fix: deep GPU integration, fix all ruff/mypy issues, add .dockerignore

- Integrate GPU scoring inline into reasoning/multi_path.py (auto-uses GPU when available)
- Integrate GPU deduplication into multi_agent/consensus_engine.py
- Add semantic_search() method to memory/semantic_graph.py with GPU acceleration
- Integrate GPU training into self_improvement/training.py AutoTrainer
- Fix all 758 ruff lint issues (whitespace, import sorting, unused imports, ambiguous vars, undefined names)
- Fix all 40 mypy type errors across the codebase (no-any-return, union-attr, arg-type, etc.)
- Fix deprecated ruff config keys (select/ignore -> [tool.ruff.lint])
- Add .dockerignore to exclude .venv/, tests/, docs/ from Docker builds
- Add type hints and docstrings to verification/outcome.py
- Fix E402 import ordering in witness_agent.py
- Fix F821 undefined names in vector_pgvector.py and native.py
- Fix E741 ambiguous variable names in reflective.py and recommender.py

All 276 tests pass. 0 ruff errors. 0 mypy errors.

Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>

fusionagi/memory/episodic.py

@@ -8,7 +8,7 @@ Episodic memory stores historical records of agent actions and outcomes:
 """
 
 import time
-from typing import Any, Callable, Iterator
+from typing import Any, Callable
 
 from fusionagi._logger import logger
 from fusionagi._time import utc_now_iso
@@ -17,7 +17,7 @@ from fusionagi._time import utc_now_iso
 class EpisodicMemory:
     """
     Append-only log of task and step outcomes.
-    
+
     Features:
     - Time-stamped event logging
     - Query by task ID
@@ -30,7 +30,7 @@ class EpisodicMemory:
     def __init__(self, max_entries: int = 10000) -> None:
         """
         Initialize episodic memory.
-        
+
         Args:
             max_entries: Maximum entries before oldest are archived/removed.
         """
@@ -48,19 +48,19 @@ class EpisodicMemory:
     ) -> int:
         """
         Append an episodic entry.
-        
+
         Args:
             task_id: Task identifier this event belongs to.
             event: Event data dictionary.
             event_type: Optional event type for categorization (e.g., "step_done", "tool_call").
-        
+
         Returns:
             Index of the appended entry.
         """
         # Enforce size limits
         if len(self._entries) >= self._max_entries:
             self._archive_oldest(self._max_entries // 10)
-        
+
         # Add metadata
         entry = {
             **event,
@@ -68,21 +68,21 @@ class EpisodicMemory:
             "timestamp": event.get("timestamp", time.monotonic()),
             "datetime": event.get("datetime", utc_now_iso()),
         }
-        
+
         if event_type:
             entry["event_type"] = event_type
-        
+
         idx = len(self._entries)
         self._entries.append(entry)
-        
+
         # Index by task
         self._by_task.setdefault(task_id, []).append(idx)
-        
+
         # Index by type if provided
         etype = event_type or event.get("type") or event.get("event_type")
         if etype:
             self._by_type.setdefault(etype, []).append(idx)
-        
+
         return idx
 
     def get_by_task(self, task_id: str, limit: int | None = None) -> list[dict[str, Any]]:
@@ -111,7 +111,7 @@ class EpisodicMemory:
     ) -> list[dict[str, Any]]:
         """
         Return entries within a time range (using monotonic timestamps).
-        
+
         Args:
             start_timestamp: Start of range (inclusive).
             end_timestamp: End of range (inclusive).
@@ -136,7 +136,7 @@ class EpisodicMemory:
     ) -> list[dict[str, Any]]:
         """
         Query entries using a custom filter function.
-        
+
         Args:
             filter_fn: Function that returns True for entries to include.
             limit: Maximum entries to return.
@@ -152,26 +152,26 @@ class EpisodicMemory:
     def get_task_summary(self, task_id: str) -> dict[str, Any]:
         """
         Get a summary of episodes for a task.
-        
+
         Returns statistics like count, first/last timestamps, event types.
         """
         entries = self.get_by_task(task_id)
         if not entries:
             return {"task_id": task_id, "count": 0}
-        
+
         event_types: dict[str, int] = {}
         success_count = 0
         failure_count = 0
-        
+
         for entry in entries:
             etype = entry.get("event_type") or entry.get("type") or "unknown"
             event_types[etype] = event_types.get(etype, 0) + 1
-            
+
             if entry.get("success"):
                 success_count += 1
             elif entry.get("error") or entry.get("success") is False:
                 failure_count += 1
-        
+
         return {
             "task_id": task_id,
             "count": len(entries),
@@ -196,16 +196,16 @@ class EpisodicMemory:
         """Archive/remove oldest entries to enforce size limits."""
         if count <= 0 or count >= len(self._entries):
             return
-        
+
         logger.info(
             "Archiving episodic memory entries",
             extra={"count": count, "total": len(self._entries)},
         )
-        
+
         # Remove oldest entries
         self._entries = self._entries[count:]
         self._archived_count += count
-        
+
         # Rebuild indices (entries shifted)
         self._by_task = {}
         self._by_type = {}
@@ -213,7 +213,7 @@ class EpisodicMemory:
             task_id = entry.get("task_id")
             if task_id:
                 self._by_task.setdefault(task_id, []).append(idx)
-            
+
             etype = entry.get("event_type") or entry.get("type")
             if etype:
                 self._by_type.setdefault(etype, []).append(idx)