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73 lines
2.3 KiB
Python
73 lines
2.3 KiB
Python
2 years ago
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"""Wrapper around Cohere APIs."""
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import os
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from typing import Any, Dict, List, Optional
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from pydantic import BaseModel, Extra, root_validator
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from langchain.llms.base import LLM
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def remove_stop_tokens(text: str, stop: List[str]) -> str:
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"""Remove stop tokens, should they occur at end."""
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for s in stop:
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if text.endswith(s):
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return text[: -len(s)]
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return text
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class Cohere(BaseModel, LLM):
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"""Wrapper around Cohere large language models."""
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client: Any
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model: str = "gptd-instruct-tft"
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max_tokens: int = 256
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temperature: float = 0.6
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k: int = 0
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p: int = 1
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frequency_penalty: int = 0
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presence_penalty: int = 0
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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 template_is_valid(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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if "COHERE_API_KEY" not in os.environ:
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raise ValueError(
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"Did not find Cohere API key, please add an environment variable"
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" `COHERE_API_KEY` which contains it."
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)
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try:
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import cohere
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values["client"] = cohere.Client(os.environ["COHERE_API_KEY"])
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except ImportError:
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raise ValueError(
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"Could not import cohere python package. "
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"Please it install it with `pip install cohere`."
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)
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return values
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def __call__(self, prompt: str, stop: Optional[List[str]] = None) -> str:
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"""Call out to Cohere's generate endpoint."""
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response = self.client.generate(
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model=self.model,
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prompt=prompt,
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max_tokens=self.max_tokens,
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temperature=self.temperature,
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k=self.k,
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p=self.p,
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frequency_penalty=self.frequency_penalty,
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presence_penalty=self.presence_penalty,
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stop_sequences=stop,
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)
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text = response.generations[0].text
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# If stop tokens are provided, Cohere's endpoint returns them.
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# In order to make this consistent with other endpoints, we strip them.
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if stop is not None:
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text = remove_stop_tokens(text, stop)
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return text
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