feat: WIP doc (vibe started and iterated)

docs/docs/concepts/modes.md

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+---
+sidebar_position: 2
+title: Operating Modes
+---
+
+# Operating Modes
+
+Reflector operates in two distinct modes to accommodate different use cases and security requirements.
+
+## Public Mode
+
+Public mode provides immediate access to core transcription features without requiring authentication.
+
+### Features Available
+- **File Upload**: Process audio files up to 2GB
+- **Live Transcription**: Stream audio from microphone
+- **Basic Processing**: Transcription and diarization
+- **Temporary Storage**: Results available for 24 hours
+
+### Limitations
+- No persistent storage
+- No meeting rooms
+- Limited to single-user sessions
+- No team collaboration features
+
+### Use Cases
+- Quick transcription needs
+- Testing and evaluation
+- Individual users
+- Public demonstrations
+
+## Private Mode
+
+Private mode unlocks the full potential of Reflector with authentication and persistent storage.
+
+### Additional Features
+- **Virtual Meeting Rooms**: Whereby integration
+- **Team Collaboration**: Share transcripts with team
+- **Persistent Storage**: Long-term transcript archive
+- **Advanced Analytics**: Meeting insights and trends
+- **Custom Integration**: Webhooks and API access
+- **User Management**: Role-based access control
+
+### Authentication Options
+
+#### Authentik Integration
+Enterprise-grade SSO with support for:
+- SAML 2.0
+- OAuth 2.0 / OIDC
+- LDAP / Active Directory
+- Multi-factor authentication
+
+#### JWT Authentication
+Stateless token-based auth for:
+- API access
+- Service-to-service communication
+- Mobile applications
+
+### Room Management
+
+Virtual rooms provide dedicated spaces for meetings:
+- **Persistent URLs**: Same link for recurring meetings
+- **Access Control**: Invite-only or open rooms
+- **Recording Consent**: Automatic consent management
+- **Custom Settings**: Per-room configuration
+
+## Mode Selection
+
+The mode is determined by your deployment configuration:
+
+```yaml
+# Public Mode (no authentication)
+REFLECTOR_AUTH_BACKEND=none
+
+# Private Mode (with authentication)
+REFLECTOR_AUTH_BACKEND=jwt
+# or
+REFLECTOR_AUTH_BACKEND=authentik
+```
+
+## Feature Comparison
+
+| Feature | Public Mode | Private Mode |
+|---------|------------|--------------|
+| File Upload | ✅ | ✅ |
+| Live Transcription | ✅ | ✅ |
+| Speaker Diarization | ✅ | ✅ |
+| Translation | ✅ | ✅ |
+| Summarization | ✅ | ✅ |
+| Meeting Rooms | ❌ | ✅ |
+| Persistent Storage | ❌ | ✅ |
+| Team Collaboration | ❌ | ✅ |
+| API Access | Limited | Full |
+| User Management | ❌ | ✅ |
+| Custom Branding | ❌ | ✅ |
+| Analytics | ❌ | ✅ |
+| Webhooks | ❌ | ✅ |
+
+## Security Considerations
+
+### Public Mode Security
+- Rate limiting to prevent abuse
+- File size restrictions
+- Automatic cleanup of old data
+- No PII storage
+
+### Private Mode Security
+- Encrypted data storage
+- Audit logging
+- Session management
+- Access control lists
+- Data retention policies
+
+## Choosing the Right Mode
+
+### Choose Public Mode if:
+- You need quick, one-time transcriptions
+- You're evaluating Reflector
+- You don't need persistent storage
+- You're processing non-sensitive content
+
+### Choose Private Mode if:
+- You need team collaboration
+- You require persistent storage
+- You're processing sensitive content
+- You need meeting room functionality
+- You want advanced analytics

docs/docs/concepts/overview.md

@@ -0,0 +1,194 @@
+---
+sidebar_position: 1
+title: Architecture Overview
+---
+
+# Architecture Overview
+
+Reflector is built as a modern, scalable, microservices-based application designed to handle audio processing workloads efficiently while maintaining data privacy and control.
+
+## System Components
+
+### Frontend Application
+
+The user interface is built with **Next.js 14** using the App Router pattern, providing:
+
+- Server-side rendering for optimal performance
+- Real-time WebSocket connections for live transcription
+- WebRTC support for audio streaming
+- Responsive design with Chakra UI components
+
+### Backend API Server
+
+The core API is powered by **FastAPI**, a modern Python framework that provides:
+
+- High-performance async request handling
+- Automatic OpenAPI documentation generation
+- Type safety with Pydantic models
+- WebSocket support for real-time updates
+
+### Processing Pipeline
+
+Audio processing is handled through a modular pipeline architecture:
+
+```
+Audio Input → Chunking → Transcription → Diarization → Post-Processing → Storage
+```
+
+Each step can run independently and in parallel, allowing for:
+- Scalable processing of large files
+- Real-time streaming capabilities
+- Fault tolerance and retry mechanisms
+
+### Worker Architecture
+
+Background tasks are managed by **Celery** workers with **Redis** as the message broker:
+
+- Distributed task processing
+- Priority queues for time-sensitive operations
+- Automatic retry on failure
+- Progress tracking and notifications
+
+### GPU Acceleration
+
+ML models run on GPU-accelerated infrastructure:
+
+- **Modal.com** for serverless GPU processing
+- Support for local GPU deployment (coming soon)
+- Automatic scaling based on demand
+- Cost-effective pay-per-use model
+
+## Data Flow
+
+### File Processing Flow
+
+1. **Upload**: User uploads audio file through web interface
+2. **Storage**: File stored temporarily or in S3
+3. **Queue**: Processing job added to Celery queue
+4. **Chunking**: Audio split into 30-second segments
+5. **Parallel Processing**: Chunks processed simultaneously
+6. **Assembly**: Results merged and aligned
+7. **Post-Processing**: Summary, topics, translation
+8. **Delivery**: Results stored and user notified
+
+### Live Streaming Flow
+
+1. **WebRTC Connection**: Browser establishes peer connection
+2. **Audio Capture**: Microphone audio streamed to server
+3. **Buffering**: Audio buffered for processing
+4. **VAD**: Voice activity detection segments speech
+5. **Real-time Processing**: Segments transcribed immediately
+6. **WebSocket Updates**: Results streamed back to client
+7. **Continuous Assembly**: Full transcript built progressively
+
+## Deployment Architecture
+
+### Container-Based Deployment
+
+All components are containerized for consistent deployment:
+
+```yaml
+services:
+  frontend:    # Next.js application
+  backend:     # FastAPI server
+  worker:      # Celery workers
+  redis:       # Message broker
+  postgres:    # Database
+  caddy:       # Reverse proxy
+```
+
+### Networking
+
+- **Host Network Mode**: Required for WebRTC/ICE compatibility
+- **Caddy Reverse Proxy**: Handles SSL termination and routing
+- **WebSocket Upgrade**: Supports real-time connections
+
+## Scalability Considerations
+
+### Horizontal Scaling
+
+- **Stateless Backend**: Multiple API server instances
+- **Worker Pools**: Add workers based on queue depth
+- **Database Pooling**: Connection management for concurrent access
+
+### Vertical Scaling
+
+- **GPU Workers**: Scale up for faster model inference
+- **Memory Optimization**: Efficient audio buffering
+- **CPU Optimization**: Multi-threaded processing where applicable
+
+## Security Architecture
+
+### Authentication & Authorization
+
+- **JWT Tokens**: Stateless authentication
+- **Authentik Integration**: Enterprise SSO support
+- **Role-Based Access**: Granular permissions
+
+### Data Protection
+
+- **Encryption at Rest**: Database and S3 encryption
+- **Encryption in Transit**: TLS for all connections
+- **Temporary Storage**: Automatic cleanup of processed files
+
+### Privacy by Design
+
+- **Local Processing**: Option to process entirely on-premises
+- **No Training on User Data**: Models are pre-trained
+- **Data Isolation**: Multi-tenant data separation
+
+## Integration Points
+
+### External Services
+
+- **Modal.com**: GPU processing
+- **AWS S3**: Long-term storage
+- **Whereby**: Video conferencing rooms
+- **Zulip**: Chat integration (optional)
+
+### APIs and Webhooks
+
+- **RESTful API**: Standard CRUD operations
+- **WebSocket API**: Real-time updates
+- **Webhook Notifications**: Processing completion events
+- **OpenAPI Specification**: Machine-readable API definition
+
+## Performance Optimization
+
+### Caching Strategy
+
+- **Redis Cache**: Frequently accessed data
+- **CDN**: Static asset delivery
+- **Browser Cache**: Client-side optimization
+
+### Database Optimization
+
+- **Indexed Queries**: Fast search and retrieval
+- **Connection Pooling**: Efficient resource usage
+- **Query Optimization**: N+1 query prevention
+
+### Processing Optimization
+
+- **Batch Processing**: Efficient GPU utilization
+- **Parallel Execution**: Multi-core CPU usage
+- **Stream Processing**: Reduced memory footprint
+
+## Monitoring and Observability
+
+### Metrics Collection
+
+- **Application Metrics**: Request rates, response times
+- **System Metrics**: CPU, memory, disk usage
+- **Business Metrics**: Transcription accuracy, processing times
+
+### Logging
+
+- **Structured Logging**: JSON format for analysis
+- **Log Aggregation**: Centralized log management
+- **Error Tracking**: Sentry integration
+
+### Health Checks
+
+- **Liveness Probes**: Component availability
+- **Readiness Probes**: Service readiness
+- **Dependency Checks**: External service status

docs/docs/concepts/pipeline.md

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+---
+sidebar_position: 4
+title: Processing Pipeline
+---
+
+# Processing Pipeline
+
+Reflector uses a modular pipeline architecture to process audio efficiently and accurately.
+
+## Pipeline Overview
+
+The processing pipeline consists of modular components that can be combined and configured based on your needs:
+
+```mermaid
+graph LR
+    A[Audio Input] --> B[Pre-processing]
+    B --> C[Chunking]
+    C --> D[Transcription]
+    D --> E[Diarization]
+    E --> F[Alignment]
+    F --> G[Post-processing]
+    G --> H[Output]
+```
+
+## Pipeline Components
+
+### Audio Input
+
+Accepts various input sources:
+- **File Upload**: MP3, WAV, M4A, WebM, MP4
+- **WebRTC Stream**: Live browser audio
+- **Recording Integration**: Whereby recordings
+- **API Upload**: Direct API submission
+
+### Pre-processing
+
+Prepares audio for optimal processing:
+- **Format Conversion**: Convert to 16kHz mono WAV
+- **Normalization**: Adjust volume to -23 LUFS
+- **Noise Reduction**: Optional background noise removal
+- **Validation**: Check duration and quality
+
+### Chunking
+
+Splits audio for parallel processing:
+- **Fixed Size**: 30-second chunks by default
+- **Overlap**: 1-second overlap for continuity
+- **Silence Detection**: Attempt to split at silence
+- **Metadata**: Track chunk positions
+
+### Transcription
+
+Converts speech to text:
+- **Model Selection**: Whisper or Parakeet
+- **Language Detection**: Automatic or specified
+- **Timestamp Generation**: Word-level timing
+- **Confidence Scores**: Quality indicators
+
+### Diarization
+
+Identifies different speakers:
+- **Voice Activity Detection**: Find speech segments
+- **Speaker Embedding**: Extract voice characteristics
+- **Clustering**: Group similar voices
+- **Label Assignment**: Assign speaker IDs
+
+### Alignment
+
+Merges all processing results:
+- **Chunk Assembly**: Combine transcription chunks
+- **Speaker Mapping**: Align speakers with text
+- **Overlap Resolution**: Handle chunk boundaries
+- **Timeline Creation**: Build unified timeline
+
+### Post-processing
+
+Enhances the final output:
+- **Formatting**: Apply punctuation and capitalization
+- **Translation**: Convert to target languages
+- **Summarization**: Generate concise summaries
+- **Topic Extraction**: Identify key themes
+- **Action Items**: Extract tasks and decisions
+
+## Processing Modes
+
+### Batch Processing
+
+For uploaded files:
+- Optimized for throughput
+- Parallel chunk processing
+- Higher accuracy models
+- Complete file analysis
+
+### Stream Processing
+
+For live audio:
+- Optimized for latency
+- Sequential processing
+- Real-time feedback
+- Progressive results
+
+### Hybrid Processing
+
+For meetings:
+- Stream during meeting
+- Batch after completion
+- Best of both modes
+- Maximum accuracy
+
+## Pipeline Configuration
+
+### Model Selection
+
+Choose models based on requirements:
+
+```python
+# High accuracy (slower)
+config = {
+    "transcription_model": "whisper-large-v3",
+    "diarization_model": "pyannote-3.1",
+    "translation_model": "seamless-m4t-large"
+}
+
+# Balanced (default)
+config = {
+    "transcription_model": "whisper-base",
+    "diarization_model": "pyannote-3.1",
+    "translation_model": "seamless-m4t-medium"
+}
+
+# Fast processing
+config = {
+    "transcription_model": "whisper-tiny",
+    "diarization_model": "pyannote-3.1-fast",
+    "translation_model": "seamless-m4t-small"
+}
+```
+
+### Processing Options
+
+Customize pipeline behavior:
+
+```yaml
+# Parallel processing
+max_parallel_chunks: 10
+chunk_size_seconds: 30
+chunk_overlap_seconds: 1
+
+# Quality settings
+enable_noise_reduction: true
+enable_normalization: true
+min_speech_confidence: 0.5
+
+# Post-processing
+enable_translation: true
+target_languages: ["es", "fr", "de"]
+enable_summarization: true
+summary_length: "medium"
+```
+
+## Performance Characteristics
+
+### Processing Times
+
+For 1 hour of audio:
+
+| Pipeline Config | Processing Time | Accuracy |
+|----------------|-----------------|----------|
+| Fast | 2-3 minutes | 85-90% |
+| Balanced | 5-8 minutes | 92-95% |
+| High Accuracy | 15-20 minutes | 95-98% |
+
+### Resource Usage
+
+| Component | CPU Usage | Memory | GPU |
+|-----------|-----------|---------|-----|
+| Transcription | Medium | 2-4 GB | Required |
+| Diarization | High | 4-8 GB | Required |
+| Translation | Low | 2-3 GB | Optional |
+| Post-processing | Low | 1-2 GB | Not needed |
+
+## Pipeline Orchestration
+
+### Celery Task Chain
+
+The pipeline is orchestrated using Celery:
+
+```python
+chain = (
+    chunk_audio.s(audio_id) |
+    group(transcribe_chunk.s(chunk) for chunk in chunks) |
+    merge_transcriptions.s() |
+    diarize_audio.s() |
+    align_speakers.s() |
+    post_process.s()
+)
+```
+
+### Error Handling
+
+Error recovery:
+- **Automatic Retry**: Failed tasks retry up to 3 times
+- **Partial Recovery**: Continue with successful chunks
+- **Fallback Models**: Use alternative models on failure
+- **Error Reporting**: Detailed error messages
+
+### Progress Tracking
+
+Real-time progress updates:
+- **Chunk Progress**: Track individual chunk processing
+- **Overall Progress**: Percentage completion
+- **ETA Calculation**: Estimated completion time
+- **WebSocket Updates**: Live progress to clients
+
+## Optimization Strategies
+
+### GPU Utilization
+
+Maximize GPU efficiency:
+- **Batch Processing**: Process multiple chunks together
+- **Model Caching**: Keep models loaded in memory
+- **Dynamic Batching**: Adjust batch size based on GPU memory
+- **Multi-GPU Support**: Distribute across available GPUs
+
+### Memory Management
+
+Efficient memory usage:
+- **Streaming Processing**: Process large files in chunks
+- **Garbage Collection**: Clean up after each chunk
+- **Memory Limits**: Prevent out-of-memory errors
+- **Disk Caching**: Use disk for large intermediate results
+
+### Network Optimization
+
+Minimize network overhead:
+- **Compression**: Compress audio before transfer
+- **CDN Integration**: Use CDN for static assets
+- **Connection Pooling**: Reuse network connections
+- **Parallel Uploads**: Multiple concurrent uploads
+
+## Quality Assurance
+
+### Accuracy Metrics
+
+Monitor processing quality:
+- **Word Error Rate (WER)**: Transcription accuracy
+- **Diarization Error Rate (DER)**: Speaker identification accuracy
+- **Translation BLEU Score**: Translation quality
+- **Summary Coherence**: Summary quality metrics
+
+### Validation Steps
+
+Ensure output quality:
+- **Confidence Thresholds**: Filter low-confidence segments
+- **Consistency Checks**: Verify timeline consistency
+- **Language Validation**: Ensure correct language detection
+- **Format Validation**: Check output format compliance
+
+## Advanced Features
+
+### Custom Models
+
+Use your own models:
+- **Fine-tuned Whisper**: Domain-specific models
+- **Custom Diarization**: Trained on your speakers
+- **Specialized Post-processing**: Industry-specific formatting
+
+### Pipeline Extensions
+
+Add custom processing steps:
+- **Sentiment Analysis**: Analyze emotional tone
+- **Entity Extraction**: Identify people, places, organizations
+- **Custom Metrics**: Calculate domain-specific metrics
+- **Integration Hooks**: Call external services

docs/docs/installation/authentik-setup.md

@@ -0,0 +1,7 @@
+---
+title: authentik setup
+---
+
+# authentik setup
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/installation/aws-setup.md

@@ -0,0 +1,7 @@
+---
+title: aws setup
+---
+
+# aws setup
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/installation/docker-setup.md

@@ -0,0 +1,23 @@
+---
+sidebar_position: 3
+title: Docker Deployment
+---
+
+# Docker Deployment
+
+See the [Docker directory](https://github.com/monadical-sas/reflector/tree/main/docker) in the repository for the complete Docker deployment configuration.
+
+## Quick Start
+
+1. Clone the repository
+2. Navigate to `/docker` directory
+3. Copy `.env.example` to `.env`
+4. Configure environment variables
+5. Run `docker compose up -d`
+
+## Configuration
+
+Check the repository for:
+- `docker-compose.yml` - Service definitions
+- `.env.example` - Environment variables
+- `Caddyfile` - Reverse proxy configuration

docs/docs/installation/modal-setup.md

@@ -0,0 +1,7 @@
+---
+title: modal setup
+---
+
+# modal setup
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/installation/overview.md

@@ -0,0 +1,162 @@
+---
+sidebar_position: 1
+title: Installation Overview
+---
+
+# Installation Overview
+
+Reflector is designed for self-hosted deployment, giving you complete control over your infrastructure and data.
+
+## Deployment Options
+
+### Docker Deployment (Recommended)
+
+The easiest way to deploy Reflector:
+- Pre-configured containers
+- Automated dependency management
+- Consistent environment
+- Easy updates
+
+### Manual Installation
+
+For custom deployments:
+- Greater control over configuration
+- Integration with existing infrastructure
+- Custom optimization options
+- Development environments
+
+## Requirements
+
+### System Requirements
+
+**Minimum Requirements:**
+- CPU: 4 cores
+- RAM: 8 GB
+- Storage: 50 GB
+- OS: Ubuntu 20.04+ or similar Linux
+
+**Recommended Requirements:**
+- CPU: 8+ cores
+- RAM: 16 GB
+- Storage: 100 GB SSD
+- GPU: NVIDIA GPU with 8GB+ VRAM (for local processing)
+
+### Network Requirements
+
+- Public IP address (for WebRTC)
+- Ports: 80, 443, 8000, 3000
+- Domain name (for SSL)
+- SSL certificate (Let's Encrypt supported)
+
+## Required Services
+
+### Core Services
+
+These services are required for basic operation:
+
+1. **PostgreSQL** - Primary database
+2. **Redis** - Message broker and cache
+3. **Docker** - Container runtime
+
+### GPU Processing
+
+Choose one:
+- **Modal.com** - Serverless GPU (recommended)
+- **Local GPU** - Self-hosted GPU processing
+
+### Optional Services
+
+Enhance functionality with:
+- **AWS S3** - Long-term storage
+- **Whereby** - Video conferencing rooms
+- **Authentik** - Enterprise authentication
+- **Zulip** - Chat integration
+
+## Quick Start
+
+### Using Docker Compose
+
+1. Clone the repository:
+```bash
+git clone https://github.com/monadical-sas/reflector.git
+cd reflector
+```
+
+2. Navigate to docker directory:
+```bash
+cd docker
+```
+
+3. Copy and configure environment:
+```bash
+cp .env.example .env
+# Edit .env with your settings
+```
+
+4. Start services:
+```bash
+docker compose up -d
+```
+
+5. Access Reflector:
+- Frontend: https://your-domain.com
+- API: https://your-domain.com/api
+
+## Configuration Overview
+
+### Essential Configuration
+
+```env
+# Database
+DATABASE_URL=postgresql://user:pass@localhost/reflector
+
+# Redis
+REDIS_URL=redis://localhost:6379
+
+# Modal.com (for GPU processing)
+TRANSCRIPT_MODAL_API_KEY=your-key
+DIARIZATION_MODAL_API_KEY=your-key
+
+# Domain
+DOMAIN=your-domain.com
+```
+
+### Security Configuration
+
+```env
+# Authentication
+REFLECTOR_AUTH_BACKEND=jwt
+NEXTAUTH_SECRET=generate-strong-secret
+
+# SSL (handled by Caddy)
+# Automatic with Let's Encrypt
+```
+
+## Service Architecture
+
+```mermaid
+graph TD
+    A[Caddy Reverse Proxy] --> B[Frontend - Next.js]
+    A --> C[Backend - FastAPI]
+    C --> D[PostgreSQL]
+    C --> E[Redis]
+    C --> F[Celery Workers]
+    F --> G[Modal.com GPU]
+```
+
+## Next Steps
+
+1. **Review Requirements**: [System Requirements](./requirements)
+2. **Docker Setup**: [Docker Deployment Guide](./docker-setup)
+3. **Configure Services**:
+   - [Modal.com Setup](./modal-setup)
+   - [Whereby Setup](./whereby-setup)
+   - [AWS S3 Setup](./aws-setup)
+4. **Optional Services**:
+   - [Authentik Setup](./authentik-setup)
+   - [Zulip Setup](./zulip-setup)
+
+## Getting Help
+
+- [GitHub Issues](https://github.com/monadical-sas/reflector/issues)
+- [Community Discord](#)

docs/docs/installation/requirements.md

@@ -0,0 +1,29 @@
+---
+sidebar_position: 2
+title: System Requirements
+---
+
+# System Requirements
+
+## Minimum Requirements
+
+- **CPU**: 4 cores
+- **RAM**: 8 GB
+- **Storage**: 50 GB SSD
+- **OS**: Ubuntu 20.04+ or compatible Linux
+- **Network**: Public IP address
+
+## Recommended Requirements
+
+- **CPU**: 8+ cores
+- **RAM**: 16 GB
+- **Storage**: 100 GB SSD
+- **GPU**: NVIDIA GPU with 8GB+ VRAM (for local processing)
+- **Network**: 1 Gbps connection
+
+## Software Requirements
+
+- Docker Engine 20.10+
+- Docker Compose 2.0+
+- Node.js 18+ (for frontend development)
+- Python 3.11+ (for backend development)

docs/docs/installation/whereby-setup.md

@@ -0,0 +1,7 @@
+---
+title: whereby setup
+---
+
+# whereby setup
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/installation/zulip-setup.md

@@ -0,0 +1,7 @@
+---
+title: zulip setup
+---
+
+# zulip setup
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/intro.md

@@ -0,0 +1,61 @@
+---
+sidebar_position: 1
+title: Introduction
+---
+
+# Welcome to Reflector
+
+Reflector is a privacy-focused, self-hosted AI-powered audio transcription and meeting analysis platform that provides real-time transcription, speaker diarization, translation, and summarization for audio content and live meetings. With complete control over your data and infrastructure, you can run models on your own hardware (roadmap - currently supports Modal.com for GPU processing).
+
+## What is Reflector?
+
+Reflector is a web application that utilizes AI to process audio content, providing:
+
+- **Real-time Transcription**: Convert speech to text using [Whisper](https://github.com/openai/whisper) (multi-language) or [Parakeet](https://github.com/NVIDIA/NeMo) (English) models
+- **Speaker Diarization**: Identify and label different speakers using [Pyannote](https://github.com/pyannote/pyannote-audio) 3.1
+- **Live Translation**: Translate audio content in real-time to 100+ languages with [Facebook Seamless-M4T](https://github.com/facebookresearch/seamless_communication)
+- **Topic Detection & Summarization**: Extract key topics and generate concise summaries using LLMs
+- **Meeting Recording**: Create permanent records of meetings with searchable transcripts
+
+## Features
+
+| Feature | Public Mode | Private Mode |
+|---------|------------|--------------|
+| **Authentication** | None required | Required |
+| **Audio Upload** | ✅ | ✅ |
+| **Live Microphone Streaming** | ✅ | ✅ |
+| **Transcription** | ✅ | ✅ |
+| **Speaker Diarization** | ✅ | ✅ |
+| **Translation** | ✅ | ✅ |
+| **Topic Detection** | ✅ | ✅ |
+| **Summarization** | ✅ | ✅ |
+| **Virtual Meeting Rooms (Whereby)** | ❌ | ✅ |
+| **Browse Transcripts Page** | ❌ | ✅ |
+| **Search Functionality** | ❌ | ✅ |
+| **Persistent Storage** | ❌ | ✅ |
+
+## Architecture Overview
+
+Reflector consists of three main components:
+
+- **Frontend**: React application built with Next.js 14
+- **Backend**: Python server using FastAPI
+- **Processing**: Scalable GPU workers for ML inference (Modal.com or local)
+
+## Getting Started
+
+Ready to deploy Reflector? Head over to our [Installation Guide](./installation/overview) to set up your own instance.
+
+For a quick overview of how Reflector processes audio, check out our [Pipeline Documentation](./pipelines/overview).
+
+## Open Source
+
+Reflector is open source software developed by [Monadical](https://monadical.com) and licensed under the **MIT License**. We welcome contributions from the community!
+
+- [GitHub Repository](https://github.com/monadical-sas/reflector)
+- [Issue Tracker](https://github.com/monadical-sas/reflector/issues)
+- [Pull Requests](https://github.com/monadical-sas/reflector/pulls)
+
+## Support
+
+Need help? Reach out to the community through GitHub Discussions.

docs/docs/pipelines/file-pipeline.md

@@ -0,0 +1,348 @@
+---
+sidebar_position: 2
+title: File Processing Pipeline
+---
+
+# File Processing Pipeline
+
+The file processing pipeline handles uploaded audio files, optimizing for accuracy and throughput.
+
+## Pipeline Stages
+
+### 1. Input Stage
+
+**Accepted Formats:**
+- MP3 (most common)
+- WAV (uncompressed)
+- M4A (Apple format)
+- WebM (browser recordings)
+- MP4 (video with audio track)
+
+**File Validation:**
+- Maximum size: 2GB (configurable)
+- Minimum duration: 5 seconds
+- Maximum duration: 6 hours
+- Sample rate: Any (will be resampled)
+
+### 2. Pre-processing
+
+**Audio Normalization:**
+```python
+# Convert to standard format
+- Sample rate: 16kHz (Whisper requirement)
+- Channels: Mono
+- Bit depth: 16-bit
+- Format: WAV
+```
+
+**Volume Normalization:**
+- Target: -23 LUFS (broadcast standard)
+- Prevents clipping
+- Improves transcription accuracy
+
+**Noise Reduction (Optional):**
+- Background noise removal
+- Echo cancellation
+- High-pass filter for rumble
+
+### 3. Chunking Strategy
+
+**Default Configuration:**
+```yaml
+chunk_size: 30  # seconds
+overlap: 1      # seconds
+max_parallel: 10
+silence_detection: true
+```
+
+**Chunking with Silence Detection:**
+- Detects silence periods
+- Attempts to break at natural pauses
+- Maintains context with overlap
+- Preserves sentence boundaries
+
+**Chunk Metadata:**
+```json
+{
+  "chunk_id": "chunk_001",
+  "start_time": 0.0,
+  "end_time": 30.0,
+  "duration": 30.0,
+  "has_speech": true,
+  "audio_hash": "sha256:..."
+}
+```
+
+### 4. Transcription Processing
+
+**Whisper Models:**
+
+| Model | Size | Speed | Accuracy | Use Case |
+|-------|------|-------|----------|----------|
+| tiny | 39M | Very Fast | 85% | Quick drafts |
+| base | 74M | Fast | 89% | Good balance |
+| small | 244M | Medium | 91% | Better accuracy |
+| medium | 769M | Slow | 93% | High quality |
+| large-v3 | 1550M | Very Slow | 96% | Best quality |
+
+**Processing Configuration:**
+```python
+transcription_config = {
+    "model": "whisper-base",
+    "language": "auto",  # or specify: "en", "es", etc.
+    "task": "transcribe",  # or "translate"
+    "temperature": 0,  # deterministic
+    "compression_ratio_threshold": 2.4,
+    "no_speech_threshold": 0.6,
+    "condition_on_previous_text": True,
+    "initial_prompt": None,  # optional context
+}
+```
+
+**Parallel Processing:**
+- Each chunk processed independently
+- GPU batching for efficiency
+- Automatic load balancing
+- Failure isolation
+
+### 5. Diarization (Speaker Identification)
+
+**Pyannote 3.1 Pipeline:**
+
+1. **Voice Activity Detection (VAD)**
+   - Identifies speech segments
+   - Filters out silence and noise
+   - Precision: 95%+
+
+2. **Speaker Embedding**
+   - Extracts voice characteristics
+   - 256-dimensional vectors
+   - Speaker-invariant features
+
+3. **Clustering**
+   - Groups similar voice embeddings
+   - Agglomerative clustering
+   - Automatic speaker count detection
+
+4. **Segmentation**
+   - Assigns speaker labels to time segments
+   - Handles overlapping speech
+   - Minimum segment duration: 0.5s
+
+**Configuration:**
+```python
+diarization_config = {
+    "min_speakers": 1,
+    "max_speakers": 10,
+    "min_duration": 0.5,
+    "clustering": "AgglomerativeClustering",
+    "embedding_model": "speechbrain/spkrec-ecapa-voxceleb",
+}
+```
+
+### 6. Alignment & Merging
+
+**Chunk Assembly:**
+```python
+# Merge overlapping segments
+for chunk in chunks:
+    # Remove overlap duplicates
+    if chunk.start < previous.end:
+        chunk.text = resolve_overlap(previous, chunk)
+
+    # Maintain timeline
+    merged_transcript.append(chunk)
+```
+
+**Speaker Alignment:**
+- Map diarization timeline to transcript
+- Resolve speaker changes mid-sentence
+- Handle multiple speakers per segment
+
+**Quality Checks:**
+- Timeline consistency
+- No gaps in transcript
+- Speaker label continuity
+- Confidence score validation
+
+### 7. Post-processing Chain
+
+**Text Formatting:**
+- Sentence capitalization
+- Punctuation restoration
+- Number formatting
+- Acronym detection
+
+**Translation (Optional):**
+```python
+translation_config = {
+    "model": "facebook/seamless-m4t-medium",
+    "source_lang": "auto",
+    "target_langs": ["es", "fr", "de"],
+    "preserve_formatting": True
+}
+```
+
+**Topic Detection:**
+- LLM-based analysis
+- Extract 3-5 key topics
+- Keyword extraction
+- Entity recognition
+
+**Summarization:**
+```python
+summary_config = {
+    "model": "openai-compatible",
+    "max_length": 500,
+    "style": "bullets",  # or "paragraph"
+    "include_action_items": True,
+    "include_decisions": True
+}
+```
+
+### 8. Storage & Delivery
+
+**Database Storage:**
+```sql
+-- Main transcript record
+INSERT INTO transcripts (
+    id, title, duration, language,
+    transcript_text, transcript_json,
+    speakers, topics, summary,
+    created_at, processing_time
+) VALUES (...);
+
+-- Processing metadata
+INSERT INTO processing_metadata (
+    transcript_id, model_versions,
+    chunk_count, total_chunks,
+    error_count, warnings
+) VALUES (...);
+```
+
+**File Storage:**
+- Original audio: S3 (optional)
+- Processed chunks: Temporary (24h)
+- Transcript exports: JSON, SRT, VTT, TXT
+
+**Notification:**
+```json
+{
+  "type": "webhook",
+  "url": "https://your-app.com/webhook",
+  "payload": {
+    "transcript_id": "...",
+    "status": "completed",
+    "duration": 3600,
+    "processing_time": 180
+  }
+}
+```
+
+## Processing Times
+
+**Estimated times for 1 hour of audio:**
+
+| Component | Fast Mode | Balanced | High Quality |
+|-----------|-----------|----------|--------------|
+| Pre-processing | 10s | 10s | 10s |
+| Transcription | 60s | 180s | 600s |
+| Diarization | 30s | 60s | 120s |
+| Post-processing | 20s | 30s | 60s |
+| **Total** | **2 min** | **5 min** | **13 min** |
+
+## Error Handling
+
+### Retry Strategy
+
+```python
+@celery.task(
+    bind=True,
+    max_retries=3,
+    default_retry_delay=60,
+    retry_backoff=True
+)
+def process_chunk(self, chunk_id):
+    try:
+        # Process chunk
+        result = transcribe(chunk_id)
+    except Exception as exc:
+        # Exponential backoff
+        raise self.retry(exc=exc)
+```
+
+### Partial Recovery
+
+- Continue with successful chunks
+- Mark failed chunks in output
+- Provide partial transcript
+- Report processing issues
+
+### Fallback Options
+
+1. **Model Fallback:**
+   - If large model fails, try medium
+   - If GPU fails, try CPU
+   - If Modal fails, try local
+
+2. **Quality Degradation:**
+   - Reduce chunk size
+   - Disable post-processing
+   - Skip diarization if needed
+
+## Optimization Tips
+
+### For Speed
+
+1. Use smaller models (tiny/base)
+2. Increase parallel chunks
+3. Disable diarization
+4. Skip post-processing
+5. Use GPU acceleration
+
+### For Accuracy
+
+1. Use larger models (medium/large)
+2. Enable all pre-processing
+3. Reduce chunk size
+4. Enable silence detection
+5. Multiple pass processing
+
+### For Cost
+
+1. Use Modal spot instances
+2. Batch multiple files
+3. Cache common phrases
+4. Optimize chunk size
+5. Selective post-processing
+
+## Monitoring
+
+### Metrics to Track
+
+```python
+metrics = {
+    "processing_time": histogram,
+    "chunk_success_rate": gauge,
+    "model_accuracy": histogram,
+    "queue_depth": gauge,
+    "gpu_utilization": gauge,
+    "cost_per_hour": counter
+}
+```
+
+### Quality Metrics
+
+- Word Error Rate (WER)
+- Diarization Error Rate (DER)
+- Confidence scores
+- Processing speed
+- User feedback
+
+### Alerts
+
+- Processing time > 30 minutes
+- Error rate > 5%
+- Queue depth > 100
+- GPU memory > 90%
+- Cost spike detected

docs/docs/pipelines/live-pipeline.md

@@ -0,0 +1,7 @@
+---
+title: live pipeline
+---
+
+# live pipeline
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/pipelines/overview.md

@@ -0,0 +1,7 @@
+---
+title: overview
+---
+
+# overview
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/api.md

@@ -0,0 +1,448 @@
+---
+title: API Reference
+---
+
+# API Reference
+
+The Reflector API provides a comprehensive RESTful interface for audio transcription, meeting management, and real-time streaming capabilities.
+
+## Base URL
+
+```
+http://localhost:8000/v1
+```
+
+All API endpoints are prefixed with `/v1/` for versioning.
+
+## Authentication
+
+Reflector supports multiple authentication modes:
+
+- **No Authentication** (Public Mode): Basic transcription and upload functionality
+- **JWT Authentication** (Private Mode): Full feature access including meeting rooms and persistent storage
+- **OAuth/OIDC via Authentik**: Enterprise single sign-on integration
+
+## Core Endpoints
+
+### Transcripts
+
+Manage audio transcriptions and their associated metadata.
+
+#### List Transcripts
+```http
+GET /v1/transcripts/
+```
+
+Returns a paginated list of transcripts with filtering options.
+
+#### Create Transcript
+```http
+POST /v1/transcripts/
+```
+
+Create a new transcript from uploaded audio or initialize for streaming.
+
+#### Get Transcript
+```http
+GET /v1/transcripts/{transcript_id}
+```
+
+Retrieve detailed information about a specific transcript.
+
+#### Update Transcript
+```http
+PATCH /v1/transcripts/{transcript_id}
+```
+
+Update transcript metadata, summary, or processing status.
+
+#### Delete Transcript
+```http
+DELETE /v1/transcripts/{transcript_id}
+```
+
+Remove a transcript and its associated data.
+
+### Audio Processing
+
+#### Upload Audio
+```http
+POST /v1/transcripts_audio/{transcript_id}/upload
+```
+
+Upload an audio file for transcription processing.
+
+**Supported formats:**
+- WAV, MP3, M4A, FLAC, OGG
+- Maximum file size: 500MB
+- Sample rates: 8kHz - 48kHz
+
+#### Download Audio
+```http
+GET /v1/transcripts_audio/{transcript_id}/download
+```
+
+Download the original or processed audio file.
+
+#### Stream Audio
+```http
+GET /v1/transcripts_audio/{transcript_id}/stream
+```
+
+Stream audio content with range support for progressive playback.
+
+### WebRTC Streaming
+
+Real-time audio streaming via WebRTC for live transcription.
+
+#### Initialize WebRTC Session
+```http
+POST /v1/transcripts_webrtc/{transcript_id}/offer
+```
+
+Create a WebRTC offer for establishing a peer connection.
+
+#### Complete WebRTC Handshake
+```http
+POST /v1/transcripts_webrtc/{transcript_id}/answer
+```
+
+Submit the WebRTC answer to complete connection setup.
+
+### WebSocket Streaming
+
+Real-time updates and live transcription via WebSocket.
+
+#### WebSocket Endpoint
+```ws
+ws://localhost:8000/v1/transcripts_websocket/{transcript_id}
+```
+
+Receive real-time transcription updates, speaker changes, and processing status.
+
+**Message Types:**
+- `transcription`: New transcribed text segments
+- `diarization`: Speaker identification updates
+- `status`: Processing status changes
+- `error`: Error notifications
+
+### Meetings
+
+Manage virtual meeting rooms and recordings.
+
+#### List Meetings
+```http
+GET /v1/meetings/
+```
+
+Get all meetings for the authenticated user.
+
+#### Create Meeting
+```http
+POST /v1/meetings/
+```
+
+Initialize a new meeting room with Whereby integration.
+
+#### Join Meeting
+```http
+POST /v1/meetings/{meeting_id}/join
+```
+
+Join an existing meeting and start recording.
+
+#### End Meeting
+```http
+POST /v1/meetings/{meeting_id}/end
+```
+
+End the meeting and finalize the recording.
+
+### Rooms
+
+Virtual meeting room configuration and management.
+
+#### List Rooms
+```http
+GET /v1/rooms/
+```
+
+Get available meeting rooms.
+
+#### Create Room
+```http
+POST /v1/rooms/
+```
+
+Create a new persistent meeting room.
+
+#### Update Room Settings
+```http
+PATCH /v1/rooms/{room_id}
+```
+
+Modify room configuration and permissions.
+
+## Response Formats
+
+### Success Response
+```json
+{
+  "id": "uuid",
+  "created_at": "2025-01-20T10:00:00Z",
+  "updated_at": "2025-01-20T10:30:00Z",
+  "data": {...}
+}
+```
+
+### Error Response
+```json
+{
+  "error": {
+    "code": "ERROR_CODE",
+    "message": "Human-readable error message",
+    "details": {...}
+  }
+}
+```
+
+### Status Codes
+
+- `200 OK`: Successful request
+- `201 Created`: Resource created successfully
+- `204 No Content`: Successful deletion
+- `400 Bad Request`: Invalid request parameters
+- `401 Unauthorized`: Authentication required
+- `403 Forbidden`: Insufficient permissions
+- `404 Not Found`: Resource not found
+- `409 Conflict`: Resource conflict
+- `422 Unprocessable Entity`: Validation error
+- `429 Too Many Requests`: Rate limit exceeded
+- `500 Internal Server Error`: Server error
+
+## Rate Limiting
+
+- **Anonymous users**: 100 requests per minute
+- **Authenticated users**: 1000 requests per minute
+- **WebSocket connections**: 10 concurrent per user
+- **File uploads**: 10 per hour for anonymous, 100 per hour for authenticated
+
+## WebSocket Protocol
+
+The WebSocket connection provides real-time updates during transcription processing. The server sends structured messages to communicate different events and data updates.
+
+### Connection
+```javascript
+const ws = new WebSocket('ws://localhost:8000/v1/transcripts_websocket/{transcript_id}');
+```
+
+### Message Types and Formats
+
+#### Transcription Update
+Sent when new text is transcribed from the audio stream.
+```json
+{
+  "type": "transcription",
+  "data": {
+    "text": "The transcribed text segment",
+    "speaker": "Speaker 1",
+    "timestamp": 1705745623.456,
+    "confidence": 0.95,
+    "segment_id": "seg_001",
+    "is_final": true
+  }
+}
+```
+
+#### Diarization Update
+Sent when speaker changes are detected or speaker labels are updated.
+```json
+{
+  "type": "diarization",
+  "data": {
+    "speaker": "Speaker 2",
+    "speaker_id": "spk_002",
+    "start_time": 1705745620.123,
+    "end_time": 1705745625.456,
+    "confidence": 0.87
+  }
+}
+```
+
+#### Processing Status
+Sent to indicate changes in the processing pipeline status.
+```json
+{
+  "type": "status",
+  "data": {
+    "status": "processing",
+    "stage": "transcription",
+    "progress": 45.5,
+    "message": "Processing audio chunk 12 of 26"
+  }
+}
+```
+
+Status values:
+- `initializing`: Setting up processing pipeline
+- `processing`: Active transcription/diarization
+- `completed`: Processing finished successfully
+- `failed`: Processing encountered an error
+- `paused`: Processing temporarily suspended
+
+#### Summary Update
+Sent when AI-generated summaries or topics are available.
+```json
+{
+  "type": "summary",
+  "data": {
+    "summary": "Brief summary of the conversation",
+    "topics": ["topic1", "topic2", "topic3"],
+    "action_items": ["action 1", "action 2"],
+    "key_points": ["point 1", "point 2"]
+  }
+}
+```
+
+#### Error Messages
+Sent when errors occur during processing.
+```json
+{
+  "type": "error",
+  "data": {
+    "code": "AUDIO_FORMAT_ERROR",
+    "message": "Unsupported audio format",
+    "details": {
+      "format": "unknown",
+      "sample_rate": 0
+    },
+    "recoverable": false
+  }
+}
+```
+
+#### Heartbeat/Keepalive
+Sent periodically to maintain the connection.
+```json
+{
+  "type": "ping",
+  "data": {
+    "timestamp": 1705745630.000
+  }
+}
+```
+
+### Client-to-Server Messages
+
+Clients can send control messages to the server:
+
+#### Start/Resume Processing
+```json
+{
+  "action": "start",
+  "params": {}
+}
+```
+
+#### Pause Processing
+```json
+{
+  "action": "pause",
+  "params": {}
+}
+```
+
+#### Request Status
+```json
+{
+  "action": "get_status",
+  "params": {}
+}
+```
+
+## OpenAPI Specification
+
+The complete OpenAPI 3.0 specification is available at:
+
+```
+http://localhost:8000/v1/openapi.json
+```
+
+You can import this specification into tools like:
+- Postman
+- Insomnia
+- Swagger UI
+- OpenAPI Generator (for client SDK generation)
+
+## SDK Support
+
+While Reflector doesn't provide official SDKs, you can generate client libraries using the OpenAPI specification with tools like:
+
+- **Python**: `openapi-python-client`
+- **TypeScript**: `openapi-typescript-codegen`
+- **Go**: `oapi-codegen`
+- **Java**: `openapi-generator`
+
+## Example Usage
+
+### Python Example
+```python
+import requests
+
+# Upload and transcribe audio
+with open('meeting.mp3', 'rb') as f:
+    response = requests.post(
+        'http://localhost:8000/v1/transcripts/',
+        files={'file': f}
+    )
+    transcript_id = response.json()['id']
+
+# Check transcription status
+status = requests.get(
+    f'http://localhost:8000/v1/transcripts/{transcript_id}'
+).json()
+
+print(f"Transcription status: {status['status']}")
+```
+
+### JavaScript WebSocket Example
+```javascript
+// Connect to WebSocket for real-time transcription updates
+const ws = new WebSocket(`ws://localhost:8000/v1/transcripts_websocket/${transcriptId}`);
+
+ws.onopen = () => {
+    console.log('Connected to transcription WebSocket');
+};
+
+ws.onmessage = (event) => {
+    const message = JSON.parse(event.data);
+
+    switch(message.type) {
+        case 'transcription':
+            console.log(`[${message.data.speaker}]: ${message.data.text}`);
+            break;
+        case 'diarization':
+            console.log(`Speaker change: ${message.data.speaker}`);
+            break;
+        case 'status':
+            console.log(`Status: ${message.data.status}`);
+            break;
+        case 'error':
+            console.error(`Error: ${message.data.message}`);
+            break;
+    }
+};
+
+ws.onerror = (error) => {
+    console.error('WebSocket error:', error);
+};
+
+ws.onclose = () => {
+    console.log('WebSocket connection closed');
+};
+```
+
+## Need Help?
+
+- Review [example implementations](https://github.com/monadical-sas/reflector/tree/main/examples)
+- Open an issue on [GitHub](https://github.com/monadical-sas/reflector/issues)

docs/docs/reference/api/overview.md

@@ -0,0 +1,7 @@
+---
+title: overview
+---
+
+# overview
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/architecture/backend.md

@@ -0,0 +1,7 @@
+---
+title: backend
+---
+
+# backend
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/architecture/database.md

@@ -0,0 +1,7 @@
+---
+title: database
+---
+
+# database
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/architecture/frontend.md

@@ -0,0 +1,7 @@
+---
+title: frontend
+---
+
+# frontend
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/architecture/overview.md

@@ -0,0 +1,7 @@
+---
+title: overview
+---
+
+# overview
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/architecture/workers.md

@@ -0,0 +1,7 @@
+---
+title: workers
+---
+
+# workers
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/configuration.md

@@ -0,0 +1,7 @@
+---
+title: configuration
+---
+
+# configuration
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/processors/analysis.md

@@ -0,0 +1,7 @@
+---
+title: analysis
+---
+
+# analysis
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/processors/diarization.md

@@ -0,0 +1,7 @@
+---
+title: diarization
+---
+
+# diarization
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/processors/transcription.md

@@ -0,0 +1,7 @@
+---
+title: transcription
+---
+
+# transcription
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/reference/processors/translation.md

@@ -0,0 +1,7 @@
+---
+title: translation
+---
+
+# translation
+
+Documentation coming soon. See [TODO.md](/docs/TODO) for required information.

docs/docs/roadmap.md

@@ -0,0 +1,139 @@
+---
+sidebar_position: 100
+title: Roadmap
+---
+
+# Product Roadmap
+
+Our development roadmap for Reflector, focusing on expanding capabilities while maintaining privacy and performance.
+
+## Planned Features
+
+### 🌍 Multi-Language Support Enhancement
+
+**Current State:**
+- Whisper supports 99+ languages for transcription
+- Parakeet supports English only with high accuracy
+- Translation available to 100+ languages
+
+**Planned Improvements:**
+- Default language selection per room/user
+- Automatic language detection improvements
+- Multi-language diarization support
+- RTL (Right-to-Left) language UI support
+- Language-specific post-processing rules
+
+### 🏠 Self-Hosted Room Providers
+
+**Jitsi Integration**
+
+Moving beyond Whereby to support self-hosted video conferencing:
+
+- No API keys required
+- Complete control over video infrastructure
+- Custom branding and configuration
+- Lower operational costs
+- Enhanced privacy with self-hosted video
+
+**Implementation Plan:**
+- WebRTC bridge for Jitsi Meet
+- Room management API integration
+- Recording synchronization
+- Participant tracking
+
+### 📅 Calendar Integration
+
+**Planned Capabilities:**
+- Google Calendar synchronization
+- Microsoft Outlook integration
+- Automatic meeting room creation
+- Pre-meeting document preparation
+- Post-meeting transcript delivery
+- Recurring meeting support
+
+**Features:**
+- Auto-join scheduled meetings
+- Calendar-based access control
+- Meeting agenda import
+- Action item export to calendar
+
+### 🖥️ Self-Hosted GPU Service
+
+**For organizations with dedicated GPU hardware (H100, A100, RTX 4090):**
+
+**Docker GPU Worker Image:**
+- Self-contained processing service
+- CUDA 11/12 support
+- Pre-loaded models:
+  - Whisper (all sizes)
+  - Pyannote diarization
+  - Seamless-M4T translation
+- Automatic model management
+
+**Deployment Options:**
+- Kubernetes GPU operators
+- Docker Compose with nvidia-docker
+- Bare metal installation
+- Hybrid cloud/on-premise
+
+**Benefits:**
+- No Modal.com dependency
+- Complete data isolation
+- Predictable costs
+- Maximum performance
+- Custom model support
+
+## Future Considerations
+
+### Enhanced Analytics
+- Meeting insights dashboard
+- Speaker participation metrics
+- Topic trends over time
+- Team collaboration patterns
+
+### Advanced AI Features
+- Real-time sentiment analysis
+- Emotion detection
+- Meeting quality scores
+- Automated coaching suggestions
+
+### Integration Ecosystem
+- Slack/Teams notifications
+- CRM integration (Salesforce, HubSpot)
+- Project management tools (Jira, Asana)
+- Knowledge bases (Notion, Confluence)
+
+### Performance Improvements
+- WebAssembly for client-side processing
+- Edge computing support
+- 5G network optimization
+- Blockchain for transcript verification
+
+## Contributing
+
+We welcome community contributions! Areas where you can help:
+
+1. **Language Support**: Add support for your language
+2. **Integrations**: Connect with your favorite tools
+3. **Models**: Fine-tune models for specific domains
+4. **Documentation**: Improve guides and examples
+
+See our [Contributing Guide](https://github.com/monadical-sas/reflector/blob/main/CONTRIBUTING.md) for details.
+
+## Timeline
+
+We don't provide specific dates as development depends on community contributions and priorities. Features are generally released when they're ready and properly tested.
+
+## Feature Requests
+
+Have an idea for Reflector? We'd love to hear it!
+
+- [Open a GitHub Issue](https://github.com/monadical-sas/reflector/issues/new)
+- [Join our Discord](#)
+- [Email us](mailto:reflector@monadical.com)
+
+## Stay Updated
+
+- Watch our [GitHub repository](https://github.com/monadical-sas/reflector)
+- Follow our [blog](#)
+- Subscribe to our [newsletter](#)