File size: 2,488 Bytes
eb55756 | 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 | """Minimal OpenAI-compatible client for a Flint SGLang server, with one tool-calling round trip.
pip install openai
python3 example_client.py --base-url http://localhost:30000/v1 [--api-key KEY]
"""
import argparse
import json
import os
from openai import OpenAI
SAMPLING = {"temperature": 1.0, "top_p": 0.95, "extra_body": {"top_k": 20}}
MAX_TOKENS = 32768 # reasoning counts toward max_tokens
TOOLS = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather for a city.",
"parameters": {
"type": "object",
"properties": {"city": {"type": "string", "description": "City name"}},
"required": ["city"],
},
},
}
]
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--base-url", default="http://localhost:30000/v1")
parser.add_argument("--api-key", default=os.environ.get("FLINT_API_KEY", "unused"))
args = parser.parse_args()
client = OpenAI(base_url=args.base_url, api_key=args.api_key)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What's the weather in Paris right now?"},
]
first = client.chat.completions.create(
model="flint", messages=messages, tools=TOOLS, max_tokens=MAX_TOKENS, **SAMPLING
)
choice = first.choices[0]
reply = choice.message
print("reasoning:", getattr(reply, "reasoning_content", None))
print("tool calls:", reply.tool_calls)
if choice.finish_reason == "length":
print(f"cut off: the turn used all {MAX_TOKENS} tokens (reasoning counts toward max_tokens)")
return
if not reply.tool_calls:
print("content:", reply.content)
return
# Echo the assistant turn (including reasoning_content) back unchanged, then add tool results.
messages.append(reply.model_dump(exclude_none=True))
for call in reply.tool_calls:
city = json.loads(call.function.arguments)["city"]
messages.append(
{"role": "tool", "tool_call_id": call.id, "content": json.dumps({"city": city, "forecast": "sunny, 21C"})}
)
second = client.chat.completions.create(
model="flint", messages=messages, tools=TOOLS, max_tokens=MAX_TOKENS, **SAMPLING
)
print("final answer:", second.choices[0].message.content)
if __name__ == "__main__":
main()
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