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# 🔬 Compileo: The Ultimate AI-Powered Document Processing & Dataset Engineering Suite
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**Compileo** is an enterprise-grade, modular platform designed to transform raw, unstructured data into high-quality, structured intelligence. Whether you're processing 1,000-page medical PDFs, scraping JavaScript-heavy websites, or engineering datasets for LLM fine-tuning and personal study, Compileo provides a unified, AI-driven lifecycle for the modern data era.
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---
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## 🌟 What can Compileo do?
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Compileo isn't just a parser—it's a comprehensive **data engineering ecosystem**. It automates the complex journey from \"Messy Source\" to \"Validated, Categorized Intelligence.\"
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### 📖 Multi-Source Knowledge Consolidation
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Imagine you have several thick textbooks and want to create a specialized dataset focused only on **disease treatments**. Compileo can:
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1. **Ingest** all books simultaneously (PDF, DOCX, etc.).
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2. **Discover** a unified \"Treatment\" taxonomy across all sources automatically.
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3. **Extract** every mention of treatments, dosages, and contraindications with high precision.
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4. **Consolidate** this into one unified, high-quality Q&A dataset for training or study.
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### 🕹️ Three Ways to Work
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Compileo is designed for every workflow:
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* **Web GUI**: A user-friendly Streamlit interface with a 7-step guided wizard.
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* **REST API**: Seamlessly integrate dataset generation into your own applications.
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* **CLI**: Automate heavy-duty processing with powerful command-line parameters.
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---
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## 🚀 Impressive Features
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### 📄 Intelligent Document Processing & AI-Assisted Chunking
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* **Massive PDF Autonomy**: Automatically splits 1,000+ page documents into manageable segments with **semantic overlaps**, ensuring LLM token limits are never hit while preserving context.
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* **Two-Pass VLM Parsing**: Employs a \"Skim and Extract\" methodology using Vision-Language Models (Grok, Gemini, Ollama) to first understand document layout and then extract high-fidelity Markdown.
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* **AI-Assisted Strategy Recommendation**: Don't guess how to split your data. Describe your goal (e.g., *\"I want to extract detailed surgical procedures\"*), and Compileo's AI will analyze your documents to recommend the optimal **Semantic**, **Token**, or **Schema-based** chunking strategy.
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### 🧠 Semantic Data Engineering
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* **AI-Assisted Taxonomy**: Don't waste weeks defining categories. Compileo's **Smart Sampling** selects representative content to suggest and build hierarchical knowledge trees automatically.
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* **Multi-Stage Extraction**: Performs **Hierarchical Classification**, moving from coarse-grained categories to fine-grained entities based on your custom or generated taxonomy.
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* **Context-Aware NER**: Uses parent context during extraction to disambiguate entities and discover deep relationships between concepts.
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### 🧪 Advanced Quality Control & Evaluation
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* **AI Confidence Scoring**: Every extracted entity and relationship is assigned an **AI confidence level** (0.0 - 1.0), allowing you to filter for only the most reliable data.
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* **Deep Quality Metrics**: Automated scoring for **Lexical Diversity**, **Demographic Bias**, **Answer Coherence**, and **Target Audience Alignment** via the `datasetqual` module.
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* **Fine-Tuned Model Testing**: Use the `benchmarking` module to evaluate how your **fine-tuned models** perform on your custom datasets using industry-standard metrics (Accuracy, F1, BLEU, ROUGE) and suites like GLUE or MMLU.
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### 🔌 Developer Extensibility
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* **Robust Plugin System**: Effortlessly extend Compileo by adding custom **Ingestion Handlers**, **Dataset Formatters**, or **API Routers** via a simple `.zip` package architecture.
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* **Custom Exports**: Out-of-the-box support for **Anki** export, allowing you to turn any technical document into a high-quality study deck.
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---
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## 🛠️ Installation
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### 🐳 Option 1: Docker
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The fastest way to deploy the full stack (API, GUI, and Redis).
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1. **Clone & Prepare**:
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```bash
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git clone https://github.com/your-org/compileo.git
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cd compileo
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cp .env.example .env # Add your API keys for Gemini, Grok, etc.
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```
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2. **Launch**:
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```bash
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docker compose up --build -d
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```
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3. **Access**:
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* **Web GUI**: `http://localhost:8501`
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* **API Docs**: `http://localhost:8000/docs`
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### 🔐 API Authentication & Security
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Compileo implements an **"Auto-Lock"** security model designed for zero-config startup without sacrificing security.
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* **Unsecured Mode (Default)**: If no API keys are defined, Compileo allows all requests. This is ideal for first-time setup and local experimentation.
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* **Secured Mode**: As soon as you define an API key, the system "locks" and strictly requires that key for all API and GUI operations.
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#### **How to Secure Your Instance (Choose One):**
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1. **GUI (Recommended)**: Launch Compileo, go to **Settings > 🔗 API Configuration**, enter an **API Key**, and click **Save**. The system locks instantly.
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2. **CLI**: Start the API with the `--api-key` flag:
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```bash
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python -m src.compileo.api.main --api-key your_secret_key
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```
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3. **Environment**: Define `COMPILEO_API_KEY=your_secret_key` in your `.env` or Docker configuration.
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#### **How to Connect to a Secured Instance:**
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All API requests must include the following header:
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```http
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X-API-Key: your_secret_key
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```
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---
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### 🐍 Option 2: Python Environment
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Ideal for local development, CLI automation, or custom integrations.
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**Prerequisites**: A running Redis server (`sudo apt install redis-server`).
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1. **Setup Environment**:
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```bash
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python -m venv .venv
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source .venv/bin/activate # Windows: .venv\Scripts\activate
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```
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2. **Install Dependencies**:
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```bash
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pip install -r requirements.txt
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```
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3. **Start Services**:
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```bash
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# 1. Start the API server (Optionally secure it with --api-key)
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python -m src.compileo.api.main --api-key my_secret_token
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# 2. Start the Web GUI (In a new terminal)
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streamlit run src/compileo/features/gui/main.py
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```
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*Note: If you secured the API in step 1, you must enter the same key in the GUI Settings to connect.*
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---
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## 📖 Explore Further
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* [API Authentication](docs/userGuide/api_authentication.md): Detailed guide on securing your Compileo API instance.
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* [GUI User Guide](docs/userGuide/gui_user_guide.md): Walk through the 7-step Dataset Creation Wizard.
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* [Plugin Development Guide](docs/developers/plugin_development_guide.md): Learn how to build your own extensions.
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* [CLI Reference](docs/userGuide/documentscli.md): Automate workflows via the command line.
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## 📄 License
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[Insert License Information]

mkdocs.yml

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site_dir: ../site
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nav:
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- Home: ../README.md
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- Home: index.md
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- User Guide:
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- API Authentication: docs/userGuide/api_authentication.md
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- Benchmarking API: docs/userGuide/benchmarkingapi.md

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