{ "spec_version": "1.4.0-otel", "timestamp": "2026-04-24T00:13:03.355457Z", "trace_id": "4bf92f3577b34da6a3ce929d0e0e4736", "span_id": "00f067aa0ba902b7", "severity_text": "WARN", "severity_number": 13, "event_name": "swarm.agent.lifecycle.deprecated", "resource": { "service.name": "swarm-orchestrator", "service.version": "4.2.0", "deployment.environment": "production", "node.id": "worker-node-aws-us-east-1a-04" }, "attributes": { "agent.id": "DataRetrievalAgent", "agent.previous_version": "v29.x", "agent.target_version": "v30", "deprecation.reason": "Transitioning to v30 architecture.", "deprecation.action_required": true }, "metrics": { "agent.core_logic.function_count": 12, "agent.capabilities.count": 0 }, "artifacts": { "provenance": { "repository": "git+ssh://repo/core/agents/data_retrieval_agent.py", "commit_sha": "a1b2c3d4e5f6g7h8i9j0", "docstring_hash": "sha256:d8c4b12389a..." }, "extracted_capabilities": [], "core_logic_signatures": [ { "name": "__init__", "ast_hash": "sha256:42e03c7542b80e72", "loc": 21, "source": "def __init__(self, config: Dict[str, Any], **kwargs):\n super().__init__(config, **kwargs)\n self.persona = self.config.get('persona', \"Data Retrieval Specialist\")\n self.description = self.config.get(\n 'description', \"Retrieves data from various configured sources based on structured requests.\")\n self.expertise = self.config.get('expertise', [\"data access\", \"file retrieval\", \"knowledge base query\"])\n\n self.risk_ratings_path = self.config.get('risk_ratings_file_path', 'data/risk_rating_mapping.json')\n self.market_baseline_path = self.config.get('market_baseline_file_path', 'data/adam_market_baseline.json')\n \n if 'knowledge_base' in self.config:\n self.knowledge_base = self.config['knowledge_base']\n else:\n try:\n self.knowledge_base = KnowledgeBase()\n except Exception as e:\n logging.error(f\"Failed to initialize KnowledgeBase in DataRetrievalAgent: {e}\")\n self.knowledge_base = None\n\n # Initialize the Live Data Connector\n self.data_fetcher = DataFetcher()" }, { "name": "execute", "ast_hash": "sha256:617b6d644f93ce30", "loc": 45, "source_omitted_for_brevity": true, "note": "In a real telemetry pipeline, large functions can be truncated or omitted entirely in favor of the 'ast_hash' to save network bandwidth and storage costs." }, { "name": "_get_company_financial_data", "ast_hash": "sha256:59bad4d66e389705", "loc": 9, "source": "def _get_company_financial_data(self, company_id: str) -> Optional[Dict[str, Any]]:\n \"\"\"\n Retrieves company financial data. Uses live data if possible, falls back to mock for testing.\n \"\"\"\n if company_id == \"ABC_TEST\":\n return self._get_mock_abc_test_data()\n\n # Use Live Data Fetcher\n return self._fetch_real_company_data(company_id)" }, { "name": "_fetch_real_company_data", "ast_hash": "sha256:89bd5df3405b6b87", "loc": 125, "source_omitted_for_brevity": true, "note": "In a real telemetry pipeline, large functions can be truncated or omitted entirely in favor of the 'ast_hash' to save network bandwidth and storage costs." }, { "name": "_get_mock_abc_test_data", "ast_hash": "sha256:aa3ed0f59dd533d6", "loc": 81, "source_omitted_for_brevity": true, "note": "In a real telemetry pipeline, large functions can be truncated or omitted entirely in favor of the 'ast_hash' to save network bandwidth and storage costs." }, { "name": "get_risk_rating", "ast_hash": "sha256:c5ded82ccbc0623b", "loc": 22, "source": "def get_risk_rating(self, company_id: str) -> Optional[str]:\n logging.info(f\"Attempting to retrieve risk rating for company_id: {company_id} from {self.risk_ratings_path}\")\n try:\n source_config = {'type': 'json', 'path': self.risk_ratings_path}\n data = load_data(source_config, cache=False)\n if data and isinstance(data, dict):\n rating = data.get(company_id)\n if rating is None:\n logging.warning(f\"Risk rating for company_id '{company_id}' not found in {self.risk_ratings_path}.\")\n raise DataNotFoundError(data_identifier=company_id, source=self.risk_ratings_path)\n return rating\n else:\n logging.error(f\"Failed to load risk ratings data from {self.risk_ratings_path}\")\n return None\n except FileReadError as e:\n logging.error(f\"FileReadError while reading risk ratings: {e}\")\n return None\n except DataNotFoundError:\n raise\n except Exception as e:\n logging.exception(f\"Unexpected error in get_risk_rating for {company_id}: {e}\")\n return None" }, { "name": "get_market_data", "ast_hash": "sha256:5b485de49dd9f205", "loc": 14, "source": "def get_market_data(self) -> Optional[Dict[str, Any]]:\n logging.info(f\"Attempting to retrieve market data from {self.market_baseline_path}\")\n try:\n source_config = {'type': 'json', 'path': self.market_baseline_path}\n market_data = load_data(source_config, cache=False)\n if market_data is None:\n logging.error(f\"Failed to load market data from {self.market_baseline_path}.\")\n return market_data\n except FileReadError as e:\n logging.error(f\"FileReadError while reading market data: {e}\")\n return None\n except Exception as e:\n logging.exception(f\"Unexpected error in get_market_data: {e}\")\n return None" }, { "name": "access_knowledge_base", "ast_hash": "sha256:d10571373b2c9760", "loc": 11, "source": "def access_knowledge_base(self, query: str) -> Optional[str]:\n if self.knowledge_base:\n try:\n logging.info(f\"Querying KnowledgeBase with: {query}\")\n return self.knowledge_base.query(query)\n except Exception as e:\n logging.error(f\"Error accessing Knowledge Base: {e}\")\n return None\n else:\n logging.warning(\"KnowledgeBase is not initialized in DataRetrievalAgent.\")\n return None" }, { "name": "access_knowledge_graph", "ast_hash": "sha256:dcc5ed6bfbc77cf1", "loc": 3, "source": "def access_knowledge_graph(self, query: str) -> str:\n logging.warning(\"Knowledge Graph access is not yet implemented. Query: {query}\")\n return \"Knowledge Graph access is not yet implemented.\"" }, { "name": "receive_message", "ast_hash": "sha256:7ed112c4c5ad8722", "loc": 3, "source": "async def receive_message(self, sender_agent: str, message: Dict[str, Any]) -> Optional[Any]:\n logging.info(f\"DataRetrievalAgent received message from {sender_agent}: {message}\")\n return await self.execute(request=message)" }, { "name": "_save_to_cache", "ast_hash": "sha256:bfd3b7c97bb34eb5", "loc": 9, "source": "def _save_to_cache(self, company_id: str, data: Dict[str, Any]):\n try:\n cache_dir = \"data/cache\"\n os.makedirs(cache_dir, exist_ok=True)\n file_path = f\"{cache_dir}/{company_id}_financials.json\"\n with open(file_path, 'w') as f:\n json.dump(data, f, indent=2)\n except Exception as e:\n logging.warning(f\"Failed to cache data for {company_id}: {e}\")" }, { "name": "_load_from_cache", "ast_hash": "sha256:cab5b4ee469c11c0", "loc": 12, "source": "def _load_from_cache(self, company_id: str) -> Optional[Dict[str, Any]]:\n try:\n file_path = f\"data/cache/{company_id}_financials.json\"\n if os.path.exists(file_path):\n logging.info(f\"Loading cached data for {company_id} from {file_path}\")\n with open(file_path, 'r') as f:\n data = json.load(f)\n data['source'] = 'cache'\n return data\n except Exception as e:\n logging.warning(f\"Failed to load cache for {company_id}: {e}\")\n return None" } ] } }