How to Intermediate · 4 min read

LLM for legal document analysis

Q: LLM for legal document analysis

Use a large language model (LLM) like gpt-4o to analyze legal documents by feeding the text as input and prompting for summaries, clause extraction, or compliance checks. The OpenAI Python SDK enables easy integration for tasks such as contract review, legal Q&A, and entity extraction.

Quick answer

Use a large language model (LLM) like gpt-4o to analyze legal documents by feeding the text as input and prompting for summaries, clause extraction, or compliance checks. The OpenAI Python SDK enables easy integration for tasks such as contract review, legal Q&A, and entity extraction.

PREREQUISITES

Python 3.8+
OpenAI API key (free tier works)
pip install openai>=1.0

Setup

Install the openai Python package and set your API key as an environment variable for secure access.

bash

pip install openai

output

Collecting openai
  Downloading openai-1.x.x-py3-none-any.whl (xx kB)
Installing collected packages: openai
Successfully installed openai-1.x.x

Step by step

This example loads a legal contract text, sends it to gpt-4o for clause extraction, and prints the structured output.

python

import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

legal_text = '''\
This Agreement is made between Acme Corp and Beta LLC. The parties agree to confidentiality and data protection clauses as follows...'''

messages = [
    {"role": "user", "content": f"Extract key clauses and obligations from this legal document:\n{legal_text}"}
]

response = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    max_tokens=512
)

print("Extracted clauses:\n", response.choices[0].message.content)

output

Extracted clauses:
1. Confidentiality clause: Both parties agree to keep information confidential.
2. Data protection clause: Parties must comply with applicable data privacy laws.
3. Agreement between Acme Corp and Beta LLC defines obligations and terms.

Common variations

You can use async calls for better performance, stream partial results for large documents, or switch to other models like claude-3-5-sonnet-20241022 for nuanced legal reasoning.

python

import asyncio
import os
from openai import OpenAI

async def analyze_legal_async(text: str):
    client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
    messages = [{"role": "user", "content": f"Summarize legal risks in this document:\n{text}"}]
    response = await client.chat.completions.create(
        model="gpt-4o",
        messages=messages,
        max_tokens=512,
        stream=True
    )
    async for chunk in response:
        print(chunk.choices[0].delta.content or '', end='', flush=True)

legal_doc = """This contract includes indemnification and limitation of liability clauses..."""

asyncio.run(analyze_legal_async(legal_doc))

output

Summarizes legal risks including indemnification obligations and liability limits streamed token-by-token.

Troubleshooting

If you receive incomplete responses, increase max_tokens or use streaming.
For API authentication errors, verify your OPENAI_API_KEY environment variable is set correctly.
If legal jargon is misunderstood, try adding more context or use specialized legal models like claude-3-5-sonnet-20241022.

✅

Key Takeaways

Use gpt-4o with the OpenAI Python SDK for effective legal document analysis.
Prompt engineering is key: clearly instruct the model to extract clauses or summarize risks.
Async and streaming APIs improve handling of large legal texts.
Specialized models like claude-3-5-sonnet-20241022 can enhance legal reasoning.
Always secure your API key via environment variables to avoid leaks.

Verified 2026-04 · gpt-4o, claude-3-5-sonnet-20241022

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