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126 lines
3.6 KiB
Python
126 lines
3.6 KiB
Python
"""Cohere 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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COHERE_MODELS = {"small", "medium", "large", "xlarge"}
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class CohereClient(Client):
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"""Cohere client."""
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# Params are defined in https://docs.cohere.ai/generate-reference
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PARAMS = {
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"engine": ("model", "xlarge"),
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"max_tokens": ("max_tokens", 20),
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"temperature": ("temperature", 0.75),
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"n": ("num_generations", 1),
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"top_k": ("k", 0),
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"top_p": ("p", 0.75),
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"frequency_penalty": ("frequency_penalty", 0.0),
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"presence_penalty": ("presence_penalty", 0.0),
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"stop_sequences": ("stop_sequences", None),
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}
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REQUEST_CLS = LMRequest
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NAME = "cohere"
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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 Cohere server.
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connection_str is passed as default COHERE_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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self.api_key = connection_str or os.environ.get("COHERE_API_KEY")
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if self.api_key is None:
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raise ValueError(
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"Cohere API key not set. Set COHERE_API_KEY environment "
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"variable or pass through `client_connection`."
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)
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self.host = "https://api.cohere.ai"
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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 COHERE_MODELS:
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raise ValueError(
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f"Invalid engine {getattr(self, 'engine')}. Must be {COHERE_MODELS}."
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)
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def close(self) -> None:
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"""Close the client."""
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def get_generation_url(self) -> str:
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"""Get generation URL."""
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return self.host + "/generate"
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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 {
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"Cohere-Version": "2021-11-08",
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"Authorization": f"Bearer {self.api_key}",
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}
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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 supports_streaming_inference(self) -> bool:
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"""Return whether the client supports streaming inference.
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Override in child client class.
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"""
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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 postprocess_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["text"],
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"text_logprob": item.get("likelihood", None),
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"token_logprobs": item.get("token_likelihoods", None),
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}
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for item in response["generations"]
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],
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}
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