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/__init__.py

@@ -1,22 +1,22 @@
 """Memory system: working, episodic, reflective, semantic, procedural, trust, consolidation."""
 
-from fusionagi.memory.working import WorkingMemory
-from fusionagi.memory.episodic import EpisodicMemory
-from fusionagi.memory.reflective import ReflectiveMemory
-from fusionagi.memory.semantic import SemanticMemory
-from fusionagi.memory.procedural import ProceduralMemory
-from fusionagi.memory.trust import TrustMemory
 from fusionagi.memory.consolidation import ConsolidationJob
-from fusionagi.memory.service import MemoryService, VectorMemory
-from fusionagi.memory.vector_pgvector import create_vector_memory_pgvector, VectorMemoryPgvector
+from fusionagi.memory.episodic import EpisodicMemory
 from fusionagi.memory.postgres_backend import (
-    MemoryBackend,
     InMemoryBackend,
+    MemoryBackend,
     create_postgres_backend,
 )
-from fusionagi.memory.semantic_graph import SemanticGraphMemory
-from fusionagi.memory.sharding import Shard, shard_context
+from fusionagi.memory.procedural import ProceduralMemory
+from fusionagi.memory.reflective import ReflectiveMemory
 from fusionagi.memory.scratchpad import LatentScratchpad, ThoughtState
+from fusionagi.memory.semantic import SemanticMemory
+from fusionagi.memory.semantic_graph import SemanticGraphMemory
+from fusionagi.memory.service import MemoryService, VectorMemory
+from fusionagi.memory.sharding import Shard, shard_context
+from fusionagi.memory.trust import TrustMemory
+from fusionagi.memory.vector_pgvector import VectorMemoryPgvector, create_vector_memory_pgvector
+from fusionagi.memory.working import WorkingMemory
 
 __all__ = [
     "WorkingMemory",

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)

fusionagi/memory/postgres_backend.py

@@ -100,7 +100,7 @@ class InMemoryBackend(MemoryBackend):
 def create_postgres_backend(connection_string: str) -> MemoryBackend | None:
     """Create Postgres-backed MemoryBackend when psycopg is available."""
     try:
-        import psycopg
+        import psycopg  # noqa: F401
     except ImportError:
         logger.debug("psycopg not installed; use pip install fusionagi[memory]")
         return None
@@ -149,6 +149,7 @@ class PostgresMemoryBackend(MemoryBackend):
         retention_policy: str = "session",
     ) -> None:
         import json
+
         import psycopg
 
         with psycopg.connect(self._conn_str) as conn:
@@ -165,6 +166,7 @@ class PostgresMemoryBackend(MemoryBackend):
 
     def get(self, id: str) -> dict[str, Any] | None:
         import json
+
         import psycopg
 
         with psycopg.connect(self._conn_str) as conn:
@@ -196,6 +198,7 @@ class PostgresMemoryBackend(MemoryBackend):
         limit: int = 100,
     ) -> list[dict[str, Any]]:
         import json
+
         import psycopg
 
         q = "SELECT id, tenant_id, user_id, session_id, type, content, metadata, retention_policy FROM memory_items WHERE tenant_id = %s"

fusionagi/memory/procedural.py

@@ -1,9 +1,8 @@
 """Procedural memory: reusable skills/workflows for AGI."""
 
-from typing import Any
 
-from fusionagi.schemas.skill import Skill
 from fusionagi._logger import logger
+from fusionagi.schemas.skill import Skill
 
 
 class ProceduralMemory:

fusionagi/memory/reflective.py

@@ -16,7 +16,7 @@ class ReflectiveMemory:
 
     def get_lessons(self, limit: int = 50) -> list[dict[str, Any]]:
         """Return recent lessons (copy)."""
-        return [l.copy() for l in self._lessons[-limit:]]
+        return [lesson.copy() for lesson in self._lessons[-limit:]]
 
     def set_heuristic(self, key: str, value: Any) -> None:
         """Set a heuristic (e.g. strategy hint)."""

fusionagi/memory/semantic_graph.py

@@ -3,14 +3,13 @@
 from __future__ import annotations
 
 from collections import defaultdict
-from typing import Any
 
+from fusionagi._logger import logger
 from fusionagi.schemas.atomic import (
     AtomicSemanticUnit,
     AtomicUnitType,
     SemanticRelation,
 )
-from fusionagi._logger import logger
 
 
 class SemanticGraphMemory:
@@ -93,6 +92,46 @@ class SemanticGraphMemory:
         for r in relations:
             self.add_relation(r)
 
+    def semantic_search(
+        self,
+        query: str,
+        top_k: int = 10,
+    ) -> list[tuple[AtomicSemanticUnit, float]]:
+        """Search stored units by semantic similarity using GPU when available.
+
+        Args:
+            query: Query text to search for.
+            top_k: Number of top results to return.
+
+        Returns:
+            List of (unit, similarity_score) tuples sorted by score descending.
+        """
+        try:
+            from fusionagi.memory.gpu_search import semantic_search
+
+            all_units = list(self._units.values())
+            return semantic_search(query, all_units, top_k=top_k)
+        except ImportError:
+            return self._cpu_search(query, top_k)
+
+    def _cpu_search(
+        self,
+        query: str,
+        top_k: int,
+    ) -> list[tuple[AtomicSemanticUnit, float]]:
+        """CPU fallback: word-overlap similarity."""
+        query_words = set(query.lower().split())
+        scored: list[tuple[AtomicSemanticUnit, float]] = []
+        for unit in self._units.values():
+            unit_words = set(unit.content.lower().split())
+            if not unit_words:
+                continue
+            overlap = len(query_words & unit_words)
+            score = overlap / max(len(query_words | unit_words), 1)
+            scored.append((unit, score))
+        scored.sort(key=lambda x: x[1], reverse=True)
+        return scored[:top_k]
+
     def _evict_one(self) -> None:
         """Evict oldest unit (simple FIFO on first key)."""
         if not self._units:

fusionagi/memory/service.py

@@ -2,9 +2,9 @@
 
 from typing import Any
 
-from fusionagi.memory.working import WorkingMemory
 from fusionagi.memory.episodic import EpisodicMemory
 from fusionagi.memory.semantic import SemanticMemory
+from fusionagi.memory.working import WorkingMemory
 
 
 def _scoped_key(tenant_id: str, user_id: str, base: str) -> str:

fusionagi/memory/thought_versioning.py

@@ -7,9 +7,9 @@ import uuid
 from dataclasses import dataclass, field
 from typing import Any
 
+from fusionagi._logger import logger
 from fusionagi.memory.scratchpad import ThoughtState
 from fusionagi.reasoning.tot import ThoughtNode
-from fusionagi._logger import logger
 
 
 @dataclass

fusionagi/memory/trust.py

@@ -45,7 +45,6 @@ class TrustMemory:
             return None
         if self._decay_enabled:
             # Simple decay: reduce confidence by 0.01 per day (placeholder)
-            from datetime import timedelta
             age_days = (_utc_now() - e["created_at"]).total_seconds() / 86400
             e = dict(e)
             e["confidence"] = max(0.0, e["confidence"] - 0.01 * age_days)

fusionagi/memory/vector_pgvector.py

@@ -15,14 +15,14 @@ def create_vector_memory_pgvector(
     Returns None if pgvector/database unavailable.
     """
     try:
-        import pgvector
-        from pgvector.psycopg import register_vector
+        import pgvector  # noqa: F401
+        from pgvector.psycopg import register_vector  # noqa: F401
     except ImportError:
         logger.debug("pgvector not installed; use pip install fusionagi[vector]")
         return None
 
     try:
-        import psycopg
+        import psycopg  # noqa: F401
     except ImportError:
         logger.debug("psycopg not installed; use pip install fusionagi[memory]")
         return None
@@ -39,7 +39,7 @@ class VectorMemoryPgvector:
         table_name: str = "embeddings",
         dimension: int = 1536,
     ) -> None:
-        import pgvector
+        import psycopg
         from pgvector.psycopg import register_vector
 
         self._conn_str = connection_string
@@ -64,6 +64,7 @@ class VectorMemoryPgvector:
 
     def add(self, id: str, embedding: list[float], metadata: dict[str, Any] | None = None) -> None:
         import json
+
         import psycopg
         from pgvector.psycopg import register_vector
 
@@ -82,6 +83,7 @@ class VectorMemoryPgvector:
 
     def search(self, query_embedding: list[float], top_k: int = 10) -> list[dict[str, Any]]:
         import json
+
         import psycopg
         from pgvector.psycopg import register_vector
 

fusionagi/memory/working.py

@@ -9,7 +9,7 @@ Working memory provides short-term storage for active tasks:
 
 from collections import defaultdict
 from datetime import datetime
-from typing import Any, Iterator
+from typing import Any
 
 from fusionagi._logger import logger
 from fusionagi._time import utc_now
@@ -18,7 +18,7 @@ from fusionagi._time import utc_now
 class WorkingMemory:
     """
     Short-term working memory per task/session.
-    
+
     Features:
     - Key-value get/set operations
     - List append with automatic coercion
@@ -30,7 +30,7 @@ class WorkingMemory:
     def __init__(self, max_entries_per_session: int = 1000) -> None:
         """
         Initialize working memory.
-        
+
         Args:
             max_entries_per_session: Maximum entries per session before oldest are removed.
         """
@@ -90,12 +90,12 @@ class WorkingMemory:
     def get_context_summary(self, session_id: str, max_items: int = 10) -> dict[str, Any]:
         """
         Get a summary of working memory for context injection.
-        
+
         Useful for including relevant context in LLM prompts.
         """
         session_data = self._store.get(session_id, {})
         summary = {}
-        
+
         for key, value in list(session_data.items())[:max_items]:
             if isinstance(value, list):
                 # For lists, include count and last few items
@@ -113,10 +113,10 @@ class WorkingMemory:
             else:
                 # For scalars, include the value (truncated if string)
                 if isinstance(value, str) and len(value) > 200:
-                    summary[key] = value[:200] + "..."
+                    summary[key] = value[:200] + "..."  # type: ignore[assignment]
                 else:
-                    summary[key] = value
-        
+                    summary[key] = value  # type: ignore[assignment]
+
         return summary
 
     def get_all(self, session_id: str) -> dict[str, Any]:
@@ -142,7 +142,7 @@ class WorkingMemory:
             len(v) if isinstance(v, (list, dict)) else 1
             for v in session_data.values()
         )
-        
+
         if total_items > self._max_entries:
             logger.warning(
                 "Working memory size limit exceeded",