cross-ai-core 0.6.0

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 (Grok), 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

Install only the provider(s) you need:

pip install "cross-ai-core[anthropic]"   # Claude
pip install "cross-ai-core[gemini]"      # Google Gemini
pip install "cross-ai-core[openai]"      # OpenAI (ChatGPT)
pip install "cross-ai-core[xai]"         # xAI Grok  (uses the OpenAI SDK)
pip install cross-ai-core                # Perplexity only (uses requests, no extra SDK)

Install all providers at once (used by cross-st, which runs all 5 simultaneously):

pip install "cross-ai-core[all]"

Dependencies

requests is always installed — it is used for the Perplexity provider and general HTTP.
The three provider SDKs are optional extras; pip installs only what you request.

Extra	Package	Version	Providers covered
(base)	requests	≥2.32.4	Perplexity
[anthropic]	anthropic	≥0.84.0	Anthropic / Claude
[gemini]	google-genai	≥1.65.0	Google Gemini
[openai]	openai	≥1.70.0	OpenAI
[xai]	openai	≥1.70.0	xAI / Grok (OpenAI-compatible API)
[all]	all three above	—	All 5 providers

Quick start

import os
from dotenv import load_dotenv
load_dotenv(os.path.expanduser("~/.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.",
    system="You are a concise technical writer.",   # omit to use each provider's default
    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.
You only need to set API keys for the providers you actually use.

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")

Development

cd ~/github/cross-ai-core
python3.11 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"     # installs the package + pytest + pytest-mock

Run the test suite:

python -m pytest tests/ -v

Tests use mocks — no real API keys required.

Note: Keep each repo's .venv separate; do not share it with dependent projects.

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.

Documentation

• API reference — all public functions, AIResponse, parallel calls, error handling
• Providers — per-provider guide: models, API keys, strengths, free tiers
• Changelog

Used by

Project	PyPI	Description
cross-st	cross-st	Multi-AI research reports with cross-product fact-checking. Installs this package automatically via cross-ai-core[all]. Full CLI toolkit — pipx install cross-st.

Building something with cross-ai-core? Open a PR or issue to get listed here.

License

MIT — free for personal, academic, and open-source use.
See COMMERCIAL_LICENSE.md for organizational and commercial use.