feat: Phase 2 - LLM Integration for Canvas

- Add canvas.ts MCP tool with validate_canvas_intent, execute_canvas_intent, interpret_canvas_intent
- Add useCanvasChat.ts bridge hook connecting canvas to chat system
- Update context_builder.py with canvas tool instructions
- Add ExecuteDialog for study name input
- Add ChatPanel for canvas-integrated Claude responses
- Connect AtomizerCanvas to Claude via useCanvasChat

Canvas workflow now:
1. Build graph visually
2. Click Validate/Analyze/Execute
3. Claude processes intent via MCP tools
4. Response shown in integrated chat panel

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
2026-01-14 20:18:46 -05:00
parent 7919511bb2
commit 1ae35382da
8 changed files with 1051 additions and 11 deletions

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@@ -235,4 +235,12 @@ Available tools:
- `get_trial_data`, `analyze_convergence`, `compare_trials`, `get_best_design`
- `generate_report`, `export_data`
- `explain_physics`, `recommend_method`, `query_extractors`
**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
- `interpret_canvas_intent` - Analyze intent and provide recommendations
When you receive a message containing "INTENT:" followed by JSON, this is from the Canvas UI.
Parse the intent and use the appropriate canvas tool to process it.
"""

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@@ -1,4 +1,4 @@
import { useCallback, useRef, DragEvent } from 'react';
import { useCallback, useRef, useState, DragEvent } from 'react';
import ReactFlow, {
Background,
Controls,
@@ -12,12 +12,17 @@ import { nodeTypes } from './nodes';
import { NodePalette } from './palette/NodePalette';
import { NodeConfigPanel } from './panels/NodeConfigPanel';
import { ValidationPanel } from './panels/ValidationPanel';
import { ExecuteDialog } from './panels/ExecuteDialog';
import { useCanvasStore } from '../../hooks/useCanvasStore';
import { useCanvasChat } from '../../hooks/useCanvasChat';
import { NodeType } from '../../lib/canvas/schema';
import { ChatPanel } from './panels/ChatPanel';
function CanvasFlow() {
const reactFlowWrapper = useRef<HTMLDivElement>(null);
const reactFlowInstance = useRef<ReactFlowInstance | null>(null);
const [showExecuteDialog, setShowExecuteDialog] = useState(false);
const [showChat, setShowChat] = useState(false);
const {
nodes,
@@ -33,6 +38,18 @@ function CanvasFlow() {
toIntent,
} = useCanvasStore();
const {
messages,
isThinking,
isExecuting,
isConnected,
executeIntent,
validateIntent,
analyzeIntent,
} = useCanvasChat({
onError: (error) => console.error('Canvas chat error:', error),
});
const onDragOver = useCallback((event: DragEvent) => {
event.preventDefault();
event.dataTransfer.dropEffect = 'move';
@@ -67,17 +84,39 @@ function CanvasFlow() {
selectNode(null);
}, [selectNode]);
const handleExecute = () => {
const handleValidate = () => {
const result = validate();
if (result.valid) {
// Also send to Claude for intelligent feedback
const intent = toIntent();
validateIntent(intent);
setShowChat(true);
}
};
const handleAnalyze = () => {
const result = validate();
if (result.valid) {
const intent = toIntent();
// Send to chat
console.log('Executing intent:', JSON.stringify(intent, null, 2));
// TODO: Connect to useChat hook
alert('Intent generated! Check console for JSON output.\n\nIn Phase 2, this will be sent to Claude.');
analyzeIntent(intent);
setShowChat(true);
}
};
const handleExecuteClick = () => {
const result = validate();
if (result.valid) {
setShowExecuteDialog(true);
}
};
const handleExecute = async (studyName: string, autoRun: boolean) => {
const intent = toIntent();
await executeIntent(intent, studyName, autoRun);
setShowExecuteDialog(false);
setShowChat(true);
};
return (
<div className="flex h-full">
{/* Left: Node Palette */}
@@ -104,16 +143,38 @@ function CanvasFlow() {
<MiniMap />
</ReactFlow>
{/* Execute Button */}
{/* Action Buttons */}
<div className="absolute bottom-4 right-4 flex gap-2 z-10">
<button
onClick={validate}
onClick={() => setShowChat(!showChat)}
className={`px-3 py-2 rounded-lg transition-colors ${
showChat
? 'bg-blue-100 text-blue-700'
: 'bg-gray-100 text-gray-600 hover:bg-gray-200'
}`}
title="Toggle Chat"
>
{isConnected ? '💬' : '🔌'}
</button>
<button
onClick={handleValidate}
className="px-4 py-2 bg-gray-600 text-white rounded-lg hover:bg-gray-700 transition-colors"
>
Validate
</button>
<button
onClick={handleExecute}
onClick={handleAnalyze}
disabled={!validation.valid}
className={`px-4 py-2 rounded-lg transition-colors ${
validation.valid
? 'bg-purple-600 text-white hover:bg-purple-700'
: 'bg-gray-300 text-gray-500 cursor-not-allowed'
}`}
>
Analyze
</button>
<button
onClick={handleExecuteClick}
disabled={!validation.valid}
className={`px-4 py-2 rounded-lg transition-colors ${
validation.valid
@@ -131,8 +192,34 @@ function CanvasFlow() {
)}
</div>
{/* Right: Config Panel */}
{selectedNode && <NodeConfigPanel nodeId={selectedNode} />}
{/* Right: Config Panel or Chat */}
{showChat ? (
<div className="w-96 border-l border-gray-200 flex flex-col bg-white">
<div className="p-3 border-b border-gray-200 flex justify-between items-center">
<h3 className="font-semibold text-gray-800">Claude Assistant</h3>
<button
onClick={() => setShowChat(false)}
className="text-gray-500 hover:text-gray-700"
>
</button>
</div>
<ChatPanel
messages={messages}
isThinking={isThinking || isExecuting}
/>
</div>
) : selectedNode ? (
<NodeConfigPanel nodeId={selectedNode} />
) : null}
{/* Execute Dialog */}
<ExecuteDialog
isOpen={showExecuteDialog}
onClose={() => setShowExecuteDialog(false)}
onExecute={handleExecute}
isExecuting={isExecuting}
/>
</div>
);
}

View File

@@ -2,4 +2,6 @@ export { AtomizerCanvas } from './AtomizerCanvas';
export { NodePalette } from './palette/NodePalette';
export { NodeConfigPanel } from './panels/NodeConfigPanel';
export { ValidationPanel } from './panels/ValidationPanel';
export { ExecuteDialog } from './panels/ExecuteDialog';
export { ChatPanel } from './panels/ChatPanel';
export * from './nodes';

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@@ -0,0 +1,48 @@
/**
* Chat Panel for Canvas - Displays messages from Claude
*/
import { useRef, useEffect } from 'react';
import { Message, ChatMessage } from '../../chat/ChatMessage';
import { ThinkingIndicator } from '../../chat/ThinkingIndicator';
interface ChatPanelProps {
messages: Message[];
isThinking: boolean;
}
export function ChatPanel({ messages, isThinking }: ChatPanelProps) {
const messagesEndRef = useRef<HTMLDivElement>(null);
// Auto-scroll to bottom when new messages arrive
useEffect(() => {
messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' });
}, [messages, isThinking]);
return (
<div className="flex-1 overflow-y-auto p-4 space-y-4 bg-gray-50">
{/* Welcome message if no messages */}
{messages.length === 0 && !isThinking && (
<div className="text-center py-8">
<div className="w-12 h-12 rounded-xl bg-blue-100 flex items-center justify-center mx-auto mb-4">
<span className="text-2xl">🧠</span>
</div>
<p className="text-gray-500 text-sm max-w-xs mx-auto">
Use <strong>Validate</strong>, <strong>Analyze</strong>, or <strong>Execute</strong> to interact with Claude about your optimization workflow.
</p>
</div>
)}
{/* Messages */}
{messages.map((message) => (
<ChatMessage key={message.id} message={message} />
))}
{/* Thinking indicator */}
{isThinking && <ThinkingIndicator />}
{/* Scroll anchor */}
<div ref={messagesEndRef} />
</div>
);
}

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@@ -0,0 +1,131 @@
/**
* Execute Dialog - Prompts for study name before executing canvas intent
*/
import { useState } from 'react';
interface ExecuteDialogProps {
isOpen: boolean;
onClose: () => void;
onExecute: (studyName: string, autoRun: boolean) => void;
isExecuting: boolean;
}
export function ExecuteDialog({
isOpen,
onClose,
onExecute,
isExecuting,
}: ExecuteDialogProps) {
const [studyName, setStudyName] = useState('');
const [autoRun, setAutoRun] = useState(false);
const [error, setError] = useState<string | null>(null);
if (!isOpen) return null;
const handleSubmit = (e: React.FormEvent) => {
e.preventDefault();
// Validate study name
const trimmed = studyName.trim();
if (!trimmed) {
setError('Study name is required');
return;
}
// Check for valid snake_case
if (!/^[a-z][a-z0-9_]*$/.test(trimmed)) {
setError('Study name must be snake_case (lowercase letters, numbers, underscores)');
return;
}
setError(null);
onExecute(trimmed, autoRun);
};
const handleClose = () => {
setStudyName('');
setAutoRun(false);
setError(null);
onClose();
};
return (
<div className="fixed inset-0 bg-black bg-opacity-50 flex items-center justify-center z-50">
<div className="bg-white rounded-lg shadow-xl w-full max-w-md p-6">
<h2 className="text-xl font-semibold text-gray-800 mb-4">
Execute with Claude
</h2>
<form onSubmit={handleSubmit}>
<div className="mb-4">
<label
htmlFor="study-name"
className="block text-sm font-medium text-gray-600 mb-1"
>
Study Name
</label>
<input
id="study-name"
type="text"
value={studyName}
onChange={(e) => setStudyName(e.target.value.toLowerCase().replace(/\s+/g, '_'))}
placeholder="my_optimization_study"
className="w-full px-3 py-2 border rounded-lg font-mono focus:ring-2 focus:ring-blue-500 focus:border-blue-500"
disabled={isExecuting}
autoFocus
/>
{error && (
<p className="mt-1 text-sm text-red-600">{error}</p>
)}
<p className="mt-1 text-xs text-gray-500">
Use snake_case (e.g., bracket_mass_v1, mirror_wfe_optimization)
</p>
</div>
<div className="mb-6">
<label className="flex items-center gap-2">
<input
type="checkbox"
checked={autoRun}
onChange={(e) => setAutoRun(e.target.checked)}
disabled={isExecuting}
className="w-4 h-4"
/>
<span className="text-sm text-gray-700">
Start optimization immediately after creation
</span>
</label>
</div>
<div className="flex gap-3 justify-end">
<button
type="button"
onClick={handleClose}
disabled={isExecuting}
className="px-4 py-2 text-gray-600 hover:text-gray-800 disabled:opacity-50"
>
Cancel
</button>
<button
type="submit"
disabled={isExecuting}
className="px-4 py-2 bg-blue-600 text-white rounded-lg hover:bg-blue-700 disabled:opacity-50 disabled:cursor-not-allowed flex items-center gap-2"
>
{isExecuting ? (
<>
<span className="animate-spin"></span>
Executing...
</>
) : (
<>
Send to Claude
</>
)}
</button>
</div>
</form>
</div>
</div>
);
}

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@@ -0,0 +1,184 @@
/**
* Canvas-Chat Bridge Hook
*
* Bridges the Canvas UI with the Chat system, allowing canvas intents
* to be sent to Claude for intelligent execution.
*/
import { useCallback, useState } from 'react';
import { useChat, ChatMode } from './useChat';
import { OptimizationIntent, formatIntentForChat } from '../lib/canvas/intent';
interface UseCanvasChatOptions {
mode?: ChatMode;
onError?: (error: string) => void;
}
interface CanvasChatState {
isExecuting: boolean;
lastIntent: OptimizationIntent | null;
executionResult: ExecutionResult | null;
}
interface ExecutionResult {
success: boolean;
action: string;
studyName?: string;
path?: string;
error?: string;
message?: string;
}
export function useCanvasChat({
mode = 'user',
onError,
}: UseCanvasChatOptions = {}) {
const chat = useChat({ mode, onError });
const [state, setState] = useState<CanvasChatState>({
isExecuting: false,
lastIntent: null,
executionResult: null,
});
/**
* Submit an intent for validation only (no execution)
*/
const validateIntent = useCallback(
async (intent: OptimizationIntent): Promise<void> => {
setState((prev) => ({
...prev,
isExecuting: true,
lastIntent: intent,
executionResult: null,
}));
// Format intent for chat and ask Claude to validate
const message = `Please validate this canvas optimization intent:
${formatIntentForChat(intent)}
Use the validate_canvas_intent tool to check for errors and provide feedback.`;
await chat.sendMessage(message);
setState((prev) => ({
...prev,
isExecuting: false,
}));
},
[chat]
);
/**
* Execute an intent (create study and optionally run)
*/
const executeIntent = useCallback(
async (
intent: OptimizationIntent,
studyName: string,
autoRun: boolean = false
): Promise<void> => {
setState((prev) => ({
...prev,
isExecuting: true,
lastIntent: intent,
executionResult: null,
}));
// Format intent for chat and ask Claude to execute
const message = `Please execute this canvas optimization intent to create study "${studyName}"${autoRun ? ' and start the optimization' : ''}:
${formatIntentForChat(intent)}
Use the execute_canvas_intent tool with:
- study_name: "${studyName}"
- auto_run: ${autoRun}
After execution, provide a summary of what was created.`;
await chat.sendMessage(message);
setState((prev) => ({
...prev,
isExecuting: false,
}));
},
[chat]
);
/**
* Get recommendations for an intent without executing
*/
const analyzeIntent = useCallback(
async (intent: OptimizationIntent): Promise<void> => {
setState((prev) => ({
...prev,
isExecuting: true,
lastIntent: intent,
}));
const message = `Please analyze this canvas optimization intent and provide recommendations:
${formatIntentForChat(intent)}
Use the interpret_canvas_intent tool to:
1. Analyze the problem characteristics
2. Suggest the best optimization method
3. Recommend trial budget
4. Identify any potential issues
Provide your recommendations in a clear, actionable format.`;
await chat.sendMessage(message);
setState((prev) => ({
...prev,
isExecuting: false,
}));
},
[chat]
);
/**
* Send a free-form message about the current canvas state
*/
const askAboutCanvas = useCallback(
async (intent: OptimizationIntent, question: string): Promise<void> => {
const message = `Given this canvas optimization intent:
${formatIntentForChat(intent)}
${question}`;
await chat.sendMessage(message);
},
[chat]
);
return {
// Chat state
messages: chat.messages,
isThinking: chat.isThinking || state.isExecuting,
isConnected: chat.isConnected,
error: chat.error,
sessionId: chat.sessionId,
mode: chat.mode,
// Canvas-specific state
isExecuting: state.isExecuting,
lastIntent: state.lastIntent,
executionResult: state.executionResult,
// Actions
validateIntent,
executeIntent,
analyzeIntent,
askAboutCanvas,
// Base chat actions
sendMessage: chat.sendMessage,
clearMessages: chat.clearMessages,
switchMode: chat.switchMode,
};
}