Torqon System Architecture
Technical documentation for Torqon's context orchestration infrastructure.
Introduction
Torqon is a context orchestration infrastructure layer for long-conversation LLM systems.
Cognitive Continuity
Maintains conversational relevance across extended sessions while minimizing context degradation.
Token Efficiency
Optimizes context composition to reduce unnecessary token usage without sacrificing continuity quality.
Context Intelligence
Coordinates retrieval, assembly, prioritization, and evaluation before requests reach language models.
"Better cognitive continuity per token."
Core Architecture
API Layer
Tech: Node.js / Express
Role: Ingestion endpoint for client requests and streaming response delivery.
Intent Engine
Tech: Regex / Lightweight Inference
Role: Classifies user intent to bypass heavy retrieval operations when possible.
Memory Engine
Tech: PostgreSQL + pgvector
Role: Semantic vector retrieval, relevance scoring, and deduplication.
Context Engine
Tech: TypeScript Core
Role: Assembles token-optimized context windows dynamically before LLM execution.
AI Gateway
Tech: Provider Abstraction
Role: Manages standard model execution, tool calls, and fallback strategies.
Evaluation System
Tech: LLM-as-Judge
Role: Automatically scores continuity and token efficiency offline.
Event Infrastructure
Tech: Redis Streams
Role: Coordinates asynchronous background tasks without blocking requests.
Observability Layer
Tech: Custom Tracing
Role: Collects trace telemetry and pipeline latency metrics per session.
Request Lifecycle
Stage 1 — Request Intake
- request ID generation
- trace initialization
- metadata registration
Stage 2 — Intent Classification
- regex heuristics
- lightweight fallback classification
- contextual dependency detection
Stage 3 — Memory Retrieval
- semantic similarity search
- retrieval thresholds
- deduplication filters
- relevance scoring
Stage 4 — Context Assembly
- token budgeting
- prioritization
- structured context merging
- history allocation
Stage 5 — LLM Processing
- provider abstraction
- request execution
- response tracking
Stage 6 — Background Intelligence
- asynchronous memory extraction
- embeddings
- analytics
- evaluations
Intent System
Current Intent Categories:
- General
- Project
Classification Strategy:
- heuristics-first
- lightweight inference fallback
- retrieval avoidance optimization
Goal:
"Prevent unnecessary memory injection while preserving contextual dependency."
Memory System
Semantic Retrieval
Uses vector similarity matching for contextual recall.
Relevance Filtering
Weak retrievals are skipped automatically.
Memory Deduplication
Near-identical memories are merged or ignored.
Observability Tracking
Retrieval quality and similarity metrics are recorded for evaluation.
Future Roadmap
- Memory graphs
- Recency weighting
- Adaptive retrieval
- Conflict resolution
- Memory aging
Context Assembly
Token Budgeting
Strict limits applied per-category to prevent window overflow.
Prioritization Strategy
High-signal knowledge is prioritized over raw conversation history.
Orchestration Constraints
Ensures models receive deterministic, structured payloads.
Context Compression
Low-value turns are aggressively compressed or discarded.
Observability
Retrieval Latency
LLM Latency
Memory Hit Rate
Token Savings
Similarity Scores
Trace IDs
Distributed Tracing
Tracks requests fully across all isolated orchestration stages.
Orchestration Inspection
Allows deep dives into exact prompt assembly decisions.
Evaluation Logging
Maintains historical logs for offline benchmark runs.
Metrics Aggregation
Provides high-level system health and efficiency reporting.
Sandbox
"The Sandbox exists for orchestration benchmarking and continuity evaluation."
Evaluation Framework
Continuity Preservation
Retrieval Usefulness
Instruction Retention
Context Relevance
Latency Impact
Token Efficiency
"Torqon evaluates orchestration quality through comparative long-conversation testing workflows."
Distributed Systems
Synchronous Request Path
- deterministic
- low latency
- debuggable
- directly orchestrated
Asynchronous Background Systems
- embeddings
- analytics
- evaluations
- distributed events
Roadmap
- hypothesis validation
- observability refinement
- retrieval benchmarking
- adaptive orchestration
- task-aware policies
- contextual intelligence
- advanced memory systems