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MODEL_NAME=gpt-4-turbo-preview
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OPENAI_API_KEY=sk-xxxx..
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LANGFUSE_PUBLIC_KEY=pk-lf-...
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LANGFUSE_SECRET_KEY=sk-lf-...
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LANGFUSE_HOST=http://brunix-observability:3000
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# Brunix Assistance Engine
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The **Brunix Assistance Engine** is a high-performance, gRPC-powered AI orchestration service. It serves as the core intelligence layer for the Brunix ecosystem, integrating advanced RAG (Retrieval-Augmented Generation) capabilities with real-time observability.
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This project is a strategic joint development:
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* **[101OBEX Corp](https://101obex.com):** Infrastructure, System Architecture, and the proprietary **AVAP Technology** stack.
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* **[MrHouston](https://mrhouston.net):** Advanced LLM Fine-tuning, Model Training, and Prompt Engineering.
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---
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## System Architecture
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The following diagram illustrates the interaction between the AVAP technology, the trained intelligence, and the infrastructure components:
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```mermaid
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graph TD
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subgraph Client_Layer [External Interface]
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Client[External Services / UI]
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end
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subgraph Engine_Layer
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BE[Brunix Assistance Engine]
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LG[LangGraph Logic]
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LC[LangChain Framework]
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end
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subgraph Intelligence_Layer
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LLM[Fine-tuned Model / OpenAI or other]
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Prompt[Prompt Engineering]
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end
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subgraph Data_Observability_Layer [System Support]
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EDB[(Elasticsearch Vector DB)]
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LF[Langfuse Observability]
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PG[(Postgres - System Data)]
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end
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Client -- gRPC:50052 --> BE
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BE --> LG
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LG --> LC
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LC --> LLM
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LLM --> Prompt
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LC -- Semantic Search --> EDB
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LC -- Tracing/Metrics --> LF
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LF -- Persistence --> PG
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```
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---
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## Technology Stack
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* **Logic Layer:** [LangChain](https://www.langchain.com/) & [LangGraph](https://langchain-ai.github.io/langgraph/) (Python 3.11).
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* **Communication:** [gRPC](https://grpc.io/) (High-performance, low-latency RPC framework).
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* **Vector Database:** [Elasticsearch 8.12](https://www.elastic.co/) (For semantic search and AVAP data retrieval).
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* **Observability:** [Langfuse](https://langfuse.com/) (End-to-end tracing, latency monitoring, and cost management).
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* **Infrastructure:** Dockerized environment with PostgreSQL 15 persistence.
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---
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## Getting Started
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### Prerequisites
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* Docker & Docker Compose
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* OpenAI API Key (or configured local provider)
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### Installation & Deployment
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1. **Clone the repository:**
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```bash
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git clone git@github.com:BRUNIX-AI/assistance-engine.git
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cd assistance-engine
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```
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2. **Configure Environment Variables:**
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Create a `.env` file in the root directory:
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```env
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OPENAI_API_KEY=your_key_here
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LANGFUSE_PUBLIC_KEY=pk-lf-...
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LANGFUSE_SECRET_KEY=sk-lf-...
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LANGFUSE_HOST=http://langfuse:3000
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```
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3. **Launch the Stack:**
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```bash
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docker-compose up -d --build
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```
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The engine will be listening for gRPC requests on port `50052`.
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---
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## Component Overview
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| Service | Container Name | Description | Role |
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| :--- | :--- | :--- | :--- |
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| **Engine** | `brunix-assistance-engine` | The AVAP-powered brain. | 101OBEX Corp |
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| **Vector DB** | `brunix-vector-db` | Elasticsearch instance (Knowledge Base). | Training Support |
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| **Observability** | `brunix-observability` | Langfuse UI (Tracing & Costs). | System Quality |
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| **System DB** | `brunix-postgres` | Internal storage for Langfuse. | Infrastructure |
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---
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## Partnership & Contributions
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This repository is private and represents the intellectual property of **101OBEX Corp** and **MrHouston**.
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* **Architecture & AVAP:** Managed by 101OBEX Engineering.
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* **Model Training & Intelligence:** Managed by MrHouston Data Science Team.
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---
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## Open Source & Intellectual Property
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The Brunix Assistance Engine is built on a hybrid architecture that balances the flexibility of open-source tools with the security of proprietary intelligence:
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* **Open Source Frameworks:** Utilizes **LangChain** and **LangGraph** (MIT License) for orchestration, and **gRPC** for high-performance communication.
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* **Infrastructure:** Deploys via **Docker** using **PostgreSQL** and **Elasticsearch** (Elastic License 2.0).
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* **Proprietary Logic:** The **AVAP Technology** (101OBEX Corp) and the specific **Model Training/Prompts** (MrHouston) are protected intellectual property.
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* **LLM Provider:** Currently configured for **OpenAI** (Proprietary SaaS). The modular design allows for future integration with locally-hosted Open Source models (e.g., Llama 3, Mistral) to ensure 100% data sovereignty if required.
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## Security & Privacy
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The system is designed with a "Security-First" approach to protect corporate intelligence:
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1. **Data in Transit:** Communication between the Engine and external clients is handled via **gRPC**, supporting **TLS/SSL encryption** to ensure that data remains private and tamper-proof.
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2. **Internal Networking:** All database interactions (Elasticsearch, PostgreSQL) occur within a **private Docker bridge network** (`avap-network`), isolated from the public internet.
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3. **Observability Governance:** **Langfuse** provides a full audit trail of every LLM interaction, allowing for real-time monitoring of data leakage or unexpected model behavior.
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4. **Enterprise Secret Management:** While local development uses `.env` files, the architecture is **Production-Ready for Kubernetes**. In production environments, sensitive credentials (API Keys, Database passwords) are managed via **Kubernetes Secrets** or **HashiCorp Vault**, ensuring that no sensitive data is stored within the container images or source control.
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```mermaid
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graph LR
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subgraph Public_Internet
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Client[External Client]
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end
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subgraph Encrypted_Tunnel [TLS/SSL]
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gRPC[gRPC Protocol]
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end
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subgraph K8s_Cluster [Production Environment]
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Engine[Brunix Engine]
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Sec{{"Kubernetes Secrets"}}
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DB[(Databases)]
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end
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Client --> gRPC
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gRPC --> Engine
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Sec -.->|Injected as Env| Engine
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Engine <--> DB
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```
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# Changelog
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All notable changes to the **Brunix Assistance Engine** will be documented in this file. This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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---
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## [1.0.0] - 2026-02-09
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### Added
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- **System Architecture:** Implementation of the triple-layer stack (Engine, Vector DB, Observability).
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- **Core Engine:** Deployment of the `brunix-assistance-engine` using **Python 3.11**, **LangChain**, and **LangGraph** for agentic workflows.
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- **Communication Layer:** Established **gRPC** as the primary high-performance interface (Port 50051/50052).
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- **Knowledge Base:** Integration of **Elasticsearch 8.12** (`brunix-vector-db`) for AVAP technology RAG support.
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- **Observability Framework:** Deployment of **Langfuse** and **PostgreSQL** for full trace audit and cost management.
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- **Security:** Initial network isolation within Docker (`avap-network`) and production-ready secret management design.
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