{
  "type": "char_location",
  "cited_text": "...the referenced source text excerpt...",
  "document_index": 0,
  "document_title": "annual-report-2025.pdf",
  "start_char_index": 1024,
  "end_char_index": 1180
}

import anthropic

client = anthropic.Anthropic(
    api_key="sk-yourClaudeAPIkey",
    base_url="https://gw.claudeapi.com"
)

doc_text = open("contract.txt", "r", encoding="utf-8").read()

response = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "document",
                "source": {
                    "type": "text",
                    "media_type": "text/plain",
                    "data": doc_text,
                },
                "title": "Partnership-Agreement-2026.txt",
                "citations": {"enabled": True}
            },
            {
                "type": "text",
                "text": "What are the penalty clauses for breach of contract?"
            }
        ]
    }]
)

for block in response.content:
    if block.type == "text":
        print(block.text)
        for cit in block.citations or []:
            print(f"  └─ Cited from {cit.document_title}")
            print(f"     Chars [{cit.start_char_index}:{cit.end_char_index}]")
            print(f"     Source: {cit.cited_text[:80]}...")

The breaching party shall pay the non-breaching party a penalty of 20% of the total contract value, payable in full within 30 days.
  └─ Cited from Partnership-Agreement-2026.txt
     Chars [4128:4280]
     Source: Article 12 — Breach of Contract: The breaching party shall pay the non-breaching...

import base64

with open("annual-report.pdf", "rb") as f:
    pdf_b64 = base64.standard_b64encode(f.read()).decode("utf-8")

response = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=2048,
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "document",
                "source": {
                    "type": "base64",
                    "media_type": "application/pdf",
                    "data": pdf_b64,
                },
                "title": "Annual-Report-2025.pdf",
                "citations": {"enabled": True}
            },
            {
                "type": "text",
                "text": "What is the net operating cash flow in the cash flow statement?"
            }
        ]
    }]
)

Net operating cash flow was $2.85 billion, a 12% year-over-year increase.
  └─ Cited from Annual-Report-2025.pdf, pages 32-32

chunks = [
    "Article 1: This agreement is entered into by Party A and Party B on January 1, 2026...",
    "Article 12 — Breach of Contract: The breaching party shall pay the non-breaching party a penalty of 20% of the total contract value...",
    "Article 15 — Dispute Resolution: Any disputes arising from this agreement..."
]

response = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "document",
                "source": {
                    "type": "content",
                    "content": [
                        {"type": "text", "text": chunk} for chunk in chunks
                    ]
                },
                "title": "Contract-Clauses-Retrieved",
                "citations": {"enabled": True}
            },
            {
                "type": "text",
                "text": "What is the penalty amount? How are disputes resolved?"
            }
        ]
    }]
)

import Anthropic from "@anthropic-ai/sdk";
import fs from "fs";

const client = new Anthropic({
  apiKey: "sk-yourClaudeAPIkey",
  baseURL: "https://gw.claudeapi.com",
});

const docText = fs.readFileSync("contract.txt", "utf-8");

const response = await client.messages.create({
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [{
    role: "user",
    content: [
      {
        type: "document",
        source: { type: "text", media_type: "text/plain", data: docText },
        title: "Partnership-Agreement.txt",
        citations: { enabled: true },
      },
      { type: "text", text: "What are the penalty clauses?" }
    ]
  }]
});

for (const block of response.content) {
  if (block.type === "text") {
    console.log(block.text);
    for (const cit of (block as any).citations || []) {
      console.log(`  └─ ${cit.document_title} [${cit.start_char_index}:${cit.end_char_index}]`);
    }
  }
}

curl https://gw.claudeapi.com/v1/messages \
  -H "x-api-key: sk-yourClaudeAPIkey" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "messages": [{
      "role": "user",
      "content": [
        {
          "type": "document",
          "source": {"type": "text", "media_type": "text/plain", "data": "This agreement is effective as of January 1, 2026..."},
          "title": "contract.txt",
          "citations": {"enabled": true}
        },
        {"type": "text", "text": "When does the agreement take effect?"}
      ]
    }]
  }'

response = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=2048,
    tools=[{"type": "web_search_20260209", "name": "web_search"}],
    messages=[{"role": "user", "content": "What is Anthropic's 2026 valuation? Cite your sources."}]
)

import anthropic
from typing import List

client = anthropic.Anthropic(
    api_key="sk-yourClaudeAPIkey",
    base_url="https://gw.claudeapi.com"
)

# Assume you have a vector database (Pinecone / Weaviate / Chroma)
def retrieve_chunks(query: str, k: int = 5) -> List[dict]:
    """Return top-k relevant legal provisions"""
    # ... your vector retrieval code
    return [
        {"source": "Civil Code", "article": "Article 585", "text": "The parties may agree that when one party breaches..."},
        {"source": "Contract Law", "article": "Article 114", "text": "If the agreed penalty is less than the loss incurred..."},
        # ...
    ]

def answer_with_citations(question: str):
    chunks = retrieve_chunks(question)

    response = client.messages.create(
        model="claude-opus-4-7",
        max_tokens=2048,
        system="You are a rigorous legal consultation assistant. Your answers must be based solely on the provided legal provisions. Do not cite any laws not included in the provided documents.",
        messages=[{
            "role": "user",
            "content": [
                {
                    "type": "document",
                    "source": {
                        "type": "content",
                        "content": [
                            {"type": "text",
                             "text": f"[{c['source']} {c['article']}] {c['text']}"}
                            for c in chunks
                        ]
                    },
                    "title": "Retrieved Legal Provisions",
                    "citations": {"enabled": True}
                },
                {"type": "text", "text": question}
            ]
        }]
    )

    # Structured output with citations
    result = {"answer": "", "citations": []}
    for block in response.content:
        if block.type == "text":
            result["answer"] += block.text
            for cit in (block.citations or []):
                idx = cit.start_block_index
                result["citations"].append({
                    "source": chunks[idx]["source"],
                    "article": chunks[idx]["article"],
                    "cited_text": cit.cited_text,
                })
    return result

print(answer_with_citations("Can the agreed penalty be adjusted if it's too low?"))

{
  "answer": "Under the law, if the agreed penalty is less than the loss incurred, the parties may request the court or arbitration institution to increase it.",
  "citations": [
    {
      "source": "Contract Law",
      "article": "Article 114",
      "cited_text": "If the agreed penalty is less than the loss incurred, the parties may request the people's court or arbitration institution to increase it..."
    }
  ]
}