Back to browse
GitHub Repository

Minimalistic, provider-agnostic, AI python library

3 starsPython

Xecai, a minimal Python interface for LLM providers for RAG systems

by adrianvi·Mar 17, 2026·1 point·0 comments

AI Analysis

MidShip It

LangChain alternative, but LiteLLM and LlamaIndex already cover this.

Strengths
  • Intentionally minimal abstraction layer avoids LangChain's complexity.
  • Common error handling across OpenAI, Anthropic, Google, and AWS.
Weaknesses
  • Zero stars and forks suggests limited real-world adoption.
  • No agent functionality limits usefulness for complex workflows.
Category
Target Audience

Python developers building RAG systems

Similar To

LiteLLM · LlamaIndex · Haystack

Post Description

A small python library to simplify LLM calls, database retrieval, reranking, conversation storage & embeddings when building RAG systems.

The library intentionally exposes only the functionality common across providers to avoid provider-specific parameters.

Libraries like LangChain provide many integrations but often rely on many abstractions, heavy use of kwargs, and complex code that can be difficult to customize.

Features: - Sync and async APIs - LLM calls: invoke and stream (temperature, reasoning level) - Response metadata: answer, token usage, stop reason - RAG documents: retrieval, reranking, embeddings - Chat history: conversation store - Common error handling across providers - Providers: OpenAI, Anthropic, Google, AWS

Retry logic is left to the user (see README). Agent functionality is not supported yet.

Similar Projects

AI/ML●●Solid

Stop Using LangChain

LangChain alternative with 2 dependencies and async-native architecture from the start.

Big BrainSolve My Problem
aminau
302mo ago
Security●●●Banger

GuardLLM, hardened tool calls for LLM apps

Lifecycle-aware security pipeline, not point tools—shared context from ingress through output.

Big BrainSolve My ProblemWizardry
mhcoen
104mo ago