payloads: logger.info("No tasks to save.") return [] logger.info(f"Attempting to save {task_payloads} tasks for org_urn: {org_urn}") response_data = bulk_upload_to_bubble(task_payloads, BUBBLE_TASKS_TABLE_NAME) # Validate response and extract IDs. if not response_data or not isinstance(response_data, list): logger.error(f"Failed to save tasks. API response was not a list: {response_data}") return None try: extracted_ids = [item['id'] for item in response_data] except (TypeError, KeyError): logger.error(f"Failed to parse IDs from task API response: {response_data}", exc_info=True) return None if len(extracted_ids) != len(task_payloads): logger.error(f"Failed to save all tasks for org_urn: {org_urn}. " f"Expected {len(task_payloads)} IDs, but got {len(extracted_ids)} from response: {response_data}") return None logger.info(f"Successfully saved {len(extracted_ids)} tasks.") return extracted_ids except Exception as e: logger.exception(f"An unexpected error occurred in save_tasks for org_urn {org_urn}: {e}") return None # --- Orchestrator Function --- def save_actionable_okrs(org_urn: str, actionable_okrs: Dict[str, Any], report_id: str): """ Orchestrates the sequential saving of objectives, key results, and tasks. """ logger.info(f"--- Starting OKR save process for org_urn: {org_urn}, report_id: {report_id} ---") try: objectives_data = actionable_okrs.get("okrs", []) # Defensive check: If data is a string, try to parse it as JSON. if isinstance(objectives_data, str): logger.warning("The 'okrs' data is a string. Attempting to parse as JSON.") try: objectives_data = json.loads(objectives_data) logger.info("Successfully parsed 'okrs' data from JSON string.") except json.JSONDecodeError: logger.error("Failed to parse 'okrs' data. The string is not valid JSON.", exc_info=True) return # Abort if data is malformed if not objectives_data: logger.warning(f"No OKRs found in the input for org_urn: {org_urn}. Aborting save process.") return # Step 1: Save the top-level objectives objective_ids = save_objectives(org_urn, report_id, objectives_data) if objective_ids is None: logger.error("OKR save process aborted due to failure in saving objectives.") return # Combine the original objective data with their new IDs for the next step objectives_with_ids = list(zip(objectives_data, objective_ids)) # Step 2: Save the key results, linking them to the objectives key_results_with_ids = save_key_results(org_urn, objectives_with_ids) if key_results_with_ids is None: logger.error("OKR save process aborted due to failure in saving key results.") return # Step 3: Save the tasks, linking them to the key results task_ids = save_tasks(org_urn, key_results_with_ids) if task_ids is None: logger.error("Task saving failed, but objectives and key results were saved.") # For now, we just log the error and complete. return logger.info(f"--- OKR save process completed successfully for org_urn: {org_urn} ---") except Exception as e: logger.exception(f"An unhandled exception occurred during the save_actionable_okrs orchestration for org_urn {org_urn}: {e}")