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/schemas/plan.py

@@ -8,7 +8,7 @@ from pydantic import BaseModel, Field, field_validator, model_validator
 class PlanStep(BaseModel):
     """
     Single step in a plan.
-    
+
     Validation:
     - id and description must be non-empty
     """
@@ -32,7 +32,7 @@ class PlanStep(BaseModel):
 class Plan(BaseModel):
     """
     Plan graph: steps and optional fallback paths.
-    
+
     Validation:
     - No duplicate step IDs
     - All dependency references must be valid step IDs
@@ -48,7 +48,7 @@ class Plan(BaseModel):
     def validate_plan(self) -> "Plan":
         """Validate the entire plan structure."""
         step_ids = {s.id for s in self.steps}
-        
+
         # Check for duplicate step IDs
         if len(step_ids) != len(self.steps):
             seen = set()
@@ -58,7 +58,7 @@ class Plan(BaseModel):
                     duplicates.append(s.id)
                 seen.add(s.id)
             raise ValueError(f"Duplicate step IDs: {duplicates}")
-        
+
         # Check all dependency references are valid
         for step in self.steps:
             invalid_deps = [d for d in step.dependencies if d not in step_ids]
@@ -66,7 +66,7 @@ class Plan(BaseModel):
                 raise ValueError(
                     f"Step '{step.id}' has invalid dependencies: {invalid_deps}"
                 )
-        
+
         # Check all fallback path references are valid
         for i, path in enumerate(self.fallback_paths):
             invalid_refs = [ref for ref in path if ref not in step_ids]
@@ -74,29 +74,29 @@ class Plan(BaseModel):
                 raise ValueError(
                     f"Fallback path {i} has invalid step references: {invalid_refs}"
                 )
-        
+
         # Check for circular dependencies
         cycles = self._find_cycles()
         if cycles:
             raise ValueError(f"Circular dependencies detected: {cycles}")
-        
+
         return self
 
     def _find_cycles(self) -> list[list[str]]:
         """Find circular dependencies in the plan graph using DFS."""
         # Build adjacency list
         graph: dict[str, list[str]] = {s.id: list(s.dependencies) for s in self.steps}
-        
+
         cycles = []
         visited = set()
         rec_stack = set()
         path = []
-        
+
         def dfs(node: str) -> bool:
             visited.add(node)
             rec_stack.add(node)
             path.append(node)
-            
+
             for neighbor in graph.get(node, []):
                 if neighbor not in visited:
                     if dfs(neighbor):
@@ -106,15 +106,15 @@ class Plan(BaseModel):
                     cycle_start = path.index(neighbor)
                     cycles.append(path[cycle_start:] + [neighbor])
                     return True
-            
+
             path.pop()
             rec_stack.remove(node)
             return False
-        
+
         for step_id in graph:
             if step_id not in visited:
                 dfs(step_id)
-        
+
         return cycles
 
     def step_ids(self) -> list[str]:
@@ -142,7 +142,7 @@ class Plan(BaseModel):
     def topological_order(self) -> list[str]:
         """
         Return step IDs in topological order (dependencies first).
-        
+
         Uses Kahn's algorithm.
         """
         # Build in-degree map
@@ -153,11 +153,11 @@ class Plan(BaseModel):
             for dep in step.dependencies:
                 if dep in dependents:
                     dependents[dep].append(step.id)
-        
+
         # Start with nodes that have no dependencies
         queue = [sid for sid, deg in in_degree.items() if deg == 0]
         result = []
-        
+
         while queue:
             node = queue.pop(0)
             result.append(node)
@@ -165,11 +165,11 @@ class Plan(BaseModel):
                 in_degree[dependent] -= 1
                 if in_degree[dependent] == 0:
                     queue.append(dependent)
-        
+
         # Add any remaining nodes (would indicate cycles, but we validate above)
         remaining = [sid for sid in in_degree if sid not in result]
         result.extend(remaining)
-        
+
         return result
 
     def to_dict(self) -> dict[str, Any]: