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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 | #!/usr/bin/env python3
"""
TokioAI Engine -- OpenAI Client Example
Shows how to use TokioAI Engine as a drop-in replacement for OpenAI API.
Prerequisites:
pip install tokioai-engine openai
python -m engine serve --model qwen3-coder --port 8080
"""
from openai import OpenAI
# Connect to TokioAI Engine (same API as OpenAI)
client = OpenAI(
base_url="http://localhost:8080/v1",
api_key="not-needed", # Engine doesn't require auth
)
# --- Tool calling ---
print("--- Tool Calling ---")
response = client.chat.completions.create(
model="tokioai-engine",
messages=[{"role": "user", "content": "check what processes are using the most memory"}],
)
msg = response.choices[0].message
if msg.tool_calls:
for tc in msg.tool_calls:
print(f"Tool: {tc.function.name}")
print(f"Arguments: {tc.function.arguments}")
else:
print(f"Response: {msg.content}")
print()
# --- Text response ---
print("--- Text Response ---")
response = client.chat.completions.create(
model="tokioai-engine",
messages=[{"role": "user", "content": "explain the TCP 3-way handshake in one paragraph"}],
)
print(f"Response: {response.choices[0].message.content}")
print()
# --- Engine metadata ---
if hasattr(response, "engine_metadata"):
print(f"Intent: {response.engine_metadata['intent']}")
print(f"Confidence: {response.engine_metadata['confidence']}")
print(f"Latency: {response.engine_metadata['latency_ms']}ms")
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