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121 lines
4.3 KiB
Python
121 lines
4.3 KiB
Python
"""Wrapper around Anyscale"""
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from typing import Any, Dict, List, Mapping, Optional
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import requests
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from pydantic import Extra, root_validator
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from langchain.callbacks.manager import CallbackManagerForLLMRun
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from langchain.llms.base import LLM
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from langchain.llms.utils import enforce_stop_tokens
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from langchain.utils import get_from_dict_or_env
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class Anyscale(LLM):
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"""Wrapper around Anyscale Services.
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To use, you should have the environment variable ``ANYSCALE_SERVICE_URL``,
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``ANYSCALE_SERVICE_ROUTE`` and ``ANYSCALE_SERVICE_TOKEN`` set with your Anyscale
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Service, or pass it as a named parameter to the constructor.
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Example:
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.. code-block:: python
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from langchain.llms import Anyscale
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anyscale = Anyscale(anyscale_service_url="SERVICE_URL",
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anyscale_service_route="SERVICE_ROUTE",
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anyscale_service_token="SERVICE_TOKEN")
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# Use Ray for distributed processing
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import ray
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prompt_list=[]
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@ray.remote
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def send_query(llm, prompt):
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resp = llm(prompt)
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return resp
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futures = [send_query.remote(anyscale, prompt) for prompt in prompt_list]
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results = ray.get(futures)
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"""
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model_kwargs: Optional[dict] = None
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"""Key word arguments to pass to the model. Reserved for future use"""
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anyscale_service_url: Optional[str] = None
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anyscale_service_route: Optional[str] = None
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anyscale_service_token: Optional[str] = None
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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anyscale_service_url = get_from_dict_or_env(
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values, "anyscale_service_url", "ANYSCALE_SERVICE_URL"
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)
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anyscale_service_route = get_from_dict_or_env(
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values, "anyscale_service_route", "ANYSCALE_SERVICE_ROUTE"
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)
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anyscale_service_token = get_from_dict_or_env(
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values, "anyscale_service_token", "ANYSCALE_SERVICE_TOKEN"
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)
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try:
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anyscale_service_endpoint = f"{anyscale_service_url}/-/route"
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headers = {"Authorization": f"Bearer {anyscale_service_token}"}
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requests.get(anyscale_service_endpoint, headers=headers)
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except requests.exceptions.RequestException as e:
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raise ValueError(e)
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values["anyscale_service_url"] = anyscale_service_url
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values["anyscale_service_route"] = anyscale_service_route
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values["anyscale_service_token"] = anyscale_service_token
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return values
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@property
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def _identifying_params(self) -> Mapping[str, Any]:
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"""Get the identifying parameters."""
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return {
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"anyscale_service_url": self.anyscale_service_url,
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"anyscale_service_route": self.anyscale_service_route,
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}
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@property
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def _llm_type(self) -> str:
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"""Return type of llm."""
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return "anyscale"
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def _call(
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self,
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prompt: str,
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stop: Optional[List[str]] = None,
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run_manager: Optional[CallbackManagerForLLMRun] = None,
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) -> str:
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"""Call out to Anyscale Service endpoint.
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Args:
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prompt: The prompt to pass into the model.
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stop: Optional list of stop words to use when generating.
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Returns:
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The string generated by the model.
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Example:
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.. code-block:: python
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response = anyscale("Tell me a joke.")
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"""
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anyscale_service_endpoint = (
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f"{self.anyscale_service_url}/{self.anyscale_service_route}"
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)
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headers = {"Authorization": f"Bearer {self.anyscale_service_token}"}
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body = {"prompt": prompt}
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resp = requests.post(anyscale_service_endpoint, headers=headers, json=body)
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if resp.status_code != 200:
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raise ValueError(
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f"Error returned by service, status code {resp.status_code}"
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)
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text = resp.text
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if stop is not None:
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# This is a bit hacky, but I can't figure out a better way to enforce
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# stop tokens when making calls to huggingface_hub.
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text = enforce_stop_tokens(text, stop)
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return text
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