> ## Documentation Index > Fetch the complete documentation index at: https://docs.gptproto.com/llms.txt > Use this file to discover all available pages before exploring further. # Claude-3-7-Sonnet-20250219 - File Analysis - openai > Claude-3-7-Sonnet-20250219 — File Analysis (openai). GPTProto API reference. Claude's openai format for the file analysis API. ```bash cURL (with URL) theme={null} curl -X POST "https://gptproto.com/v1/chat/completions" \ -H "Authorization: YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "claude-3-7-sonnet-20250219", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this PDF document and provide a summary of its content" }, { "type": "file", "file": { "filename": "api-doc.pdf", "file_data": "https://www.bt.cn/data/api-doc.pdf" } } ] } ], "max_tokens": 1000, "stream": false }' ``` ```bash cURL (with Base64) theme={null} curl -X POST "https://gptproto.com/v1/chat/completions" \ -H "Authorization: YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "claude-3-7-sonnet-20250219", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this PDF document and extract the key information, main topics, and summary" }, { "type": "file", "file": { "filename": "document.pdf", "file_data": "data:application/pdf;base64,JVBERi0xLjQKJeLjz9MK..." } } ] } ], "max_tokens": 2000, "stream": false }' ``` ```python Python (with URL) theme={null} import requests import json url = "https://gptproto.com/v1/chat/completions" headers = { "Authorization": "YOUR_API_KEY", "Content-Type": "application/json" } data = { "model": "claude-3-7-sonnet-20250219", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this PDF document and provide a summary of its content" }, { "type": "file", "file": { "filename": "api-doc.pdf", "file_data": "https://www.bt.cn/data/api-doc.pdf" } } ] } ], "max_tokens": 1000, "stream": False } response = requests.post(url, headers=headers, json=data) result = response.json() print(json.dumps(result, indent=2)) ``` ```python Python (with Base64) theme={null} import requests import json import base64 url = "https://gptproto.com/v1/chat/completions" headers = { "Authorization": "YOUR_API_KEY", "Content-Type": "application/json" } # Read and encode file with open("document.pdf", "rb") as file: base64_file = base64.b64encode(file.read()).decode('utf-8') data = { "model": "claude-3-7-sonnet-20250219", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this PDF document and extract the key information, main topics, and summary" }, { "type": "file", "file": { "filename": "document.pdf", "file_data": f"data:application/pdf;base64,{base64_file}" } } ] } ], "max_tokens": 2000, "stream": False } response = requests.post(url, headers=headers, json=data) result = response.json() print(json.dumps(result, indent=2)) ``` ```javascript JavaScript (with URL) theme={null} const url = "https://gptproto.com/v1/chat/completions"; const headers = { "Authorization": "YOUR_API_KEY", "Content-Type": "application/json" }; const data = { "model": "claude-3-7-sonnet-20250219", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this PDF document and provide a summary of its content" }, { "type": "file", "file": { "filename": "api-doc.pdf", "file_data": "https://www.bt.cn/data/api-doc.pdf" } } ] } ], "max_tokens": 1000, "stream": false }; fetch(url, { method: "POST", headers: headers, body: JSON.stringify(data) }) .then(response => response.json()) .then(data => console.log(data)) .catch(error => console.error("Error:", error)); ``` ```javascript JavaScript (with Base64) theme={null} const url = "https://gptproto.com/v1/chat/completions"; const headers = { "Authorization": "YOUR_API_KEY", "Content-Type": "application/json" }; // Read and encode file const fs = require('fs'); const base64File = fs.readFileSync('document.pdf').toString('base64'); const data = { "model": "claude-3-7-sonnet-20250219", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this PDF document and extract the key information, main topics, and summary" }, { "type": "file", "file": { "filename": "document.pdf", "file_data": `data:application/pdf;base64,${base64File}` } } ] } ], "max_tokens": 2000, "stream": false }; fetch(url, { method: "POST", headers: headers, body: JSON.stringify(data) }) .then(response => response.json()) .then(data => console.log(data)) .catch(error => console.error("Error:", error)); ``` ```go Go (with URL) theme={null} package main import ( "bytes" "encoding/json" "fmt" "io/ioutil" "net/http" ) func main() { url := "https://gptproto.com/v1/chat/completions" payload := map[string]interface{}{ "model": "claude-3-7-sonnet-20250219", "messages": []map[string]interface{}{ { "role": "user", "content": []map[string]interface{}{ { "type": "text", "text": "Please analyze this PDF document and provide a summary of its content", }, { "type": "file", "file": map[string]string{ "filename": "api-doc.pdf", "file_data": "https://www.bt.cn/data/api-doc.pdf", }, }, }, }, }, "max_tokens": 1000, "stream": false, } jsonData, _ := json.Marshal(payload) req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData)) req.Header.Set("Authorization", "YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") client := &http.Client{} resp, err := client.Do(req) if err != nil { panic(err) } defer resp.Body.Close() body, _ := ioutil.ReadAll(resp.Body) fmt.Println(string(body)) } ``` ```go Go (with Base64) theme={null} package main import ( "bytes" "encoding/base64" "encoding/json" "fmt" "io/ioutil" "net/http" "os" ) func main() { url := "https://gptproto.com/v1/chat/completions" // Read and encode file fileData, _ := os.ReadFile("document.pdf") base64File := base64.StdEncoding.EncodeToString(fileData) payload := map[string]interface{}{ "model": "claude-3-7-sonnet-20250219", "messages": []map[string]interface{}{ { "role": "user", "content": []map[string]interface{}{ { "type": "text", "text": "Please analyze this PDF document and extract the key information, main topics, and summary", }, { "type": "file", "file": map[string]string{ "filename": "document.pdf", "file_data": "data:application/pdf;base64," + base64File, }, }, }, }, }, "max_tokens": 2000, "stream": false, } jsonData, _ := json.Marshal(payload) req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData)) req.Header.Set("Authorization", "YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") client := &http.Client{} resp, err := client.Do(req) if err != nil { panic(err) } defer resp.Body.Close() body, _ := ioutil.ReadAll(resp.Body) fmt.Println(string(body)) } ``` ```json 200 - Success theme={null} { "id": "chatcmpl-abc123", "object": "chat.completion", "created": 1699896916, "model": "claude-3-7-sonnet-20250219", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "# Document Analysis Summary\n\n## Key Information:\n- Document Type: Technical API Documentation\n- Total Pages: 35\n- Version: 2.0\n\n## Main Topics:\n1. **Authentication**: The API uses Bearer token authentication with API keys\n2. **Endpoints**: Contains 12 main API endpoints for different operations\n3. **Rate Limiting**: Implements tiered rate limiting based on subscription level\n4. **Error Handling**: Comprehensive error codes and handling strategies\n\n## Key Sections:\n\n### Getting Started\n- Quick start guide for new developers\n- Authentication setup instructions\n- First API call examples in multiple languages\n\n### API Reference\n- Detailed endpoint documentation\n- Request/response formats\n- Parameter descriptions and constraints\n\n### Best Practices\n- Recommended usage patterns\n- Performance optimization tips\n- Security considerations\n\n### Code Examples\n- Python, JavaScript, Go, and cURL examples\n- Common use case implementations\n- Error handling patterns\n\n## Important Notes:\n- All requests must include valid API key\n- Rate limits: 100 requests/minute for free tier, 1000/minute for premium\n- Support for both JSON and XML response formats\n- Webhook notifications available for asynchronous operations" }, "finish_reason": "stop" } ], "usage": { "prompt_tokens": 3500, "completion_tokens": 285, "total_tokens": 3785 } } ``` ```json 401 - Invalid signature theme={null} { "error": { "message": "Invalid signature", "type": "401" } } ``` ```json 403 - Insufficient balance theme={null} { "error": { "message": "Insufficient balance", "type": "403" } } ``` ```json 500 - Internal server error theme={null} { "error": { "message": "Internal server error", "type": "500" } } ``` ```json 503 - Content policy violation theme={null} { "error": { "message": "Input may not meet the guidelines. Please adjust and try again.", "type": "503" } } ``` ## Parameters | Parameter | Type | Required | Default | Description | | - | - | - | - | - | | `model` | string | ✅ Yes | `claude-3-7-sonnet-20250219` | The model to use for file analysis. Must be `claude-3-7-sonnet-20250219` or another Claude model with file analysis capabilities. | | `messages` | array | ✅ Yes | - | Array of message objects for the conversation. Each message contains: - **role**: `user`, `assistant`, or `system` - **content**: Array of content objects supporting: - **type: "text"**: Text prompt with `text` field - **type: "file"**: File input with `file` object containing: - `filename`: Name of the file - `file_data`: URL to file or base64 encoded data Supported file formats: PDF, DOCX, XLSX, TXT, CSV, JSON, XML, HTML Maximum file size: 20MB Example structure: `json [ { "role": "user", "content": [ { "type": "text", "text": "Summarize the contents of this document" }, { "type": "file", "file": { "filename": "document.pdf", "file_data": "https://example.com/document.pdf" } } ] } ] ` | | `max_tokens` | integer | ❌ No | `1000` | Maximum number of tokens to generate in the response | | `stream` | boolean | ❌ No | `false` | Whether to stream the response | | `temperature` | number | ❌ No | `1.0` | Sampling temperature between 0 and 2. Higher values make output more random. | ### Messages Array Structure Each message object in the `messages` array should have the following structure: | Field | Type | Required | Description | | - | - | - | - | | `role` | string | ✅ Yes | The role of the message. Can be: `user`, `assistant`, or `system` | | `content` | array/string | ✅ Yes | The content of the message | ### Content Array Structure (when content is an array) | Field | Type | Required | Example | Description | | - | - | - | - | - | | `type` | string | ✅ Yes | `text` | The type of content | | `text` | string | ✅ Yes | `"The positive prompt for the generation."` | The text content when type is `text` | This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.