Aevum Python SDK

Quick Start

Initialize the client and make your first API call. The SDK handles authentication, retries, and pagination automatically.

import os
from aevum import AevumClient

# Initialize with your API key
client = AevumClient(api_key=os.getenv("AEVUM_API_KEY"))

# Fetch a verified article
article = client.articles.get("quantum_computing")
print(article.title)
print(article.summary)
print(article.last_updated)

# Semantic search with AI ranking
results = client.search.query(
    q="CRISPR gene editing mechanisms",
    language="en",
    limit=5,
    ai_rank=True
)

for hit in results:
    print(f"{hit.title} [{hit.relevance_score}]")

# Explore connected concepts
graph = client.graph.explore("behavioral_economics", depth=2)

for node in graph.nodes:
    print(f"Concept: {node.id}")
    for edge in node.edges:
        print(f"  └─ {edge.type} → {edge.target}")

Authentication

Authenticate using an API key from your Aevum Dashboard. We recommend using environment variables for security.

# .env file
AEVUM_API_KEY=your_live_api_key_here

# Python
import os
from aevum import AevumClient

client = AevumClient(
    api_key=os.getenv("AEVUM_API_KEY"),
    environment="production" # or "sandbox"
)

Core Features

• AI-Powered Search — Context-aware queries with relevance scoring and auto-correction
• Knowledge Graphs — Programmatic access to semantic relationships between 2.4M+ entities
• Multilingual Support — Fetch, translate, and compare articles across 140+ languages
• Real-time Sync — Webhooks and polling for live updates on trending topics
• Async & Sync APIs — `asyncio`-compatible methods for high-throughput applications

Async Example

import asyncio
from aevum import AsyncAevumClient

async def main():
    client = AsyncAevumClient(api_key="...")
    # Fetch multiple articles concurrently
    tasks = [client.articles.get(slug) for slug in [
        "machine_learning", "renaissance_art", "climate_science"
    ]]
    results = await asyncio.gather(*tasks)
    print(f"Fetched {len(results)} articles")

asyncio.run(main())

Error Handling & Rate Limits

The SDK raises specific exceptions for network issues, authentication failures, and API limits. All clients include automatic retry logic with exponential backoff.

from aevum.exceptions import AevumError, RateLimitError, NotFoundError

try:
    data = client.search.query("nonexistent_topic")
except NotFoundError:
    print("Topic not found in the encyclopedia.")
except RateLimitError as e:
    print(f"Retry after {e.retry_after} seconds")
except AevumError as e:
    print(f"API Error: {e.message}")

Advanced Configuration

Customize timeouts, proxies, caching, and request headers to match your infrastructure.

client = AevumClient(
    api_key="...",
    timeout=15.0,
    retries=3,
    cache_enabled=True,
    proxy="http://proxy.internal:8080",
    headers={"X-Custom-App": "my-research-tool"}
)