Αντικατάσταση drop‑in
ΣυμβατόΛειτουργεί με SDK των OpenAI και Anthropic. Απλώς αλλάξτε το βασικό URL.
Όλες οι γλώσσες είναι ίσες. Επιλέξτε αυτή που θέλετε να χρησιμοποιήσετε.
Συμβατό AI API με OpenAI και Anthropic, με κλήση συναρτήσεων, αναζήτηση ιστού και δομημένες εξόδους.
Όλα όσα χρειάζεσαι για κυκλοφορία με το συμβατό με OpenAI/Anthropic API της Shannon.
https://api.shannon-ai.com/v1/chat/completions Χρησιμοποιήστε το Chat Completions API με function calling και streaming.
https://api.shannon-ai.com/v1/messages Μορφή Claude Messages με tools και header anthropic-version.
Εξουσιοδότηση: Bearer <to-kleidi-sou> Ή χρησιμοποιήστε X-API-Key + anthropic-version για κλήσεις τύπου Claude.
Public docs - Key required to call Streaming, function calling, δομημένες αποκρίσεις και web search.
Άμεση αντικατάσταση για OpenAI και Anthropic APIs με native υποστήριξη για tools, δομημένες αποκρίσεις και ενσωματωμένο web search.
Λειτουργεί με SDK των OpenAI και Anthropic. Απλώς αλλάξτε το βασικό URL.
Ορίστε εργαλεία και αφήστε το Shannon να τα καλέσει. Υποστηρίζει τις λειτουργίες auto, forced και none.
Αναζήτηση ιστού σε πραγματικό χρόνο με παραπομπές πηγών. Διαθέσιμη αυτόματα.
Λειτουργία JSON και επιβολή JSON Schema για αξιόπιστη εξαγωγή δεδομένων.
Αυτόματοι βρόχοι εκτέλεσης συναρτήσεων. Έως 10 επαναλήψεις ανά αίτημα.
Server‑sent events για ροή token σε πραγματικό χρόνο.
Ξεκινήστε σε τρία βήματα. Το Shannon αντικατοπτρίζει πελάτες OpenAI και Anthropic.
Χρησιμοποιήστε endpoint συμβατό με OpenAI.
https://api.shannon-ai.com/v1/chat/completions Χρησιμοποιήστε Bearer auth στην κεφαλίδα Authorization.
Επιλέξτε γλώσσα και βάλτε το κλειδί σας.
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
}
} Δοκιμάστε το Shannon API απευθείας στο πρόγραμμα περιήγησης. Δημιουργήστε αίτημα, εκτελέστε το και δείτε την απόκριση σε πραγματικό χρόνο.
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.
/el/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.
Όλα τα API requests απαιτούν authentication με το Shannon API key σας.
Authorization: Bearer YOUR_API_KEY X-API-Key: YOUR_API_KEY
anthropic-version: 2023-06-01 Το Shannon προσφέρει πολλαπλά μοντέλα βελτιστοποιημένα για διαφορετικά 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 Το Shannon υποστηρίζει επίσης το Anthropic 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 Το Shannon χρησιμοποιεί τυπικούς κωδικούς κατάστασης HTTP και επιστρέφει λεπτομερή σφάλματα.
{
"error": {
"message": "Invalid API key provided",
"type": "authentication_error",
"code": "invalid_api_key"
}
} Recent updates and improvements to the Shannon API.
YOUR_API_KEY Κρατήστε το API key μυστικό. Η ανανέωση δημιουργεί νέο κλειδί και ακυρώνει το παλιό.
Δείτε κατανάλωση token και αναζητήσεων σε αυτή τη σελίδα μετά τη σύνδεση.
Όριο βάσει κλήσεων για Shannon Coder (shannon-coder-1). Επαναφέρεται κάθε 4 ώρες.
Get your API key and start building with Shannon AI today.
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