File size: 3,386 Bytes
164e036 | 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 76 77 78 79 80 81 82 83 84 85 86 87 88 | #!/usr/bin/env python3
"""Call a self-hosted claim drafter and validate what comes back.
Assumes vLLM is serving the exported adapter (see deploy/export_model.py):
vllm serve Qwen/Qwen3.5-9B --lora-modules claim-drafter=./export/peft_adapter
Then:
python3 deploy/example_client.py
python3 deploy/example_client.py --file my_disclosure.txt
vLLM exposes an OpenAI-compatible API, so the standard client works against your
own server — nothing leaves your infrastructure.
"""
import argparse
import os
import sys
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from claim_drafter.rewards import claim_reward, split_claims
# Must stay byte-identical to the training system prompt. It was constant across
# all 9,662 examples; changing it at inference is off-distribution.
SYSTEM_PROMPT = (
"You are an expert US patent attorney. Draft a set of independent and "
"dependent claims based on the provided invention description. Use "
"correct USPTO formatting."
)
EXAMPLE_DISCLOSURE = """Title: Adaptive Battery Thermal Management
Technical Field and Background:
Electric vehicle battery packs lose capacity when individual cells operate
outside a narrow temperature band. Existing thermal management systems circulate
coolant through the entire pack at a single flow rate, which wastes energy and
still leaves interior modules measurably hotter than modules at the pack edge.
Invention Disclosure:
A controller reads temperature from sensors mounted on each battery module and
drives an independent coolant valve for each module, holding every module inside
a target temperature band rather than cooling the pack as a single unit. The
controller adjusts each valve continuously from the per-module readings."""
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--base-url", default=os.environ.get("CLAIM_DRAFTER_URL",
"http://localhost:8000/v1"))
ap.add_argument("--model", default="claim-drafter")
ap.add_argument("--file", help="path to a disclosure; uses a built-in example if omitted")
ap.add_argument("--max-tokens", type=int, default=3072)
args = ap.parse_args()
disclosure = open(args.file).read() if args.file else EXAMPLE_DISCLOSURE
from openai import OpenAI
client = OpenAI(base_url=args.base_url, api_key="not-used")
response = client.chat.completions.create(
model=args.model,
messages=[{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": disclosure}],
temperature=0.0, # drafting is not a creative task
max_tokens=args.max_tokens,
)
claims = response.choices[0].message.content
print("=" * 70)
print(claims)
print("=" * 70)
# The same function that provided the RL reward is the production guardrail.
score = claim_reward(claims)
n_claims = len(split_claims(claims))
print("\nformal validity: %.3f over %d claims" % (score, n_claims))
if score < 0.9:
print("BELOW THRESHOLD — numbering or dependency defect.")
print("Regenerate, or route to an attorney for review before showing a user.")
sys.exit(1)
print("Passed the formal checks.")
print("Note: this verifies FORM, not novelty or patentability.")
if __name__ == "__main__":
main()
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