Drop-in प्रतिस्थापन
अनुकूलOpenAI र Anthropic SDK हरूसँग काम गर्छ। केवल base URL परिवर्तन गर्नुहोस्।
API प्रलेखन
Shannon API
फङ्क्शन कलिङ, वेब खोज र संरचित आउटपुट सहित OpenAI र Anthropic अनुकूल AI API।
Shannon AI API Documentation
सारांश
सार्वजनिक प्रलेखनShannon को OpenAI र Anthropic अनुकूल API सँग सुरु गर्न आवश्यक सबै कुरा।
https://api.shannon-ai.com/v1/chat/completions Chat Completions API लाई फङ्क्शन कलिङ र स्ट्रिमिङसँग प्रयोग गर्नुहोस्।
https://api.shannon-ai.com/v1/messages Claude Messages ढाँचा उपकरणहरू र anthropic-version हेडरसहित।
Authorization: Bearer <api-key> वा Claude शैलीका कलहरूका लागि X-API-Key र anthropic-version।
सार्वजनिक प्रलेखन - कल गर्न की आवश्यक स्ट्रिमिङ, फङ्क्शन कलिङ, संरचित आउटपुट, वेब खोज।
लन्च चेकलिस्ट
- + सेटअपSDK लाई Shannon तर्फ देखाउनुहोस्baseURL लाई माथिको OpenAI वा Anthropic एन्डपोइन्टमा सेट गर्नुहोस्।
- + सुरक्षाआफ्नो API की जोड्नुहोस्OpenAI कलका लागि Bearer टोकन वा X-API-Key + anthropic-version प्रयोग गर्नुहोस्।
- + क्षमताहरूउपकरण र संरचित आउटपुट सक्षम गर्नुहोस्OpenAI tools/functions, JSON schema र built-in web_search समर्थन गर्छ।
- + विश्लेषणप्रयोग ट्र्याक गर्नुहोस्साइन इन भएपछि यस पृष्ठमा टोकन र खोज खर्च हेर्नुहोस्।
क्षमताहरू
OpenAI + AnthropicOpenAI र Anthropic API हरूको drop-in प्रतिस्थापन; उपकरण, संरचित आउटपुट र built-in वेब खोज समर्थन।
फङ्क्शन कलिङ
उपकरणहरूउपकरणहरू परिभाषित गर्नुहोस्, Shannon लाई तिनीहरू कल गर्न दिनुहोस्। auto, forced, none मोडहरू समर्थित छन्।
निर्मित वेब खोज
खोजस्रोत उद्धरणसहित वास्तविक समय वेब खोज। स्वतः उपलब्ध।
संरचित आउटपुट
JSONविश्वसनीय डेटा निकासीका लागि JSON मोड र JSON Schema लागू।
बहु-चरण उपकरणहरू
एजेन्टिकस्वचालित फङ्क्शन एक्सिक्युशन लूपहरू। प्रति अनुरोध 10 पुनरावृत्तिसम्म।
स्ट्रिमिङ
द्रुतरियल-टाइम टोकन स्ट्रिमिङका लागि Server-sent events।
छिटो सुरु
5 मिनेटतीन चरणमा सुरु गर्नुहोस्। Shannon ले OpenAI र Anthropic क्लाइन्टहरू प्रतिबिम्बित गर्छ।
1
Base URL सेट गर्नुहोस्
OpenAI-अनुकूल endpoint प्रयोग गर्नुहोस्।
https://api.shannon-ai.com/v1/chat/completions 2
API की थप्नुहोस्
Authorization हेडरमा Bearer auth प्रयोग गर्नुहोस्।
3
पहिलो सन्देश पठाउनुहोस्
भाषा छान्नुहोस् र आफ्नो की परिवर्तन गर्नुहोस्।
Python
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) JavaScript
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); Go
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
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
}'जवाफ ढाँचा
सफल जवाफ
{
"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
}
}API Playground
नयाँShannon API लाई ब्राउजरमै परीक्षण गर्नुहोस्। आफ्नो अनुरोध बनाउनुहोस्, चलाउनुहोस् र वास्तविक समयको जवाफ हेर्नुहोस्।
1
Chat, Responses, Messages
Switch across OpenAI Chat Completions, Responses, and Anthropic Messages without leaving the playground.
2
Stream live output
Run real requests, inspect raw JSON, and view stream events from the same operator console.
3
Reuse your key
Signed-in users can pull their Shannon API key straight into the dedicated playground workspace.
/ne/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.
प्रमाणीकरण
सबै API अनुरोधहरूमा तपाईंको Shannon API की प्रयोग गरी प्रमाणीकरण आवश्यक छ।
OpenAI ढाँचा (सिफारिस गरिएको)
HTTP
Authorization: Bearer YOUR_API_KEYAnthropic ढाँचा
HTTP
X-API-Key: YOUR_API_KEY
anthropic-version: 2023-06-01मोडेलहरू
Shannon ले विभिन्न उपयोगका लागि अप्टिमाइज्ड धेरै मोडेलहरू प्रदान गर्छ।
shannon-1.6-lite Shannon 1.6 Lite दैनिक कामका लागि छिटो र कुशल जवाफ
shannon-1.6-pro Shannon 1.6 Pro जटिल समस्याका लागि उन्नत तर्क
shannon-2-lite Shannon 2 Lite
shannon-2-pro Shannon 2 Pro
shannon-coder-1 Shannon Coder Claude Code CLI का लागि कल-आधारित कोटासहित अनुकूलित
कल-आधारित कोटा
फङ्क्शन कलिङ
Shannon ले कार्यहरू गर्न वा जानकारी ल्याउन कल गर्न सक्ने उपकरणहरू परिभाषित गर्नुहोस्।
Python
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}") JavaScript
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);
}उपकरण छनोट विकल्पहरू
फङ्क्शन कल जवाफ
मोडेलले फङ्क्शन कल गर्दा
{
"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"
}
]
}संरचित आउटपुट
Shannon लाई तपाईंको schema अनुसार मान्य JSON फर्काउन बाध्य गर्नुहोस्।
Python
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"} JavaScript
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" }जवाफ ढाँचा विकल्पहरू
स्ट्रिमिङ
उत्तरदायी UI का लागि Server-Sent Events सँग रियल-टाइम टोकन स्ट्रिमिङ सक्षम गर्नुहोस्।
Python
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) JavaScript
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);
} टिप: स्ट्रिमिङ जवाफहरू Server-Sent Events रूपमा आउँछन्। प्रत्येक अंशमा आंशिक सामग्रीको delta हुन्छ।
निर्मित वेब खोज
Shannon ले स्वचालित रूपमा उपलब्ध web_search फङ्क्शन समेट्छ।
Python
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 JavaScript
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 Pro टिप: वेब खोज परिणामहरूमा उद्धरणहरू हुन्छन्। Shannon ले स्वचालित रूपमा स्रोतहरू उद्धृत गर्छ।
Anthropic ढाँचा
Shannon ले Anthropic Messages API ढाँचालाई पनि समर्थन गर्छ।
https://api.shannon-ai.com/v1/messages Python
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) JavaScript
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); आवश्यक हेडर: Anthropic ढाँचाका लागि anthropic-version: 2023-06-01 आवश्यक हुन्छ।
CLI Coding Agents
NEWUse Shannon as the AI backend for popular CLI coding agents. Read files, edit code, run tests — all powered by Shannon's API.
CLI Claude Code
Anthropic's official CLI coding agent. Point it at Shannon to use as your AI backend for reading, editing, and running code directly in your terminal.
ANTHROPIC_BASE_URL=https://api.shannon-ai.com ANTHROPIC_API_KEY=sk-YOUR_KEY claude --bare CLI Codex CLI
OpenAI's open-source coding agent. Uses the Responses API for multi-turn tool use, file editing, and shell commands — all routed through Shannon.
OPENAI_BASE_URL=https://api.shannon-ai.com/v1 OPENAI_API_KEY=sk-YOUR_KEY codex Claude Code
Anthropic's official CLI coding agent. Set two environment variables and launch with --bare to skip Anthropic account login.
Bash
# Install Claude Code (requires Node.js 18+)
npm install -g @anthropic-ai/claude-code
# Connect to Shannon AI as backend
export ANTHROPIC_BASE_URL=https://api.shannon-ai.com
export ANTHROPIC_API_KEY=sk-YOUR_API_KEY
# Launch Claude Code in bare mode (no Anthropic account needed)
claude --bare
# Or run a one-shot command
claude --bare -p "Explain this codebase"
# Claude Code will use Shannon's Anthropic-compatible API
# for all AI operations: reading files, editing code,
# running tests, and multi-turn tool use. Shell Config
# Alternative: set env vars permanently in your shell profile
# ~/.bashrc or ~/.zshrc
export ANTHROPIC_BASE_URL=https://api.shannon-ai.com
export ANTHROPIC_API_KEY=sk-YOUR_API_KEY
# Then just run:
claude --bare
# Supported features through Shannon:
# - Multi-turn conversations with full context
# - File reading and editing (tool use)
# - Shell command execution
# - Streaming responses
# - All Claude Code slash commands (/compact, /clear, etc.)Codex CLI
OpenAI's open-source coding agent. Uses the Responses API for multi-turn tool use, file editing, and shell commands.
Bash
# Install Codex CLI
npm install -g @openai/codex
# Connect to Shannon AI as backend
export OPENAI_BASE_URL=https://api.shannon-ai.com/v1
export OPENAI_API_KEY=sk-YOUR_API_KEY
# Launch Codex
codex
# Or run a one-shot command
codex "fix the bug in main.py"
# Codex uses the Responses API (POST /v1/responses)
# Shannon handles tool calls including:
# - Reading and writing files
# - Running shell commands
# - Multi-turn function calling Shell Config
# Alternative: set env vars permanently
# ~/.bashrc or ~/.zshrc
export OPENAI_BASE_URL=https://api.shannon-ai.com/v1
export OPENAI_API_KEY=sk-YOUR_API_KEY
# Then just run:
codex
# Supported features through Shannon:
# - Responses API with full tool use
# - Function calling (file read/write, shell exec)
# - Streaming with real-time output
# - Multi-turn conversations
# - All Codex approval modes (suggest, auto-edit, full-auto) How It Works: Both tools send standard API requests (Anthropic Messages or OpenAI Responses) to Shannon. Shannon routes them through Gemini with full tool-use support. No Anthropic or OpenAI account needed — just your Shannon API key.
SDKहरू
अनुकूलकुनै पनि OpenAI वा Anthropic SDK प्रयोग गर्नुहोस् — केवल base URL परिवर्तन गर्नुहोस्।
OpenAI-अनुकूल SDKहरू
SDK Python
आधिकारिक OpenAI Python SDK — Shannon सँग काम गर्छ
pip install openai SDK JavaScript / TypeScript
आधिकारिक OpenAI Node.js SDK — Shannon सँग काम गर्छ
npm install openai SDK Go
OpenAI-अनुकूल API का लागि समुदाय Go क्लाइन्ट
go get github.com/sashabaranov/go-openai SDK Ruby
OpenAI-अनुकूल API का लागि समुदाय Ruby क्लाइन्ट
gem install ruby-openai SDK PHP
OpenAI-अनुकूल API का लागि समुदाय PHP क्लाइन्ट
composer require openai-php/client SDK Rust
OpenAI-अनुकूल API का लागि Async Rust क्लाइन्ट
cargo add async-openai Anthropic-अनुकूल SDKहरू
SDK Python (Anthropic)
आधिकारिक Anthropic Python SDK — Shannon सँग काम गर्छ
pip install anthropic SDK TypeScript (Anthropic)
आधिकारिक Anthropic TypeScript SDK — Shannon सँग काम गर्छ
npm install @anthropic-ai/sdk त्रुटि व्यवस्थापन
Shannon ले मानक HTTP स्थिति कोड प्रयोग गर्छ र विस्तृत त्रुटि सन्देश फिर्ता गर्छ।
400 गलत अनुरोध अनुरोध ढाँचा वा प्यारामिटरहरू अमान्य छन्
401 अनधिकृत API की अमान्य वा हराएको
402 कोटा नाघ्यो टोकन वा खोज कोटा नाघ्यो
429 रेट सीमा धेरै अनुरोध, कृपया ढिलो गर्नुहोस्
500 सर्भर त्रुटि आन्तरिक त्रुटि, पछि प्रयास गर्नुहोस्
त्रुटि जवाफ ढाँचा
त्रुटि जवाफ
{
"error": {
"message": "Invalid API key provided",
"type": "authentication_error",
"code": "invalid_api_key"
}
}परिवर्तन सूची
LOGShannon API को हालैका अपडेट र सुधारहरू।
v2.2.0
2026-03-28 - नयाँ Claude Code support — use Shannon as your Anthropic backend for the official CLI coding agent
- नयाँ Codex CLI support — full Responses API with multi-turn tool use for OpenAI's coding agent
- सुधारिएको Anthropic streaming format fixes — proper content_block lifecycle, tool_use deltas, toolu_ prefixes
- सुधारिएको Schema sanitization for Gemini — strips $schema, additionalProperties, $ref and other unsupported fields from tool schemas
v2.1.0
2025-01-03 - नयाँ Claude Code CLI एकीकरणका लागि shannon-coder-1 मोडेल थपियो
- नयाँ Coder मोडेलका लागि कल-आधारित कोटा प्रणाली
- सुधारिएको फङ्क्शन कलिङको विश्वसनीयता सुधारियो
v2.0.0
2024-12-15 - नयाँ Anthropic Messages API अनुकूलता थपियो
- नयाँ बहु-चरण उपकरण कार्यान्वयन (१० पुनरावृत्तिसम्म)
- नयाँ JSON Schema जवाफ ढाँचा समर्थन
- सुधारिएको उत्तम उद्धरणहरूसहित वेब खोज सुधारियो
v1.5.0
2024-11-20 - नयाँ जटिल तर्कका लागि shannon-deep-dapo मोडेल थपियो
- नयाँ निर्मित web_search फङ्क्शन
- सुधारिएको स्ट्रिमिङ जवाफको विलम्ब घटाइयो
v1.0.0
2024-10-01 - नयाँ API प्रारम्भिक रिलीज
- नयाँ OpenAI-अनुकूल chat completions endpoint
- नयाँ फङ्क्शन कलिङ समर्थन
- नयाँ Server-Sent Events मार्फत स्ट्रिमिङ
तपाईंको API की
प्रवेश OpenAI कलका लागि Bearer टोकन वा X-API-Key + anthropic-version प्रयोग गर्नुहोस्।
YOUR_API_KEY आफ्नो API की गोप्य राख्नुहोस्। पुनःजेनरेट गर्दा नयाँ की बन्न्छ र पुरानो अमान्य हुन्छ।
तपाईंको प्रयोग
साइन इन भएपछि यस पृष्ठमा टोकन र खोज खर्च हेर्नुहोस्।
-- API कलहरू
-- प्रयोग गरिएका टोकनहरू
Shannon Coder (shannon-coder-1)
Shannon Coder (shannon-coder-1) का लागि कल-आधारित कोटा। प्रत्येक 4 घण्टामा रिसेट हुन्छ।
0 प्रयोग गरिएका कल
0 बाँकी कल
बनाउन तयार हुनुहुन्छ?
API की प्राप्त गर्नुहोस् र आजै Shannon AI सँग बनाउनुहोस्।
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