| # Stack 2.9 Technical Architecture |
|
|
| This document provides an in-depth look at Stack 2.9's technical architecture, system components, and design decisions. |
|
|
| ## Table of Contents |
|
|
| - [System Overview](#system-overview) |
| - [System Components](#system-components) |
| - [Data Flow](#data-flow) |
| - [Pattern Memory System](#pattern-memory-system) |
| - [Training Pipeline](#training-pipeline) |
| - [Tool System](#tool-system) |
| - [Memory System](#memory-system) |
|
|
| --- |
|
|
| ## System Overview |
|
|
| ``` |
| ┌──────────────────────────────────────────────────────────────────────────────┐ |
| │ STACK 2.9 SYSTEM │ |
| ├──────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌────────────────────────────────────────────────────────────────────────┐ │ |
| │ │ CLIENT LAYER │ │ |
| │ │ CLI │ Web UI │ IDE Plugins │ Voice Interface │ External API Clients │ │ |
| │ └────────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌────────────────────────────────────────────────────────────────────────┐ │ |
| │ │ API GATEWAY │ │ |
| │ │ OpenAI-compatible REST │ WebSocket │ Auth │ Rate Limiting │ │ |
| │ └────────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌────────────────────────────────────────────────────────────────────────┐ │ |
| │ │ ORCHESTRATION LAYER │ │ |
| │ │ Agent │ Context Manager │ Tool Coordinator │ Router │ │ |
| │ └────────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ┌────────────────────────┼────────────────────────┐ │ |
| │ │ │ │ │ |
| │ ▼ ▼ ▼ │ |
| │ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────┐ │ |
| │ │ MODEL LAYER │ │ TOOL ENGINE │ │ PATTERN MEMORY │ │ |
| │ │ Qwen2.5-Coder │ │ 37 Tools │ │ Observe/Learn │ │ |
| │ │ 32B + LoRA │ │ Sandbox Exec │ │ Memory/Train │ │ |
| │ └──────────────────┘ └──────────────────┘ └──────────────────┘ │ |
| │ │ |
| └──────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| --- |
|
|
| ## System Components |
|
|
| ### 1. Client Layer |
|
|
| The client layer handles user interaction through multiple interfaces: |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────────────┐ |
| │ CLIENT LAYER │ |
| ├─────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ |
| │ │ CLI │ │ Web UI │ │ IDE │ │ |
| │ │ (Python) │ │ (Gradio) │ │ Plugins │ │ |
| │ └─────────────┘ └─────────────┘ └─────────────┘ │ |
| │ │ |
| │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ |
| │ │ Voice │ │ REST API │ │ WebSocket │ │ |
| │ │ Interface │ │ Client │ │ Client │ │ |
| │ └─────────────┘ └─────────────┘ └─────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| **Components:** |
|
|
| - **CLI (stack_cli/cli.py)**: Command-line interface for terminal interaction |
| - **Web UI (Gradio)**: Browser-based interface with voice support |
| - **IDE Plugins**: VS Code, PyCharm, JetBrains integration |
| - **Voice Interface**: Speech-to-text and text-to-speech processing |
| - **API Clients**: OpenAI-compatible client libraries |
| |
| ### 2. API Gateway |
| |
| The API gateway provides OpenAI-compatible endpoints with additional features: |
| |
| ``` |
| ┌─────────────────────────────────────────────────────────────────┐ |
| │ API GATEWAY │ |
| ├─────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌──────────────────────────────────────────────────────────┐ │ |
| │ │ Request Router │ │ |
| │ │ /v1/chat/completions │ /v1/models │ │ |
| │ └──────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ |
| │ │ Auth │ │ Rate │ │ Request │ │ |
| │ │ Middleware│ │ Limiter │ │ Validator │ │ |
| │ └─────────────┘ └─────────────┘ └─────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌──────────────────────────────────────────────────────────┐ │ |
| │ │ Response Handler │ │ |
| │ │ Format │ Stream │ Error │ Metrics │ │ |
| │ └──────────────────────────────────────────────────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────┘ |
| ``` |
| |
| **Features:** |
| |
| - OpenAI-compatible REST API |
| - WebSocket streaming support |
| - JWT/API key authentication |
| - Rate limiting per tier |
| - Request validation |
| - Response formatting |
| - Usage metrics |
| |
| ### 3. Orchestration Layer |
| |
| The orchestration layer coordinates the agent's activities: |
| |
| ``` |
| ┌─────────────────────────────────────────────────────────────────┐ |
| │ ORCHESTRATION LAYER │ |
| ├─────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌─────────────────────────────────────────────────────────┐ │ |
| │ │ AGENT │ │ |
| │ │ ┌───────────┐ ┌───────────┐ ┌───────────┐ │ │ |
| │ │ │ Intent │ │ Decision │ │ Action │ │ │ |
| │ │ │ Detector │ │ Maker │ │ Executor │ │ │ |
| │ │ └───────────┘ └───────────┘ └───────────┘ │ │ |
| │ └─────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │ |
| │ │ Context │ │ Tool │ │ Memory │ │ |
| │ │ Manager │ │ Coordinator │ │ Bridge │ │ |
| │ └───────────────┘ └───────────────┘ └───────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────┘ |
| ``` |
| |
| **Components:** |
| |
| - **Agent (agent.py)**: Main orchestration logic |
| - **Context Manager (context.py)**: Manages conversation context and truncation |
| - **Tool Coordinator**: Routes tool calls and manages execution |
| - **Memory Bridge**: Interfaces with the pattern memory memory system |
| |
| ### 4. Model Layer |
| |
| The model layer provides the AI inference capabilities: |
| |
| ``` |
| ┌─────────────────────────────────────────────────────────────────┐ |
| │ MODEL LAYER │ |
| ├─────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌─────────────────────────────────────────────────────────┐ │ |
| │ │ QWEN2.5-CODER-32B BASE MODEL │ │ |
| │ │ 32B parameters │ 131K context │ AWQ quant │ │ |
| │ └─────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────┐ │ |
| │ │ FINE-TUNING LAYER │ │ |
| │ │ ┌─────────────────┐ ┌─────────────────┐ │ │ |
| │ │ │ OpenClaw │ │ Voice │ │ │ |
| │ │ │ Tool Patterns │ │ Training │ │ │ |
| │ │ └─────────────────┘ └─────────────────┘ │ │ |
| │ └─────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────┐ │ |
| │ │ LoRA ADAPTERS │ │ |
| │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ |
| │ │ │ coding │ │ tools │ │ voice │ │ memory │ │ │ |
| │ │ │ self-evol │ │ 37 tool │ │ clone │ │ pattern │ │ │ |
| │ │ │ patterns │ │ patterns │ │ synth │ │ retrieval │ │ │ |
| │ │ └─────────────┘ └─────────────┘ └─────────────┘ └─────────────┘ │ │ |
| │ └─────────────────────────────────────────────────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────┘ |
| ``` |
| |
| **Configuration:** |
| |
| ```python |
| # Model configuration |
| MODEL_CONFIG = { |
| "name": "qwen/qwen2.5-coder-32b", |
| "context_window": 131072, |
| "quantization": "awq", # AWQ 4-bit quantization |
| "tensor_parallelism": 1, |
| "gpu_memory_utilization": 0.9, |
| "max_tokens": 4096, |
| "temperature": 0.7, |
| "top_p": 0.95, |
| } |
| ``` |
| |
| --- |
| |
| ## Data Flow |
| |
| ### Request Processing Flow |
| |
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ REQUEST PROCESSING FLOW │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ User Input │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ │ |
| │ │ Client │ ─── Text, Voice, or API Request │ |
| │ └─────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ │ |
| │ │ Gateway │ ─── Auth │ Rate Limit │ Validate │ |
| │ └─────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ │ |
| │ │ Router │ ─── Route to appropriate handler │ |
| │ └─────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ ORCHESTRATION LAYER │ │ |
| │ │ │ │ |
| │ │ 1. Intent Detection ─── Classify request type │ │ |
| │ │ │ │ │ |
| │ │ ▼ │ │ |
| │ │ 2. Context Assembly ─── Load relevant context + memories │ │ |
| │ │ │ │ │ |
| │ │ ▼ │ │ |
| │ │ 3. Tool Selection ─── Choose appropriate tools │ │ |
| │ │ │ │ │ |
| │ │ ▼ │ │ |
| │ │ 4. Execution Loop ─── Execute tools, stream results │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ RESPONSE HANDLING │ │ |
| │ │ │ │ |
| │ │ • Format response (OpenAI-compatible) │ │ |
| │ │ • Stream chunks (if requested) │ │ |
| │ │ • Record to pattern memory system │ │ |
| │ │ • Update metrics │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ Response ─── Stream or Complete JSON │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
| |
| ### Tool Execution Flow |
| |
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ TOOL EXECUTION FLOW │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ Model Output (Tool Call) │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ │ |
| │ │ Validate │ ─── Check tool name, parameters │ |
| │ └─────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ │ |
| │ │ Security │ ─── Sandbox │ Permission check │ Timeout │ |
| │ │ Check │ │ |
| │ └─────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ │ |
| │ │ Execute │ ─── Run in sandbox/container │ |
| │ └─────────────┘ │ |
| │ │ │ |
| │ ├──────────────────────────────┐ │ |
| │ │ │ │ |
| │ ▼ ▼ │ |
| │ ┌─────────────┐ ┌─────────────┐ │ |
| │ │ Success │ │ Error │ │ |
| │ │ ──────── │ │ ────── │ │ |
| │ │ Format │ │ Format │ │ |
| │ │ result │ │ error msg │ │ |
| │ └─────────────┘ └─────────────┘ │ |
| │ │ │ │ |
| │ └──────────────┬───────────────┘ │ |
| │ ▼ │ |
| │ Return to Model │ |
| │ for next token │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
| |
| --- |
| |
| ## Pattern Memory System |
| |
| Stack 2.9's pattern memory system enables continuous improvement through experience: |
| |
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ PATTERN MEMORY ARCHITECTURE │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ OBSERVER │ │ |
| │ │ │ │ |
| │ │ • Monitors all task executions │ │ |
| │ │ • Records decision points and outcomes │ │ |
| │ │ • Tracks tool usage patterns │ │ |
| │ │ • Logs success/failure details │ │ |
| │ │ │ │ |
| │ │ Output: Raw observation events │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ LEARNER │ │ |
| │ │ │ │ |
| │ │ • Analyzes observation patterns │ │ |
| │ │ • Extracts successful approaches (≥3 occurrences) │ │ |
| │ │ • Identifies failure patterns (≥2 occurrences) │ │ |
| │ │ • Generates improvement suggestions │ │ |
| │ │ • Updates lesson statistics │ │ |
| │ │ │ │ |
| │ │ Input: Observation events │ │ |
| │ │ Output: Learned patterns, improvements │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ MEMORY │ │ |
| │ │ │ │ |
| │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ |
| │ │ │ SQLite │ │ Vector │ │ Lesson │ │ │ |
| │ │ │ Store │ │ Embeddings │ │ Store │ │ │ |
| │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ |
| │ │ │ │ |
| │ │ • Persistent storage for all learnings │ │ |
| │ │ • Similarity-based retrieval │ │ |
| │ │ • Success rate tracking │ │ |
| │ │ • Session history │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ TRAINER │ │ |
| │ │ │ │ |
| │ │ • Fine-tunes LoRA adapters based on learnings │ │ |
| │ │ • Updates tool pattern weights │ │ |
| │ │ • Applies successful improvements │ │ |
| │ │ • Validates model improvements │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
| |
| ### Observer Component (self_evolution/observer.py) |
| |
| ```python |
| class TaskObserver: |
| """Observes and records task execution details.""" |
| |
| def observe_task_start(self, task_id: str, task_type: str, input_data: dict): |
| """Record task start with metadata.""" |
| event = { |
| "event_type": "task_start", |
| "task_id": task_id, |
| "task_type": task_type, |
| "timestamp": datetime.utcnow().isoformat(), |
| "input_data_hash": hash(input_data) |
| } |
| self._log_event(event) |
| |
| def observe_decision_point(self, task_id: str, options: list, choice: str, |
| rationale: str): |
| """Record decision-making moments.""" |
| event = { |
| "event_type": "decision", |
| "task_id": task_id, |
| "options": options, |
| "choice": choice, |
| "rationale": rationale, |
| "timestamp": datetime.utcnow().isoformat() |
| } |
| self._log_event(event) |
| |
| def observe_tool_usage(self, task_id: str, tool_name: str, |
| success: bool, duration_ms: int): |
| """Record tool usage patterns.""" |
| event = { |
| "event_type": "tool_usage", |
| "task_id": task_id, |
| "tool_name": tool_name, |
| "success": success, |
| "duration_ms": duration_ms, |
| "timestamp": datetime.utcnow().isoformat() |
| } |
| self._log_event(event) |
| |
| def observe_task_complete(self, task_id: str, success: bool, |
| output_summary: str): |
| """Record task completion.""" |
| event = { |
| "event_type": "task_complete", |
| "task_id": task_id, |
| "success": success, |
| "output_summary": output_summary, |
| "timestamp": datetime.utcnow().isoformat() |
| } |
| self._log_event(event) |
| ``` |
| |
| ### Learner Component (self_evolution/learner.py) |
| |
| ```python |
| class ExperienceLearner: |
| """Analyzes experiences and extracts actionable learnings.""" |
| |
| def analyze_task_outcome(self, task_id: str, task_type: str, |
| success: bool, steps: List[Dict], |
| decisions: List[Dict]) -> Dict: |
| """Analyze a completed task and extract learnings.""" |
| learnings = [] |
| |
| # Analyze decision patterns for success |
| if success: |
| good_decisions = [d for d in decisions if d.get('rationale')] |
| for decision in good_decisions: |
| learnings.append({ |
| 'type': 'success_pattern', |
| 'content': f"Using {decision.get('choice')} worked well" |
| }) |
| |
| # Document failure patterns |
| if not success: |
| for decision in decisions: |
| learnings.append({ |
| 'type': 'failure_pattern', |
| 'content': f"Avoid {decision.get('choice')} for {task_type}" |
| }) |
| |
| # Generate improvement suggestions |
| if not success: |
| suggestions = self._generate_improvements(task_type, steps, decisions) |
| learnings.extend(suggestions) |
| |
| return {'learnings': learnings} |
| ``` |
| |
| ### Memory Component (self_evolution/memory.py) |
| |
| ```python |
| class PersistentMemory: |
| """Vector-based persistent memory with SQLite storage.""" |
| |
| def store_memory(self, content: str, category: str = 'general', |
| metadata: Dict = None) -> int: |
| """Store a new memory with embedding.""" |
| embedding_id = self._generate_embedding_id(content) |
| embedding = self._compute_embedding(content) |
| |
| # Save embedding for similarity search |
| np.save(self.embeddings_dir / f'{embedding_id}.npy', embedding) |
| |
| # Store in SQLite |
| conn = sqlite3.connect(str(self.db_path)) |
| cursor = conn.cursor() |
| cursor.execute(''' |
| INSERT INTO memories |
| (content, embedding_id, category, created_at, updated_at, metadata) |
| VALUES (?, ?, ?, ?, ?, ?) |
| ''', (content, embedding_id, category, |
| datetime.utcnow().isoformat(), datetime.utcnow().isoformat(), |
| json.dumps(metadata) if metadata else None)) |
| |
| return cursor.lastrowid |
| |
| def find_similar(self, query: str, limit: int = 5, |
| min_similarity: float = 0.3) -> List[Dict]: |
| """Find similar memories using vector similarity.""" |
| query_embedding = self._compute_embedding(query) |
| |
| memories = self.get_all_memories() |
| results = [] |
| |
| for mem in memories: |
| emb_path = self.embeddings_dir / f"{mem['embedding_id']}.npy" |
| if emb_path.exists(): |
| stored_emb = np.load(emb_path) |
| similarity = self._cosine_similarity(query_embedding, stored_emb) |
| |
| if similarity >= min_similarity: |
| results.append({**mem, 'similarity': similarity}) |
| |
| return sorted(results, key=lambda x: x['similarity'], reverse=True)[:limit] |
| ``` |
| |
| --- |
|
|
| ## Training Pipeline |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ TRAINING PIPELINE │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ DATA COLLECTION │ │ |
| │ │ │ │ |
| │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ |
| │ │ │ Production │ │ Self- │ │ Expert │ │ │ |
| │ │ │ Logs │ │ Evolution │ │ Data │ │ │ |
| │ │ │ │ │ Memory │ │ │ │ │ |
| │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ DATA PROCESSING │ │ |
| │ │ │ │ |
| │ │ • Filter high-quality interactions │ │ |
| │ │ • Format to instruction-following format │ │ |
| │ │ • Apply OpenClaw tool pattern templates │ │ |
| │ │ • Quality scoring and filtering │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ TRAINING STAGES │ │ |
| │ │ │ │ |
| │ │ Stage 1: SFT (Supervised Fine-Tuning) │ │ |
| │ │ ├── Base model: Qwen2.5-Coder-32B │ │ |
| │ │ ├── Dataset: Tool-augmented conversations │ │ |
| │ │ └── Duration: 1-3 epochs │ │ |
| │ │ │ │ |
| │ │ Stage 2: RLHF (Reinforcement Learning) │ │ |
| │ │ ├── Reward model training │ │ |
| │ │ ├── PPO optimization │ │ |
| │ │ └── Duration: 1-2 epochs │ │ |
| │ │ │ │ |
| │ │ Stage 3: LoRA Adapter Training │ │ |
| │ │ ├── Pattern Memory patterns │ │ |
| │ │ ├── Voice integration │ │ |
| │ │ └── Duration: 1 epoch │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ EVALUATION │ │ |
| │ │ │ │ |
| │ │ • HumanEval, MBPP benchmarks │ │ |
| │ │ • Tool use accuracy │ │ |
| │ │ • Pattern Memory effectiveness │ │ |
| │ │ • Quality regression testing │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ DEPLOYMENT │ │ |
| │ │ │ │ |
| │ │ • Quantization (AWQ 4-bit) │ │ |
| │ │ • Model merging │ │ |
| │ │ • Containerization │ │ |
| │ │ • A/B testing infrastructure │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| ### Training Data Format |
|
|
| ```json |
| { |
| "messages": [ |
| {"role": "system", "content": "You are Stack 2.9, a coding assistant."}, |
| {"role": "user", "content": "Write a function to read a file"}, |
| {"role": "assistant", "content": null, "tool_calls": [ |
| { |
| "id": "call_123", |
| "type": "function", |
| "function": { |
| "name": "read_file", |
| "arguments": "{\"path\": \"example.txt\"}" |
| } |
| } |
| ]}, |
| {"role": "tool", "tool_call_id": "call_123", |
| "content": "File content here..."}, |
| {"role": "assistant", "content": "The file contains: ..."} |
| ] |
| } |
| ``` |
|
|
| --- |
|
|
| ## Tool System |
|
|
| Stack 2.9 includes 37 built-in tools organized into categories: |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ TOOL SYSTEM │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │ |
| │ │ File │ │ Search │ │ Git │ │ |
| │ │ Operations │ │ Operations │ │ Operations │ │ |
| │ ├───────────────┤ ├───────────────┤ ├───────────────┤ │ |
| │ │ • read_file │ │ • grep │ │ • git_status │ │ |
| │ │ • write_file │ │ • search_code │ │ • git_log │ │ |
| │ │ • edit_file │ │ • find_files │ │ • git_diff │ │ |
| │ │ • delete_file │ │ • search_web │ │ • git_commit │ │ |
| │ │ • list_dir │ │ │ │ • git_push │ │ |
| │ │ • create_dir │ │ │ │ • git_pull │ │ |
| │ │ • copy_file │ │ │ │ • git_branch │ │ |
| │ │ • move_file │ │ │ │ • git_merge │ │ |
| │ └───────────────┘ └───────────────┘ └───────────────┘ │ |
| │ │ |
| │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │ |
| │ │ Shell │ │ API/Web │ │ Voice │ │ |
| │ │ Commands │ │ Operations │ │ Processing │ │ |
| │ ├───────────────┤ ├───────────────┤ ├───────────────┤ │ |
| │ │ • run_command │ │ • http_request │ │ • speech_to │ │ |
| │ │ • background │ │ • download │ │ text │ │ |
| │ │ • job_control │ │ • parse_json │ │ • text_to │ │ |
| │ │ • env_vars │ │ • scrape_web │ │ speech │ │ |
| │ │ • process_ │ │ • rest_client │ │ • voice_clone │ │ |
| │ │ info │ │ │ │ │ │ |
| │ └───────────────┘ └───────────────┘ └───────────────┘ │ |
| │ │ |
| │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │ |
| │ │ Memory │ │ Context │ │ Debug │ │ |
| │ │ Operations │ │ Management │ │ Tools │ │ |
| │ ├───────────────┤ ├───────────────┤ ├───────────────┤ │ |
| │ │ • store_ │ │ • get_context │ │ • run_tests │ │ |
| │ │ memory │ │ • update_ │ │ • debug_code │ │ |
| │ │ • search_ │ │ context │ │ • stack_ │ │ |
| │ │ memory │ │ • truncate_ │ │ trace │ │ |
| │ │ • get_ │ │ context │ │ • lint_code │ │ |
| │ │ lessons │ │ │ │ │ │ |
| │ └───────────────┘ └───────────────┘ └───────────────┘ │ |
| │ │ |
| │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │ |
| │ │ Deploy │ │ Data │ │ General │ │ |
| │ │ Operations │ │ Processing │ │ Utilities │ │ |
| │ ├───────────────┤ ├───────────────┤ ├───────────────┤ │ |
| │ │ • deploy_ │ │ • parse_csv │ │ • calculate │ │ |
| │ │ docker │ │ • parse_json │ │ • format_ │ │ |
| │ │ • deploy_k8s │ │ • query_sql │ │ json │ │ |
| │ │ • run_ │ │ • data_ │ │ • now │ │ |
| │ │ migrate │ │ transform │ │ • echo │ │ |
| │ └───────────────┘ └───────────────┘ └───────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| ### Tool Definition Schema |
|
|
| ```json |
| { |
| "type": "function", |
| "function": { |
| "name": "read_file", |
| "description": "Read the contents of a file from the file system", |
| "parameters": { |
| "type": "object", |
| "properties": { |
| "path": { |
| "type": "string", |
| "description": "Absolute path to the file" |
| }, |
| "offset": { |
| "type": "integer", |
| "description": "Line number to start reading from", |
| "default": 0 |
| }, |
| "limit": { |
| "type": "integer", |
| "description": "Maximum number of lines to read", |
| "default": 1000 |
| } |
| }, |
| "required": ["path"] |
| } |
| } |
| } |
| ``` |
|
|
| ### Tool Execution Sandbox |
|
|
| ```python |
| class ToolSandbox: |
| """Isolated environment for tool execution.""" |
| |
| def execute(self, tool_name: str, arguments: dict, timeout: int = 30): |
| """Execute a tool in a sandboxed environment.""" |
| |
| # Security checks |
| self._check_permissions(tool_name, arguments) |
| self._validate_paths(arguments) |
| self._check_dangerous_commands(tool_name, arguments) |
| |
| # Execute in sandbox |
| with sandbox.Sandbox( |
| timeout=timeout, |
| memory_limit="512MB", |
| network=self._requires_network(tool_name), |
| filesystem=self._get_filesystem_scope(tool_name) |
| ) as sandbox: |
| result = sandbox.run(tool_name, arguments) |
| |
| return result |
| ``` |
|
|
| --- |
|
|
| ## Memory System |
|
|
| Stack 2.9 uses a sophisticated memory system combining SQLite and vector embeddings: |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ MEMORY SYSTEM │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ MEMORY LAYERS │ │ |
| │ │ │ │ |
| │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ |
| │ │ │ SHORT-TERM MEMORY │ │ │ |
| │ │ │ │ │ │ |
| │ │ │ • Current conversation context │ │ │ |
| │ │ │ • Active task state │ │ │ |
| │ │ │ • Recently accessed files │ │ │ |
| │ │ │ • Session variables │ │ │ |
| │ │ │ │ │ │ |
| │ │ │ Capacity: ~131K tokens (full context window) │ │ │ |
| │ │ └─────────────────────────────────────────────────────────────┘ │ │ |
| │ │ │ │ │ |
| │ │ ▼ │ │ |
| │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ |
| │ │ │ LONG-TERM MEMORY │ │ │ |
| │ │ │ │ │ │ |
| │ │ │ ┌───────────────────┐ ┌───────────────────┐ │ │ │ |
| │ │ │ │ SQLite │ │ Vector Store │ │ │ │ |
| │ │ │ │ Structured │ │ Embeddings │ │ │ │ |
| │ │ │ │ Data │ │ (128-dim) │ │ │ │ |
| │ │ │ └───────────────────┘ └───────────────────┘ │ │ │ |
| │ │ │ │ │ │ |
| │ │ │ • Learned patterns │ │ │ |
| │ │ │ • Success/failure history │ │ │ |
| │ │ │ • User preferences │ │ │ |
| │ │ │ • Project-specific knowledge │ │ │ |
| │ │ │ │ │ │ |
| │ │ │ Capacity: Unlimited (with retrieval) │ │ │ |
| │ │ └─────────────────────────────────────────────────────────────┘ │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ RETRIEVAL FLOW │ │ |
| │ │ │ │ |
| │ │ New Query ──▶ Embed Query ──▶ Similarity Search ──▶ Top-K │ │ |
| │ │ │ │ │ │ │ |
| │ │ ▼ ▼ ▼ │ │ |
| │ │ ┌─────────────┐ ┌─────────────┐ ┌──────┐ │ │ |
| │ │ │ Vector │ │ Threshold │ │Add to│ │ │ |
| │ │ │ Index │─────────▶│ Filter │ │Context│ │ │ |
| │ │ └─────────────┘ └─────────────┘ └──────┘ │ │ |
| │ │ │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| ### Database Schema |
|
|
| ```sql |
| -- Core memories table |
| CREATE TABLE memories ( |
| id INTEGER PRIMARY KEY AUTOINCREMENT, |
| content TEXT NOT NULL, |
| embedding_id TEXT UNIQUE, |
| category TEXT, |
| success_rate REAL DEFAULT 0.5, |
| use_count INTEGER DEFAULT 0, |
| last_used TEXT, |
| created_at TEXT NOT NULL, |
| updated_at TEXT NOT NULL, |
| metadata TEXT |
| ); |
| |
| -- Lessons learned table |
| CREATE TABLE lessons ( |
| id INTEGER PRIMARY KEY AUTOINCREMENT, |
| title TEXT NOT NULL, |
| description TEXT NOT NULL, |
| pattern TEXT, |
| success_count INTEGER DEFAULT 0, |
| failure_count INTEGER DEFAULT 0, |
| contexts TEXT, |
| created_at TEXT NOT NULL, |
| verified BOOLEAN DEFAULT 0 |
| ); |
| |
| -- Improvement suggestions table |
| CREATE TABLE improvements ( |
| id INTEGER PRIMARY KEY AUTOINCREMENT, |
| suggestion TEXT NOT NULL, |
| category TEXT, |
| priority INTEGER DEFAULT 5, |
| implemented BOOLEAN DEFAULT 0, |
| impact_score REAL DEFAULT 0.0, |
| created_at TEXT NOT NULL, |
| implemented_at TEXT |
| ); |
| |
| -- Session history |
| CREATE TABLE sessions ( |
| id INTEGER PRIMARY KEY AUTOINCREMENT, |
| session_id TEXT UNIQUE, |
| started_at TEXT NOT NULL, |
| ended_at TEXT, |
| tasks_completed INTEGER DEFAULT 0, |
| tasks_failed INTEGER DEFAULT 0, |
| learnings TEXT |
| ); |
| |
| -- Indexes for fast retrieval |
| CREATE INDEX idx_memories_category ON memories(category); |
| CREATE INDEX idx_memories_embedding ON memories(embedding_id); |
| CREATE INDEX idx_lessons_pattern ON lessons(pattern); |
| ``` |
|
|
| --- |
|
|
| ## Performance Optimization |
|
|
| ### Quantization |
|
|
| Stack 2.9 uses AWQ (Activation-Aware Weight Quantization) for efficient inference: |
|
|
| | Precision | Model Size | Memory | Performance | |
| |-----------|------------|--------|-------------| |
| | FP16 | 64 GB | ~64 GB | 100% | |
| | AWQ 4-bit | 64 GB | ~18 GB | ~95% | |
| | GPTQ 4-bit | 64 GB | ~18 GB | ~93% | |
|
|
| ### Batching |
|
|
| ```python |
| # Dynamic batching for throughput |
| class DynamicBatcher: |
| def __init__(self, max_batch_size=8, max_wait_ms=100): |
| self.queue = [] |
| self.max_batch_size = max_batch_size |
| self.max_wait_ms = max_wait_ms |
| |
| async def add_request(self, request): |
| self.queue.append(request) |
| |
| if len(self.queue) >= self.max_batch_size: |
| return await self._process_batch() |
| |
| # Wait for more requests or timeout |
| await asyncio.sleep(self.max_wait_ms / 1000) |
| return await self._process_batch() |
| ``` |
|
|
| ### Caching |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ CACHING LAYERS │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ Request ──▶ KV Cache ──▶ Model ──▶ Response Cache ──▶ Client │ |
| │ │ │ |
| │ │ │ |
| │ ┌─────────────┐ │ |
| │ │ GPU VRAM │ │ |
| │ │ (KV Cache) │ │ |
| │ └─────────────┘ │ |
| │ │ |
| │ Response Cache (Redis/Memory) │ |
| │ • Token patterns │ |
| │ • Tool results │ |
| │ • Context summaries │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| --- |
|
|
| ## Security |
|
|
| ### Authentication Flow |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ AUTHENTICATION FLOW │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ Client │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────┐ │ |
| │ │ API Key or │ │ |
| │ │ JWT Token │ │ |
| │ └────────┬───────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────┐ │ |
| │ │ Gateway │ │ |
| │ │ Middleware │ ─── Validate │ Rate Limit │ |
| │ └────────┬───────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────┐ │ |
| │ │ Auth Service │ ─── Verify │ Generate session │ |
| │ └────────┬───────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────┐ │ |
| │ │ Request │ │ |
| │ │ Processing │ │ |
| │ └─────────────────┘ │ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| ### Sandbox Security |
|
|
| - All tool execution runs in isolated containers |
| - Filesystem access scoped to allowed directories |
| - Network access restricted per-tool |
| - Resource limits (CPU, memory, time) |
| - Command allowlisting for shell tools |
|
|
| --- |
|
|
| ## Monitoring and Observability |
|
|
| ### Metrics |
|
|
| ```python |
| # Key metrics to track |
| METRICS = { |
| # Request metrics |
| "requests_total": Counter, |
| "requests_by_model": Counter, |
| "requests_by_status": Counter, |
| |
| # Token metrics |
| "tokens_prompt": Histogram, |
| "tokens_completion": Histogram, |
| "tokens_total": Histogram, |
| |
| # Performance metrics |
| "latency_seconds": Histogram, |
| "time_to_first_token": Histogram, |
| |
| # Tool metrics |
| "tool_calls_total": Counter, |
| "tool_execution_time": Histogram, |
| "tool_errors": Counter, |
| |
| # Pattern Memory metrics |
| "memories_created": Counter, |
| "patterns_extracted": Counter, |
| "improvements_applied": Counter, |
| } |
| ``` |
|
|
| ### Logging |
|
|
| ```python |
| # Structured logging format |
| LOG_FORMAT = { |
| "timestamp": "ISO8601", |
| "level": "INFO|WARN|ERROR", |
| "service": "stack-2.9", |
| "trace_id": "uuid", |
| "span_id": "uuid", |
| "message": "string", |
| "metadata": { |
| "model": "string", |
| "user_id": "string", |
| "request_id": "string", |
| "duration_ms": "number" |
| } |
| } |
| ``` |
|
|
| --- |
|
|
| ## Deployment Architecture |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────────────────────────┐ |
| │ DEPLOYMENT ARCHITECTURE │ |
| ├─────────────────────────────────────────────────────────────────────────────┤ |
| │ │ |
| │ ┌─────────────┐ │ |
| │ │ Clients │ │ |
| │ └──────┬──────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────┐ │ |
| │ │ CDN │ │ |
| │ │ (Static) │ │ |
| │ └──────┬──────┘ │ |
| │ │ │ |
| │ ▼ │ |
| │ ┌─────────────────────────────────────────────────────────────────────┐ │ |
| │ │ LOAD BALANCER │ │ |
| │ │ (Multiple AZs) │ │ |
| │ └─────────────────────────────────────────────────────────────────────┘ │ |
| │ │ │ |
| │ ┌──────────────────────────┼──────────────────────────┐ │ |
| │ │ │ │ │ |
| │ ▼ ▼ ▼ │ |
| │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐│ |
| │ │ API Server │ │ API Server │ │ API Server ││ |
| │ │ (Node 1) │ │ (Node 2) │ │ (Node 3) ││ |
| │ └───────────────┘ └───────────────┘ └───────────────┘│ |
| │ │ │ │ │ |
| │ └──────────────────────────┼──────────────────────────┘ │ |
| │ ▼ │ |
| │ ┌─────────────────────┐ │ |
| │ │ Redis Cluster │ │ |
| │ │ (Rate Limits, │ │ |
| │ │ Caching, Sessions)│ │ |
| │ └─────────────────────┘ │ |
| │ │ │ |
| │ ┌──────────────────────────┼──────────────────────────┐ │ |
| │ ▼ ▼ ▼ │ |
| │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐│ |
| │ │ GPU Node │ │ GPU Node │ │ GPU Node ││ |
| │ │ (A100 80G) │ │ (A100 80G) │ │ (A100 80G) ││ |
| │ │ vLLM Server │ │ vLLM Server │ │ vLLM Server ││ |
| │ └───────────────┘ └───────────────┘ └───────────────┘│ |
| │ │ |
| └─────────────────────────────────────────────────────────────────────────────┘ |
| ``` |
|
|
| --- |
|
|
| ## Future Architecture Considerations |
|
|
| ### Planned Enhancements |
|
|
| 1. **Distributed Training**: Multi-node training pipeline |
| 2. **Federated Learning**: Privacy-preserving model updates |
| 3. **Knowledge Distillation**: Smaller, faster models |
| 4. **Multi-Modal Support**: Image understanding and generation |
| 5. **Enhanced Voice**: Real-time voice-to-voice conversation |
|
|
