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https://github.com/Significant-Gravitas/AutoGPT.git
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0b7b4af622
- Created modular execution_data_client to abstract DB and caching - Simple in-memory cache for hot path operations (get_node, get_node_executions) - Non-blocking queue for output and status updates - Removed direct references to DatabaseManager and Redis from manager.py - All execution data access now goes through generic ExecutionDataClient This reduces blocking I/O operations during graph execution by caching frequently accessed data in memory and queuing non-critical updates. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
import logging
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from typing import Any
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from backend.executor.simple_cache import get_cache
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logger = logging.getLogger(__name__)
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class CachedDatabaseClient:
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def __init__(self, original_client):
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self._client = original_client
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self._cache = get_cache()
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def get_node(self, node_id: str) -> Any:
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cached = self._cache.get_node(node_id)
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if cached:
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return cached
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node = self._client.get_node(node_id)
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if node:
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self._cache.cache_node(node_id, node)
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return node
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def get_node_executions(self, graph_exec_id: str, *args, **kwargs) -> Any:
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if not args and not kwargs:
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cached = self._cache.get_node_executions(graph_exec_id)
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if cached:
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return cached
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executions = self._client.get_node_executions(graph_exec_id, *args, **kwargs)
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if not args and not kwargs:
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self._cache.cache_node_executions(graph_exec_id, executions)
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return executions
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def upsert_execution_output(self, *args, **kwargs) -> Any:
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node_exec_id = kwargs.get("node_exec_id") or (args[0] if args else None)
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output = kwargs.get("output") or (args[1] if len(args) > 1 else None)
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if node_exec_id and output:
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self._cache.queue_output_update(node_exec_id, output)
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return {"success": True}
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return self._client.upsert_execution_output(*args, **kwargs)
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def update_node_execution_status(self, *args, **kwargs) -> Any:
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node_exec_id = kwargs.get("node_exec_id") or (args[0] if args else None)
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status = kwargs.get("status") or (args[1] if len(args) > 1 else None)
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if node_exec_id and status:
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self._cache.queue_status_update(node_exec_id, status)
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return {"success": True}
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return self._client.update_node_execution_status(*args, **kwargs)
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def __getattr__(self, name):
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return getattr(self._client, name)
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def wrap_client(original_client):
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return CachedDatabaseClient(original_client)
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