LLM Providers¶

mnesis uses litellm internally, which means it works with any provider litellm supports — Anthropic, OpenAI, Google Gemini, OpenRouter, Azure, and more. You never interact with litellm directly; just pass a model string and set the corresponding API key.

Model string format¶

"<provider>/<model-name>"

Provider	Example model string	API key env var
Anthropic	`"anthropic/claude-opus-4-6"`	`ANTHROPIC_API_KEY`
OpenAI	`"openai/gpt-4o"`	`OPENAI_API_KEY`
Google Gemini	`"gemini/gemini-1.5-pro"`	`GEMINI_API_KEY`
OpenRouter	`"openrouter/anthropic/claude-opus-4-6"`	`OPENROUTER_API_KEY`
Azure OpenAI	`"azure/<your-deployment>"`	`AZURE_API_KEY` + `AZURE_API_BASE`

The provider prefix is optional for well-known model names (e.g. "gpt-4o" resolves to OpenAI automatically), but the full form is recommended for clarity.

Examples¶

AnthropicOpenAIGoogle GeminiOpenRouter

import os
from mnesis import MnesisSession

os.environ["ANTHROPIC_API_KEY"] = "sk-ant-..."
session = await MnesisSession.create(model="anthropic/claude-opus-4-6")

import os
from mnesis import MnesisSession

os.environ["OPENAI_API_KEY"] = "sk-..."
session = await MnesisSession.create(model="openai/gpt-4o")

import os
from mnesis import MnesisSession

os.environ["GEMINI_API_KEY"] = "AIza..."
session = await MnesisSession.create(model="gemini/gemini-1.5-pro")

import os
from mnesis import MnesisSession

os.environ["OPENROUTER_API_KEY"] = "sk-or-..."
session = await MnesisSession.create(
    model="openrouter/meta-llama/llama-3.1-70b-instruct"
)

Using a cheaper model for compaction¶

Compaction (context summarisation) defaults to the session model. You can point it at a cheaper, faster model to save cost:

from mnesis import MnesisSession, MnesisConfig, CompactionConfig

config = MnesisConfig(
    compaction=CompactionConfig(
        compaction_model="openai/gpt-4o-mini",
    )
)
session = await MnesisSession.create(model="openai/gpt-4o", config=config)

Passing extra litellm parameters¶

For provider-specific options (custom api_base, extra headers for OpenRouter, etc.), configure litellm globally before creating a session:

import litellm

litellm.api_base = "https://my-proxy.example.com"
litellm.headers = {"X-Custom-Header": "value"}

See the litellm provider docs for the full list of supported providers and their options.

Prefer your own SDK?¶

If you want to use the Anthropic, OpenAI, or another SDK directly for LLM calls, see BYO-LLM — mnesis can act as a pure memory/compaction layer without routing calls through litellm at all.