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Llama API Benchmark

Project description

llama_api_bench

PyPI - Version PyPI - Python Version

Table of Contents

Installation

pip install llama-api-bench

Install from source

pip install -e .

# dev
pip install -e ".[dev]"

Usage

Run All

llama-api-bench run-all

Run Subset

  • Run on a specific criteria for all models and providers
llama-api-bench run-criteria --criteria tool_call
  • Run on a specific test case data for all models and providers
llama-api-bench run-test-case --test-case tool_call_get_weather
  • Run all test cases on a specific provider
llama-api-bench run-provider --provider openrouter
  • Run on a specific test case x model x provider
# streaming
llama-api-bench run --test-case basic_dont_call_tool --model Cerebras-Llama-4-Scout-17B-16E-Instruct --provider llamaapi --stream

# non-streaming
llama-api-bench run --test-case basic_dont_call_tool --model Cerebras-Llama-4-Scout-17B-16E-Instruct --provider llamaapi --no-stream
  • Run on specific provider x model
llama-api-bench run-provider --provider openai --models gpt-4o

llama-api-bench run-provider --provider llamaapi --models Llama-4-Maverick-17B-128E-Instruct-FP8

cli

Customization

Add a New Test Case / Criteria

  1. Add a new test case in llama_api_bench/data/.
  2. If the new test case requires a new Test Criteria to run evaluation, add it to llama_api_bench/core/criterias.

Add New Provider

  1. Add supported models in llama_api_bench/models/. See an example in llamaapi.py.
  2. Add ProviderConfig in llama_api_bench/core/providers.py.
  3. If the provider requires has a new request format, add it to get_request_json.
  4. If the provider requires a new response format parsing, add its evaluation criteria in llama_api_bench/core/criterias.

License

llama-api-bench is distributed under the terms of the MIT license.

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