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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,28 +1,104 @@ | ||
| from typing import Dict, Any, List | ||
| import json | ||
| from app.knowledge.knowledge_graph import KnowledgeGraph | ||
| from app.entropy.entropy_manager import EntropyManager # Import EntropyManager | ||
| import time | ||
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| class ContextManager: | ||
| def __init__(self): | ||
| def __init__(self, knowledge_graph: KnowledgeGraph, entropy_manager: EntropyManager): | ||
| self.task_history: List[Dict[str, Any]] = [] | ||
| self.working_memory: Dict[str, Any] = {} | ||
| self.knowledge_graph = knowledge_graph | ||
| self.entropy_manager = entropy_manager # Initialize EntropyManager | ||
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| def add_task(self, task: str, action: str, result: str): | ||
| self.task_history.append({ | ||
| async def add_task(self, task: str, action: str, result: str, score: float): | ||
| task_entry = { | ||
| "task": task, | ||
| "action": action, | ||
| "result": result | ||
| }) | ||
| "result": result, | ||
| "score": score | ||
| } | ||
| self.task_history.append(task_entry) | ||
| await self.knowledge_graph.add_task_result(task, result, score) | ||
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| # Update working memory with the latest task | ||
| await self.update_working_memory("latest_task", task_entry) | ||
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| def update_working_memory(self, key: str, value: Any): | ||
| async def update_working_memory(self, key: str, value: Any): | ||
| self.working_memory[key] = value | ||
| await self.knowledge_graph.store_compressed_knowledge(json.dumps(self.working_memory)) | ||
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| def get_recent_context(self, num_tasks: int = 5) -> str: | ||
| async def get_recent_context(self, num_tasks: int = 5) -> str: | ||
| recent_tasks = self.task_history[-num_tasks:] | ||
| context = "Recent tasks:\n" | ||
| for task in recent_tasks: | ||
| context += f"Task: {task['task']}\nAction: {task['action']}\nResult: {task['result']}\n\n" | ||
| context += f"Task: {task['task']}\nAction: {task['action']}\nResult: {task['result']}\nScore: {task['score']}\n\n" | ||
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| relevant_knowledge = await self.knowledge_graph.get_relevant_knowledge(context) | ||
| context += f"Relevant knowledge: {json.dumps(relevant_knowledge, indent=2)}\n\n" | ||
| context += f"Working memory: {json.dumps(self.working_memory, indent=2)}" | ||
| return context | ||
|
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| def get_task_history(self, limit: int = 10) -> List[Dict[str, Any]]: | ||
| return self.task_history[-limit:] | ||
| async def get_task_history(self, limit: int = 10) -> List[Dict[str, Any]]: | ||
| return self.task_history[-limit:] | ||
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| async def get_performance_metrics(self) -> Dict[str, float]: | ||
| return await self.knowledge_graph.get_system_performance() | ||
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| async def add_tool_usage(self, tool_name: str, subtask: Dict[str, Any], result: Dict[str, Any]): | ||
| await self.knowledge_graph.store_tool_usage(tool_name, subtask, result) | ||
| # Update working memory with the latest tool usage | ||
| await self.update_working_memory("latest_tool_usage", { | ||
| "tool_name": tool_name, | ||
| "subtask": subtask, | ||
| "result": result | ||
| }) | ||
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| async def get_recent_tool_usage(self, limit: int = 5) -> List[Dict[str, Any]]: | ||
| return await self.knowledge_graph.get_tool_usage_history(limit=limit) | ||
|
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| async def get_working_memory(self, key: str) -> Any: | ||
| return self.working_memory.get(key) | ||
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| async def store_spatial_memory(self, location: str, context: Dict[str, Any]): | ||
| await self.knowledge_graph.add_or_update_node("SpatialMemory", { | ||
| "location": location, | ||
| "context": json.dumps(context), | ||
| "timestamp": time.time() | ||
| }) | ||
|
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| async def retrieve_spatial_memory(self, location: str) -> Dict[str, Any]: | ||
| result = await self.knowledge_graph.get_node("SpatialMemory", {"location": location}) | ||
| return json.loads(result['context']) if result else {} | ||
|
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| async def compress_long_term_memory(self): | ||
| old_memories = await self.knowledge_graph.get_old_memories(threshold_days=30) | ||
| compressed_memory = await self.entropy_manager.compress_memories(old_memories) # Use EntropyManager for memory compression | ||
| await self.knowledge_graph.store_compressed_memory(compressed_memory) | ||
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| async def update_spatial_memory(self, location: str, context: Dict[str, Any]): | ||
| existing_context = await self.retrieve_spatial_memory(location) | ||
| updated_context = {**existing_context, **context} | ||
| await self.store_spatial_memory(location, updated_context) | ||
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| async def get_memory_summary(self) -> Dict[str, Any]: | ||
| return { | ||
| "working_memory": self.working_memory, | ||
| "recent_tasks": self.task_history[-5:], | ||
| "recent_tool_usage": await self.get_recent_tool_usage(), | ||
| } | ||
|
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| async def create_task_context(self, task: str) -> Dict[str, Any]: | ||
| return {"original_task": task, "steps": []} | ||
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| async def get_contextual_knowledge(self, task: str, task_context: Dict[str, Any]) -> Dict[str, Any]: | ||
| recent_context = await self.get_recent_context() | ||
| relevant_knowledge = await self.knowledge_graph.get_relevant_knowledge(task) | ||
| relevant_episodes = await self.knowledge_graph.recall_relevant_episodes(task_context) | ||
|
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| return { | ||
| "recent_context": recent_context, | ||
| "relevant_knowledge": relevant_knowledge, | ||
| "relevant_episodes": relevant_episodes | ||
| } |
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