anymodel-py 0.6.3

OpenRouter-compatible LLM router with unified batch support. Route requests across OpenAI, Anthropic, and Google with a single API.

anymodel-py

OpenRouter-compatible LLM router with unified batch support. Self-hosted, zero fees.

Route requests across OpenAI, Anthropic, and Google with a single API. Add any OpenAI-compatible provider. Run as an SDK or standalone HTTP server.

Why anymodel?

One SDK, 11+ providers, no vendor lock-in. Swap models by changing a string, not rewriting your integration.

Self-hosted and transparent. Your API keys, your infrastructure, zero routing fees. Unlike OpenRouter, nothing passes through a third party.

Native batch APIs (OpenAI, Anthropic, Google) run at 50% cost with zero config. For other providers, anymodel falls back to concurrent execution automatically.

Zero provider SDK dependencies. The only runtime requirement is httpx. Server mode is drop-in compatible with the OpenAI SDK, so existing code works without changes.

Install

pip install anymodel-py

For server mode, install with the server extra:

pip install anymodel-py[server]

Quick Start

Set your API keys as environment variables:

export OPENAI_API_KEY=sk-...
export ANTHROPIC_API_KEY=sk-ant-...
export GOOGLE_API_KEY=AIza...

SDK Usage

from anymodel import AnyModel

client = AnyModel()

response = await client.chat.completions.create(
    model="anthropic/claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Hello!"}],
)

print(response.choices[0].message.content)

Streaming

stream = await client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Write a haiku"}],
    stream=True,
)

async for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="", flush=True)

Supported Providers

Set the env var and go. Models are auto-discovered from each provider's API.

Provider	Env Var	Example Model
OpenAI	OPENAI_API_KEY	openai/gpt-4o
Anthropic	ANTHROPIC_API_KEY	anthropic/claude-sonnet-4-6
Google	GOOGLE_API_KEY	google/gemini-2.5-pro
Mistral	MISTRAL_API_KEY	mistral/mistral-large-latest
Groq	GROQ_API_KEY	groq/llama-3.3-70b-versatile
DeepSeek	DEEPSEEK_API_KEY	deepseek/deepseek-chat
xAI	XAI_API_KEY	xai/grok-4
Together	TOGETHER_API_KEY	together/meta-llama/Llama-3.3-70B-Instruct-Turbo
Fireworks	FIREWORKS_API_KEY	fireworks/accounts/fireworks/models/llama-v3p3-70b-instruct
Perplexity	PERPLEXITY_API_KEY	perplexity/sonar-pro
Ollama	OLLAMA_BASE_URL	ollama/llama3.3

Ollama runs locally with no API key. Just set OLLAMA_BASE_URL (defaults to http://localhost:11434/v1).

Fallback Routing

Try multiple models in order. If one fails, the next is attempted:

response = await client.chat.completions.create(
    model="",
    models=[
        "anthropic/claude-sonnet-4-6",
        "openai/gpt-4o",
        "google/gemini-2.5-pro",
    ],
    route="fallback",
    messages=[{"role": "user", "content": "Hello"}],
)

Batch Processing

Process many requests with native provider batch APIs or concurrent fallback. OpenAI, Anthropic, and Google batches run server-side at up to 50% cost. Other providers fall back to concurrent execution automatically.

Submit and wait

results = await client.batches.create_and_poll(
    model="openai/gpt-4o-mini",
    requests=[
        {"custom_id": "req-1", "messages": [{"role": "user", "content": "Summarize AI"}]},
        {"custom_id": "req-2", "messages": [{"role": "user", "content": "Summarize ML"}]},
        {"custom_id": "req-3", "messages": [{"role": "user", "content": "Summarize NLP"}]},
    ],
)

for result in results.results:
    print(result.custom_id, result.response.choices[0].message.content)

Native batches (OpenAI, Anthropic, Google) are processed asynchronously on the provider's infrastructure. For all other providers, anymodel runs requests concurrently with adaptive rate limiting. See Advanced Usage for BatchBuilder, submit-now-check-later, adaptive concurrency, and batch configuration.

Server Mode

Run as a standalone HTTP server compatible with the OpenAI SDK:

anymodel serve --port 4141

Point any OpenAI-compatible client at http://localhost:4141/api/v1. See Advanced Usage for the full endpoint reference.

Configuration

client = AnyModel(
    anthropic={"api_key": "sk-ant-..."},
    openai={"api_key": "sk-..."},
    google={"api_key": "AIza..."},
    aliases={
        "default": "anthropic/claude-sonnet-4-6",
        "fast": "anthropic/claude-haiku-4-5",
        "smart": "anthropic/claude-opus-4-6",
    },
    defaults={
        "temperature": 0.7,
        "max_tokens": 4096,
        "retries": 2,
        "timeout": 120,
    },
)

# Use aliases as model names
response = await client.chat.completions.create(
    model="fast",
    messages=[{"role": "user", "content": "Quick answer"}],
)

Configuration can also be loaded from an anymodel.config.json file. Both camelCase and snake_case keys are accepted (apiKey or api_key, pollInterval or poll_interval). See Advanced Usage for config file details and resolution order.

Built-in Resilience

• Retries: Automatic retry with exponential backoff on 429/502/503 errors (configurable via defaults.retries)
• Rate limit tracking: Per-provider rate limit state from response headers. Automatically skips rate-limited providers during fallback routing.
• Adaptive concurrency: Auto mode discovers your provider's actual rate limit ceiling using TCP-style slow-start + AIMD, reading x-ratelimit-remaining-requests headers proactively.
• Parameter translation: max_tokens automatically sent as max_completion_tokens for newer OpenAI models. Unsupported parameters stripped before forwarding.
• Smart batch defaults: Automatic max_tokens estimation per-request in batches. Calculates safe values from input size and model context limits, preventing truncation and overflow without manual tuning.
• Memory-efficient batching: Concurrent batch requests are streamed from disk. Only N requests (default 5) are in-flight at a time, making 10K+ request batches safe without memory spikes.
• High-volume IO: All batch file operations use concurrency-limited async queues with atomic durable writes (temp file + fsync + rename) to prevent corruption on crash.

See Advanced Usage for tool calling, structured output, BatchBuilder, adaptive concurrency, custom providers, transforms, generation stats, auto pricing, and more.

See Also

Package	Description
anymodel	TypeScript version of this package
anymodel-go	Go version of this package
@probeo/anyserp	Unified SERP API router for TypeScript
@probeo/workflow	Stage-based pipeline engine for TypeScript

Support

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License

MIT