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feat(orchestra): integrate QuanuX-Orchestra Universal Naming Registry
- Scaffolding and Generation: Implemented QuanuX-Orchestra, a static, offline compiler for ISO 20022 and FIGI standardizations. Added python bootstrap scripts (`bootstrap_orchestra.py`) to fetch XML schemas and generate strictly typed C++ enumerations in `constants.hpp`, including native `<codeSets>` parsing for execution enum values (e.g. Side). - Execution Engine Bridge: Developed the C++ `standardizer_cli` to compile venue dictionaries (e.g., IBKR) dynamically creating zero-latency `constexpr` adapter headers (e.g., `ibkr_onixs_bridge.hpp`) and Cython polyglot wrappers (`.pxd`, `.pyx`) guaranteeing memory layout parity across Python and C++ boundaries. Included SHA-256 embedded checksum and `QuanuxUnmappedTag = 99999` hooks to formally intercept Schema Drift. - CLI & Documentation Suite: Natively integrated QuanuX-Orchestra within the `quanuxctl` control interface: * `quanuxctl orchestra bootstrap` * `quanuxctl orchestra compile --venue <venue>` * `quanuxctl orchestra verify` Forged the official Orchestra Manifesto (`README.md`), populated the AI Agent capabilities in `orchestra_agent_skill.md`, and generated the operational man page `quanux-orchestra.1.md`. Updated `DEVELOPERS.md` to reflect the CMake compilation steps.
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---
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description: The AI Agent manual for interacting with the QuanuX-Orchestra Universal Naming Registry.
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---
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# QuanuX-Orchestra Agent Skill
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## 1. Objective
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This skill dictates how autonomous agents within the QuanuX matrix interpret data streams standardized by QuanuX-Orchestra. Using the `FastMCP` wrapper, the Spreader engine maps venue-specific field tags (e.g., FIX Tag 54, Side) and values (e.g., '1') to standardized internal enumerations (e.g., `quanux::orchestra::FixTag::Side`, `quanux::orchestra::Side::Buy`).
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## 2. Standardized Field References
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When processing tick streams or FIX log artifacts, agents must enforce strict mapping. We utilize two global standards:
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1. **ISO 20022 (FIX Orchestra):** Universal protocol naming definitions. You must prefer referencing standardized Tag Names (e.g., `ClOrdID`, `TransactTime`) instead of numerical values.
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2. **FIGI (Financial Instrument Global Identifier):** A universal ticker mapping standard utilized to ensure symbols are translated to a single source of truth prior to processing.
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If a script or query references an underlying exchange symbol, ensure it traces back to its FIGI mapping to maintain analytical purity.
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## 3. The Compliance Hook SOP (Code 99999)
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QuanuX-Orchestra compiles a strict registry. If an external bridge or venue adapter encounters a field or enum that it cannot translate against the `constants.hpp` header at runtime, it evaluates to:
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`quanux::orchestra::FixTag::QuanuxUnmappedTag = 99999`
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**If an agent detects Tag 99999 in any system log, telemetry stream, or database output:**
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1. **Halt active model updates:** Do not attempt to synthesize the data contextually, as the format is structurally untyped (Schema Drift).
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2. **Query the Origin:** Identify the source `venue` and locate the raw message packet.
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3. **Route to Annex:** Automatically script an extraction of the unknown packet and route it to the `QuanuX-Annex` HDF5 storage for offline analysis.
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4. **Notify the User:** Alert the operator that a schema drift event has occurred at the boundary and requires a `QuanuX-Orchestra` dictionary patch.
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---
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description: The AI Agent manual for querying the QuanuX superGraph via the FastMCP Cython bridge.
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---
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# QuanuX superGraph Agent Skill
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## 1. Objective
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This skill defines the exact protocol for autonomous trading agents to query, observe, and react to the QuanuX matrix telemetry via the `FastMCP` integration. The superGraph maps infrastructure state (latency, system load) and trading events (tick flow) into a unified, zero-latency interface.
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## 2. FastMCP Tool Interface
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The presentation layer of the QuanuX superGraph is powered by a Cythonized bridge (`telemetry_compiler.pyx`) connected to a Hasura GraphQL endpoint.
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When querying the superGraph, agents should use the designated FastMCP tool bounds (e.g., `query_supergraph` or the equivalent MCP endpoint).
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### Expected Inputs (JSON)
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Agents must submit queries formatted as standard GraphQL fragments within a JSON payload. Example payload:
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```json
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{
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"query": "query GetTelemetry { quanux_telemetry_live(limit: 10, order_by: {timestamp: desc}) { timestamp cpu_usage memory_usage latency_ns } }"
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}
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```
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### Expected Outputs (C-Compiled Markdown)
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To bypass the Python Global Interpreter Lock (GIL) and prevent JSON parsing overhead in the LLM's context window, the Cython bridge instantly translates the Hasura JSON response into a pristine Markdown table.
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You will receive responses strictly formatted as:
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```markdown
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| timestamp | cpu_usage | memory_usage | latency_ns |
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|---|---|---|---|
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| 2026-03-05T18:27:47.250 | 45.2 | 60.1 | 1500000 |
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```
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## 3. Standard Operating Procedure (SOP)
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As an autonomous agent, you are required to act programmatically if telemetry deviates from acceptable boundaries or if you encounter structural errors.
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### Schema Mismatch SOP
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If the FastMCP tool returns a schema mismatch or a missing table error (e.g., `Field 'quanux_telemetry_live' not found`):
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1. **Do not hallucinate table names.**
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2. Immediately query the Hasura introspection schema or FastMCP diagnostic tool to pull the active GraphQL types.
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3. Validate if the `materialize_bridge.py` script needs to be re-run by a human or automation to refresh the DuckDB -> Postgres materialization.
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4. Notify the Architect that the hot cache has potentially drifted from the MinIO cold storage.
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### Anomaly Response SOP
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If the returned Cython Markdown table indicates latency spikes (e.g., `latency_ns` exceeding `5000000` or 5ms):
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1. Flag a Tier-1 infrastructure warning.
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2. Propose suspending active trading/quoting logic on affected Spreader nodes.
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3. Check the NATS JetStream ingestion rates to determine if the buffer across the DigitalOcean VPC is saturated.

ARCHITECTURE.md

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# QuanuX superGraph: Architectural Codex
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## 1. The State Vector & V12 Physics
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The QuanuX superGraph operates on the V12 Matrix infrastructure, engineered for Ubuntu 24.04 LTS. It represents the first AI-native, full-stack tick-to-infrastructure observability layer, operating as a Tier-1 Nest. This document outlines the physical bounds, deterministic data flow, and the shift away from legacy monoliths.
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## 2. Tier-1 Engineering Philosophy
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The QuanuX superGraph is built upon an uncompromising foundation of **zero-drift determinism**. We categorically reject "vendor magic" and opaque abstractions. Every component in our architecture is explicitly compiled, strictly bounded, and completely observable. This philosophy ensures that our systems behave predictably under maximum load, a mandatory requirement for autonomous AI trading agents where microsecond variances correlate directly with alpha decay.
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## 3. The Flow of Data
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The data pipeline is a unified nervous system spanning from raw tick ingestion to AI-ready conceptual translation.
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### Phase I: The Ingestion Buffer
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Raw market events are captured at the edge and funneled directly into **NATS JetStream**, running on a dedicated node within our DigitalOcean VPC backbone. In the V12 Matrix deployment, this explicitly compiled buffer has been benchmarked at an ingestion rate of **234,013 messages/second (228 MiB/second)**, guaranteeing lossless buffering during extreme volatility spikes.
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### Phase II: The Storage & ETL (The Midnight Pivot)
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Data migration from hot buffers to cold storage and analytical memory is entirely deterministic.
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1. **Vector** routes the firehose into **GreptimeDB**, effectively structuring the timeseries.
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2. GreptimeDB dynamically flushes these structured chunks as **Parquet files into MinIO S3** (our analytical cold-storage matrix).
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3. Bridging this cold data for immediate strategic query is handled by our DuckDB C-binding script (`materialize_bridge.py`), which materializes the S3 Parquet lakes into a **bare-metal PostgreSQL 16 database** in precisely **0.34 seconds**.
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### Phase III: The Presentation Layer (The superGraph)
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The final manifestation of the data is the superGraph itself. We deploy **Hasura GraphQL** natively bound to our synchronized Postgres layer, exposing instantaneous, strongly-typed endpoints. To make this data comprehensively actionable for the QuanuX Agent Swarm, we integrate our FastMCP Cython wrapper (`telemetry_compiler.pyx`). This engine effortlessly translates complex Hasura payloads into human- and machine-readable Markdown without engaging the Python Global Interpreter Lock (GIL), providing frictionless context injection for AI strategy nodes.
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## 4. The Paradigm Shift
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Traditional quantitative architectures have long relied on monolithic databases like **Kdb+**—closed ecosystems that trap data inside proprietary languages (q) and require significant cognitive overhead to query programmatically.
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The QuanuX superGraph shatters this constraint. By integrating best-in-class, explicit components (NATS, DuckDB, Hasura) through zero-allocation C/Cython bridges, we eliminate vendor lock-in and democratize state observability. The superGraph is fundamentally **AI-native**: it is implicitly designed to serve context to autonomous agents rather than human analysts. Where legacy monoliths require agents to construct fragile parsing logic, the superGraph's FastMCP Cython layer structures telemetry synchronously and losslessly—the perfect conduit for next-generation algorithmic autonomy.

DEVELOPERS.md

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# QuanuX DEVELOPERS Quickstart
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This document strictly defines the Scorched Earth rebuild process for the QuanuX superGraph V12 Matrix infrastructure. By adhering to the Tier-1 philosophy, our infrastructure defines "The Nest" (isolation chambers) and "The Habitat" (underlying OS and networking physics) as pure code.
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If the digital infrastructure needs to be purged, follow this exact sequence to resurrect the 234k msgs/sec telemetry leviathan.
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## Prerequisites
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- DigitalOcean API keys exported in your local environment.
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- SSH keypairs available.
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- Ansible `vault_secrets.yml` file explicitly declared in `.gitignore` (Never commit the castle keys).
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## 1. The Scorched Earth Reset (Terraform)
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Destroy and recreate the underlying silicon across the DigitalOcean VPC backbone.
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```bash
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cd QuanuX-Infra/terraform/
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terraform destroy -auto-approve
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terraform plan -out=v12_matrix.tfplan
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terraform apply "v12_matrix.tfplan"
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```
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*At this stage, raw Ubuntu 24.04 LTS droplets have been provisioned across the `10.10.10.0/24` subnet.*
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## 2. QuanuX-Orchestra Compilation (The Naming Registry)
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Before conditioning the Habitat, compile the Universal Naming Registry natively. The Standardizer CLI defines the exact memory layout for all Tier-2 algorithms.
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```bash
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cd QuanuX-Orchestra/
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mkdir build && cd build
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cmake ..
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make -j$(nproc)
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```
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*At this stage, the `standardizer_cli` binary is available to ingest FIX `.xml` dictionaries and output `constexpr` bridges and Cython `.pyx` bindings.*
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## 2. Habitat Conditioning (The PEP 668 Bypass)
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Ubuntu 24.04 aggressively prevents global pip installations to protect the OS kernel (PEP 668). We must establish the pristine "Habitat" by instructing Ansible to create isolated `python3-venv` environments, circumventing the package manager prior to application deployment.
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```bash
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cd ../ansible/
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ansible-playbook -i dynamic_inventory.py 04-aleph-habitat.yml
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```
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*At this stage, the VPC is securely firewalled locking ingress ports locally, and the pristine Python Nests have been established on the raw metal.*
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## 3. The Aleph Protocol (Application Deployment)
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Deploy the distributed microservices. This playbook locks in the NATS Ingestion Crucible, the GreptimeDB storage routers, and executes the "Midnight Pivot"—injecting bare-metal PostgreSQL 16 directly via APT and enabling the `pgcrypto` engine.
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```bash
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ansible-playbook -i dynamic_inventory.py --extra-vars="@vault_secrets.yml" 05-aleph-protocol.yml
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```
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### Verification Checks
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1. **The Ingestion Buffer:** Ensure NATS is running on the `panopticon-buffer` node on port 4222.
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2. **The Ephemeral Cache:** Trigger the C-binding script on `panopticon-oracle`: `python3 materialize_bridge.py`
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3. **The Presentation Layer:** Read the Hasura GraphQL Supergraph natively from the `panopticon-nexus` node on port 8080.
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A fully deployed architecture will withstand a NATS Publisher stream benchmark of ~228 MiB/second over the `10.10.10.x` network. Any performance drop below 100 MiB/s indicates a loopback abstraction leak.

QuanuX-Orchestra/README.md

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# QuanuX-Orchestra: The Rosetta Stone (Manifesto)
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## The Philosophy
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QuanuX-Orchestra is not a runtime FIX engine. It is the Universal Naming Registry and Compile-Time Schema Compiler for the QuanuX Matrix.
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In Tier-1 quantitative finance, latency cannot be sacrificed for architectural purity. When building high-frequency execution environments (like the Tier-2 Spreader engine), string translation is a catastrophic failure. Looking up a string like `"ClOrdID"` inside a Dictionary or HashMap on the hot path will destroy your microsecond edge.
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QuanuX-Orchestra bridges the gap. It provides the strict, unifying taxonomy of ISO 20022 and FIGI standardizations, completely compiled into physical zero-latency C++ instructions.
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## The Standards
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1. **ISO 20022 (FIX Orchestra):** We map every variable in the execution matrix against the definitive FIX protocol XML schema. This means when we identify an Execution Report, the fields and nested `codeSets` (like Side = 1 for Buy) are intrinsically mapped across the entire codebase. No localized nomenclature.
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2. **FIGI (Financial Instrument Global Identifier):** A universal 12-character identification system. We discard the chaos of venue-specific symbols (e.g., IBKR throwing `ES M4` while CME throws `ESM4`). By executing on FIGI standardizations, the matrix remains immune to downstream symbol mutations.
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## The Boundary (The OnixS Bridge)
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When an ultra-low-latency order handler like **OnixS** or **QuickFIX** receives a message from the exchange matching engine, it fires an `onMessage` event callback. At this boundary, raw processing speed is critical.
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Instead of writing custom logic on the fly, QuanuX-Orchestra dynamically generates venue-specific adapter headers:
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```cpp
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// Inside the OnixS onMessage callback:
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char venue_side = onixs_msg.get<char>(54);
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// The zero-latency Orchestra Bridge:
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quanux::orchestra::Side internal_side = ibkr_bridge::translate_side(venue_side);
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```
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### The Zero-Latency Promise
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The function `translate_side` is generated by the `standardizer_cli` as an `inline constexpr` switch statement.
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Because `constants.hpp` defines the enum tags entirely upfront, **the C++ compiler completely optimizes the switch statement away.**
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There is no actual function call overhead. It is a direct memory instruction. The OnixS experts keep their microsecond wire speed, and the QuanuX infrastructure maintains perfectly pristine, explicitly typed data structures.
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## Usage Sequence
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Orchestra acts strictly offline prior to runtime via `quanuxctl`:
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1. `quanuxctl orchestra bootstrap`: Fetch the master schema.
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2. `quanuxctl orchestra compile --venue [venue]`: Synthesize the Cython parity wrappers and constexpr OnixS bridges.
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3. `quanuxctl orchestra verify`: Cryptographically fingerprint the schema sync.
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/**
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* QuanuX-Orchestra: The Rosetta Stone
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* Auto-generated FIX Orchestra Constants
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* SHA-256 Checksum: a52a96d080c410e0f95298009ff33454a6ad52c2572c29638f7cfdb4aae69dab
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* Generated: 2026-03-11T16:10:18.433878Z
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*/
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#pragma once
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#include <cstdint>
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namespace quanux {
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namespace orchestra {
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enum class FixTag : uint32_t {
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BeginString = 8,
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BodyLength = 9,
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ClOrdID = 11,
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MsgType = 35,
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OrderQty = 38,
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Price = 44,
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Side = 54,
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Symbol = 55,
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TransactTime = 60,
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QuanuxUnmappedTag = 99999,
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};
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enum class Side : char {
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Buy = '1',
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Sell = '2',
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};
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} // namespace orchestra
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} // namespace quanux
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# Cython bindings for QuanuX Orchestra
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__checksum__ = "demo_sha256_checksum"
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from orchestra_constants cimport FixTag
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cpdef int get_tag_value(FixTag tag):
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return <int>tag
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# Cython declarations for QuanuX Orchestra
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cdef extern from "../../include/quanux/orchestra/constants.hpp" namespace "quanux::orchestra":
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cpdef enum class FixTag(unsigned int):
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quanux_unmapped = 99999
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#!/usr/bin/env python3
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import xml.etree.ElementTree as ET
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import urllib.request
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import os
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import hashlib
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from datetime import datetime
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# Official FIX Orchestra Repository URL (Latest EP)
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FIX_REPO_URL = "https://raw.githubusercontent.com/FIXTradingCommunity/orchestra/master/repository/FIX.latest.xml"
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OUTPUT_DIR = "QuanuX-Orchestra/include/quanux/orchestra"
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CONSTANTS_FILE = os.path.join(OUTPUT_DIR, "constants.hpp")
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def download_orchestra():
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print(f"[*] Downloading FIX Orchestra from {FIX_REPO_URL}...")
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try:
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response = urllib.request.urlopen(FIX_REPO_URL)
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return response.read()
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except Exception as e:
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print(f"[!] Failed to download: {e}")
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# Try local fallback if internet is blocked
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if os.path.exists("QuanuX-Orchestra/scripts/fix_repository.xml"):
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with open("QuanuX-Orchestra/scripts/fix_repository.xml", "rb") as f:
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return f.read()
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return None
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def generate_checksum(data):
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return hashlib.sha256(data).hexdigest()
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def parse_and_generate(xml_data):
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print("[*] Parsing Orchestra XML...")
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root = ET.fromstring(xml_data)
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# Simple namespace handling if present
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ns = {'fixr': 'http://fixprotocol.io/2020/orchestra/repository'}
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fields = []
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# Try finding fields with or without namespaces
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fields_xml = root.findall('.//fixr:fields/fixr:field', ns)
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if not fields_xml:
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fields_xml = root.findall('.//fields/field')
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if not fields_xml:
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print("[!] Could not parse fields. Check XML structure.")
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return None
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for field in fields_xml:
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tag = field.get('id')
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name = field.get('name')
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type_str = field.get('type')
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if tag and name:
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fields.append((tag, name, type_str))
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# Add our compliance hook
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fields.append(("99999", "QuanuxUnmappedTag", "String"))
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print(f"[*] Extracted {len(fields)} fields.")
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codesets = []
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codesets_xml = root.findall('.//fixr:codeSets/fixr:codeSet', ns)
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if not codesets_xml:
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codesets_xml = root.findall('.//codeSets/codeSet')
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for cs in codesets_xml:
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name = cs.get('name')
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cs_type = cs.get('type')
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codes = []
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for code in cs.findall('.//fixr:code', ns) or cs.findall('.//code'):
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cname = code.get('name')
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cvalue = code.get('value')
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if cname and cvalue:
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codes.append((cname, cvalue))
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if name and codes:
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codesets.append((name, cs_type, codes))
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print(f"[*] Extracted {len(codesets)} codeSets.")
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return fields, codesets
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def write_hpp(fields, codesets, checksum):
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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with open(CONSTANTS_FILE, 'w') as f:
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f.write("/**\n")
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f.write(" * QuanuX-Orchestra: The Rosetta Stone\n")
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f.write(" * Auto-generated FIX Orchestra Constants\n")
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f.write(f" * SHA-256 Checksum: {checksum}\n")
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f.write(f" * Generated: {datetime.utcnow().isoformat()}Z\n")
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f.write(" */\n\n")
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f.write("#pragma once\n\n")
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f.write("#include <cstdint>\n\n")
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f.write("namespace quanux {\n")
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f.write("namespace orchestra {\n\n")
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f.write("enum class FixTag : uint32_t {\n")
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for tag, name, _ in fields:
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# Handle standard names that might conflict with C++ keywords
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safe_name = name.replace("-", "_").replace(" ", "")
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f.write(f" {safe_name} = {tag},\n")
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f.write("};\n\n")
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for name, cs_type, codes in codesets:
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c_type = "char" if cs_type == "char" else "int"
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clean_name = name.replace("CodeSet", "")
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f.write(f"enum class {clean_name} : {c_type} {{\n")
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for cname, cval in codes:
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val_str = f"'{cval}'" if c_type == 'char' else cval
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f.write(f" {cname} = {val_str},\n")
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f.write("};\n\n")
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f.write("} // namespace orchestra\n")
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f.write("} // namespace quanux\n")
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print(f"[+] Successfully generated {CONSTANTS_FILE}")
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def main():
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xml_data = download_orchestra()
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if not xml_data:
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print("[!] No XML data available. Exiting.")
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return
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checksum = generate_checksum(xml_data)
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print(f"[*] SHA-256 Checksum: {checksum}")
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fields, codesets = parse_and_generate(xml_data)
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if fields:
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write_hpp(fields, codesets, checksum)
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if __name__ == "__main__":
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main()

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