File size: 1,908 Bytes
4b97c3b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | #!/usr/bin/env python3
"""
TokioAI Engine -- Basic Usage Example
Prerequisites:
pip install tokioai-engine
ollama serve &
ollama pull qwen3-coder
"""
from engine.pipeline import Pipeline, EngineConfig
# Create engine with default config (connects to local Ollama)
config = EngineConfig(
model_name="qwen3-coder", # Any Ollama model
ollama_host="http://localhost:11434",
max_retries=2, # Retry on bad output
use_guided_gen=True, # Force valid JSON for tool calls
use_memory=True, # Learn from successful interactions
verbose=True, # Show engine internals
)
engine = Pipeline(config)
# --- Tool Call Example ---
print("=" * 60)
print("TOOL CALL: 'check disk space'")
print("=" * 60)
result = engine.process("check disk space")
print(f"Intent: {result.intent}")
print(f"Type: {result.output_type}")
print(f"Calls: {result.tool_calls}")
print(f"Latency: {result.latency_ms}ms")
print(f"Retries: {result.attempts}")
print()
# --- Text Response Example ---
print("=" * 60)
print("TEXT: 'what is SQL injection'")
print("=" * 60)
engine.reset()
result = engine.process("what is SQL injection")
print(f"Intent: {result.intent}")
print(f"Type: {result.output_type}")
print(f"Text: {result.text[:200]}")
print(f"Latency: {result.latency_ms}ms")
print()
# --- Decision Example ---
print("=" * 60)
print("DECISION: 'is docker running'")
print("=" * 60)
engine.reset()
result = engine.process("is docker running")
print(f"Intent: {result.intent}")
print(f"Type: {result.output_type}")
if result.tool_calls:
print(f"Calls: {result.tool_calls}")
else:
print(f"Text: {result.text[:200]}")
print(f"Latency: {result.latency_ms}ms")
print()
# --- Stats ---
print("=" * 60)
print("ENGINE STATS")
print("=" * 60)
import json
print(json.dumps(engine.get_stats(), indent=2))
|