cross-ai-core 0.2.0

Multi-provider AI dispatcher with response caching and error handling.

cross-ai-core

Multi-provider AI dispatcher with MD5-keyed response caching and unified error handling.

Supports Anthropic, xAI, OpenAI, Google Gemini, and Perplexity through a single consistent interface.

Requirements

• Python 3.10 or newer (3.11 recommended for development)
• No upper version limit — tested on 3.10–3.13

Install

pip install cross-ai-core

Dependencies

Package	Version	Purpose
anthropic	≥0.84.0	Anthropic / Claude API client
google-genai	≥1.65.0	Google Gemini API client
openai	≥1.70.0	OpenAI and xAI (Grok) API client
requests	≥2.32.4	HTTP for Perplexity API

Quick start

from dotenv import load_dotenv
load_dotenv("~/.crossenv")          # your app loads keys; the library reads os.environ

from cross_ai_core import process_prompt, get_content, get_default_ai

provider = get_default_ai()         # reads DEFAULT_AI from env, falls back to "xai"
result   = process_prompt(provider, "Explain transformer attention in 3 sentences.",
                          verbose=False, use_cache=True)
print(get_content(provider, result.response))

Configuration (environment variables)

Variable	Default	Purpose
DEFAULT_AI	xai	Default provider when none is specified
XAI_API_KEY	—	xAI / Grok API key
ANTHROPIC_API_KEY	—	Anthropic / Claude API key
OPENAI_API_KEY	—	OpenAI API key
GEMINI_API_KEY	—	Google Gemini API key
PERPLEXITY_API_KEY	—	Perplexity API key
CROSS_API_CACHE_DIR	~/.cross_api_cache/	Response cache directory
CROSS_NO_CACHE	—	Set to 1 to disable caching globally

The library only reads from os.environ — it never calls load_dotenv() itself.
Load your .env or ~/.crossenv before importing.

Caching

Responses are cached by MD5 hash of the request payload in ~/.cross_api_cache/.
The cache is safe to delete at any time.

# Bypass cache for one call
result = process_prompt(provider, prompt, verbose=False, use_cache=False)

# Check if a response was served from cache
if result.was_cached:
    print("from cache")

Adding a provider

1. Create cross_ai_core/ai_<name>.py implementing BaseAIHandler (get_payload, get_client, get_cached_response, get_model, get_make, get_content, put_content, get_data_content, get_title, get_usage).
2. Register in cross_ai_core/ai_handler.py: add to AI_HANDLER_REGISTRY and AI_LIST.

License

MIT