TokenFlux

https://tokenflux.ai/docs
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TokenFlux is a unified API gateway providing seamless access to 200+ AI models and services with...
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### Python Installation

Source: https://tokenflux.ai/docs

Install the OpenAI client library for Python.

```python
pip install openai
```

--------------------------------

### JavaScript/TypeScript Installation

Source: https://tokenflux.ai/docs

Install the OpenAI client library for JavaScript/TypeScript.

```javascript
npm install openai
# or
yarn add openai
# or
bun add openai
```

--------------------------------

### Create Images Example

Source: https://tokenflux.ai/docs

Example of generating images from text descriptions.

```javascript
// Note: Image generation has a different response format
const response = await fetch('https://tokenflux.ai/v1/images/generations', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-Api-Key': 'YOUR_TOKENFLUX_API_KEY',
  },
  body: JSON.stringify({
    model: 'flux-pro',
    prompt: 'A futuristic city with flying cars at sunset',
    width: 1024,
    height: 1024,
  }),
});

const generation = await response.json();
console.log(`Generation ID: ${generation.id}`);
// Poll for completion or check status
```

--------------------------------

### Try Different Models Example

Source: https://tokenflux.ai/docs

Example of iterating through different models for chat completions.

```javascript
// Try different models
const models = [
  'gpt-4o',              // OpenAI GPT-4
  'claude-3.5-sonnet',   // Anthropic Claude
  'gemini-pro',          // Google Gemini
  'mistral-large',       // Mistral AI
  'deepseek-chat',       // DeepSeek
];

for (const model of models) {
  const completion = await client.chat.completions.create({
    model: model,
    messages: [{ role: 'user', content: 'What makes you unique?' }],
  });
  
  console.log(`${model}: ${completion.choices[0].message.content}`);
}
```

--------------------------------

### Streaming Responses Example

Source: https://tokenflux.ai/docs

Example of enabling streaming for chat completions.

```javascript
const stream = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{ role: 'user', content: 'Write a short story' }],
  stream: true,
});

for await (const chunk of stream) {
  const content = chunk.choices[0]?.delta?.content || '';
  process.stdout.write(content);
}
```

--------------------------------

### Generate Embeddings Example

Source: https://tokenflux.ai/docs

Example of creating vector embeddings.

```javascript
const embedding = await client.embeddings.create({
  model: 'text-embedding-3-small',
  input: 'TokenFlux makes AI integration simple',
});

console.log(`Embedding dimensions: ${embedding.data[0].embedding.length}`);
```

--------------------------------

### Quick Start Example (JavaScript/TypeScript)

Source: https://tokenflux.ai/docs/introduction

A basic example demonstrating how to use the OpenAI client library with TokenFlux by updating the baseURL and apiKey.

```javascript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'your-tokenflux-api-key',
  baseURL: 'https://tokenflux.ai/v1',
});

const completion = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    { role: 'user', content: 'Hello, TokenFlux!' }
  ],
});

console.log(completion.choices[0].message.content);
```

--------------------------------

### Python First API Call

Source: https://tokenflux.ai/docs

Make your first chat completion request using Python.

```python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_TOKENFLUX_API_KEY",
    base_url="https://tokenflux.ai/v1"
)

completion = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "Hello, TokenFlux!"}
    ]
)

print(completion.choices[0].message.content)
```

--------------------------------

### cURL First API Call

Source: https://tokenflux.ai/docs

Make your first chat completion request using cURL.

```bash
curl https://tokenflux.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "X-Api-Key: YOUR_TOKENFLUX_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "user", "content": "Hello, TokenFlux!"}
    ]
  }'
```

--------------------------------

### JavaScript First API Call

Source: https://tokenflux.ai/docs

Make your first chat completion request using JavaScript.

```javascript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_TOKENFLUX_API_KEY',
  baseURL: 'https://tokenflux.ai/v1',
});

async function main() {
  const completion = await client.chat.completions.create({
    model: 'gpt-4o',
    messages: [
      { role: 'user', content: 'Hello, TokenFlux!' }
    ],
  });

  console.log(completion.choices[0].message.content);
}

main();
```

--------------------------------

### Example with idempotency

Source: https://tokenflux.ai/docs/api-reference/images

Example of making a request with an idempotency key.

```curl
curl https://tokenflux.ai/v1/images/generations \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer YOUR_TOKENFLUX_KEY' \
  -H 'Idempotency-Key: unique-request-id-12345' \
  -d '{
    "model": "black-forest-labs/flux-schnell",
    "input": {
      "prompt": "A serene mountain landscape at sunset",
      "aspect_ratio": "16:9"
    }
  }'
```

--------------------------------

### Example Refinement Prompt

Source: https://tokenflux.ai/docs/projects

An example prompt to refine an existing project by adding new features.

```plaintext
Great! Now add:
- Export to CSV feature
- Dark mode toggle
- Mobile-responsive design

```

--------------------------------

### Example Project Prompt

Source: https://tokenflux.ai/docs/projects

An example prompt to build a simple expense tracker web app.

```plaintext
Build a simple expense tracker web app with:
- Add/edit/delete expenses
- Categories (food, transport, entertainment)
- Monthly summary with charts
- Clean, modern UI

```

--------------------------------

### Search Tab - File Search Example

Source: https://tokenflux.ai/docs/projects/web-ui

Example of how to search for files by name.

```text
Query: "component"
Results: Button.tsx, Card.tsx, Modal.tsx...
```

--------------------------------

### Get a generation response example

Source: https://tokenflux.ai/docs/api-reference/images

Example response for the get a generation endpoint, showing the status and generated images.

```json
{
  "success": true,
  "code": 200,
  "data": {
    "id": "0a4c1d62-2cd0-4cf1-9e0c-1b2f7f4f5678",
    "model": "black-forest-labs/flux-schnell",
    "status": "succeeded",
    "cost": 0.05,
    "images": [
      {
        "url": "https://replicate.delivery/pbxt/abc123.png"
      }
    ]
  }
}
```

--------------------------------

### Start Claude Code Session

Source: https://tokenflux.ai/docs/integrations/claude-code

Commands to navigate to a project directory and start the Claude Code CLI.

```bash
cd /path/to/your/project
claude
```

--------------------------------

### Search Tab - Content Search Example

Source: https://tokenflux.ai/docs/projects/web-ui

Example of how to search for content within files.

```text
Query: "useState"
Results: App.tsx (line 5), Form.tsx (line 12)...
```

--------------------------------

### Importing Git Repositories - SSH URL Example

Source: https://tokenflux.ai/docs/projects/web-ui

Example of an SSH URL for importing a Git repository.

```git
git@github.com:user/repo.git
```

--------------------------------

### Install Claude Code

Source: https://tokenflux.ai/docs/integrations/claude-code

Command to install the Claude Code package globally using npm.

```bash
npm install -g @anthropic-ai/claude-code
```

--------------------------------

### Importing Git Repositories - HTTPS URL Example

Source: https://tokenflux.ai/docs/projects/web-ui

Example of an HTTPS URL for importing a Git repository.

```git
https://github.com/user/repo.git
```

--------------------------------

### Quick Question Example

Source: https://tokenflux.ai/docs/projects/telegram

Example of a user asking for an explanation of JavaScript 'let' and 'const', and Alfred providing a concise answer.

```javascript
**let vs const in JavaScript:**

• `const` - Cannot be reassigned after declaration
  const name = "Alice";
  name = "Bob";  // ❌ Error

• `let` - Can be reassigned
  let count = 1;
  count = 2;  // ✅ Works

Both are block-scoped (unlike `var`). Use `const` by default,
`let` only when you need to reassign.
```

--------------------------------

### Message Content Example

Source: https://tokenflux.ai/docs/api-reference/chat-completions

Example of message content with multimodal capabilities.

```json
{
  "role": "user",
  "content": [
    { "type": "text", "text": "Describe the attached image." },
    { "type": "image_url", "image_url": { "url": "https://example.com/street.png" } }
  ]
}
```

--------------------------------

### Example Chat Interaction

Source: https://tokenflux.ai/docs/projects/feishu

An example of a user interacting with the AI agent in Chinese within Feishu/Lark.

```text
You: 帮我写一个 Python 爬虫脚本

Agent: 好的，我来帮你写一个 Python 爬虫脚本...
```

--------------------------------

### get_model Response Example

Source: https://tokenflux.ai/docs/api-reference/images-mcp

Example response from the get_model tool, detailing a specific model and its input schema.

```json
{
  "id": "black-forest-labs/flux-schnell",
  "name": "FLUX.1 [schnell]",
  "description": "The fastest image generation model tailored for local development",
  "pricing": { "price": 0.025, "currency": "USD", "unit": 1 },
  "input_schema": {
    "properties": {
      "prompt": { "type": "string", "description": "Prompt for generated image" },
      "aspect_ratio": { "type": "string", "enum": ["1:1", "16:9", "21:9", "3:2"] },
      "num_outputs": { "type": "integer", "default": 1 }
    }
  }
}
```

--------------------------------

### list_models Response Example

Source: https://tokenflux.ai/docs/api-reference/images-mcp

Example response from the list_models tool, showing available VLM models.

```json
[
  {
    "id": "black-forest-labs/flux-schnell",
    "name": "FLUX.1 [schnell]",
    "description": "The fastest image generation model tailored for local development",
    "pricing": { "price": 0.025, "currency": "USD", "unit": 1 }
  }
]
```

--------------------------------

### Example Chat Prompt

Source: https://tokenflux.ai/docs/projects/web-ui

An example of a natural language prompt to an AI agent for building a weather dashboard.

```natural_language
Build a weather dashboard that:
- Shows current weather for any city
- Displays 5-day forecast
- Has a clean, modern design
- Uses the OpenWeatherMap API
```

--------------------------------

### generate_image Response Example (completed)

Source: https://tokenflux.ai/docs/api-reference/images-mcp

Example response from the generate_image tool when the image generation is completed successfully.

```json
{
  "id": "0a4c1d62-2cd0-4cf1-9e0c-1b2f7f4f5678",
  "status": "succeeded",
  "images": [
    { "url": "https://replicate.delivery/pbxt/abc123.png" }
  ]
}
```

--------------------------------

### cURL Example (non-streaming)

Source: https://tokenflux.ai/docs/api-reference/messages

Example of how to call the Messages API using cURL for a non-streaming request.

```bash
curl https://tokenflux.ai/anthropic/v1/messages \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer YOUR_TOKENFLUX_KEY' \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms."}
    ]
  }'
```

--------------------------------

### Embedding response example

Source: https://tokenflux.ai/docs/api-reference/embeddings

An example of the JSON response when creating embeddings.

```json
{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        0.0023064255,
        -0.009327292,
        0.018224157,
        0.00456132
      ]
    }
  ],
  "model": "openai/text-embedding-3-small",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}
```

--------------------------------

### Non-streaming Response Example

Source: https://tokenflux.ai/docs/api-reference/chat-completions

Example of a non-streaming chat completion response.

```json
{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1734470400,
  "model": "gpt-4o",
  "system_fingerprint": "fp_4oA1",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I help you today?"
      },
      "finish_reason": "stop",
      "logprobs": null
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 8,
    "total_tokens": 20
  }
}
```

--------------------------------

### Error response example

Source: https://tokenflux.ai/docs/api-reference/embeddings

Examples of error responses for different error conditions.

```json
{ "success": false, "code": 400, "message": "failed to bind request: ..." }
```

```json
{ "success": false, "code": 403, "message": "user quota exceeded" }
```

```json
{ "success": false, "code": 500, "message": "internal error, please try again later" }
```

--------------------------------

### get_generation Response Example

Source: https://tokenflux.ai/docs/api-reference/images-mcp

Example response from the get_generation tool, showing the status and result of an image generation request.

```json
{
  "id": "0a4c1d62-2cd0-4cf1-9e0c-1b2f7f4f5678",
  "model": "black-forest-labs/flux-schnell",
  "status": "succeeded",
  "images": [
    { "url": "https://replicate.delivery/pbxt/abc123.png" }
  ],
  "cost": 0.025
}
```

--------------------------------

### generate_image Response Example (processing)

Source: https://tokenflux.ai/docs/api-reference/images-mcp

Example response from the generate_image tool when the image generation is still in progress.

```json
{
  "id": "0a4c1d62-2cd0-4cf1-9e0c-1b2f7f4f5678",
  "status": "processing"
}
```

--------------------------------

### Coding Task Example

Source: https://tokenflux.ai/docs/projects/telegram

Example of a user requesting a Python function and Alfred generating the code.

```python
def is_palindrome(s: str) -> bool:
    """Check if a string is a palindrome, ignoring case and spaces."""
    cleaned = ''.join(c.lower() for c in s if c.isalnum())
    return cleaned == cleaned[::-1]

# Examples:
print(is_palindrome("A man a plan a canal Panama"))  # True
print(is_palindrome("hello"))  # False
```

--------------------------------

### Create image generation response example

Source: https://tokenflux.ai/docs/api-reference/images

Example response for the create image generation endpoint, returning the newly created job wrapped in a JSONResult.

```json
{
  "success": true,
  "code": 200,
  "data": {
    "id": "0a4c1d62-2cd0-4cf1-9e0c-1b2f7f4f5678",
    "model": "black-forest-labs/flux-schnell",
    "status": "starting"
  }
}
```

--------------------------------

### Basic Conversation Example

Source: https://tokenflux.ai/docs/projects/telegram

Example of a user asking a question and Alfred providing a detailed answer about CSS centering techniques.

```text
You: What's the best way to center a div in CSS?

Alfred: There are several modern approaches to center a div:

1. **Flexbox** (recommended):
   .parent {
     display: flex;
     justify-content: center;
     align-items: center;
   }

2. **Grid**:
   .parent {
     display: grid;
     place-items: center;
   }
...
```

--------------------------------

### cURL example for creating embeddings

Source: https://tokenflux.ai/docs/api-reference/embeddings

A cURL command to demonstrate creating embeddings.

```curl
curl https://tokenflux.ai/v1/embeddings \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer YOUR_TOKENFLUX_KEY' \
  -d '{
    "model": "openai/text-embedding-3-small",
    "input": "The quick brown fox jumps over the lazy dog"
  }'
```

--------------------------------

### JavaScript (OpenAI SDK)

Source: https://tokenflux.ai/docs/api-reference/chat-completions

Example using the OpenAI SDK in JavaScript for chat completions.

```javascript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.TOKENFLUX_KEY,
  baseURL: 'https://tokenflux.ai/v1'
});

const completion = await client.chat.completions.create({
  model: 'openai/gpt-4o-mini',
  messages: [
    { role: 'system', content: 'You write concise summaries.' },
    { role: 'user', content: 'Summarize the highlights from the attached PDF.' }
  ],
  max_tokens: 150
});

console.log(completion.choices[0].message.content);
```

--------------------------------

### Streaming in Node.js

Source: https://tokenflux.ai/docs/api-reference/chat-completions

Example demonstrating streaming chat completions in Node.js using the OpenAI SDK.

```javascript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.TOKENFLUX_KEY,
  baseURL: 'https://tokenflux.ai/v1'
});

const stream = await client.chat.completions.create({
  model: 'deepseek/deepseek-r1',
  messages: [{ role: 'user', content: 'Solve the puzzle step by step.' }],
  stream: true
});

for await (const chunk of stream) {
  const delta = chunk.choices[0].delta;
  if (delta?.reasoning) {
    process.stdout.write(`\n[reasoning] ${delta.reasoning}\n`);
  }
  if (delta?.content) {
    process.stdout.write(delta.content);
  }
  if (chunk.usage) {
    console.log('\nUsage:', chunk.usage);
  }
}
```

--------------------------------

### List image models response example

Source: https://tokenflux.ai/docs/api-reference/images

Example response for the list image models endpoint, showing a JSONResult envelope with a data array of model descriptors.

```json
{
  "success": true,
  "code": 200,
  "data": [
    {
      "id": "black-forest-labs/flux-schnell",
      "name": "FLUX.1 [schnell]",
      "model_provider": "black-forest-labs",
      "description": "The fastest image generation model tailored for local development and personal use",
      "tags": ["text-to-image"],
      "pricing": { "price": 0.025, "currency": "USD", "unit": 1 },
      "input_schema": {
        "properties": {
          "prompt": { "type": "string", "description": "Prompt for generated image" },
          "aspect_ratio": { "type": "string", "enum": ["1:1", "16:9", "21:9", "3:2"] }
        }
      }
    }
  ]
}
```

--------------------------------

### Authentication headers

Source: https://tokenflux.ai/docs/api-reference/embeddings

Examples of how to authenticate requests using an API key.

```http
Authorization: Bearer <tokenflux_api_key>
```

```http
X-Api-Key: <tokenflux_api_key>
```

--------------------------------

### Start Fresh Command

Source: https://tokenflux.ai/docs/projects/telegram

Command to initiate a new conversation session with Alfred.

```bash
/new
```

--------------------------------

### TypeScript (Anthropic SDK)

Source: https://tokenflux.ai/docs/api-reference/messages

Example of how to use the Anthropic SDK in TypeScript to create a message.

```typescript
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.TOKENFLUX_KEY,
  baseURL: 'https://tokenflux.ai/anthropic'
});

const message = await client.messages.create({
  model: 'anthropic/claude-sonnet-4-20250514',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Explain async/await in JavaScript.' }
  ]
});

console.log(message.content[0].text);
```

--------------------------------

### Python (Anthropic SDK)

Source: https://tokenflux.ai/docs/api-reference/messages

Example of how to use the Anthropic SDK in Python to create a message.

```python
import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_TOKENFLUX_KEY",
    base_url="https://tokenflux.ai/anthropic"
)

message = client.messages.create(
    model="anthropic/claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "What are the benefits of TypeScript?"}
    ]
)

print(message.content[0].text)
```

--------------------------------

### cURL (streaming)

Source: https://tokenflux.ai/docs/api-reference/messages

Example of how to make a streaming request to the Messages API using cURL.

```bash
curl https://tokenflux.ai/anthropic/v1/messages \
  -H 'Content-Type: application/json' \
  -H 'X-Api-Key: YOUR_TOKENFLUX_KEY' \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "stream": true,
    "messages": [
      {"role": "user", "content": "Write a haiku about programming."}
    ]
  }' \
  --no-buffer
```

--------------------------------

### cURL (streaming)

Source: https://tokenflux.ai/docs/api-reference/chat-completions

Example cURL request for streaming chat completions.

```curl
curl https://tokenflux.ai/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -H 'X-Api-Key: YOUR_TOKENFLUX_KEY' \
  -d '{
    "model": "anthropic\/claude-3.5-sonnet",
    "messages": [
      {"role": "user", "content": "Draft a launch announcement for our new feature."}
    ],
    "stream": true
  }' \
  --no-buffer
```

--------------------------------

### JavaScript (OpenAI SDK)

Source: https://tokenflux.ai/docs/api-reference/embeddings

Example of creating embeddings using the OpenAI SDK with Tokenflux.ai's base URL.

```javascript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.TOKENFLUX_KEY,
  baseURL: 'https://tokenflux.ai/v1'
});

const result = await client.embeddings.create({
  model: 'qwen/text-embedding-v4',
  input: '向量检索有什么用途？',
  dimensions: 768
});

console.log(result.data[0].embedding.length); // -> 768
```

--------------------------------

### Streaming in TypeScript

Source: https://tokenflux.ai/docs/api-reference/messages

Example of how to handle streaming responses in TypeScript using the Anthropic SDK.

```typescript
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.TOKENFLUX_KEY,
  baseURL: 'https://tokenflux.ai/anthropic'
});

const stream = await client.messages.stream({
  model: 'anthropic/claude-sonnet-4-20250514',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Write a short story about a robot.' }
  ]
});

for await (const event of stream) {
  if (event.type === 'content_block_delta' && event.delta.type === 'text_delta') {
    process.stdout.write(event.delta.text);
  }
}
```

--------------------------------

### Python example for creating embeddings

Source: https://tokenflux.ai/docs/api-reference/embeddings

A Python script using the requests library to create embeddings.

```python
import requests

BASE_URL = "https://tokenflux.ai/v1"
API_KEY = "YOUR_TOKENFLUX_KEY"

payload = {
    "model": "openai/text-embedding-3-small",
    "input": [
        "The quick brown fox jumps over the lazy dog",
        "A similar sentence for comparison"
    ]
}

resp = requests.post(
    f"{BASE_URL}/embeddings",
    headers={
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    },
    json=payload,
    timeout=30
)
resp.raise_for_status()
embeddings = resp.json()["data"]
print(f"Generated {len(embeddings)} embeddings")
```

--------------------------------

### Self-Hosting Configuration

Source: https://tokenflux.ai/docs/projects/feishu

Configuration variables for self-hosting the Feishu integration.

```shell
# Feishu App Credentials
FEISHU_APP_ID=cli_xxxxx
FEISHU_APP_SECRET=xxxxx

# Event Verification
FEISHU_VERIFICATION_TOKEN=xxxxx
FEISHU_ENCRYPT_KEY=xxxxx  # Optional

# Signing key for link tokens
IM_SIGNING_KEY=your-secret-key
```

--------------------------------

### Claude Code GitHub Action Configuration

Source: https://tokenflux.ai/docs/integrations/claude-code

Example configuration for using the Claude Code GitHub Action with TokenFlux.

```yaml
- name: Run Claude Code
  uses: anthropics/claude-code-action@v1
  with:
    anthropic_api_key: ${{ secrets.TOKENFLUX_API_KEY }}
  env:
    ANTHROPIC_BASE_URL: https://tokenflux.ai/anthropic
```

--------------------------------

### Non-streaming Response

Source: https://tokenflux.ai/docs/api-reference/messages

Example of a non-streaming response from the Messages API.

```json
{
  "id": "msg_abc123",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "The capital of France is Paris."
    }
  ],
  "model": "claude-sonnet-4-20250514",
  "stop_reason": "end_turn",
  "usage": {
    "input_tokens": 12,
    "output_tokens": 8
  }
}
```

--------------------------------

### Streaming Response

Source: https://tokenflux.ai/docs/api-reference/messages

Example of a streaming response using Server-Sent Events.

```sse
event: message_start
data: {"type":"message_start","message":{"id":"msg_abc123","type":"message","role":"assistant","content":[],"model":"claude-sonnet-4-20250514"}}

event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"The capital"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" of France is Paris."}}

event: content_block_stop
data: {"type":"content_block_stop","index":0}

event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"end_turn"},"usage":{"output_tokens":8}}

event: message_stop
data: {"type":"message_stop"}
```

--------------------------------

### Interface Overview Diagram

Source: https://tokenflux.ai/docs/projects/web-ui

A text-based diagram illustrating the three-panel layout of the web interface: Sessions, Chat Area, and Explorer.

```text
┌─────────────┬───────────────────────────┬─────────────────┐
│  Sessions   │        Chat Area          │    Explorer     │
│             │                           │                 │
│  • Chat 1   │  You: Build a todo app    │  📁 src/        │
│  • Chat 2   │                           │    📄 app.tsx   │
│  • Chat 3   │  Agent: I'll create...    │    📄 style.css │
│             │  [writes code]            │  📁 public/     │
│  + New      │  Done! Here's the app...  │  📄 package.json│
│             │                           │                 │
└─────────────┴───────────────────────────┴─────────────────┘
```

--------------------------------

### cURL (non-streaming)

Source: https://tokenflux.ai/docs/api-reference/chat-completions

Example cURL request for non-streaming chat completions.

```curl
curl https://tokenflux.ai/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer YOUR_TOKENFLUX_KEY' \
  -d '{
    "model": "openai\/gpt-4o",
    "messages": [
      {"role": "system", "content": "You are a concise assistant."},
      {"role": "user", "content": "Summarize the key points from this meeting."}
    ],
    "max_tokens": 200
  }'
```

--------------------------------

### List messages-capable models Response

Source: https://tokenflux.ai/docs/api-reference/messages

Example response structure for listing models.

```json
{
  "object": "list",
  "data": [
    {
      "id": "anthropic/claude-sonnet-4-20250514",
      "name": "Anthropic: Claude Sonnet 4",
      "type": "chat",
      ...
    }
  ]
}
```

--------------------------------

### Response

Source: https://tokenflux.ai/docs/api-reference/images

Returns up to 100 successful generations for the authenticated user ordered by `created_at DESC`. In-progress or failed jobs are excluded from this list. Use the individual `GET /{id}` endpoint to inspect pending jobs.

```json
{
  "success": true,
  "code": 200,
  "data": [
    {
      "id": "0a4c1d62-2cd0-4cf1-9e0c-1b2f7f4f5678",
      "model": "black-forest-labs/flux-schnell",
      "status": "succeeded",
      "cost": 0.05,
      "images": [
        { "url": "https://replicate.delivery/pbxt/abc123.png" },
        { "url": "https://replicate.delivery/pbxt/def456.png" }
      ]
    }
  ]
}
```
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