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119 lines
3.2 KiB
Python
119 lines
3.2 KiB
Python
"""AI21 client."""
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import logging
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import os
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from typing import Any, Dict, Optional
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from manifest.clients.client import Client
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from manifest.request import LMRequest
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logger = logging.getLogger(__name__)
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AI21_ENGINES = {
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"j1-jumbo",
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"j1-grande",
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"j1-large",
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}
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class AI21Client(Client):
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"""AI21Client client."""
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# User param -> (client param, default value)
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PARAMS = {
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"engine": ("engine", "j1-large"),
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"temperature": ("temperature", 1.0),
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"max_tokens": ("maxTokens", 10),
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"top_k": ("topKReturn", 0),
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"n": ("numResults", 1),
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"top_p": ("topP", 1.0),
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"stop_sequences": ("stopSequences", []),
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}
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REQUEST_CLS = LMRequest
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NAME = "ai21"
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def connect(
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self,
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connection_str: Optional[str] = None,
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client_args: Dict[str, Any] = {},
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) -> None:
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"""
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Connect to the AI21 server.
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connection_str is passed as default AI21_API_KEY if variable not set.
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Args:
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connection_str: connection string.
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client_args: client arguments.
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"""
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# Taken from https://studio.ai21.com/docs/api/
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self.host = "https://api.ai21.com/studio/v1"
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self.api_key = os.environ.get("AI21_API_KEY", connection_str)
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if self.api_key is None:
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raise ValueError(
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"AI21 API key not set. Set AI21_API_KEY environment "
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"variable or pass through `client_connection`."
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)
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for key in self.PARAMS:
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setattr(self, key, client_args.pop(key, self.PARAMS[key][1]))
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if getattr(self, "engine") not in AI21_ENGINES:
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raise ValueError(
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f"Invalid engine {getattr(self, 'engine')}. Must be {AI21_ENGINES}."
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)
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def close(self) -> None:
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"""Close the client."""
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pass
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def get_generation_url(self) -> str:
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"""Get generation URL."""
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return self.host + "/" + getattr(self, "engine") + "/complete"
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def get_generation_header(self) -> Dict[str, str]:
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"""
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Get generation header.
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Returns:
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header.
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"""
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return {"Authorization": f"Bearer {self.api_key}"}
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def supports_batch_inference(self) -> bool:
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"""Return whether the client supports batch inference."""
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return False
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def get_model_params(self) -> Dict:
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"""
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Get model params.
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By getting model params from the server, we can add to request
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and make sure cache keys are unique to model.
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Returns:
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model params.
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"""
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return {"model_name": self.NAME, "engine": getattr(self, "engine")}
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def validate_response(self, response: Dict, request: Dict) -> Dict[str, Any]:
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"""
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Format response to dict.
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Args:
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response: response
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request: request
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Return:
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response as dict
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"""
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return {
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"object": "text_completion",
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"model": getattr(self, "engine"),
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"choices": [
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{
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"text": item["data"]["text"],
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"token_logprobs": item["data"]["tokens"],
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}
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for item in response["completions"]
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],
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}
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