keystone-ai 0.2.1

Python SDK for Nexus AI Platform - The keystone of your AI applications

Nexus AI Python SDK

Official Python SDK for Nexus AI - A unified AI capabilities platform.

🎉 Stable Release v0.2.1

Production Ready - 95.2% test pass rate with 100% P0 core features passing.

Installation:

pip install keystone-ai

Quick Start:

from nexusai import NexusAIClient

client = NexusAIClient(api_key="your_api_key")
response = client.text.generate("Hello, AI!")
print(response.text)

Features

• 🚀 Simple & Intuitive - Clean API design with sensible defaults
• 🔄 Multi-Model Support - 6 text models + 2 image models
• 📡 Streaming - Real-time streaming for text generation
• 💬 Session Management - Stateful conversations with automatic context handling
• 🧠 Knowledge Bases - RAG capabilities with semantic search
• 🎨 Multi-Modal - Text, images, audio (ASR), and document processing
• 🔐 Type-Safe - Full type hints with Pydantic models
• 🌐 Production Ready - Defaults to production API at https://nexus-ai.juncai-ai.com/api/v1

Installation

pip install keystone-ai

国内镜像加速:

# 清华镜像
pip install keystone-ai -i https://pypi.tuna.tsinghua.edu.cn/simple

# 阿里云镜像
pip install keystone-ai -i https://mirrors.aliyun.com/pypi/simple/

从源码安装:

git clone https://github.com/nexus-ai/python-sdk.git
cd python-sdk
poetry install

Quick Start

1. Set up your API key

Create a .env file in your project root:

NEXUS_API_KEY=nxs_your_api_key_here
# SDK automatically uses production: https://nexus-ai.juncai-ai.com/api/v1
# For local development, set: NEXUS_BASE_URL=http://localhost:8000/api/v1

2. Initialize the client

from nexusai import NexusAIClient

# Simple - uses production API automatically
client = NexusAIClient(api_key="nxs_your_api_key")

# Or read from environment variables
client = NexusAIClient()

# For local development
client = NexusAIClient(
    api_key="nxs_your_api_key",
    base_url="http://localhost:8000/api/v1"
)

3. Generate text

# Simple mode (省心模式) - uses default model
response = client.text.generate("写一首关于春天的诗")
print(response.text)

# With model selection
response = client.text.generate(
    prompt="Explain quantum computing",
    model="gpt-5-mini",       # Recommended: fast and cost-effective
    temperature=0.7,
    max_tokens=500
)
print(response.text)
print(f"Tokens used: {response.usage.total_tokens}")

# Available models (三档体系):
# 🥇 高端: "gpt-5" (fastest premium), "gemini-2.5-pro" (strongest reasoning)
# 🥈 中端: "gpt-5-mini" (recommended), "gpt-4o-mini" (alternative)
# 🥉 经济: "deepseek-v3.2-exp" (cheapest)

4. Stream text generation

for chunk in client.text.stream("Tell me a story"):
    if "delta" in chunk:
        print(chunk["delta"].get("content", ""), end="", flush=True)
print()

5. Work with sessions (conversations)

# Create a session
session = client.sessions.create(
    name="My Chat",
    agent_config={
        "model": "gpt-5-mini",   # Recommended model for conversations
        "temperature": 0.7
    }
)

# Have a conversation
response = session.invoke("My name is Alice")
print(response.response.content)

response = session.invoke("What's my name?")
print(response.response.content)  # Remembers "Alice"

# Get conversation history
history = session.history()
for message in history:
    print(f"{message.role}: {message.content}")

6. Generate images

# Simple mode
image = client.image.generate("A futuristic city")
print(image.url)

# With options
image = client.image.generate(
    prompt="A sunset over mountains, digital art",
    model="doubao-seedream-4-0-250828",  # Default recommended model (ByteDance Doubao)
    aspect_ratio="16:9",                  # Use ratio instead of pixel size
    num_images=1
)
print(f"Image: {image.url}")

# Supported aspect ratios: "1:1", "16:9", "9:16", "4:3", "3:4", "21:9"
# Image models: "doubao-seedream-4-0-250828" (default), "gemini-2.5-flash-image" (alternative)

7. Speech-to-Text (ASR)

# Upload audio file
file_meta = client.files.upload("meeting.mp3")

# Transcribe
transcription = client.audio.transcribe(
    file_id=file_meta.file_id,
    language="zh"
)
print(transcription.text)

8. Knowledge Base & RAG

# Create knowledge base
kb = client.knowledge_bases.create(
    name="Company Docs",
    description="Internal documentation"
)

# Upload documents (uses unified file architecture internally)
task = client.knowledge_bases.upload_document(
    kb_id=kb.kb_id,
    file="policy.pdf"
)

# Or use two-step process for file reuse
file_meta = client.files.upload("policy.pdf")
task = client.knowledge_bases.add_document(kb.kb_id, file_meta.file_id)
# Same file can be added to multiple knowledge bases!

# Search
results = client.knowledge_bases.search(
    query="What is the vacation policy?",
    knowledge_base_ids=[kb.kb_id],
    top_k=3
)

# Use results for RAG
context = "\n\n".join([r.content for r in results.results])
answer = client.text.generate(
    prompt=f"Based on this context:\n{context}\n\nQuestion: What is the vacation policy?"
)
print(answer.text)

Configuration

The SDK can be configured via environment variables or constructor parameters:

Environment Variable	Default	Description
NEXUS_API_KEY	(required)	Your API key
NEXUS_BASE_URL	https://nexus-ai.juncai-ai.com/api/v1	API base URL
NEXUS_TIMEOUT	30	Request timeout (seconds)
NEXUS_MAX_RETRIES	3	Maximum retry attempts
NEXUS_POLL_INTERVAL	2	Task polling interval (seconds)
NEXUS_POLL_TIMEOUT	300	Task polling timeout (seconds)

Production vs Development Mode

Production Mode (Default):

# Uses production API by default - zero configuration needed!
client = NexusAIClient(api_key="nxs_your_api_key")
# → Connects to https://nexus-ai.juncai-ai.com/api/v1

Local Development Mode:

# Set environment variable
export NEXUS_BASE_URL=http://localhost:8000/api/v1

Or in code:

client = NexusAIClient(
    api_key="nxs_dev_key",
    base_url="http://localhost:8000/api/v1"
)

Error Handling

The SDK provides specific exception types for different error scenarios:

from nexusai import NexusAIClient
from nexusai.error import (
    AuthenticationError,
    RateLimitError,
    NotFoundError,
    APITimeoutError,
)

client = NexusAIClient()

try:
    response = client.text.generate("Hello")
except AuthenticationError:
    print("Invalid API key")
except RateLimitError as e:
    print(f"Rate limited. Retry after {e.retry_after}s")
except NotFoundError:
    print("Resource not found")
except APITimeoutError:
    print("Request timed out")
except Exception as e:
    print(f"Unexpected error: {e}")

Context Manager

The client supports context manager for automatic cleanup:

with NexusAIClient() as client:
    response = client.text.generate("Hello")
    print(response.text)
# Client automatically closed

API Reference

For detailed API documentation, see docs/api_reference.md.

Examples

Check out the examples/ directory for more usage examples:

• basic_usage.py - Core features demonstration
• streaming_example.py - Streaming text generation
• session_chat.py - Multi-turn conversations
• knowledge_base_rag.py - RAG with knowledge bases

Requirements

• Python 3.8+
• httpx >= 0.25.0
• pydantic >= 2.5.0
• python-dotenv >= 1.0.0

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• Documentation: https://nexus-ai.juncai-ai.com/docs
• Issues: https://github.com/nexus-ai/python-sdk/issues
• Email: [e-mail]

Changelog

v0.1.0 (2025-01-03)

• Initial release
• Text generation (sync, async, streaming)
• Image generation
• Session management
• Audio processing (ASR/TTS)
• Knowledge base management
• File upload system
• Full type hints with Pydantic