File size: 2,087 Bytes
52da7b7 | 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 74 75 | from __future__ import annotations
import json
import sys
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parents[1]
if str(REPO_ROOT) not in sys.path:
sys.path.insert(0, str(REPO_ROOT))
from reframr.cli import compose_generation_context
from reframr.model import ReframrModel
def main() -> None:
model = ReframrModel.load(REPO_ROOT / "model.safetensors")
messages = [
{
"role": "system",
"content": (
"Answer from tool evidence when it is provided. "
"If the question needs fresh information and no source is available, say what is missing."
),
},
{
"role": "user",
"content": "Who won the Rivergate mayoral runoff, and what number should I cite?",
},
{
"role": "assistant",
"tool_calls": [
{
"id": "call_1",
"type": "function",
"function": {
"name": "web.search",
"arguments": json.dumps({"query": "Rivergate mayoral runoff result vote share"}),
},
}
],
},
{
"role": "tool",
"tool_call_id": "call_1",
"name": "web.search",
"content": json.dumps(
{
"ok": True,
"source": {
"title": "Local Civic Wire",
"url": "https://example.org/rivergate-runoff",
"snippet": "Mara Ibekwe won the Rivergate mayoral runoff with 52.4 percent of the vote.",
},
}
),
},
]
context = compose_generation_context("", messages=messages)
print(
model.generate_text(
context,
max_tokens=90,
temperature=0.58,
top_k=64,
top_p=0.92,
repetition_penalty=1.25,
)
)
if __name__ == "__main__":
main()
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