Rirọpo ju-ni
Ni ibamuṢiṣẹ pẹlu OpenAI ati Anthropic SDKs. Kan yi URL ipilẹ pada.
Gbogbo awọn ede jẹ dogba. Yan eyi ti o fẹ lọ kiri lori ayelujara.
Ṣii AI & Anthropic ibaramu AI API pẹlu pipe iṣẹ, wiwa wẹẹbu, ati awọn abajade ti a ṣeto.
Ohun gbogbo ti o nilo lati firanṣẹ pẹlu Shannon's OpenAI ati API ibaramu Anthropic.
https://api.shannon-ai.com/v1/chat/completions Lo API Iwiregbe Ipari pẹlu pipe iṣẹ ati ṣiṣanwọle.
https://api.shannon-ai.com/v1/messages Claude Awọn ifiranṣẹ kika pẹlu irinṣẹ ati anthropic-version akọsori.
Aṣẹ: Olugbeni <ọrọ-rẹ> Tabi X-API-Key pẹlu ẹya anthropic fun awọn ipe ara Claude.
Awọn iwe aṣẹ ti gbogbo eniyan - Bọtini nilo lati pe Ṣiṣanwọle, pipe iṣẹ, awọn abajade ti a ṣeto, wiwa wẹẹbu.
Rirọpo ju silẹ fun OpenAI ati Awọn API Anthropic pẹlu atilẹyin abinibi fun awọn irinṣẹ, awọn abajade ti a ṣeto, ati wiwa wẹẹbu ti a ṣe sinu.
Ṣiṣẹ pẹlu OpenAI ati Anthropic SDKs. Kan yi URL ipilẹ pada.
Ṣe alaye awọn irinṣẹ, jẹ ki Shannon pe wọn. Ṣe atilẹyin adaṣe, fi agbara mu, ati pe ko si awọn ipo.
Wiwa wẹẹbu gidi-akoko pẹlu awọn itọka orisun. Wa ni aifọwọyi.
Ipo JSON ati JSON Iṣaṣe ilana fun isediwon data ti o gbẹkẹle.
Awọn losiwajulosehin ipaniyan iṣẹ adaṣe. Titi di awọn aṣetunṣe 10 fun ibeere.
Awọn iṣẹlẹ ti a firanṣẹ olupin fun ṣiṣanwọle ami-akoko gidi.
Bẹrẹ ni awọn igbesẹ mẹta. Awọn digi Shannon OpenAI ati awọn alabara Anthropic.
Lo OpenAI-ibaramu aaye ipari.
https://api.shannon-ai.com/v1/chat/completions Lo auth Oluduro ni akọsori Aṣẹ.
Yan ede kan ki o paarọ sinu bọtini rẹ.
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
}
} Idanwo Shannon API taara ninu ẹrọ aṣawakiri rẹ. Kọ ibeere rẹ, ṣiṣẹ, ki o wo idahun ni akoko gidi.
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.
/yo/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.
Gbogbo awọn ibeere API nilo ìfàṣẹsí nipa lilo bọtini Shannon API rẹ.
Authorization: Bearer YOUR_API_KEY X-API-Key: YOUR_API_KEY
anthropic-version: 2023-06-01 Shannon nfunni ni ọpọlọpọ awọn awoṣe iṣapeye fun awọn ọran lilo oriṣiriṣi.
shannon-1.6-lite Shannon 1.6 Lite Yara, awọn idahun ti o munadoko fun awọn iṣẹ ṣiṣe lojoojumọ
shannon-1.6-pro Shannon 1.6 Pro To ti ni ilọsiwaju idi fun eka isoro
shannon-2-lite Shannon 2 Lite
shannon-2-pro Shannon 2 Pro
shannon-coder-1 Shannon Coder Iṣapeye fun koodu Claude CLI pẹlu ipin-orisun ipe
Ṣetumo awọn irinṣẹ ti Shannon le pe lati ṣe awọn iṣe tabi gba alaye pada.
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" Awoṣe pinnu boya lati pe iṣẹ kan (aiyipada) "none" Pa iṣẹ pipe fun ibeere yii {"type": "function", "function": {"name": "..."}} Fi ipa mu ipe iṣẹ kan pato {
"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"
}
]
} Fi ipa mu Shannon lati dahun pẹlu JSON to wulo ti o baamu ero rẹ.
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"} Fi ipa mu iṣẹjade JSON (ko si eto kan pato) {"type": "json_schema", "json_schema": {...}} Fi ipa mu iṣẹjade ti o baamu eto gangan rẹ Muu ṣiṣanwọle ami-akoko gidi ṣiṣẹ pẹlu Awọn iṣẹlẹ ti a firanṣẹ Server fun awọn UI idahun.
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 pẹlu iṣẹ wiwa wẹẹbu ti a ṣe sinu ti o wa laifọwọyi.
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 tun ṣe atilẹyin ọna kika Awọn ifiranṣẹ Anthropic.
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); Lo eyikeyi OpenAI tabi Anthropic SDK - kan yi URL ipilẹ pada.
OpenAI Python SDK osise - ṣiṣẹ pẹlu Shannon
pip install openai OpenAI Node.js SDK osise - ṣiṣẹ pẹlu Shannon
npm install openai Community Go onibara fun OpenAI-ibaramu APIs
go get github.com/sashabaranov/go-openai Onibara Ruby Agbegbe fun OpenAI-ibaramu APIs
gem install ruby-openai Onibara PHP agbegbe fun OpenAI-ibaramu APIs
composer require openai-php/client Onibara Async Rust fun OpenAI-ibaramu APIs
cargo add async-openai Official Anthropic Python SDK - ṣiṣẹ pẹlu Shannon
pip install anthropic Official Anthropic TypeScript SDK - ṣiṣẹ pẹlu Shannon
npm install @anthropic-ai/sdk Shannon nlo awọn koodu ipo HTTP boṣewa ati da awọn ifiranṣẹ aṣiṣe alaye pada.
{
"error": {
"message": "Invalid API key provided",
"type": "authentication_error",
"code": "invalid_api_key"
}
} Awọn imudojuiwọn aipẹ ati awọn ilọsiwaju si Shannon API.
YOUR_API_KEY Tọju aṣiri bọtini API rẹ. Atunse ṣẹda bọtini titun ati sọ ti atijọ di asan.
Wo àmi ati lilo wiwa lori oju-iwe yii nigbati o wọle si akọọlẹ rẹ.
Iwọn orisun ipe fun Shannon Coder (shannon-coder-1). Tunto ni gbogbo wakati 4.
Gba bọtini API rẹ ki o bẹrẹ kikọ pẹlu Shannon AI loni.
Awọn iwadii olokiki: