llama-cpp-cffi 0.1.15

Python binding for llama.cpp using cffi

llama-cpp-cffi

Python binding for llama.cpp using cffi. Supports CPU, CUDA 12.5.1 and CUDA 12.6 execution.

NOTE: Currently supported operating system is Linux (manylinux_2_28 and musllinux_1_2), but we are working on both Windows and MacOS versions.

Install

Basic library install:

pip install llama-cpp-cffi

In case you want OpenAI © Chat Completions API compatible API:

pip install llama-cpp-cffi[openai]

IMPORTANT: If you want to take advantage of Nvidia GPU acceleration, make sure that you have installed CUDA 12. If you don't have CUDA 12.X installed follow instructions here: https://developer.nvidia.com/cuda-downloads .

GPU Compute Capability: compute_61, compute_70, compute_75, compute_80, compute_86, compute_89 covering from most of GPUs from GeForce GTX 1050 to NVIDIA H100. GPU Compute Capability.

Example

Library Usage

References:

• examples/demo_tinyllama_chat.py
• examples/demo_tinyllama_tool.py

from llama import llama_generate, get_config, Model, Options


model = Model(
    creator_hf_repo='TinyLlama/TinyLlama-1.1B-Chat-v1.0',
    hf_repo='TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF',
    hf_file='tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf',
)

config = get_config(model.creator_hf_repo)

messages = [
    {'role': 'system', 'content': 'You are a helpful assistant.'},
    {'role': 'user', 'content': '1 + 1 = ?'},
    {'role': 'assistant', 'content': '2'},
    {'role': 'user', 'content': 'Evaluate 1 + 2 in Python.'},
]

options = Options(
    ctx_size=config.max_position_embeddings,
    predict=-2,
    model=model,
    prompt=messages,
)

for chunk in llama_generate(options):
    print(chunk, flush=True, end='')

# newline
print()

OpenAI © compatible Chat Completions API - Server and Client

Run OpenAI compatible server:

python -m llama.openai
# or
python -B -u -m gunicorn --bind '0.0.0.0:11434' --timeout 300 --workers 1 --worker-class aiohttp.GunicornWebWorker 'llama.openai:build_app()'

Run OpenAI compatible client examples/demo_openai_0.py:

python -B examples/demo_openai_0.py

from openai import OpenAI
from llama import Model


client = OpenAI(
    base_url = 'http://localhost:11434/v1',
    api_key='llama-cpp-cffi',
)

model = Model(
    creator_hf_repo='TinyLlama/TinyLlama-1.1B-Chat-v1.0',
    hf_repo='TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF',
    hf_file='tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf',
)

messages = [
    {'role': 'system', 'content': 'You are a helpful assistant.'},
    {'role': 'user', 'content': '1 + 1 = ?'},
    {'role': 'assistant', 'content': '2'},
    {'role': 'user', 'content': 'Evaluate 1 + 2 in Python.'}
]


def demo_chat_completions():
    print('demo_chat_completions:')

    response = client.chat.completions.create(
        model=str(model),
        messages=messages,
        temperature=0.0,
    )

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


def demo_chat_completions_stream():
    print('demo_chat_completions_stream:')

    response = client.chat.completions.create(
        model=str(model),
        messages=messages,
        temperature=0.0,
        stream=True,
    )

    for chunk in response:
        print(chunk.choices[0].delta.content, flush=True, end='')

    print()


if __name__ == '__main__':
    demo_chat_completions()
    demo_chat_completions_stream()

Demos

python -B examples/demo_tinyllama_chat.py
python -B examples/demo_tinyllama_tool.py