Anthropic/claude-opus-5.5-file-analysis

claude-opus-5.5-file-analysis

Try Claude Opus 5.5 API by Anthropic for document review, summaries, and file Q&A through Flaq AI's stable, affordable API with streaming responses for apps.

File Analysis

Related Claude Opus 5.5 Models

claude-opus-5.5-text-to-texttext-to-text

claude-opus-5.5-file-analysisfile-analysis

Documentation

API Examples

JavaScriptPythoncURL

Submit Example

const response = await fetch('https://api.flaq.ai/api/v1/chat/completions', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer YOUR_API_KEY',
    Accept: 'text/event-stream',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'claude-opus-5.5-file-analysis',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Summarize this file and extract the key risks.' },
          {
            type: 'file',
            file: {
              filename: 'demo.pdf',
              file_data: 'https://example.com/demo.pdf'
            }
          }
        ]
      }
    ],
    stream: true,
    max_tokens: 4096
  })
});

if (!response.ok) {
  const errorBody = await response.json().catch(() => null);
  throw new Error(errorBody?.error?.message ?? errorBody?.message ?? `HTTP ${response.status}`);
}

const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
let assistantText = '';

while (true) {
  const { done, value } = await reader.read();
  if (done) break;

  buffer += decoder.decode(value, { stream: true });
  const frames = buffer.split(/\r?\n\r?\n/);
  buffer = frames.pop() || '';

  for (const frame of frames) {
    const lines = frame.split(/\r?\n/).filter(Boolean);
    let eventName = 'message';
    const dataLines = [];

    for (const line of lines) {
      if (line.startsWith('event:')) {
        eventName = line.slice(6).trim();
      } else if (line.startsWith('data:')) {
        dataLines.push(line.replace(/^data:\s*/, ''));
      }
    }

    const raw = dataLines.join('\n').trim();
    if (raw === '[DONE]') {
      console.log('\nFinal text:', assistantText);
      continue;
    }

    let payload;
    try {
      payload = JSON.parse(raw);
    } catch {
      continue;
    }

    if (eventName === 'error' || payload.error) {
      const msg = payload.error?.message ?? payload.message ?? 'Chat request failed';
      throw new Error(msg);
    }

    const delta = payload.choices?.[0]?.delta;
    if (delta?.content) {
      assistantText += delta.content;
      console.log(assistantText);
    }
  }
}

Submit Example

import json
import requests

response = requests.post(
    'https://api.flaq.ai/api/v1/chat/completions',
    headers={
        'Authorization': 'Bearer YOUR_API_KEY',
        'Accept': 'text/event-stream',
        'Content-Type': 'application/json',
    },
    json={
        'model': 'claude-opus-5.5-file-analysis',
        'messages': [
            {
                'role': 'user',
                'content': [
                    {'type': 'text', 'text': 'Summarize this file and extract the key risks.'},
                    {
                        'type': 'file',
                        'file': {
                            'filename': 'demo.pdf',
                            'file_data': 'https://example.com/demo.pdf'
                        }
                    },
                ],
            }
        ],
        'stream': True,
        'max_tokens': 4096,
    },
    stream=True,
)

response.raise_for_status()

event_name = 'message'
assistant_text = ''

for raw_line in response.iter_lines(decode_unicode=True):
    if not raw_line:
        event_name = 'message'
        continue

    if raw_line.startswith('event:'):
        event_name = raw_line.replace('event:', '', 1).strip()
        continue

    if raw_line.startswith('data:'):
        raw_data = raw_line.replace('data:', '', 1).strip()
        if raw_data == '[DONE]':
            print('\nFinal text:', assistant_text)
            continue

        payload = json.loads(raw_data)

        if event_name == 'error' or payload.get('error'):
            error = payload.get('error') or payload
            raise RuntimeError(error.get('message', 'Chat request failed'))

        choices = payload.get('choices') or []
        if choices:
            delta = choices[0].get('delta') or {}
            content = delta.get('content')
            if content:
                assistant_text += content
                print(content, end='', flush=True)

Submit Example

curl -N -X POST "https://api.flaq.ai/api/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Accept: text/event-stream" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-5.5-file-analysis",
    "messages": [
      {
        "role": "user",
        "content": [
          { "type": "text", "text": "Summarize this file and extract the key risks." },
          {
            "type": "file",
            "file": {
              "filename": "demo.pdf",
              "file_data": "https://example.com/demo.pdf"
            }
          }
        ]
      }
    ],
    "stream": true,
    "max_tokens": 4096
  }'

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Claude Opus 5.5 File Analysis Pricing

Parameters	Price	Original Price	Discount

Token: input	$3.6000 per 1M input tokens	$4.0000 per 1M input tokens	90%
Token: output	$18.0000 per 1M output tokens	$20.0000 per 1M output tokens	90%

README

Frontier Multimodal Claude Opus 5.5 File Analysis API (Anthropic Deep Document and Evidence Understanding)

Claude Opus 5.5 File Analysis API brings Anthropic's model for long-running knowledge work to document evaluation, data extraction, and visual evidence review on Flaq AI. With supported text, image, and file inputs in a conversational workflow, analysts, engineers, and researchers can ask questions about PDFs, technical diagrams, and multiple source documents, then review the resulting summaries against the originals.

Key Features of Claude Opus 5.5 File Analysis API

Frontier Multimodal Ingestion: Ingest and analyze combinations of supported text documents, high-resolution images, and scanned files within a unified conversational context.
Document & Diagram Comprehension: Ask questions about multi-column layouts, financial tables, flowcharts, and technical figures while checking extracted details against the source.
Cross-Document Evidentiary Synthesis: Compare and contrast findings across multiple uploaded documents to highlight discrepancies, historical revisions, and contractual dependencies.
Visual Evidence & Layout Reasoning: Evaluate visual assets, architectural diagrams, and photographed pages directly alongside textual context to maintain holistic situational awareness.
Custom Structured Output Formatting: Format findings into bespoke markdown tables, executive risk matrices, audit checklists, or structured classifications following natural-language prompts.
High-Reliability Streaming Delivery: Stream complex multi-page document syntheses progressively via server-sent events for responsive interactive interfaces.

How to Use Claude Opus 5.5 File Analysis API for Document Workflows on Flaq AI

Input: Conversation messages that may include supported text, images, or files, plus task instructions when needed.
Output: Thorough analytical reports, structured data extractions, cross-file comparative summaries, and evidence-grounded answers.
Output Length: Optionally set a maximum output token count for concise extracts or detailed reviews. No default maximum is specified for this parameter; model output limits still apply.
Streaming: Deliver responses incrementally through server-sent events to ensure uninterrupted interactive engagement.
Capabilities: Multimodal file review, complex table extraction, cross-referencing, visual diagram interpretation, and structured synthesis via Flaq AI API integration.

Best Use Cases for Claude Opus 5.5 File Analysis API Integration

Regulatory & Legal Document Review: Compare clauses, flag possible conflicts, and draft working notes for qualified reviewers to assess against applicable requirements.
Institutional Investment & Financial Auditing: Extract intricate financial disclosures, balance sheet footnotes, and risk factors from 10-K filings and investor prospectuses.
Academic & Scientific Literature Synthesis: Cross-examine multi-study clinical trials, laboratory preprints, and scientific appendices to synthesize research meta-analyses.
Technical Blueprint & Engineering Manual Analysis: Evaluate aerospace, civil, or software system documentation containing interwoven text and intricate schematics.
Enterprise Policy Governance: Audit organizational policies against evolving regulatory standards, outputting detailed gap analyses and action plans.

Note Confirm file permissions and review extracted information before relying on it for legal, financial, medical, compliance, or other high-impact decisions. Ensure uploaded materials adhere to Anthropic's safety guidelines and Flaq AI terms.

Claude Opus 5.5 File Analysis vs Competitors: Comparative Analysis

Claude Opus 5.5 File Analysis vs. Claude Opus 5 File Analysis
Claude Opus 5 File Analysis supports document review in the earlier model series. Claude Opus 5.5 File Analysis brings the newer model to long-running knowledge work; teams should compare extraction quality on their own files before migrating.
Claude Opus 5.5 File Analysis vs. GPT 6 Sol File Analysis
GPT 6 Sol File Analysis offers an OpenAI-based option for file questions and extraction. Claude Opus 5.5 File Analysis provides an Anthropic-based option for reviewing supplied documents and explaining findings in natural language.
Claude Opus 5.5 File Analysis vs. Gemini 3.5 Pro Document Understanding
Gemini 3.5 Pro fits workflows built around Google's multimodal tools. Claude Opus 5.5 File Analysis serves teams seeking Anthropic-based document and image review through Flaq AI.
Claude Opus 5.5 File Analysis vs. Dedicated Enterprise Extraction Tools
Template-based extraction tools can be useful for repeatable fields and fixed layouts. Claude Opus 5.5 File Analysis also supports open-ended questions and summaries when document structure or the review goal varies.