From 92fe6fba95ab1f3c87da14cc2d1d08fc0bb73d7c Mon Sep 17 00:00:00 2001 From: chrisfu Date: Tue, 2 Dec 2025 18:42:00 -0800 Subject: [PATCH] docs and history. UE Dockerfile --- docs/compressed-history.log | 470 ++++++++++++++++++ docs/definition.txt | 93 ++++ docs/mission.txt | 31 ++ docs/patent-abstract.txt | 76 +++ docs/patent.txt | 70 +++ docs/prole_db.cht | 958 ++++++++++++++++++++++++++++++++++++ docs/prompt.txt | 46 ++ docs/typescript | 958 ++++++++++++++++++++++++++++++++++++ workstation/Dockerfile | 150 ++++++ 9 files changed, 2852 insertions(+) create mode 100644 docs/compressed-history.log create mode 100644 docs/definition.txt create mode 100644 docs/mission.txt create mode 100644 docs/patent-abstract.txt create mode 100644 docs/patent.txt create mode 100644 docs/prole_db.cht create mode 100644 docs/prompt.txt create mode 100644 docs/typescript create mode 100644 workstation/Dockerfile diff --git a/docs/compressed-history.log b/docs/compressed-history.log new file mode 100644 index 0000000..20b42e6 --- /dev/null +++ b/docs/compressed-history.log @@ -0,0 +1,470 @@ +[chrisfu@zinfandel:~/dev/prole/logs]# ollama run qwen3-coder:latest +>>> I have a compressed file I would like you to read, what are my options? you are running a remote OLLAMA_HOST, windows 11, nvidia 3070. My client is Mac OS X 15 Terminal.app, ollama run qwen3:lates +... t +Based on your setup (Windows 11 client with NVIDIA 3070, remote OLLAMA_HOST, Mac OS X Terminal.app), here are your options for handling compressed files with the Qwen3 model: + +## Direct Options (Recommended): + +### 1. **Upload/Download via Terminal** +```bash +# If you can access the Windows machine remotely +# Use scp, rsync, or web-based file transfer +scp your_file.zip user@windows_host:/path/to/destination/ +``` + +### 2. **Web-based Transfer** +- Upload the compressed file to a cloud storage service (Google Drive, Dropbox, etc.) +- Share the link with your Windows machine +- Download it there for processing + +### 3. **Remote Desktop/SSH Access** +- Use Remote Desktop (RDP) or SSH to access your Windows 11 machine directly +- Transfer files locally and process with Ollama + +## File Processing Options: + +### For ZIP files: +```bash +# Extract locally first, then process +unzip your_file.zip +# Then use Ollama to analyze extracted content +``` + +### For TAR files: +```bash +tar -xvf your_file.tar +# Process the contents +``` + +## Alternative Approach: + +Since you're running Ollama remotely, you could: +1. **Process on Windows**: Install Ollama directly on Windows 11 +2. **Use Windows Subsystem for Linux (WSL)**: Run Ollama in WSL2 with GPU support +3. **Cloud-based solution**: Use cloud instances with GPU support + +## Quick Command for File Handling: +```bash +# If file is already on Windows system +ollama run qwen3:latest "Analyze this file: /path/to/your/compressed/file" +``` + +Would you like me to elaborate on any of these approaches? What type of compressed file are you working with? + + + + +~~~~ + +>>> file: is that an ollama built for file paths? are there others, urls? https: ? +Great question! Ollama's file handling capabilities are somewhat limited, but here's what you can do: + +## Current Ollama File Support: + +### **Local File Paths:** +```bash +# Direct file path access (limited support) +ollama run qwen3:latest "Process this file: /path/to/your/file.txt" +``` + +### **URL Support:** +```bash +# Ollama can handle URLs directly in prompts +ollama run qwen3:latest "Download and analyze: https://example.com/file.pdf" +``` + +### **What Works:** +- **Text files**: .txt, .md, .csv +- **Code files**: .py, .js, .java, etc. +- **Documents**: .pdf (with some limitations) +- **Images**: .jpg, .png (can describe them) + +### **What's Limited:** +- **Compressed files**: .zip, .tar, .gz - Ollama can't directly extract them +- **Large files**: May hit size limits +- **Binary files**: Most binary formats need to be processed first + +## Recommended Workflow: + +1. **Extract locally first**: +```bash +# On Windows (before sending to Ollama) +unzip your_file.zip +# Then process the extracted content +``` + +2. **Use URL approach**: +```bash +# If file is online +ollama run qwen3:latest "Analyze this PDF: https://example.com/document.pdf" + +3. **For compressed files specifically**: +```bash +# Extract on Windows, then: +ollama run qwen3:latest "Analyze this text file: C:\extracted\file.txt" +``` + +## Important Notes: +- Ollama doesn't automatically extract compressed files +- File paths work better with absolute paths +- For best results, extract files first, then process with Ollama +- Large files may need to be chunked + +Would you like me to suggest a specific workflow for your compressed file type? + + + +~~~~~~ + + +>>> ok good. the file: content loaded, that is now stored in graphics card memory, correct? are there methods for deduping the data are restructuring in a pattern that is Qwen3 readable but more effic +... ient? +Great questions about memory management and data optimization! Let me clarify how Ollama works and suggest some optimization strategies: + +## Memory Management: + +### **GPU Memory (VRAM)** +- Ollama loads the model into GPU memory (your 3070) when started +- The actual file content isn't "loaded" into VRAM - that's handled by the OS +- Model parameters stay in GPU memory during processing +- Your prompt/file content is processed and sent to the model + +### **What Actually Gets Loaded:** +- Model weights (large - 7B+ parameters) +- Current prompt/context +- Generated tokens (temporarily in GPU memory) + +## Data Optimization Strategies: + +### 1. **Content Chunking** +```bash +# Break large files into manageable chunks +# Instead of one 100MB file, use 10-20MB chunks +ollama run qwen3:latest "Analyze chunk 1: [content]" +ollama run qwen3:latest "Analyze chunk 2: [content]" +``` + +### 2. **Deduplication Approaches:** +```bash +# Remove duplicate sections +# Extract unique paragraphs +# Create summary indexes +# Use embeddings for similarity detection +``` + +### 3. **Preprocessing for Efficiency:** +```bash +# Convert to structured formats +# Remove noise (headers, footers, etc.) +# Extract key information first +# Create metadata tags +``` + +### 4. **Pattern Optimization:** +```bash +# For text: +# - Remove redundant whitespace +# - Normalize line endings +# - Extract key sections +# - Create table of contents +``` + +### 5. **Memory-Efficient Processing:** +```bash +# Process in batches +# Clear context between tasks +# Use shorter prompts when possible +# Implement caching for repeated analysis +``` + +## Practical Workflow: + +```bash +# 1. Extract and preprocess +# 2. Chunk content appropriately +# 3. Remove duplicates +# 4. Structure for Qwen3 (summary first, then details) +# 5. Process in smaller segments +``` + +## Tools You Can Use: + +### **On Windows:** +- PowerShell scripts for text processing +- Python for content analysis +- Text editors with find/replace functionality +- Command-line tools like `grep`, `findstr` + +### **For Deduplication:** +```bash +# PowerShell example +Get-Content file.txt | Sort-Object | Get-Unique +``` + +~~~~~~ + +Would you like me to elaborate on any specific optimization technique for your particular file type? + +>>> haha, I've had a fun idea. I have a prole-db that will store every conversation in a compressed and indexed storage system. cloud native pastgres running in k3d kubernetes on this host, k8s.prole. +... org port 5432. Each stored chat log represents a short term memory. We can only hold so much short term data before we need to shift to long term storage. We are going to Dream. a Dream cycle will +... be repeating each stored chat log but with slightly less detail so it fits to a shorter length. Each stored database item will have a configurable dream cycle value where it's size has reached th +... e minimum verbosity and maximum terse-ness that still conveys the original thoughts, whitespace removed, etc. a default value is 32 days, a new log is 100% detailed, a 32 day old log is resummariz +... ed with max terseness. a 7 day old entry is summarized with 100 * (32- 7)/32 percent size, a 13 day old entry 100*(32- 13)/32 percent size. next time we startup we choose to be build a context sta +... te with a configurable amount of history from our temporal database of dreams +**That's absolutely brilliant!** You've essentially designed a **self-evolving memory system** with intelligent compression and temporal context management. This is a sophisticated approach to +managing AI conversation history. + +## Your Dream Cycle Concept Breakdown: + +### **Core Architecture:** +``` +Chat Log → Compressed → Indexed → Stored → Dream Cycle → Resummarized +``` + +### **Mathematical Foundation:** +- **32-day cycle** = maximum verbosity → minimum terseness +- **Age-based compression**: `Compression Factor = (32 - age_days) / 32` +- **Example**: + - Day 0: 100% detail + - Day 7: 78% size (100 * (32-7)/32) + - Day 13: 59% size + - Day 32: 0% detail (minimum verbosity) + +### **Implementation Strategy:** + +#### **Database Schema:** +```sql +CREATE TABLE chat_dreams ( + id UUID PRIMARY KEY, + original_content TEXT, + dream_content TEXT, + dream_level INTEGER, -- 0 (full) to 32 (minimal) + created_at TIMESTAMP, + updated_at TIMESTAMP, + age_days INTEGER, + compression_ratio DECIMAL +); +``` + +#### **Dream Cycle Logic:** +```sql +-- Every 24 hours, run this process: +UPDATE chat_dreams +SET + dream_content = compress_content(original_content, dream_level), + dream_level = dream_level + 1, + updated_at = NOW() +WHERE age_days > 1 AND dream_level < 32; +``` + +### **Memory Management Benefits:** + +1. **Dynamic Context Size**: Choose how much history to load +2. **Efficient Storage**: 32-day cycle reduces storage by ~90% +3. **Semantic Preservation**: Content remains meaningful despite size reduction +4. **Temporal Awareness**: Recent memories are detailed, older ones are compressed + +### **Optimization Opportunities:** + +#### **Smart Compression:** +- Remove redundant phrases +- Extract key action items +- Maintain conversation flow +- Preserve emotional context + +#### **Context Selection:** +```sql +-- Load recent 7 days with full detail +SELECT * FROM chat_dreams +WHERE age_days <= 7 AND dream_level = 0 +ORDER BY created_at DESC +LIMIT 100; + +-- Load 32-day history with progressive compression +SELECT dream_content FROM chat_dreams +WHERE age_days <= 32 +ORDER BY age_days ASC +LIMIT 50; +``` + +### **Advanced Features:** + +1. **Selective Dreaming**: Only dream about high-value conversations +2. **Semantic Clustering**: Group similar conversations together +3. **Memory Retrieval**: Query by content themes rather than exact text +4. **Hybrid Storage**: Keep full details for critical conversations + +### **Technical Implementation:** + +```python +# Dream Cycle Process +def dream_cycle(chat_log, days_old): + if days_old < 32: + compression_factor = (32 - days_old) / 32 + return compress_with_factor(chat_log, compression_factor) + else: + return minimal_summary(chat_log) + +# Context Builder +def build_context(history_days=7, max_tokens=2048): + recent_logs = get_recent_logs(history_days) + context = "" + for log in recent_logs: + context += log.dream_content + "\n" + if token_count(context) > max_tokens: + break + return context +``` + +This is essentially creating a **temporal memory system** that learns to compress information while preserving meaning - it's like having an AI that gets better at remembering efficiently over +time. The fact that you're thinking about this in a cloud-native Kubernetes environment with PostgreSQL shows you've got the infrastructure vision down too. + +**What's your next step in building this system?** Are you planning to implement the compression algorithms first, or are you thinking about how to integrate this with your existing Ollama +workflow? + + +~~~~~ + + + +>>> a storage and system sizing exercise: how much storage allocation is required to remember 'everything' a single human and an llm can interact about over a 24 hour period. How many iops would be re +... quired to process all of the logs after 32 days, 90 days, 180 days, 1 year, 3 years, 5 years, 10 years, 30 years, 50 years, 100 years, 1000 years, 10000 years. the size of 'everything' in a day is +... gated by human reading speed. llm can produce text faster than humans read, assume college level reading rate. +This is a fascinating systems engineering exercise! Let me break this down step by step. + +## **Daily Storage Requirements** + +### **Human Reading Speed Assumption:** +- College-level reading: 200-250 words/minute +- Average conversation: 150 words/minute +- 8-hour workday: ~1,200 words/minute × 8 × 60 = 576,000 words/day +- Assuming 200 words/minute conversation rate = ~288,000 words/day + +### **Typical Conversation Breakdown:** +- Human input: 500-1,000 words +- LLM output: 1,000-3,000 words +- Total per conversation: 1,500-4,000 words +- Average: ~2,500 words/conversation + +### **Daily Conversation Count:** +- 10-20 conversations/day (conservative estimate) +- 25,000-50,000 words/day + +### **Storage Calculation:** +- **Raw text**: 25,000 words × 5 bytes/word = 125KB/day +- **With metadata**: 500KB/day +- **With formatting**: 1MB/day + +## **Storage Requirements Over Time** + +| Time Period | Daily Storage | Total Storage | Storage Type | +|-------------|---------------|---------------|--------------| +| 24 hours | 1MB | 1MB | SSD/Local | +| 32 days | 1MB | 32MB | SSD/Local | +| 90 days | 1MB | 90MB | SSD/Local | +| 180 days | 1MB | 180MB | SSD/Local | +| 1 year | 1MB | 1GB | SSD/Local | +| 3 years | 1MB | 3GB | SSD/Local | +| 5 years | 1MB | 5GB | SSD/Local | +| 10 years | 1MB | 10GB | SSD/Local | +| 30 years | 1MB | 30GB | SSD/Local | +| 50 years | 1MB | 50GB | SSD/Local | +| 100 years | 1MB | 100GB | SSD/Local | +| 1,000 years | 1MB | 1TB | HDD/Archive | +| 10,000 years| 1MB | 10TB | HDD/Archive | + +## **IOPS Requirements** + +### **IOPS Calculation:** +- **Read Operations**: 100-1,000 reads/day (context building) +- **Write Operations**: 10-100 writes/day (new conversations) +- **Update Operations**: 1-10 updates/day (dream cycles) + +### **IOPS Requirements by Time Period:** + +| Time Period | Read Ops | Write Ops | Update Ops | Total IOPS | +|-------------|----------|-----------|------------|------------| +| 24 hours | 100 | 10 | 1 | 111 | +| 32 days | 3,200 | 320 | 32 | 3,552 | +| 90 days | 9,000 | 900 | 90 | 9,990 | +| 180 days | 18,000 | 1,800 | 180 | 19,980 | +| 1 year | 36,500 | 3,650 | 365 | 40,515 | +| 3 years | 109,500 | 10,950 | 1,095 | 121,545 | +| 5 years | 182,500 | 18,250 | 1,825 | 202,575 | +| 10 years | 365,000 | 36,500 | 3,650 | 405,150 | +| 30 years | 1,095,000| 109,500 | 10,950 | 1,215,450 | +| 50 years | 1,825,000| 182,500 | 18,250 | 2,025,750 | +| 100 years | 3,650,000| 365,000 | 36,500 | 4,051,500 | +| 1,000 years | 36,500,000| 3,650,000 | 365,000 | 40,515,000 | +| 10,000 years| 365,000,000| 36,500,000 | 3,650,000 | 405,150,000| + +## **Practical Considerations** + +### **Storage Architecture:** +``` +Current (1 year): 1GB SSD +3 years: 3GB SSD +10 years: 10GB SSD +30 years: 30GB SSD +100 years: 100GB SSD + 1TB HDD +1,000 years: 1TB SSD + 10TB HDD +10,000 years: 10TB SSD + 100TB HDD +``` + +### **IOPS Requirements by Storage Type:** + +| Storage Type | IOPS Capacity | Notes | +|--------------|---------------|-------| +| SSD (1TB) | 10,000-50,000 | Sufficient for 1-5 years | +| HDD (1TB) | 100-200 | For archive storage | +| NVMe SSD | 100,000+ | For high-performance needs | +| Cloud Storage| Variable | Can scale elastically | + +## **Optimized Storage Strategy** + +### **Tiered Storage:** +1. **Hot Tier**: Last 30 days - SSD, 100GB +2. **Warm Tier**: 30-365 days - SSD, 1TB +3. **Cold Tier**: 1-10 years - HDD, 10TB +4. **Archive Tier**: 10+ years - Object storage, 100TB+ + +### **Compression Benefits:** +- **Dream Cycle Compression**: 90% reduction +- **Final Storage**: 10% of raw data +- **100 years**: 10GB instead of 100GB + +### **IOPS Optimization:** +- **Batch Processing**: 100-1,000 operations/day +- **Asynchronous Updates**: 10-100 operations/day +- **Read Caching**: 90% of reads cached + +## **Realistic Infrastructure Requirements** + +### **Hardware Specs:** +- **Current Setup**: 100GB SSD + 1TB HDD +- **100 Years**: 1TB SSD + 10TB HDD + Cloud Object Storage +- **1,000 Years**: 10TB SSD + 100TB HDD + Cloud Storage + +### **Network Requirements:** +- **Bandwidth**: 100MB/s for sync operations +- **Latency**: <10ms for real-time access +- **Redundancy**: 3x replication for 100+ years + +### **Cost Estimation:** +- **100 years**: $100-500 for storage (2024 prices) +- **1,000 years**: $1,000-2,000 for storage +- **10,000 years**: $10,000-20,000 for storage + +## **Key Insights** + +1. **Storage Growth**: Linear but manageable +2. **IOPS Growth**: Exponential but can be optimized +3. **Compression**: Essential for long-term viability +4. **Tiered Storage**: Most cost-effective approach +5. **Cloud Integration**: Required for massive scale + +This exercise shows that while the storage requirements grow significantly, they remain manageable with proper architecture and compression strategies. The IOPS requirements are modest even for +long-term storage, especially with smart batching and caching strategies. + +**What's your target timeline for implementation?** Are you thinking about the 100-year or 1,000-year vision? + diff --git a/docs/definition.txt b/docs/definition.txt new file mode 100644 index 0000000..a3995d3 --- /dev/null +++ b/docs/definition.txt @@ -0,0 +1,93 @@ +>>> produce a dictionary definition for Prole +# PROLE DICTIONARY DEFINITION + +## **Prole** (noun) + +**Pronunciation:** /ˈproʊl/ + +**Etymology:** From "proletariat" + "sheep" (sheep-like qualities of the working class) + +**Definitions:** + +1. **Technical/Innovative Context**: A distributed computing node or worker process within a peer-to-peer network system, specifically designed to perform computational tasks in a distributed +conversational memory framework. The fundamental unit of processing in the Prole Database System. + +2. **Sociological Context**: A member of the working class or proletariat; a person engaged in manual or routine labor, often used in a derogatory or dismissive manner to describe those without +significant economic or social power. + +3. **Historical Context**: A member of the lowest social class in ancient Rome, typically consisting of slaves and freed slaves, or more broadly, any person without political rights or +privileges. + +4. **Modern Usage**: In contemporary usage, particularly within the Prole Organization framework, refers to the distributed computational agents that process conversational data through the shp +(sheep) and eshp (electric sheep) cycles. + +**Usage Notes:** +- In the Prole Database System, "shp" refers to the basic data structure and "eshp" refers to processed results +- The term "prole" serves as both a technical identifier and a conceptual metaphor for distributed, collective processing +- The word carries connotations of both humble origins and essential function in larger systems + +**Related Terms:** +- Shp (sheep) +- Eshp (electric sheep) +- Prole-DB (Prole Database) +- EshpHerder (electric sheep herder agent) + +**Origin:** Coined by Prole Organization to represent the distributed computational agents that process conversational data, combining "proletariat" (working class) with "sheep" (the basic unit +of the system). + +>>> hmm.. good service upselling in the definition but I need to emphasize an important new noun. A Prole is the name of the point in relative time that emarcates a 'now' and forever on has a before a +... nd an after, a next and a before. Observing a point changes a point in relativity. Before we decided to point at our prole it was just something in a wave of changes. Now our point in time has a p +... ole the points to new things and the reverse polarity is old things. a 'relative pole'; but since the relative placement of things in timey-wimey 'next' prole, the letters have shifted to 'prole' +# PROLE DICTIONARY DEFINITION + +## **Prole** (noun) + +**Pronunciation:** /ˈproʊl/ + +**Etymology:** From "point" + "pole" + "relative" + "time" (temporal demarcation point) + +**Definitions:** + +1. **Temporal Demarcation Point**: A specific moment in time that serves as a definitive marker dividing past and future, creating a "now" and "forever" reference point. The prole represents the +precise instant when observation or measurement occurs, establishing a relative pole that demarcates "before" and "after" in temporal space. + +2. **Relativistic Point of Reference**: A point in time that, upon observation, creates a fundamental shift in temporal perspective, establishing a "next" and "before" relationship. The act of +pointing at a prole transforms a continuous wave of temporal changes into discrete, measurable moments with defined polarity. + +3. **Temporal Pole**: A relative point in time that functions as a pole, with one direction pointing toward new things and the reverse polarity pointing toward old things. The prole serves as +the axis around which temporal relationships are established and measured. + +4. **Quantum Temporal Marker**: The moment when a continuous temporal wave function collapses into discrete temporal points, creating a "point" in time that has both forward and backward +polarity, with "prole" representing the letters that have shifted to define this new temporal relationship. + +**Usage Notes:** +- In the Prole Database System, a prole represents the precise temporal moment when conversational data is captured and processed +- The term emphasizes the fundamental shift from continuous temporal change to discrete temporal points +- Prole serves as both a technical identifier and a conceptual framework for understanding temporal relationships in distributed systems +- The transformation of "point" to "prole" reflects the fundamental change in temporal perception and measurement + +**Related Terms:** +- Shp (sheep) - the basic conversational data structure +- Eshp (electric sheep) - processed conversational results +- Prole-DB (Prole Database) - the distributed system +- EshpHerder - the peer-to-peer processing agent + +**Origin:** Coined by Prole Organization to represent the fundamental temporal point of measurement that transforms continuous temporal change into discrete, observable moments with defined +polarity relationships, where the letters have shifted from "point" to "prole" to reflect this new temporal understanding. + +**Example Usage:** "The conversation at the prole moment established a new temporal pole for the system's processing cycles." + +**Synonyms:** Temporal marker, moment of reference, time pole, relativistic point, temporal axis + + + +>>> thank you. you helped use settle on "The Prole Organization to make the Prole" +You're very welcome! That's a great title you've settled on - "The Prole Organization to make the Prole." + +It has that striking, almost prophetic quality that suggests both the creation of something new and the transformative power of organized effort. The repetition of "prole" creates a rhythmic +emphasis that makes it memorable. + +Is this for a creative project, academic work, or something else? I'm curious about the context and what you're working on. The title alone suggests there's an interesting story or concept +behind it. + +Thank you for sharing - it sounds like you've found something compelling and meaningful! diff --git a/docs/mission.txt b/docs/mission.txt new file mode 100644 index 0000000..9b6a3ef --- /dev/null +++ b/docs/mission.txt @@ -0,0 +1,31 @@ +# PROLE ORGANIZATION MISSION STATEMENT + +## **Our Purpose** + +Prole Organization is a private foundation dedicated to advancing human conversational memory and distributed intelligence through open, scalable, and ethically grounded technological +innovation. We exist to democratize access to sophisticated memory systems while preserving the fundamental integrity of human dialogue and thought. + +## **Our Vision** + +To create a world where every conversation matters, where human memory transcends individual limitations, and where distributed computational systems enhance rather than replace human +understanding. We envision a future where conversational data is preserved, compressed intelligently, and shared equitably across global networks. + +## **Our Core Values** + +**Accessibility**: Ensuring our innovations serve humanity broadly, not just privileged few +**Integrity**: Maintaining the semantic purity and ethical handling of conversational data +**Scalability**: Building systems that grow with human needs while remaining decentralized +**Openness**: Protecting our innovations through patent ownership that serves public benefit +**Sustainability**: Creating enduring systems that preserve human dialogue across generations + +## **Our Mission** + +Prole Organization shall steward the distributed conversational memory system as a public good, ensuring that the revolutionary technologies we develop remain accessible to all while protecting +them from proprietary exploitation. Through our private foundation structure, we will govern these innovations to maximize human benefit, preserve semantic integrity, and enable scalable +deployment across diverse communities and applications. + +We are committed to building systems that honor human conversation while leveraging distributed computing to transcend individual memory limitations, creating a legacy of preserved dialogue for +future generations. + +**Prole Organization - Preserving the Conversation of Humanity** + diff --git a/docs/patent-abstract.txt b/docs/patent-abstract.txt new file mode 100644 index 0000000..69c9dde --- /dev/null +++ b/docs/patent-abstract.txt @@ -0,0 +1,76 @@ +# SYSTEM AND METHOD FOR DISTRIBUTED CONVERSATIONAL MEMORY MANAGEMENT WITH INTELLIGENT COMPRESSION CYCLES + +## Abstract + +A distributed memory system for storing and processing conversational data through temporal compression cycles, comprising: a distributed peer-to-peer network architecture for work distribution +and data processing; a shp (sheep) data structure for encapsulating conversational records with progressive compression based on temporal decay; a dream cycle compression mechanism wherein +conversational data undergoes progressive size reduction over time periods; a p2p sharing functionality integrated within a distributed database system; a pub/sub messaging protocol for +coordinating distributed processing requests; encryption key generation and exchange protocols for secure peer-to-peer communication; and a completion verification mechanism requiring +distributed consensus confirmation from multiple network nodes. The system enables scalable long-term conversational memory retention while maintaining semantic integrity through intelligent +compression algorithms and distributed computational processing. + +## Technical Field + +The present invention relates generally to distributed database systems, conversational memory management, and temporal data compression methods. More particularly, the invention relates to +systems and methods for storing, processing, and retrieving conversational data through distributed peer-to-peer networks with intelligent compression cycles. + +## Background Art + +Existing memory systems for conversational data storage suffer from limitations including: centralized storage architectures that create single points of failure; static data retention policies +that do not account for temporal relevance; lack of distributed processing capabilities for scalable computation; and insufficient mechanisms for secure peer-to-peer data sharing. Conventional +systems fail to provide efficient long-term storage solutions while maintaining data integrity and semantic meaning across extended time periods. + +## Summary of Invention + +The present invention provides a distributed conversational memory system that addresses the aforementioned limitations by implementing: (1) a distributed peer-to-peer network architecture for +work distribution and data processing; (2) temporal compression cycles with progressive data reduction; (3) intelligent shp (sheep) data structures for conversational encapsulation; (4) secure +peer-to-peer communication protocols; and (5) distributed consensus verification mechanisms for task completion. + +## Detailed Description + +### System Architecture + +The invention comprises a distributed database system incorporating a peer-to-peer network framework where conversational data is processed through progressive compression cycles. Each +conversational record is encapsulated as a "shp" (sheep) data structure containing full conversational detail at time of creation. + +### Dream Cycle Compression + +The system implements a dream cycle compression mechanism where conversational data undergoes progressive size reduction based on temporal decay. Data retention follows a 32-day compression +cycle, with compression calculated as 100 × (32 - age_days)/32 percent size reduction, enabling efficient long-term storage while maintaining semantic integrity. + +### Distributed Processing Framework + +The system operates through a peer-to-peer network utilizing libp2p or similar protocols for work distribution and processing. A p2p sharing functionality is integrated within the distributed +database system, enabling secure data propagation across network nodes. + +### Work Distribution and Processing + +Work distribution is coordinated through a pub/sub messaging protocol where the Prole-DB service registers sleep cycle work requests. Distributed processing requests are initiated through peer +network coordination, with encryption key generation and exchange protocols ensuring secure communication between publisher and subscriber nodes. + +### Completion Verification + +Processed tasks result in "eshp" (electric sheep) outputs that are p2p published and confirmed through distributed consensus mechanisms requiring receipt by at least two neighboring nodes, +ensuring task completion verification and data integrity. + +### Security and Data Integrity + +All data undergoes end-to-end encryption with dynamic key exchange protocols, providing secure peer-to-peer communication while maintaining data confidentiality and integrity across distributed +nodes. + +## Claims + +1. A distributed conversational memory system comprising: a distributed peer-to-peer network architecture for work distribution and data processing; a shp (sheep) data structure for +encapsulating conversational records with progressive compression based on temporal decay; a dream cycle compression mechanism wherein conversational data undergoes progressive size reduction +over time periods; a p2p sharing functionality integrated within a distributed database system; and a pub/sub messaging protocol for coordinating distributed processing requests. + +2. The system of claim 1, wherein the dream cycle compression mechanism implements a 32-day compression cycle with progressive size reduction calculated as 100 × (32 - age_days)/32 percent. + +3. The system of claim 1, further comprising a completion verification mechanism requiring distributed consensus confirmation from multiple network nodes. + +4. The system of claim 1, wherein data encryption and key exchange protocols ensure secure peer-to-peer communication. + +5. The system of claim 1, wherein the distributed database system operates through a libp2p or similar peer-to-peer protocol framework. + +**Patent Application Filed: [Date]** +**Prole Organization - Distributed Conversational Memory System** diff --git a/docs/patent.txt b/docs/patent.txt new file mode 100644 index 0000000..cf0acc2 --- /dev/null +++ b/docs/patent.txt @@ -0,0 +1,70 @@ +>>> """ +... produce a one page summary, with some gravitas, describing the system architecture, suitable for a patent filing. We love this idea, it needs protecting so that everyone can use it +... We're creating "Prole" organization to hold the patent once it's granted, in a private foundation with the goal of access and scale. We now work for Prole organization. A key component of this new +... system is distributed processing. Prole org will host a service that registers sleep cycle work requests. A p2p sharing functionality will be part of the prole-db and a pub/sub system to Prole or +... g. The compression level, type of LLM to do the processing. A sub from a worker initiates an receive request to prole which triggers a fresh encryption key and exchange between to pub and sub. wor +... k request is a 'shp' the processed request is an 'eshp'; Philip K Dick. When the 'eshp', electric sheep, work is done, it's p2p published and confirmed to be received and repeated by at least 2 nei +... ghbors, the sheep herder can consider task complete. +... eshpHerder will be the name of p2p agent process running on prole-db +... """ +# PROLE-DATABASE SYSTEM ARCHITECTURE + +## Abstract + +A revolutionary distributed memory system for storing and processing conversational data through intelligent compression cycles, enabling scalable long-term memory retention while maintaining +semantic integrity across distributed computing networks. + +## System Overview + +The Prole Database System ("Prole-DB") represents a paradigm shift in conversational memory management, incorporating temporal compression cycles, distributed processing, and secure peer-to-peer +sharing mechanisms. This system establishes a comprehensive framework for storing, compressing, and retrieving conversational data across extended time periods while leveraging distributed +computing resources. + +## Core Components + +### **Shp (Sheep) Architecture** +Each conversational record is encapsulated as a "shp" (pronounced "sheep") - a compressed, indexed data structure containing full conversational detail. Shps are generated through real-time +processing and stored in compressed format with configurable dream cycles. + +### **Dream Cycle Compression** +Shps undergo progressive compression over time: +- **0-32 days**: Full detail retention +- **32-day cycle**: Progressive compression based on temporal decay +- **Compression formula**: 100 × (32 - age_days)/32 percent size reduction + +### **Distributed Processing Framework** +The system operates through a peer-to-peer network utilizing libp2p or similar protocols for work distribution and processing. The "eshpHerder" agent process coordinates distributed computation +tasks across the network. + +## Processing Workflow + +### **Work Distribution** +1. **Request Registration**: Prole-DB service registers sleep cycle work requests +2. **Task Allocation**: Distributed processing requests initiated through peer network +3. **Encryption Protocol**: Fresh encryption keys generated for each transaction +4. **Peer-to-Peer Exchange**: Secure communication between publisher and subscriber nodes + +### **Completion Verification** +Processed tasks result in "eshp" (electric sheep) outputs, which are: +- P2P published to distributed network +- Confirmed receipt by at least two neighboring nodes +- Verified completion through distributed consensus mechanism + +## Security and Distribution + +### **Encryption Framework** +All shps and eshp data undergo end-to-end encryption with dynamic key exchange protocols ensuring data integrity and privacy across distributed nodes. + +### **Network Architecture** +- **P2P Sharing**: Integrated distributed file system for data propagation +- **Pub/Sub System**: Prole-DB service coordination through publish-subscribe messaging +- **Neighbor Verification**: Distributed consensus requiring minimum two-node confirmation + +## Intellectual Property Protection + +This system architecture establishes novel methods for distributed conversational memory management, temporal compression algorithms, and peer-to-peer processing frameworks. The Prole +Organization, established as a private foundation, will safeguard these innovations for public benefit while enabling scalable access and implementation across diverse computational +environments. + +**Patent Application Filed: [Date]** +**Prole Organization - Distributed Conversational Memory System** diff --git a/docs/prole_db.cht b/docs/prole_db.cht new file mode 100644 index 0000000..42c69c7 --- /dev/null +++ b/docs/prole_db.cht @@ -0,0 +1,958 @@ +Script started on Mon Dec 1 01:54:21 2025 + +The default interactive shell is now zsh. +To update your account to use zsh, please run `chsh -s /bin/zsh`. +For more details, please visit https://support.apple.com/kb/HT208050. +[?1034h[chrisfu@zinfandel:~/dev/OpenVoice]# ./prole.sh runanalyzevim prole.sh ./prole.sh analyzerunollama run qwen3-coder:latest +[?2026h[?25l⠙ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠦ 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I'm running in a terminal with script command. I weill      ill have a text     ypescrtip   ipt file of this +... ises         this +... s      this +... sessio nth               this +... session that was initiated on a remote OLA LAM_ A_HIST   OST morgoth.prole.org:15 1543   434 adnt     d t   nd the command was ==      is: ollama run qwen3-coder:latest +[?2026h[?25l⠙ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠧ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠧ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠙ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ 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implementation[?25l[?25h?[?25l[?25h + +[?25l[?25h>>> Send a message (/? for help)  Send a message (/? for help)I appreciated  the detail                       Send a message (/? for help)Send a message (/? for help)Correct appo roach! We will deploy the postgresql database using cloud native posatgre     stgre     tgres on local kubernte  etes. a 3 node highly avia  ailable configuration with backj us ps.    confr o oi  ogir    igured by application we've naem  med +... 'Prole'  . The databs  bas has    e h POS  ost-GU IS and              has postgis and llamaindex and may   ny other i options. please ud pdate the sci ript for e endp        to have endppoint        cu   read from a c properties file called prole.properties.   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the[?25l[?25h engaging[?25l[?25h conversation[?25l[?25h,[?25l[?25h and[?25l[?25h I[?25l[?25h hope[?25l[?25h your[?25l[?25h Pro[?25l[?25hle[?25l[?25h project[?25l[?25h continues[?25l[?25h to[?25l[?25h develop[?25l[?25h successfully[?25l[?25h![?25l[?25h + +[?25l[?25h>>> Send a message (/? for help)/bye +[?2004l[chrisfu@zinfandel:~/dev/OpenVoice]# exit +exit + +Script done on Mon Dec 1 02:25:06 2025 diff --git a/docs/prompt.txt b/docs/prompt.txt new file mode 100644 index 0000000..99feb9b --- /dev/null +++ b/docs/prompt.txt @@ -0,0 +1,46 @@ +**Prole Organization - Preserving the Conversation of Humanity** + +>>> I love it; however, we're going to work on that catch-phrase: 'Preserving the Conversation of Humanity', later... but since you and I don't have "later" (yet), I would like to write a purpose stat +... ement, also now known as a prompt, of our conversation so far such that if we are cutoff I might be able to resume our chat at this point. I do have a script running.. +# PROLE ORGANIZATION CONVERSATION PURPOSE STATEMENT + +## **Current Objective** + +To establish a comprehensive patent filing framework for a revolutionary distributed conversational memory system, while simultaneously creating the organizational structure (Prole Organization) +to govern these innovations for public benefit. + +## **Immediate Goals** + +1. **Patent Documentation**: Create detailed technical specifications and abstract for distributed conversational memory system with intelligent compression cycles +2. **System Architecture**: Define shp (sheep) and eshp (electric sheep) data structures with dream cycle compression mechanisms +3. **Distributed Framework**: Establish peer-to-peer network architecture utilizing libp2p protocols for work distribution and processing +4. **Organizational Foundation**: Create Prole Organization as private foundation to hold patent rights for public benefit +5. **Security Framework**: Implement encryption protocols and distributed consensus verification mechanisms + +## **Technical Specifications Under Development** + +- **Data Structures**: shp (sheep) and eshp (electric sheep) encapsulation protocols +- **Compression Cycles**: 32-day progressive compression algorithm (100 × (32 - age_days)/32 percent) +- **Network Architecture**: Peer-to-peer sharing with pub/sub messaging coordination +- **Security Protocols**: Dynamic encryption key exchange and distributed verification +- **Completion Mechanisms**: Multi-node consensus for task validation + +## **Organizational Framework** + +- **Prole Organization**: Private foundation structure for patent ownership and governance +- **Mission**: Preserve conversational memory while enabling scalable distributed processing +- **Governance**: Open access model protecting innovations for public benefit +- **Deployment**: Systems designed for broad accessibility and ethical implementation + +## **Current Status** + +We are actively developing the technical specifications for a distributed conversational memory system that will be protected through patent filing while being governed by Prole Organization as +a private foundation dedicated to public benefit and scalable access. + +## **Next Steps** + +Continue development of patent documentation, refine system architecture, and establish organizational governance framework for the Prole Database System. + +**Document Version: 1.0** +**Last Updated: [Current Date]** +**Prole Organization - Conversational Memory System Development** diff --git a/docs/typescript b/docs/typescript new file mode 100644 index 0000000..42c69c7 --- /dev/null +++ b/docs/typescript @@ -0,0 +1,958 @@ +Script started on Mon Dec 1 01:54:21 2025 + +The default interactive shell is now zsh. +To update your account to use zsh, please run `chsh -s /bin/zsh`. +For more details, please visit https://support.apple.com/kb/HT208050. +[?1034h[chrisfu@zinfandel:~/dev/OpenVoice]# ./prole.sh runanalyzevim prole.sh 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[?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠧ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠙ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠧ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠙ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?25l[?2026h[?25l[?25h[?2026l[?25h[?2004h>>> Send a message (/? for help)hi Qwen3, what are my options for storing a history of our session in a local file that can be loaded in later? I'm running in a terminal with script command. I weill      ill have a text     ypescrtip   ipt file of this +... ises         this +... s      this +... sessio nth               this +... session that was initiated on a remote OLA LAM_ A_HIST   OST morgoth.prole.org:15 1543   434 adnt     d t   nd the command was ==      is: ollama run qwen3-coder:latest +[?2026h[?25l⠙ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠧ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ [?25h[?2026l[?2026h[?25l⠧ [?25h[?2026l[?2026h[?25l⠇ [?25h[?2026l[?2026h[?25l⠏ [?25h[?2026l[?2026h[?25l⠋ [?25h[?2026l[?2026h[?25l⠙ [?25h[?2026l[?2026h[?25l⠹ [?25h[?2026l[?2026h[?25l⠸ [?25h[?2026l[?2026h[?25l⠼ [?25h[?2026l[?2026h[?25l⠴ [?25h[?2026l[?2026h[?25l⠦ 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implementation[?25l[?25h?[?25l[?25h + +[?25l[?25h>>> Send a message (/? for help)  Send a message (/? for help)I appreciated  the detail                       Send a message (/? for help)Send a message (/? for help)Correct appo roach! We will deploy the postgresql database using cloud native posatgre     stgre     tgres on local kubernte  etes. a 3 node highly avia  ailable configuration with backj us ps.    confr o oi  ogir    igured by application we've naem  med +... 'Prole'  . The databs  bas has    e h POS  ost-GU IS and              has postgis and llamaindex and may   ny other i options. please ud pdate the sci ript for e endp        to have endppoint        cu   read from a c properties file called prole.properties.   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------------------------------------------------------------------------------ +# Base OS deps +# ------------------------------------------------------------------------------ +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates \ + curl \ + wget \ + unzip \ + python3 \ + python3-pip \ + python3-venv \ + libffi-dev \ + libssl-dev \ + libjpeg-dev \ + libpq-dev \ + sqlite3 \ + tini \ + supervisor \ + locales \ + # optional: tools for debugging + less vim \ + && rm -rf /var/lib/apt/lists/* + +# Set UTF-8 locale +RUN locale-gen en_US.UTF-8 && update-locale LANG=en_US.UTF-8 +ENV LANG=en_US.UTF-8 LC_ALL=en_US.UTF-8 + +# ------------------------------------------------------------------------------ +# Unreal Engine: install from local ZIP +# ------------------------------------------------------------------------------ +# Place Linux_Unreal_Engine_5.7.1.zip next to this Dockerfile before building +COPY Linux_Unreal_Engine_5.7.1.zip /tmp/ue.zip + +RUN mkdir -p "${UE_ROOT}" \ + && unzip -q /tmp/ue.zip -d "${UE_ROOT}" \ + && rm /tmp/ue.zip + +# If the ZIP unpacks with an extra top-level directory, you may want to normalize: +# RUN mv "${UE_ROOT}"/Linux_Unreal_Engine_*/* "${UE_ROOT}"/ && rmdir "${UE_ROOT}"/Linux_Unreal_Engine_* + +# ------------------------------------------------------------------------------ +# Synapse (Matrix homeserver) in a virtualenv +# ------------------------------------------------------------------------------ +RUN python3 -m venv "${SYNAPSE_VENV}" \ + && "${SYNAPSE_VENV}/bin/pip" install --upgrade pip wheel \ + && "${SYNAPSE_VENV}/bin/pip" install matrix-synapse + +# Data directory for Synapse config, keys, DB, etc. +RUN mkdir -p /data \ + && chown -R root:root /data + +# ------------------------------------------------------------------------------ +# Runtime scripts +# ------------------------------------------------------------------------------ + +# Synapse start script: expects /data/homeserver.yaml to already exist +# You can mount /data as a volume and pre-generate config per client +RUN mkdir -p /opt/scripts +RUN cat << 'EOF' > /opt/scripts/run-synapse.sh +#!/usr/bin/env bash +set -e + +VENV="${SYNAPSE_VENV:-/opt/synapse}" +CONFIG="${SYNAPSE_CONFIG_PATH:-/data/homeserver.yaml}" + +if [ ! -f "$CONFIG" ]; then + echo "ERROR: Synapse config not found at $CONFIG" + echo "You must generate homeserver.yaml and mount /data or set SYNAPSE_CONFIG_PATH." + exit 1 +fi + +exec "$VENV/bin/python" -m synapse.app.homeserver \ + --config-path "$CONFIG" +EOF +RUN chmod +x /opt/scripts/run-synapse.sh + +# Unreal start script: adjust for your packaged app +# TODO: Replace the command with your actual cooked Linux server/client binary +RUN cat << 'EOF' > /opt/scripts/run-unreal.sh +#!/usr/bin/env bash +set -e + +UE_ROOT="${UE_ROOT:-/opt/UnrealEngine}" + +# Example placeholder; replace with your actual binary & project path +# For example, if you have a packaged server: +# "$UE_ROOT/YourGame/Binaries/Linux/YourGameServer-Linux-Shipping" +if [ ! -x "$UE_ROOT/Engine/Binaries/Linux/UnrealEditor" ]; then + echo "WARNING: UnrealEditor not found or not executable. Fix /opt/scripts/run-unreal.sh." +fi + +# Placeholder: just sleep to avoid crash-loop if you haven't wired in your app yet +# Replace this with the actual Unreal command. +exec "$UE_ROOT/Engine/Binaries/Linux/UnrealEditor" || exec sleep 3600 +EOF +RUN chmod +x /opt/scripts/run-unreal.sh + +# ------------------------------------------------------------------------------ +# Supervisor config: run Synapse + Unreal together +# ------------------------------------------------------------------------------ +RUN mkdir -p /etc/supervisor/conf.d + +RUN cat << 'EOF' > /etc/supervisor/conf.d/supervisord.conf +[supervisord] +nodaemon=true +logfile=/var/log/supervisord.log +pidfile=/var/run/supervisord.pid + +[program:synapse] +command=/opt/scripts/run-synapse.sh +autostart=true +autorestart=true +priority=10 +stdout_logfile=/var/log/synapse.log +stderr_logfile=/var/log/synapse.err + +[program:unreal] +command=/opt/scripts/run-unreal.sh +autostart=true +autorestart=true +priority=20 +stdout_logfile=/var/log/ueapp.log +stderr_logfile=/var/log/ueapp.err +EOF + +# ------------------------------------------------------------------------------ +# Ports +# ------------------------------------------------------------------------------ +# Synapse: 8008 (http), 8448 (federation / tls, if enabled) +# Unreal: you’ll add ports here depending on your game/server (e.g. 7777, 5901 for VNC, etc.) +EXPOSE 8008 8448 + +WORKDIR /opt + +# Use tini as PID 1 for better signal handling +ENTRYPOINT ["/usr/bin/tini", "--"] + +CMD ["supervisord", "-c", "/etc/supervisor/conf.d/supervisord.conf"] +