> ## 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-Opus-4-1-20250805-Thinking - File Analysis
> Claude-Opus-4-1-20250805-Thinking — File Analysis. GPTProto API reference.
Claude's official format for the file analysis API.
```bash cURL (with URL) theme={null}
curl -X POST "https://gptproto.com/v1/messages" \
-H "Authorization: YOUR_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-opus-4-1-20250805-thinking",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Please analyze this PDF document and provide a summary of its content"
},
{
"type": "document",
"source": {
"type": "url",
"url": "https://www.bt.cn/data/api-doc.pdf"
}
}
]
}
]
}'
```
```bash cURL (with Base64) theme={null}
curl -X POST "https://gptproto.com/v1/messages" \
-H "Authorization: YOUR_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-opus-4-1-20250805-thinking",
"max_tokens": 2000,
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Please analyze this PDF document and extract the key information, main topics, and summary"
},
{
"type": "document",
"source": {
"type": "base64",
"media_type": "application/pdf",
"data": "JVBERi0xLjQKJeLjz9MK..."
}
}
]
}
]
}'
```
```python Python (with URL) theme={null}
import anthropic
client = anthropic.Anthropic(
api_key="YOUR_API_KEY",
base_url="https://gptproto.com"
)
message = client.messages.create(
model="claude-opus-4-1-20250805-thinking",
max_tokens=1024,
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "Please analyze this PDF document and provide a summary of its content"
},
{
"type": "document",
"source": {
"type": "url",
"url": "https://www.bt.cn/data/api-doc.pdf"
}
}
]
}
]
)
print(message.content)
```
```python Python (with Base64) theme={null}
import anthropic
import base64
client = anthropic.Anthropic(
api_key="YOUR_API_KEY",
base_url="https://gptproto.com"
)
# Read and encode file
with open("document.pdf", "rb") as file:
base64_file = base64.b64encode(file.read()).decode('utf-8')
message = client.messages.create(
model="claude-opus-4-1-20250805-thinking",
max_tokens=2000,
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "Please analyze this PDF document and extract the key information, main topics, and summary"
},
{
"type": "document",
"source": {
"type": "base64",
"media_type": "application/pdf",
"data": base64_file
}
}
]
}
]
)
print(message.content)
```
```javascript JavaScript (with URL) theme={null}
import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://gptproto.com'
});
const message = await client.messages.create({
model: 'claude-opus-4-1-20250805-thinking',
max_tokens: 1024,
messages: [
{
role: 'user',
content: [
{
type: 'text',
text: 'Please analyze this PDF document and provide a summary of its content'
},
{
type: 'document',
source: {
type: 'url',
url: 'https://www.bt.cn/data/api-doc.pdf'
}
}
]
}
]
});
console.log(message.content);
```
```javascript JavaScript (with Base64) theme={null}
import Anthropic from '@anthropic-ai/sdk';
import fs from 'fs';
const client = new Anthropic({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://gptproto.com'
});
// Read and encode file
const base64File = fs.readFileSync('document.pdf').toString('base64');
const message = await client.messages.create({
model: 'claude-opus-4-1-20250805-thinking',
max_tokens: 2000,
messages: [
{
role: 'user',
content: [
{
type: 'text',
text: 'Please analyze this PDF document and extract the key information, main topics, and summary'
},
{
type: 'document',
source: {
type: 'base64',
media_type: 'application/pdf',
data: base64File
}
}
]
}
]
});
console.log(message.content);
```
```go Go (with URL) theme={null}
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://gptproto.com/v1/messages"
payload := []byte(`{
"model": "claude-opus-4-1-20250805-thinking",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Please analyze this PDF document and provide a summary of its content"
},
{
"type": "document",
"source": {
"type": "url",
"url": "https://www.bt.cn/data/api-doc.pdf"
}
}
]
}
]
}`)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(payload))
req.Header.Set("Authorization", "YOUR_API_KEY")
req.Header.Set("anthropic-version", "2023-06-01")
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/messages"
// Read and encode file
fileData, _ := os.ReadFile("document.pdf")
base64File := base64.StdEncoding.EncodeToString(fileData)
payload := map[string]interface{}{
"model": "claude-opus-4-1-20250805-thinking",
"max_tokens": 2000,
"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": "document",
"source": map[string]interface{}{
"type": "base64",
"media_type": "application/pdf",
"data": base64File,
},
},
},
},
},
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "YOUR_API_KEY")
req.Header.Set("anthropic-version", "2023-06-01")
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 401 - Invalid API Key theme={null}
{
"error": {
"type": "authentication_error",
"message": "Invalid API key"
}
}
```
```json 400 - Invalid Request theme={null}
{
"error": {
"type": "invalid_request_error",
"message": "messages: field required"
}
}
```
```json 429 - Rate Limit Exceeded theme={null}
{
"error": {
"type": "rate_limit_error",
"message": "Rate limit exceeded"
}
}
```
```json 500 - Internal Server Error theme={null}
{
"error": {
"type": "api_error",
"message": "Internal server error"
}
}
```
```json 529 - Overloaded theme={null}
{
"error": {
"type": "overloaded_error",
"message": "Service is temporarily overloaded"
}
}
```
## Parameters
| Parameter | Type | Required | Default | Description |
| ---------------- | ------- | -------- | ----------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model` | string | ✅ Yes | `claude-opus-4-1-20250805-thinking` | The model to use for file analysis |
| `messages` | array | ✅ Yes | - | Array of message objects for the conversation. Each message must have a role (user or assistant) and content. Content can include: - Text blocks with type "text" - Document blocks with type "document" containing: - source: Object with type "base64" or "url" - For base64: media\_type (e.g., "application/pdf") and data (base64 string) - For url: url field with the file URL Supported file formats: PDF, DOCX, XLSX, TXT, CSV, JSON, XML, HTML Maximum file size: 20MB Example with URL: `json [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this document" }, { "type": "document", "source": { "type": "url", "url": "https://example.com/document.pdf" } } ] } ] ` Example with base64: `json [ { "role": "user", "content": [ { "type": "text", "text": "Please analyze this document" }, { "type": "document", "source": { "type": "base64", "media_type": "application/pdf", "data": "JVBERi0xLjQKJeLjz9MK..." } } ] } ] ` |
| `max_tokens` | integer | ✅ Yes | `1024` | The maximum number of tokens to generate before stopping |
| `temperature` | number | ❌ No | `1.0` | Amount of randomness injected into the response. Ranges from 0.0 to 1.0 |
| `top_p` | number | ❌ No | `1.0` | Use nucleus sampling. Ranges from 0.0 to 1.0 |
| `top_k` | integer | ❌ No | `null` | Only sample from the top K options for each subsequent token |
| `stream` | boolean | ❌ No | `false` | Whether to incrementally stream the response using server-sent events |
| `stop_sequences` | array | ❌ No | - | Custom text sequences that will cause the model to stop generating |
### 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` |