scitex-genai 0.1.0

SciTeX GenAI — modality-organised generative-AI provider abstraction (LLM, agents, image/audio/video stubs)

scitex-genai

Modality-organised generative-AI provider abstraction for scientific research.

Full Documentation · pip install scitex-genai

---

Problem and Solution

#	Problem	Solution
1	Per-provider boilerplate — every project re-writes thin wrappers around openai, anthropic, google.genai, groq, etc., each with subtly different cost / streaming / history semantics.	Unified GenAI factory — same call shape across OpenAI, Anthropic, Google, Groq, DeepSeek, Perplexity, Llama. Cost tracking, conversation history, and message formatting are provider-agnostic.
2	Modality fragmentation — generative AI is splintering by modality (text, agents, image, audio, video, embeddings, multimodal); ad-hoc namespaces age badly.	Modality-organised layout — scitex_genai.{llm,agent,image,audio,video,embed,multimodal} is the public top-level shape from day one. Reserved namespaces import successfully but raise NotImplementedError until features land, so import paths never need to migrate.
3	Heavy LLM SDKs leak into ML workflows — pulling in scikit-learn shouldn't pull openai and friends, and vice versa.	Split package — classical / deep ML lives in scitex-ml; scitex-genai carries only generative-AI deps.
4	Future-proofing for litellm + Ollama — locking the public API to one provider SDK closes off cheap routing improvements.	Litellm-ready façade — the planned llm rewrite routes through litellm, giving 100+ providers with one OpenAI-compatible interface (Ollama is just model="ollama/llama3") without changing the GenAI(...) call surface.

Installation

pip install scitex-genai            # core (LLM providers)
pip install scitex-genai[agent]     # + claude-agent-sdk (forthcoming `agent` submodule)
pip install scitex-genai[litellm]   # + litellm router (preview)
pip install scitex-genai[ollama]    # + local ollama
pip install scitex-genai[all]       # everything available today

Through the umbrella: pip install scitex[genai]. Requires Python ≥ 3.10.

Quick Start

import scitex_genai

ai = scitex_genai.GenAI(model="gpt-4o-mini")
print(ai("Explain neural networks in one sentence."))
print("cost USD:", ai.cost)

# Switch backends without changing the call shape:
ai = scitex_genai.GenAI(model="claude-sonnet-4-6")
ai("Same call, different provider.")

For a runnable walk-through see examples/01_genai.ipynb.

Demo

A runnable provider walk-through (init GenAI, single completion, cost summary, provider switch) lives in examples/01_genai.ipynb. Each cell skips gracefully when the relevant API key is unset.

flowchart LR
    User[your code] -->|GenAI(model)| Factory[scitex_genai.llm.GenAI]
    Factory -->|dispatch| OpenAI[OpenAI]
    Factory --> Anthropic[Anthropic]
    Factory --> Google[Google]
    Factory --> Groq[Groq]
    Factory --> DeepSeek[DeepSeek]
    Factory --> Perplexity[Perplexity]
    Factory --> Llama[Llama]
    OpenAI -.->|tokens / cost| Tracker[BaseGenAI<br/>cost + history]
    Anthropic -.-> Tracker
    Google -.-> Tracker
    Groq -.-> Tracker
    Tracker --> Out[ai&#40;...&#41; · ai.cost · ai.history]

A second examples/example_genai.py runs the same flow as a script and is wired into tests/examples/test_example_genai.py for CI smoke coverage.

Architecture

scitex-genai is organised top-down by modality, not by provider:

scitex-python (umbrella)
    └── scitex.genai ── thin sys.modules-aliasing shim
                        └── scitex_genai (this package)
                              ├── llm/         provider factory ``GenAI``
                              │                 ├── _BaseGenAI         common interface
                              │                 ├── _OpenAI / _Anthropic / _Google /
                              │                 │   _Groq / _DeepSeek / _Perplexity / _Llama
                              │                 ├── _PARAMS            model catalogue
                              │                 ├── _calc_cost         token-cost accounting
                              │                 └── _format_output_func text/markdown formatting
                              ├── agent/        reserved (claude-agent-sdk wrapper planned)
                              ├── image/        reserved
                              ├── audio/        reserved
                              ├── video/        reserved
                              ├── embed/        reserved
                              └── multimodal/   reserved

Reserved modality namespaces import successfully but raise NotImplementedError on attribute access, so the public import paths are stable as features land. Provider SDKs (openai, anthropic, google-genai, groq) are eager core dependencies today; a follow-up will route llm/ through litellm to demote them to optional and add Ollama out of the box.

Modality layout

Submodule	Status	Notes
scitex_genai.llm	✅ implemented	Provider factory GenAI. Litellm-backed in a follow-up.
scitex_genai.agent	🔒 reserved	Wrapper over claude-agent-sdk and friends planned.
scitex_genai.image	🔒 reserved	Image generation / editing.
scitex_genai.audio	🔒 reserved	TTS / STT / music.
scitex_genai.video	🔒 reserved	Video generation.
scitex_genai.embed	🔒 reserved	Embeddings.
scitex_genai.multimodal	🔒 reserved	Any-to-any unified models.

Reserved namespaces import successfully but raise NotImplementedError on attribute access — import paths are stable as features land.

4 Interfaces

Python API ⭐⭐⭐ (primary)

from scitex_genai import GenAI

ai = GenAI(model="gpt-4o-mini")
print(ai("..."))
print("cost USD:", ai.cost)

Full API reference

CLI ⭐ — none

scitex-genai ships no dedicated CLI. Drive completions from Python or use the umbrella scitex CLI.

MCP ⭐ — none

No MCP server in this package today. The umbrella surfaces LLM-related MCP tools separately.

Skills ⭐⭐

Skill index for AI agents lives at src/scitex_genai/_skills/scitex-genai/SKILL.md. Sub-skill llm.md documents the provider factory.

Full skills directory

Part of SciTeX

scitex-genai is part of SciTeX. Install via the umbrella with pip install scitex[genai] to use as scitex.genai (Python).

import scitex

scitex.genai.GenAI  # same object as scitex_genai.GenAI
scitex.genai.llm    # same object as scitex_genai.llm

scitex.genai delegates to scitex_genai — they share the same API.

The SciTeX system follows the Four Freedoms for Research below, inspired by the Free Software Definition:

Four Freedoms for Research

0. The freedom to run your research anywhere — your machine, your terms.
1. The freedom to study how every step works — from raw data to final manuscript.
2. The freedom to redistribute your workflows, not just your papers.
3. The freedom to modify any module and share improvements with the community.

AGPL-3.0 — because we believe research infrastructure deserves the same freedoms as the software it runs on.

---