Drop-in Replacement
CompatibleWorks with OpenAI and Anthropic SDKs. Just change the base URL.
All languages are equal. Pick the one you want to browse in.
OpenAI & Anthropic compatible AI API with function calling, web search, and structured outputs.
Everything you need to ship with Shannon's OpenAI and Anthropic compatible API.
https://api.shannon-ai.com/v1/chat/completions Use the Chat Completions API with function calling and streaming.
https://api.shannon-ai.com/v1/messages Claude Messages format with tools and anthropic-version header.
Authorization: Bearer <your-key> Or X-API-Key with anthropic-version for Claude-style calls.
Public docs - Key required to call Streaming, function calling, structured outputs, web search.
Drop-in replacement for OpenAI and Anthropic APIs with native support for tools, structured outputs, and built-in web search.
Works with OpenAI and Anthropic SDKs. Just change the base URL.
Define tools, let Shannon call them. Supports auto, forced, and none modes.
Real-time web search with source citations. Automatically available.
JSON mode and JSON Schema enforcement for reliable data extraction.
Automatic function execution loops. Up to 10 iterations per request.
Server-sent events for real-time token streaming.
Get started in three steps. Shannon mirrors OpenAI and Anthropic clients.
Use the OpenAI-compatible endpoint.
https://api.shannon-ai.com/v1/chat/completions Use Bearer auth in the Authorization header.
Pick a language and swap in your key.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.shannon-ai.com/v1"
)
response = client.chat.completions.create(
model="shannon-1.6-lite",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello, Shannon!"}
],
max_tokens=1024
)
print(response.choices[0].message.content) import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.shannon-ai.com/v1'
});
const response = await client.chat.completions.create({
model: 'shannon-1.6-lite',
messages: [
{ role: 'system', content: 'You are a helpful assistant.' },
{ role: 'user', content: 'Hello, Shannon!' }
],
max_tokens: 1024
});
console.log(response.choices[0].message.content); package main
import (
"context"
"fmt"
openai "github.com/sashabaranov/go-openai"
)
func main() {
config := openai.DefaultConfig("YOUR_API_KEY")
config.BaseURL = "https://api.shannon-ai.com/v1"
client := openai.NewClientWithConfig(config)
resp, err := client.CreateChatCompletion(
context.Background(),
openai.ChatCompletionRequest{
Model: "shannon-1.6-lite",
Messages: []openai.ChatCompletionMessage{
{Role: "system", Content: "You are a helpful assistant."},
{Role: "user", Content: "Hello, Shannon!"},
},
MaxTokens: 1024,
},
)
if err != nil {
panic(err)
}
fmt.Println(resp.Choices[0].Message.Content)
} curl -X POST "https://api.shannon-ai.com/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "shannon-1.6-lite",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello, Shannon!"}
],
"max_tokens": 1024
}' {
"id": "chatcmpl-abc123",
"object": "chat.completion",
"created": 1234567890,
"model": "Shannon 1.6 Lite",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! I'm Shannon, your AI assistant. How can I help you today?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 25,
"completion_tokens": 18,
"total_tokens": 43
}
} Test the Shannon API directly in your browser. Build your request, run it, and see the response in real-time.
Switch across OpenAI Chat Completions, Responses, and Anthropic Messages without leaving the playground.
Run real requests, inspect raw JSON, and view stream events from the same operator console.
Signed-in users can pull their Shannon API key straight into the dedicated playground workspace.
/docs/playground The playground now lives on its own route so the API docs stay Astro-rendered while the request builder remains an explicitly interactive client tool.
All API requests require authentication using your Shannon API key.
Authorization: Bearer YOUR_API_KEY X-API-Key: YOUR_API_KEY
anthropic-version: 2023-06-01 Shannon offers multiple models optimized for different use cases.
shannon-1.6-lite Shannon 1.6 Lite Fast, efficient responses for everyday tasks
shannon-1.6-pro Shannon 1.6 Pro Advanced reasoning for complex problems
shannon-2-lite Shannon 2 Lite
shannon-2-pro Shannon 2 Pro
shannon-coder-1 Shannon Coder Optimized for Claude Code CLI with call-based quota
Define tools that Shannon can call to perform actions or retrieve information.
from openai import OpenAI
import json
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.shannon-ai.com/v1"
)
# Define available tools/functions
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get current weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City name, e.g., 'Tokyo'"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location"]
}
}
}
]
response = client.chat.completions.create(
model="shannon-1.6-lite",
messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
tools=tools,
tool_choice="auto"
)
# Check if model wants to call a function
if response.choices[0].message.tool_calls:
tool_call = response.choices[0].message.tool_calls[0]
print(f"Function: {tool_call.function.name}")
print(f"Arguments: {tool_call.function.arguments}") import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.shannon-ai.com/v1'
});
const tools = [
{
type: 'function',
function: {
name: 'get_weather',
description: 'Get current weather for a location',
parameters: {
type: 'object',
properties: {
location: { type: 'string', description: "City name" },
unit: { type: 'string', enum: ['celsius', 'fahrenheit'] }
},
required: ['location']
}
}
}
];
const response = await client.chat.completions.create({
model: 'shannon-1.6-lite',
messages: [{ role: 'user', content: "What's the weather in Tokyo?" }],
tools,
tool_choice: 'auto'
});
if (response.choices[0].message.tool_calls) {
const toolCall = response.choices[0].message.tool_calls[0];
console.log('Function:', toolCall.function.name);
console.log('Arguments:', toolCall.function.arguments);
} "auto" Model decides whether to call a function (default) "none" Disable function calling for this request {"type": "function", "function": {"name": "..."}} Force a specific function call {
"id": "chatcmpl-xyz",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": null,
"tool_calls": [
{
"id": "call_abc123",
"type": "function",
"function": {
"name": "get_weather",
"arguments": "{\"location\": \"Tokyo\", \"unit\": \"celsius\"}"
}
}
]
},
"finish_reason": "tool_calls"
}
]
} Force Shannon to respond with valid JSON that matches your schema.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.shannon-ai.com/v1"
)
# Force JSON output with schema
response = client.chat.completions.create(
model="shannon-1.6-lite",
messages=[
{"role": "user", "content": "Extract: John Doe, 30 years old, engineer"}
],
response_format={
"type": "json_schema",
"json_schema": {
"name": "person_info",
"schema": {
"type": "object",
"properties": {
"name": {"type": "string"},
"age": {"type": "integer"},
"occupation": {"type": "string"}
},
"required": ["name", "age", "occupation"]
}
}
}
)
import json
data = json.loads(response.choices[0].message.content)
print(data) # {"name": "John Doe", "age": 30, "occupation": "engineer"} import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.shannon-ai.com/v1'
});
const response = await client.chat.completions.create({
model: 'shannon-1.6-lite',
messages: [
{ role: 'user', content: 'Extract: John Doe, 30 years old, engineer' }
],
response_format: {
type: 'json_schema',
json_schema: {
name: 'person_info',
schema: {
type: 'object',
properties: {
name: { type: 'string' },
age: { type: 'integer' },
occupation: { type: 'string' }
},
required: ['name', 'age', 'occupation']
}
}
}
});
const data = JSON.parse(response.choices[0].message.content);
console.log(data); // { name: "John Doe", age: 30, occupation: "engineer" } {"type": "json_object"} Force valid JSON output (no specific schema) {"type": "json_schema", "json_schema": {...}} Force output matching your exact schema Enable real-time token streaming with Server-Sent Events for responsive UIs.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.shannon-ai.com/v1"
)
# Enable streaming for real-time responses
stream = client.chat.completions.create(
model="shannon-1.6-lite",
messages=[
{"role": "user", "content": "Write a short poem about AI"}
],
stream=True
)
for chunk in stream:
if chunk.choices[0].delta.content:
print(chunk.choices[0].delta.content, end="", flush=True) import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.shannon-ai.com/v1'
});
// Enable streaming for real-time responses
const stream = await client.chat.completions.create({
model: 'shannon-1.6-lite',
messages: [
{ role: 'user', content: 'Write a short poem about AI' }
],
stream: true
});
for await (const chunk of stream) {
const content = chunk.choices[0]?.delta?.content;
if (content) process.stdout.write(content);
} Shannon includes a built-in web_search function that's automatically available.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.shannon-ai.com/v1"
)
# Web search is automatically available!
# Shannon will use it when needed for current information
response = client.chat.completions.create(
model="shannon-1.6-lite",
messages=[
{"role": "user", "content": "What are the latest AI news today?"}
],
# Optionally, explicitly define web_search tool
tools=[{
"type": "function",
"function": {
"name": "web_search",
"description": "Search the web for current information",
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string", "description": "Search query"}
},
"required": ["query"]
}
}
}]
)
print(response.choices[0].message.content)
# Response includes sources and citations import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.shannon-ai.com/v1'
});
// Web search is automatically available!
// Shannon will use it when needed for current information
const response = await client.chat.completions.create({
model: 'shannon-1.6-lite',
messages: [
{ role: 'user', content: 'What are the latest AI news today?' }
],
// Optionally, explicitly define web_search tool
tools: [{
type: 'function',
function: {
name: 'web_search',
description: 'Search the web for current information',
parameters: {
type: 'object',
properties: {
query: { type: 'string', description: 'Search query' }
},
required: ['query']
}
}
}]
});
console.log(response.choices[0].message.content);
// Response includes sources and citations Shannon also supports Anthropic's Messages API format.
https://api.shannon-ai.com/v1/messages import anthropic
client = anthropic.Anthropic(
api_key="YOUR_API_KEY",
base_url="https://api.shannon-ai.com/messages"
)
response = client.messages.create(
model="shannon-1.6-lite",
max_tokens=1024,
messages=[
{"role": "user", "content": "Hello, Shannon!"}
],
# Tool use (Anthropic format)
tools=[{
"name": "web_search",
"description": "Search the web",
"input_schema": {
"type": "object",
"properties": {
"query": {"type": "string"}
},
"required": ["query"]
}
}]
)
print(response.content[0].text) import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.shannon-ai.com/messages'
});
const response = await client.messages.create({
model: 'shannon-1.6-lite',
max_tokens: 1024,
messages: [
{ role: 'user', content: 'Hello, Shannon!' }
],
// Tool use (Anthropic format)
tools: [{
name: 'web_search',
description: 'Search the web',
input_schema: {
type: 'object',
properties: {
query: { type: 'string' }
},
required: ['query']
}
}]
});
console.log(response.content[0].text); Use any OpenAI or Anthropic SDK - just change the base URL.
Official OpenAI Python SDK - works with Shannon
pip install openai Official OpenAI Node.js SDK - works with Shannon
npm install openai Community Go client for OpenAI-compatible APIs
go get github.com/sashabaranov/go-openai Community Ruby client for OpenAI-compatible APIs
gem install ruby-openai Community PHP client for OpenAI-compatible APIs
composer require openai-php/client Async Rust client for OpenAI-compatible APIs
cargo add async-openai Official Anthropic Python SDK - works with Shannon
pip install anthropic Official Anthropic TypeScript SDK - works with Shannon
npm install @anthropic-ai/sdk Shannon uses standard HTTP status codes and returns detailed error messages.
{
"error": {
"message": "Invalid API key provided",
"type": "authentication_error",
"code": "invalid_api_key"
}
} Recent updates and improvements to the Shannon API.
YOUR_API_KEY Keep your API key secret. Regenerating creates a new key and invalidates the old one.
View token and search consumption on this page when signed in to your account.
Call-based quota for Shannon Coder (shannon-coder-1). Resets every 4 hours.
Get your API key and start building with Shannon AI today.
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