Standard OCR fails at semantic extraction. Here is the exact Python and Anthropic API architecture to force Claude 4.7 to extract liability clauses into strict JSON.
If you are still paying paralegals to manually review 100-page Master Services Agreements to find the governing law and liability caps, your law firm is burning cash.
The Problem with Standard OCR
Standard OCR reads text. It does not understand semantics. If a contract says "Jurisdiction: Delaware" or "This agreement shall be governed by the laws of the State of Delaware", traditional regex parsers break. You need an LLM. But if you just dump the text into ChatGPT, it hallucinates or gives you a conversational summary. We need strict JSON.
The Claude 4.7 Architecture
Anthropic's Claude 4.7 API allows you to enforce output schemas. Here is the exact Python plumbing to extract specific clauses deterministically.
import anthropic
import json
client = anthropic.Anthropic(api_key="sk-ant-...")
def extract_clauses(contract_text):
prompt = f"""
You are an expert legal AI. Extract the following from the contract:
1. Governing Law
2. Liability Cap
Return ONLY a valid JSON object. No conversational text.
{contract_text}
"""
response = client.messages.create(
model="claude-3-5-sonnet-20241022",
max_tokens=1000,
temperature=0,
system="You output strictly in JSON.",
messages=[{"role": "user", "content": prompt}]
)
return json.loads(response.content[0].text)This is human capability multiplication in practice. You pipe the PDF text in, you get database-ready JSON out.
Want to deploy this in your practice? Download the Blueprint .