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Creative Studio - Comprehensive Implementation Plan

Platform: 灵感工坊 (Creative Studio) - AI 创作平台 Version: 2.0 Date: 2024-01-24 Status: Active Development

Executive Summary

This document provides a comprehensive implementation plan for the Creative Studio platform, based on the complete platform specification document. The platform follows a Skill-centric architecture where Agents provide fixed workflow frameworks and Skills provide configurable behavioral guidance.

Current Implementation Status

Component	Status	Completion
Backend Framework	✅ Implemented	90%
Skills CRUD	✅ Implemented	95%
Agents Viewing	✅ Implemented	80%
Projects CRUD	⚠️ Partial	60%
Memory System	❌ Missing	0%
Review System	❌ Missing	0%
Execution Monitoring	⚠️ Basic	40%
Frontend Pages	⚠️ Partial	50%
Skill Marketplace	❌ Missing	0%

Architecture Overview

Core Design Principles

"Agent 固定，Skill 可配" - Platform maintains Agent framework, users configure Skills
"Skill 指导行为" - Skill behavior guides are integrated into prompts to guide LLM behavior
"全局上下文 + 记忆系统" - Global context + memory system ensures multi-episode consistency
"全自动 + 人工审核" - Full automatic creation with human review

System Hierarchy

Series Project (剧集项目)
    ├── Uses Agent (固定工作流模板)
    │       └── Calls Skills (可配置能力单元)
    │
    ├── Global Context (全局上下文)
    │   ├── World Setting (世界观)
    │   ├── Character Profiles (人物小传)
    │   ├── Scene Settings (场景设定)
    │   └── Overall Outline (整体大纲)
    │
    ├── Memory System (记忆系统)
    │   ├── Event Timeline (事件时间线)
    │   ├── Pending Threads (待收线问题)
    │   ├── Foreshadowing (伏笔追踪)
    │   └── Character States (人物状态)
    │
    └── Episodes (子项目)
        ├── EP01, EP02, ...
        └── Each episode: Structure → Outline → Content → Review → Memory Update

Phase 1: Core Foundation (Current - Week 1-2)

1.1 Backend Infrastructure ✅ (90% Complete)

Status: Implemented Location: C:\Users\Wolfycz\huijing\creative_studio\backend\

Implemented Components:

FastAPI Application (app/main.py)
- CORS configuration
- Lifespan management
- Route registration
- Health checks
Skill Management (app/core/skills/skill_manager.py)
- Load and parse SKILL.md files
- Extract behavior guides
- Cache management
- Builtin vs User Skills separation
- CRUD operations for user Skills
Data Models (app/models/)
- skill.py: Skill, SkillTool, SkillConfig
- project.py: SeriesProject, Episode, GlobalContext, Memory
LLM Integration (app/core/llm/glm_client.py)
- GLM-4.7 integration
- chat_with_skill() method for Skill-guided generation
Series Creation Agent (app/core/agents/series_creation_agent.py)
- Fixed workflow implementation
- 5-stage execution: Structure → Outline → Dialogue → Review → Memory
- Context building
- Basic retry logic

Remaining Tasks:

Enhance error handling and logging
Add API rate limiting
Implement request/response validation
Add API versioning strategy
Create comprehensive test suite

API Endpoints Implemented:

Endpoint	Method	Status
`/api/v1/skills/`	GET	✅
`/api/v1/skills/{id}`	GET	✅
`/api/v1/skills/`	POST	✅
`/api/v1/skills/{id}`	PUT	✅
`/api/v1/skills/{id}`	DELETE	✅
`/api/v1/skills/{id}/test`	POST	✅
`/api/v1/projects/`	GET	✅
`/api/v1/projects/`	POST	✅
`/api/v1/projects/{id}`	GET	✅
`/api/v1/projects/{id}/execute`	POST	✅
`/api/v1/projects/{id}/execute-batch`	POST	✅

1.2 Frontend Infrastructure ⚠️ (50% Complete)

Status: Partially Implemented Location: C:\Users\Wolfycz\huijing\creative_studio\frontend\

Implemented Pages:

Skill Management (src/pages/SkillManagement.tsx) ✅
- Skills listing with filtering
- Builtin vs User Skills distinction
- Create, Edit, Delete operations
- Skill testing modal
- Detail drawer with behavior guide view
- Search and category filtering
- Grid/List view toggle
Agent Management (src/pages/AgentManagement.tsx) ✅
- Read-only Agent viewing
- Workflow visualization
- Skill bindings display
Project List (src/pages/ProjectList.tsx) ✅
- Project listing
- Status indicators
Project Create (src/pages/ProjectCreate.tsx) ⚠️
- Basic form
- Needs enhancement for global context
Execution Monitor (src/pages/ExecutionMonitor.tsx) ⚠️
- Basic monitoring
- Needs real-time updates

Missing Frontend Components:

Global Context Editor
Memory System Viewer
Review System UI
Episode Detail View
Skill Configuration Interface
Batch Execution Controls
Quality Report Viewer
Skill Marketplace

Phase 2: Memory System Implementation (Week 3-4)

2.1 Backend - Memory System

Priority: HIGH Complexity: Medium

Data Models to Implement:

# Event Timeline
class TimelineEvent(BaseModel):
    episode: int
    event: str
    timestamp: datetime
    characters_involved: List[str] = []
    importance: str = "medium"  # low, medium, high

# Pending Threads (Foreshadowing)
class PendingThread(BaseModel):
    id: str
    description: str
    introduced_at: int
    importance: str  # high, medium, low
    resolved: bool = False
    resolved_at: Optional[int] = None
    reminder_episode: Optional[int] = None
    status: str = "pending"  # pending,跟进中,已收线

# Character State History
class CharacterStateChange(BaseModel):
    episode: int
    state: str
    change: str
    emotional_impact: Optional[str] = None

# Enhanced Memory System
class EnhancedMemory(BaseModel):
    eventTimeline: List[TimelineEvent] = []
    pendingThreads: List[PendingThread] = []
    characterStates: Dict[str, List[CharacterStateChange]] = {}
    foreshadowing: List[ForeshadowingEvent] = []
    relationships: Dict[str, Dict[str, str]] = {}  # character relationships

API Endpoints to Create:

Endpoint	Method	Description
`/api/v1/projects/{id}/memory`	GET	Get project memory
`/api/v1/projects/{id}/memory/timeline`	GET	Get event timeline
`/api/v1/projects/{id}/memory/threads`	GET	Get pending threads
`/api/v1/projects/{id}/memory/threads`	POST	Add new thread
`/api/v1/projects/{id}/memory/threads/{thread_id}`	PUT	Update thread
`/api/v1/projects/{id}/memory/characters`	GET	Get character states
`/api/v1/projects/{id}/memory/resolve-thread`	POST	Mark thread as resolved

Memory Manager Implementation:

# app/core/memory/memory_manager.py

class MemoryManager:
    """Manage project memory system"""

    async def extract_events_from_episode(
        self,
        episode_content: str,
        episode_number: int
    ) -> List[TimelineEvent]:
        """Extract key events from completed episode"""
        # Use LLM to identify and extract events
        pass

    async def detect_foreshadowing(
        self,
        episode_content: str,
        episode_number: int
    ) -> List[ForeshadowingEvent]:
        """Detect new foreshadowing in episode"""
        pass

    async def update_character_states(
        self,
        episode_content: str,
        episode_number: int,
        characters: List[str]
    ) -> Dict[str, CharacterStateChange]:
        """Track character state changes"""
        pass

    async def check_consistency(
        self,
        episode_content: str,
        memory: Memory
    ) -> List[ConsistencyIssue]:
        """Check episode consistency with memory"""
        pass

    async def suggest_thread_resolution(
        self,
        thread: PendingThread,
        current_episode: int
    ) -> ResolutionSuggestion:
        """Suggest how to resolve pending threads"""
        pass

2.2 Frontend - Memory System UI

Components to Build:

Memory System Viewer Page (src/pages/MemorySystem.tsx)

interface MemorySystemProps {
  projectId: string;
}

// Features:
// - Tabbed interface: Timeline | Threads | Characters | Foreshadowing
// - Timeline: Chronological event list with episode markers
// - Threads: Cards showing pending threads with urgency indicators
// - Characters: State history for each character
// - Visual relationship graph

Timeline Component

// Features:
// - Vertical timeline visualization
// - Episode markers
// - Event cards with character avatars
// - Importance color-coding
// - Filter by character/episode/importance
// - Click to view details

Pending Threads Component

// Features:
// - Thread cards with:
//   - Description
//   - Introduced episode
//   - Importance level (High/Medium/Low)
//   - Status (Pending/In Progress/Resolved)
//   - Suggested resolution episode
// - Manual add/edit thread
// - Mark as resolved
// - Set reminder episode
// - Filter by status/importance

Character States Component

// Features:
// - Character list with current states
// - State history timeline per character
// - State change indicators
// - Relationship visualization
// - Emotional state tracking

Phase 3: Review System Implementation (Week 5-6)

3.1 Backend - Review System

Priority: HIGH Complexity: High

Review Configuration Model:

class ReviewConfig(BaseModel):
    """Review configuration - customizable by users"""

    # Enabled review Skills
    enabled_review_skills: List[str] = [
        "consistency_checker",
        "dialogue_quality_checker",
        "plot_logic_checker"
    ]

    # Overall strictness
    overall_strictness: str = "medium"  # loose, medium, strict

    # Dimension-specific settings
    dimension_settings: Dict[str, DimensionConfig] = {}

    # Custom rules
    custom_rules: List[CustomRule] = []

    # Presets
    preset_name: Optional[str] = None

class DimensionConfig(BaseModel):
    enabled: bool = True
    strictness: float = 0.5  # 0.0 to 1.0
    custom_rules: List[CustomRule] = []

class CustomRule(BaseModel):
    id: str
    name: str
    description: str
    trigger_condition: str
    severity: str  # low, medium, high
    enabled: bool = True

Review Result Model:

class ReviewResult(BaseModel):
    episode_id: str
    episode_number: int

    # Overall score
    overall_score: float
    passed: bool

    # Dimension scores
    dimension_scores: Dict[str, float] = {}

    # Issues found
    issues: List[ReviewIssue] = []

    # New foreshadowing detected
    new_foreshadowing: List[ForeshadowingEvent] = []

    # Resolved threads
    resolved_threads: List[str] = []

class ReviewIssue(BaseModel):
    id: str
    type: str
    dimension: str
    severity: str  # low, medium, high
    location: Location
    description: str
    original_text: Optional[str] = None
    suggestion: str
    auto_fix_available: bool = False

class Location(BaseModel):
    episode: int
    scene: int
    line: Optional[int] = None

Review Manager Implementation:

# app/core/review/review_manager.py

class ReviewManager:
    """Manage review process"""

    async def review_episode(
        self,
        episode: Episode,
        project: SeriesProject,
        config: ReviewConfig
    ) -> ReviewResult:
        """Execute full review process"""

        # Run each enabled review Skill
        dimension_results = []
        for skill_id in config.enabled_review_skills:
            result = await self._run_review_skill(
                skill_id, episode, project, config
            )
            dimension_results.append(result)

        # Aggregate results
        review_result = self._aggregate_results(dimension_results)

        # Check custom rules
        custom_issues = await self._check_custom_rules(
            episode, config.custom_rules
        )
        review_result.issues.extend(custom_issues)

        # Determine pass/fail
        threshold = config.dimension_settings.get("threshold", 85)
        review_result.passed = review_result.overall_score >= threshold

        return review_result

    async def _run_review_skill(
        self,
        skill_id: str,
        episode: Episode,
        project: SeriesProject,
        config: ReviewConfig
    ) -> DimensionResult:
        """Run a single review Skill"""
        skill = await skill_manager.load_skill(skill_id)

        # Build review prompt
        prompt = self._build_review_prompt(
            skill, episode, project, config
        )

        # Execute with Skill behavior guide
        response = await glm_client.chat_with_skill(
            skill_behavior=skill.behavior_guide,
            user_input=prompt,
            context={
                "episode_content": episode.content,
                "global_context": project.globalContext,
                "memory": project.memory
            },
            temperature=0.3
        )

        # Parse response
        return self._parse_review_response(response, skill_id)

    def _aggregate_results(
        self,
        dimension_results: List[DimensionResult]
    ) -> ReviewResult:
        """Aggregate dimension results into overall score"""
        # Weighted average based on dimension settings
        pass

API Endpoints:

Endpoint	Method	Description
`/api/v1/projects/{id}/review-config`	GET	Get review config
`/api/v1/projects/{id}/review-config`	PUT	Update review config
`/api/v1/projects/{id}/review-presets`	GET	List preset configs
`/api/v1/projects/{id}/episodes/{ep_num}/review`	POST	Run review
`/api/v1/review/dimensions`	GET	List available dimensions
`/api/v1/review/custom-rules`	POST	Add custom rule
`/api/v1/review/custom-rules/{id}`	DELETE	Delete custom rule

3.2 Frontend - Review System UI

Components to Build:

Review Configuration Page (src/pages/ReviewConfig.tsx)

// Features:
// - Dimension selection with toggles
// - Strictness sliders per dimension
// - Custom rules builder
// - Preset selection (Draft/Standard/Strict)
// - Save/load presets
// - Preview configuration impact

Dimension Configuration Component

// Features:
// - Enable/disable dimension
// - Strictness slider (0-100)
// - Weight adjustment
// - Custom rules for dimension
// - Examples of what's checked

Custom Rule Builder

// Features:
// - Rule name and description
// - Trigger condition builder (natural language)
// - Severity selector
// - Test rule with sample content
// - Rule templates

Review Results Viewer (src/pages/ReviewResults.tsx)

// Features:
// - Overall score display with gauge
// - Dimension score breakdown (bar chart)
// - Issues list grouped by severity
// - Issue detail cards:
//   - Location link
//   - Original text
//   - Suggestion
//   - Auto-fix button (if available)
//   - Ignore option
// - Accept/Reject decisions
// - Export report

Review Dashboard

// Features:
// - Batch review summary
// - Pass/fail statistics
// - Common issues
// - Trend analysis
// - Quality metrics over time

Phase 4: Advanced Execution Features (Week 7-8)

4.1 Backend - Enhanced Execution

Priority: MEDIUM Complexity: High

Features to Implement:

Batch Execution Mode

# app/core/execution/batch_executor.py

class BatchExecutor:
    """Execute episodes in batches with user review between"""

    async def execute_batch(
        self,
        project: SeriesProject,
        start_episode: int,
        end_episode: int,
        batch_config: BatchConfig
    ) -> BatchResult:
        """Execute a batch of episodes"""

        results = []
        for ep_num in range(start_episode, end_episode + 1):
            # Execute episode
            episode = await agent.execute_episode(
                project, ep_num
            )

            # Run review
            review = await review_manager.review_episode(
                episode, project, project.review_config
            )

            # Check if meets quality threshold
            if review.overall_score < batch_config.quality_threshold:
                # Auto-retry or mark for review
                if episode.retry_count < batch_config.max_retries:
                    episode = await self._retry_episode(
                        project, ep_num, review
                    )
                else:
                    episode.status = "needs-review"

            results.append(episode)

        # Wait for user approval before next batch
        return BatchResult(
            episodes=results,
            needs_review=[ep for ep in results if ep.status == "needs-review"],
            batch_summary=self._generate_summary(results)
        )

Real-time Progress Streaming

# Use WebSocket or Server-Sent Events for real-time updates

@app.websocket("/ws/projects/{project_id}/execute")
async def execute_episode_stream(
    websocket: WebSocket,
    project_id: str,
    episode_number: int
):
    """Stream execution progress in real-time"""

    await websocket.accept()

    # Send stage updates
    for stage in agent.execution_stages:
        await websocket.send_json({
            "type": "stage_start",
            "stage": stage.name,
            "message": f"Starting {stage.display_name}..."
        })

        result = await stage.execute()

        await websocket.send_json({
            "type": "stage_complete",
            "stage": stage.name,
            "result": result
        })

    await websocket.send_json({
        "type": "episode_complete",
        "episode": episode_result
    })

Auto-retry with Feedback

class RetryManager:
    """Manage automatic retry logic"""

    async def should_retry(
        self,
        episode: Episode,
        review: ReviewResult
    ) -> bool:
        """Determine if episode should be retried"""

        config = episode.project.autoRetryConfig

        # Check retry count
        if episode.retry_count >= config.maxRetries:
            return False

        # Check score threshold
        if review.overall_score >= config.qualityThreshold:
            return False

        # Check if issues are fixable
        fixable_issues = [
            issue for issue in review.issues
            if issue.auto_fix_available or issue.severity != "high"
        ]

        return len(fixable_issues) > 0

    async def retry_episode(
        self,
        episode: Episode,
        review: ReviewResult
    ) -> Episode:
        """Retry episode generation with review feedback"""

        # Build retry context
        retry_context = {
            "attempt": episode.retry_count + 1,
            "previous_result": episode.content,
            "review_feedback": self._build_feedback(review.issues),
            "suggestions": [issue.suggestion for issue in review.issues]
        }

        # Re-execute with feedback
        new_episode = await agent.execute_episode(
            episode.project,
            episode.number,
            retry_context=retry_context
        )

        new_episode.retry_count = episode.retry_count + 1
        return new_episode

API Endpoints:

Endpoint	Method	Description
`/api/v1/projects/{id}/execute-batch`	POST	Execute batch
`/api/v1/projects/{id}/execute-auto`	POST	Full auto execution
`/api/v1/projects/{id}/execution-status`	GET	Get execution status
`/api/v1/projects/{id}/stop-execution`	POST	Stop execution
`/ws/projects/{id}/execute`	WebSocket	Real-time execution stream

4.2 Frontend - Enhanced Execution UI

Components to Build:

Batch Execution Config (src/pages/BatchExecution.tsx)

// Features:
// - Batch size selector
// - Episode range picker
// - Per-episode configuration:
//   - Duration target
//   - Style preset
//   - Focus areas
// - Quality threshold setting
// - Auto-retry configuration
// - Preview batch plan

Real-time Execution Monitor (Enhanced)

// Features:
// - Live progress bar
// - Current stage display
// - Real-time content preview (streaming)
// - Stage-by-stage logs
// - Pause/Resume/Stop controls
// - Time estimation
// - Quality metrics live update

Batch Review Dashboard

// Features:
// - Batch completion summary
// - Episode cards with status
// - Quality score comparison
// - Issues overview
// - Batch approval decision:
//   - Accept all
//   - Review issues
//   - Retry failed
//   - Regenerate batch
// - Next batch configuration

Quality Report Viewer (src/pages/QualityReport.tsx)

// Features:
// - Overall quality metrics
// - Dimension score charts
// - Trend analysis across episodes
// - Issue statistics
// - Comparison to thresholds
// - Improvement suggestions
// - Export to PDF/Excel

Phase 5: Skill Marketplace (Week 9-10)

5.1 Backend - Marketplace

Priority: MEDIUM Complexity: Medium

Data Models:

class MarketplaceSkill(BaseModel):
    """Skill in marketplace"""

    # Base skill data
    skill: Skill

    # Marketplace-specific
    author_id: str
    author_name: str
    published_at: datetime
    downloads: int = 0
    rating: float = 0.0
    rating_count: int = 0

    # Categorization
    category: str
    tags: List[str]

    # Usage stats
    usage_count: int = 0
    success_rate: float = 0.0

    # Versioning
    version: str
    changelog: List[str] = []
    parent_skill_id: Optional[str] = None  # If forked

class SkillReview(BaseModel):
    skill_id: str
    user_id: str
    rating: int  # 1-5
    comment: str
    created_at: datetime
    usage_context: Optional[str] = None

Marketplace Manager:

# app/core/marketplace/marketplace_manager.py

class MarketplaceManager:
    """Manage Skill marketplace"""

    async def publish_skill(
        self,
        skill_id: str,
        user_id: str,
        marketplace_data: MarketplaceMetadata
    ) -> MarketplaceSkill:
        """Publish user skill to marketplace"""

        # Validate skill
        skill = await skill_manager.load_skill(skill_id)
        if not skill or skill.type != "user":
            raise ValueError("Only user skills can be published")

        # Create marketplace listing
        marketplace_skill = MarketplaceSkill(
            skill=skill,
            author_id=user_id,
            **marketplace_data.dict()
        )

        # Save to marketplace storage
        await self.marketplace_repo.create(marketplace_skill)

        return marketplace_skill

    async def fork_skill(
        self,
        original_skill_id: str,
        user_id: str,
        modifications: SkillUpdate
    ) -> Skill:
        """Create a fork of existing skill"""

        original = await self.get_marketplace_skill(original_skill_id)

        # Create new user skill
        new_skill_id = f"{original_skill_id}-fork-{uuid.uuid4().hex[:8]}"
        new_skill = await skill_manager.create_user_skill(
            SkillCreate(
                id=new_skill_id,
                name=f"{original.skill.name} (Fork)",
                content=original.skill.behavior_guide,
                category=original.category,
                tags=original.tags
            )
        )

        # Track fork relationship
        new_skill.parent_skill_id = original_skill_id

        return new_skill

    async def rate_skill(
        self,
        skill_id: str,
        user_id: str,
        rating: int,
        comment: str
    ) -> SkillReview:
        """Rate and review a skill"""
        pass

    async def get_recommendations(
        self,
        project_type: str,
        user_history: List[str]
    ) -> List[MarketplaceSkill]:
        """Get recommended skills based on context"""
        pass

API Endpoints:

Endpoint	Method	Description
`/api/v1/marketplace/skills`	GET	Browse marketplace
`/api/v1/marketplace/skills/{id}`	GET	Get skill details
`/api/v1/marketplace/skills/{id}/install`	POST	Install skill
`/api/v1/marketplace/skills/publish`	POST	Publish skill
`/api/v1/marketplace/skills/{id}/fork`	POST	Fork skill
`/api/v1/marketplace/skills/{id}/rate`	POST	Rate skill
`/api/v1/marketplace/skills/{id}/reviews`	GET	Get reviews
`/api/v1/marketplace/recommendations`	GET	Get recommendations
`/api/v1/marketplace/categories`	GET	Get categories

5.2 Frontend - Marketplace UI

Components to Build:

Marketplace Home (src/pages/Marketplace.tsx)

// Features:
// - Search bar with filters
// - Category browsing
// - Featured skills carousel
// - Popular skills grid
// - New arrivals
// - User's custom skills section
// - Skill cards with:
//   - Name, description
//   - Rating, downloads
//   - Author, category
//   - Install/Fork buttons

Skill Detail Page (src/pages/MarketplaceSkillDetail.tsx)

// Features:
// - Full skill description
// - Behavior guide preview
// - Configuration parameters
// - Usage examples
// - Reviews section
// - Rating distribution
// - Related skills
// - Version history
// - Install/Fork actions

Skill Publisher (src/pages/PublishSkill.tsx)

// Features:
// - Skill selection
// - Marketplace metadata:
//   - Display name
//   - Description
//   - Category, tags
//   - Screenshots
//   - Examples
// - Version notes
// - Pricing (if applicable)
// - Preview listing
// - Publish action

My Skills Dashboard

// Features:
// - Published skills list
// - Stats: downloads, ratings, usage
// - Fork management
// - Review responses
// - Version management
// - Skill analytics

Phase 6: Advanced Features (Week 11-12)

6.1 Global Context Editor

Backend:

Enhanced CRUD for GlobalContext
Version history
Conflict detection
Template system

Frontend:

Rich text editors for each section
Visual character relationship editor
Scene builder with previews
Import/export templates
Version comparison

6.2 Skill Configuration Interface

Backend:

Parameter schema validation
Configuration templates
Preset management

Frontend:

Visual parameter editors:
- Sliders for numeric values
- Selects for options
- Toggles for booleans
- Rich text for guides
Real-time preview
Configuration save/load
Preset application

6.3 Export System

Backend:

Multi-format export:
- Markdown
- PDF
- Word (DOCX)
- Final Draft
- Custom templates

Frontend:

Export configuration
Template selection
Format options
Preview before export
Batch export

6.4 Analytics Dashboard

Backend:

Usage metrics collection
Performance tracking
Quality analytics
Storage optimization

Frontend:

Usage statistics
Creation speed charts
Quality trends
Storage usage
API rate limits

Data Models Summary

Core Models Status

Model	Status	Fields	Completeness
Skill	✅	15 fields	95%
SkillTool	✅	4 fields	100%
SkillConfig	✅	3 fields	90%
SeriesProject	⚠️	12 fields	70%
GlobalContext	⚠️	5 fields	60%
CharacterProfile	⚠️	7 fields	70%
SceneSetting	⚠️	3 fields	80%
Memory	❌	4 fields	0%
Episode	⚠️	12 fields	70%
EpisodeIssue	✅	4 fields	100%
ReviewConfig	❌	TBD	0%
ReviewResult	❌	TBD	0%
MarketplaceSkill	❌	TBD	0%

API Endpoints Summary

Implemented (13 endpoints)

Skills:
✅ GET    /api/v1/skills/
✅ GET    /api/v1/skills/{id}
✅ POST   /api/v1/skills/
✅ PUT    /api/v1/skills/{id}
✅ DELETE /api/v1/skills/{id}
✅ POST   /api/v1/skills/{id}/test
✅ GET    /api/v1/skills/categories/list

Projects:
✅ GET    /api/v1/projects/
✅ POST   /api/v1/projects/
✅ GET    /api/v1/projects/{id}
✅ PUT    /api/v1/projects/{id}
✅ DELETE /api/v1/projects/{id}
✅ GET    /api/v1/projects/{id}/episodes
✅ GET    /api/v1/projects/{id}/episodes/{ep_num}
✅ POST   /api/v1/projects/{id}/execute
✅ POST   /api/v1/projects/{id}/execute-batch
✅ GET    /api/v1/projects/{id}/memory

To Implement (40+ endpoints)

Memory System:
❌ GET    /api/v1/projects/{id}/memory/timeline
❌ POST   /api/v1/projects/{id}/memory/threads
❌ PUT    /api/v1/projects/{id}/memory/threads/{thread_id}
❌ POST   /api/v1/projects/{id}/memory/resolve-thread
❌ GET    /api/v1/projects/{id}/memory/characters

Review System:
❌ GET    /api/v1/projects/{id}/review-config
❌ PUT    /api/v1/projects/{id}/review-config
❌ GET    /api/v1/projects/{id}/review-presets
❌ POST   /api/v1/projects/{id}/episodes/{ep_num}/review
❌ GET    /api/v1/review/dimensions
❌ POST   /api/v1/review/custom-rules
❌ DELETE /api/v1/review/custom-rules/{id}

Execution:
❌ POST   /api/v1/projects/{id}/execute-auto
❌ GET    /api/v1/projects/{id}/execution-status
❌ POST   /api/v1/projects/{id}/stop-execution
❌ WS     /ws/projects/{id}/execute

Marketplace:
❌ GET    /api/v1/marketplace/skills
❌ GET    /api/v1/marketplace/skills/{id}
❌ POST   /api/v1/marketplace/skills/{id}/install
❌ POST   /api/v1/marketplace/skills/publish
❌ POST   /api/v1/marketplace/skills/{id}/fork
❌ POST   /api/v1/marketplace/skills/{id}/rate
❌ GET    /api/v1/marketplace/skills/{id}/reviews
❌ GET    /api/v1/marketplace/recommendations
❌ GET    /api/v1/marketplace/categories

Export:
❌ POST   /api/v1/projects/{id}/export
❌ GET    /api/v1/projects/{id}/export/{export_id}

Analytics:
❌ GET    /api/v1/analytics/usage
❌ GET    /api/v1/analytics/performance
❌ GET    /api/v1/analytics/quality

Frontend Components Summary

Implemented (4 pages)

✅ SkillManagement - Complete
✅ AgentManagement - Read-only
✅ ProjectList - Basic
⚠️ ProjectCreate - Basic
⚠️ ExecutionMonitor - Basic
✅ HomePage - Basic

To Build (15+ components)

Core Pages:

❌ GlobalContextEditor
❌ MemorySystemViewer
❌ ReviewConfig
❌ ReviewResults
❌ EpisodeDetail
❌ BatchExecution
❌ QualityReport
❌ Marketplace
❌ MarketplaceSkillDetail
❌ PublishSkill
❌ MySkills
❌ ExportPage
❌ AnalyticsDashboard
❌ Settings

Shared Components:

❌ TimelineViewer
❌ ThreadTracker
❌ CharacterStateViewer
❌ RelationshipGraph
❌ DimensionConfig
❌ CustomRuleBuilder
❌ RealTimeMonitor
❌ QualityGauge
❌ SkillCard
❌ EpisodeCard

Implementation Priority Matrix

High Priority (Must Have)

Feature	Complexity	Impact	Timeline
Memory System	Medium	High	Week 3-4
Review System	High	High	Week 5-6
Enhanced Execution	Medium	High	Week 7-8
Global Context Editor	Medium	High	Week 6
Episode Detail View	Low	High	Week 5

Medium Priority (Should Have)

Feature	Complexity	Impact	Timeline
Skill Marketplace	Medium	Medium	Week 9-10
Batch Execution UI	Medium	Medium	Week 8
Quality Reports	Low	Medium	Week 8
Export System	Medium	Medium	Week 11
Analytics	Low	Medium	Week 12

Low Priority (Nice to Have)

Feature	Complexity	Impact	Timeline
Skill Recommendations	High	Low	Week 10
Custom Themes	Low	Low	Week 12
Team Collaboration	High	Low	Post-MVP
API Platform	High	Low	Post-MVP

Technical Debt & Refactoring

Current Issues

Memory System: Not implemented - placeholder only
Review System: Basic consistency check only
Data Persistence: In-memory only, needs database
Error Handling: Basic, needs comprehensive coverage
Testing: No test coverage
Documentation: Incomplete
Frontend State Management: Basic, needs optimization

Refactoring Priorities

Week 3-4: Add database persistence (PostgreSQL/MongoDB)
Week 5-6: Implement comprehensive error handling
Week 7-8: Add unit and integration tests
Week 9-10: Performance optimization
Week 11-12: Security audit and hardening

Development Guidelines

Backend Development

Follow FastAPI best practices
- Use async/await throughout
- Implement proper dependency injection
- Use Pydantic for validation
- Add comprehensive error handling

Code Organization

backend/
├── app/
│   ├── api/v1/          # API routes
│   ├── core/            # Core business logic
│   │   ├── agents/      # Agent implementations
│   │   ├── skills/      # Skill management
│   │   ├── memory/      # Memory system
│   │   ├── review/      # Review system
│   │   └── execution/   # Execution engine
│   ├── models/          # Pydantic models
│   ├── db/              # Database repositories
│   └── utils/           # Utilities
└── tests/               # Test suite

API Design Principles
- RESTful conventions
- Consistent response formats
- Proper HTTP status codes
- Comprehensive OpenAPI docs

Frontend Development

Follow React best practices
- Functional components with hooks
- TypeScript for type safety
- Ant Design for UI components
- Proper state management

Code Organization

frontend/
├── src/
│   ├── pages/           # Page components
│   ├── components/      # Reusable components
│   ├── services/        # API services
│   ├── stores/          # State management
│   ├── types/           # TypeScript types
│   └── utils/           # Utilities
└── tests/               # Test suite

UI/UX Principles
- Responsive design
- Loading states
- Error handling
- User feedback
- Accessibility

Testing Strategy

Backend Testing

Unit Tests (Target: 80% coverage)
- Model validation
- Business logic
- Utility functions
Integration Tests
- API endpoints
- Database operations
- External service calls
End-to-End Tests
- Complete workflows
- Multi-step operations
- Error scenarios

Frontend Testing

Component Tests
- Individual components
- User interactions
- State changes
Integration Tests
- Page flows
- API integration
- State management
E2E Tests
- User journeys
- Critical paths
- Cross-browser testing

Deployment Strategy

Development Environment

Backend: FastAPI with uvicorn
Frontend: Vite dev server
Database: SQLite (local), PostgreSQL (staging)
Hot reload enabled

Staging Environment

Docker containerization
PostgreSQL database
Redis for caching
Load testing

Production Environment

Kubernetes deployment
Horizontal scaling
Database replication
CDN for static assets
Monitoring and logging

Success Metrics

Technical Metrics

API Response Time: < 500ms (p95)
Frontend Load Time: < 2s
Test Coverage: > 80%
Uptime: > 99.9%
Error Rate: < 0.1%

User Metrics

Project Creation Success: > 95%
Episode Generation Quality: > 85%
User Satisfaction: > 4.5/5
Daily Active Users: Track growth
Feature Adoption: Track usage

Risk Assessment

High Risk Items

LLM API Stability
- Mitigation: Implement retry logic, fallback models
- Priority: High
Data Consistency
- Mitigation: Comprehensive review system
- Priority: High
Performance at Scale
- Mitigation: Caching, async processing
- Priority: Medium
User Experience Complexity
- Mitigation: Intuitive UI, onboarding
- Priority: Medium

Medium Risk Items

Third-party Dependencies
- Mitigation: Version pinning, regular updates
- Priority: Medium
Security Vulnerabilities
- Mitigation: Regular audits, penetration testing
- Priority: High

Next Steps (Immediate Actions)

Week 1-2: Foundation

Set up PostgreSQL database
Implement data persistence layer
Add comprehensive error handling
Set up testing framework
Create development documentation

Week 3-4: Memory System

Implement MemoryManager
Create memory API endpoints
Build MemorySystemViewer UI
Add memory extraction from episodes
Test memory consistency

Week 5-6: Review System

Implement ReviewManager
Create review API endpoints
Build ReviewConfig UI
Build ReviewResults UI
Add custom rule builder
Test review accuracy

Conclusion

This implementation plan provides a comprehensive roadmap for building the Creative Studio platform. The key focus areas are:

Memory System: Ensure multi-episode consistency
Review System: Maintain quality standards
Enhanced Execution: Provide flexible creation modes
Skill Marketplace: Enable skill sharing
User Experience: Intuitive, powerful interface

The current implementation has a solid foundation with Skills CRUD, basic Agent framework, and project management. The next phases focus on adding the missing critical features while maintaining code quality and user experience.

Estimated Total Timeline: 12 weeks for full MVP Team Size: 2-3 developers recommended Budget: Consider API costs, infrastructure, and development resources

Document Version: 1.0 Last Updated: 2024-01-24 Next Review: 2024-02-01

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Creative Studio - Comprehensive Implementation Plan

Executive Summary

Current Implementation Status

Architecture Overview

Core Design Principles

System Hierarchy

Phase 1: Core Foundation (Current - Week 1-2)

1.1 Backend Infrastructure ✅ (90% Complete)

Implemented Components:

Remaining Tasks:

1.2 Frontend Infrastructure ⚠️ (50% Complete)

Implemented Pages:

Missing Frontend Components:

Phase 2: Memory System Implementation (Week 3-4)

2.1 Backend - Memory System

Data Models to Implement:

API Endpoints to Create:

Memory Manager Implementation:

2.2 Frontend - Memory System UI

Phase 3: Review System Implementation (Week 5-6)

3.1 Backend - Review System

Review Configuration Model:

Review Result Model:

Review Manager Implementation:

API Endpoints:

3.2 Frontend - Review System UI

Phase 4: Advanced Execution Features (Week 7-8)

4.1 Backend - Enhanced Execution

Features to Implement:

API Endpoints:

4.2 Frontend - Enhanced Execution UI

Phase 5: Skill Marketplace (Week 9-10)

5.1 Backend - Marketplace

Data Models:

Marketplace Manager:

API Endpoints:

5.2 Frontend - Marketplace UI

Phase 6: Advanced Features (Week 11-12)

6.1 Global Context Editor

6.2 Skill Configuration Interface

6.3 Export System

6.4 Analytics Dashboard

Data Models Summary

Core Models Status

API Endpoints Summary

Implemented (13 endpoints)

To Implement (40+ endpoints)

Frontend Components Summary

Implemented (4 pages)

To Build (15+ components)

Implementation Priority Matrix

High Priority (Must Have)

Medium Priority (Should Have)

Low Priority (Nice to Have)

Technical Debt & Refactoring

Current Issues

Refactoring Priorities

Development Guidelines

Backend Development

Frontend Development

Testing Strategy

Backend Testing

Frontend Testing

Deployment Strategy

Development Environment

Staging Environment

Production Environment

Success Metrics

Technical Metrics

User Metrics

Risk Assessment

High Risk Items

Medium Risk Items

Next Steps (Immediate Actions)

Week 1-2: Foundation

Week 3-4: Memory System

Week 5-6: Review System

Conclusion

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