Anthropic/claude-sonnet-5-file-analysis

claude-sonnet-5-file-analysis

Free to try Claude Sonnet 5 File Analysis API for PDF review, image-aware document reasoning, extraction, summaries, and stable production workflows.

File Analysis

Related Claude Sonnet 5 Models

claude-sonnet-5-text-to-texttext-to-text

claude-sonnet-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-sonnet-5-file-analysis',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Summarize the key points of this PDF.' },
          {
            type: 'file',
            file: {
              filename: 'gptproto.pdf',
              file_data: 'https://tos.gptproto.com/resource/gptproto.pdf'
            }
          }
        ]
      }
    ],
    stream: true,
    max_tokens: 1000,
    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-sonnet-5-file-analysis',
        'messages': [
            {
                'role': 'user',
                'content': [
                    {'type': 'text', 'text': 'Summarize the key points of this PDF.'},
                    {
                        'type': 'file',
                        'file': {
                            'filename': 'gptproto.pdf',
                            'file_data': 'https://tos.gptproto.com/resource/gptproto.pdf'
                        }
                    },
                ],
            }
        ],
        'stream': True,
        'max_tokens': 1000,
        '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-sonnet-5-file-analysis",
    "messages": [
      {
        "role": "user",
        "content": [
          { "type": "text", "text": "Summarize the key points of this PDF." },
          {
            "type": "file",
            "file": {
              "filename": "gptproto.pdf",
              "file_data": "https://tos.gptproto.com/resource/gptproto.pdf"
            }
          }
        ]
      }
    ],
    "stream": true,
    "max_tokens": 1000,
    "top_p": 0.5,
    "top_k": 50
  }'

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Claude Sonnet 5 File Analysis Pricing

Parameters	Price	Original Price	Discount

Token: input	$1.8000 per 1M input tokens	$2.0000 per 1M input tokens	90%
Token: output	$9.0000 per 1M output tokens	$10.0000 per 1M output tokens	90%

README

Fast & Affordable Claude Sonnet 5 File Analysis API (Anthropic Document Intelligence Integration)

Claude Sonnet 5 File Analysis API on Flaq AI brings Anthropic's advanced reasoning, coding, and knowledge-work capabilities to document-centered applications. This production-ready Claude API integration lets developers combine natural-language instructions with supported files and images for summarization, extraction, comparison, and detailed analysis. With multi-file input, conversational follow-up, streaming responses, and flexible generation controls, teams can turn complex source material into useful answers without building separate document-processing infrastructure.

Key Features of Claude Sonnet 5 File Analysis API

Multi-File Document Understanding: Analyze multiple supported files in one workflow and connect information across reports, specifications, briefs, and records.
Advanced Document Reasoning: Move beyond basic extraction to compare evidence, identify relationships, explain findings, and produce structured conclusions from source material.
Image-Aware File Analysis: Combine an optional image with text and file inputs when a workflow needs visual context alongside document content.
Reliable Instruction Following: Guide summaries, tables, comparisons, and other outputs with clear requirements for focus, format, tone, and level of detail.
Conversational Follow-Up: Continue asking questions about uploaded material while preserving useful context across a multi-turn analysis session.
Streaming API Responses: Return analysis progressively through a stable chat completion workflow for responsive document and knowledge applications.

How to Use Claude Sonnet 5 File Analysis API on Flaq AI

Input: Supported files, an optional image, and natural-language instructions for extraction, summarization, comparison, or reasoning.
Output: Summaries, extracted facts, comparisons, tables, explanations, and structured analysis grounded in the supplied material.
File Workflow: Submit one or more supported files with the message content, then use conversational prompts to refine or extend the analysis.
Configuration: Use supported context, output length, and sampling controls to shape the response for each document task.
Capabilities: Document summarization, cross-file comparison, technical review, information extraction, visual-context analysis, and knowledge synthesis through Claude API integration.

Best Use Cases for Claude Sonnet 5 File Analysis API Integration

Research and Report Review: Condense long reports, papers, and briefing documents into clear findings, evidence summaries, and next steps.
Contract and Policy Analysis: Compare clauses, locate important obligations, and organize relevant details for legal, finance, and operations workflows.
Technical Documentation Review: Analyze specifications, requirements, manuals, and implementation documents for engineering and product teams.
Knowledge Base Processing: Turn collections of internal documents into structured summaries, question-answering workflows, and reusable insights.
Multi-Document Comparison: Evaluate proposals, document versions, vendor materials, or research sources against consistent criteria.

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

Claude Sonnet 5 File Analysis vs Competitors: Comparative Analysis

Claude Sonnet 5 vs. Claude Sonnet 4.6 File Analysis
Claude Sonnet 4.6 supports dependable document reasoning and professional analysis. Claude Sonnet 5 builds on that foundation with stronger task execution, reasoning, coding, and knowledge-work performance for demanding file workflows.
Claude Sonnet 5 vs. Claude Opus 4.8 File Analysis
Claude Opus 4.8 targets workloads that prioritize Anthropic's highest capability tier. Claude Sonnet 5 provides a Sonnet-class option for scalable file analysis with a more balanced cost-performance profile.
Claude Sonnet 5 vs. GPT 5.5 File Analysis
GPT 5.5 offers advanced OpenAI document and multimodal workflows. Claude Sonnet 5 is a strong alternative for teams that value Claude's careful instruction following, sustained analysis, and Anthropic ecosystem.
Claude Sonnet 5 vs. Gemini File Analysis
Gemini models fit naturally into Google-centered multimodal and productivity workflows. Claude Sonnet 5 is well suited to document-heavy applications that prioritize detailed reasoning, structured synthesis, and conversational review.
Claude Sonnet 5 vs. Open-Model Document Pipelines
Open models can provide deployment control and customization but require additional serving and processing infrastructure. Claude Sonnet 5 offers managed file analysis through a production-oriented API on Flaq AI.