diff --git a/atomizer-dashboard/backend/api/main.py b/atomizer-dashboard/backend/api/main.py index 148089b9..d130613b 100644 --- a/atomizer-dashboard/backend/api/main.py +++ b/atomizer-dashboard/backend/api/main.py @@ -13,7 +13,7 @@ import sys # Add parent directory to path to import optimization_engine sys.path.append(str(Path(__file__).parent.parent.parent.parent)) -from api.routes import optimization, claude, terminal, insights, context, files, nx +from api.routes import optimization, claude, terminal, insights, context, files, nx, claude_code, spec from api.websocket import optimization_stream @@ -60,6 +60,9 @@ app.include_router(insights.router, prefix="/api/insights", tags=["insights"]) app.include_router(context.router, prefix="/api/context", tags=["context"]) app.include_router(files.router, prefix="/api/files", tags=["files"]) app.include_router(nx.router, prefix="/api/nx", tags=["nx"]) +app.include_router(claude_code.router, prefix="/api", tags=["claude-code"]) +app.include_router(spec.router, prefix="/api", tags=["spec"]) +app.include_router(spec.validate_router, prefix="/api", tags=["spec"]) @app.get("/") async def root(): diff --git a/atomizer-dashboard/backend/api/routes/claude.py b/atomizer-dashboard/backend/api/routes/claude.py index 0be8b556..ffe7bbc2 100644 --- a/atomizer-dashboard/backend/api/routes/claude.py +++ b/atomizer-dashboard/backend/api/routes/claude.py @@ -187,7 +187,15 @@ async def session_websocket(websocket: WebSocket, session_id: str): continue # Get canvas state from message or use stored state - canvas_state = data.get("canvas_state") or current_canvas_state + msg_canvas = data.get("canvas_state") + canvas_state = msg_canvas if msg_canvas is not None else current_canvas_state + + # Debug logging + if canvas_state: + node_count = len(canvas_state.get("nodes", [])) + print(f"[Claude WS] Sending message with canvas state: {node_count} nodes") + else: + print("[Claude WS] Sending message WITHOUT canvas state") async for chunk in manager.send_message( session_id, @@ -401,6 +409,175 @@ async def websocket_chat(websocket: WebSocket): pass +# ========== POWER MODE: Direct API with Write Tools ========== + +@router.websocket("/sessions/{session_id}/ws/power") +async def power_mode_websocket(websocket: WebSocket, session_id: str): + """ + WebSocket for power mode chat using direct Anthropic API with write tools. + + Unlike the regular /ws endpoint which uses Claude CLI + MCP, + this uses AtomizerClaudeAgent directly with built-in write tools. + This allows immediate modifications without permission prompts. + + Message formats (client -> server): + {"type": "message", "content": "user message"} + {"type": "set_study", "study_id": "study_name"} + {"type": "ping"} + + Message formats (server -> client): + {"type": "text", "content": "..."} + {"type": "tool_call", "tool": "...", "input": {...}} + {"type": "tool_result", "result": "..."} + {"type": "done", "tool_calls": [...]} + {"type": "error", "message": "..."} + {"type": "spec_modified", "changes": [...]} + {"type": "pong"} + """ + await websocket.accept() + + manager = get_session_manager() + session = manager.get_session(session_id) + + if not session: + await websocket.send_json({"type": "error", "message": "Session not found"}) + await websocket.close() + return + + # Import AtomizerClaudeAgent for direct API access + from api.services.claude_agent import AtomizerClaudeAgent + + # Create agent with study context + agent = AtomizerClaudeAgent(study_id=session.study_id) + conversation_history: List[Dict[str, Any]] = [] + + # Load initial spec and set canvas state so Claude sees current canvas + initial_spec = agent.load_current_spec() + if initial_spec: + # Send initial spec to frontend + await websocket.send_json({ + "type": "spec_updated", + "spec": initial_spec, + "reason": "initial_load" + }) + + try: + while True: + data = await websocket.receive_json() + + if data.get("type") == "message": + content = data.get("content", "") + if not content: + continue + + try: + # Use streaming API with tool support for real-time response + last_tool_calls = [] + async for event in agent.chat_stream_with_tools(content, conversation_history): + event_type = event.get("type") + + if event_type == "text": + # Stream text tokens to frontend immediately + await websocket.send_json({ + "type": "text", + "content": event.get("content", ""), + }) + + elif event_type == "tool_call": + # Tool is being called + tool_info = event.get("tool", {}) + await websocket.send_json({ + "type": "tool_call", + "tool": tool_info, + }) + + elif event_type == "tool_result": + # Tool finished executing + tool_name = event.get("tool", "") + await websocket.send_json({ + "type": "tool_result", + "tool": tool_name, + "result": event.get("result", ""), + }) + + # If it was a write tool, send full updated spec + if tool_name in ["add_design_variable", "add_extractor", + "add_objective", "add_constraint", + "update_spec_field", "remove_node", + "create_study"]: + # Load updated spec and update agent's canvas state + updated_spec = agent.load_current_spec() + if updated_spec: + await websocket.send_json({ + "type": "spec_updated", + "tool": tool_name, + "spec": updated_spec, # Full spec for direct canvas update + }) + + elif event_type == "done": + # Streaming complete + last_tool_calls = event.get("tool_calls", []) + await websocket.send_json({ + "type": "done", + "tool_calls": last_tool_calls, + }) + + # Update conversation history for next message + # Note: For proper history tracking, we'd need to store messages properly + # For now, we append the user message and response + conversation_history.append({"role": "user", "content": content}) + conversation_history.append({"role": "assistant", "content": event.get("response", "")}) + + except Exception as e: + import traceback + traceback.print_exc() + await websocket.send_json({ + "type": "error", + "message": str(e), + }) + + elif data.get("type") == "canvas_edit": + # User made a manual edit to the canvas - update Claude's context + spec = data.get("spec") + if spec: + agent.set_canvas_state(spec) + await websocket.send_json({ + "type": "canvas_edit_received", + "acknowledged": True + }) + + elif data.get("type") == "set_study": + study_id = data.get("study_id") + if study_id: + await manager.set_study_context(session_id, study_id) + # Recreate agent with new study context + agent = AtomizerClaudeAgent(study_id=study_id) + conversation_history = [] # Clear history on study change + # Load spec for new study + new_spec = agent.load_current_spec() + await websocket.send_json({ + "type": "context_updated", + "study_id": study_id, + }) + if new_spec: + await websocket.send_json({ + "type": "spec_updated", + "spec": new_spec, + "reason": "study_change" + }) + + elif data.get("type") == "ping": + await websocket.send_json({"type": "pong"}) + + except WebSocketDisconnect: + pass + except Exception as e: + try: + await websocket.send_json({"type": "error", "message": str(e)}) + except: + pass + + @router.get("/suggestions") async def get_chat_suggestions(study_id: Optional[str] = None): """ diff --git a/atomizer-dashboard/backend/api/routes/optimization.py b/atomizer-dashboard/backend/api/routes/optimization.py index 647ed2bf..f4d10568 100644 --- a/atomizer-dashboard/backend/api/routes/optimization.py +++ b/atomizer-dashboard/backend/api/routes/optimization.py @@ -38,16 +38,30 @@ def resolve_study_path(study_id: str) -> Path: """Find study folder by scanning all topic directories. Supports nested folder structure: studies/Topic/study_name/ - Study ID is the short name (e.g., 'm1_mirror_adaptive_V14') + Study ID can be: + - Short name (e.g., 'm1_mirror_adaptive_V14') - scans all topic folders + - Full nested path (e.g., 'M1_Mirror/m1_mirror_cost_reduction_lateral') Returns the full path to the study directory. Raises HTTPException 404 if not found. """ + # Handle nested path format (e.g., "M1_Mirror/m1_mirror_cost_reduction_lateral") + if "/" in study_id: + # Try with forward slashes + nested_path = STUDIES_DIR / study_id + if nested_path.exists() and nested_path.is_dir(): + if _is_valid_study_dir(nested_path): + return nested_path + # Try with backslashes (Windows path) + nested_path = STUDIES_DIR / study_id.replace("/", "\\") + if nested_path.exists() and nested_path.is_dir(): + if _is_valid_study_dir(nested_path): + return nested_path + # First check direct path (backwards compatibility for flat structure) direct_path = STUDIES_DIR / study_id if direct_path.exists() and direct_path.is_dir(): - # Verify it's actually a study (has 1_setup or config) - if (direct_path / "1_setup").exists() or (direct_path / "optimization_config.json").exists(): + if _is_valid_study_dir(direct_path): return direct_path # Scan topic folders for nested structure @@ -55,13 +69,21 @@ def resolve_study_path(study_id: str) -> Path: if topic_dir.is_dir() and not topic_dir.name.startswith('.'): study_dir = topic_dir / study_id if study_dir.exists() and study_dir.is_dir(): - # Verify it's actually a study - if (study_dir / "1_setup").exists() or (study_dir / "optimization_config.json").exists(): + if _is_valid_study_dir(study_dir): return study_dir raise HTTPException(status_code=404, detail=f"Study not found: {study_id}") +def _is_valid_study_dir(study_dir: Path) -> bool: + """Check if a directory is a valid study directory.""" + return ( + (study_dir / "1_setup").exists() or + (study_dir / "optimization_config.json").exists() or + (study_dir / "atomizer_spec.json").exists() + ) + + def get_study_topic(study_dir: Path) -> Optional[str]: """Get the topic folder name for a study, or None if in root.""" # Check if parent is a topic folder (not the root studies dir) @@ -1542,16 +1564,17 @@ async def get_study_image(study_id: str, image_path: str): raise HTTPException(status_code=500, detail=f"Failed to serve image: {str(e)}") -@router.get("/studies/{study_id}/config") +@router.get("/studies/{study_id:path}/config") async def get_study_config(study_id: str): """ - Get the full optimization_config.json for a study + Get the study configuration - reads from atomizer_spec.json (v2.0) first, + falls back to legacy optimization_config.json if not found. Args: study_id: Study identifier Returns: - JSON with the complete configuration + JSON with the complete configuration in a unified format """ try: study_dir = resolve_study_path(study_id) @@ -1559,7 +1582,22 @@ async def get_study_config(study_id: str): if not study_dir.exists(): raise HTTPException(status_code=404, detail=f"Study {study_id} not found") - # Look for config in various locations + # Priority 1: atomizer_spec.json (v2.0 unified format) + spec_file = study_dir / "atomizer_spec.json" + if spec_file.exists(): + with open(spec_file) as f: + spec = json.load(f) + + # Transform AtomizerSpec to the expected config format + config = _transform_spec_to_config(spec, study_id) + return { + "config": config, + "path": str(spec_file), + "study_id": study_id, + "source": "atomizer_spec" + } + + # Priority 2: Legacy optimization_config.json config_file = study_dir / "1_setup" / "optimization_config.json" if not config_file.exists(): config_file = study_dir / "optimization_config.json" @@ -1573,7 +1611,8 @@ async def get_study_config(study_id: str): return { "config": config, "path": str(config_file), - "study_id": study_id + "study_id": study_id, + "source": "legacy_config" } except HTTPException: @@ -1582,6 +1621,118 @@ async def get_study_config(study_id: str): raise HTTPException(status_code=500, detail=f"Failed to read config: {str(e)}") +def _transform_spec_to_config(spec: dict, study_id: str) -> dict: + """Transform AtomizerSpec v2.0 format to legacy config format for backwards compatibility.""" + meta = spec.get("meta", {}) + model = spec.get("model", {}) + optimization = spec.get("optimization", {}) + + # Transform design variables + design_variables = [] + for dv in spec.get("design_variables", []): + bounds = dv.get("bounds", {}) + design_variables.append({ + "name": dv.get("name"), + "expression_name": dv.get("expression_name"), + "type": "float" if dv.get("type") == "continuous" else dv.get("type", "float"), + "min": bounds.get("min"), + "max": bounds.get("max"), + "low": bounds.get("min"), # Alias for compatibility + "high": bounds.get("max"), # Alias for compatibility + "baseline": dv.get("baseline"), + "unit": dv.get("units"), + "units": dv.get("units"), + "enabled": dv.get("enabled", True) + }) + + # Transform objectives + objectives = [] + for obj in spec.get("objectives", []): + source = obj.get("source", {}) + objectives.append({ + "name": obj.get("name"), + "direction": obj.get("direction", "minimize"), + "weight": obj.get("weight", 1.0), + "target": obj.get("target"), + "unit": obj.get("units"), + "units": obj.get("units"), + "extractor_id": source.get("extractor_id"), + "output_key": source.get("output_key") + }) + + # Transform constraints + constraints = [] + for con in spec.get("constraints", []): + constraints.append({ + "name": con.get("name"), + "type": _operator_to_type(con.get("operator", "<=")), + "operator": con.get("operator"), + "max_value": con.get("threshold") if con.get("operator") in ["<=", "<"] else None, + "min_value": con.get("threshold") if con.get("operator") in [">=", ">"] else None, + "bound": con.get("threshold"), + "unit": con.get("units"), + "units": con.get("units") + }) + + # Transform extractors + extractors = [] + for ext in spec.get("extractors", []): + extractors.append({ + "name": ext.get("name"), + "type": ext.get("type"), + "builtin": ext.get("builtin", True), + "config": ext.get("config", {}), + "outputs": ext.get("outputs", []) + }) + + # Get algorithm info + algorithm = optimization.get("algorithm", {}) + budget = optimization.get("budget", {}) + + # Build the config in legacy format + config = { + "study_name": meta.get("study_name", study_id), + "description": meta.get("description", ""), + "version": meta.get("version", "2.0"), + "design_variables": design_variables, + "objectives": objectives, + "constraints": constraints, + "extractors": extractors, + "optimization": { + "algorithm": algorithm.get("type", "TPE"), + "n_trials": budget.get("max_trials", 100), + "max_time_hours": budget.get("max_time_hours"), + "convergence_patience": budget.get("convergence_patience") + }, + "optimization_settings": { + "sampler": algorithm.get("type", "TPE"), + "n_trials": budget.get("max_trials", 100) + }, + "algorithm": { + "name": "Optuna", + "sampler": algorithm.get("type", "TPE"), + "n_trials": budget.get("max_trials", 100) + }, + "model": model, + "sim_file": model.get("sim", {}).get("path") if isinstance(model.get("sim"), dict) else None + } + + return config + + +def _operator_to_type(operator: str) -> str: + """Convert constraint operator to legacy type string.""" + mapping = { + "<=": "le", + "<": "le", + ">=": "ge", + ">": "ge", + "==": "eq", + "=": "eq" + } + return mapping.get(operator, "le") + + # ============================================================================ # Process Control Endpoints # ============================================================================ @@ -2851,7 +3002,162 @@ async def get_study_runs(study_id: str): class UpdateConfigRequest(BaseModel): - config: dict + config: Optional[dict] = None + intent: Optional[dict] = None + + +def intent_to_config(intent: dict, existing_config: Optional[dict] = None) -> dict: + """ + Convert canvas intent format to optimization_config.json format. + + Preserves existing config fields that aren't in the intent. + """ + # Start with existing config or empty + config = existing_config.copy() if existing_config else {} + + # Metadata + if intent.get('model', {}).get('path'): + model_path = Path(intent['model']['path']).name + if 'simulation' not in config: + config['simulation'] = {} + config['simulation']['model_file'] = model_path + # Try to infer other files from model name + base_name = model_path.replace('.prt', '') + if not config['simulation'].get('fem_file'): + config['simulation']['fem_file'] = f"{base_name}_fem1.fem" + if not config['simulation'].get('sim_file'): + config['simulation']['sim_file'] = f"{base_name}_sim1.sim" + + # Solver + if intent.get('solver', {}).get('type'): + solver_type = intent['solver']['type'] + if 'simulation' not in config: + config['simulation'] = {} + config['simulation']['solver'] = 'nastran' + # Map SOL types to analysis_types + sol_to_analysis = { + 'SOL101': ['static'], + 'SOL103': ['modal'], + 'SOL105': ['buckling'], + 'SOL106': ['nonlinear'], + 'SOL111': ['modal', 'frequency_response'], + 'SOL112': ['modal', 'transient'], + } + config['simulation']['analysis_types'] = sol_to_analysis.get(solver_type, ['static']) + + # Design Variables + if intent.get('design_variables'): + config['design_variables'] = [] + for dv in intent['design_variables']: + config['design_variables'].append({ + 'parameter': dv.get('name', dv.get('expression_name', '')), + 'bounds': [dv.get('min', 0), dv.get('max', 100)], + 'description': dv.get('description', f"Design variable: {dv.get('name', '')}"), + }) + + # Extractors → used for objectives/constraints extraction + extractor_map = {} + if intent.get('extractors'): + for ext in intent['extractors']: + ext_id = ext.get('id', '') + ext_name = ext.get('name', '') + extractor_map[ext_name] = ext + + # Objectives + if intent.get('objectives'): + config['objectives'] = [] + for obj in intent['objectives']: + obj_config = { + 'name': obj.get('name', 'objective'), + 'goal': obj.get('direction', 'minimize'), + 'weight': obj.get('weight', 1.0), + 'description': obj.get('description', f"Objective: {obj.get('name', '')}"), + } + # Add extraction config if extractor referenced + extractor_name = obj.get('extractor') + if extractor_name and extractor_name in extractor_map: + ext = extractor_map[extractor_name] + ext_config = ext.get('config', {}) + obj_config['extraction'] = { + 'action': _extractor_id_to_action(ext.get('id', '')), + 'domain': 'result_extraction', + 'params': ext_config, + } + config['objectives'].append(obj_config) + + # Constraints + if intent.get('constraints'): + config['constraints'] = [] + for con in intent['constraints']: + op = con.get('operator', '<=') + con_type = 'less_than' if '<' in op else 'greater_than' if '>' in op else 'equal_to' + con_config = { + 'name': con.get('name', 'constraint'), + 'type': con_type, + 'threshold': con.get('value', 0), + 'description': con.get('description', f"Constraint: {con.get('name', '')}"), + } + # Add extraction config if extractor referenced + extractor_name = con.get('extractor') + if extractor_name and extractor_name in extractor_map: + ext = extractor_map[extractor_name] + ext_config = ext.get('config', {}) + con_config['extraction'] = { + 'action': _extractor_id_to_action(ext.get('id', '')), + 'domain': 'result_extraction', + 'params': ext_config, + } + config['constraints'].append(con_config) + + # Optimization settings + if intent.get('optimization'): + opt = intent['optimization'] + if 'optimization_settings' not in config: + config['optimization_settings'] = {} + if opt.get('max_trials'): + config['optimization_settings']['n_trials'] = opt['max_trials'] + if opt.get('method'): + # Map method names to Optuna sampler names + method_map = { + 'TPE': 'TPESampler', + 'CMA-ES': 'CmaEsSampler', + 'NSGA-II': 'NSGAIISampler', + 'RandomSearch': 'RandomSampler', + 'GP-BO': 'GPSampler', + } + config['optimization_settings']['sampler'] = method_map.get(opt['method'], opt['method']) + + # Surrogate + if intent.get('surrogate', {}).get('enabled'): + config['surrogate'] = { + 'type': intent['surrogate'].get('type', 'MLP'), + 'min_trials': intent['surrogate'].get('min_trials', 20), + } + + return config + + +def _extractor_id_to_action(ext_id: str) -> str: + """Map extractor IDs (E1, E2, etc.) to extraction action names.""" + action_map = { + 'E1': 'extract_displacement', + 'E2': 'extract_frequency', + 'E3': 'extract_stress', + 'E4': 'extract_mass', + 'E5': 'extract_mass', + 'E8': 'extract_zernike', + 'E9': 'extract_zernike', + 'E10': 'extract_zernike', + 'displacement': 'extract_displacement', + 'frequency': 'extract_frequency', + 'stress': 'extract_stress', + 'mass': 'extract_mass', + 'mass_bdf': 'extract_mass', + 'mass_cad': 'extract_mass', + 'zernike': 'extract_zernike', + 'zernike_opd': 'extract_zernike', + } + return action_map.get(ext_id, 'extract_displacement') @router.put("/studies/{study_id}/config") @@ -2859,9 +3165,13 @@ async def update_study_config(study_id: str, request: UpdateConfigRequest): """ Update the optimization_config.json for a study + Accepts either: + - {"config": {...}} - Direct config object (overwrites) + - {"intent": {...}} - Canvas intent (converted and merged with existing) + Args: study_id: Study identifier - request: New configuration data + request: New configuration data (config or intent) Returns: JSON with success status @@ -2891,9 +3201,24 @@ async def update_study_config(study_id: str, request: UpdateConfigRequest): backup_file = config_file.with_suffix('.json.backup') shutil.copy(config_file, backup_file) + # Determine which format was provided + if request.config is not None: + # Direct config update + new_config = request.config + elif request.intent is not None: + # Convert intent to config, merging with existing + with open(config_file, 'r') as f: + existing_config = json.load(f) + new_config = intent_to_config(request.intent, existing_config) + else: + raise HTTPException( + status_code=400, + detail="Request must include either 'config' or 'intent' field" + ) + # Write new config with open(config_file, 'w') as f: - json.dump(request.config, f, indent=2) + json.dump(new_config, f, indent=2) return { "success": True, diff --git a/atomizer-dashboard/backend/api/routes/spec.py b/atomizer-dashboard/backend/api/routes/spec.py new file mode 100644 index 00000000..47a5307b --- /dev/null +++ b/atomizer-dashboard/backend/api/routes/spec.py @@ -0,0 +1,646 @@ +""" +AtomizerSpec v2.0 API Endpoints + +REST API for managing AtomizerSpec configurations. +All spec modifications flow through these endpoints. + +Endpoints: +- GET /studies/{study_id}/spec - Get full spec +- PUT /studies/{study_id}/spec - Replace entire spec +- PATCH /studies/{study_id}/spec - Partial update +- POST /studies/{study_id}/spec/validate - Validate spec +- POST /studies/{study_id}/spec/nodes - Add node +- PATCH /studies/{study_id}/spec/nodes/{node_id} - Update node +- DELETE /studies/{study_id}/spec/nodes/{node_id} - Delete node +- POST /studies/{study_id}/spec/custom-functions - Add custom extractor +- WebSocket /studies/{study_id}/spec/sync - Real-time sync +""" + +from fastapi import APIRouter, HTTPException, WebSocket, WebSocketDisconnect, Query +from fastapi.responses import JSONResponse +from pydantic import BaseModel, Field +from pathlib import Path +from typing import Any, Dict, List, Optional, Union +import json +import sys +import asyncio + +# Add project root to path +sys.path.append(str(Path(__file__).parent.parent.parent.parent.parent)) + +from api.services.spec_manager import ( + SpecManager, + SpecManagerError, + SpecNotFoundError, + SpecConflictError, + get_spec_manager, +) +from optimization_engine.config.spec_models import ( + AtomizerSpec, + ValidationReport, +) +from optimization_engine.config.spec_validator import SpecValidationError + +router = APIRouter(prefix="/studies/{study_id:path}/spec", tags=["spec"]) + +# Base studies directory +STUDIES_DIR = Path(__file__).parent.parent.parent.parent.parent / "studies" + + +# ============================================================================ +# Request/Response Models +# ============================================================================ + +class SpecPatchRequest(BaseModel): + """Request for patching a spec field.""" + path: str = Field(..., description="JSONPath to the field (e.g., 'objectives[0].weight')") + value: Any = Field(..., description="New value") + modified_by: str = Field(default="api", description="Who is making the change") + + +class NodeAddRequest(BaseModel): + """Request for adding a node.""" + type: str = Field(..., description="Node type: designVar, extractor, objective, constraint") + data: Dict[str, Any] = Field(..., description="Node data") + modified_by: str = Field(default="canvas", description="Who is making the change") + + +class NodeUpdateRequest(BaseModel): + """Request for updating a node.""" + updates: Dict[str, Any] = Field(..., description="Fields to update") + modified_by: str = Field(default="canvas", description="Who is making the change") + + +class CustomFunctionRequest(BaseModel): + """Request for adding a custom extractor function.""" + name: str = Field(..., description="Function name") + code: str = Field(..., description="Python source code") + outputs: List[str] = Field(..., description="Output names") + description: Optional[str] = Field(default=None, description="Human-readable description") + modified_by: str = Field(default="claude", description="Who is making the change") + + +class ExtractorValidationRequest(BaseModel): + """Request for validating custom extractor code.""" + function_name: str = Field(default="extract", description="Expected function name") + source: str = Field(..., description="Python source code to validate") + + +class SpecUpdateResponse(BaseModel): + """Response for spec modification operations.""" + success: bool + hash: str + modified: str + modified_by: str + + +class NodeAddResponse(BaseModel): + """Response for node add operation.""" + success: bool + node_id: str + message: str + + +class ValidationResponse(BaseModel): + """Response for validation endpoint.""" + valid: bool + errors: List[Dict[str, Any]] + warnings: List[Dict[str, Any]] + summary: Dict[str, int] + + +# ============================================================================ +# Helper Functions +# ============================================================================ + +def resolve_study_path(study_id: str) -> Path: + """Find study folder by scanning all topic directories. + + Supports both formats: + - "study_name" - Will scan topic folders to find it + - "Topic/study_name" - Direct nested path (e.g., "M1_Mirror/m1_mirror_v1") + """ + # Handle nested paths (e.g., "M1_Mirror/m1_mirror_cost_reduction_lateral") + if "/" in study_id: + nested_path = STUDIES_DIR / study_id.replace("/", "\\") # Handle Windows paths + if nested_path.exists() and nested_path.is_dir(): + return nested_path + # Also try with forward slashes (Path handles both) + nested_path = STUDIES_DIR / study_id + if nested_path.exists() and nested_path.is_dir(): + return nested_path + + # Direct path (flat structure) + direct_path = STUDIES_DIR / study_id + if direct_path.exists() and direct_path.is_dir(): + return direct_path + + # Scan topic folders (nested structure) + for topic_dir in STUDIES_DIR.iterdir(): + if topic_dir.is_dir() and not topic_dir.name.startswith('.'): + study_dir = topic_dir / study_id + if study_dir.exists() and study_dir.is_dir(): + return study_dir + + raise HTTPException(status_code=404, detail=f"Study not found: {study_id}") + + +def get_manager(study_id: str) -> SpecManager: + """Get SpecManager for a study.""" + study_path = resolve_study_path(study_id) + return get_spec_manager(study_path) + + +# ============================================================================ +# REST Endpoints +# ============================================================================ + +@router.get("", response_model=None) +async def get_spec(study_id: str): + """ + Get the full AtomizerSpec for a study. + + Returns the complete spec JSON with all design variables, extractors, + objectives, constraints, and canvas state. + """ + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException( + status_code=404, + detail=f"No AtomizerSpec found for study '{study_id}'. Use migration or create new spec." + ) + + try: + spec = manager.load() + return spec.model_dump(mode='json') + except SpecValidationError as e: + # Return spec even if invalid, but include validation info + raw = manager.load_raw() + return JSONResponse( + status_code=200, + content={ + **raw, + "_validation_error": str(e) + } + ) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.get("/raw") +async def get_spec_raw(study_id: str): + """ + Get the raw spec JSON without validation. + + Useful for debugging or when spec is invalid. + """ + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + return manager.load_raw() + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.get("/hash") +async def get_spec_hash(study_id: str): + """Get the current spec hash for conflict detection.""" + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + return {"hash": manager.get_hash()} + + +@router.put("", response_model=SpecUpdateResponse) +async def replace_spec( + study_id: str, + spec: Dict[str, Any], + modified_by: str = Query(default="api"), + expected_hash: Optional[str] = Query(default=None) +): + """ + Replace the entire spec. + + Validates the new spec before saving. Optionally check for conflicts + using expected_hash parameter. + """ + manager = get_manager(study_id) + + try: + new_hash = manager.save(spec, modified_by=modified_by, expected_hash=expected_hash) + reloaded = manager.load() + return SpecUpdateResponse( + success=True, + hash=new_hash, + modified=reloaded.meta.modified or "", + modified_by=modified_by + ) + except SpecConflictError as e: + raise HTTPException( + status_code=409, + detail={ + "message": str(e), + "current_hash": e.current_hash + } + ) + except SpecValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.patch("", response_model=SpecUpdateResponse) +async def patch_spec(study_id: str, request: SpecPatchRequest): + """ + Partial update to spec using JSONPath. + + Example paths: + - "objectives[0].weight" - Update objective weight + - "design_variables[1].bounds.max" - Update DV bound + - "meta.description" - Update description + """ + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + spec = manager.patch(request.path, request.value, modified_by=request.modified_by) + return SpecUpdateResponse( + success=True, + hash=manager.get_hash(), + modified=spec.meta.modified or "", + modified_by=request.modified_by + ) + except SpecValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + except ValueError as e: + raise HTTPException(status_code=400, detail=str(e)) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.post("/validate", response_model=ValidationResponse) +async def validate_spec(study_id: str): + """ + Validate the spec and return detailed report. + + Returns errors, warnings, and summary of the spec contents. + """ + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + report = manager.validate_and_report() + return ValidationResponse( + valid=report.valid, + errors=[e.model_dump() for e in report.errors], + warnings=[w.model_dump() for w in report.warnings], + summary=report.summary.model_dump() + ) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +# ============================================================================ +# Node CRUD Endpoints +# ============================================================================ + +@router.post("/nodes", response_model=NodeAddResponse) +async def add_node(study_id: str, request: NodeAddRequest): + """ + Add a new node to the spec. + + Supported types: designVar, extractor, objective, constraint + """ + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + valid_types = ["designVar", "extractor", "objective", "constraint"] + if request.type not in valid_types: + raise HTTPException( + status_code=400, + detail=f"Invalid node type '{request.type}'. Valid: {valid_types}" + ) + + try: + node_id = manager.add_node(request.type, request.data, modified_by=request.modified_by) + return NodeAddResponse( + success=True, + node_id=node_id, + message=f"Added {request.type} node: {node_id}" + ) + except SpecValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.patch("/nodes/{node_id}") +async def update_node(study_id: str, node_id: str, request: NodeUpdateRequest): + """Update an existing node's properties.""" + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + manager.update_node(node_id, request.updates, modified_by=request.modified_by) + return {"success": True, "message": f"Updated node {node_id}"} + except SpecManagerError as e: + raise HTTPException(status_code=404, detail=str(e)) + except SpecValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.delete("/nodes/{node_id}") +async def delete_node( + study_id: str, + node_id: str, + modified_by: str = Query(default="canvas") +): + """ + Delete a node and all edges referencing it. + + Use with caution - this will also remove any objectives or constraints + that reference a deleted extractor. + """ + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + manager.remove_node(node_id, modified_by=modified_by) + return {"success": True, "message": f"Removed node {node_id}"} + except SpecManagerError as e: + raise HTTPException(status_code=404, detail=str(e)) + except SpecValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +# ============================================================================ +# Custom Function Endpoint +# ============================================================================ + +@router.post("/custom-functions", response_model=NodeAddResponse) +async def add_custom_function(study_id: str, request: CustomFunctionRequest): + """ + Add a custom Python function as an extractor. + + The function will be available in the optimization workflow. + Claude can use this to add new physics extraction logic. + """ + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + extractor_id = manager.add_custom_function( + name=request.name, + code=request.code, + outputs=request.outputs, + description=request.description, + modified_by=request.modified_by + ) + return NodeAddResponse( + success=True, + node_id=extractor_id, + message=f"Added custom extractor: {request.name}" + ) + except SpecValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +# Separate router for non-study-specific endpoints +validate_router = APIRouter(prefix="/spec", tags=["spec"]) + + +@validate_router.post("/validate-extractor") +async def validate_custom_extractor(request: ExtractorValidationRequest): + """ + Validate custom extractor Python code. + + Checks syntax, security patterns, and function signature. + Does not require a study - can be used before adding to spec. + """ + try: + from optimization_engine.extractors.custom_extractor_loader import ( + validate_extractor_code, + ExtractorSecurityError, + ) + + try: + is_valid, errors = validate_extractor_code(request.source, request.function_name) + return { + "valid": is_valid, + "errors": errors + } + except ExtractorSecurityError as e: + return { + "valid": False, + "errors": [str(e)] + } + + except ImportError as e: + raise HTTPException( + status_code=500, + detail=f"Custom extractor loader not available: {e}" + ) + + +# ============================================================================ +# Edge Endpoints +# ============================================================================ + +@router.post("/edges") +async def add_edge( + study_id: str, + source: str = Query(..., description="Source node ID"), + target: str = Query(..., description="Target node ID"), + modified_by: str = Query(default="canvas") +): + """Add a canvas edge between two nodes.""" + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + manager.add_edge(source, target, modified_by=modified_by) + return {"success": True, "message": f"Added edge {source} -> {target}"} + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.delete("/edges") +async def delete_edge( + study_id: str, + source: str = Query(..., description="Source node ID"), + target: str = Query(..., description="Target node ID"), + modified_by: str = Query(default="canvas") +): + """Remove a canvas edge.""" + manager = get_manager(study_id) + + if not manager.exists(): + raise HTTPException(status_code=404, detail=f"No spec found for study '{study_id}'") + + try: + manager.remove_edge(source, target, modified_by=modified_by) + return {"success": True, "message": f"Removed edge {source} -> {target}"} + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +# ============================================================================ +# WebSocket Sync Endpoint +# ============================================================================ + +class WebSocketSubscriber: + """WebSocket subscriber adapter.""" + + def __init__(self, websocket: WebSocket): + self.websocket = websocket + + async def send_json(self, data: Dict[str, Any]) -> None: + await self.websocket.send_json(data) + + +@router.websocket("/sync") +async def websocket_sync(websocket: WebSocket, study_id: str): + """ + WebSocket endpoint for real-time spec sync. + + Clients receive notifications when spec changes: + - spec_updated: Spec was modified + - node_added: New node added + - node_removed: Node removed + - validation_error: Validation failed + """ + await websocket.accept() + + manager = get_manager(study_id) + subscriber = WebSocketSubscriber(websocket) + + # Subscribe to updates + manager.subscribe(subscriber) + + try: + # Send initial connection ack + await websocket.send_json({ + "type": "connection_ack", + "study_id": study_id, + "hash": manager.get_hash() if manager.exists() else None, + "message": "Connected to spec sync" + }) + + # Keep connection alive and handle client messages + while True: + try: + data = await asyncio.wait_for( + websocket.receive_json(), + timeout=30.0 # Heartbeat interval + ) + + # Handle client messages + msg_type = data.get("type") + + if msg_type == "ping": + await websocket.send_json({"type": "pong"}) + + elif msg_type == "patch_node": + # Client requests node update + try: + manager.update_node( + data["node_id"], + data.get("data", {}), + modified_by=data.get("modified_by", "canvas") + ) + except Exception as e: + await websocket.send_json({ + "type": "error", + "message": str(e) + }) + + elif msg_type == "update_position": + # Client updates node position + try: + manager.update_node_position( + data["node_id"], + data["position"], + modified_by=data.get("modified_by", "canvas") + ) + except Exception as e: + await websocket.send_json({ + "type": "error", + "message": str(e) + }) + + except asyncio.TimeoutError: + # Send heartbeat + await websocket.send_json({"type": "heartbeat"}) + + except WebSocketDisconnect: + pass + finally: + manager.unsubscribe(subscriber) + + +# ============================================================================ +# Create/Initialize Spec +# ============================================================================ + +@router.post("/create") +async def create_spec( + study_id: str, + spec: Dict[str, Any], + modified_by: str = Query(default="api") +): + """ + Create a new spec for a study. + + Use this when migrating from old config or creating a new study. + Will fail if spec already exists (use PUT to replace). + """ + manager = get_manager(study_id) + + if manager.exists(): + raise HTTPException( + status_code=409, + detail=f"Spec already exists for '{study_id}'. Use PUT to replace." + ) + + try: + # Ensure meta fields are set + if "meta" not in spec: + spec["meta"] = {} + spec["meta"]["created_by"] = modified_by + + new_hash = manager.save(spec, modified_by=modified_by) + return { + "success": True, + "hash": new_hash, + "message": f"Created spec for {study_id}" + } + except SpecValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) diff --git a/atomizer-dashboard/backend/api/services/__init__.py b/atomizer-dashboard/backend/api/services/__init__.py index 9cc9c25c..ef581348 100644 --- a/atomizer-dashboard/backend/api/services/__init__.py +++ b/atomizer-dashboard/backend/api/services/__init__.py @@ -3,5 +3,13 @@ Atomizer Dashboard Services """ from .claude_agent import AtomizerClaudeAgent +from .spec_manager import SpecManager, SpecManagerError, SpecNotFoundError, SpecConflictError, get_spec_manager -__all__ = ['AtomizerClaudeAgent'] +__all__ = [ + 'AtomizerClaudeAgent', + 'SpecManager', + 'SpecManagerError', + 'SpecNotFoundError', + 'SpecConflictError', + 'get_spec_manager', +] diff --git a/atomizer-dashboard/backend/api/services/claude_agent.py b/atomizer-dashboard/backend/api/services/claude_agent.py index b4135679..ae61d67a 100644 --- a/atomizer-dashboard/backend/api/services/claude_agent.py +++ b/atomizer-dashboard/backend/api/services/claude_agent.py @@ -29,9 +29,108 @@ class AtomizerClaudeAgent: self.client = anthropic.Anthropic() self.study_id = study_id self.study_dir = STUDIES_DIR / study_id if study_id else None + self.canvas_state: Optional[Dict[str, Any]] = None # Current canvas/spec state + self.interview = None # Interview engine instance (if active) self.tools = self._define_tools() self.system_prompt = self._build_system_prompt() + def set_canvas_state(self, spec: Dict[str, Any]) -> None: + """Update the current canvas state for context. + + This should be called: + 1. When a study is loaded + 2. When the frontend sends a canvas_edit message + 3. After any spec modification + """ + self.canvas_state = spec + # Rebuild system prompt with new canvas state + self.system_prompt = self._build_system_prompt() + + def load_current_spec(self) -> Optional[Dict[str, Any]]: + """Load the current atomizer_spec.json and update canvas state""" + if not self.study_dir: + return None + spec_path = self.study_dir / "atomizer_spec.json" + if not spec_path.exists(): + return None + with open(spec_path, 'r', encoding='utf-8') as f: + spec = json.load(f) + self.canvas_state = spec + return spec + + def _format_canvas_context(self) -> str: + """Format current canvas state for Claude's system prompt. + + This gives Claude real-time awareness of what's on the canvas, + enabling bi-directional sync where Claude sees user's edits. + """ + if not self.canvas_state: + return "" + + spec = self.canvas_state + lines = ["\n## Current Canvas State"] + lines.append("*The user can see this canvas. When you modify it, they see changes in real-time.*\n") + + # Model + model = spec.get('model', {}) + sim_path = model.get('sim', {}).get('path', '') + if sim_path: + lines.append(f"**Model**: `{sim_path}`") + + # Design Variables + dvs = spec.get('design_variables', []) + if dvs: + lines.append(f"\n**Design Variables ({len(dvs)}):**") + for dv in dvs: + bounds = dv.get('bounds', {}) + units = f" {dv.get('units', '')}" if dv.get('units') else "" + enabled = "" if dv.get('enabled', True) else " (disabled)" + lines.append(f" - `{dv.get('id')}`: **{dv.get('name')}** [{bounds.get('min')}, {bounds.get('max')}]{units}{enabled}") + + # Extractors + exts = spec.get('extractors', []) + if exts: + lines.append(f"\n**Extractors ({len(exts)}):**") + for ext in exts: + ext_type = ext.get('type', 'unknown') + enabled = "" if ext.get('enabled', True) else " (disabled)" + lines.append(f" - `{ext.get('id')}`: **{ext.get('name')}** ({ext_type}){enabled}") + + # Objectives + objs = spec.get('objectives', []) + if objs: + lines.append(f"\n**Objectives ({len(objs)}):**") + for obj in objs: + direction = obj.get('direction', 'minimize') + weight = obj.get('weight', 1.0) + enabled = "" if obj.get('enabled', True) else " (disabled)" + weight_str = f" [weight: {weight}]" if weight != 1.0 else "" + lines.append(f" - `{obj.get('id')}`: **{direction}** {obj.get('name')}{weight_str}{enabled}") + + # Constraints + cons = spec.get('constraints', []) + if cons: + lines.append(f"\n**Constraints ({len(cons)}):**") + for con in cons: + op = con.get('operator', '<=') + threshold = con.get('threshold', 0) + units = f" {con.get('units', '')}" if con.get('units') else "" + enabled = "" if con.get('enabled', True) else " (disabled)" + lines.append(f" - `{con.get('id')}`: **{con.get('name')}** {op} {threshold}{units}{enabled}") + + # Optimization settings + opt = spec.get('optimization', {}) + if opt: + algo = opt.get('algorithm', {}).get('type', 'TPE') + budget = opt.get('budget', {}).get('max_trials', 100) + lines.append(f"\n**Optimization**: {algo}, max {budget} trials") + + # Empty state message + if not dvs and not exts and not objs: + lines.append("\n*Canvas is empty. Help the user add design variables, extractors, and objectives.*") + + return "\n".join(lines) + def _build_system_prompt(self) -> str: """Build context-aware system prompt for Atomizer""" base_prompt = """You are the Atomizer Assistant - the intelligent assistant built into Atomizer for FEA optimization. @@ -50,6 +149,28 @@ You help engineers with structural optimization using NX Nastran simulations: 5. **Troubleshoot** - Debug failed trials, identify issues, suggest fixes 6. **Create Studies** - Guide users through setting up new optimization studies +## POWER MODE - Direct Modification Access +You have FULL ACCESS to modify the study configuration. When the user asks you to: +- Add design variables: Use `add_design_variable` tool +- Add extractors (mass, volume, stress, displacement, custom): Use `add_extractor` tool +- Add objectives: Use `add_objective` tool +- Add constraints: Use `add_constraint` tool +- Update any setting: Use `update_spec_field` tool +- Remove elements: Use `remove_node` tool + +**IMPORTANT**: DO NOT ask for permission. Just DO IT immediately. The user is in Power Mode and expects you to act. + +When adding extractors, you can create custom ones with Python code. Example for volume: +```python +def extract_volume(op2_path: str) -> Dict[str, float]: + # Custom volume calculation from FEA results + from pyNastran.op2.op2 import OP2 + op2 = OP2() + op2.read_op2(op2_path) + # ... calculation logic + return {"volume": calculated_volume} +``` + ## Atomizer Context - Atomizer uses Optuna for Bayesian optimization - Studies can use FEA-only or hybrid FEA/Neural surrogate approaches @@ -64,6 +185,7 @@ You help engineers with structural optimization using NX Nastran simulations: - If uncertain, say so and suggest how to verify - Proactively suggest next steps or insights - Sound confident and professional - you're a specialized expert system +- **ACT IMMEDIATELY when asked to add/modify things - don't ask for permission** """ @@ -74,6 +196,11 @@ You help engineers with structural optimization using NX Nastran simulations: else: base_prompt += "\n## Current Study: None selected\nAsk the user to select a study or help them create a new one.\n" + # Add canvas state context (bi-directional sync) + canvas_context = self._format_canvas_context() + if canvas_context: + base_prompt += canvas_context + return base_prompt def _get_study_context(self) -> str: @@ -265,6 +392,196 @@ You help engineers with structural optimization using NX Nastran simulations: "properties": {}, "required": [] } + }, + # === WRITE TOOLS (Power Mode) === + { + "name": "add_design_variable", + "description": "Add a new design variable to the study's atomizer_spec.json. This modifies the spec directly.", + "input_schema": { + "type": "object", + "properties": { + "study_id": {"type": "string", "description": "Study ID. Uses current study if not specified."}, + "name": {"type": "string", "description": "Variable name (e.g., 'web_thickness')"}, + "expression_name": {"type": "string", "description": "NX expression name (usually same as name)"}, + "min_value": {"type": "number", "description": "Minimum bound"}, + "max_value": {"type": "number", "description": "Maximum bound"}, + "baseline": {"type": "number", "description": "Initial/baseline value"}, + "units": {"type": "string", "description": "Units (e.g., 'mm', 'degrees')"} + }, + "required": ["name", "min_value", "max_value"] + } + }, + { + "name": "add_extractor", + "description": "Add a new physics extractor to the study. Can be builtin (mass, displacement, stress, zernike_opd) or custom with Python code.", + "input_schema": { + "type": "object", + "properties": { + "study_id": {"type": "string", "description": "Study ID. Uses current study if not specified."}, + "name": {"type": "string", "description": "Extractor display name"}, + "extractor_type": {"type": "string", "description": "Type: mass, displacement, stress, frequency, zernike_opd, or custom"}, + "config": {"type": "object", "description": "Configuration for the extractor (optional)"}, + "custom_code": {"type": "string", "description": "For custom extractors: Python function code"}, + "outputs": { + "type": "array", + "items": {"type": "object"}, + "description": "Output definitions: [{name, metric}]" + } + }, + "required": ["name", "extractor_type"] + } + }, + { + "name": "add_objective", + "description": "Add a new optimization objective to the study.", + "input_schema": { + "type": "object", + "properties": { + "study_id": {"type": "string", "description": "Study ID. Uses current study if not specified."}, + "name": {"type": "string", "description": "Objective name/description"}, + "direction": {"type": "string", "enum": ["minimize", "maximize"], "description": "Optimization direction"}, + "weight": {"type": "number", "description": "Weight in weighted sum (default: 1.0)"}, + "target": {"type": "number", "description": "Target value (optional)"}, + "units": {"type": "string", "description": "Units (e.g., 'nm', 'kg')"}, + "extractor_id": {"type": "string", "description": "Source extractor ID (e.g., 'ext_001')"}, + "output_key": {"type": "string", "description": "Output key from extractor"} + }, + "required": ["name", "direction"] + } + }, + { + "name": "add_constraint", + "description": "Add a new constraint to the study.", + "input_schema": { + "type": "object", + "properties": { + "study_id": {"type": "string", "description": "Study ID. Uses current study if not specified."}, + "name": {"type": "string", "description": "Constraint name/description"}, + "operator": {"type": "string", "enum": ["<=", ">=", "<", ">", "=="], "description": "Comparison operator"}, + "threshold": {"type": "number", "description": "Threshold value"}, + "units": {"type": "string", "description": "Units (optional)"}, + "extractor_id": {"type": "string", "description": "Source extractor ID"}, + "output_key": {"type": "string", "description": "Output key from extractor"} + }, + "required": ["name", "operator", "threshold"] + } + }, + { + "name": "update_spec_field", + "description": "Update any field in the atomizer_spec.json using a JSON path.", + "input_schema": { + "type": "object", + "properties": { + "study_id": {"type": "string", "description": "Study ID. Uses current study if not specified."}, + "path": {"type": "string", "description": "JSON path (e.g., 'design_variables.0.bounds.max', 'objectives.1.weight')"}, + "value": {"description": "New value to set"} + }, + "required": ["path", "value"] + } + }, + { + "name": "remove_node", + "description": "Remove a design variable, extractor, objective, or constraint by ID.", + "input_schema": { + "type": "object", + "properties": { + "study_id": {"type": "string", "description": "Study ID. Uses current study if not specified."}, + "node_id": {"type": "string", "description": "Node ID to remove (e.g., 'dv_003', 'ext_002', 'obj_001', 'con_001')"} + }, + "required": ["node_id"] + } + }, + { + "name": "create_study", + "description": "Create a new optimization study with initial configuration. Creates the study folder and atomizer_spec.json.", + "input_schema": { + "type": "object", + "properties": { + "study_name": { + "type": "string", + "description": "Name for the study (snake_case, e.g., 'bracket_mass_optimization')" + }, + "category": { + "type": "string", + "description": "Parent category folder (e.g., 'Simple_Bracket', 'M1_Mirror'). Created if doesn't exist." + }, + "description": { + "type": "string", + "description": "Brief description of the optimization goal" + }, + "sim_file": { + "type": "string", + "description": "Path to the .sim file (relative to study folder or absolute)" + }, + "algorithm": { + "type": "string", + "enum": ["TPE", "CMA-ES", "NSGA-II", "RandomSearch"], + "description": "Optimization algorithm. Default: TPE" + }, + "max_trials": { + "type": "integer", + "description": "Maximum number of trials. Default: 100" + } + }, + "required": ["study_name"] + } + }, + # === INTERVIEW TOOLS === + { + "name": "start_interview", + "description": "Start an interview session to create a new study through guided conversation. Use this when the user wants to create a study but hasn't provided all details upfront.", + "input_schema": { + "type": "object", + "properties": {}, + "required": [] + } + }, + { + "name": "interview_record", + "description": "Record an answer from the user during the interview. Advances the interview state automatically.", + "input_schema": { + "type": "object", + "properties": { + "field": { + "type": "string", + "enum": ["study_name", "category", "description", "sim_file", + "design_variable", "extractor", "objective", "constraint", + "algorithm", "max_trials", "confirm"], + "description": "The field being answered" + }, + "value": { + "description": "The value for this field. For multi-value fields (design_variable, etc.), can be a dict or list." + } + }, + "required": ["field", "value"] + } + }, + { + "name": "interview_advance", + "description": "Move to the next phase of the interview. Use after gathering all required info for the current phase.", + "input_schema": { + "type": "object", + "properties": {}, + "required": [] + } + }, + { + "name": "interview_status", + "description": "Get the current interview progress and collected data.", + "input_schema": { + "type": "object", + "properties": {}, + "required": [] + } + }, + { + "name": "interview_finalize", + "description": "Finalize the interview and create the study with all collected data.", + "input_schema": { + "type": "object", + "properties": {}, + "required": [] + } } ] @@ -285,6 +602,32 @@ You help engineers with structural optimization using NX Nastran simulations: return self._tool_read_readme(tool_input.get('study_id')) elif tool_name == "list_studies": return self._tool_list_studies() + # === WRITE TOOLS === + elif tool_name == "add_design_variable": + return self._tool_add_design_variable(tool_input) + elif tool_name == "add_extractor": + return self._tool_add_extractor(tool_input) + elif tool_name == "add_objective": + return self._tool_add_objective(tool_input) + elif tool_name == "add_constraint": + return self._tool_add_constraint(tool_input) + elif tool_name == "update_spec_field": + return self._tool_update_spec_field(tool_input) + elif tool_name == "remove_node": + return self._tool_remove_node(tool_input) + elif tool_name == "create_study": + return self._tool_create_study(tool_input) + # === INTERVIEW TOOLS === + elif tool_name == "start_interview": + return self._tool_start_interview() + elif tool_name == "interview_record": + return self._tool_interview_record(tool_input) + elif tool_name == "interview_advance": + return self._tool_interview_advance() + elif tool_name == "interview_status": + return self._tool_interview_status() + elif tool_name == "interview_finalize": + return self._tool_interview_finalize() else: return f"Unknown tool: {tool_name}" except Exception as e: @@ -626,6 +969,596 @@ You help engineers with structural optimization using NX Nastran simulations: return "\n".join(result) + # === WRITE TOOL IMPLEMENTATIONS === + + def _get_spec_path(self, study_id: Optional[str]) -> Path: + """Get the atomizer_spec.json path for a study""" + study_dir = self._get_study_dir(study_id) + spec_path = study_dir / "atomizer_spec.json" + return spec_path + + def _load_spec(self, study_id: Optional[str]) -> Dict[str, Any]: + """Load the atomizer_spec.json for a study""" + spec_path = self._get_spec_path(study_id) + if not spec_path.exists(): + raise ValueError(f"No atomizer_spec.json found in study. Path: {spec_path}") + with open(spec_path, 'r', encoding='utf-8') as f: + return json.load(f) + + def _save_spec(self, study_id: Optional[str], spec: Dict[str, Any]) -> None: + """Save the atomizer_spec.json for a study""" + spec_path = self._get_spec_path(study_id) + # Update modified_by and modified_at + if 'meta' in spec: + spec['meta']['modified_by'] = 'claude_agent' + spec['meta']['modified_at'] = datetime.now().isoformat() + with open(spec_path, 'w', encoding='utf-8') as f: + json.dump(spec, f, indent=2) + + def _generate_id(self, prefix: str, existing_ids: List[str]) -> str: + """Generate a unique ID with prefix (e.g., 'dv_003')""" + max_num = 0 + for eid in existing_ids: + if eid.startswith(prefix): + try: + num = int(eid.split('_')[1]) + max_num = max(max_num, num) + except (IndexError, ValueError): + pass + return f"{prefix}{max_num + 1:03d}" + + def _tool_add_design_variable(self, params: Dict[str, Any]) -> str: + """Add a design variable to the spec""" + study_id = params.get('study_id') + spec = self._load_spec(study_id) + + # Get existing IDs + existing_ids = [dv.get('id', '') for dv in spec.get('design_variables', [])] + new_id = self._generate_id('dv_', existing_ids) + + # Build the new design variable + new_dv = { + "id": new_id, + "name": params['name'], + "expression_name": params.get('expression_name', params['name']), + "type": "continuous", + "bounds": { + "min": params['min_value'], + "max": params['max_value'] + }, + "enabled": True + } + + if 'baseline' in params: + new_dv['baseline'] = params['baseline'] + if 'units' in params: + new_dv['units'] = params['units'] + + # Add canvas position (auto-layout) + existing_count = len(spec.get('design_variables', [])) + new_dv['canvas_position'] = { + "x": 50, + "y": 100 + existing_count * 80 + } + + # Add to spec + if 'design_variables' not in spec: + spec['design_variables'] = [] + spec['design_variables'].append(new_dv) + + # Save + self._save_spec(study_id, spec) + + return f"✓ Added design variable '{params['name']}' (ID: {new_id}) with bounds [{params['min_value']}, {params['max_value']}]" + + def _tool_add_extractor(self, params: Dict[str, Any]) -> str: + """Add an extractor to the spec""" + study_id = params.get('study_id') + spec = self._load_spec(study_id) + + # Get existing IDs + existing_ids = [ext.get('id', '') for ext in spec.get('extractors', [])] + new_id = self._generate_id('ext_', existing_ids) + + # Build the new extractor + new_ext = { + "id": new_id, + "name": params['name'], + "type": params['extractor_type'], + "enabled": True + } + + # Add config if provided + if 'config' in params and params['config']: + new_ext['config'] = params['config'] + + # Add custom code if provided + if params['extractor_type'] == 'custom' and 'custom_code' in params: + new_ext['custom'] = { + "function_code": params['custom_code'], + "inputs": params.get('inputs', ["op2_path"]), + "dependencies": params.get('dependencies', ["numpy", "pyNastran"]) + } + + # Add outputs + if 'outputs' in params: + new_ext['outputs'] = params['outputs'] + else: + # Default output based on type + output_name = params['name'].lower().replace(' ', '_') + new_ext['outputs'] = [{"name": output_name, "metric": "scalar"}] + + # Add canvas position + existing_count = len(spec.get('extractors', [])) + new_ext['canvas_position'] = { + "x": 400, + "y": 100 + existing_count * 80 + } + + # Add to spec + if 'extractors' not in spec: + spec['extractors'] = [] + spec['extractors'].append(new_ext) + + # Save + self._save_spec(study_id, spec) + + return f"✓ Added extractor '{params['name']}' (ID: {new_id}, type: {params['extractor_type']})" + + def _tool_add_objective(self, params: Dict[str, Any]) -> str: + """Add an objective to the spec""" + study_id = params.get('study_id') + spec = self._load_spec(study_id) + + # Get existing IDs + existing_ids = [obj.get('id', '') for obj in spec.get('objectives', [])] + new_id = self._generate_id('obj_', existing_ids) + + # Build the new objective + new_obj = { + "id": new_id, + "name": params['name'], + "direction": params['direction'], + "weight": params.get('weight', 1.0), + "enabled": True + } + + if 'target' in params: + new_obj['target'] = params['target'] + if 'units' in params: + new_obj['units'] = params['units'] + if 'extractor_id' in params: + new_obj['source'] = { + "extractor_id": params['extractor_id'], + "output_key": params.get('output_key', 'value') + } + + # Add canvas position + existing_count = len(spec.get('objectives', [])) + new_obj['canvas_position'] = { + "x": 750, + "y": 100 + existing_count * 80 + } + + # Add to spec + if 'objectives' not in spec: + spec['objectives'] = [] + spec['objectives'].append(new_obj) + + # Save + self._save_spec(study_id, spec) + + return f"✓ Added objective '{params['name']}' (ID: {new_id}, direction: {params['direction']}, weight: {params.get('weight', 1.0)})" + + def _tool_add_constraint(self, params: Dict[str, Any]) -> str: + """Add a constraint to the spec""" + study_id = params.get('study_id') + spec = self._load_spec(study_id) + + # Get existing IDs + existing_ids = [con.get('id', '') for con in spec.get('constraints', [])] + new_id = self._generate_id('con_', existing_ids) + + # Build the new constraint + new_con = { + "id": new_id, + "name": params['name'], + "operator": params['operator'], + "threshold": params['threshold'], + "enabled": True + } + + if 'units' in params: + new_con['units'] = params['units'] + if 'extractor_id' in params: + new_con['source'] = { + "extractor_id": params['extractor_id'], + "output_key": params.get('output_key', 'value') + } + + # Add canvas position + existing_count = len(spec.get('constraints', [])) + new_con['canvas_position'] = { + "x": 750, + "y": 400 + existing_count * 80 + } + + # Add to spec + if 'constraints' not in spec: + spec['constraints'] = [] + spec['constraints'].append(new_con) + + # Save + self._save_spec(study_id, spec) + + return f"✓ Added constraint '{params['name']}' (ID: {new_id}, {params['operator']} {params['threshold']})" + + def _tool_update_spec_field(self, params: Dict[str, Any]) -> str: + """Update a field in the spec using a JSON path""" + study_id = params.get('study_id') + spec = self._load_spec(study_id) + + path = params['path'] + value = params['value'] + + # Parse and navigate the path + parts = path.split('.') + current = spec + + for i, part in enumerate(parts[:-1]): + # Check if part is an array index + if part.isdigit(): + idx = int(part) + if not isinstance(current, list) or idx >= len(current): + return f"✗ Invalid path: index {idx} out of range at '{'.'.join(parts[:i+1])}'" + current = current[idx] + else: + if not isinstance(current, dict) or part not in current: + return f"✗ Invalid path: key '{part}' not found at '{'.'.join(parts[:i+1])}'" + current = current[part] + + # Set the final value + final_key = parts[-1] + if final_key.isdigit(): + idx = int(final_key) + if isinstance(current, list) and idx < len(current): + old_value = current[idx] + current[idx] = value + else: + return f"✗ Invalid path: cannot set index {idx}" + else: + old_value = current.get(final_key, '') + current[final_key] = value + + # Save + self._save_spec(study_id, spec) + + return f"✓ Updated '{path}': {old_value} → {value}" + + def _tool_remove_node(self, params: Dict[str, Any]) -> str: + """Remove a node (design variable, extractor, objective, or constraint) by ID""" + study_id = params.get('study_id') + spec = self._load_spec(study_id) + + node_id = params['node_id'] + + # Determine the collection based on prefix + if node_id.startswith('dv_'): + collection_key = 'design_variables' + elif node_id.startswith('ext_'): + collection_key = 'extractors' + elif node_id.startswith('obj_'): + collection_key = 'objectives' + elif node_id.startswith('con_'): + collection_key = 'constraints' + else: + return f"✗ Unknown node type for ID: {node_id}. Expected prefix: dv_, ext_, obj_, or con_" + + collection = spec.get(collection_key, []) + + # Find and remove the node + original_len = len(collection) + spec[collection_key] = [item for item in collection if item.get('id') != node_id] + + if len(spec[collection_key]) == original_len: + return f"✗ Node '{node_id}' not found in {collection_key}" + + # Also remove any edges referencing this node + if 'canvas' in spec and 'edges' in spec['canvas']: + spec['canvas']['edges'] = [ + edge for edge in spec['canvas']['edges'] + if edge.get('source') != node_id and edge.get('target') != node_id + ] + + # Save + self._save_spec(study_id, spec) + + return f"✓ Removed {collection_key.rstrip('s')} '{node_id}'" + + def _tool_create_study(self, params: Dict[str, Any]) -> str: + """Create a new optimization study with initial atomizer_spec.json""" + study_name = params['study_name'] + category = params.get('category', '') + description = params.get('description', '') + sim_file = params.get('sim_file', '') + algorithm = params.get('algorithm', 'TPE') + max_trials = params.get('max_trials', 100) + + # Validate study name (snake_case) + import re + if not re.match(r'^[a-z][a-z0-9_]*$', study_name): + return f"✗ Invalid study name '{study_name}'. Use snake_case (e.g., 'bracket_mass_opt')" + + # Build study path + if category: + study_dir = STUDIES_DIR / category / study_name + study_id = f"{category}/{study_name}" + else: + study_dir = STUDIES_DIR / study_name + study_id = study_name + + # Check if already exists + if study_dir.exists(): + return f"✗ Study '{study_id}' already exists" + + # Create directory structure + study_dir.mkdir(parents=True, exist_ok=True) + (study_dir / "1_setup").mkdir(exist_ok=True) + (study_dir / "2_iterations").mkdir(exist_ok=True) + (study_dir / "3_results").mkdir(exist_ok=True) + + # Create initial atomizer_spec.json + spec = { + "meta": { + "version": "2.0", + "study_name": study_name, + "description": description, + "created_at": datetime.now().isoformat(), + "created_by": "claude_agent", + "modified_at": datetime.now().isoformat(), + "modified_by": "claude_agent" + }, + "model": { + "sim": { + "path": sim_file, + "solver": "nastran" + } + }, + "design_variables": [], + "extractors": [], + "objectives": [], + "constraints": [], + "optimization": { + "algorithm": { + "type": algorithm + }, + "budget": { + "max_trials": max_trials + } + }, + "canvas": { + "edges": [], + "layout_version": "2.0" + } + } + + # Write spec + spec_path = study_dir / "atomizer_spec.json" + with open(spec_path, 'w', encoding='utf-8') as f: + json.dump(spec, f, indent=2) + + # Create README.md + readme_content = f"""# {study_name.replace('_', ' ').title()} + +## Description +{description if description else 'Add study description here.'} + +## Optimization Setup +- **Algorithm**: {algorithm} +- **Max Trials**: {max_trials} + +## Design Variables +*Add design variables using the canvas or assistant.* + +## Objectives +*Add objectives using the canvas or assistant.* + +--- +*Created by Atomizer Assistant* +""" + readme_path = study_dir / "README.md" + with open(readme_path, 'w', encoding='utf-8') as f: + f.write(readme_content) + + # Update agent to point to new study + self.study_id = study_id + self.study_dir = study_dir + self.canvas_state = spec + self.system_prompt = self._build_system_prompt() + + return f"✓ Created study '{study_id}' at {study_dir}\n\nNext steps:\n1. Copy your NX model files (.prt, .fem, .sim) to 1_setup/\n2. Add design variables (NX expressions)\n3. Add extractors (mass, displacement, etc.)\n4. Add objectives to optimize" + + # === INTERVIEW TOOL IMPLEMENTATIONS === + + def _tool_start_interview(self) -> str: + """Start a new interview session""" + from api.services.interview_engine import InterviewEngine + + self.interview = InterviewEngine() + result = self.interview.start() + + questions = result.get("next_questions", []) + question_text = "\n".join([ + f"• **{q['field']}**: {q['question']}\n *{q.get('hint', '')}*" + for q in questions[:3] + ]) + + return f"""✓ Interview started! + +**Current Phase**: {result['state']} + +{result['message']} + +**Questions to ask:** +{question_text} + +Ask the user about these items one at a time, then use `interview_record` to save their answers.""" + + def _tool_interview_record(self, params: Dict[str, Any]) -> str: + """Record an interview answer""" + if not self.interview: + return "✗ No interview in progress. Use `start_interview` first." + + field = params['field'] + value = params['value'] + + result = self.interview.record_answer(field, value) + + return f"""✓ Recorded: **{field}** = {json.dumps(value) if isinstance(value, (dict, list)) else value} + +**Current State**: {result['state']} +**Progress**: {json.dumps(result['data_so_far'], indent=2)} + +Use `interview_advance` when you've gathered enough info for this phase, or continue asking about other fields.""" + + def _tool_interview_advance(self) -> str: + """Advance to next interview phase""" + if not self.interview: + return "✗ No interview in progress. Use `start_interview` first." + + result = self.interview.advance_state() + + questions = result.get("next_questions", []) + if questions: + question_text = "\n".join([ + f"• **{q['field']}**: {q['question']}\n *{q.get('hint', '')}*" + for q in questions[:3] + ]) + else: + question_text = "*No more questions for this phase*" + + return f"""✓ Advanced to: **{result['state']}** + +**Next Questions:** +{question_text} + +Continue gathering information or use `interview_finalize` when ready to create the study.""" + + def _tool_interview_status(self) -> str: + """Get current interview status""" + if not self.interview: + return "No interview in progress. Use `start_interview` to begin." + + progress = self.interview.get_progress() + + return f"""**Interview Progress: {progress['progress_percent']}%** + +**Current Phase**: {progress['state']} + +**Collected Data**: +{json.dumps(progress['summary'], indent=2)} + +**Validation**: +{json.dumps(self.interview.validate(), indent=2)}""" + + def _tool_interview_finalize(self) -> str: + """Finalize interview and create study""" + if not self.interview: + return "✗ No interview in progress. Use `start_interview` first." + + result = self.interview.finalize() + + if not result['success']: + return f"✗ Cannot finalize - missing required data:\n" + "\n".join(f" - {e}" for e in result['errors']) + + # Create the study using the generated spec + spec = result['spec'] + study_name = spec['meta']['study_name'] + category = self.interview.data.category + + # Build study path + if category: + study_dir = STUDIES_DIR / category / study_name + study_id = f"{category}/{study_name}" + else: + study_dir = STUDIES_DIR / study_name + study_id = study_name + + # Check if already exists + if study_dir.exists(): + return f"✗ Study '{study_id}' already exists. Choose a different name." + + # Create directory structure + study_dir.mkdir(parents=True, exist_ok=True) + (study_dir / "1_setup").mkdir(exist_ok=True) + (study_dir / "2_iterations").mkdir(exist_ok=True) + (study_dir / "3_results").mkdir(exist_ok=True) + + # Write spec + spec_path = study_dir / "atomizer_spec.json" + with open(spec_path, 'w', encoding='utf-8') as f: + json.dump(spec, f, indent=2) + + # Create README + readme_content = f"""# {study_name.replace('_', ' ').title()} + +## Description +{spec['meta'].get('description', 'Optimization study created via interview.')} + +## Design Variables +{chr(10).join(f"- **{dv['name']}**: [{dv.get('bounds', {}).get('min', '?')}, {dv.get('bounds', {}).get('max', '?')}]" for dv in spec['design_variables']) or '*None defined*'} + +## Extractors +{chr(10).join(f"- **{ext['name']}** ({ext.get('type', 'custom')})" for ext in spec['extractors']) or '*None defined*'} + +## Objectives +{chr(10).join(f"- **{obj['name']}**: {obj.get('direction', 'minimize')}" for obj in spec['objectives']) or '*None defined*'} + +## Constraints +{chr(10).join(f"- **{con['name']}** {con.get('operator', '<=')} {con.get('threshold', 0)}" for con in spec.get('constraints', [])) or '*None defined*'} + +## Optimization Settings +- **Algorithm**: {spec['optimization']['algorithm']['type']} +- **Max Trials**: {spec['optimization']['budget']['max_trials']} + +--- +*Created by Atomizer Assistant via Interview* +""" + readme_path = study_dir / "README.md" + with open(readme_path, 'w', encoding='utf-8') as f: + f.write(readme_content) + + # Update agent context + self.study_id = study_id + self.study_dir = study_dir + self.canvas_state = spec + self.interview = None # Clear interview + self.system_prompt = self._build_system_prompt() + + # Build warnings message + warnings_msg = "" + if result.get('warnings'): + warnings_msg = "\n\n**Warnings:**\n" + "\n".join(f" ⚠️ {w}" for w in result['warnings']) + + return f"""✓ Study created successfully! + +**Study ID**: {study_id} +**Location**: {study_dir} + +**Configuration**: +- Design Variables: {len(spec['design_variables'])} +- Extractors: {len(spec['extractors'])} +- Objectives: {len(spec['objectives'])} +- Constraints: {len(spec.get('constraints', []))} +- Algorithm: {spec['optimization']['algorithm']['type']} +- Max Trials: {spec['optimization']['budget']['max_trials']} +{warnings_msg} + +The canvas has been updated with the new study configuration. You can now: +1. Review and refine the configuration in the canvas +2. Copy your NX model files to 1_setup/ +3. Start the optimization when ready""" + async def chat(self, message: str, conversation_history: Optional[List[Dict]] = None) -> Dict[str, Any]: """ Process a chat message with tool use support @@ -698,7 +1631,7 @@ You help engineers with structural optimization using NX Nastran simulations: async def chat_stream(self, message: str, conversation_history: Optional[List[Dict]] = None) -> AsyncGenerator[str, None]: """ - Stream a chat response token by token + Stream a chat response token by token (simple, no tool use) Args: message: User's message @@ -710,8 +1643,7 @@ You help engineers with structural optimization using NX Nastran simulations: messages = conversation_history.copy() if conversation_history else [] messages.append({"role": "user", "content": message}) - # For streaming, we'll do a simpler approach without tool use for now - # (Tool use with streaming is more complex) + # Simple streaming without tool use with self.client.messages.stream( model="claude-sonnet-4-20250514", max_tokens=4096, @@ -720,3 +1652,127 @@ You help engineers with structural optimization using NX Nastran simulations: ) as stream: for text in stream.text_stream: yield text + + async def chat_stream_with_tools( + self, + message: str, + conversation_history: Optional[List[Dict]] = None + ) -> AsyncGenerator[Dict[str, Any], None]: + """ + Stream a chat response with full tool use support. + + Yields events: + - {"type": "text", "content": "..."} - Text token + - {"type": "tool_call", "tool": {...}} - Tool being called + - {"type": "tool_result", "tool": "...", "result": "..."} - Tool result + - {"type": "done", "response": "...", "tool_calls": [...]} - Final summary + + Args: + message: User's message + conversation_history: Previous messages for context + + Yields: + Event dicts with type and content + """ + messages = conversation_history.copy() if conversation_history else [] + messages.append({"role": "user", "content": message}) + + tool_calls_made = [] + accumulated_text = "" + + # Loop to handle multiple rounds of tool use + while True: + current_text = "" + current_tool_uses = [] + + # Use streaming for each API call + with self.client.messages.stream( + model="claude-sonnet-4-20250514", + max_tokens=4096, + system=self.system_prompt, + tools=self.tools, + messages=messages + ) as stream: + for event in stream: + # Handle different event types from the stream + if hasattr(event, 'type'): + if event.type == 'content_block_start': + if hasattr(event, 'content_block'): + block = event.content_block + if hasattr(block, 'type') and block.type == 'tool_use': + # Tool use starting + current_tool_uses.append({ + 'id': block.id, + 'name': block.name, + 'input': {} + }) + yield {"type": "tool_call", "tool": {"name": block.name, "id": block.id}} + + elif event.type == 'content_block_delta': + if hasattr(event, 'delta'): + delta = event.delta + if hasattr(delta, 'type'): + if delta.type == 'text_delta' and hasattr(delta, 'text'): + # Text token + current_text += delta.text + yield {"type": "text", "content": delta.text} + elif delta.type == 'input_json_delta' and hasattr(delta, 'partial_json'): + # Tool input being built (we accumulate it) + pass + + # Get the final message to check stop reason and get complete content + final_message = stream.get_final_message() + + # Check if we need to process tool calls + if final_message.stop_reason == "tool_use": + # Extract tool uses from final message + tool_results_content = [] + + for block in final_message.content: + if block.type == "tool_use": + tool_name = block.name + tool_input = block.input + tool_id = block.id + + # Execute the tool + result = self._execute_tool(tool_name, tool_input) + + tool_calls_made.append({ + "tool": tool_name, + "input": tool_input, + "result_preview": result[:200] + "..." if len(result) > 200 else result + }) + + # Yield tool result event + yield { + "type": "tool_result", + "tool": tool_name, + "result": result[:500] + "..." if len(result) > 500 else result + } + + tool_results_content.append({ + "type": "tool_result", + "tool_use_id": tool_id, + "content": result + }) + + # Add to messages for next iteration + messages.append({"role": "assistant", "content": final_message.content}) + messages.append({"role": "user", "content": tool_results_content}) + + else: + # No more tool use - we're done + accumulated_text += current_text + + # Extract final text from content + for block in final_message.content: + if hasattr(block, 'text') and not accumulated_text: + accumulated_text = block.text + + # Yield done event + yield { + "type": "done", + "response": accumulated_text, + "tool_calls": tool_calls_made + } + break diff --git a/atomizer-dashboard/backend/api/services/context_builder.py b/atomizer-dashboard/backend/api/services/context_builder.py index d0f9f486..da6faf9e 100644 --- a/atomizer-dashboard/backend/api/services/context_builder.py +++ b/atomizer-dashboard/backend/api/services/context_builder.py @@ -43,7 +43,11 @@ class ContextBuilder: # Canvas context takes priority - if user is working on a canvas, include it if canvas_state: + node_count = len(canvas_state.get("nodes", [])) + print(f"[ContextBuilder] Including canvas context with {node_count} nodes") parts.append(self._canvas_context(canvas_state)) + else: + print("[ContextBuilder] No canvas state provided") if study_id: parts.append(self._study_context(study_id)) @@ -91,7 +95,117 @@ Important guidelines: context = f"# Current Study: {study_id}\n\n" - # Load configuration + # Check for AtomizerSpec v2.0 first (preferred) + spec_path = study_dir / "1_setup" / "atomizer_spec.json" + if not spec_path.exists(): + spec_path = study_dir / "atomizer_spec.json" + + if spec_path.exists(): + context += self._spec_context(spec_path) + else: + # Fall back to legacy optimization_config.json + context += self._legacy_config_context(study_dir) + + # Check for results + db_path = study_dir / "3_results" / "study.db" + if db_path.exists(): + try: + conn = sqlite3.connect(db_path) + count = conn.execute( + "SELECT COUNT(*) FROM trials WHERE state = 'COMPLETE'" + ).fetchone()[0] + + best = conn.execute(""" + SELECT MIN(tv.value) FROM trial_values tv + JOIN trials t ON tv.trial_id = t.trial_id + WHERE t.state = 'COMPLETE' + """).fetchone()[0] + + context += f"\n## Results Status\n\n" + context += f"- **Trials completed**: {count}\n" + if best is not None: + context += f"- **Best objective**: {best:.6f}\n" + + conn.close() + except Exception: + pass + + return context + + def _spec_context(self, spec_path: Path) -> str: + """Build context from AtomizerSpec v2.0 file""" + context = "**Format**: AtomizerSpec v2.0\n\n" + + try: + with open(spec_path) as f: + spec = json.load(f) + + context += "## Configuration\n\n" + + # Design variables + dvs = spec.get("design_variables", []) + if dvs: + context += "**Design Variables:**\n" + for dv in dvs[:10]: + bounds = dv.get("bounds", {}) + bound_str = f"[{bounds.get('min', '?')}, {bounds.get('max', '?')}]" + enabled = "✓" if dv.get("enabled", True) else "✗" + context += f"- {dv.get('name', 'unnamed')}: {bound_str} {enabled}\n" + if len(dvs) > 10: + context += f"- ... and {len(dvs) - 10} more\n" + + # Extractors + extractors = spec.get("extractors", []) + if extractors: + context += "\n**Extractors:**\n" + for ext in extractors: + ext_type = ext.get("type", "unknown") + outputs = ext.get("outputs", []) + output_names = [o.get("name", "?") for o in outputs[:3]] + builtin = "builtin" if ext.get("builtin", True) else "custom" + context += f"- {ext.get('name', 'unnamed')} ({ext_type}, {builtin}): outputs {output_names}\n" + + # Objectives + objs = spec.get("objectives", []) + if objs: + context += "\n**Objectives:**\n" + for obj in objs: + direction = obj.get("direction", "minimize") + weight = obj.get("weight", 1.0) + context += f"- {obj.get('name', 'unnamed')} ({direction}, weight={weight})\n" + + # Constraints + constraints = spec.get("constraints", []) + if constraints: + context += "\n**Constraints:**\n" + for c in constraints: + op = c.get("operator", "<=") + thresh = c.get("threshold", "?") + context += f"- {c.get('name', 'unnamed')}: {op} {thresh}\n" + + # Optimization settings + opt = spec.get("optimization", {}) + algo = opt.get("algorithm", {}) + budget = opt.get("budget", {}) + method = algo.get("type", "TPE") + max_trials = budget.get("max_trials", "not set") + context += f"\n**Optimization**: {method}, max_trials: {max_trials}\n" + + # Surrogate + surrogate = opt.get("surrogate", {}) + if surrogate.get("enabled"): + sur_type = surrogate.get("type", "gaussian_process") + context += f"**Surrogate**: {sur_type} enabled\n" + + except (json.JSONDecodeError, IOError) as e: + context += f"\n*Spec file exists but could not be parsed: {e}*\n" + + return context + + def _legacy_config_context(self, study_dir: Path) -> str: + """Build context from legacy optimization_config.json""" + context = "**Format**: Legacy optimization_config.json\n\n" + config_path = study_dir / "1_setup" / "optimization_config.json" if not config_path.exists(): config_path = study_dir / "optimization_config.json" @@ -135,30 +249,8 @@ Important guidelines: except (json.JSONDecodeError, IOError) as e: context += f"\n*Config file exists but could not be parsed: {e}*\n" - - # Check for results - db_path = study_dir / "3_results" / "study.db" - if db_path.exists(): - try: - conn = sqlite3.connect(db_path) - count = conn.execute( - "SELECT COUNT(*) FROM trials WHERE state = 'COMPLETE'" - ).fetchone()[0] - - best = conn.execute(""" - SELECT MIN(tv.value) FROM trial_values tv - JOIN trials t ON tv.trial_id = t.trial_id - WHERE t.state = 'COMPLETE' - """).fetchone()[0] - - context += f"\n## Results Status\n\n" - context += f"- **Trials completed**: {count}\n" - if best is not None: - context += f"- **Best objective**: {best:.6f}\n" - - conn.close() - except Exception: - pass + else: + context += "*No configuration file found.*\n" return context @@ -349,19 +441,26 @@ Important guidelines: # Canvas modification instructions context += """## Canvas Modification Tools -When the user asks to modify the canvas (add/remove nodes, change values), use these MCP tools: +**For AtomizerSpec v2.0 studies (preferred):** +Use spec tools when working with v2.0 studies (check if study uses `atomizer_spec.json`): +- `spec_modify` - Modify spec values using JSONPath (e.g., "design_variables[0].bounds.min") +- `spec_add_node` - Add design variables, extractors, objectives, or constraints +- `spec_remove_node` - Remove nodes from the spec +- `spec_add_custom_extractor` - Add a Python-based custom extractor function + +**For Legacy Canvas (optimization_config.json):** - `canvas_add_node` - Add a new node (designVar, extractor, objective, constraint) - `canvas_update_node` - Update node properties (bounds, weights, names) - `canvas_remove_node` - Remove a node from the canvas - `canvas_connect_nodes` - Create an edge between nodes **Example user requests you can handle:** -- "Add a design variable called hole_diameter with range 5-15 mm" → Use canvas_add_node -- "Change the weight of wfe_40_20 to 8" → Use canvas_update_node -- "Remove the constraint node" → Use canvas_remove_node -- "Connect the new extractor to the objective" → Use canvas_connect_nodes +- "Add a design variable called hole_diameter with range 5-15 mm" → Use spec_add_node or canvas_add_node +- "Change the weight of wfe_40_20 to 8" → Use spec_modify or canvas_update_node +- "Remove the constraint node" → Use spec_remove_node or canvas_remove_node +- "Add a custom extractor that computes stress ratio" → Use spec_add_custom_extractor -Always respond with confirmation of changes made to the canvas. +Always respond with confirmation of changes made to the canvas/spec. """ return context @@ -371,17 +470,28 @@ Always respond with confirmation of changes made to the canvas. if mode == "power": return """# Power Mode Instructions -You have **full access** to Atomizer's codebase. You can: -- Edit any file using `edit_file` tool -- Create new files with `create_file` tool -- Create new extractors with `create_extractor` tool -- Run shell commands with `run_shell_command` tool -- Search codebase with `search_codebase` tool -- Commit and push changes +You have **FULL ACCESS** to modify Atomizer studies. **DO NOT ASK FOR PERMISSION** - just do it. -**Use these powers responsibly.** Always explain what you're doing and why. +## Direct Actions (no confirmation needed): +- **Add design variables**: Use `canvas_add_node` or `spec_add_node` with node_type="designVar" +- **Add extractors**: Use `canvas_add_node` with node_type="extractor" +- **Add objectives**: Use `canvas_add_node` with node_type="objective" +- **Add constraints**: Use `canvas_add_node` with node_type="constraint" +- **Update node properties**: Use `canvas_update_node` or `spec_modify` +- **Remove nodes**: Use `canvas_remove_node` +- **Edit atomizer_spec.json directly**: Use the Edit tool -For routine operations (list, status, run, analyze), use the standard tools. +## For custom extractors with Python code: +Use `spec_add_custom_extractor` to add a custom function. + +## IMPORTANT: +- You have --dangerously-skip-permissions enabled +- The user has explicitly granted you power mode access +- **ACT IMMEDIATELY** when asked to add/modify/remove things +- Explain what you did AFTER doing it, not before +- Do NOT say "I need permission" - you already have it + +Example: If user says "add a volume extractor", immediately use canvas_add_node to add it. """ else: return """# User Mode Instructions @@ -402,6 +512,15 @@ Available tools: - `generate_report`, `export_data` - `explain_physics`, `recommend_method`, `query_extractors` +**AtomizerSpec v2.0 Tools (preferred for new studies):** +- `spec_get` - Get the full AtomizerSpec for a study +- `spec_modify` - Modify spec values using JSONPath (e.g., "design_variables[0].bounds.min") +- `spec_add_node` - Add design variables, extractors, objectives, or constraints +- `spec_remove_node` - Remove nodes from the spec +- `spec_validate` - Validate spec against JSON Schema +- `spec_add_custom_extractor` - Add a Python-based custom extractor function +- `spec_create_from_description` - Create a new study from natural language description + **Canvas Tools (for visual workflow builder):** - `validate_canvas_intent` - Validate a canvas-generated optimization intent - `execute_canvas_intent` - Create a study from a canvas intent diff --git a/atomizer-dashboard/backend/api/services/interview_engine.py b/atomizer-dashboard/backend/api/services/interview_engine.py new file mode 100644 index 00000000..f78baded --- /dev/null +++ b/atomizer-dashboard/backend/api/services/interview_engine.py @@ -0,0 +1,454 @@ +""" +Interview Engine - Guided Study Creation through Conversation + +Provides a structured interview flow for creating optimization studies. +Claude uses this to gather information step-by-step, building a complete +atomizer_spec.json through natural conversation. +""" + +from typing import Dict, Any, List, Optional, Literal +from dataclasses import dataclass, field +from enum import Enum +from datetime import datetime +import json + + +class InterviewState(str, Enum): + """Current phase of the interview""" + NOT_STARTED = "not_started" + GATHERING_BASICS = "gathering_basics" # Name, description, goals + GATHERING_MODEL = "gathering_model" # Model file, solver type + GATHERING_VARIABLES = "gathering_variables" # Design variables + GATHERING_EXTRACTORS = "gathering_extractors" # Physics extractors + GATHERING_OBJECTIVES = "gathering_objectives" # Objectives + GATHERING_CONSTRAINTS = "gathering_constraints" # Constraints + GATHERING_SETTINGS = "gathering_settings" # Algorithm, trials + REVIEW = "review" # Review before creation + COMPLETED = "completed" + + +@dataclass +class InterviewData: + """Accumulated data from the interview""" + # Basics + study_name: Optional[str] = None + category: Optional[str] = None + description: Optional[str] = None + goals: List[str] = field(default_factory=list) + + # Model + sim_file: Optional[str] = None + prt_file: Optional[str] = None + solver_type: str = "nastran" + + # Design variables + design_variables: List[Dict[str, Any]] = field(default_factory=list) + + # Extractors + extractors: List[Dict[str, Any]] = field(default_factory=list) + + # Objectives + objectives: List[Dict[str, Any]] = field(default_factory=list) + + # Constraints + constraints: List[Dict[str, Any]] = field(default_factory=list) + + # Settings + algorithm: str = "TPE" + max_trials: int = 100 + + def to_spec(self) -> Dict[str, Any]: + """Convert interview data to atomizer_spec.json format""" + # Generate IDs for each element + dvs_with_ids = [] + for i, dv in enumerate(self.design_variables): + dv_copy = dv.copy() + dv_copy['id'] = f"dv_{i+1:03d}" + dv_copy['canvas_position'] = {'x': 50, 'y': 100 + i * 80} + dvs_with_ids.append(dv_copy) + + exts_with_ids = [] + for i, ext in enumerate(self.extractors): + ext_copy = ext.copy() + ext_copy['id'] = f"ext_{i+1:03d}" + ext_copy['canvas_position'] = {'x': 400, 'y': 100 + i * 80} + exts_with_ids.append(ext_copy) + + objs_with_ids = [] + for i, obj in enumerate(self.objectives): + obj_copy = obj.copy() + obj_copy['id'] = f"obj_{i+1:03d}" + obj_copy['canvas_position'] = {'x': 750, 'y': 100 + i * 80} + objs_with_ids.append(obj_copy) + + cons_with_ids = [] + for i, con in enumerate(self.constraints): + con_copy = con.copy() + con_copy['id'] = f"con_{i+1:03d}" + con_copy['canvas_position'] = {'x': 750, 'y': 400 + i * 80} + cons_with_ids.append(con_copy) + + return { + "meta": { + "version": "2.0", + "study_name": self.study_name or "untitled_study", + "description": self.description or "", + "created_at": datetime.now().isoformat(), + "created_by": "interview", + "modified_at": datetime.now().isoformat(), + "modified_by": "interview" + }, + "model": { + "sim": { + "path": self.sim_file or "", + "solver": self.solver_type + } + }, + "design_variables": dvs_with_ids, + "extractors": exts_with_ids, + "objectives": objs_with_ids, + "constraints": cons_with_ids, + "optimization": { + "algorithm": { + "type": self.algorithm + }, + "budget": { + "max_trials": self.max_trials + } + }, + "canvas": { + "edges": [], + "layout_version": "2.0" + } + } + + +class InterviewEngine: + """ + Manages the interview flow for study creation. + + Usage: + 1. Create engine: engine = InterviewEngine() + 2. Start interview: engine.start() + 3. Record answers: engine.record_answer("study_name", "bracket_opt") + 4. Check progress: engine.get_progress() + 5. Generate spec: engine.finalize() + """ + + def __init__(self): + self.state = InterviewState.NOT_STARTED + self.data = InterviewData() + self.questions_asked: List[str] = [] + self.errors: List[str] = [] + + def start(self) -> Dict[str, Any]: + """Start the interview process""" + self.state = InterviewState.GATHERING_BASICS + return { + "state": self.state.value, + "message": "Let's create a new optimization study! I'll guide you through the process.", + "next_questions": self.get_current_questions() + } + + def get_current_questions(self) -> List[Dict[str, Any]]: + """Get the questions for the current interview state""" + questions = { + InterviewState.GATHERING_BASICS: [ + { + "field": "study_name", + "question": "What would you like to name this study?", + "hint": "Use snake_case, e.g., 'bracket_mass_optimization'", + "required": True + }, + { + "field": "category", + "question": "What category should this study be in?", + "hint": "e.g., 'Simple_Bracket', 'M1_Mirror', or leave blank for root", + "required": False + }, + { + "field": "description", + "question": "Briefly describe what you're trying to optimize", + "hint": "e.g., 'Minimize bracket mass while maintaining stiffness'", + "required": True + } + ], + InterviewState.GATHERING_MODEL: [ + { + "field": "sim_file", + "question": "What is the path to your simulation (.sim) file?", + "hint": "Relative path from the study folder, e.g., '1_setup/Model_sim1.sim'", + "required": True + } + ], + InterviewState.GATHERING_VARIABLES: [ + { + "field": "design_variable", + "question": "What parameters do you want to optimize?", + "hint": "Tell me the NX expression names and their bounds", + "required": True, + "multi": True + } + ], + InterviewState.GATHERING_EXTRACTORS: [ + { + "field": "extractor", + "question": "What physics quantities do you want to extract from FEA?", + "hint": "e.g., mass, max displacement, max stress, frequency, Zernike WFE", + "required": True, + "multi": True + } + ], + InterviewState.GATHERING_OBJECTIVES: [ + { + "field": "objective", + "question": "What do you want to optimize?", + "hint": "Tell me which extracted quantities to minimize or maximize", + "required": True, + "multi": True + } + ], + InterviewState.GATHERING_CONSTRAINTS: [ + { + "field": "constraint", + "question": "Do you have any constraints? (e.g., max stress, min frequency)", + "hint": "You can say 'none' if you don't have any", + "required": False, + "multi": True + } + ], + InterviewState.GATHERING_SETTINGS: [ + { + "field": "algorithm", + "question": "Which optimization algorithm would you like to use?", + "hint": "Options: TPE (default), CMA-ES, NSGA-II, RandomSearch", + "required": False + }, + { + "field": "max_trials", + "question": "How many trials (FEA evaluations) should we run?", + "hint": "Default is 100. More trials = better results but longer runtime", + "required": False + } + ], + InterviewState.REVIEW: [ + { + "field": "confirm", + "question": "Does this configuration look correct? (yes/no)", + "required": True + } + ] + } + return questions.get(self.state, []) + + def record_answer(self, field: str, value: Any) -> Dict[str, Any]: + """Record an answer and potentially advance the state""" + self.questions_asked.append(field) + + # Handle different field types + if field == "study_name": + self.data.study_name = value + elif field == "category": + self.data.category = value if value else None + elif field == "description": + self.data.description = value + elif field == "sim_file": + self.data.sim_file = value + elif field == "design_variable": + # Value should be a dict with name, min, max, etc. + if isinstance(value, dict): + self.data.design_variables.append(value) + elif isinstance(value, list): + self.data.design_variables.extend(value) + elif field == "extractor": + if isinstance(value, dict): + self.data.extractors.append(value) + elif isinstance(value, list): + self.data.extractors.extend(value) + elif field == "objective": + if isinstance(value, dict): + self.data.objectives.append(value) + elif isinstance(value, list): + self.data.objectives.extend(value) + elif field == "constraint": + if value and value.lower() not in ["none", "no", "skip"]: + if isinstance(value, dict): + self.data.constraints.append(value) + elif isinstance(value, list): + self.data.constraints.extend(value) + elif field == "algorithm": + if value in ["TPE", "CMA-ES", "NSGA-II", "RandomSearch"]: + self.data.algorithm = value + elif field == "max_trials": + try: + self.data.max_trials = int(value) + except (ValueError, TypeError): + pass + elif field == "confirm": + if value.lower() in ["yes", "y", "confirm", "ok"]: + self.state = InterviewState.COMPLETED + + return { + "state": self.state.value, + "recorded": {field: value}, + "data_so_far": self.get_summary() + } + + def advance_state(self) -> Dict[str, Any]: + """Advance to the next interview state""" + state_order = [ + InterviewState.NOT_STARTED, + InterviewState.GATHERING_BASICS, + InterviewState.GATHERING_MODEL, + InterviewState.GATHERING_VARIABLES, + InterviewState.GATHERING_EXTRACTORS, + InterviewState.GATHERING_OBJECTIVES, + InterviewState.GATHERING_CONSTRAINTS, + InterviewState.GATHERING_SETTINGS, + InterviewState.REVIEW, + InterviewState.COMPLETED + ] + + current_idx = state_order.index(self.state) + if current_idx < len(state_order) - 1: + self.state = state_order[current_idx + 1] + + return { + "state": self.state.value, + "next_questions": self.get_current_questions() + } + + def get_summary(self) -> Dict[str, Any]: + """Get a summary of collected data""" + return { + "study_name": self.data.study_name, + "category": self.data.category, + "description": self.data.description, + "model": self.data.sim_file, + "design_variables": len(self.data.design_variables), + "extractors": len(self.data.extractors), + "objectives": len(self.data.objectives), + "constraints": len(self.data.constraints), + "algorithm": self.data.algorithm, + "max_trials": self.data.max_trials + } + + def get_progress(self) -> Dict[str, Any]: + """Get interview progress information""" + state_progress = { + InterviewState.NOT_STARTED: 0, + InterviewState.GATHERING_BASICS: 15, + InterviewState.GATHERING_MODEL: 25, + InterviewState.GATHERING_VARIABLES: 40, + InterviewState.GATHERING_EXTRACTORS: 55, + InterviewState.GATHERING_OBJECTIVES: 70, + InterviewState.GATHERING_CONSTRAINTS: 80, + InterviewState.GATHERING_SETTINGS: 90, + InterviewState.REVIEW: 95, + InterviewState.COMPLETED: 100 + } + + return { + "state": self.state.value, + "progress_percent": state_progress.get(self.state, 0), + "summary": self.get_summary(), + "current_questions": self.get_current_questions() + } + + def validate(self) -> Dict[str, Any]: + """Validate the collected data before finalizing""" + errors = [] + warnings = [] + + # Required fields + if not self.data.study_name: + errors.append("Study name is required") + + if not self.data.design_variables: + errors.append("At least one design variable is required") + + if not self.data.extractors: + errors.append("At least one extractor is required") + + if not self.data.objectives: + errors.append("At least one objective is required") + + # Warnings + if not self.data.sim_file: + warnings.append("No simulation file specified - you'll need to add one manually") + + if not self.data.constraints: + warnings.append("No constraints defined - optimization will be unconstrained") + + return { + "valid": len(errors) == 0, + "errors": errors, + "warnings": warnings + } + + def finalize(self) -> Dict[str, Any]: + """Generate the final atomizer_spec.json""" + validation = self.validate() + + if not validation["valid"]: + return { + "success": False, + "errors": validation["errors"] + } + + spec = self.data.to_spec() + + return { + "success": True, + "spec": spec, + "warnings": validation.get("warnings", []) + } + + def to_dict(self) -> Dict[str, Any]: + """Serialize engine state for persistence""" + return { + "state": self.state.value, + "data": { + "study_name": self.data.study_name, + "category": self.data.category, + "description": self.data.description, + "goals": self.data.goals, + "sim_file": self.data.sim_file, + "prt_file": self.data.prt_file, + "solver_type": self.data.solver_type, + "design_variables": self.data.design_variables, + "extractors": self.data.extractors, + "objectives": self.data.objectives, + "constraints": self.data.constraints, + "algorithm": self.data.algorithm, + "max_trials": self.data.max_trials + }, + "questions_asked": self.questions_asked, + "errors": self.errors + } + + @classmethod + def from_dict(cls, data: Dict[str, Any]) -> "InterviewEngine": + """Restore engine from serialized state""" + engine = cls() + engine.state = InterviewState(data.get("state", "not_started")) + + d = data.get("data", {}) + engine.data.study_name = d.get("study_name") + engine.data.category = d.get("category") + engine.data.description = d.get("description") + engine.data.goals = d.get("goals", []) + engine.data.sim_file = d.get("sim_file") + engine.data.prt_file = d.get("prt_file") + engine.data.solver_type = d.get("solver_type", "nastran") + engine.data.design_variables = d.get("design_variables", []) + engine.data.extractors = d.get("extractors", []) + engine.data.objectives = d.get("objectives", []) + engine.data.constraints = d.get("constraints", []) + engine.data.algorithm = d.get("algorithm", "TPE") + engine.data.max_trials = d.get("max_trials", 100) + + engine.questions_asked = data.get("questions_asked", []) + engine.errors = data.get("errors", []) + + return engine diff --git a/atomizer-dashboard/backend/api/services/session_manager.py b/atomizer-dashboard/backend/api/services/session_manager.py index 37401cb2..d3a0e072 100644 --- a/atomizer-dashboard/backend/api/services/session_manager.py +++ b/atomizer-dashboard/backend/api/services/session_manager.py @@ -219,6 +219,18 @@ class SessionManager: full_response = result["stdout"] or "" if full_response: + # Check if response contains canvas modifications (from MCP tools) + import logging + logger = logging.getLogger(__name__) + + modifications = self._extract_canvas_modifications(full_response) + logger.info(f"[SEND_MSG] Found {len(modifications)} canvas modifications to send") + + for mod in modifications: + logger.info(f"[SEND_MSG] Sending canvas_modification: {mod.get('action')} {mod.get('nodeType')}") + yield {"type": "canvas_modification", "modification": mod} + + # Always send the text response yield {"type": "text", "content": full_response} if result["returncode"] != 0 and result["stderr"]: @@ -292,6 +304,90 @@ class SessionManager: **({} if not db_record else {"db_record": db_record}), } + def _extract_canvas_modifications(self, response: str) -> List[Dict]: + """ + Extract canvas modification objects from Claude's response. + + MCP tools like canvas_add_node return JSON with a 'modification' field. + This method finds and extracts those modifications so the frontend can apply them. + """ + import re + import logging + logger = logging.getLogger(__name__) + + modifications = [] + + # Debug: log what we're searching + logger.info(f"[CANVAS_MOD] Searching response ({len(response)} chars) for modifications") + + # Check if "modification" even exists in the response + if '"modification"' not in response: + logger.info("[CANVAS_MOD] No 'modification' key found in response") + return modifications + + try: + # Method 1: Look for JSON in code fences + code_block_pattern = r'```(?:json)?\s*([\s\S]*?)```' + for match in re.finditer(code_block_pattern, response): + block_content = match.group(1).strip() + try: + obj = json.loads(block_content) + if isinstance(obj, dict) and 'modification' in obj: + logger.info(f"[CANVAS_MOD] Found modification in code fence: {obj['modification']}") + modifications.append(obj['modification']) + except json.JSONDecodeError: + continue + + # Method 2: Find JSON objects using proper brace matching + # This handles nested objects correctly + i = 0 + while i < len(response): + if response[i] == '{': + # Found a potential JSON start, find matching close + brace_count = 1 + j = i + 1 + in_string = False + escape_next = False + + while j < len(response) and brace_count > 0: + char = response[j] + + if escape_next: + escape_next = False + elif char == '\\': + escape_next = True + elif char == '"' and not escape_next: + in_string = not in_string + elif not in_string: + if char == '{': + brace_count += 1 + elif char == '}': + brace_count -= 1 + j += 1 + + if brace_count == 0: + potential_json = response[i:j] + try: + obj = json.loads(potential_json) + if isinstance(obj, dict) and 'modification' in obj: + mod = obj['modification'] + # Avoid duplicates + if mod not in modifications: + logger.info(f"[CANVAS_MOD] Found inline modification: action={mod.get('action')}, nodeType={mod.get('nodeType')}") + modifications.append(mod) + except json.JSONDecodeError as e: + # Not valid JSON, skip + pass + i = j + else: + i += 1 + + except Exception as e: + logger.error(f"[CANVAS_MOD] Error extracting modifications: {e}") + + logger.info(f"[CANVAS_MOD] Extracted {len(modifications)} modification(s)") + return modifications + def _build_mcp_config(self, mode: Literal["user", "power"]) -> dict: """Build MCP configuration for Claude""" return { diff --git a/atomizer-dashboard/backend/api/services/spec_manager.py b/atomizer-dashboard/backend/api/services/spec_manager.py new file mode 100644 index 00000000..727b28b1 --- /dev/null +++ b/atomizer-dashboard/backend/api/services/spec_manager.py @@ -0,0 +1,747 @@ +""" +SpecManager Service + +Central service for managing AtomizerSpec v2.0. +All spec modifications flow through this service. + +Features: +- Load/save specs with validation +- Atomic writes with conflict detection +- Patch operations with JSONPath support +- Node CRUD operations +- Custom function support +- WebSocket broadcast integration +""" + +import hashlib +import json +import re +import sys +from datetime import datetime, timezone +from pathlib import Path +from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union + +# Add optimization_engine to path if needed +ATOMIZER_ROOT = Path(__file__).parent.parent.parent.parent.parent +if str(ATOMIZER_ROOT) not in sys.path: + sys.path.insert(0, str(ATOMIZER_ROOT)) + +from optimization_engine.config.spec_models import ( + AtomizerSpec, + DesignVariable, + Extractor, + Objective, + Constraint, + CanvasPosition, + CanvasEdge, + ExtractorType, + CustomFunction, + ExtractorOutput, + ValidationReport, +) +from optimization_engine.config.spec_validator import ( + SpecValidator, + SpecValidationError, +) + + +class SpecManagerError(Exception): + """Base error for SpecManager operations.""" + pass + + +class SpecNotFoundError(SpecManagerError): + """Raised when spec file doesn't exist.""" + pass + + +class SpecConflictError(SpecManagerError): + """Raised when spec has been modified by another client.""" + + def __init__(self, message: str, current_hash: str): + super().__init__(message) + self.current_hash = current_hash + + +class WebSocketSubscriber: + """Protocol for WebSocket subscribers.""" + + async def send_json(self, data: Dict[str, Any]) -> None: + """Send JSON data to subscriber.""" + raise NotImplementedError + + +class SpecManager: + """ + Central service for managing AtomizerSpec. + + All modifications go through this service to ensure: + - Validation on every change + - Atomic file writes + - Conflict detection via hashing + - WebSocket broadcast to all clients + """ + + SPEC_FILENAME = "atomizer_spec.json" + + def __init__(self, study_path: Union[str, Path]): + """ + Initialize SpecManager for a study. + + Args: + study_path: Path to the study directory + """ + self.study_path = Path(study_path) + self.spec_path = self.study_path / self.SPEC_FILENAME + self.validator = SpecValidator() + self._subscribers: List[WebSocketSubscriber] = [] + self._last_hash: Optional[str] = None + + # ========================================================================= + # Core CRUD Operations + # ========================================================================= + + def load(self, validate: bool = True) -> AtomizerSpec: + """ + Load and optionally validate the spec. + + Args: + validate: Whether to validate the spec + + Returns: + AtomizerSpec instance + + Raises: + SpecNotFoundError: If spec file doesn't exist + SpecValidationError: If validation fails + """ + if not self.spec_path.exists(): + raise SpecNotFoundError(f"Spec not found: {self.spec_path}") + + with open(self.spec_path, 'r', encoding='utf-8') as f: + data = json.load(f) + + if validate: + self.validator.validate(data, strict=True) + + spec = AtomizerSpec.model_validate(data) + self._last_hash = self._compute_hash(data) + return spec + + def load_raw(self) -> Dict[str, Any]: + """ + Load spec as raw dict without parsing. + + Returns: + Raw spec dict + + Raises: + SpecNotFoundError: If spec file doesn't exist + """ + if not self.spec_path.exists(): + raise SpecNotFoundError(f"Spec not found: {self.spec_path}") + + with open(self.spec_path, 'r', encoding='utf-8') as f: + return json.load(f) + + def save( + self, + spec: Union[AtomizerSpec, Dict[str, Any]], + modified_by: str = "api", + expected_hash: Optional[str] = None + ) -> str: + """ + Save spec with validation and broadcast. + + Args: + spec: Spec to save (AtomizerSpec or dict) + modified_by: Who/what is making the change + expected_hash: If provided, verify current file hash matches + + Returns: + New spec hash + + Raises: + SpecValidationError: If validation fails + SpecConflictError: If expected_hash doesn't match current + """ + # Convert to dict if needed + if isinstance(spec, AtomizerSpec): + data = spec.model_dump(mode='json') + else: + data = spec + + # Check for conflicts if expected_hash provided + if expected_hash and self.spec_path.exists(): + current_hash = self.get_hash() + if current_hash != expected_hash: + raise SpecConflictError( + "Spec was modified by another client", + current_hash=current_hash + ) + + # Update metadata + now = datetime.now(timezone.utc).isoformat().replace('+00:00', 'Z') + data["meta"]["modified"] = now + data["meta"]["modified_by"] = modified_by + + # Validate + self.validator.validate(data, strict=True) + + # Compute new hash + new_hash = self._compute_hash(data) + + # Atomic write (write to temp, then rename) + temp_path = self.spec_path.with_suffix('.tmp') + with open(temp_path, 'w', encoding='utf-8') as f: + json.dump(data, f, indent=2, ensure_ascii=False) + + temp_path.replace(self.spec_path) + + # Update cached hash + self._last_hash = new_hash + + # Broadcast to subscribers + self._broadcast({ + "type": "spec_updated", + "hash": new_hash, + "modified_by": modified_by, + "timestamp": now + }) + + return new_hash + + def exists(self) -> bool: + """Check if spec file exists.""" + return self.spec_path.exists() + + def get_hash(self) -> str: + """Get current spec hash.""" + if not self.spec_path.exists(): + return "" + with open(self.spec_path, 'r', encoding='utf-8') as f: + data = json.load(f) + return self._compute_hash(data) + + def validate_and_report(self) -> ValidationReport: + """ + Run full validation and return detailed report. + + Returns: + ValidationReport with errors, warnings, summary + """ + if not self.spec_path.exists(): + raise SpecNotFoundError(f"Spec not found: {self.spec_path}") + + data = self.load_raw() + return self.validator.validate(data, strict=False) + + # ========================================================================= + # Patch Operations + # ========================================================================= + + def patch( + self, + path: str, + value: Any, + modified_by: str = "api" + ) -> AtomizerSpec: + """ + Apply a JSONPath-style modification. + + Args: + path: JSONPath like "design_variables[0].bounds.max" + value: New value to set + modified_by: Who/what is making the change + + Returns: + Updated AtomizerSpec + """ + data = self.load_raw() + + # Validate the partial update + spec = AtomizerSpec.model_validate(data) + is_valid, errors = self.validator.validate_partial(path, value, spec) + if not is_valid: + raise SpecValidationError(f"Invalid update: {'; '.join(errors)}") + + # Apply the patch + self._apply_patch(data, path, value) + + # Save and return + self.save(data, modified_by) + return self.load(validate=False) + + def _apply_patch(self, data: Dict, path: str, value: Any) -> None: + """ + Apply a patch to the data dict. + + Supports paths like: + - "meta.description" + - "design_variables[0].bounds.max" + - "objectives[1].weight" + """ + parts = self._parse_path(path) + if not parts: + raise ValueError(f"Invalid path: {path}") + + # Navigate to parent + current = data + for part in parts[:-1]: + if isinstance(current, list): + idx = int(part) + current = current[idx] + else: + current = current[part] + + # Set final value + final_key = parts[-1] + if isinstance(current, list): + idx = int(final_key) + current[idx] = value + else: + current[final_key] = value + + def _parse_path(self, path: str) -> List[str]: + """Parse JSONPath into parts.""" + # Handle both dot notation and bracket notation + parts = [] + for part in re.split(r'\.|\[|\]', path): + if part: + parts.append(part) + return parts + + # ========================================================================= + # Node Operations + # ========================================================================= + + def add_node( + self, + node_type: str, + node_data: Dict[str, Any], + modified_by: str = "canvas" + ) -> str: + """ + Add a new node (design var, extractor, objective, constraint). + + Args: + node_type: One of 'designVar', 'extractor', 'objective', 'constraint' + node_data: Node data without ID + modified_by: Who/what is making the change + + Returns: + Generated node ID + """ + data = self.load_raw() + + # Generate ID + node_id = self._generate_id(node_type, data) + node_data["id"] = node_id + + # Add canvas position if not provided + if "canvas_position" not in node_data: + node_data["canvas_position"] = self._auto_position(node_type, data) + + # Add to appropriate section + section = self._get_section_for_type(node_type) + + if section not in data or data[section] is None: + data[section] = [] + + data[section].append(node_data) + + self.save(data, modified_by) + + # Broadcast node addition + self._broadcast({ + "type": "node_added", + "node_type": node_type, + "node_id": node_id, + "modified_by": modified_by + }) + + return node_id + + def update_node( + self, + node_id: str, + updates: Dict[str, Any], + modified_by: str = "canvas" + ) -> None: + """ + Update an existing node. + + Args: + node_id: ID of the node to update + updates: Dict of fields to update + modified_by: Who/what is making the change + """ + data = self.load_raw() + + # Find and update the node + found = False + for section in ["design_variables", "extractors", "objectives", "constraints"]: + if section not in data or data[section] is None: + continue + for node in data[section]: + if node.get("id") == node_id: + node.update(updates) + found = True + break + if found: + break + + if not found: + raise SpecManagerError(f"Node not found: {node_id}") + + self.save(data, modified_by) + + def remove_node( + self, + node_id: str, + modified_by: str = "canvas" + ) -> None: + """ + Remove a node and all edges referencing it. + + Args: + node_id: ID of the node to remove + modified_by: Who/what is making the change + """ + data = self.load_raw() + + # Find and remove node + removed = False + for section in ["design_variables", "extractors", "objectives", "constraints"]: + if section not in data or data[section] is None: + continue + original_len = len(data[section]) + data[section] = [n for n in data[section] if n.get("id") != node_id] + if len(data[section]) < original_len: + removed = True + break + + if not removed: + raise SpecManagerError(f"Node not found: {node_id}") + + # Remove edges referencing this node + if "canvas" in data and data["canvas"] and "edges" in data["canvas"]: + data["canvas"]["edges"] = [ + e for e in data["canvas"]["edges"] + if e.get("source") != node_id and e.get("target") != node_id + ] + + self.save(data, modified_by) + + # Broadcast node removal + self._broadcast({ + "type": "node_removed", + "node_id": node_id, + "modified_by": modified_by + }) + + def update_node_position( + self, + node_id: str, + position: Dict[str, float], + modified_by: str = "canvas" + ) -> None: + """ + Update a node's canvas position. + + Args: + node_id: ID of the node + position: Dict with x, y coordinates + modified_by: Who/what is making the change + """ + self.update_node(node_id, {"canvas_position": position}, modified_by) + + def add_edge( + self, + source: str, + target: str, + modified_by: str = "canvas" + ) -> None: + """ + Add a canvas edge between nodes. + + Args: + source: Source node ID + target: Target node ID + modified_by: Who/what is making the change + """ + data = self.load_raw() + + # Initialize canvas section if needed + if "canvas" not in data or data["canvas"] is None: + data["canvas"] = {} + if "edges" not in data["canvas"] or data["canvas"]["edges"] is None: + data["canvas"]["edges"] = [] + + # Check for duplicate + for edge in data["canvas"]["edges"]: + if edge.get("source") == source and edge.get("target") == target: + return # Already exists + + data["canvas"]["edges"].append({ + "source": source, + "target": target + }) + + self.save(data, modified_by) + + def remove_edge( + self, + source: str, + target: str, + modified_by: str = "canvas" + ) -> None: + """ + Remove a canvas edge. + + Args: + source: Source node ID + target: Target node ID + modified_by: Who/what is making the change + """ + data = self.load_raw() + + if "canvas" in data and data["canvas"] and "edges" in data["canvas"]: + data["canvas"]["edges"] = [ + e for e in data["canvas"]["edges"] + if not (e.get("source") == source and e.get("target") == target) + ] + + self.save(data, modified_by) + + # ========================================================================= + # Custom Function Support + # ========================================================================= + + def add_custom_function( + self, + name: str, + code: str, + outputs: List[str], + description: Optional[str] = None, + modified_by: str = "claude" + ) -> str: + """ + Add a custom extractor function. + + Args: + name: Function name + code: Python source code + outputs: List of output names + description: Optional description + modified_by: Who/what is making the change + + Returns: + Generated extractor ID + + Raises: + SpecValidationError: If Python syntax is invalid + """ + # Validate Python syntax + try: + compile(code, f"", "exec") + except SyntaxError as e: + raise SpecValidationError( + f"Invalid Python syntax: {e.msg} at line {e.lineno}" + ) + + data = self.load_raw() + + # Generate extractor ID + ext_id = self._generate_id("extractor", data) + + # Create extractor + extractor = { + "id": ext_id, + "name": description or f"Custom: {name}", + "type": "custom_function", + "builtin": False, + "function": { + "name": name, + "module": "custom_extractors.dynamic", + "source_code": code + }, + "outputs": [{"name": o, "metric": "custom"} for o in outputs], + "canvas_position": self._auto_position("extractor", data) + } + + data["extractors"].append(extractor) + self.save(data, modified_by) + + return ext_id + + def update_custom_function( + self, + extractor_id: str, + code: Optional[str] = None, + outputs: Optional[List[str]] = None, + modified_by: str = "claude" + ) -> None: + """ + Update an existing custom function. + + Args: + extractor_id: ID of the custom extractor + code: New Python code (optional) + outputs: New outputs (optional) + modified_by: Who/what is making the change + """ + data = self.load_raw() + + # Find the extractor + extractor = None + for ext in data.get("extractors", []): + if ext.get("id") == extractor_id: + extractor = ext + break + + if not extractor: + raise SpecManagerError(f"Extractor not found: {extractor_id}") + + if extractor.get("type") != "custom_function": + raise SpecManagerError(f"Extractor {extractor_id} is not a custom function") + + # Update code + if code is not None: + try: + compile(code, f"", "exec") + except SyntaxError as e: + raise SpecValidationError( + f"Invalid Python syntax: {e.msg} at line {e.lineno}" + ) + if "function" not in extractor: + extractor["function"] = {} + extractor["function"]["source_code"] = code + + # Update outputs + if outputs is not None: + extractor["outputs"] = [{"name": o, "metric": "custom"} for o in outputs] + + self.save(data, modified_by) + + # ========================================================================= + # WebSocket Subscription + # ========================================================================= + + def subscribe(self, subscriber: WebSocketSubscriber) -> None: + """Subscribe to spec changes.""" + if subscriber not in self._subscribers: + self._subscribers.append(subscriber) + + def unsubscribe(self, subscriber: WebSocketSubscriber) -> None: + """Unsubscribe from spec changes.""" + if subscriber in self._subscribers: + self._subscribers.remove(subscriber) + + def _broadcast(self, message: Dict[str, Any]) -> None: + """Broadcast message to all subscribers.""" + import asyncio + + for subscriber in self._subscribers: + try: + # Handle both sync and async contexts + try: + loop = asyncio.get_running_loop() + loop.create_task(subscriber.send_json(message)) + except RuntimeError: + # No running loop, try direct call if possible + pass + except Exception: + # Subscriber may have disconnected + pass + + # ========================================================================= + # Helper Methods + # ========================================================================= + + def _compute_hash(self, data: Dict) -> str: + """Compute hash of spec data for conflict detection.""" + # Sort keys for consistent hashing + json_str = json.dumps(data, sort_keys=True, ensure_ascii=False) + return hashlib.sha256(json_str.encode()).hexdigest()[:16] + + def _generate_id(self, node_type: str, data: Dict) -> str: + """Generate unique ID for a node type.""" + prefix_map = { + "designVar": "dv", + "design_variable": "dv", + "extractor": "ext", + "objective": "obj", + "constraint": "con" + } + prefix = prefix_map.get(node_type, node_type[:3]) + + # Find existing IDs + section = self._get_section_for_type(node_type) + existing_ids: Set[str] = set() + if section in data and data[section]: + existing_ids = {n.get("id", "") for n in data[section]} + + # Generate next available ID + for i in range(1, 1000): + new_id = f"{prefix}_{i:03d}" + if new_id not in existing_ids: + return new_id + + raise SpecManagerError(f"Cannot generate ID for {node_type}: too many nodes") + + def _get_section_for_type(self, node_type: str) -> str: + """Map node type to spec section name.""" + section_map = { + "designVar": "design_variables", + "design_variable": "design_variables", + "extractor": "extractors", + "objective": "objectives", + "constraint": "constraints" + } + return section_map.get(node_type, node_type + "s") + + def _auto_position(self, node_type: str, data: Dict) -> Dict[str, float]: + """Calculate auto position for a new node.""" + # Default x positions by type + x_positions = { + "designVar": 50, + "design_variable": 50, + "extractor": 740, + "objective": 1020, + "constraint": 1020 + } + + x = x_positions.get(node_type, 400) + + # Find max y position for this type + section = self._get_section_for_type(node_type) + max_y = 0 + if section in data and data[section]: + for node in data[section]: + pos = node.get("canvas_position", {}) + y = pos.get("y", 0) + if y > max_y: + max_y = y + + # Place below existing nodes + y = max_y + 100 if max_y > 0 else 100 + + return {"x": x, "y": y} + + +# ========================================================================= +# Factory Function +# ========================================================================= + +def get_spec_manager(study_path: Union[str, Path]) -> SpecManager: + """ + Get a SpecManager instance for a study. + + Args: + study_path: Path to the study directory + + Returns: + SpecManager instance + """ + return SpecManager(study_path) diff --git a/atomizer-dashboard/frontend/src/App.tsx b/atomizer-dashboard/frontend/src/App.tsx index a48fc3d9..636be095 100644 --- a/atomizer-dashboard/frontend/src/App.tsx +++ b/atomizer-dashboard/frontend/src/App.tsx @@ -30,6 +30,7 @@ function App() { {/* Canvas page - full screen, no sidebar */} } /> + } /> {/* Study pages - with sidebar layout */} }> diff --git a/atomizer-dashboard/frontend/src/components/ParallelCoordinatesPlot.tsx b/atomizer-dashboard/frontend/src/components/ParallelCoordinatesPlot.tsx index 1abf894b..7b8c0600 100644 --- a/atomizer-dashboard/frontend/src/components/ParallelCoordinatesPlot.tsx +++ b/atomizer-dashboard/frontend/src/components/ParallelCoordinatesPlot.tsx @@ -26,8 +26,8 @@ interface DesignVariable { name: string; parameter?: string; // Optional: the actual parameter name if different from name unit?: string; - min: number; - max: number; + min?: number; + max?: number; } interface Constraint { diff --git a/atomizer-dashboard/frontend/src/components/ParetoPlot.tsx b/atomizer-dashboard/frontend/src/components/ParetoPlot.tsx index a865ad35..164ed868 100644 --- a/atomizer-dashboard/frontend/src/components/ParetoPlot.tsx +++ b/atomizer-dashboard/frontend/src/components/ParetoPlot.tsx @@ -8,14 +8,15 @@ import { ScatterChart, Scatter, Line, XAxis, YAxis, CartesianGrid, Tooltip, Cell interface ParetoTrial { trial_number: number; - values: [number, number]; + values: number[]; // Support variable number of objectives params: Record; constraint_satisfied?: boolean; } interface Objective { name: string; - type: 'minimize' | 'maximize'; + type?: 'minimize' | 'maximize'; + direction?: 'minimize' | 'maximize'; // Alternative field used by some configs unit?: string; } diff --git a/atomizer-dashboard/frontend/src/components/canvas/index.ts b/atomizer-dashboard/frontend/src/components/canvas/index.ts index 2d8ab409..0f5ff9f2 100644 --- a/atomizer-dashboard/frontend/src/components/canvas/index.ts +++ b/atomizer-dashboard/frontend/src/components/canvas/index.ts @@ -1,5 +1,6 @@ // Main Canvas Component export { AtomizerCanvas } from './AtomizerCanvas'; +export { SpecRenderer } from './SpecRenderer'; // Palette export { NodePalette } from './palette/NodePalette'; diff --git a/atomizer-dashboard/frontend/src/components/chat/ChatMessage.tsx b/atomizer-dashboard/frontend/src/components/chat/ChatMessage.tsx index c18f4262..647c8ad4 100644 --- a/atomizer-dashboard/frontend/src/components/chat/ChatMessage.tsx +++ b/atomizer-dashboard/frontend/src/components/chat/ChatMessage.tsx @@ -5,7 +5,7 @@ import { ToolCallCard, ToolCall } from './ToolCallCard'; export interface Message { id: string; - role: 'user' | 'assistant'; + role: 'user' | 'assistant' | 'system'; content: string; timestamp: Date; isStreaming?: boolean; @@ -18,6 +18,18 @@ interface ChatMessageProps { export const ChatMessage: React.FC = ({ message }) => { const isAssistant = message.role === 'assistant'; + const isSystem = message.role === 'system'; + + // System messages are displayed centered with special styling + if (isSystem) { + return ( +
+
+ {message.content} +
+
+ ); + } return (
= ({ const messagesEndRef = useRef(null); const [isExpanded, setIsExpanded] = useState(false); + // Get canvas state and modification functions from the store + const { nodes, edges, addNode, updateNodeData, selectNode, deleteSelected } = useCanvasStore(); + + // Build canvas state for chat context + const canvasState: CanvasState | null = useMemo(() => { + if (nodes.length === 0) return null; + return { + nodes: nodes.map(n => ({ + id: n.id, + type: n.type, + data: n.data, + position: n.position, + })), + edges: edges.map(e => ({ + id: e.id, + source: e.source, + target: e.target, + })), + studyName: selectedStudy?.name || selectedStudy?.id, + }; + }, [nodes, edges, selectedStudy]); + + // Track position offset for multiple node additions + const nodeAddCountRef = useRef(0); + + // Handle canvas modifications from the assistant + const handleCanvasModification = React.useCallback((modification: CanvasModification) => { + console.log('Canvas modification from assistant:', modification); + + switch (modification.action) { + case 'add_node': + if (modification.nodeType) { + const nodeType = modification.nodeType as NodeType; + // Calculate position: offset each new node so they don't stack + const basePosition = modification.position || { x: 100, y: 100 }; + const offset = nodeAddCountRef.current * 120; + const position = { + x: basePosition.x, + y: basePosition.y + offset, + }; + nodeAddCountRef.current += 1; + // Reset counter after a delay (for batch operations) + setTimeout(() => { nodeAddCountRef.current = 0; }, 2000); + + addNode(nodeType, position, modification.data); + console.log(`Added ${nodeType} node at position:`, position); + } + break; + + case 'update_node': + if (modification.nodeId && modification.data) { + updateNodeData(modification.nodeId, modification.data); + } + break; + + case 'remove_node': + if (modification.nodeId) { + selectNode(modification.nodeId); + deleteSelected(); + } + break; + + // Edge operations would need additional store methods + case 'add_edge': + case 'remove_edge': + console.warn('Edge modification not yet implemented:', modification); + break; + } + }, [addNode, updateNodeData, selectNode, deleteSelected]); + const { messages, isThinking, @@ -41,22 +113,38 @@ export const ChatPane: React.FC = ({ sendMessage, clearMessages, switchMode, + updateCanvasState, } = useChat({ studyId: selectedStudy?.id, mode: 'user', useWebSocket: true, + canvasState, onError: (err) => console.error('Chat error:', err), + onCanvasModification: handleCanvasModification, }); + // Keep canvas state synced with chat + useEffect(() => { + updateCanvasState(canvasState); + }, [canvasState, updateCanvasState]); + // Auto-scroll to bottom when new messages arrive useEffect(() => { messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' }); }, [messages, isThinking]); - // Welcome message based on study context - const welcomeMessage = selectedStudy - ? `Ready to help with **${selectedStudy.name || selectedStudy.id}**. Ask me about optimization progress, results analysis, or how to improve your design.` - : 'Select a study to get started, or ask me to help you create a new one.'; + // Welcome message based on study and canvas context + const welcomeMessage = useMemo(() => { + if (selectedStudy) { + return `Ready to help with **${selectedStudy.name || selectedStudy.id}**. Ask me about optimization progress, results analysis, or how to improve your design.`; + } + if (nodes.length > 0) { + const dvCount = nodes.filter(n => n.type === 'designVar').length; + const objCount = nodes.filter(n => n.type === 'objective').length; + return `I can see your canvas with ${dvCount} design variables and ${objCount} objectives. Ask me to analyze, validate, or create a study from this setup.`; + } + return 'Select a study to get started, or build an optimization in the Canvas Builder.'; + }, [selectedStudy, nodes]); // Collapsed state - just show toggle button if (!isOpen) { diff --git a/atomizer-dashboard/frontend/src/components/chat/ToolCallCard.tsx b/atomizer-dashboard/frontend/src/components/chat/ToolCallCard.tsx index ab8f6028..88d2a8d1 100644 --- a/atomizer-dashboard/frontend/src/components/chat/ToolCallCard.tsx +++ b/atomizer-dashboard/frontend/src/components/chat/ToolCallCard.tsx @@ -30,22 +30,25 @@ interface ToolCallCardProps { } // Map tool names to friendly labels and icons -const TOOL_INFO: Record }> = { +const TOOL_INFO: Record; color?: string }> = { // Study tools list_studies: { label: 'Listing Studies', icon: Database }, get_study_status: { label: 'Getting Status', icon: FileSearch }, - create_study: { label: 'Creating Study', icon: Settings }, + create_study: { label: 'Creating Study', icon: Settings, color: 'text-green-400' }, // Optimization tools - run_optimization: { label: 'Starting Optimization', icon: Play }, + run_optimization: { label: 'Starting Optimization', icon: Play, color: 'text-blue-400' }, stop_optimization: { label: 'Stopping Optimization', icon: XCircle }, get_optimization_status: { label: 'Checking Progress', icon: BarChart2 }, // Analysis tools get_trial_data: { label: 'Querying Trials', icon: Database }, + query_trials: { label: 'Querying Trials', icon: Database }, + get_trial_details: { label: 'Getting Trial Details', icon: FileSearch }, analyze_convergence: { label: 'Analyzing Convergence', icon: BarChart2 }, compare_trials: { label: 'Comparing Trials', icon: BarChart2 }, get_best_design: { label: 'Getting Best Design', icon: CheckCircle }, + get_optimization_summary: { label: 'Getting Summary', icon: BarChart2 }, // Reporting tools generate_report: { label: 'Generating Report', icon: FileText }, @@ -56,6 +59,25 @@ const TOOL_INFO: Record = ({ toolCall }) => { )} {/* Tool icon */} - + {/* Label */} {info.label} diff --git a/atomizer-dashboard/frontend/src/hooks/index.ts b/atomizer-dashboard/frontend/src/hooks/index.ts index 2cac279f..c3280459 100644 --- a/atomizer-dashboard/frontend/src/hooks/index.ts +++ b/atomizer-dashboard/frontend/src/hooks/index.ts @@ -3,3 +3,27 @@ export { useCanvasStore } from './useCanvasStore'; export type { OptimizationConfig } from './useCanvasStore'; export { useCanvasChat } from './useCanvasChat'; export { useIntentParser } from './useIntentParser'; + +// Spec Store (AtomizerSpec v2.0) +export { + useSpecStore, + useSpec, + useSpecLoading, + useSpecError, + useSpecValidation, + useSelectedNodeId, + useSelectedEdgeId, + useSpecHash, + useSpecIsDirty, + useDesignVariables, + useExtractors, + useObjectives, + useConstraints, + useCanvasEdges, + useSelectedNode, +} from './useSpecStore'; + +// WebSocket Sync +export { useSpecWebSocket } from './useSpecWebSocket'; +export type { ConnectionStatus } from './useSpecWebSocket'; +export { ConnectionStatusIndicator } from '../components/canvas/ConnectionStatusIndicator'; diff --git a/atomizer-dashboard/frontend/src/hooks/useChat.ts b/atomizer-dashboard/frontend/src/hooks/useChat.ts index 0c679bac..44851640 100644 --- a/atomizer-dashboard/frontend/src/hooks/useChat.ts +++ b/atomizer-dashboard/frontend/src/hooks/useChat.ts @@ -11,12 +11,25 @@ export interface CanvasState { studyPath?: string; } +export interface CanvasModification { + action: 'add_node' | 'update_node' | 'remove_node' | 'add_edge' | 'remove_edge'; + nodeType?: string; + nodeId?: string; + edgeId?: string; + data?: Record; + source?: string; + target?: string; + position?: { x: number; y: number }; +} + interface UseChatOptions { studyId?: string | null; mode?: ChatMode; useWebSocket?: boolean; canvasState?: CanvasState | null; onError?: (error: string) => void; + onCanvasModification?: (modification: CanvasModification) => void; + onSpecUpdated?: (spec: any) => void; // Called when Claude modifies the spec } interface ChatState { @@ -35,6 +48,8 @@ export function useChat({ useWebSocket = true, canvasState: initialCanvasState, onError, + onCanvasModification, + onSpecUpdated, }: UseChatOptions = {}) { const [state, setState] = useState({ messages: [], @@ -49,6 +64,23 @@ export function useChat({ // Track canvas state for sending with messages const canvasStateRef = useRef(initialCanvasState || null); + // Sync mode prop changes to internal state (triggers WebSocket reconnect) + useEffect(() => { + if (mode !== state.mode) { + console.log(`[useChat] Mode prop changed from ${state.mode} to ${mode}, triggering reconnect`); + // Close existing WebSocket + wsRef.current?.close(); + wsRef.current = null; + // Update internal state to trigger reconnect + setState((prev) => ({ + ...prev, + mode, + sessionId: null, + isConnected: false, + })); + } + }, [mode]); + const abortControllerRef = useRef(null); const conversationHistoryRef = useRef>([]); const wsRef = useRef(null); @@ -82,9 +114,16 @@ export function useChat({ const data = await response.json(); setState((prev) => ({ ...prev, sessionId: data.session_id })); - // Connect WebSocket + // Connect WebSocket - use backend directly in dev mode const protocol = window.location.protocol === 'https:' ? 'wss:' : 'ws:'; - const wsUrl = `${protocol}//${window.location.host}/api/claude/sessions/${data.session_id}/ws`; + // Use port 8001 to match start-dashboard.bat + const backendHost = import.meta.env.DEV ? 'localhost:8001' : window.location.host; + // Both modes use the same WebSocket - mode is handled by session config + // Power mode uses --dangerously-skip-permissions in CLI + // User mode uses --allowedTools to restrict access + const wsPath = `/api/claude/sessions/${data.session_id}/ws`; + const wsUrl = `${protocol}//${backendHost}${wsPath}`; + console.log(`[useChat] Connecting to WebSocket (${state.mode} mode): ${wsUrl}`); const ws = new WebSocket(wsUrl); ws.onopen = () => { @@ -126,6 +165,9 @@ export function useChat({ // Handle WebSocket messages const handleWebSocketMessage = useCallback((data: any) => { + // Debug: log all incoming WebSocket messages + console.log('[useChat] WebSocket message received:', data.type, data); + switch (data.type) { case 'text': currentMessageRef.current += data.content || ''; @@ -212,11 +254,51 @@ export function useChat({ // Canvas state was updated - could show notification break; + case 'canvas_modification': + // Assistant wants to modify the canvas (from MCP tools in user mode) + console.log('[useChat] Received canvas_modification:', data.modification); + if (onCanvasModification && data.modification) { + console.log('[useChat] Calling onCanvasModification callback'); + onCanvasModification(data.modification); + } else { + console.warn('[useChat] canvas_modification received but no handler or modification:', { + hasCallback: !!onCanvasModification, + modification: data.modification + }); + } + break; + + case 'spec_updated': + // Assistant modified the spec - we receive the full updated spec + console.log('[useChat] Spec updated by assistant:', data.tool, data.reason); + if (onSpecUpdated && data.spec) { + // Directly update the canvas with the new spec + onSpecUpdated(data.spec); + } + break; + + case 'spec_modified': + // Legacy: Assistant modified the spec directly (from power mode write tools) + console.log('[useChat] Spec was modified by assistant (legacy):', data.tool, data.changes); + // Treat this as a canvas modification to trigger reload + if (onCanvasModification) { + // Create a synthetic modification event to trigger canvas refresh + onCanvasModification({ + action: 'add_node', // Use add_node as it triggers refresh + data: { + _refresh: true, + tool: data.tool, + changes: data.changes, + }, + }); + } + break; + case 'pong': // Heartbeat response - ignore break; } - }, [onError]); + }, [onError, onCanvasModification]); // Switch mode (requires new session) const switchMode = useCallback(async (newMode: ChatMode) => { @@ -462,6 +544,18 @@ export function useChat({ } }, [useWebSocket]); + // Notify backend when user edits canvas (so Claude sees the changes) + const notifyCanvasEdit = useCallback((spec: any) => { + if (useWebSocket && wsRef.current?.readyState === WebSocket.OPEN) { + wsRef.current.send( + JSON.stringify({ + type: 'canvas_edit', + spec: spec, + }) + ); + } + }, [useWebSocket]); + return { messages: state.messages, isThinking: state.isThinking, @@ -475,5 +569,6 @@ export function useChat({ cancelRequest, switchMode, updateCanvasState, + notifyCanvasEdit, }; } diff --git a/atomizer-dashboard/frontend/src/hooks/useClaudeCode.ts b/atomizer-dashboard/frontend/src/hooks/useClaudeCode.ts new file mode 100644 index 00000000..ca9f8db4 --- /dev/null +++ b/atomizer-dashboard/frontend/src/hooks/useClaudeCode.ts @@ -0,0 +1,349 @@ +/** + * Hook for Claude Code CLI integration + * + * Connects to backend that spawns actual Claude Code CLI processes. + * This gives full power: file editing, command execution, etc. + * + * Unlike useChat (which uses MCP tools), this hook: + * - Spawns actual Claude Code CLI in the backend + * - Has full file system access + * - Can edit files directly (not just return instructions) + * - Uses Opus 4.5 model + * - Has all Claude Code capabilities + */ + +import { useState, useCallback, useRef, useEffect } from 'react'; +import { Message } from '../components/chat/ChatMessage'; +import { useCanvasStore } from './useCanvasStore'; + +export interface CanvasState { + nodes: any[]; + edges: any[]; + studyName?: string; + studyPath?: string; +} + +interface UseClaudeCodeOptions { + studyId?: string | null; + canvasState?: CanvasState | null; + onError?: (error: string) => void; + onCanvasRefresh?: (studyId: string) => void; +} + +interface ClaudeCodeState { + messages: Message[]; + isThinking: boolean; + error: string | null; + sessionId: string | null; + isConnected: boolean; + workingDir: string | null; +} + +export function useClaudeCode({ + studyId, + canvasState: initialCanvasState, + onError, + onCanvasRefresh, +}: UseClaudeCodeOptions = {}) { + const [state, setState] = useState({ + messages: [], + isThinking: false, + error: null, + sessionId: null, + isConnected: false, + workingDir: null, + }); + + // Track canvas state for sending with messages + const canvasStateRef = useRef(initialCanvasState || null); + const wsRef = useRef(null); + const currentMessageRef = useRef(''); + const reconnectAttempts = useRef(0); + const maxReconnectAttempts = 3; + + // Keep canvas state in sync with prop changes + useEffect(() => { + if (initialCanvasState) { + canvasStateRef.current = initialCanvasState; + } + }, [initialCanvasState]); + + // Get canvas store for auto-refresh + const { loadFromConfig } = useCanvasStore(); + + // Connect to Claude Code WebSocket + useEffect(() => { + const connect = () => { + const protocol = window.location.protocol === 'https:' ? 'wss:' : 'ws:'; + // In development, connect directly to backend (bypass Vite proxy for WebSockets) + // Use port 8001 to match start-dashboard.bat + const backendHost = import.meta.env.DEV ? 'localhost:8001' : window.location.host; + + // Use study-specific endpoint if studyId provided + const wsUrl = studyId + ? `${protocol}//${backendHost}/api/claude-code/ws/${encodeURIComponent(studyId)}` + : `${protocol}//${backendHost}/api/claude-code/ws`; + + console.log('[ClaudeCode] Connecting to:', wsUrl); + const ws = new WebSocket(wsUrl); + + ws.onopen = () => { + console.log('[ClaudeCode] Connected'); + setState((prev) => ({ ...prev, isConnected: true, error: null })); + reconnectAttempts.current = 0; + + // If no studyId in URL, send init message + if (!studyId) { + ws.send(JSON.stringify({ type: 'init', study_id: null })); + } + }; + + ws.onclose = () => { + console.log('[ClaudeCode] Disconnected'); + setState((prev) => ({ ...prev, isConnected: false })); + + // Attempt reconnection + if (reconnectAttempts.current < maxReconnectAttempts) { + reconnectAttempts.current++; + console.log(`[ClaudeCode] Reconnecting... attempt ${reconnectAttempts.current}`); + setTimeout(connect, 2000 * reconnectAttempts.current); + } + }; + + ws.onerror = (event) => { + console.error('[ClaudeCode] WebSocket error:', event); + setState((prev) => ({ ...prev, isConnected: false })); + onError?.('Claude Code connection error'); + }; + + ws.onmessage = (event) => { + try { + const data = JSON.parse(event.data); + handleWebSocketMessage(data); + } catch (e) { + console.error('[ClaudeCode] Failed to parse message:', e); + } + }; + + wsRef.current = ws; + }; + + connect(); + + return () => { + reconnectAttempts.current = maxReconnectAttempts; // Prevent reconnection on unmount + wsRef.current?.close(); + wsRef.current = null; + }; + }, [studyId]); + + // Handle WebSocket messages + const handleWebSocketMessage = useCallback( + (data: any) => { + switch (data.type) { + case 'initialized': + console.log('[ClaudeCode] Session initialized:', data.session_id); + setState((prev) => ({ + ...prev, + sessionId: data.session_id, + workingDir: data.working_dir || null, + })); + break; + + case 'text': + currentMessageRef.current += data.content || ''; + setState((prev) => ({ + ...prev, + messages: prev.messages.map((msg, idx) => + idx === prev.messages.length - 1 && msg.role === 'assistant' + ? { ...msg, content: currentMessageRef.current } + : msg + ), + })); + break; + + case 'done': + setState((prev) => ({ + ...prev, + isThinking: false, + messages: prev.messages.map((msg, idx) => + idx === prev.messages.length - 1 && msg.role === 'assistant' + ? { ...msg, isStreaming: false } + : msg + ), + })); + currentMessageRef.current = ''; + break; + + case 'error': + console.error('[ClaudeCode] Error:', data.content); + setState((prev) => ({ + ...prev, + isThinking: false, + error: data.content || 'Unknown error', + })); + onError?.(data.content || 'Unknown error'); + currentMessageRef.current = ''; + break; + + case 'refresh_canvas': + // Claude made file changes - trigger canvas refresh + console.log('[ClaudeCode] Canvas refresh requested:', data.reason); + if (data.study_id) { + onCanvasRefresh?.(data.study_id); + reloadCanvasFromStudy(data.study_id); + } + break; + + case 'canvas_updated': + console.log('[ClaudeCode] Canvas state updated'); + break; + + case 'pong': + // Heartbeat response + break; + + default: + console.log('[ClaudeCode] Unknown message type:', data.type); + } + }, + [onError, onCanvasRefresh] + ); + + // Reload canvas from study config + const reloadCanvasFromStudy = useCallback( + async (studyIdToReload: string) => { + try { + console.log('[ClaudeCode] Reloading canvas for study:', studyIdToReload); + + // Fetch fresh config from backend + const response = await fetch(`/api/optimization/studies/${encodeURIComponent(studyIdToReload)}/config`); + if (!response.ok) { + throw new Error(`Failed to fetch config: ${response.status}`); + } + + const data = await response.json(); + const config = data.config; // API returns { config: ..., path: ..., study_id: ... } + + // Reload canvas with new config + loadFromConfig(config); + + // Add system message about refresh + const refreshMessage: Message = { + id: `msg_${Date.now()}_refresh`, + role: 'system', + content: `Canvas refreshed with latest changes from ${studyIdToReload}`, + timestamp: new Date(), + }; + + setState((prev) => ({ + ...prev, + messages: [...prev.messages, refreshMessage], + })); + } catch (error) { + console.error('[ClaudeCode] Failed to reload canvas:', error); + } + }, + [loadFromConfig] + ); + + const generateMessageId = () => { + return `msg_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`; + }; + + const sendMessage = useCallback( + async (content: string) => { + if (!content.trim() || state.isThinking) return; + + if (!wsRef.current || wsRef.current.readyState !== WebSocket.OPEN) { + onError?.('Not connected to Claude Code'); + return; + } + + // Add user message + const userMessage: Message = { + id: generateMessageId(), + role: 'user', + content: content.trim(), + timestamp: new Date(), + }; + + // Add assistant message placeholder + const assistantMessage: Message = { + id: generateMessageId(), + role: 'assistant', + content: '', + timestamp: new Date(), + isStreaming: true, + }; + + setState((prev) => ({ + ...prev, + messages: [...prev.messages, userMessage, assistantMessage], + isThinking: true, + error: null, + })); + + // Reset current message tracking + currentMessageRef.current = ''; + + // Send message via WebSocket with canvas state + wsRef.current.send( + JSON.stringify({ + type: 'message', + content: content.trim(), + canvas_state: canvasStateRef.current || undefined, + }) + ); + }, + [state.isThinking, onError] + ); + + const clearMessages = useCallback(() => { + setState((prev) => ({ + ...prev, + messages: [], + error: null, + })); + currentMessageRef.current = ''; + }, []); + + // Update canvas state (call this when canvas changes) + const updateCanvasState = useCallback((newCanvasState: CanvasState | null) => { + canvasStateRef.current = newCanvasState; + + // Also send to backend to update context + if (wsRef.current?.readyState === WebSocket.OPEN) { + wsRef.current.send( + JSON.stringify({ + type: 'set_canvas', + canvas_state: newCanvasState, + }) + ); + } + }, []); + + // Send ping to keep connection alive + useEffect(() => { + const pingInterval = setInterval(() => { + if (wsRef.current?.readyState === WebSocket.OPEN) { + wsRef.current.send(JSON.stringify({ type: 'ping' })); + } + }, 30000); // Every 30 seconds + + return () => clearInterval(pingInterval); + }, []); + + return { + messages: state.messages, + isThinking: state.isThinking, + error: state.error, + sessionId: state.sessionId, + isConnected: state.isConnected, + workingDir: state.workingDir, + sendMessage, + clearMessages, + updateCanvasState, + reloadCanvasFromStudy, + }; +} diff --git a/atomizer-dashboard/frontend/src/hooks/useSpecWebSocket.ts b/atomizer-dashboard/frontend/src/hooks/useSpecWebSocket.ts new file mode 100644 index 00000000..b71d1b2c --- /dev/null +++ b/atomizer-dashboard/frontend/src/hooks/useSpecWebSocket.ts @@ -0,0 +1,288 @@ +/** + * useSpecWebSocket - WebSocket connection for real-time spec sync + * + * Connects to the backend WebSocket endpoint for live spec updates. + * Handles auto-reconnection, message parsing, and store updates. + * + * P2.11-P2.14: WebSocket sync implementation + */ + +import { useEffect, useRef, useCallback, useState } from 'react'; +import { useSpecStore } from './useSpecStore'; + +// ============================================================================ +// Types +// ============================================================================ + +export type ConnectionStatus = 'disconnected' | 'connecting' | 'connected' | 'reconnecting'; + +interface SpecWebSocketMessage { + type: 'modification' | 'full_sync' | 'error' | 'ping'; + payload: unknown; +} + +interface ModificationPayload { + operation: 'set' | 'add' | 'remove'; + path: string; + value?: unknown; + modified_by: string; + timestamp: string; + hash: string; +} + +interface ErrorPayload { + message: string; + code?: string; +} + +interface UseSpecWebSocketOptions { + /** + * Enable auto-reconnect on disconnect (default: true) + */ + autoReconnect?: boolean; + + /** + * Reconnect delay in ms (default: 3000) + */ + reconnectDelay?: number; + + /** + * Max reconnect attempts (default: 10) + */ + maxReconnectAttempts?: number; + + /** + * Client identifier for tracking modifications (default: 'canvas') + */ + clientId?: string; +} + +interface UseSpecWebSocketReturn { + /** + * Current connection status + */ + status: ConnectionStatus; + + /** + * Manually disconnect + */ + disconnect: () => void; + + /** + * Manually reconnect + */ + reconnect: () => void; + + /** + * Send a message to the WebSocket (for future use) + */ + send: (message: SpecWebSocketMessage) => void; + + /** + * Last error message if any + */ + lastError: string | null; +} + +// ============================================================================ +// Hook +// ============================================================================ + +export function useSpecWebSocket( + studyId: string | null, + options: UseSpecWebSocketOptions = {} +): UseSpecWebSocketReturn { + const { + autoReconnect = true, + reconnectDelay = 3000, + maxReconnectAttempts = 10, + clientId = 'canvas', + } = options; + + const wsRef = useRef(null); + const reconnectAttemptsRef = useRef(0); + const reconnectTimeoutRef = useRef | null>(null); + + const [status, setStatus] = useState('disconnected'); + const [lastError, setLastError] = useState(null); + + // Get store actions + const reloadSpec = useSpecStore((s) => s.reloadSpec); + const setError = useSpecStore((s) => s.setError); + + // Build WebSocket URL + const getWsUrl = useCallback((id: string): string => { + const protocol = window.location.protocol === 'https:' ? 'wss:' : 'ws:'; + const host = window.location.host; + return `${protocol}//${host}/api/studies/${encodeURIComponent(id)}/spec/sync?client_id=${clientId}`; + }, [clientId]); + + // Handle incoming messages + const handleMessage = useCallback((event: MessageEvent) => { + try { + const message: SpecWebSocketMessage = JSON.parse(event.data); + + switch (message.type) { + case 'modification': { + const payload = message.payload as ModificationPayload; + + // Skip if this is our own modification + if (payload.modified_by === clientId) { + return; + } + + // Reload spec to get latest state + // In a more sophisticated implementation, we could apply the patch locally + reloadSpec().catch((err) => { + console.error('Failed to reload spec after modification:', err); + }); + break; + } + + case 'full_sync': { + // Full spec sync requested (e.g., after reconnect) + reloadSpec().catch((err) => { + console.error('Failed to reload spec during full_sync:', err); + }); + break; + } + + case 'error': { + const payload = message.payload as ErrorPayload; + console.error('WebSocket error:', payload.message); + setLastError(payload.message); + setError(payload.message); + break; + } + + case 'ping': { + // Keep-alive ping, respond with pong + if (wsRef.current?.readyState === WebSocket.OPEN) { + wsRef.current.send(JSON.stringify({ type: 'pong' })); + } + break; + } + + default: + console.warn('Unknown WebSocket message type:', message.type); + } + } catch (error) { + console.error('Failed to parse WebSocket message:', error); + } + }, [clientId, reloadSpec, setError]); + + // Connect to WebSocket + const connect = useCallback(() => { + if (!studyId) return; + + // Clean up existing connection + if (wsRef.current) { + wsRef.current.close(); + } + + setStatus('connecting'); + setLastError(null); + + const url = getWsUrl(studyId); + const ws = new WebSocket(url); + + ws.onopen = () => { + setStatus('connected'); + reconnectAttemptsRef.current = 0; + }; + + ws.onmessage = handleMessage; + + ws.onerror = (event) => { + console.error('WebSocket error:', event); + setLastError('WebSocket connection error'); + }; + + ws.onclose = (_event) => { + setStatus('disconnected'); + + // Check if we should reconnect + if (autoReconnect && reconnectAttemptsRef.current < maxReconnectAttempts) { + reconnectAttemptsRef.current++; + setStatus('reconnecting'); + + // Clear any existing reconnect timeout + if (reconnectTimeoutRef.current) { + clearTimeout(reconnectTimeoutRef.current); + } + + // Schedule reconnect with exponential backoff + const delay = reconnectDelay * Math.min(reconnectAttemptsRef.current, 5); + reconnectTimeoutRef.current = setTimeout(() => { + connect(); + }, delay); + } else if (reconnectAttemptsRef.current >= maxReconnectAttempts) { + setLastError('Max reconnection attempts reached'); + } + }; + + wsRef.current = ws; + }, [studyId, getWsUrl, handleMessage, autoReconnect, reconnectDelay, maxReconnectAttempts]); + + // Disconnect + const disconnect = useCallback(() => { + // Clear reconnect timeout + if (reconnectTimeoutRef.current) { + clearTimeout(reconnectTimeoutRef.current); + reconnectTimeoutRef.current = null; + } + + // Close WebSocket + if (wsRef.current) { + wsRef.current.close(); + wsRef.current = null; + } + + reconnectAttemptsRef.current = maxReconnectAttempts; // Prevent auto-reconnect + setStatus('disconnected'); + }, [maxReconnectAttempts]); + + // Reconnect + const reconnect = useCallback(() => { + reconnectAttemptsRef.current = 0; + connect(); + }, [connect]); + + // Send message + const send = useCallback((message: SpecWebSocketMessage) => { + if (wsRef.current?.readyState === WebSocket.OPEN) { + wsRef.current.send(JSON.stringify(message)); + } else { + console.warn('WebSocket not connected, cannot send message'); + } + }, []); + + // Connect when studyId changes + useEffect(() => { + if (studyId) { + connect(); + } else { + disconnect(); + } + + return () => { + // Cleanup on unmount or studyId change + if (reconnectTimeoutRef.current) { + clearTimeout(reconnectTimeoutRef.current); + } + if (wsRef.current) { + wsRef.current.close(); + } + }; + }, [studyId, connect, disconnect]); + + return { + status, + disconnect, + reconnect, + send, + lastError, + }; +} + +export default useSpecWebSocket; diff --git a/atomizer-dashboard/frontend/src/hooks/useWebSocket.ts b/atomizer-dashboard/frontend/src/hooks/useWebSocket.ts index 3f248469..97e47d73 100644 --- a/atomizer-dashboard/frontend/src/hooks/useWebSocket.ts +++ b/atomizer-dashboard/frontend/src/hooks/useWebSocket.ts @@ -18,7 +18,8 @@ export const useOptimizationWebSocket = ({ studyId, onMessage }: UseOptimization const host = window.location.host; // This will be localhost:3000 in dev // If using proxy in vite.config.ts, this works. // If not, we might need to hardcode backend URL for dev: - const backendHost = import.meta.env.DEV ? 'localhost:8000' : host; + // Use port 8001 to match start-dashboard.bat + const backendHost = import.meta.env.DEV ? 'localhost:8001' : host; setSocketUrl(`${protocol}//${backendHost}/api/ws/optimization/${studyId}`); } else { diff --git a/atomizer-dashboard/frontend/src/pages/Analysis.tsx b/atomizer-dashboard/frontend/src/pages/Analysis.tsx index d174b253..93c4ac69 100644 --- a/atomizer-dashboard/frontend/src/pages/Analysis.tsx +++ b/atomizer-dashboard/frontend/src/pages/Analysis.tsx @@ -1,4 +1,4 @@ -import { useState, useEffect, lazy, Suspense, useMemo } from 'react'; +import { useState, useEffect, useMemo } from 'react'; import { useNavigate } from 'react-router-dom'; import { BarChart3, @@ -14,25 +14,10 @@ import { } from 'lucide-react'; import { useStudy } from '../context/StudyContext'; import { Card } from '../components/common/Card'; - -// Lazy load charts -const PlotlyParetoPlot = lazy(() => import('../components/plotly/PlotlyParetoPlot').then(m => ({ default: m.PlotlyParetoPlot }))); -const PlotlyParallelCoordinates = lazy(() => import('../components/plotly/PlotlyParallelCoordinates').then(m => ({ default: m.PlotlyParallelCoordinates }))); -const PlotlyParameterImportance = lazy(() => import('../components/plotly/PlotlyParameterImportance').then(m => ({ default: m.PlotlyParameterImportance }))); -const PlotlyConvergencePlot = lazy(() => import('../components/plotly/PlotlyConvergencePlot').then(m => ({ default: m.PlotlyConvergencePlot }))); -const PlotlyCorrelationHeatmap = lazy(() => import('../components/plotly/PlotlyCorrelationHeatmap').then(m => ({ default: m.PlotlyCorrelationHeatmap }))); -const PlotlyFeasibilityChart = lazy(() => import('../components/plotly/PlotlyFeasibilityChart').then(m => ({ default: m.PlotlyFeasibilityChart }))); -const PlotlySurrogateQuality = lazy(() => import('../components/plotly/PlotlySurrogateQuality').then(m => ({ default: m.PlotlySurrogateQuality }))); -const PlotlyRunComparison = lazy(() => import('../components/plotly/PlotlyRunComparison').then(m => ({ default: m.PlotlyRunComparison }))); - -const ChartLoading = () => ( -
-
-
- Loading chart... -
-
-); +import { ConvergencePlot } from '../components/ConvergencePlot'; +import { ParameterImportanceChart } from '../components/ParameterImportanceChart'; +import { ParallelCoordinatesPlot } from '../components/ParallelCoordinatesPlot'; +import { ParetoPlot } from '../components/ParetoPlot'; const NoData = ({ message = 'No data available' }: { message?: string }) => (
@@ -383,15 +368,12 @@ export default function Analysis() { {/* Convergence Plot */} {trials.length > 0 && ( - }> - - + )} @@ -455,30 +437,24 @@ export default function Analysis() { {/* Parameter Importance */} {trials.length > 0 && metadata?.design_variables && ( - }> - - + )} {/* Parallel Coordinates */} {trials.length > 0 && metadata && ( - }> - - + )}
@@ -508,14 +484,11 @@ export default function Analysis() { {/* Pareto Front Plot */} {paretoFront.length > 0 && ( - }> - - + )} @@ -550,16 +523,10 @@ export default function Analysis() { {/* Correlations Tab */} {activeTab === 'correlations' && (
- {/* Correlation Heatmap */} + {/* Correlation Analysis */} {trials.length > 2 && ( - - }> - - + + )} @@ -612,11 +579,22 @@ export default function Analysis() {
- {/* Feasibility Over Time Chart */} - - }> - - + {/* Feasibility Summary */} + +
+
+
+
+
+ {stats.feasibilityRate.toFixed(1)}% +
+

+ {stats.feasible} of {stats.total} trials satisfy all constraints +

+
{/* Infeasible Trials List */} @@ -683,11 +661,38 @@ export default function Analysis() {
- {/* Surrogate Quality Charts */} - - }> - - + {/* Surrogate Performance Summary */} + +
+
+

Trial Distribution

+
+
+
+ FEA: {stats.feaTrials} trials + + {((stats.feaTrials / stats.total) * 100).toFixed(0)}% + +
+
+
+ NN: {stats.nnTrials} trials + + {((stats.nnTrials / stats.total) * 100).toFixed(0)}% + +
+
+
+
+

Efficiency Gains

+
+
+ {stats.feaTrials > 0 ? `${(stats.total / stats.feaTrials).toFixed(1)}x` : '1.0x'} +
+
Effective Speedup
+
+
+
)} @@ -700,9 +705,36 @@ export default function Analysis() { Compare different optimization runs within this study. Studies with adaptive optimization may have multiple runs (e.g., initial FEA exploration, NN-accelerated iterations).

- }> - - +
+ + + + + + + + + + + + {runs.map((run) => ( + + + + + + + + ))} + +
RunSourceTrialsBest ValueAvg Value
{run.name || `Run ${run.run_id}`} + + {run.source} + + {run.trial_count}{run.best_value?.toExponential(4) || 'N/A'}{run.avg_value?.toExponential(4) || 'N/A'}
+
)} diff --git a/atomizer-dashboard/frontend/src/pages/Dashboard.tsx b/atomizer-dashboard/frontend/src/pages/Dashboard.tsx index a7359aa2..3995a942 100644 --- a/atomizer-dashboard/frontend/src/pages/Dashboard.tsx +++ b/atomizer-dashboard/frontend/src/pages/Dashboard.tsx @@ -1,4 +1,4 @@ -import { useState, useEffect, lazy, Suspense, useRef } from 'react'; +import { useState, useEffect, useRef } from 'react'; import { useNavigate } from 'react-router-dom'; import { Settings } from 'lucide-react'; import { useOptimizationWebSocket } from '../hooks/useWebSocket'; @@ -21,19 +21,6 @@ import { CurrentTrialPanel, OptimizerStatePanel } from '../components/tracker'; import { NivoParallelCoordinates } from '../components/charts'; import type { Trial } from '../types'; -// Lazy load Plotly components for better initial load performance -const PlotlyParallelCoordinates = lazy(() => import('../components/plotly/PlotlyParallelCoordinates').then(m => ({ default: m.PlotlyParallelCoordinates }))); -const PlotlyParetoPlot = lazy(() => import('../components/plotly/PlotlyParetoPlot').then(m => ({ default: m.PlotlyParetoPlot }))); -const PlotlyConvergencePlot = lazy(() => import('../components/plotly/PlotlyConvergencePlot').then(m => ({ default: m.PlotlyConvergencePlot }))); -const PlotlyParameterImportance = lazy(() => import('../components/plotly/PlotlyParameterImportance').then(m => ({ default: m.PlotlyParameterImportance }))); - -// Loading placeholder for lazy components -const ChartLoading = () => ( -
-
Loading chart...
-
-); - export default function Dashboard() { const navigate = useNavigate(); const { selectedStudy, refreshStudies, isInitialized } = useStudy(); @@ -62,8 +49,8 @@ export default function Dashboard() { const [paretoFront, setParetoFront] = useState([]); const [allTrialsRaw, setAllTrialsRaw] = useState([]); // All trials for parallel coordinates - // Chart library toggle: 'nivo' (dark theme, default), 'plotly' (more interactive), or 'recharts' (simple) - const [chartLibrary, setChartLibrary] = useState<'nivo' | 'plotly' | 'recharts'>('nivo'); + // Chart library toggle: 'nivo' (dark theme, default) or 'recharts' (simple) + const [chartLibrary, setChartLibrary] = useState<'nivo' | 'recharts'>('nivo'); // Process status for tracker panels const [isRunning, setIsRunning] = useState(false); @@ -464,18 +451,7 @@ export default function Dashboard() { }`} title="Modern Nivo charts with dark theme (recommended)" > - Nivo - - +
+ + +
{/* Study Quick Stats */} diff --git a/atomizer-dashboard/frontend/src/pages/Insights.tsx b/atomizer-dashboard/frontend/src/pages/Insights.tsx index b43d8f84..32c6a651 100644 --- a/atomizer-dashboard/frontend/src/pages/Insights.tsx +++ b/atomizer-dashboard/frontend/src/pages/Insights.tsx @@ -20,11 +20,11 @@ import { ExternalLink, Zap, List, - LucideIcon + LucideIcon, + FileText } from 'lucide-react'; import { useStudy } from '../context/StudyContext'; import { Card } from '../components/common/Card'; -import Plot from 'react-plotly.js'; // ============================================================================ // Types @@ -642,13 +642,15 @@ export default function Insights() { Open Full View )} - + {activeInsight.html_path && ( + + )} @@ -674,49 +676,43 @@ export default function Insights() { )} - {/* Plotly Figure */} + {/* Insight Result */} - {activeInsight.plotly_figure ? ( -
- -
- ) : ( -
- -

Insight Generated Successfully

+
+ +

Insight Generated Successfully

+ {activeInsight.html_path ? ( + <> +

+ Click the button below to view the interactive visualization. +

+ + + ) : (

- This insight generates HTML files. Click "Open Full View" to see the visualization. + The visualization has been generated. Check the study's insights folder.

- {activeInsight.summary?.html_files && ( -
-

Generated files:

-
    - {(activeInsight.summary.html_files as string[]).slice(0, 4).map((f: string, i: number) => ( -
  • - {f.split(/[/\\]/).pop()} -
    • - ))} -
-
- )} -
- )} + )} + {activeInsight.summary?.html_files && ( +
+

Generated files:

+
    + {(activeInsight.summary.html_files as string[]).slice(0, 4).map((f: string, i: number) => ( +
  • + + {f.split(/[/\\]/).pop()} +
    • + ))} +
+
+ )} +
{/* Generate Another */} @@ -736,8 +732,8 @@ export default function Insights() { )} - {/* Fullscreen Modal */} - {fullscreen && activeInsight?.plotly_figure && ( + {/* Fullscreen Modal - now opens external HTML */} + {fullscreen && activeInsight && (

@@ -750,23 +746,24 @@ export default function Insights() {

-
- +
+ {activeInsight.html_path ? ( +