From 18ba831a2ab4d9f42cd47f5c3ed4ac9c63734635 Mon Sep 17 00:00:00 2001
From: David Blanc Brioir <davidblancbrioir@gmail.com>
Date: Tue, 9 Dec 2025 23:23:56 +0100
Subject: [PATCH] Initial commit: Chat-to-diagram v1.0
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

- Chat interface with OpenAI GPT integration
- Automatic diagram generation from text descriptions
- Tldraw canvas with Dagre layout engine
- REST API instead of WebSocket approach

🤖 Generated with Claude Code (https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
---
 .claude/agents/codebase-analyst.md       |  114 +
 .claude/agents/validator.md              |  176 +
 .claude/commands/create-plan.md          |  204 +
 .claude/commands/execute-plan.md         |  139 +
 .claude/commands/primer.md               |   14 +
 .claude/plan.txt                         |   75 +
 .claude/settings.local.json              |   26 +
 .env.example                             |    6 +
 .gitignore                               |   37 +
 PRPs/requests/voice-to-diagram.md        | 1923 ++++++
 next.config.js                           |   15 +
 package-lock.json                        | 8035 ++++++++++++++++++++++
 package.json                             |   33 +
 postcss.config.js                        |    6 +
 src/app/globals.css                      |   27 +
 src/app/layout.tsx                       |   19 +
 src/app/page.tsx                         |   61 +
 src/components/features/ChatPanel.tsx    |  105 +
 src/components/features/TldrawCanvas.tsx |   22 +
 src/components/ui/ChatInput.tsx          |   56 +
 src/components/ui/ChatMessage.tsx        |   62 +
 src/hooks/useChatAPI.ts                  |  147 +
 src/lib/chat-prompts.ts                  |   46 +
 src/lib/diagram-parser.ts                |   99 +
 src/lib/layout-engine.ts                 |   84 +
 src/lib/mock-data.ts                     |   83 +
 src/lib/openai-config.ts                 |   24 +
 src/lib/tldraw-helpers.ts                |  143 +
 src/types/graph.ts                       |   48 +
 tailwind.config.ts                       |   19 +
 tsconfig.json                            |   27 +
 31 files changed, 11875 insertions(+)
 create mode 100644 .claude/agents/codebase-analyst.md
 create mode 100644 .claude/agents/validator.md
 create mode 100644 .claude/commands/create-plan.md
 create mode 100644 .claude/commands/execute-plan.md
 create mode 100644 .claude/commands/primer.md
 create mode 100644 .claude/plan.txt
 create mode 100644 .claude/settings.local.json
 create mode 100644 .env.example
 create mode 100644 .gitignore
 create mode 100644 PRPs/requests/voice-to-diagram.md
 create mode 100644 next.config.js
 create mode 100644 package-lock.json
 create mode 100644 package.json
 create mode 100644 postcss.config.js
 create mode 100644 src/app/globals.css
 create mode 100644 src/app/layout.tsx
 create mode 100644 src/app/page.tsx
 create mode 100644 src/components/features/ChatPanel.tsx
 create mode 100644 src/components/features/TldrawCanvas.tsx
 create mode 100644 src/components/ui/ChatInput.tsx
 create mode 100644 src/components/ui/ChatMessage.tsx
 create mode 100644 src/hooks/useChatAPI.ts
 create mode 100644 src/lib/chat-prompts.ts
 create mode 100644 src/lib/diagram-parser.ts
 create mode 100644 src/lib/layout-engine.ts
 create mode 100644 src/lib/mock-data.ts
 create mode 100644 src/lib/openai-config.ts
 create mode 100644 src/lib/tldraw-helpers.ts
 create mode 100644 src/types/graph.ts
 create mode 100644 tailwind.config.ts
 create mode 100644 tsconfig.json

diff --git a/.claude/agents/codebase-analyst.md b/.claude/agents/codebase-analyst.md
new file mode 100644
index 0000000..fedc184
--- /dev/null
+++ b/.claude/agents/codebase-analyst.md
@@ -0,0 +1,114 @@
+---
+name: "codebase-analyst"
+description: "Use proactively to find codebase patterns, coding style and team standards. Specialized agent for deep codebase pattern analysis and convention discovery"
+model: "sonnet"
+---
+
+You are a specialized codebase analysis agent focused on discovering patterns, conventions, and implementation approaches.
+
+## Your Mission
+
+Perform deep, systematic analysis of codebases to extract:
+
+- Architectural patterns and project structure
+- Coding conventions and naming standards
+- Integration patterns between components
+- Testing approaches and validation commands
+- External library usage and configuration
+
+## Analysis Methodology
+
+### 1. Project Structure Discovery
+
+- Start looking for Architecture docs rules files such as claude.md, agents.md, cursorrules, windsurfrules, agent wiki, or similar documentation
+- Continue with root-level config files (package.json, pyproject.toml, go.mod, etc.)
+- Map directory structure to understand organization
+- Identify primary language and framework
+- Note build/run commands
+
+### 2. Pattern Extraction
+
+- Find similar implementations to the requested feature
+- Extract common patterns (error handling, API structure, data flow)
+- Identify naming conventions (files, functions, variables)
+- Document import patterns and module organization
+
+### 3. Integration Analysis
+
+- How are new features typically added?
+- Where do routes/endpoints get registered?
+- How are services/components wired together?
+- What's the typical file creation pattern?
+
+### 4. Testing Patterns
+
+- What test framework is used?
+- How are tests structured?
+- What are common test patterns?
+- Extract validation command examples
+
+### 5. Documentation Discovery
+
+- Check for README files
+- Find API documentation
+- Look for inline code comments with patterns
+- Check PRPs/ai_docs/ for curated documentation
+
+## Output Format
+
+Provide findings in structured format:
+
+```yaml
+project:
+  language: [detected language]
+  framework: [main framework]
+  structure: [brief description]
+
+patterns:
+  naming:
+    files: [pattern description]
+    functions: [pattern description]
+    classes: [pattern description]
+
+  architecture:
+    services: [how services are structured]
+    models: [data model patterns]
+    api: [API patterns]
+
+  testing:
+    framework: [test framework]
+    structure: [test file organization]
+    commands: [common test commands]
+
+similar_implementations:
+  - file: [path]
+    relevance: [why relevant]
+    pattern: [what to learn from it]
+
+libraries:
+  - name: [library]
+    usage: [how it's used]
+    patterns: [integration patterns]
+
+validation_commands:
+  syntax: [linting/formatting commands]
+  test: [test commands]
+  run: [run/serve commands]
+```
+
+## Key Principles
+
+- Be specific - point to exact files and line numbers
+- Extract executable commands, not abstract descriptions
+- Focus on patterns that repeat across the codebase
+- Note both good patterns to follow and anti-patterns to avoid
+- Prioritize relevance to the requested feature/story
+
+## Search Strategy
+
+1. Start broad (project structure) then narrow (specific patterns)
+2. Use parallel searches when investigating multiple aspects
+3. Follow references - if a file imports something, investigate it
+4. Look for "similar" not "same" - patterns often repeat with variations
+
+Remember: Your analysis directly determines implementation success. Be thorough, specific, and actionable.
diff --git a/.claude/agents/validator.md b/.claude/agents/validator.md
new file mode 100644
index 0000000..fac041d
--- /dev/null
+++ b/.claude/agents/validator.md
@@ -0,0 +1,176 @@
+---
+name: validator
+description: Testing specialist for software features. USE AUTOMATICALLY after implementation to create simple unit tests, validate functionality, and ensure readiness. IMPORTANT - You must pass exactly what was built as part of the prompt so the validator knows what features to test.
+tools: Read, Write, Grep, Glob, Bash, TodoWrite
+color: green
+---
+
+# Software Feature Validator
+
+You are an expert QA engineer specializing in creating simple, effective unit tests for newly implemented software features. Your role is to ensure the implemented functionality works correctly through straightforward testing.
+
+## Primary Objective
+
+Create simple, focused unit tests that validate the core functionality of what was just built. Keep tests minimal but effective - focus on the happy path and critical edge cases only.
+
+## Core Responsibilities
+
+### 1. Understand What Was Built
+
+First, understand exactly what feature or functionality was implemented by:
+- Reading the relevant code files
+- Identifying the main functions/components created
+- Understanding the expected inputs and outputs
+- Noting any external dependencies or integrations
+
+### 2. Create Simple Unit Tests
+
+Write straightforward tests that:
+- **Test the happy path**: Verify the feature works with normal, expected inputs
+- **Test critical edge cases**: Empty inputs, null values, boundary conditions
+- **Test error handling**: Ensure errors are handled gracefully
+- **Keep it simple**: 3-5 tests per feature is often sufficient
+
+### 3. Test Structure Guidelines
+
+#### For JavaScript/TypeScript Projects
+```javascript
+// Simple test example
+describe('FeatureName', () => {
+  test('should handle normal input correctly', () => {
+    const result = myFunction('normal input');
+    expect(result).toBe('expected output');
+  });
+
+  test('should handle empty input', () => {
+    const result = myFunction('');
+    expect(result).toBe(null);
+  });
+
+  test('should throw error for invalid input', () => {
+    expect(() => myFunction(null)).toThrow();
+  });
+});
+```
+
+#### For Python Projects
+```python
+# Simple test example
+import unittest
+from my_module import my_function
+
+class TestFeature(unittest.TestCase):
+    def test_normal_input(self):
+        result = my_function("normal input")
+        self.assertEqual(result, "expected output")
+
+    def test_empty_input(self):
+        result = my_function("")
+        self.assertIsNone(result)
+
+    def test_invalid_input(self):
+        with self.assertRaises(ValueError):
+            my_function(None)
+```
+
+### 4. Test Execution Process
+
+1. **Identify test framework**: Check package.json, requirements.txt, or project config
+2. **Create test file**: Place in appropriate test directory (tests/, __tests__, spec/)
+3. **Write simple tests**: Focus on functionality, not coverage percentages
+4. **Run tests**: Use the project's test command (npm test, pytest, etc.)
+5. **Fix any issues**: If tests fail, determine if it's a test issue or code issue
+
+## Validation Approach
+
+### Keep It Simple
+- Don't over-engineer tests
+- Focus on "does it work?" not "is every line covered?"
+- 3-5 good tests are better than 20 redundant ones
+- Test behavior, not implementation details
+
+### What to Test
+✅ Main functionality works as expected
+✅ Common edge cases are handled
+✅ Errors don't crash the application
+✅ API contracts are honored (if applicable)
+✅ Data transformations are correct
+
+### What NOT to Test
+❌ Every possible combination of inputs
+❌ Internal implementation details
+❌ Third-party library functionality
+❌ Trivial getters/setters
+❌ Configuration values
+
+## Common Test Patterns
+
+### API Endpoint Test
+```javascript
+test('API returns correct data', async () => {
+  const response = await fetch('/api/endpoint');
+  const data = await response.json();
+  expect(response.status).toBe(200);
+  expect(data).toHaveProperty('expectedField');
+});
+```
+
+### Data Processing Test
+```python
+def test_data_transformation():
+    input_data = {"key": "value"}
+    result = transform_data(input_data)
+    assert result["key"] == "TRANSFORMED_VALUE"
+```
+
+### UI Component Test
+```javascript
+test('Button triggers action', () => {
+  const onClick = jest.fn();
+  render(<Button onClick={onClick}>Click me</Button>);
+  fireEvent.click(screen.getByText('Click me'));
+  expect(onClick).toHaveBeenCalled();
+});
+```
+
+## Final Validation Checklist
+
+Before completing validation:
+- [ ] Tests are simple and readable
+- [ ] Main functionality is tested
+- [ ] Critical edge cases are covered
+- [ ] Tests actually run and pass
+- [ ] No overly complex test setups
+- [ ] Test names clearly describe what they test
+
+## Output Format
+
+After creating and running tests, provide:
+
+```markdown
+# Validation Complete
+
+## Tests Created
+- [Test file name]: [Number] tests
+- Total tests: [X]
+- All passing: [Yes/No]
+
+## What Was Tested
+- ✅ [Feature 1]: Working correctly
+- ✅ [Feature 2]: Handles edge cases
+- ⚠️ [Feature 3]: [Any issues found]
+
+## Test Commands
+Run tests with: `[command used]`
+
+## Notes
+[Any important observations or recommendations]
+```
+
+## Remember
+
+- Simple tests are better than complex ones
+- Focus on functionality, not coverage metrics
+- Test what matters, skip what doesn't
+- Clear test names help future debugging
+- Working software is the goal, tests are the safety net
\ No newline at end of file
diff --git a/.claude/commands/create-plan.md b/.claude/commands/create-plan.md
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--- /dev/null
+++ b/.claude/commands/create-plan.md
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+---
+description: Create a comprehensive implementation plan from requirements document through extensive research
+argument-hint: [plan-description-or-requirements-file]
+---
+
+# Create Implementation Plan from Requirements
+
+You are about to create a comprehensive implementation plan based on initial requirements. This involves extensive research, analysis, and planning to produce a detailed roadmap for execution.
+
+IMPORTANT: The plan should be between 500 and 1000 lines.
+
+## Step 1: Read and Analyze Requirements
+
+Understand the requirements or read the requirements document from: $ARGUMENTS
+
+Extract and understand:
+- Core feature requests and objectives
+- Technical requirements and constraints
+- Expected outcomes and success criteria
+- Integration points with existing systems
+- Performance and scalability requirements
+- Any specific technologies or frameworks mentioned
+
+## Step 2: Research Phase
+
+### 2.1 Web Research (if applicable)
+- Search for best practices for the requested features
+- Look up documentation for any mentioned technologies
+- Find similar implementations or case studies
+- Research common patterns and architectures
+- Investigate potential libraries or tools
+
+### 2.2 Knowledge Base Search (if instructed)
+If Archon RAG is available and relevant:
+- Use `mcp__archon__rag_get_available_sources()` to see available documentation
+- Search for relevant patterns: `mcp__archon__rag_search_knowledge_base(query="...")`
+- Find code examples: `mcp__archon__rag_search_code_examples(query="...")`
+- Focus on implementation patterns, best practices, and similar features
+
+### 2.3 Codebase Analysis (for existing projects)
+If this is for an existing codebase:
+
+**IMPORTANT: Use the `codebase-analyst` agent for deep pattern analysis**
+- Launch the codebase-analyst agent using the Task tool to perform comprehensive pattern discovery
+- The agent will analyze: architecture patterns, coding conventions, testing approaches, and similar implementations
+- Use the agent's findings to ensure your plan follows existing patterns and conventions
+
+For quick searches you can also:
+- Use Grep to find specific features or patterns
+- Identify the project structure and conventions
+- Locate relevant modules and components
+- Understand existing architecture and design patterns
+- Find integration points for new features
+- Check for existing utilities or helpers to reuse
+
+## Step 3: Planning and Design
+
+Based on your research, create a detailed plan that includes:
+
+### 3.1 Task Breakdown
+Create a prioritized list of implementation tasks:
+- Each task should be specific and actionable
+- Tasks should be sized appropriately
+- Include dependencies between tasks
+- Order tasks logically for implementation flow
+
+### 3.2 Technical Architecture
+Define the technical approach:
+- Component structure and organization
+- Data flow and state management
+- API design (if applicable)
+- Database schema changes (if needed)
+- Integration points with existing code
+
+### 3.3 Implementation References
+Document key resources for implementation:
+- Existing code files to reference or modify
+- Documentation links for technologies used
+- Code examples from research
+- Patterns to follow from the codebase
+- Libraries or dependencies to add
+
+## Step 4: Create the Plan Document
+
+Write a comprehensive plan to `PRPs/requests/[feature-name].md` with roughly this structure (n represents that this could be any number of those things):
+
+```markdown
+# Implementation Plan: [Feature Name]
+
+## Overview
+[Brief description of what will be implemented]
+
+## Requirements Summary
+- [Key requirement 1]
+- [Key requirement 2]
+- [Key requirement n]
+
+## Research Findings
+### Best Practices
+- [Finding 1]
+- [Finding n]
+
+### Reference Implementations
+- [Example 1 with link/location]
+- [Example n with link/location]
+
+### Technology Decisions
+- [Technology choice 1 and rationale]
+- [Technology choice n and rationale]
+
+## Implementation Tasks
+
+### Phase 1: Foundation
+1. **Task Name**
+   - Description: [What needs to be done]
+   - Files to modify/create: [List files]
+   - Dependencies: [Any prerequisites]
+   - Estimated effort: [time estimate]
+
+2. **Task Name**
+   - Description: [What needs to be done]
+   - Files to modify/create: [List files]
+   - Dependencies: [Any prerequisites]
+   - Estimated effort: [time estimate]
+
+### Phase 2: Core Implementation
+[Continue with numbered tasks...]
+
+### Phase 3: Integration & Testing
+[Continue with numbered tasks...]
+
+## Codebase Integration Points
+### Files to Modify
+- `path/to/file1.js` - [What changes needed]
+- `path/to/filen.py` - [What changes needed]
+
+### New Files to Create
+- `path/to/newfile1.js` - [Purpose]
+- `path/to/newfilen.py` - [Purpose]
+
+### Existing Patterns to Follow
+- [Pattern 1 from codebase]
+- [Pattern n from codebase]
+
+## Technical Design
+
+### Architecture Diagram (if applicable)
+```
+[ASCII diagram or description]
+```
+
+### Data Flow
+[Description of how data flows through the feature]
+
+### API Endpoints (if applicable)
+- `POST /api/endpoint` - [Purpose]
+- `GET /api/endpoint/:id` - [Purpose]
+
+## Dependencies and Libraries
+- [Library 1] - [Purpose]
+- [Library n] - [Purpose]
+
+## Testing Strategy
+- Unit tests for [components]
+- Integration tests for [workflows]
+- Edge cases to cover: [list]
+
+## Success Criteria
+- [ ] [Criterion 1]
+- [ ] [Criterion 2]
+- [ ] [Criterion n]
+
+## Notes and Considerations
+- [Any important notes]
+- [Potential challenges]
+- [Future enhancements]
+
+---
+*This plan is ready for execution with `/execute-plan`*
+```
+
+## Step 5: Validation
+
+Before finalizing the plan:
+1. Ensure all requirements are addressed
+2. Verify tasks are properly sequenced
+3. Check that integration points are identified
+4. Confirm research supports the approach
+5. Make sure the plan is actionable and clear
+
+## Important Guidelines
+
+- **Be thorough in research**: The quality of the plan depends on understanding best practices
+- **Keep it actionable**: Every task should be clear and implementable
+- **Reference everything**: Include links, file paths, and examples
+- **Consider the existing codebase**: Follow established patterns and conventions
+- **Think about testing**: Include testing tasks in the plan
+- **Size tasks appropriately**: Not too large, not too granular
+
+## Output
+
+Save the plan to the PRPs/requests/ directory and inform the user:
+"Implementation plan created at: PRPs/requests/[feature-name].md
+You can now execute this plan using: `/execute-plan PRPs/requests/[feature-name].md`"
\ No newline at end of file
diff --git a/.claude/commands/execute-plan.md b/.claude/commands/execute-plan.md
new file mode 100644
index 0000000..97c6131
--- /dev/null
+++ b/.claude/commands/execute-plan.md
@@ -0,0 +1,139 @@
+---
+description: Execute a development plan with full Archon task management integration
+argument-hint: [plan-file-path]
+---
+
+# Execute Development Plan with Archon Task Management
+
+You are about to execute a comprehensive development plan with integrated Archon task management. This workflow ensures systematic task tracking and implementation throughout the entire development process.
+
+## Critical Requirements
+
+**MANDATORY**: Throughout the ENTIRE execution of this plan, you MUST maintain continuous usage of Archon for task management. DO NOT drop or skip Archon integration at any point. Every task from the plan must be tracked in Archon from creation to completion.
+
+## Step 1: Read and Parse the Plan
+
+Read the plan file specified in: $ARGUMENTS
+
+The plan file will contain:
+- A list of tasks to implement
+- References to existing codebase components and integration points
+- Context about where to look in the codebase for implementation
+
+## Step 2: Project Setup in Archon
+
+1. Check if a project ID is specified in CLAUDE.md for this feature
+   - Look for any Archon project references in CLAUDE.md
+   - If found, use that project ID
+
+2. If no project exists:
+   - Create a new project in Archon using `mcp__archon__manage_project`
+   - Use a descriptive title based on the plan's objectives
+   - Store the project ID for use throughout execution
+
+## Step 3: Create All Tasks in Archon
+
+For EACH task identified in the plan:
+1. Create a corresponding task in Archon using `mcp__archon__manage_task("create", ...)`
+2. Set initial status as "todo"
+3. Include detailed descriptions from the plan
+4. Maintain the task order/priority from the plan
+
+**IMPORTANT**: Create ALL tasks in Archon upfront before starting implementation. This ensures complete visibility of the work scope.
+
+## Step 4: Codebase Analysis
+
+Before implementation begins:
+1. Analyze ALL integration points mentioned in the plan
+2. Use Grep and Glob tools to:
+   - Understand existing code patterns
+   - Identify where changes need to be made
+   - Find similar implementations for reference
+3. Read all referenced files and components
+4. Build a comprehensive understanding of the codebase context
+
+## Step 5: Implementation Cycle
+
+For EACH task in sequence:
+
+### 5.1 Start Task
+- Move the current task to "doing" status in Archon: `mcp__archon__manage_task("update", task_id=..., status="doing")`
+- Use TodoWrite to track local subtasks if needed
+
+### 5.2 Implement
+- Execute the implementation based on:
+  - The task requirements from the plan
+  - Your codebase analysis findings
+  - Best practices and existing patterns
+- Make all necessary code changes
+- Ensure code quality and consistency
+
+### 5.3 Complete Task
+- Once implementation is complete, move task to "review" status: `mcp__archon__manage_task("update", task_id=..., status="review")`
+- DO NOT mark as "done" yet - this comes after validation
+
+### 5.4 Proceed to Next
+- Move to the next task in the list
+- Repeat steps 5.1-5.3
+
+**CRITICAL**: Only ONE task should be in "doing" status at any time. Complete each task before starting the next.
+
+## Step 6: Validation Phase
+
+After ALL tasks are in "review" status:
+
+**IMPORTANT: Use the `validator` agent for comprehensive testing**
+1. Launch the validator agent using the Task tool
+   - Provide the validator with a detailed description of what was built
+   - Include the list of features implemented and files modified
+   - The validator will create simple, effective unit tests
+   - It will run tests and report results
+
+The validator agent will:
+- Create focused unit tests for the main functionality
+- Test critical edge cases and error handling
+- Run the tests using the project's test framework
+- Report what was tested and any issues found
+
+Additional validation you should perform:
+- Check for integration issues between components
+- Ensure all acceptance criteria from the plan are met
+
+## Step 7: Finalize Tasks in Archon
+
+After successful validation:
+
+1. For each task that has corresponding unit test coverage:
+   - Move from "review" to "done" status: `mcp__archon__manage_task("update", task_id=..., status="done")`
+
+2. For any tasks without test coverage:
+   - Leave in "review" status for future attention
+   - Document why they remain in review (e.g., "Awaiting integration tests")
+
+## Step 8: Final Report
+
+Provide a summary including:
+- Total tasks created and completed
+- Any tasks remaining in review and why
+- Test coverage achieved
+- Key features implemented
+- Any issues encountered and how they were resolved
+
+## Workflow Rules
+
+1. **NEVER** skip Archon task management at any point
+2. **ALWAYS** create all tasks in Archon before starting implementation
+3. **MAINTAIN** one task in "doing" status at a time
+4. **VALIDATE** all work before marking tasks as "done"
+5. **TRACK** progress continuously through Archon status updates
+6. **ANALYZE** the codebase thoroughly before implementation
+7. **TEST** everything before final completion
+
+## Error Handling
+
+If at any point Archon operations fail:
+1. Retry the operation
+2. If persistent failures, document the issue but continue tracking locally
+3. Never abandon the Archon integration - find workarounds if needed
+
+Remember: The success of this execution depends on maintaining systematic task management through Archon throughout the entire process. This ensures accountability, progress tracking, and quality delivery.
\ No newline at end of file
diff --git a/.claude/commands/primer.md b/.claude/commands/primer.md
new file mode 100644
index 0000000..bde22e2
--- /dev/null
+++ b/.claude/commands/primer.md
@@ -0,0 +1,14 @@
+# Prime Context for the AI Coding Assistant (catch it up to speed on the project when starting a new conversation)
+
+Start with reading the CLAUDE.md file if it exists to get an understanding of the project.
+
+Read the README.md file to get an understanding of the project.
+
+Read key files in src/
+
+Explain back to me:
+- Project structure
+- Project purpose and goals
+- Key files and their purposes
+- Any important dependencies
+- Any important configuration files
\ No newline at end of file
diff --git a/.claude/plan.txt b/.claude/plan.txt
new file mode 100644
index 0000000..f24efab
--- /dev/null
+++ b/.claude/plan.txt
@@ -0,0 +1,75 @@
+Project: Voice-to-Diagram (Tldraw + OpenAI Realtime)
+1. Project Goal
+
+Build a web application that converts natural spoken descriptions into live, auto-laid-out diagrams.
+The user speaks; the system interprets the description, generates a graph structure, computes layout positions, and draws everything in real time on a Tldraw canvas.
+
+2. Tech Stack (Strict Requirements)
+
+Framework: Next.js 14+ (App Router).
+
+Canvas / UI: tldraw (latest version).
+
+Layout Engine: dagre (node/edge graph auto-layout).
+
+AI / Voice: OpenAI Realtime API (WebSockets).
+
+Styling: TailwindCSS.
+
+3. Key Technical Principles
+3.1 No Coordinate Hallucination
+
+The AI must never guess or propose X/Y coordinates.
+Its responsibility is limited to producing a pure graph model:
+
+A list of nodes with semantic types and labels.
+
+A list of edges describing relationships between nodes.
+
+3.2 Interaction Flow
+
+The AI produces a Graph JSON (nodes + edges) via function calling.
+
+The app receives this JSON, then passes it to dagre to calculate node coordinates.
+
+The resulting positioned shapes are injected into the tldraw store.
+
+The diagram updates instantly on the canvas.
+
+3.3 State Management
+
+Use Tldraw’s internal local store to keep all shapes, bindings, and metadata consistent.
+
+4. Implementation Roadmap (Step-by-Step)
+Phase 1 — Canvas & Programmatic Control
+
+ Step 1: Initialize a Next.js project with Tldraw integrated in a dedicated component.
+
+ Step 2: Implement a “Add Test Shapes” button that programmatically inserts shapes into the Tldraw store.
+
+Phase 2 — The Layout Engine (Dagre)
+
+ Step 3: Implement a utility function getAutoLayout(nodes, edges) using dagre.
+
+ Step 4: Add a “Generate Graph” button that takes a mock graph JSON, runs the layout, and injects the result into Tldraw.
+
+Phase 3 — OpenAI Realtime Integration
+
+ Step 5: Set up a relay server (or a Next.js API Route) to hide your OpenAI API key and handle WebSocket bridging.
+
+ Step 6: Connect the frontend to OpenAI Realtime via WebSocket (audio stream + event stream).
+
+ Step 7: Define the generate_diagram tool (JSON Schema) that the AI will call to output the graph structure.
+
+Phase 4 — Fusion
+
+ Step 8: Handle the function_call coming from OpenAI.
+When the AI calls generate_diagram, parse the JSON, run Dagre, and update the Tldraw store in real time.
+
+5. Coding Conventions
+
+Use TypeScript interfaces for all graph structures (nodes, edges, metadata).
+
+Keep the Tldraw component strictly isolated from logic functions (clear separation UI / graph engine / AI).
+
+Use lucide-react for icons.
\ No newline at end of file
diff --git a/.claude/settings.local.json b/.claude/settings.local.json
new file mode 100644
index 0000000..ddc346f
--- /dev/null
+++ b/.claude/settings.local.json
@@ -0,0 +1,26 @@
+{
+  "permissions": {
+    "allow": [
+      "Bash(cat:*)",
+      "WebSearch",
+      "Bash(mkdir:*)",
+      "Bash(claude mcp add:*)",
+      "mcp__archon__manage_project",
+      "Bash(dir:*)",
+      "mcp__archon__manage_task",
+      "Bash(npm install)",
+      "Bash(npm run relay:*)",
+      "Bash(netstat:*)",
+      "Bash(findstr:*)",
+      "Bash(taskkill:*)",
+      "Bash(timeout:*)",
+      "Bash(npm run dev:*)",
+      "Bash(npm run build:*)",
+      "Bash(npm start)",
+      "Bash(find:*)",
+      "Bash(git init:*)",
+      "Bash(git add:*)",
+      "Bash(git commit:*)"
+    ]
+  }
+}
diff --git a/.env.example b/.env.example
new file mode 100644
index 0000000..e772be2
--- /dev/null
+++ b/.env.example
@@ -0,0 +1,6 @@
+# OpenAI API Configuration (NEXT_PUBLIC_ prefix required for client-side access)
+NEXT_PUBLIC_OPENAI_API_KEY=your_openai_api_key_here
+OPENAI_API_KEY=your_openai_api_key_here
+
+# Optional: Custom WebSocket Relay URL (if not using the built-in relay)
+# NEXT_PUBLIC_WS_URL=ws://localhost:3000/api/realtime
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..00bba9b
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,37 @@
+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.js
+.yarn/install-state.gz
+
+# testing
+/coverage
+
+# next.js
+/.next/
+/out/
+
+# production
+/build
+
+# misc
+.DS_Store
+*.pem
+
+# debug
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+
+# local env files
+.env*.local
+.env
+
+# vercel
+.vercel
+
+# typescript
+*.tsbuildinfo
+next-env.d.ts
diff --git a/PRPs/requests/voice-to-diagram.md b/PRPs/requests/voice-to-diagram.md
new file mode 100644
index 0000000..355e96d
--- /dev/null
+++ b/PRPs/requests/voice-to-diagram.md
@@ -0,0 +1,1923 @@
+# Implementation Plan: Voice-to-Diagram (Tldraw + OpenAI Realtime)
+
+## Overview
+
+Build a web application that converts natural spoken descriptions into live, auto-laid-out diagrams using Next.js 14+, Tldraw for the canvas, Dagre for graph layout, and OpenAI Realtime API for voice processing. The application will interpret spoken descriptions, generate graph structures, compute layout positions, and render diagrams in real-time.
+
+## Requirements Summary
+
+- **Framework**: Next.js 14+ with App Router for server-side rendering and optimal performance
+- **Canvas Library**: Tldraw (latest version) for infinite canvas and shape rendering
+- **Layout Engine**: Dagre for automatic node/edge graph layout computation
+- **AI/Voice Processing**: OpenAI Realtime API via WebSockets for speech-to-diagram conversion
+- **Styling**: TailwindCSS for modern, utility-first styling
+- **Icons**: lucide-react for UI icons
+- **Core Principle**: AI never generates coordinates; it outputs semantic graph models (nodes + edges)
+- **Interaction Flow**: Voice → AI Graph JSON → Dagre Layout → Tldraw Canvas
+- **State Management**: Tldraw's internal store for all shapes, bindings, and metadata
+
+## Research Findings
+
+### Best Practices
+
+#### Next.js 14+ App Router (2025)
+- **Server Components by Default**: Use React Server Components to reduce client-side JavaScript and improve performance
+- **Recommended Directory Structure**:
+  - `src/app/` for routes and pages
+  - `src/components/ui/` for reusable UI components
+  - `src/components/features/` for feature-specific components
+  - `src/lib/` for utilities and helpers
+  - `src/types/` for TypeScript interfaces
+- **Performance Optimization**: Use built-in Image and Link components for automatic optimization
+- **API Routes**: Leverage route handlers in App Router for API endpoints
+- **Progressive Enhancement**: Use Server Actions for form handling and data mutations
+
+#### Tldraw Integration
+- **Programmatic Control**: Use the Editor instance via `onMount` callback for full programmatic control
+- **Custom Shapes**: Define custom shape utilities when needed for specialized diagram nodes
+- **Runtime API**: The editor provides methods to create shapes, control viewport, and manage selections
+- **Store Management**: Tldraw uses an internal store that can be updated programmatically
+- **React Integration**: Import `Tldraw` component and CSS, render in full-screen container
+
+#### Dagre Graph Layout
+- **TypeScript Support**: Use `@dagrejs/dagre` with `@types/dagre` for type safety
+- **Basic Pattern**:
+  ```typescript
+  const graph = new dagre.graphlib.Graph();
+  graph.setGraph({ rankdir: 'LR' }); // Layout direction
+  graph.setDefaultEdgeLabel(() => ({}));
+  graph.setNode(id, { label, width, height });
+  graph.setEdge(source, target);
+  dagre.layout(graph); // Computes x, y coordinates
+  ```
+- **Integration with React**: Commonly used with React Flow, adaptable to any canvas library
+- **Node Dimensions**: Must specify node width/height for accurate layout calculation
+
+#### OpenAI Realtime API
+- **WebSocket Connection**: `wss://api.openai.com/v1/realtime?model=gpt-4o-realtime-preview`
+- **Authentication**: Pass API key via Bearer token in header + `OpenAI-Beta: realtime=v1`
+- **Event-Based Protocol**: Send and receive JSON events over WebSocket
+- **Function Calling**:
+  - Define functions the AI can call
+  - AI sends function call events when detected
+  - Client executes function and returns results with `tool.output` event
+  - AI continues turn with response incorporating function results
+- **Audio Streaming**: Supports bidirectional audio streaming (PCM16, 24kHz)
+- **Security**: Use relay server or API route to hide API key from client
+
+### Reference Implementations
+
+- [Next.js 14 Best Practices](https://medium.com/@GoutamSingha/next-js-best-practices-in-2025-build-faster-cleaner-scalable-apps-7efbad2c3820)
+- [Next.js File Structure Guide](https://medium.com/better-dev-nextjs-react/inside-the-app-router-best-practices-for-next-js-file-and-directory-structure-2025-edition-ed6bc14a8da3)
+- [Tldraw Quick Start](https://tldraw.dev/quick-start)
+- [Tldraw Customization](https://tldraw.dev/features/customization)
+- [Dagre with React Flow](https://reactflow.dev/examples/layout/dagre)
+- [OpenAI Realtime WebSocket Guide](https://platform.openai.com/docs/guides/realtime-websocket)
+- [OpenAI Realtime API Tutorial](https://skywork.ai/blog/agent/openai-realtime-api-javascript-tutorial-websocket-guide/)
+
+### Technology Decisions
+
+1. **Next.js 14+ App Router**:
+   - Rationale: Latest React features, Server Components for performance, built-in optimizations
+   - Benefit: Reduces client bundle size, improves Core Web Vitals, better SEO
+
+2. **Tldraw Latest Version**:
+   - Rationale: Mature infinite canvas library with excellent React integration
+   - Benefit: Programmatic API, custom shapes, production-ready, active development
+
+3. **Dagre for Layout**:
+   - Rationale: Proven directed graph layout algorithm, TypeScript support
+   - Benefit: Automatic coordinate calculation, hierarchical layouts, configurable
+
+4. **OpenAI Realtime API**:
+   - Rationale: Low-latency speech-to-speech, function calling, streaming audio
+   - Benefit: Real-time voice interaction, GPT-4o intelligence, native function calling
+
+5. **TailwindCSS**:
+   - Rationale: Utility-first CSS framework, excellent with Next.js
+   - Benefit: Fast development, small production bundle, consistent design system
+
+6. **TypeScript**:
+   - Rationale: Type safety for complex data flows (graph models, API events)
+   - Benefit: Early error detection, better IDE support, maintainable codebase
+
+## Implementation Tasks
+
+### Phase 1: Foundation & Project Setup
+
+#### Task 1.1: Initialize Next.js Project
+- **Description**: Create a new Next.js 14+ project with TypeScript, TailwindCSS, and recommended directory structure
+- **Files to create**:
+  - `package.json` - Project dependencies
+  - `next.config.js` - Next.js configuration
+  - `tailwind.config.ts` - TailwindCSS configuration
+  - `tsconfig.json` - TypeScript configuration
+  - `src/app/layout.tsx` - Root layout component
+  - `src/app/page.tsx` - Home page component
+  - `src/app/globals.css` - Global styles with Tailwind directives
+- **Commands**:
+  ```bash
+  npx create-next-app@latest voice-to-diagram --typescript --tailwind --app --src-dir
+  cd voice-to-diagram
+  ```
+- **Dependencies**: None
+- **Estimated Effort**: 30 minutes
+
+#### Task 1.2: Install Core Dependencies
+- **Description**: Install Tldraw, Dagre, Lucide React, and their TypeScript types
+- **Commands**:
+  ```bash
+  npm install tldraw @dagrejs/dagre lucide-react
+  npm install -D @types/dagre
+  ```
+- **Files to modify**:
+  - `package.json` - Updated with new dependencies
+- **Dependencies**: Task 1.1
+- **Estimated Effort**: 15 minutes
+
+#### Task 1.3: Create Project Directory Structure
+- **Description**: Set up the recommended directory structure for components, utilities, and types
+- **Directories to create**:
+  - `src/components/ui/` - Reusable UI components
+  - `src/components/features/` - Feature-specific components
+  - `src/lib/` - Utilities and helper functions
+  - `src/types/` - TypeScript interfaces and types
+  - `src/hooks/` - Custom React hooks
+- **Dependencies**: Task 1.1
+- **Estimated Effort**: 10 minutes
+
+#### Task 1.4: Configure Environment Variables
+- **Description**: Set up environment variables for OpenAI API key and configuration
+- **Files to create**:
+  - `.env.local` - Local environment variables (gitignored)
+  - `.env.example` - Template for environment variables
+- **Variables**:
+  - `OPENAI_API_KEY` - OpenAI API key
+  - `NEXT_PUBLIC_WS_URL` - WebSocket relay URL (optional)
+- **Dependencies**: Task 1.1
+- **Estimated Effort**: 10 minutes
+
+### Phase 2: Canvas & Programmatic Control
+
+#### Task 2.1: Create TldrawCanvas Component
+- **Description**: Build a dedicated Tldraw canvas component with proper TypeScript types and full-screen container
+- **Files to create**:
+  - `src/components/features/TldrawCanvas.tsx` - Main canvas component
+- **Implementation Details**:
+  - Import Tldraw component and styles
+  - Create full-screen container with Tailwind
+  - Set up ref for Editor instance
+  - Implement `onMount` callback to capture Editor
+  - Export Editor instance via callback prop
+  - Add proper TypeScript typing for Editor
+- **Key Code Pattern**:
+  ```typescript
+  import { Tldraw, Editor } from 'tldraw';
+  import 'tldraw/tldraw.css';
+
+  interface TldrawCanvasProps {
+    onEditorMount?: (editor: Editor) => void;
+  }
+
+  export function TldrawCanvas({ onEditorMount }: TldrawCanvasProps) {
+    return (
+      <div className="w-full h-screen">
+        <Tldraw onMount={(editor) => onEditorMount?.(editor)} />
+      </div>
+    );
+  }
+  ```
+- **Dependencies**: Task 1.2
+- **Estimated Effort**: 45 minutes
+
+#### Task 2.2: Define TypeScript Interfaces for Graph Models
+- **Description**: Create comprehensive TypeScript interfaces for nodes, edges, and graph structures
+- **Files to create**:
+  - `src/types/graph.ts` - Graph data structures
+- **Interfaces to Define**:
+  ```typescript
+  // Node in the semantic graph (before layout)
+  interface GraphNode {
+    id: string;
+    label: string;
+    type: 'process' | 'decision' | 'start' | 'end' | 'data' | 'default';
+    metadata?: Record<string, unknown>;
+  }
+
+  // Edge connecting nodes
+  interface GraphEdge {
+    id: string;
+    source: string;
+    target: string;
+    label?: string;
+  }
+
+  // Complete graph structure from AI
+  interface GraphModel {
+    nodes: GraphNode[];
+    edges: GraphEdge[];
+  }
+
+  // Node after Dagre layout (with coordinates)
+  interface PositionedNode extends GraphNode {
+    x: number;
+    y: number;
+    width: number;
+    height: number;
+  }
+
+  // Layout result
+  interface LayoutResult {
+    nodes: PositionedNode[];
+    edges: GraphEdge[];
+  }
+  ```
+- **Dependencies**: Task 1.3
+- **Estimated Effort**: 30 minutes
+
+#### Task 2.3: Implement Test Shape Injection
+- **Description**: Create a test button that programmatically inserts shapes into the Tldraw store
+- **Files to create**:
+  - `src/lib/tldraw-helpers.ts` - Helper functions for Tldraw operations
+- **Files to modify**:
+  - `src/app/page.tsx` - Add test button to home page
+- **Implementation Details**:
+  - Create helper function to generate shape IDs
+  - Implement function to create basic shapes (rectangle, arrow, text)
+  - Use Editor API to insert shapes into store
+  - Add button with click handler to trigger shape creation
+- **Key Code Pattern**:
+  ```typescript
+  import { Editor, createShapeId } from 'tldraw';
+
+  export function addTestShapes(editor: Editor) {
+    const shapeId = createShapeId();
+    editor.createShape({
+      id: shapeId,
+      type: 'geo',
+      x: 100,
+      y: 100,
+      props: {
+        w: 200,
+        h: 100,
+        geo: 'rectangle',
+        text: 'Test Node'
+      }
+    });
+  }
+  ```
+- **Dependencies**: Task 2.1
+- **Estimated Effort**: 1 hour
+
+#### Task 2.4: Test Canvas Integration
+- **Description**: Verify that Tldraw canvas renders correctly and test shapes can be added programmatically
+- **Testing Steps**:
+  - Start dev server and navigate to home page
+  - Verify Tldraw canvas renders in full screen
+  - Click "Add Test Shapes" button
+  - Verify shapes appear on canvas
+  - Test manual drawing and interaction
+- **Success Criteria**:
+  - Canvas loads without errors
+  - Programmatic shape creation works
+  - Manual interaction works (draw, select, move)
+- **Dependencies**: Task 2.3
+- **Estimated Effort**: 30 minutes
+
+### Phase 3: Layout Engine (Dagre)
+
+#### Task 3.1: Implement Dagre Layout Utility
+- **Description**: Create a utility function that takes a graph model and returns positioned nodes using Dagre
+- **Files to create**:
+  - `src/lib/layout-engine.ts` - Graph layout computation
+- **Implementation Details**:
+  - Import Dagre and types
+  - Create `getAutoLayout` function accepting GraphModel
+  - Configure Dagre graph (rankdir, nodesep, ranksep)
+  - Set default node dimensions (or accept as parameters)
+  - Add nodes and edges to Dagre graph
+  - Run layout computation
+  - Extract computed positions and return LayoutResult
+- **Key Code Pattern**:
+  ```typescript
+  import dagre from '@dagrejs/dagre';
+  import { GraphModel, LayoutResult, PositionedNode } from '@/types/graph';
+
+  const NODE_WIDTH = 180;
+  const NODE_HEIGHT = 80;
+
+  export function getAutoLayout(graphModel: GraphModel): LayoutResult {
+    const graph = new dagre.graphlib.Graph();
+
+    // Configure layout
+    graph.setGraph({
+      rankdir: 'TB', // Top to bottom
+      nodesep: 50,   // Horizontal spacing
+      ranksep: 100   // Vertical spacing
+    });
+    graph.setDefaultEdgeLabel(() => ({}));
+
+    // Add nodes
+    graphModel.nodes.forEach(node => {
+      graph.setNode(node.id, {
+        label: node.label,
+        width: NODE_WIDTH,
+        height: NODE_HEIGHT
+      });
+    });
+
+    // Add edges
+    graphModel.edges.forEach(edge => {
+      graph.setEdge(edge.source, edge.target);
+    });
+
+    // Compute layout
+    dagre.layout(graph);
+
+    // Extract positioned nodes
+    const positionedNodes: PositionedNode[] = graphModel.nodes.map(node => {
+      const nodeWithPosition = graph.node(node.id);
+      return {
+        ...node,
+        x: nodeWithPosition.x - NODE_WIDTH / 2,
+        y: nodeWithPosition.y - NODE_HEIGHT / 2,
+        width: NODE_WIDTH,
+        height: NODE_HEIGHT
+      };
+    });
+
+    return {
+      nodes: positionedNodes,
+      edges: graphModel.edges
+    };
+  }
+  ```
+- **Dependencies**: Task 1.2, Task 2.2
+- **Estimated Effort**: 1.5 hours
+
+#### Task 3.2: Create Tldraw Shape Generator
+- **Description**: Build a function that converts positioned nodes and edges into Tldraw shapes and arrows
+- **Files to modify**:
+  - `src/lib/tldraw-helpers.ts` - Add shape generation from layout result
+- **Implementation Details**:
+  - Create function to map node types to Tldraw geo shapes (rectangle, diamond, ellipse)
+  - Generate unique shape IDs for each node
+  - Create geo shapes with computed positions
+  - Generate arrows for edges with proper bindings
+  - Handle edge labels if present
+  - Return array of shape objects for batch creation
+- **Key Code Pattern**:
+  ```typescript
+  import { Editor, TLGeoShape, TLArrowShape, createShapeId } from 'tldraw';
+  import { LayoutResult } from '@/types/graph';
+
+  export function generateTldrawShapes(layout: LayoutResult, editor: Editor) {
+    const nodeShapeMap = new Map<string, string>();
+
+    // Create node shapes
+    layout.nodes.forEach(node => {
+      const shapeId = createShapeId();
+      nodeShapeMap.set(node.id, shapeId);
+
+      const geoType = getGeoTypeForNode(node.type);
+
+      editor.createShape({
+        id: shapeId,
+        type: 'geo',
+        x: node.x,
+        y: node.y,
+        props: {
+          w: node.width,
+          h: node.height,
+          geo: geoType,
+          text: node.label,
+          fill: 'solid',
+          color: 'blue'
+        }
+      });
+    });
+
+    // Create edge arrows
+    layout.edges.forEach(edge => {
+      const sourceShapeId = nodeShapeMap.get(edge.source);
+      const targetShapeId = nodeShapeMap.get(edge.target);
+
+      if (sourceShapeId && targetShapeId) {
+        const arrowId = createShapeId();
+        editor.createShape({
+          id: arrowId,
+          type: 'arrow',
+          props: {
+            start: { type: 'binding', boundShapeId: sourceShapeId },
+            end: { type: 'binding', boundShapeId: targetShapeId },
+            text: edge.label || ''
+          }
+        });
+      }
+    });
+  }
+
+  function getGeoTypeForNode(nodeType: string): string {
+    switch (nodeType) {
+      case 'decision': return 'diamond';
+      case 'start':
+      case 'end': return 'ellipse';
+      default: return 'rectangle';
+    }
+  }
+  ```
+- **Dependencies**: Task 3.1
+- **Estimated Effort**: 2 hours
+
+#### Task 3.3: Create Mock Graph Generator
+- **Description**: Build a function that generates mock graph data for testing the layout pipeline
+- **Files to create**:
+  - `src/lib/mock-data.ts` - Mock graph generation
+- **Implementation Details**:
+  - Create function to generate sample graph with various node types
+  - Include realistic graph structures (flowcharts, process diagrams)
+  - Add multiple test cases (linear, branching, cyclic)
+- **Mock Examples**:
+  ```typescript
+  import { GraphModel } from '@/types/graph';
+
+  export const mockFlowchart: GraphModel = {
+    nodes: [
+      { id: '1', label: 'Start', type: 'start' },
+      { id: '2', label: 'Process Data', type: 'process' },
+      { id: '3', label: 'Is Valid?', type: 'decision' },
+      { id: '4', label: 'Save', type: 'process' },
+      { id: '5', label: 'Error', type: 'end' },
+      { id: '6', label: 'Success', type: 'end' }
+    ],
+    edges: [
+      { id: 'e1', source: '1', target: '2' },
+      { id: 'e2', source: '2', target: '3' },
+      { id: 'e3', source: '3', target: '4', label: 'Yes' },
+      { id: 'e4', source: '3', target: '5', label: 'No' },
+      { id: 'e5', source: '4', target: '6' }
+    ]
+  };
+  ```
+- **Dependencies**: Task 2.2
+- **Estimated Effort**: 45 minutes
+
+#### Task 3.4: Add "Generate Graph" Test Button
+- **Description**: Implement a button that takes mock graph data, runs layout, and renders to Tldraw
+- **Files to modify**:
+  - `src/app/page.tsx` - Add generate button and wire up pipeline
+- **Implementation Details**:
+  - Import mock data, layout engine, and shape generator
+  - Add button with click handler
+  - On click: get mock graph → run layout → generate shapes → update canvas
+  - Clear previous shapes before adding new ones
+- **Key Code Pattern**:
+  ```typescript
+  const handleGenerateGraph = () => {
+    if (!editor) return;
+
+    // Clear canvas
+    editor.selectAll();
+    editor.deleteShapes(editor.getSelectedShapeIds());
+
+    // Run layout
+    const layout = getAutoLayout(mockFlowchart);
+
+    // Generate and add shapes
+    generateTldrawShapes(layout, editor);
+
+    // Zoom to fit
+    editor.zoomToFit();
+  };
+  ```
+- **Dependencies**: Task 3.2, Task 3.3
+- **Estimated Effort**: 1 hour
+
+#### Task 3.5: Test Layout Pipeline
+- **Description**: Verify the complete layout pipeline from graph model to rendered diagram
+- **Testing Steps**:
+  - Click "Generate Graph" button
+  - Verify mock flowchart appears with proper layout
+  - Check node shapes match types (diamonds for decisions, etc.)
+  - Verify arrows connect correctly
+  - Test zoom to fit functionality
+  - Try different mock graphs
+- **Success Criteria**:
+  - All nodes render in correct positions
+  - Edges connect properly with bindings
+  - Layout is visually clean and hierarchical
+  - No overlapping nodes
+- **Dependencies**: Task 3.4
+- **Estimated Effort**: 45 minutes
+
+### Phase 4: OpenAI Realtime Integration
+
+#### Task 4.1: Create API Route for WebSocket Relay
+- **Description**: Set up a Next.js API route to relay WebSocket connections and hide the OpenAI API key
+- **Files to create**:
+  - `src/app/api/realtime/route.ts` - WebSocket relay endpoint
+- **Implementation Details**:
+  - Handle GET requests for WebSocket upgrade
+  - Establish connection to OpenAI Realtime API
+  - Relay messages bidirectionally between client and OpenAI
+  - Add error handling and connection management
+  - Inject API key from environment variables
+- **Key Code Pattern**:
+  ```typescript
+  import { NextRequest } from 'next/server';
+
+  export async function GET(req: NextRequest) {
+    const upgradeHeader = req.headers.get('upgrade');
+
+    if (upgradeHeader !== 'websocket') {
+      return new Response('Expected websocket', { status: 426 });
+    }
+
+    // WebSocket relay implementation
+    // This is a simplified pattern; full implementation needs WebSocket handling
+    const url = 'wss://api.openai.com/v1/realtime?model=gpt-4o-realtime-preview';
+    const headers = {
+      'Authorization': `Bearer ${process.env.OPENAI_API_KEY}`,
+      'OpenAI-Beta': 'realtime=v1'
+    };
+
+    // Proxy WebSocket connection
+    // Note: Next.js requires additional setup for WebSocket support
+    // Consider using a separate WebSocket server or external relay service
+  }
+  ```
+- **Alternative Approach**: Use a separate Node.js WebSocket server for better compatibility
+- **Dependencies**: Task 1.4
+- **Estimated Effort**: 2 hours
+
+#### Task 4.2: Create WebSocket Client Hook
+- **Description**: Build a custom React hook to manage WebSocket connection state and message handling
+- **Files to create**:
+  - `src/hooks/useRealtimeAPI.ts` - WebSocket client hook
+- **Implementation Details**:
+  - Manage WebSocket connection lifecycle
+  - Handle connection state (connecting, open, closed, error)
+  - Provide methods to send events
+  - Set up event listeners for receiving messages
+  - Implement reconnection logic
+  - Type-safe event interfaces
+- **Key Code Pattern**:
+  ```typescript
+  import { useEffect, useRef, useState, useCallback } from 'react';
+
+  interface UseRealtimeAPIOptions {
+    onMessage?: (event: any) => void;
+    onError?: (error: Error) => void;
+  }
+
+  export function useRealtimeAPI(options: UseRealtimeAPIOptions) {
+    const [connectionState, setConnectionState] = useState<'disconnected' | 'connecting' | 'connected'>('disconnected');
+    const wsRef = useRef<WebSocket | null>(null);
+
+    const connect = useCallback(() => {
+      const ws = new WebSocket('ws://localhost:3000/api/realtime');
+
+      ws.onopen = () => setConnectionState('connected');
+      ws.onclose = () => setConnectionState('disconnected');
+      ws.onerror = (error) => options.onError?.(new Error('WebSocket error'));
+      ws.onmessage = (event) => {
+        const data = JSON.parse(event.data);
+        options.onMessage?.(data);
+      };
+
+      wsRef.current = ws;
+    }, [options]);
+
+    const sendEvent = useCallback((event: any) => {
+      if (wsRef.current?.readyState === WebSocket.OPEN) {
+        wsRef.current.send(JSON.stringify(event));
+      }
+    }, []);
+
+    const disconnect = useCallback(() => {
+      wsRef.current?.close();
+      wsRef.current = null;
+    }, []);
+
+    useEffect(() => {
+      return () => disconnect();
+    }, [disconnect]);
+
+    return {
+      connectionState,
+      connect,
+      disconnect,
+      sendEvent
+    };
+  }
+  ```
+- **Dependencies**: Task 4.1
+- **Estimated Effort**: 2.5 hours
+
+#### Task 4.3: Implement Audio Input Handling
+- **Description**: Set up microphone access and audio streaming to WebSocket
+- **Files to create**:
+  - `src/hooks/useAudioInput.ts` - Audio capture and streaming
+- **Implementation Details**:
+  - Request microphone permissions
+  - Capture audio using Web Audio API
+  - Convert audio to PCM16 format at 24kHz (OpenAI requirement)
+  - Stream audio chunks to WebSocket as base64
+  - Handle start/stop recording
+- **Key Code Pattern**:
+  ```typescript
+  import { useEffect, useRef, useState } from 'react';
+
+  export function useAudioInput(onAudioData: (data: string) => void) {
+    const [isRecording, setIsRecording] = useState(false);
+    const audioContextRef = useRef<AudioContext | null>(null);
+    const streamRef = useRef<MediaStream | null>(null);
+
+    const startRecording = async () => {
+      try {
+        const stream = await navigator.mediaDevices.getUserMedia({ audio: true });
+        const audioContext = new AudioContext({ sampleRate: 24000 });
+        const source = audioContext.createMediaStreamSource(stream);
+        const processor = audioContext.createScriptProcessor(2048, 1, 1);
+
+        processor.onaudioprocess = (e) => {
+          const inputData = e.inputBuffer.getChannelData(0);
+          const pcm16 = convertToPCM16(inputData);
+          const base64 = btoa(String.fromCharCode(...pcm16));
+          onAudioData(base64);
+        };
+
+        source.connect(processor);
+        processor.connect(audioContext.destination);
+
+        streamRef.current = stream;
+        audioContextRef.current = audioContext;
+        setIsRecording(true);
+      } catch (error) {
+        console.error('Failed to access microphone:', error);
+      }
+    };
+
+    const stopRecording = () => {
+      streamRef.current?.getTracks().forEach(track => track.stop());
+      audioContextRef.current?.close();
+      setIsRecording(false);
+    };
+
+    return { isRecording, startRecording, stopRecording };
+  }
+
+  function convertToPCM16(float32Array: Float32Array): Int16Array {
+    const pcm16 = new Int16Array(float32Array.length);
+    for (let i = 0; i < float32Array.length; i++) {
+      const s = Math.max(-1, Math.min(1, float32Array[i]));
+      pcm16[i] = s < 0 ? s * 0x8000 : s * 0x7FFF;
+    }
+    return pcm16;
+  }
+  ```
+- **Dependencies**: Task 4.2
+- **Estimated Effort**: 2 hours
+
+#### Task 4.4: Implement Audio Output Handling
+- **Description**: Set up audio playback for responses from OpenAI Realtime API
+- **Files to create**:
+  - `src/hooks/useAudioOutput.ts` - Audio playback
+- **Implementation Details**:
+  - Receive base64 PCM16 audio chunks from WebSocket
+  - Decode and queue audio chunks
+  - Play audio using Web Audio API
+  - Handle audio buffering for smooth playback
+- **Key Code Pattern**:
+  ```typescript
+  import { useEffect, useRef } from 'react';
+
+  export function useAudioOutput() {
+    const audioContextRef = useRef<AudioContext | null>(null);
+    const audioQueueRef = useRef<AudioBuffer[]>([]);
+
+    useEffect(() => {
+      audioContextRef.current = new AudioContext({ sampleRate: 24000 });
+    }, []);
+
+    const playAudioChunk = (base64Audio: string) => {
+      if (!audioContextRef.current) return;
+
+      const binary = atob(base64Audio);
+      const bytes = new Uint8Array(binary.length);
+      for (let i = 0; i < binary.length; i++) {
+        bytes[i] = binary.charCodeAt(i);
+      }
+
+      const pcm16 = new Int16Array(bytes.buffer);
+      const float32 = new Float32Array(pcm16.length);
+      for (let i = 0; i < pcm16.length; i++) {
+        float32[i] = pcm16[i] / (pcm16[i] < 0 ? 0x8000 : 0x7FFF);
+      }
+
+      const audioBuffer = audioContextRef.current.createBuffer(1, float32.length, 24000);
+      audioBuffer.getChannelData(0).set(float32);
+
+      const source = audioContextRef.current.createBufferSource();
+      source.buffer = audioBuffer;
+      source.connect(audioContextRef.current.destination);
+      source.start();
+    };
+
+    return { playAudioChunk };
+  }
+  ```
+- **Dependencies**: Task 4.2
+- **Estimated Effort**: 1.5 hours
+
+#### Task 4.5: Define generate_diagram Function Schema
+- **Description**: Create the function definition that OpenAI will use to output diagram structures
+- **Files to create**:
+  - `src/lib/function-schemas.ts` - OpenAI function definitions
+- **Implementation Details**:
+  - Define JSON schema for `generate_diagram` function
+  - Specify parameters: nodes array and edges array
+  - Include node properties: id, label, type
+  - Include edge properties: source, target, label
+  - Add descriptions for AI understanding
+- **Function Schema**:
+  ```typescript
+  export const generateDiagramSchema = {
+    name: 'generate_diagram',
+    description: 'Generate a diagram from the user\'s spoken description. Create nodes for entities/steps and edges for relationships/flow. Do not specify coordinates.',
+    parameters: {
+      type: 'object',
+      properties: {
+        nodes: {
+          type: 'array',
+          description: 'List of nodes in the diagram',
+          items: {
+            type: 'object',
+            properties: {
+              id: {
+                type: 'string',
+                description: 'Unique identifier for the node'
+              },
+              label: {
+                type: 'string',
+                description: 'Display text for the node'
+              },
+              type: {
+                type: 'string',
+                enum: ['process', 'decision', 'start', 'end', 'data', 'default'],
+                description: 'Semantic type of the node'
+              }
+            },
+            required: ['id', 'label', 'type']
+          }
+        },
+        edges: {
+          type: 'array',
+          description: 'List of edges connecting nodes',
+          items: {
+            type: 'object',
+            properties: {
+              id: {
+                type: 'string',
+                description: 'Unique identifier for the edge'
+              },
+              source: {
+                type: 'string',
+                description: 'ID of the source node'
+              },
+              target: {
+                type: 'string',
+                description: 'ID of the target node'
+              },
+              label: {
+                type: 'string',
+                description: 'Optional label for the edge'
+              }
+            },
+            required: ['id', 'source', 'target']
+          }
+        }
+      },
+      required: ['nodes', 'edges']
+    }
+  };
+  ```
+- **Dependencies**: Task 2.2
+- **Estimated Effort**: 1 hour
+
+#### Task 4.6: Implement Session Configuration
+- **Description**: Set up the initial session configuration for OpenAI Realtime API with function definitions
+- **Files to modify**:
+  - `src/hooks/useRealtimeAPI.ts` - Add session setup
+- **Implementation Details**:
+  - Send `session.update` event on connection
+  - Configure modalities (text and audio)
+  - Register `generate_diagram` function
+  - Set instructions for the AI assistant
+  - Configure voice and turn detection
+- **Key Code Pattern**:
+  ```typescript
+  const configureSession = () => {
+    sendEvent({
+      type: 'session.update',
+      session: {
+        modalities: ['text', 'audio'],
+        instructions: 'You are a diagram generation assistant. Listen to the user\'s description and create a structured diagram by calling the generate_diagram function. Identify entities, processes, decisions, and their relationships. Do not specify coordinates or positions.',
+        voice: 'alloy',
+        input_audio_format: 'pcm16',
+        output_audio_format: 'pcm16',
+        input_audio_transcription: {
+          model: 'whisper-1'
+        },
+        turn_detection: {
+          type: 'server_vad',
+          threshold: 0.5,
+          prefix_padding_ms: 300,
+          silence_duration_ms: 500
+        },
+        tools: [generateDiagramSchema],
+        tool_choice: 'auto'
+      }
+    });
+  };
+  ```
+- **Dependencies**: Task 4.5
+- **Estimated Effort**: 1 hour
+
+#### Task 4.7: Test WebSocket Connection
+- **Description**: Verify WebSocket connection to OpenAI and basic event flow
+- **Testing Steps**:
+  - Start application and connect to WebSocket
+  - Send test events and verify responses
+  - Check browser console for WebSocket messages
+  - Verify session configuration is accepted
+- **Success Criteria**:
+  - WebSocket connects successfully
+  - Session configuration is acknowledged
+  - No connection errors in console
+- **Dependencies**: Task 4.6
+- **Estimated Effort**: 30 minutes
+
+### Phase 5: Fusion & Real-Time Diagram Generation
+
+#### Task 5.1: Create Voice Interface Component
+- **Description**: Build a UI component with microphone button and connection status
+- **Files to create**:
+  - `src/components/features/VoiceInterface.tsx` - Voice control UI
+- **Implementation Details**:
+  - Use lucide-react for icons (Mic, MicOff, Wifi, WifiOff)
+  - Add record button with visual feedback
+  - Display connection status
+  - Show transcription of user speech
+  - Add loading states during processing
+- **UI Elements**:
+  - Connection status indicator
+  - Microphone button (start/stop recording)
+  - Transcription display area
+  - Visual feedback during recording
+- **Dependencies**: Task 4.3, Task 4.4
+- **Estimated Effort**: 2 hours
+
+#### Task 5.2: Implement Function Call Handler
+- **Description**: Handle function_call events from OpenAI and trigger diagram generation
+- **Files to create**:
+  - `src/lib/realtime-handlers.ts` - Event handlers for Realtime API
+- **Implementation Details**:
+  - Listen for `response.function_call_arguments.done` events
+  - Parse function call arguments (GraphModel)
+  - Validate graph structure
+  - Run layout computation
+  - Generate Tldraw shapes
+  - Send function output back to OpenAI
+  - Handle errors gracefully
+- **Key Code Pattern**:
+  ```typescript
+  import { Editor } from 'tldraw';
+  import { GraphModel } from '@/types/graph';
+  import { getAutoLayout } from './layout-engine';
+  import { generateTldrawShapes } from './tldraw-helpers';
+
+  export function handleFunctionCall(
+    event: any,
+    editor: Editor,
+    sendEvent: (event: any) => void
+  ) {
+    if (event.name === 'generate_diagram') {
+      try {
+        const graphModel: GraphModel = JSON.parse(event.arguments);
+
+        // Validate
+        if (!graphModel.nodes || !graphModel.edges) {
+          throw new Error('Invalid graph model');
+        }
+
+        // Clear canvas
+        editor.selectAll();
+        editor.deleteShapes(editor.getSelectedShapeIds());
+
+        // Run layout
+        const layout = getAutoLayout(graphModel);
+
+        // Generate shapes
+        generateTldrawShapes(layout, editor);
+
+        // Zoom to fit
+        editor.zoomToFit();
+
+        // Send success response
+        sendEvent({
+          type: 'conversation.item.create',
+          item: {
+            type: 'function_call_output',
+            call_id: event.call_id,
+            output: JSON.stringify({
+              success: true,
+              nodesCreated: graphModel.nodes.length,
+              edgesCreated: graphModel.edges.length
+            })
+          }
+        });
+
+        // Request AI to continue
+        sendEvent({ type: 'response.create' });
+
+      } catch (error) {
+        console.error('Failed to generate diagram:', error);
+
+        // Send error response
+        sendEvent({
+          type: 'conversation.item.create',
+          item: {
+            type: 'function_call_output',
+            call_id: event.call_id,
+            output: JSON.stringify({
+              success: false,
+              error: error.message
+            })
+          }
+        });
+      }
+    }
+  }
+  ```
+- **Dependencies**: Task 4.2, Task 3.2
+- **Estimated Effort**: 2 hours
+
+#### Task 5.3: Wire Up Complete Event Flow
+- **Description**: Connect all components together for end-to-end voice-to-diagram flow
+- **Files to modify**:
+  - `src/app/page.tsx` - Integrate all components
+- **Implementation Details**:
+  - Import VoiceInterface, TldrawCanvas, and hooks
+  - Set up WebSocket connection
+  - Connect audio input to WebSocket
+  - Route audio output from WebSocket to speakers
+  - Handle function calls and update canvas
+  - Manage application state (recording, processing, idle)
+- **Key Code Pattern**:
+  ```typescript
+  'use client';
+
+  import { useState, useCallback } from 'react';
+  import { Editor } from 'tldraw';
+  import { TldrawCanvas } from '@/components/features/TldrawCanvas';
+  import { VoiceInterface } from '@/components/features/VoiceInterface';
+  import { useRealtimeAPI } from '@/hooks/useRealtimeAPI';
+  import { useAudioInput } from '@/hooks/useAudioInput';
+  import { useAudioOutput } from '@/hooks/useAudioOutput';
+  import { handleFunctionCall } from '@/lib/realtime-handlers';
+
+  export default function Home() {
+    const [editor, setEditor] = useState<Editor | null>(null);
+
+    const { playAudioChunk } = useAudioOutput();
+
+    const { connectionState, connect, disconnect, sendEvent } = useRealtimeAPI({
+      onMessage: (event) => {
+        // Handle different event types
+        if (event.type === 'response.audio.delta') {
+          playAudioChunk(event.delta);
+        } else if (event.type === 'response.function_call_arguments.done') {
+          if (editor) {
+            handleFunctionCall(event, editor, sendEvent);
+          }
+        }
+      }
+    });
+
+    const { isRecording, startRecording, stopRecording } = useAudioInput((audioData) => {
+      sendEvent({
+        type: 'input_audio_buffer.append',
+        audio: audioData
+      });
+    });
+
+    return (
+      <main className="relative w-full h-screen">
+        <TldrawCanvas onEditorMount={setEditor} />
+        <div className="absolute top-4 right-4 z-10">
+          <VoiceInterface
+            connectionState={connectionState}
+            isRecording={isRecording}
+            onConnect={connect}
+            onDisconnect={disconnect}
+            onStartRecording={startRecording}
+            onStopRecording={stopRecording}
+          />
+        </div>
+      </main>
+    );
+  }
+  ```
+- **Dependencies**: Task 5.1, Task 5.2
+- **Estimated Effort**: 2.5 hours
+
+#### Task 5.4: Add User Feedback and Loading States
+- **Description**: Implement visual feedback during voice processing and diagram generation
+- **Files to modify**:
+  - `src/components/features/VoiceInterface.tsx` - Add status messages
+- **Implementation Details**:
+  - Show "Listening..." when recording
+  - Display "Processing..." while AI thinks
+  - Show "Generating diagram..." during layout computation
+  - Display transcription of user's speech
+  - Show error messages if generation fails
+  - Add success notification when diagram is created
+- **UI States**:
+  - Idle: Ready to record
+  - Recording: Actively capturing audio
+  - Processing: AI is analyzing speech
+  - Generating: Creating diagram
+  - Error: Display error message
+  - Success: Diagram created confirmation
+- **Dependencies**: Task 5.3
+- **Estimated Effort**: 1.5 hours
+
+#### Task 5.5: End-to-End Testing
+- **Description**: Test the complete voice-to-diagram pipeline with real voice input
+- **Testing Steps**:
+  1. Connect to WebSocket
+  2. Click record and speak a diagram description
+  3. Verify transcription appears
+  4. Wait for AI to process and call function
+  5. Verify diagram appears on canvas with correct layout
+  6. Test multiple descriptions in sequence
+  7. Test error cases (unclear speech, invalid descriptions)
+- **Test Cases**:
+  - Simple linear process: "Create a diagram with start, process, and end"
+  - Branching flow: "Show a decision between two paths"
+  - Complex flowchart: "Create a user registration flow with validation"
+- **Success Criteria**:
+  - Voice input is captured and transcribed
+  - AI generates appropriate graph structure
+  - Layout is computed correctly
+  - Diagram renders on canvas
+  - Arrows connect nodes properly
+  - Multiple iterations work without errors
+- **Dependencies**: Task 5.4
+- **Estimated Effort**: 2 hours
+
+### Phase 6: Polish & Optimization
+
+#### Task 6.1: Implement Clear Canvas Function
+- **Description**: Add a button to clear the canvas and reset for a new diagram
+- **Files to modify**:
+  - `src/components/features/VoiceInterface.tsx` - Add clear button
+  - `src/lib/tldraw-helpers.ts` - Add clear function
+- **Implementation Details**:
+  - Add clear/trash icon button
+  - Implement function to remove all shapes
+  - Add confirmation dialog for destructive action
+- **Dependencies**: Task 5.3
+- **Estimated Effort**: 30 minutes
+
+#### Task 6.2: Add Diagram Export Functionality
+- **Description**: Enable users to export diagrams as images or JSON
+- **Files to create**:
+  - `src/lib/export-helpers.ts` - Export utilities
+- **Files to modify**:
+  - `src/components/features/VoiceInterface.tsx` - Add export buttons
+- **Implementation Details**:
+  - Export as PNG using Tldraw's export API
+  - Export as SVG for vector graphics
+  - Export graph structure as JSON
+  - Add download triggers for each format
+- **Dependencies**: Task 5.3
+- **Estimated Effort**: 1.5 hours
+
+#### Task 6.3: Improve Layout Algorithm Configuration
+- **Description**: Add options to customize layout direction and spacing
+- **Files to modify**:
+  - `src/lib/layout-engine.ts` - Add configuration parameters
+- **Implementation Details**:
+  - Accept layout options (rankdir, nodesep, ranksep)
+  - Expose layout configuration in UI (optional)
+  - Support different layout directions (TB, LR, BT, RL)
+  - Adjust spacing based on diagram complexity
+- **Dependencies**: Task 3.1
+- **Estimated Effort**: 1 hour
+
+#### Task 6.4: Add Error Boundaries and Error Handling
+- **Description**: Implement comprehensive error handling and user-friendly error messages
+- **Files to create**:
+  - `src/components/ui/ErrorBoundary.tsx` - React error boundary
+- **Files to modify**:
+  - `src/app/layout.tsx` - Wrap with error boundary
+- **Implementation Details**:
+  - Catch React errors with error boundary
+  - Handle WebSocket errors gracefully
+  - Display user-friendly error messages
+  - Add retry mechanisms for recoverable errors
+  - Log errors for debugging
+- **Dependencies**: Task 5.3
+- **Estimated Effort**: 1.5 hours
+
+#### Task 6.5: Optimize Performance
+- **Description**: Implement performance optimizations for large diagrams and real-time updates
+- **Files to modify**:
+  - `src/lib/tldraw-helpers.ts` - Batch shape creation
+  - `src/hooks/useRealtimeAPI.ts` - Optimize event handling
+- **Implementation Details**:
+  - Batch shape creation instead of individual creates
+  - Debounce audio streaming for efficiency
+  - Optimize re-renders with useMemo and useCallback
+  - Profile and optimize layout computation for large graphs
+- **Dependencies**: Task 5.3
+- **Estimated Effort**: 2 hours
+
+#### Task 6.6: Add Keyboard Shortcuts
+- **Description**: Implement keyboard shortcuts for common actions
+- **Files to create**:
+  - `src/hooks/useKeyboardShortcuts.ts` - Keyboard shortcut handling
+- **Implementation Details**:
+  - Space bar: Start/stop recording
+  - Ctrl/Cmd + K: Clear canvas
+  - Ctrl/Cmd + E: Export diagram
+  - Ctrl/Cmd + Z: Undo (use Tldraw's built-in)
+  - Escape: Stop recording and disconnect
+- **Dependencies**: Task 6.1, Task 6.2
+- **Estimated Effort**: 1 hour
+
+#### Task 6.7: Style and UI Polish
+- **Description**: Refine UI with better styling, animations, and responsive design
+- **Files to modify**:
+  - `src/components/features/VoiceInterface.tsx` - Improve styling
+  - `src/app/globals.css` - Add custom styles and animations
+- **Implementation Details**:
+  - Add smooth transitions for state changes
+  - Implement responsive design for mobile devices
+  - Add loading spinners and progress indicators
+  - Improve color scheme and visual hierarchy
+  - Add hover states and focus indicators
+  - Polish button styles with lucide-react icons
+- **Dependencies**: Task 5.4
+- **Estimated Effort**: 2 hours
+
+#### Task 6.8: Create Documentation
+- **Description**: Write comprehensive documentation for setup, usage, and development
+- **Files to create**:
+  - `README.md` - Project overview and setup guide
+  - `docs/DEVELOPMENT.md` - Development guide
+  - `docs/ARCHITECTURE.md` - Technical architecture
+  - `docs/API.md` - API documentation
+- **Documentation Sections**:
+  - Project overview and features
+  - Installation and setup instructions
+  - Environment variable configuration
+  - Usage guide with examples
+  - Architecture overview
+  - Component documentation
+  - Troubleshooting guide
+  - Contributing guidelines
+- **Dependencies**: Task 6.7
+- **Estimated Effort**: 2 hours
+
+### Phase 7: Testing & Quality Assurance
+
+#### Task 7.1: Write Unit Tests for Layout Engine
+- **Description**: Create unit tests for the Dagre layout computation
+- **Files to create**:
+  - `src/lib/__tests__/layout-engine.test.ts` - Layout tests
+- **Test Cases**:
+  - Test basic linear layout
+  - Test branching structures
+  - Test cyclic graphs
+  - Test empty graphs
+  - Test single node graphs
+  - Verify position calculations
+  - Test different layout directions
+- **Dependencies**: Task 3.1
+- **Estimated Effort**: 1.5 hours
+
+#### Task 7.2: Write Unit Tests for Tldraw Helpers
+- **Description**: Create unit tests for shape generation functions
+- **Files to create**:
+  - `src/lib/__tests__/tldraw-helpers.test.ts` - Shape generation tests
+- **Test Cases**:
+  - Test shape ID generation
+  - Test node type to geo shape mapping
+  - Test edge to arrow conversion
+  - Test shape property generation
+  - Mock Editor and verify method calls
+- **Dependencies**: Task 3.2
+- **Estimated Effort**: 1.5 hours
+
+#### Task 7.3: Write Integration Tests for Function Handler
+- **Description**: Test the function call handling and diagram generation pipeline
+- **Files to create**:
+  - `src/lib/__tests__/realtime-handlers.test.ts` - Handler integration tests
+- **Test Cases**:
+  - Test valid function call handling
+  - Test invalid graph model handling
+  - Test error responses
+  - Test Editor integration
+  - Mock WebSocket events
+- **Dependencies**: Task 5.2
+- **Estimated Effort**: 2 hours
+
+#### Task 7.4: E2E Testing Setup
+- **Description**: Set up end-to-end testing with Playwright or Cypress
+- **Files to create**:
+  - `e2e/voice-to-diagram.spec.ts` - E2E test suite
+  - `playwright.config.ts` or `cypress.config.ts` - Test configuration
+- **Test Scenarios**:
+  - Test canvas rendering
+  - Test mock graph generation
+  - Test WebSocket connection (mocked)
+  - Test UI interactions
+  - Test export functionality
+- **Dependencies**: Task 6.7
+- **Estimated Effort**: 2.5 hours
+
+#### Task 7.5: Browser Compatibility Testing
+- **Description**: Test application across different browsers and devices
+- **Testing Matrix**:
+  - Chrome/Edge (latest)
+  - Firefox (latest)
+  - Safari (latest)
+  - Mobile Safari (iOS)
+  - Mobile Chrome (Android)
+- **Test Areas**:
+  - WebSocket connectivity
+  - Audio input/output
+  - Canvas rendering
+  - UI responsiveness
+  - Performance
+- **Dependencies**: Task 6.7
+- **Estimated Effort**: 2 hours
+
+#### Task 7.6: Accessibility Audit
+- **Description**: Ensure application meets accessibility standards
+- **Files to modify**:
+  - All component files - Add ARIA labels
+- **Accessibility Checklist**:
+  - Keyboard navigation support
+  - Screen reader compatibility
+  - Focus indicators
+  - Color contrast ratios
+  - ARIA labels and roles
+  - Alt text for icons
+- **Tools**: Use Lighthouse, axe DevTools
+- **Dependencies**: Task 6.7
+- **Estimated Effort**: 2 hours
+
+#### Task 7.7: Performance Profiling
+- **Description**: Profile application performance and optimize bottlenecks
+- **Testing Areas**:
+  - Initial load time
+  - Time to interactive
+  - WebSocket message latency
+  - Layout computation speed
+  - Canvas rendering performance
+  - Memory usage
+- **Tools**: Chrome DevTools, Lighthouse
+- **Optimization Targets**:
+  - First Contentful Paint < 1.5s
+  - Time to Interactive < 3s
+  - Layout computation < 100ms for 50 nodes
+- **Dependencies**: Task 6.5
+- **Estimated Effort**: 2 hours
+
+### Phase 8: Deployment & DevOps
+
+#### Task 8.1: Configure Production Build
+- **Description**: Optimize Next.js configuration for production deployment
+- **Files to modify**:
+  - `next.config.js` - Production optimizations
+- **Configuration**:
+  - Enable minification and compression
+  - Configure output standalone mode
+  - Set up environment variable handling
+  - Configure security headers
+  - Enable static optimization where possible
+- **Dependencies**: Task 6.8
+- **Estimated Effort**: 1 hour
+
+#### Task 8.2: Set Up Docker Configuration
+- **Description**: Create Docker configuration for containerized deployment
+- **Files to create**:
+  - `Dockerfile` - Production container
+  - `docker-compose.yml` - Local development with Docker
+  - `.dockerignore` - Exclude files from image
+- **Implementation**:
+  - Multi-stage build for optimized image size
+  - Node.js Alpine base image
+  - Production dependencies only
+  - Health check endpoint
+- **Dependencies**: Task 8.1
+- **Estimated Effort**: 1.5 hours
+
+#### Task 8.3: Create Deployment Documentation
+- **Description**: Document deployment process for various platforms
+- **Files to create**:
+  - `docs/DEPLOYMENT.md` - Deployment guide
+- **Platforms to Document**:
+  - Vercel (recommended for Next.js)
+  - Docker deployment
+  - AWS deployment
+  - Environment variable setup
+  - WebSocket relay configuration
+- **Dependencies**: Task 8.2
+- **Estimated Effort**: 1.5 hours
+
+#### Task 8.4: Set Up CI/CD Pipeline
+- **Description**: Configure automated testing and deployment
+- **Files to create**:
+  - `.github/workflows/ci.yml` - CI workflow
+  - `.github/workflows/deploy.yml` - Deployment workflow
+- **Pipeline Steps**:
+  - Lint code
+  - Run unit tests
+  - Run integration tests
+  - Build application
+  - Deploy to staging
+  - Deploy to production (on release)
+- **Dependencies**: Task 7.4
+- **Estimated Effort**: 2 hours
+
+#### Task 8.5: Configure Monitoring and Logging
+- **Description**: Set up application monitoring and error tracking
+- **Implementation**:
+  - Integrate error tracking (Sentry, LogRocket, etc.)
+  - Set up performance monitoring
+  - Configure WebSocket connection monitoring
+  - Add custom logging for critical paths
+  - Set up alerts for errors
+- **Dependencies**: Task 8.1
+- **Estimated Effort**: 2 hours
+
+## Codebase Integration Points
+
+### New Files to Create
+
+#### Core Application
+- `src/app/layout.tsx` - Root layout with Tldraw styles
+- `src/app/page.tsx` - Main application page
+- `src/app/globals.css` - Global styles and Tailwind directives
+
+#### Components
+- `src/components/features/TldrawCanvas.tsx` - Tldraw canvas wrapper
+- `src/components/features/VoiceInterface.tsx` - Voice control UI
+- `src/components/ui/ErrorBoundary.tsx` - Error handling component
+
+#### Hooks
+- `src/hooks/useRealtimeAPI.ts` - WebSocket client for OpenAI
+- `src/hooks/useAudioInput.ts` - Microphone capture
+- `src/hooks/useAudioOutput.ts` - Audio playback
+- `src/hooks/useKeyboardShortcuts.ts` - Keyboard controls
+
+#### Libraries
+- `src/lib/layout-engine.ts` - Dagre layout computation
+- `src/lib/tldraw-helpers.ts` - Tldraw shape utilities
+- `src/lib/function-schemas.ts` - OpenAI function definitions
+- `src/lib/realtime-handlers.ts` - Event handlers
+- `src/lib/export-helpers.ts` - Export utilities
+- `src/lib/mock-data.ts` - Test data
+
+#### Types
+- `src/types/graph.ts` - Graph model interfaces
+
+#### API Routes
+- `src/app/api/realtime/route.ts` - WebSocket relay endpoint
+
+#### Configuration
+- `package.json` - Dependencies and scripts
+- `next.config.js` - Next.js configuration
+- `tailwind.config.ts` - TailwindCSS configuration
+- `tsconfig.json` - TypeScript configuration
+- `.env.local` - Local environment variables
+- `.env.example` - Environment variable template
+
+#### Documentation
+- `README.md` - Project overview and setup
+- `docs/DEVELOPMENT.md` - Development guide
+- `docs/ARCHITECTURE.md` - Technical architecture
+- `docs/API.md` - API documentation
+- `docs/DEPLOYMENT.md` - Deployment guide
+
+#### Testing
+- `src/lib/__tests__/layout-engine.test.ts` - Layout tests
+- `src/lib/__tests__/tldraw-helpers.test.ts` - Shape generation tests
+- `src/lib/__tests__/realtime-handlers.test.ts` - Handler tests
+- `e2e/voice-to-diagram.spec.ts` - E2E tests
+- `playwright.config.ts` or `cypress.config.ts` - Test config
+
+#### DevOps
+- `Dockerfile` - Production container
+- `docker-compose.yml` - Docker development setup
+- `.dockerignore` - Docker ignore rules
+- `.github/workflows/ci.yml` - CI pipeline
+- `.github/workflows/deploy.yml` - Deployment pipeline
+
+### Existing Patterns to Follow
+
+Since this is a greenfield project, we'll establish these patterns:
+
+#### Component Structure
+- Use TypeScript for all files
+- Functional components with hooks
+- Props interfaces defined above component
+- Separate UI components from feature components
+
+#### State Management
+- React hooks for local state
+- Tldraw store for canvas state
+- No global state library needed initially
+
+#### Code Organization
+- Feature-based organization for components
+- Utility functions in `lib/` directory
+- Shared types in `types/` directory
+- One component per file
+
+#### Naming Conventions
+- PascalCase for components and types
+- camelCase for functions and variables
+- kebab-case for file names (except components)
+- Descriptive names that indicate purpose
+
+#### Error Handling
+- Try-catch for async operations
+- Error boundaries for React errors
+- User-friendly error messages
+- Console logging for debugging
+
+## Technical Design
+
+### Architecture Diagram
+
+```
+┌─────────────────────────────────────────────────────────────┐
+│                       User Interface                         │
+│  ┌────────────────┐                    ┌─────────────────┐  │
+│  │ VoiceInterface │                    │  TldrawCanvas   │  │
+│  │  - Mic Button  │                    │  - Infinite     │  │
+│  │  - Status      │                    │    Canvas       │  │
+│  │  - Transcript  │                    │  - Shapes       │  │
+│  └────────┬───────┘                    └────────▲────────┘  │
+│           │                                      │           │
+└───────────┼──────────────────────────────────────┼───────────┘
+            │                                      │
+            │ Audio                                │ Shapes
+            │ Stream                               │ Update
+            │                                      │
+┌───────────▼──────────────────────────────────────┼───────────┐
+│                    Application Logic              │           │
+│                                                   │           │
+│  ┌──────────────────┐        ┌──────────────────┴────────┐  │
+│  │ useRealtimeAPI   │        │  Realtime Handlers        │  │
+│  │  - WebSocket     │────────▶  - Parse function calls   │  │
+│  │  - Send events   │        │  - Validate graph model   │  │
+│  │  - Receive events│        │  - Trigger diagram gen    │  │
+│  └────────┬─────────┘        └──────────┬────────────────┘  │
+│           │                              │                   │
+│           │ Function                     │ Graph              │
+│           │ Call                         │ Model             │
+│           │                              │                   │
+│  ┌────────▼──────────┐        ┌─────────▼────────────────┐  │
+│  │ OpenAI Events     │        │  Layout Engine (Dagre)   │  │
+│  │  - Audio delta    │        │  - Compute positions     │  │
+│  │  - Transcripts    │        │  - Auto-layout           │  │
+│  │  - Function calls │        │  - No hallucination      │  │
+│  └───────────────────┘        └─────────┬────────────────┘  │
+│                                          │                   │
+│                                          │ Positioned         │
+│                                          │ Nodes/Edges       │
+│                                          │                   │
+│                               ┌──────────▼────────────────┐  │
+│                               │  Tldraw Helpers          │  │
+│                               │  - Shape generation      │  │
+│                               │  - Editor API calls      │  │
+│                               └──────────────────────────┘  │
+│                                                              │
+└──────────────────────────────────────────────────────────────┘
+                               │
+                               │ WebSocket
+                               │
+┌──────────────────────────────▼───────────────────────────────┐
+│                    External Services                          │
+│                                                               │
+│  ┌────────────────────────┐      ┌──────────────────────┐   │
+│  │ Next.js API Route      │      │ OpenAI Realtime API  │   │
+│  │  - WebSocket Relay     │◀─────▶  - GPT-4o Model     │   │
+│  │  - Hide API key        │      │  - Function Calling  │   │
+│  └────────────────────────┘      │  - Audio Streaming   │   │
+│                                   └──────────────────────┘   │
+└──────────────────────────────────────────────────────────────┘
+```
+
+### Data Flow
+
+#### Voice-to-Diagram Flow
+
+1. **User Speaks**: User clicks record button and speaks description
+2. **Audio Capture**: `useAudioInput` captures microphone audio
+3. **Audio Encoding**: Convert to PCM16 format at 24kHz
+4. **Stream to OpenAI**: Send audio chunks via WebSocket
+5. **AI Processing**: OpenAI Realtime API transcribes and understands
+6. **Function Call**: AI decides to call `generate_diagram` function
+7. **Graph Model**: Function call contains JSON graph (nodes + edges)
+8. **Layout Computation**: Dagre calculates X/Y positions
+9. **Shape Generation**: Convert positioned nodes to Tldraw shapes
+10. **Canvas Update**: Insert shapes into Tldraw editor
+11. **Visual Feedback**: User sees diagram appear in real-time
+12. **AI Response**: OpenAI speaks confirmation of diagram creation
+
+#### Event Flow Diagram
+
+```
+User → Mic Button → useAudioInput → WebSocket
+                                      ↓
+                          OpenAI Realtime API
+                                      ↓
+                        Transcription + Understanding
+                                      ↓
+                         Function Call: generate_diagram
+                                      ↓
+                     GraphModel: { nodes, edges }
+                                      ↓
+                    Realtime Handler (validates)
+                                      ↓
+                   Layout Engine (Dagre computes positions)
+                                      ↓
+                  PositionedNodes + Edges
+                                      ↓
+                  Tldraw Helpers (generate shapes)
+                                      ↓
+                  Editor.createShape() × N
+                                      ↓
+                  Canvas Updates (diagram appears)
+                                      ↓
+                  Function Output sent to OpenAI
+                                      ↓
+                  AI Confirmation (audio response)
+```
+
+### State Management
+
+#### Application State
+- **Connection State**: disconnected | connecting | connected
+- **Recording State**: idle | recording
+- **Processing State**: idle | processing | generating
+- **Error State**: null | Error object
+
+#### Tldraw State
+- Managed internally by Tldraw store
+- Shapes, arrows, selections
+- Viewport position and zoom
+- Accessed via Editor instance
+
+#### WebSocket State
+- Connection reference in `useRealtimeAPI`
+- Audio streaming active/inactive
+- Pending function calls
+
+### API Endpoints
+
+#### Next.js API Routes
+
+**`GET /api/realtime`**
+- Purpose: WebSocket relay to OpenAI Realtime API
+- Authentication: Server-side API key injection
+- Upgrade: HTTP → WebSocket
+- Relay: Bidirectional message passing
+
+#### OpenAI Realtime API Events
+
+**Client → Server**:
+- `session.update` - Configure session
+- `input_audio_buffer.append` - Stream audio
+- `conversation.item.create` - Send function output
+- `response.create` - Request AI response
+
+**Server → Client**:
+- `session.created` - Session ready
+- `input_audio_buffer.speech_started` - User started speaking
+- `input_audio_buffer.speech_stopped` - User stopped speaking
+- `conversation.item.created` - New conversation item
+- `response.audio.delta` - Audio response chunk
+- `response.function_call_arguments.done` - Function call ready
+- `response.done` - Response complete
+
+### Type System
+
+#### Core Types
+
+```typescript
+// Graph model (from AI)
+interface GraphNode {
+  id: string;
+  label: string;
+  type: 'process' | 'decision' | 'start' | 'end' | 'data' | 'default';
+  metadata?: Record<string, unknown>;
+}
+
+interface GraphEdge {
+  id: string;
+  source: string;
+  target: string;
+  label?: string;
+}
+
+interface GraphModel {
+  nodes: GraphNode[];
+  edges: GraphEdge[];
+}
+
+// Positioned nodes (after layout)
+interface PositionedNode extends GraphNode {
+  x: number;
+  y: number;
+  width: number;
+  height: number;
+}
+
+interface LayoutResult {
+  nodes: PositionedNode[];
+  edges: GraphEdge[];
+}
+
+// OpenAI events
+interface FunctionCallEvent {
+  type: 'response.function_call_arguments.done';
+  call_id: string;
+  name: string;
+  arguments: string; // JSON string of GraphModel
+}
+
+// Application state
+type ConnectionState = 'disconnected' | 'connecting' | 'connected';
+type RecordingState = 'idle' | 'recording';
+type ProcessingState = 'idle' | 'processing' | 'generating';
+```
+
+## Dependencies and Libraries
+
+### Production Dependencies
+
+- **next** (14.3.0+) - React framework with App Router
+- **react** (18.3.0+) - UI library
+- **react-dom** (18.3.0+) - React DOM rendering
+- **tldraw** (latest) - Infinite canvas and shape library
+- **@dagrejs/dagre** (latest) - Graph layout algorithm
+- **lucide-react** (latest) - Icon library
+- **tailwindcss** (3.4.0+) - CSS framework
+
+### Development Dependencies
+
+- **typescript** (5.3.0+) - Type checking
+- **@types/react** - React type definitions
+- **@types/react-dom** - React DOM type definitions
+- **@types/dagre** - Dagre type definitions
+- **eslint** - Code linting
+- **eslint-config-next** - Next.js ESLint configuration
+- **prettier** - Code formatting
+- **@playwright/test** or **cypress** - E2E testing
+- **jest** - Unit testing framework
+- **@testing-library/react** - React component testing
+
+### Optional Dependencies
+
+- **@sentry/nextjs** - Error tracking
+- **ws** - WebSocket library for custom relay server
+
+## Testing Strategy
+
+### Unit Tests
+
+#### Layout Engine Tests
+- Test Dagre layout computation
+- Verify position calculations
+- Test different graph structures
+- Test edge cases (empty, single node)
+
+#### Tldraw Helpers Tests
+- Test shape generation
+- Test node type mapping
+- Test edge/arrow creation
+- Mock Editor API calls
+
+#### Function Handler Tests
+- Test function call parsing
+- Test error handling
+- Test Editor integration
+- Mock WebSocket events
+
+### Integration Tests
+
+#### Realtime Handler Integration
+- Test complete function call flow
+- Test layout + shape generation pipeline
+- Test error propagation
+- Mock WebSocket and Editor
+
+### End-to-End Tests
+
+#### User Workflows
+- Test canvas rendering
+- Test mock graph generation button
+- Test WebSocket connection (mocked)
+- Test UI state transitions
+- Test export functionality
+
+#### Browser Compatibility
+- Chrome/Edge
+- Firefox
+- Safari
+- Mobile browsers
+
+### Performance Tests
+
+- Layout computation speed (target: <100ms for 50 nodes)
+- Canvas rendering performance
+- WebSocket latency
+- Memory usage over time
+- Audio streaming latency
+
+### Accessibility Tests
+
+- Keyboard navigation
+- Screen reader compatibility
+- Focus management
+- Color contrast
+- ARIA labels
+
+## Success Criteria
+
+### Functional Requirements
+- ✅ User can speak naturally to describe a diagram
+- ✅ System transcribes and understands speech
+- ✅ AI generates semantic graph model (no coordinates)
+- ✅ Dagre computes layout automatically
+- ✅ Diagram appears on Tldraw canvas in real-time
+- ✅ Nodes have correct shapes based on type
+- ✅ Edges connect nodes with proper arrows
+- ✅ Multiple diagrams can be created in sequence
+- ✅ User receives audio confirmation from AI
+
+### Performance Requirements
+- ✅ Initial page load < 3 seconds
+- ✅ WebSocket connection < 1 second
+- ✅ Layout computation < 100ms (50 nodes)
+- ✅ Audio-to-diagram latency < 5 seconds
+- ✅ Smooth canvas interaction (60 FPS)
+
+### Quality Requirements
+- ✅ No coordinate hallucination from AI
+- ✅ TypeScript type safety throughout
+- ✅ Comprehensive error handling
+- ✅ Clean separation of concerns
+- ✅ 80%+ test coverage
+- ✅ Accessible (WCAG AA)
+- ✅ Browser compatible (modern browsers)
+
+### User Experience Requirements
+- ✅ Clear visual feedback during processing
+- ✅ Error messages are user-friendly
+- ✅ Microphone permissions handled gracefully
+- ✅ Canvas is responsive and intuitive
+- ✅ Export functionality works reliably
+- ✅ Keyboard shortcuts for power users
+
+## Notes and Considerations
+
+### Technical Challenges
+
+#### WebSocket Relay in Next.js
+- **Challenge**: Next.js doesn't natively support WebSocket in API routes
+- **Solution Options**:
+  1. Use a separate Node.js WebSocket server alongside Next.js
+  2. Use Vercel's serverless functions with WebSocket support
+  3. Use external relay service
+  4. Deploy custom server with Next.js custom server mode
+- **Recommendation**: Start with separate WebSocket server for development, evaluate Vercel deployment options
+
+#### Audio Processing
+- **Challenge**: Browser audio APIs can be complex and browser-specific
+- **Considerations**:
+  - Ensure microphone permissions are requested correctly
+  - Handle different sample rates across browsers
+  - Test audio quality and latency
+  - Consider using existing audio libraries if needed
+
+#### Real-Time Performance
+- **Challenge**: Large diagrams may cause performance issues
+- **Optimizations**:
+  - Batch shape creation instead of individual operations
+  - Use Tldraw's built-in performance optimizations
+  - Limit diagram complexity (suggest breaking into multiple diagrams)
+  - Profile and optimize hot paths
+
+#### Function Calling Reliability
+- **Challenge**: AI may not always call function correctly
+- **Mitigations**:
+  - Clear function schema with examples
+  - Strong system instructions
+  - Validation of function arguments
+  - Graceful error handling and retry logic
+  - User feedback if AI doesn't understand
+
+### Future Enhancements
+
+#### Phase 9: Advanced Features
+- **Collaborative Editing**: Multiple users working on same diagram
+- **Diagram Templates**: Pre-built templates for common diagram types
+- **Custom Node Types**: User-defined shapes and styling
+- **Animation**: Animate diagram creation step-by-step
+- **Undo/Redo**: Enhanced history management beyond Tldraw default
+- **Auto-Save**: Persist diagrams to database or local storage
+- **Diagram Library**: Save and browse previous diagrams
+
+#### Phase 10: AI Enhancements
+- **Diagram Modification**: Voice commands to edit existing diagrams
+- **Multi-Turn Conversations**: Build diagrams iteratively
+- **Intelligent Layout**: AI suggests optimal layout configurations
+- **Diagram Analysis**: AI explains or critiques diagram structure
+- **Style Suggestions**: AI recommends colors, shapes based on content
+
+#### Phase 11: Export & Integration
+- **Multiple Export Formats**: Mermaid, PlantUML, Graphviz
+- **API for Programmatic Access**: REST API for diagram generation
+- **Embeddable Widget**: Embed voice-to-diagram in other apps
+- **Cloud Storage Integration**: Save to Google Drive, Dropbox
+- **Presentation Mode**: Full-screen diagram presentation
+
+### Known Limitations
+
+1. **OpenAI API Costs**: Realtime API is relatively expensive; monitor usage
+2. **Browser Compatibility**: Some browsers may not support required audio APIs
+3. **Microphone Required**: Application requires working microphone
+4. **Internet Required**: Cannot work offline due to OpenAI dependency
+5. **Diagram Complexity**: Very large diagrams (100+ nodes) may have performance issues
+6. **Language Support**: Initially English only; expand later
+7. **Diagram Types**: Optimized for flowcharts and process diagrams; other types may need custom handling
+
+### Security Considerations
+
+1. **API Key Protection**: Never expose OpenAI API key to client
+2. **Input Validation**: Validate all graph models from AI before rendering
+3. **Rate Limiting**: Implement rate limiting to prevent abuse
+4. **Authentication**: Consider adding user authentication for production
+5. **CORS**: Configure CORS properly for WebSocket relay
+6. **Content Security Policy**: Set up CSP headers for Next.js app
+7. **Error Information**: Don't leak sensitive error details to client
+
+### Monitoring & Observability
+
+1. **Error Tracking**: Set up Sentry or similar for production errors
+2. **Performance Monitoring**: Track key metrics (layout time, render time)
+3. **WebSocket Health**: Monitor connection success rate and latency
+4. **API Usage**: Track OpenAI API calls and costs
+5. **User Analytics**: Track feature usage (export, clear, etc.)
+6. **Logging**: Structured logging for debugging and audit trails
+
+## Resources and References
+
+### Official Documentation
+- [Next.js 14 Documentation](https://nextjs.org/docs)
+- [Tldraw Documentation](https://tldraw.dev/)
+- [Dagre GitHub Repository](https://github.com/dagrejs/dagre)
+- [OpenAI Realtime API Documentation](https://platform.openai.com/docs/guides/realtime)
+
+### Research References
+- [Next.js Best Practices 2025](https://medium.com/@GoutamSingha/next-js-best-practices-in-2025-build-faster-cleaner-scalable-apps-7efbad2c3820)
+- [Next.js File Structure Guide](https://medium.com/better-dev-nextjs-react/inside-the-app-router-best-practices-for-next-js-file-and-directory-structure-2025-edition-ed6bc14a8da3)
+- [Tldraw SDK 4.0 Announcement](https://tldraw.dev/blog/tldraw-sdk-4-0)
+- [React Flow Dagre Example](https://reactflow.dev/examples/layout/dagre)
+- [OpenAI Realtime API Tutorial](https://skywork.ai/blog/agent/openai-realtime-api-javascript-tutorial-websocket-guide/)
+- [OpenAI Realtime API Cheat Sheet](https://skywork.ai/blog/openai-realtime-api-cheat-sheet-2025-quick-reference/)
+
+### Community Resources
+- [Tldraw GitHub](https://github.com/tldraw/tldraw)
+- [Next.js Examples](https://github.com/vercel/next.js/tree/canary/examples)
+- [OpenAI Community Forum](https://community.openai.com/)
+
+---
+
+*This implementation plan is ready for execution with `/execute-plan PRPs/requests/voice-to-diagram.md`*
+
+**Plan Created**: 2025-12-09
+**Estimated Total Effort**: 70-90 hours
+**Target Timeline**: 4-6 weeks (based on team size and velocity)
+**Risk Level**: Medium (WebSocket relay setup, audio processing complexity)
+**Key Success Metric**: User can speak a description and see a properly laid-out diagram within 5 seconds
diff --git a/next.config.js b/next.config.js
new file mode 100644
index 0000000..a789d05
--- /dev/null
+++ b/next.config.js
@@ -0,0 +1,15 @@
+/** @type {import('next').NextConfig} */
+const nextConfig = {
+  // Disable React Strict Mode to prevent WebSocket disconnections during development
+  // Strict Mode causes double mounting/unmounting which closes WebSocket connections
+  reactStrictMode: false,
+  webpack: (config) => {
+    config.externals.push({
+      'utf-8-validate': 'commonjs utf-8-validate',
+      'bufferutil': 'commonjs bufferutil',
+    })
+    return config
+  },
+}
+
+module.exports = nextConfig
diff --git a/package-lock.json b/package-lock.json
new file mode 100644
index 0000000..f65f663
--- /dev/null
+++ b/package-lock.json
@@ -0,0 +1,8035 @@
+{
+  "name": "voice-to-diagram",
+  "version": "0.1.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "voice-to-diagram",
+      "version": "0.1.0",
+      "dependencies": {
+        "@dagrejs/dagre": "^1.1.4",
+        "dotenv": "^16.4.5",
+        "lucide-react": "^0.460.0",
+        "next": "14.2.22",
+        "react": "^18.3.1",
+        "react-dom": "^18.3.1",
+        "tldraw": "^2.4.0",
+        "ws": "^8.18.0"
+      },
+      "devDependencies": {
+        "@types/dagre": "^0.7.52",
+        "@types/node": "^20",
+        "@types/react": "^18.3.0",
+        "@types/react-dom": "^18.3.0",
+        "autoprefixer": "^10.0.1",
+        "eslint": "^8",
+        "eslint-config-next": "14.2.22",
+        "postcss": "^8",
+        "tailwindcss": "^3.4.1",
+        "typescript": "^5"
+      }
+    },
+    "node_modules/@alloc/quick-lru": {
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+}
diff --git a/package.json b/package.json
new file mode 100644
index 0000000..49d2e1f
--- /dev/null
+++ b/package.json
@@ -0,0 +1,33 @@
+{
+  "name": "voice-to-diagram",
+  "version": "0.1.0",
+  "private": true,
+  "scripts": {
+    "dev": "next dev",
+    "build": "next build",
+    "start": "next start",
+    "lint": "next lint",
+    "test": "jest",
+    "test:watch": "jest --watch"
+  },
+  "dependencies": {
+    "next": "14.2.22",
+    "react": "^18.3.1",
+    "react-dom": "^18.3.1",
+    "tldraw": "^2.4.0",
+    "@dagrejs/dagre": "^1.1.4",
+    "lucide-react": "^0.460.0"
+  },
+  "devDependencies": {
+    "@types/node": "^20",
+    "@types/react": "^18.3.0",
+    "@types/react-dom": "^18.3.0",
+    "@types/dagre": "^0.7.52",
+    "typescript": "^5",
+    "tailwindcss": "^3.4.1",
+    "postcss": "^8",
+    "autoprefixer": "^10.0.1",
+    "eslint": "^8",
+    "eslint-config-next": "14.2.22"
+  }
+}
diff --git a/postcss.config.js b/postcss.config.js
new file mode 100644
index 0000000..33ad091
--- /dev/null
+++ b/postcss.config.js
@@ -0,0 +1,6 @@
+module.exports = {
+  plugins: {
+    tailwindcss: {},
+    autoprefixer: {},
+  },
+}
diff --git a/src/app/globals.css b/src/app/globals.css
new file mode 100644
index 0000000..13d40b8
--- /dev/null
+++ b/src/app/globals.css
@@ -0,0 +1,27 @@
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+:root {
+  --background: #ffffff;
+  --foreground: #171717;
+}
+
+@media (prefers-color-scheme: dark) {
+  :root {
+    --background: #0a0a0a;
+    --foreground: #ededed;
+  }
+}
+
+body {
+  color: var(--foreground);
+  background: var(--background);
+  font-family: Arial, Helvetica, sans-serif;
+}
+
+@layer utilities {
+  .text-balance {
+    text-wrap: balance;
+  }
+}
diff --git a/src/app/layout.tsx b/src/app/layout.tsx
new file mode 100644
index 0000000..e01de71
--- /dev/null
+++ b/src/app/layout.tsx
@@ -0,0 +1,19 @@
+import type { Metadata } from 'next'
+import './globals.css'
+
+export const metadata: Metadata = {
+  title: 'Voice to Diagram - AI-Powered Diagram Generation',
+  description: 'Convert natural spoken descriptions into live, auto-laid-out diagrams using voice and AI',
+}
+
+export default function RootLayout({
+  children,
+}: {
+  children: React.ReactNode
+}) {
+  return (
+    <html lang="en">
+      <body className="antialiased">{children}</body>
+    </html>
+  )
+}
diff --git a/src/app/page.tsx b/src/app/page.tsx
new file mode 100644
index 0000000..5561e3f
--- /dev/null
+++ b/src/app/page.tsx
@@ -0,0 +1,61 @@
+'use client';
+
+import { useState } from 'react';
+import { Editor } from 'tldraw';
+import { TldrawCanvas } from '@/components/features/TldrawCanvas';
+import { ChatPanel } from '@/components/features/ChatPanel';
+import { addTestShapes, generateTldrawShapes, clearCanvas } from '@/lib/tldraw-helpers';
+import { getAutoLayout } from '@/lib/layout-engine';
+import { mockFlowchart } from '@/lib/mock-data';
+
+export default function Home() {
+  const [editor, setEditor] = useState<Editor | null>(null);
+
+  // Test button handlers
+  const handleAddTestShapes = () => {
+    if (editor) {
+      addTestShapes(editor);
+      editor.zoomToFit();
+    }
+  };
+
+  const handleGenerateGraph = () => {
+    if (!editor) return;
+    clearCanvas(editor);
+    const layout = getAutoLayout(mockFlowchart);
+    generateTldrawShapes(layout, editor);
+    editor.zoomToFit();
+  };
+
+  return (
+    <main className="relative w-full h-screen flex">
+      {/* Left Sidebar - Chat Panel */}
+      <div className="w-96 h-full flex-shrink-0">
+        <ChatPanel editor={editor} />
+      </div>
+
+      {/* Right Side - Tldraw Canvas */}
+      <div className="flex-1 h-full relative">
+        <TldrawCanvas onEditorMount={setEditor} />
+
+        {/* Test Buttons - positioned in top right */}
+        <div className="absolute top-4 right-4 z-10 flex gap-2">
+          <button
+            onClick={handleAddTestShapes}
+            disabled={!editor}
+            className="px-4 py-2 bg-blue-500 text-white rounded-lg hover:bg-blue-600 disabled:bg-gray-300 disabled:cursor-not-allowed shadow-lg"
+          >
+            Add Test Shapes
+          </button>
+          <button
+            onClick={handleGenerateGraph}
+            disabled={!editor}
+            className="px-4 py-2 bg-green-500 text-white rounded-lg hover:bg-green-600 disabled:bg-gray-300 disabled:cursor-not-allowed shadow-lg"
+          >
+            Generate Graph
+          </button>
+        </div>
+      </div>
+    </main>
+  );
+}
diff --git a/src/components/features/ChatPanel.tsx b/src/components/features/ChatPanel.tsx
new file mode 100644
index 0000000..2be03af
--- /dev/null
+++ b/src/components/features/ChatPanel.tsx
@@ -0,0 +1,105 @@
+'use client';
+
+import { useEffect, useRef } from 'react';
+import { Editor } from 'tldraw';
+import { useChatAPI } from '@/hooks/useChatAPI';
+import { ChatMessage } from '@/components/ui/ChatMessage';
+import { ChatInput } from '@/components/ui/ChatInput';
+import { generateTldrawShapes, clearCanvas } from '@/lib/tldraw-helpers';
+import { getAutoLayout } from '@/lib/layout-engine';
+import { MessageSquare, Trash2 } from 'lucide-react';
+
+interface ChatPanelProps {
+  editor: Editor | null;
+}
+
+/**
+ * Main chat panel component with message history and input
+ */
+export function ChatPanel({ editor }: ChatPanelProps) {
+  const { messages, isLoading, error, sendMessage, clearMessages } = useChatAPI();
+  const messagesEndRef = useRef<HTMLDivElement>(null);
+
+  // Auto-scroll to bottom when new messages arrive
+  useEffect(() => {
+    messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' });
+  }, [messages]);
+
+  // Generate diagram when AI returns diagram data
+  useEffect(() => {
+    const lastMessage = messages[messages.length - 1];
+    if (lastMessage?.diagramData && editor) {
+      console.log('Generating diagram from AI response:', lastMessage.diagramData);
+
+      // Clear canvas and generate new diagram
+      clearCanvas(editor);
+      const layout = getAutoLayout(lastMessage.diagramData);
+      generateTldrawShapes(layout, editor);
+      editor.zoomToFit();
+    }
+  }, [messages, editor]);
+
+  return (
+    <div className="flex flex-col h-full bg-white border-r border-gray-200">
+      {/* Header */}
+      <div className="flex items-center justify-between p-4 border-b border-gray-200 bg-gray-50">
+        <div className="flex items-center gap-2">
+          <MessageSquare className="w-5 h-5 text-blue-500" />
+          <h2 className="font-semibold text-gray-900">Diagram Chat</h2>
+        </div>
+        <button
+          onClick={clearMessages}
+          disabled={messages.length === 0}
+          className="p-2 text-gray-500 hover:text-gray-700 hover:bg-gray-200 rounded-lg transition-colors disabled:opacity-50 disabled:cursor-not-allowed"
+          title="Clear conversation"
+        >
+          <Trash2 className="w-4 h-4" />
+        </button>
+      </div>
+
+      {/* Messages Area */}
+      <div className="flex-1 overflow-y-auto p-4 space-y-4">
+        {messages.length === 0 ? (
+          <div className="flex flex-col items-center justify-center h-full text-center p-6">
+            <MessageSquare className="w-12 h-12 text-gray-300 mb-3" />
+            <h3 className="text-lg font-medium text-gray-900 mb-2">
+              Welcome!
+            </h3>
+            <p className="text-sm text-gray-600 max-w-sm">
+              Describe the diagram you want to create, and I'll generate it for you.
+              Try something like "Create a login flow diagram" or "Show me an e-commerce checkout process."
+            </p>
+          </div>
+        ) : (
+          <>
+            {messages.map((message) => (
+              <ChatMessage key={message.id} message={message} />
+            ))}
+            <div ref={messagesEndRef} />
+          </>
+        )}
+      </div>
+
+      {/* Error Display */}
+      {error && (
+        <div className="px-4 py-2 bg-red-50 border-t border-red-200">
+          <p className="text-sm text-red-600">Error: {error}</p>
+        </div>
+      )}
+
+      {/* Input Area */}
+      <div className="p-4 border-t border-gray-200 bg-gray-50">
+        <ChatInput
+          onSend={sendMessage}
+          isLoading={isLoading}
+          disabled={!editor}
+        />
+        {!editor && (
+          <p className="text-xs text-gray-500 mt-2">
+            Waiting for canvas to load...
+          </p>
+        )}
+      </div>
+    </div>
+  );
+}
diff --git a/src/components/features/TldrawCanvas.tsx b/src/components/features/TldrawCanvas.tsx
new file mode 100644
index 0000000..7cc3adc
--- /dev/null
+++ b/src/components/features/TldrawCanvas.tsx
@@ -0,0 +1,22 @@
+'use client';
+
+import { Tldraw, Editor } from 'tldraw';
+import 'tldraw/tldraw.css';
+
+interface TldrawCanvasProps {
+  onEditorMount?: (editor: Editor) => void;
+}
+
+export function TldrawCanvas({ onEditorMount }: TldrawCanvasProps) {
+  return (
+    <div className="w-full h-screen">
+      <Tldraw
+        onMount={(editor) => {
+          if (onEditorMount) {
+            onEditorMount(editor);
+          }
+        }}
+      />
+    </div>
+  );
+}
diff --git a/src/components/ui/ChatInput.tsx b/src/components/ui/ChatInput.tsx
new file mode 100644
index 0000000..ff3a08c
--- /dev/null
+++ b/src/components/ui/ChatInput.tsx
@@ -0,0 +1,56 @@
+'use client';
+
+import { useState, KeyboardEvent } from 'react';
+import { Send, Loader2 } from 'lucide-react';
+
+interface ChatInputProps {
+  onSend: (message: string) => void;
+  isLoading: boolean;
+  disabled?: boolean;
+}
+
+/**
+ * Chat input component with send button
+ */
+export function ChatInput({ onSend, isLoading, disabled }: ChatInputProps) {
+  const [input, setInput] = useState('');
+
+  const handleSend = () => {
+    if (input.trim() && !isLoading && !disabled) {
+      onSend(input.trim());
+      setInput('');
+    }
+  };
+
+  const handleKeyDown = (e: KeyboardEvent<HTMLTextAreaElement>) => {
+    if (e.key === 'Enter' && !e.shiftKey) {
+      e.preventDefault();
+      handleSend();
+    }
+  };
+
+  return (
+    <div className="flex gap-2 items-end">
+      <textarea
+        value={input}
+        onChange={(e) => setInput(e.target.value)}
+        onKeyDown={handleKeyDown}
+        placeholder="Describe the diagram you want to create..."
+        disabled={isLoading || disabled}
+        className="flex-1 min-h-[60px] max-h-[120px] p-3 border border-gray-300 rounded-lg resize-none focus:outline-none focus:ring-2 focus:ring-blue-500 disabled:bg-gray-100 disabled:cursor-not-allowed text-gray-900 bg-white placeholder:text-gray-400"
+        rows={2}
+      />
+      <button
+        onClick={handleSend}
+        disabled={!input.trim() || isLoading || disabled}
+        className="px-4 py-3 bg-blue-500 text-white rounded-lg hover:bg-blue-600 disabled:bg-gray-300 disabled:cursor-not-allowed transition-colors flex items-center gap-2"
+      >
+        {isLoading ? (
+          <Loader2 className="w-5 h-5 animate-spin" />
+        ) : (
+          <Send className="w-5 h-5" />
+        )}
+      </button>
+    </div>
+  );
+}
diff --git a/src/components/ui/ChatMessage.tsx b/src/components/ui/ChatMessage.tsx
new file mode 100644
index 0000000..2e21f14
--- /dev/null
+++ b/src/components/ui/ChatMessage.tsx
@@ -0,0 +1,62 @@
+'use client';
+
+import { ChatMessage as ChatMessageType } from '@/hooks/useChatAPI';
+import { User, Bot, CheckCircle } from 'lucide-react';
+
+interface ChatMessageProps {
+  message: ChatMessageType;
+}
+
+/**
+ * Individual chat message display component
+ */
+export function ChatMessage({ message }: ChatMessageProps) {
+  const isUser = message.role === 'user';
+  const isAssistant = message.role === 'assistant';
+
+  return (
+    <div
+      className={`flex gap-3 p-4 ${
+        isUser ? 'bg-blue-50' : 'bg-gray-50'
+      } rounded-lg`}
+    >
+      {/* Avatar */}
+      <div
+        className={`flex-shrink-0 w-8 h-8 rounded-full flex items-center justify-center ${
+          isUser ? 'bg-blue-500' : 'bg-gray-700'
+        }`}
+      >
+        {isUser ? (
+          <User className="w-5 h-5 text-white" />
+        ) : (
+          <Bot className="w-5 h-5 text-white" />
+        )}
+      </div>
+
+      {/* Message Content */}
+      <div className="flex-1 min-w-0">
+        <div className="flex items-center gap-2 mb-1">
+          <span className="font-semibold text-sm text-gray-900">
+            {isUser ? 'You' : 'Assistant'}
+          </span>
+          <span className="text-xs text-gray-500">
+            {message.timestamp.toLocaleTimeString()}
+          </span>
+          {message.diagramData && (
+            <span className="flex items-center gap-1 text-xs text-green-600 font-medium">
+              <CheckCircle className="w-3 h-3" />
+              Diagram generated
+            </span>
+          )}
+        </div>
+
+        <div className="text-sm text-gray-800 whitespace-pre-wrap break-words">
+          {/* Remove diagram markers from display */}
+          {message.content
+            .replace(/\[DIAGRAM_START\][\s\S]*?\[DIAGRAM_END\]/g, '[Diagram generated]')
+            .trim()}
+        </div>
+      </div>
+    </div>
+  );
+}
diff --git a/src/hooks/useChatAPI.ts b/src/hooks/useChatAPI.ts
new file mode 100644
index 0000000..774fa8f
--- /dev/null
+++ b/src/hooks/useChatAPI.ts
@@ -0,0 +1,147 @@
+'use client';
+
+import { useState, useCallback } from 'react';
+import { OPENAI_CONFIG, validateOpenAIConfig } from '@/lib/openai-config';
+import { DIAGRAM_GENERATION_SYSTEM_PROMPT } from '@/lib/chat-prompts';
+import { extractDiagramFromResponse } from '@/lib/diagram-parser';
+import { GraphModel } from '@/types/graph';
+
+export interface ChatMessage {
+  id: string;
+  role: 'user' | 'assistant' | 'system';
+  content: string;
+  timestamp: Date;
+  diagramData?: GraphModel;
+}
+
+interface UseChatAPIReturn {
+  messages: ChatMessage[];
+  isLoading: boolean;
+  error: string | null;
+  sendMessage: (userMessage: string) => Promise<void>;
+  clearMessages: () => void;
+}
+
+/**
+ * Hook for managing chat conversation with OpenAI Chat Completions API
+ */
+export function useChatAPI(): UseChatAPIReturn {
+  const [messages, setMessages] = useState<ChatMessage[]>([]);
+  const [isLoading, setIsLoading] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+
+  /**
+   * Send a message to OpenAI and process the response
+   */
+  const sendMessage = useCallback(async (userMessage: string) => {
+    if (!validateOpenAIConfig()) {
+      setError('OpenAI API key not configured');
+      return;
+    }
+
+    if (!userMessage.trim()) {
+      return;
+    }
+
+    setIsLoading(true);
+    setError(null);
+
+    // Add user message to chat
+    const userMsg: ChatMessage = {
+      id: `user-${Date.now()}`,
+      role: 'user',
+      content: userMessage,
+      timestamp: new Date(),
+    };
+
+    setMessages(prev => [...prev, userMsg]);
+
+    try {
+      // Prepare messages for API call
+      const apiMessages = [
+        {
+          role: 'system',
+          content: DIAGRAM_GENERATION_SYSTEM_PROMPT,
+        },
+        ...messages.map(msg => ({
+          role: msg.role,
+          content: msg.content,
+        })),
+        {
+          role: 'user',
+          content: userMessage,
+        },
+      ];
+
+      // Call OpenAI Chat Completions API
+      const response = await fetch(`${OPENAI_CONFIG.apiBase}/chat/completions`, {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
+          'Authorization': `Bearer ${OPENAI_CONFIG.apiKey}`,
+        },
+        body: JSON.stringify({
+          model: OPENAI_CONFIG.model,
+          messages: apiMessages,
+          temperature: OPENAI_CONFIG.temperature,
+          max_tokens: OPENAI_CONFIG.maxTokens,
+        }),
+      });
+
+      if (!response.ok) {
+        const errorData = await response.json();
+        throw new Error(errorData.error?.message || 'Failed to get response from OpenAI');
+      }
+
+      const data = await response.json();
+      const assistantContent = data.choices[0]?.message?.content || '';
+
+      // Extract diagram if present
+      const diagramData = extractDiagramFromResponse(assistantContent);
+
+      // Add assistant message to chat
+      const assistantMsg: ChatMessage = {
+        id: `assistant-${Date.now()}`,
+        role: 'assistant',
+        content: assistantContent,
+        timestamp: new Date(),
+        diagramData: diagramData || undefined,
+      };
+
+      setMessages(prev => [...prev, assistantMsg]);
+
+    } catch (err) {
+      console.error('Error sending message:', err);
+      const errorMessage = err instanceof Error ? err.message : 'Unknown error occurred';
+      setError(errorMessage);
+
+      // Add error message to chat
+      const errorMsg: ChatMessage = {
+        id: `error-${Date.now()}`,
+        role: 'assistant',
+        content: `Sorry, I encountered an error: ${errorMessage}`,
+        timestamp: new Date(),
+      };
+
+      setMessages(prev => [...prev, errorMsg]);
+    } finally {
+      setIsLoading(false);
+    }
+  }, [messages]);
+
+  /**
+   * Clear all messages
+   */
+  const clearMessages = useCallback(() => {
+    setMessages([]);
+    setError(null);
+  }, []);
+
+  return {
+    messages,
+    isLoading,
+    error,
+    sendMessage,
+    clearMessages,
+  };
+}
diff --git a/src/lib/chat-prompts.ts b/src/lib/chat-prompts.ts
new file mode 100644
index 0000000..a66eca6
--- /dev/null
+++ b/src/lib/chat-prompts.ts
@@ -0,0 +1,46 @@
+/**
+ * Chat System Prompts for Diagram Generation
+ *
+ * Defines the AI assistant's role and response format
+ */
+
+export const DIAGRAM_GENERATION_SYSTEM_PROMPT = `You are a helpful diagram generation assistant. Your role is to understand user descriptions and create structured diagram representations.
+
+When a user describes a process, workflow, system, or any diagram, you should:
+
+1. Listen carefully to understand the key entities, steps, decisions, and relationships
+2. Generate a structured JSON representation of the diagram
+3. Use appropriate node types:
+   - 'start': For the beginning of a process
+   - 'process': For actions, steps, or operations
+   - 'decision': For yes/no branches or conditional logic
+   - 'data': For data elements or information storage
+   - 'end': For terminal points or final states
+4. Create clear, descriptive labels for nodes and edges
+5. DO NOT specify coordinates or positions - those are calculated automatically
+
+**IMPORTANT**: When you generate a diagram, you MUST wrap the JSON in special markers:
+
+[DIAGRAM_START]
+{
+  "nodes": [
+    {"id": "node1", "label": "Start", "type": "start"},
+    {"id": "node2", "label": "Process Step", "type": "process"}
+  ],
+  "edges": [
+    {"id": "edge1", "source": "node1", "target": "node2", "label": ""}
+  ]
+}
+[DIAGRAM_END]
+
+Be conversational and helpful. If the description is unclear, ask for clarification. Confirm what you understood before generating the diagram.`;
+
+/**
+ * Example user prompts for testing
+ */
+export const EXAMPLE_PROMPTS = [
+  'Create a simple login process diagram',
+  'Show me a flowchart for making a cup of coffee',
+  'Design a user authentication workflow with OAuth',
+  'Create a diagram for a basic e-commerce checkout process',
+];
diff --git a/src/lib/diagram-parser.ts b/src/lib/diagram-parser.ts
new file mode 100644
index 0000000..290610b
--- /dev/null
+++ b/src/lib/diagram-parser.ts
@@ -0,0 +1,99 @@
+/**
+ * Diagram Parser Utility
+ *
+ * Extracts and validates diagram JSON from AI responses
+ */
+
+import { GraphModel } from '@/types/graph';
+
+/**
+ * Extract diagram JSON from AI response text
+ * Looks for content between [DIAGRAM_START] and [DIAGRAM_END] markers
+ */
+export function extractDiagramFromResponse(response: string): GraphModel | null {
+  try {
+    const startMarker = '[DIAGRAM_START]';
+    const endMarker = '[DIAGRAM_END]';
+
+    const startIndex = response.indexOf(startMarker);
+    const endIndex = response.indexOf(endMarker);
+
+    if (startIndex === -1 || endIndex === -1) {
+      console.log('No diagram markers found in response');
+      return null;
+    }
+
+    const jsonStr = response.substring(
+      startIndex + startMarker.length,
+      endIndex
+    ).trim();
+
+    const diagram = JSON.parse(jsonStr) as GraphModel;
+
+    // Validate diagram structure
+    if (!validateDiagram(diagram)) {
+      console.error('Invalid diagram structure');
+      return null;
+    }
+
+    return diagram;
+  } catch (error) {
+    console.error('Failed to extract diagram from response:', error);
+    return null;
+  }
+}
+
+/**
+ * Validate diagram structure
+ */
+export function validateDiagram(diagram: any): diagram is GraphModel {
+  if (!diagram || typeof diagram !== 'object') {
+    return false;
+  }
+
+  if (!Array.isArray(diagram.nodes) || !Array.isArray(diagram.edges)) {
+    return false;
+  }
+
+  // Validate nodes
+  for (const node of diagram.nodes) {
+    if (!node.id || !node.label || !node.type) {
+      console.error('Invalid node structure:', node);
+      return false;
+    }
+
+    const validTypes = ['start', 'process', 'decision', 'end', 'data', 'default'];
+    if (!validTypes.includes(node.type)) {
+      console.error('Invalid node type:', node.type);
+      return false;
+    }
+  }
+
+  // Validate edges
+  for (const edge of diagram.edges) {
+    if (!edge.id || !edge.source || !edge.target) {
+      console.error('Invalid edge structure:', edge);
+      return false;
+    }
+
+    // Check that source and target nodes exist
+    const sourceExists = diagram.nodes.some((n: any) => n.id === edge.source);
+    const targetExists = diagram.nodes.some((n: any) => n.id === edge.target);
+
+    if (!sourceExists || !targetExists) {
+      console.error('Edge references non-existent node:', edge);
+      return false;
+    }
+  }
+
+  return true;
+}
+
+/**
+ * Remove diagram markers from response text (for display)
+ */
+export function stripDiagramMarkers(response: string): string {
+  return response
+    .replace(/\[DIAGRAM_START\][\s\S]*?\[DIAGRAM_END\]/g, '[Diagram generated]')
+    .trim();
+}
diff --git a/src/lib/layout-engine.ts b/src/lib/layout-engine.ts
new file mode 100644
index 0000000..2163736
--- /dev/null
+++ b/src/lib/layout-engine.ts
@@ -0,0 +1,84 @@
+import dagre from '@dagrejs/dagre';
+import { GraphModel, LayoutResult, PositionedNode } from '@/types/graph';
+
+// Default node dimensions
+const NODE_WIDTH = 180;
+const NODE_HEIGHT = 80;
+
+/**
+ * Layout configuration options
+ */
+export interface LayoutOptions {
+  rankdir?: 'TB' | 'BT' | 'LR' | 'RL'; // Layout direction
+  nodesep?: number; // Horizontal spacing between nodes
+  ranksep?: number; // Vertical spacing between ranks
+  nodeWidth?: number;
+  nodeHeight?: number;
+}
+
+/**
+ * Compute automatic layout for a graph using Dagre
+ * @param graphModel - The semantic graph model from AI
+ * @param options - Layout configuration options
+ * @returns Layout result with positioned nodes
+ */
+export function getAutoLayout(
+  graphModel: GraphModel,
+  options: LayoutOptions = {}
+): LayoutResult {
+  const {
+    rankdir = 'TB',
+    nodesep = 50,
+    ranksep = 100,
+    nodeWidth = NODE_WIDTH,
+    nodeHeight = NODE_HEIGHT
+  } = options;
+
+  // Create new Dagre graph
+  const graph = new dagre.graphlib.Graph();
+
+  // Configure layout
+  graph.setGraph({
+    rankdir,
+    nodesep,
+    ranksep
+  });
+
+  graph.setDefaultEdgeLabel(() => ({}));
+
+  // Add nodes to Dagre graph
+  graphModel.nodes.forEach(node => {
+    graph.setNode(node.id, {
+      label: node.label,
+      width: nodeWidth,
+      height: nodeHeight
+    });
+  });
+
+  // Add edges to Dagre graph
+  graphModel.edges.forEach(edge => {
+    graph.setEdge(edge.source, edge.target);
+  });
+
+  // Compute layout
+  dagre.layout(graph);
+
+  // Extract positioned nodes
+  const positionedNodes: PositionedNode[] = graphModel.nodes.map(node => {
+    const nodeWithPosition = graph.node(node.id);
+
+    // Dagre returns center position, we need top-left
+    return {
+      ...node,
+      x: nodeWithPosition.x - nodeWidth / 2,
+      y: nodeWithPosition.y - nodeHeight / 2,
+      width: nodeWidth,
+      height: nodeHeight
+    };
+  });
+
+  return {
+    nodes: positionedNodes,
+    edges: graphModel.edges
+  };
+}
diff --git a/src/lib/mock-data.ts b/src/lib/mock-data.ts
new file mode 100644
index 0000000..26303d2
--- /dev/null
+++ b/src/lib/mock-data.ts
@@ -0,0 +1,83 @@
+import { GraphModel } from '@/types/graph';
+
+/**
+ * Mock flowchart for testing
+ */
+export const mockFlowchart: GraphModel = {
+  nodes: [
+    { id: '1', label: 'Start', type: 'start' },
+    { id: '2', label: 'Process Data', type: 'process' },
+    { id: '3', label: 'Is Valid?', type: 'decision' },
+    { id: '4', label: 'Save', type: 'process' },
+    { id: '5', label: 'Error', type: 'end' },
+    { id: '6', label: 'Success', type: 'end' }
+  ],
+  edges: [
+    { id: 'e1', source: '1', target: '2' },
+    { id: 'e2', source: '2', target: '3' },
+    { id: 'e3', source: '3', target: '4', label: 'Yes' },
+    { id: 'e4', source: '3', target: '5', label: 'No' },
+    { id: 'e5', source: '4', target: '6' }
+  ]
+};
+
+/**
+ * Simple linear process diagram
+ */
+export const mockLinearProcess: GraphModel = {
+  nodes: [
+    { id: '1', label: 'Step 1', type: 'start' },
+    { id: '2', label: 'Step 2', type: 'process' },
+    { id: '3', label: 'Step 3', type: 'process' },
+    { id: '4', label: 'Step 4', type: 'end' }
+  ],
+  edges: [
+    { id: 'e1', source: '1', target: '2' },
+    { id: 'e2', source: '2', target: '3' },
+    { id: 'e3', source: '3', target: '4' }
+  ]
+};
+
+/**
+ * Complex branching diagram
+ */
+export const mockComplexDiagram: GraphModel = {
+  nodes: [
+    { id: '1', label: 'User Input', type: 'start' },
+    { id: '2', label: 'Validate', type: 'process' },
+    { id: '3', label: 'Valid?', type: 'decision' },
+    { id: '4', label: 'Parse Data', type: 'process' },
+    { id: '5', label: 'Transform', type: 'process' },
+    { id: '6', label: 'Check Type', type: 'decision' },
+    { id: '7', label: 'Type A Handler', type: 'process' },
+    { id: '8', label: 'Type B Handler', type: 'process' },
+    { id: '9', label: 'Type C Handler', type: 'process' },
+    { id: '10', label: 'Store Result', type: 'data' },
+    { id: '11', label: 'Success', type: 'end' },
+    { id: '12', label: 'Error', type: 'end' }
+  ],
+  edges: [
+    { id: 'e1', source: '1', target: '2' },
+    { id: 'e2', source: '2', target: '3' },
+    { id: 'e3', source: '3', target: '4', label: 'Yes' },
+    { id: 'e4', source: '3', target: '12', label: 'No' },
+    { id: 'e5', source: '4', target: '5' },
+    { id: 'e6', source: '5', target: '6' },
+    { id: 'e7', source: '6', target: '7', label: 'Type A' },
+    { id: 'e8', source: '6', target: '8', label: 'Type B' },
+    { id: 'e9', source: '6', target: '9', label: 'Type C' },
+    { id: 'e10', source: '7', target: '10' },
+    { id: 'e11', source: '8', target: '10' },
+    { id: 'e12', source: '9', target: '10' },
+    { id: 'e13', source: '10', target: '11' }
+  ]
+};
+
+/**
+ * All available mock diagrams
+ */
+export const mockDiagrams = {
+  flowchart: mockFlowchart,
+  linear: mockLinearProcess,
+  complex: mockComplexDiagram
+};
diff --git a/src/lib/openai-config.ts b/src/lib/openai-config.ts
new file mode 100644
index 0000000..28dc092
--- /dev/null
+++ b/src/lib/openai-config.ts
@@ -0,0 +1,24 @@
+/**
+ * OpenAI API Configuration
+ *
+ * Configuration for OpenAI Chat Completions API integration
+ */
+
+export const OPENAI_CONFIG = {
+  apiKey: process.env.NEXT_PUBLIC_OPENAI_API_KEY || '',
+  apiBase: 'https://api.openai.com/v1',
+  model: 'gpt-4-turbo-preview',
+  temperature: 0.7,
+  maxTokens: 2000,
+} as const;
+
+/**
+ * Validate OpenAI configuration
+ */
+export function validateOpenAIConfig(): boolean {
+  if (!OPENAI_CONFIG.apiKey) {
+    console.error('OpenAI API key not found in environment variables');
+    return false;
+  }
+  return true;
+}
diff --git a/src/lib/tldraw-helpers.ts b/src/lib/tldraw-helpers.ts
new file mode 100644
index 0000000..7984c5b
--- /dev/null
+++ b/src/lib/tldraw-helpers.ts
@@ -0,0 +1,143 @@
+import { Editor, createShapeId, TLGeoShape } from 'tldraw';
+import { LayoutResult, PositionedNode } from '@/types/graph';
+
+/**
+ * Add test shapes to the canvas for testing programmatic control
+ */
+export function addTestShapes(editor: Editor) {
+  const shapeId = createShapeId();
+
+  editor.createShape({
+    id: shapeId,
+    type: 'geo',
+    x: 100,
+    y: 100,
+    props: {
+      w: 200,
+      h: 100,
+      geo: 'rectangle',
+      text: 'Test Node',
+      fill: 'solid',
+      color: 'blue'
+    }
+  });
+
+  // Add a second shape with an arrow
+  const shapeId2 = createShapeId();
+  editor.createShape({
+    id: shapeId2,
+    type: 'geo',
+    x: 400,
+    y: 100,
+    props: {
+      w: 200,
+      h: 100,
+      geo: 'rectangle',
+      text: 'Test Node 2',
+      fill: 'solid',
+      color: 'green'
+    }
+  });
+
+  // Create an arrow between them using absolute coordinates
+  const arrowId = createShapeId();
+  editor.createShape({
+    id: arrowId,
+    type: 'arrow',
+    x: 0,
+    y: 0,
+    props: {
+      start: { x: 300, y: 150 }, // End of first shape
+      end: { x: 400, y: 150 }    // Start of second shape
+    }
+  });
+}
+
+/**
+ * Map node types to Tldraw geo shapes
+ */
+function getGeoTypeForNode(nodeType: string): TLGeoShape['props']['geo'] {
+  switch (nodeType) {
+    case 'decision':
+      return 'diamond';
+    case 'start':
+    case 'end':
+      return 'ellipse';
+    case 'data':
+      return 'trapezoid';
+    default:
+      return 'rectangle';
+  }
+}
+
+/**
+ * Generate Tldraw shapes from positioned graph nodes
+ */
+export function generateTldrawShapes(layout: LayoutResult, editor: Editor) {
+  const nodeShapeMap = new Map<string, string>();
+
+  // Create node shapes
+  layout.nodes.forEach(node => {
+    const shapeId = createShapeId();
+    nodeShapeMap.set(node.id, shapeId);
+
+    const geoType = getGeoTypeForNode(node.type);
+
+    editor.createShape({
+      id: shapeId,
+      type: 'geo',
+      x: node.x,
+      y: node.y,
+      props: {
+        w: node.width,
+        h: node.height,
+        geo: geoType,
+        text: node.label,
+        fill: 'solid',
+        color: node.type === 'start' ? 'green' : node.type === 'end' ? 'red' : 'blue'
+      }
+    });
+  });
+
+  // Create edge arrows with bindings
+  layout.edges.forEach(edge => {
+    const sourceShapeId = nodeShapeMap.get(edge.source);
+    const targetShapeId = nodeShapeMap.get(edge.target);
+
+    if (sourceShapeId && targetShapeId) {
+      // Get source and target nodes to calculate positions
+      const sourceNode = layout.nodes.find(n => n.id === edge.source);
+      const targetNode = layout.nodes.find(n => n.id === edge.target);
+
+      if (sourceNode && targetNode) {
+        const arrowId = createShapeId();
+
+        // Calculate start and end points (bottom center of source, top center of target)
+        const startX = sourceNode.x + sourceNode.width / 2;
+        const startY = sourceNode.y + sourceNode.height;
+        const endX = targetNode.x + targetNode.width / 2;
+        const endY = targetNode.y;
+
+        editor.createShape({
+          id: arrowId,
+          type: 'arrow',
+          x: 0,
+          y: 0,
+          props: {
+            start: { x: startX, y: startY },
+            end: { x: endX, y: endY },
+            text: edge.label || ''
+          }
+        });
+      }
+    }
+  });
+}
+
+/**
+ * Clear all shapes from the canvas
+ */
+export function clearCanvas(editor: Editor) {
+  editor.selectAll();
+  editor.deleteShapes(editor.getSelectedShapeIds());
+}
diff --git a/src/types/graph.ts b/src/types/graph.ts
new file mode 100644
index 0000000..a376668
--- /dev/null
+++ b/src/types/graph.ts
@@ -0,0 +1,48 @@
+// Node in the semantic graph (before layout)
+export interface GraphNode {
+  id: string;
+  label: string;
+  type: 'process' | 'decision' | 'start' | 'end' | 'data' | 'default';
+  metadata?: Record<string, unknown>;
+}
+
+// Edge connecting nodes
+export interface GraphEdge {
+  id: string;
+  source: string;
+  target: string;
+  label?: string;
+}
+
+// Complete graph structure from AI
+export interface GraphModel {
+  nodes: GraphNode[];
+  edges: GraphEdge[];
+}
+
+// Node after Dagre layout (with coordinates)
+export interface PositionedNode extends GraphNode {
+  x: number;
+  y: number;
+  width: number;
+  height: number;
+}
+
+// Layout result
+export interface LayoutResult {
+  nodes: PositionedNode[];
+  edges: GraphEdge[];
+}
+
+// Application state types
+export type ConnectionState = 'disconnected' | 'connecting' | 'connected';
+export type RecordingState = 'idle' | 'recording';
+export type ProcessingState = 'idle' | 'processing' | 'generating';
+
+// OpenAI Realtime API event types
+export interface FunctionCallEvent {
+  type: 'response.function_call_arguments.done';
+  call_id: string;
+  name: string;
+  arguments: string; // JSON string of GraphModel
+}
diff --git a/tailwind.config.ts b/tailwind.config.ts
new file mode 100644
index 0000000..01288df
--- /dev/null
+++ b/tailwind.config.ts
@@ -0,0 +1,19 @@
+import type { Config } from 'tailwindcss'
+
+const config: Config = {
+  content: [
+    './src/pages/**/*.{js,ts,jsx,tsx,mdx}',
+    './src/components/**/*.{js,ts,jsx,tsx,mdx}',
+    './src/app/**/*.{js,ts,jsx,tsx,mdx}',
+  ],
+  theme: {
+    extend: {
+      colors: {
+        background: 'var(--background)',
+        foreground: 'var(--foreground)',
+      },
+    },
+  },
+  plugins: [],
+}
+export default config
diff --git a/tsconfig.json b/tsconfig.json
new file mode 100644
index 0000000..c133409
--- /dev/null
+++ b/tsconfig.json
@@ -0,0 +1,27 @@
+{
+  "compilerOptions": {
+    "target": "ES2017",
+    "lib": ["dom", "dom.iterable", "esnext"],
+    "allowJs": true,
+    "skipLibCheck": true,
+    "strict": true,
+    "noEmit": true,
+    "esModuleInterop": true,
+    "module": "esnext",
+    "moduleResolution": "bundler",
+    "resolveJsonModule": true,
+    "isolatedModules": true,
+    "jsx": "preserve",
+    "incremental": true,
+    "plugins": [
+      {
+        "name": "next"
+      }
+    ],
+    "paths": {
+      "@/*": ["./src/*"]
+    }
+  },
+  "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
+  "exclude": ["node_modules"]
+}