Anthropic/claude-opus-4.6-file-analysis

claude-opus-4.6-file-analysis

Claude Opus 4.6 API for deep document review, contract analysis, report summaries, and file Q&A. Stable and affordable for professional team workflows. Built for free testing and stable API workflows.

File Analysis

Related Claude Opus 4.6 Models

claude-opus-4.6-text-to-texttext-to-text

claude-opus-4.6-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-4.6-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,
    top_p: 0.5,
    top_k: 50
  })
});

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('\n\n');
  buffer = frames.pop() || '';

  for (const frame of frames) {
    const lines = frame.split('\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-4.6-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,
        'top_p': 0.5,
        'top_k': 50,
    },
    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-4.6-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,
    "top_p": 0.5,
    "top_k": 50
  }'

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Claude Opus 4.6 File Analysis Pricing

Parameters	Price	Original Price	Discount

Token: input	$4.5000 per 1M input tokens	$5.0000 per 1M input tokens	90%
Token: output	$22.5000 per 1M output tokens	$25.0000 per 1M output tokens	90%

README

Fast & Affordable Claude Opus 4.6 File Analysis API (an advanced Claude Opus model for deep reasoning and agentic work)

Claude Opus 4.6 File Analysis API on Flaq AI provides Claude API access for complex workflows that require careful analysis, clear instruction following, and reliable long-form output. This deep, controlled, and production-ready Claude API integration helps developers build file analysis experiences with flexible conversation context, document-aware prompting, supported tool workflows, and route-specific settings on Flaq AI. Built for production workloads, it gives teams a stable way to add advanced AI capability without managing model infrastructure or writing provider-specific plumbing from scratch.

Key Features of Claude Opus 4.6 File Analysis API

Multi-File Document Understanding: Analyze uploaded files in one workflow and connect details across reports, briefs, specifications, and records.
Long-Context File Reasoning: Preserve document details across larger inputs while producing clear summaries, comparisons, and next-step recommendations.
Flexible API Controls: Use conversation context, document-aware prompting, supported tool workflows, and route-specific settings on Flaq AI to guide simple requests, deep analysis, and production automation.
Production Tool Support: Connect supported tool workflows, retrieval, automation, and advanced application features without surfacing low-level provider settings.
Cost-Effective Integration: Build file analysis features through Flaq AI with clear routing, stable model pages, and durable API messaging for production workflows.
Developer-Friendly Workflow: Use natural-language instructions, structured prompts, and route-specific inputs to move quickly from prototype to production.

How to Use Claude Opus 4.6 File Analysis API for Document Analysis on Flaq AI

Input: Uploaded files plus natural-language instructions for extraction, summarization, comparison, or reasoning.
Output: Document summaries, extracted insights, comparisons, tables, decisions, or structured analysis from uploaded files.
Route Configuration: Designed for multi-document analysis workflows with file input support and flexible follow-up context.
Configuration: flexible conversation context, document-aware prompting, supported tool workflows, and route-specific settings on Flaq AI.
Capabilities: PDF and document analysis, spreadsheet-style reasoning, contract review, report summarization, and multi-file comparison through deep, controlled, and production-ready Claude API integration.

Best Use Cases for Claude Opus 4.6 File Analysis API Integration

Research Report Summaries: Condense long reports, white papers, and briefing documents into executive-ready takeaways.
Contract & Policy Review: Compare clauses, flag important obligations, and summarize risks for legal, finance, or operations teams.
Data & Spreadsheet Analysis: Inspect structured files, find trends, and explain tables in plain language for business users.
Knowledge Base Processing: Turn uploaded manuals, docs, and support articles into searchable answers and reusable summaries.
Multi-Document Comparison: Compare versions, proposals, requirements, or vendor documents with consistent criteria and clean output.

Note Please ensure your prompts, uploaded files, and application workflows comply with Anthropic safety and usage guidelines. If an error occurs, review the input for restricted content, simplify the request, and try again.

Claude Opus 4.6 File Analysis vs Competitors: Comparative Analysis

Claude Opus 4.6 vs. GPT 5.5 GPT 5.5 is positioned for advanced OpenAI reasoning and coding workflows. Claude Opus 4.6 stands out for Claude-style instruction following, careful analysis, and a strong fit for writing, file, and agent workflows.
Claude Opus 4.6 vs. GPT 5.4 GPT 5.4 emphasizes affordable OpenAI performance for professional work. Claude Opus 4.6 offers a Claude API alternative with careful response quality, practical controls, and dependable output for file analysis tasks.
Claude Opus 4.6 vs. Gemini Gemini models are strong for Google-native multimodal use cases. Claude Opus 4.6 differentiates with Claude's careful response style, practical document reasoning, and production-oriented tool behavior.
Claude Opus 4.6 vs. DeepSeek Reasoner DeepSeek Reasoner is useful for cost-sensitive reasoning workloads. Claude Opus 4.6 provides managed Claude quality, safer production behavior, and stronger fit for professional writing, coding, and analysis workflows.
Claude Opus 4.6 vs. Llama Llama models give developers open-model control and self-hosting flexibility. Claude Opus 4.6 is better for teams that want a managed API, strong instruction following, and high-quality output without model infrastructure work.