aitbc/plugins/ollama/README.md

AITBC Ollama Plugin

Provides GPU-powered LLM inference services through Ollama, allowing miners to earn AITBC by processing AI/ML inference jobs.

Features

• 🤖 13 Available Models: From lightweight 1B to large 14B models
• 💰 Earn AITBC: Get paid for GPU inference work
• 🚀 Fast Processing: Direct GPU acceleration via CUDA
• 💬 Chat & Generation: Support for both chat and text generation
• 💻 Code Generation: Specialized models for code generation

Available Models

Model	Size	Best For
deepseek-r1:14b	9GB	General reasoning, complex tasks
qwen2.5-coder:14b	9GB	Code generation, programming
deepseek-coder-v2:latest	9GB	Advanced code generation
gemma3:12b	8GB	General purpose, multilingual
deepcoder:latest	9GB	Code completion, debugging
deepseek-coder:6.7b-base	4GB	Lightweight code tasks
llama3.2:3b-instruct-q8_0	3GB	Fast inference, instruction following
mistral:latest	4GB	Balanced performance
llama3.2:latest	2GB	Quick responses, general use
gemma3:4b	3GB	Efficient general tasks
qwen2.5:1.5b	1GB	Fast, lightweight tasks
gemma3:1b	815MB	Minimal resource usage
lauchacarro/qwen2.5-translator:latest	1GB	Translation tasks

Quick Start

1. Start Ollama (if not running)

ollama serve

2. Start Mining

cd /home/oib/windsurf/aitbc/plugins/ollama
python3 miner_plugin.py

3. Submit Jobs (in another terminal)

# Text generation
python3 client_plugin.py generate llama3.2:latest "Explain quantum computing"

# Chat completion
python3 client_plugin.py chat mistral:latest "What is the meaning of life?"

# Code generation
python3 client_plugin.py code deepseek-coder-v2:latest "Create a REST API in Python" --lang python

Pricing

Cost is calculated per 1M tokens:

• 14B models: ~0.12-0.14 AITBC
• 12B models: ~0.10 AITBC
• 6-9B models: ~0.06-0.08 AITBC
• 3-4B models: ~0.02-0.04 AITBC
• 1-2B models: ~0.01 AITBC

Miners earn 150% of the cost (50% markup).

API Usage

Submit Generation Job

from client_plugin import OllamaClient

client = OllamaClient("http://localhost:8001", "${CLIENT_API_KEY}")

job_id = client.submit_generation(
    model="llama3.2:latest",
    prompt="Write a poem about AI",
    max_tokens=200
)

# Wait for result
result = client.wait_for_result(job_id)
print(result['result']['output'])

Submit Chat Job

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "How does blockchain work?"}
]

job_id = client.submit_chat("mistral:latest", messages)

Submit Code Generation

job_id = client.submit_code_generation(
    model="deepseek-coder-v2:latest",
    prompt="Create a function to sort a list in Python",
    language="python"
)

Miner Configuration

The miner automatically:

• Registers all available Ollama models
• Sends heartbeats with GPU stats
• Processes jobs up to 2 concurrent tasks
• Calculates earnings based on token usage

Testing

Run the test suite:

python3 test_ollama_plugin.py

Integration with AITBC

The Ollama plugin integrates seamlessly with:

• Coordinator: Job distribution and management
• Wallet: Automatic earnings tracking
• Explorer: Job visibility as blocks
• GPU Monitoring: Real-time resource tracking

Tips

1. Choose the right model: Smaller models for quick tasks, larger for complex reasoning
2. Monitor earnings: Check with cd home/miner && python3 wallet.py balance
3. Batch jobs: Submit multiple jobs for better utilization
4. Temperature tuning: Lower temp (0.3) for code, higher (0.8) for creative tasks

Troubleshooting

• Ollama not running: Start with ollama serve
• Model not found: Pull with ollama pull <model-name>
• Jobs timing out: Increase TTL when submitting
• Low earnings: Use larger models for higher value jobs