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llm-adapters

A minimal, auditable Python library for calling multiple LLM providers. Built as a lightweight alternative to LiteLLM after the March 2026 PyPI supply chain attack.

Why?

  • Only 2 dependencies: httpx + pydantic — no official SDKs, no bloat
  • Each provider is a single file — fully readable and auditable
  • All deps pinned with hash verification in CI
  • < 2000 lines of code — anyone can review the entire codebase in minutes

Install

pip install llm-dial

Quick Start

from llm_adapters import LLMClient

client = LLMClient()

# Unified interface — auto-routes to the correct provider
response = await client.chat(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.content)

# Streaming
async for chunk in client.chat_stream(
    model="anthropic/claude-sonnet-4-20250514",
    messages=[{"role": "user", "content": "Tell me a story"}],
):
    print(chunk.content, end="")

Supported Providers

Provider Models Auth
OpenAI GPT-4o, GPT-4, o1, o3, etc. OPENAI_API_KEY
Anthropic Claude 4, Claude 3.5, etc. ANTHROPIC_API_KEY
DeepSeek deepseek-chat, deepseek-coder DEEPSEEK_API_KEY
Ollama Any local model (llama3, mistral, etc.) None (local)

Three Ways to Use

Your app
    │
    ├── As a library: from llm_adapters import LLMClient
    │
    ├── As a proxy: app → localhost:4000 → llm-adapters serve → LLM APIs
    │       (drop-in LiteLLM sidecar replacement, zero code changes)
    │
    └── As a gateway base: app → llm-gateway → llm-adapters → LLM APIs
            (add routing / auth / rate limiting / budget / observability)

Comparison with LiteLLM

LiteLLM llm-adapters
Dependencies 100+ transitive 2 (httpx + pydantic)
Install size ~50MB <1MB
Supply chain risk Compromised March 2026 Minimal attack surface
Supported models 100+ Core 4 providers (enough for most)
Code size Tens of thousands of lines <2000 lines
Auditability Complex One file per adapter

Security

This library was born from the LiteLLM supply chain incident. We take dependency security seriously:

  • Minimal dependency tree (2 direct deps)
  • All versions pinned with SHA-256 hashes in CI
  • Automated pip-audit on every PR
  • SBOM included in releases
  • Published via GitHub Actions OIDC (Trusted Publishers) — no PyPI tokens

License

MIT

Metadata

Release files for llm-dial 0.1.4

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