Adapter

Index

• Adapter

  • adapter.adapter

  • adapter.api

  • adapter.diffusers

  • adapter.openai

adapter.adapter

adapter.api

gptcache.adapter.api.get(prompt: str, **kwargs) → Any

search api, search the cache data according to the prompt Please make sure that the pre_embedding_func param is get_prompt when initializing the cache

Example

from gptcache.adapter.api import save
from gptcache.processor.pre import get_prompt

cache.init(pre_embedding_func=get_prompt)
put("hello", "foo")
print(get("hello"))

gptcache.adapter.api.put(prompt: str, data: Any, **kwargs) → None

save api, save qa pair information to GPTCache Please make sure that the pre_embedding_func param is get_prompt when initializing the cache

Example

from gptcache.adapter.api import save
from gptcache.processor.pre import get_prompt

cache.init(pre_embedding_func=get_prompt)
put("hello", "foo")

adapter.diffusers

class gptcache.adapter.diffusers.StableDiffusionPipeline(*args, **kwargs)

Diffuser StableDiffusionPipeline Wrapper

Example

import torch

from gptcache import cache
from gptcache.processor.pre import get_prompt
from gptcache.adapter.diffusers import StableDiffusionPipeline

# init gptcache
cache.init(pre_embedding_func=get_prompt)

# run with gptcache
model_id = "stabilityai/stable-diffusion-2-1"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")

prompt = "a photo of an astronaut riding a horse on mars"
image = pipe(prompt=prompt).images[0]

adapter.openai

class gptcache.adapter.openai.Audio(id=None, api_key=None, api_version=None, api_type=None, organization=None, response_ms: Optional[int] = None, api_base=None, engine=None, **params)

Openai Audio Wrapper

Example

from gptcache import cache
from gptcache.processor.pre import get_file_bytes
# init gptcache
cache.init(pre_embedding_func=get_file_bytes)
cache.set_openai_key()

from gptcache.adapter import openai
# run audio transcribe model with gptcache
audio_file= open("/path/to/audio.mp3", "rb")
transcript = openai.Audio.transcribe("whisper-1", audio_file)

# run audio transcribe model with gptcache
audio_file= open("/path/to/audio.mp3", "rb")
transcript = openai.Audio.translate("whisper-1", audio_file)

class gptcache.adapter.openai.ChatCompletion(engine: Optional[str] = None, **kwargs)

Openai ChatCompletion Wrapper

Example

from gptcache import cache
from gptcache.processor.pre import get_prompt
# init gptcache
cache.init(pre_embedding_func=get_prompt)
cache.set_openai_key()

from gptcache.adapter import openai
# run ChatCompletion model with gptcache
response = openai.ChatCompletion.create(
              model='gpt-3.5-turbo',
              messages=[
                {
                    'role': 'user',
                    'content': "what's github"
                }],
            )
response_content = response['choices'][0]['message']['content']

classmethod create(*args, **kwargs)

Creates a new chat completion for the provided messages and parameters.

See https://platform.openai.com/docs/api-reference/chat-completions/create for a list of valid parameters.

class gptcache.adapter.openai.Completion(engine: Optional[str] = None, **kwargs)

Openai Completion Wrapper

Example

from gptcache import cache
from gptcache.processor.pre import get_prompt
# init gptcache
cache.init(pre_embedding_func=get_prompt)
cache.set_openai_key()

from gptcache.adapter import openai
# run Completion model with gptcache
response = openai.Completion.create(model="text-davinci-003",
                                    prompt="Hello world.")
response_text = response["choices"][0]["text"]

classmethod create(*args, **kwargs)

Creates a new completion for the provided prompt and parameters.

See https://platform.openai.com/docs/api-reference/completions/create for a list of valid parameters.

class gptcache.adapter.openai.Image(id=None, api_key=None, api_version=None, api_type=None, organization=None, response_ms: Optional[int] = None, api_base=None, engine=None, **params)

Openai Image Wrapper

Example

from gptcache import cache
from gptcache.processor.pre import get_prompt
# init gptcache
cache.init(pre_embedding_func=get_prompt)
cache.set_openai_key()

from gptcache.adapter import openai
# run image generation model with gptcache
response = openai.Image.create(
  prompt="a white siamese cat",
  n=1,
  size="256x256"
)
response_url = response['data'][0]['url']