wehub-resource-sync
150 lines
5.1 KiB
Python
150 lines
5.1 KiB
Python
# Copyright 2025 LiveKit, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import annotations
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import os
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import platform
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from typing import Any
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import httpx
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import openai
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from openai.types import ReasoningEffort
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from livekit.agents import __version__ as livekit_version
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from livekit.agents.llm import ToolChoice
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from livekit.agents.types import NOT_GIVEN, NotGivenOr
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from livekit.agents.utils import is_given
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from livekit.plugins.openai.llm import LLM as OpenAILLM
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from .models import SarvamLLMModels
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SARVAM_LLM_BASE_URL = "https://api.sarvam.ai/v1"
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USER_AGENT = f"Livekit/{livekit_version} Python/{platform.python_version()}"
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_SUPPORTED_MODELS = {
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"sarvam-m",
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"sarvam-30b",
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"sarvam-30b-16k", # deprecated by Sarvam, kept for backward compatibility
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"sarvam-105b",
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"sarvam-105b-32k", # deprecated by Sarvam, kept for backward compatibility
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}
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_ALLOWED_EXTRA_BODY_PARAMS = {
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"frequency_penalty",
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"max_tokens",
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"n",
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"presence_penalty",
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"seed",
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"stop",
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"wiki_grounding",
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}
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class LLM(OpenAILLM):
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def __init__(
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self,
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*,
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model: str | SarvamLLMModels = "sarvam-30b",
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api_key: NotGivenOr[str] = NOT_GIVEN,
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base_url: NotGivenOr[str] = SARVAM_LLM_BASE_URL,
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client: openai.AsyncClient | None = None,
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user: NotGivenOr[str] = NOT_GIVEN,
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temperature: NotGivenOr[float] = NOT_GIVEN,
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top_p: NotGivenOr[float] = NOT_GIVEN,
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tool_choice: NotGivenOr[ToolChoice] = NOT_GIVEN,
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reasoning_effort: NotGivenOr[ReasoningEffort] = NOT_GIVEN,
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max_tokens: NotGivenOr[int] = NOT_GIVEN,
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wiki_grounding: NotGivenOr[bool] = NOT_GIVEN,
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stop: NotGivenOr[str | list[str]] = NOT_GIVEN,
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n: NotGivenOr[int] = NOT_GIVEN,
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seed: NotGivenOr[int] = NOT_GIVEN,
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frequency_penalty: NotGivenOr[float] = NOT_GIVEN,
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presence_penalty: NotGivenOr[float] = NOT_GIVEN,
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extra_headers: NotGivenOr[dict[str, str]] = NOT_GIVEN,
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extra_body: NotGivenOr[dict[str, Any]] = NOT_GIVEN,
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timeout: httpx.Timeout | None = None,
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) -> None:
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"""
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Create a new instance of Sarvam LLM.
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``api_key`` must be set to your Sarvam API key, either using the argument or by setting
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the ``SARVAM_API_KEY`` environment variable.
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"""
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validated_model = _validate_model(model)
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sarvam_api_key = _get_api_key(api_key)
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merged_headers = dict(extra_headers) if is_given(extra_headers) else {}
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# Sarvam chat-completions auth and telemetry headers are always enforced.
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merged_headers["api-subscription-key"] = sarvam_api_key
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merged_headers["User-Agent"] = USER_AGENT
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merged_body = dict(extra_body) if is_given(extra_body) else {}
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if is_given(max_tokens):
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merged_body["max_tokens"] = max_tokens
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if is_given(wiki_grounding):
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merged_body["wiki_grounding"] = wiki_grounding
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if is_given(stop):
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merged_body["stop"] = stop
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if is_given(n):
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merged_body["n"] = n
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if is_given(seed):
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merged_body["seed"] = seed
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if is_given(frequency_penalty):
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merged_body["frequency_penalty"] = frequency_penalty
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if is_given(presence_penalty):
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merged_body["presence_penalty"] = presence_penalty
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filtered_body = _filter_extra_body(merged_body)
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super().__init__(
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model=validated_model,
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api_key=sarvam_api_key,
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base_url=base_url,
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client=client,
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user=user,
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temperature=temperature,
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top_p=top_p,
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tool_choice=tool_choice,
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reasoning_effort=reasoning_effort,
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extra_headers=merged_headers,
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extra_body=filtered_body if filtered_body else NOT_GIVEN,
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timeout=timeout,
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)
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@property
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def model(self) -> str:
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return self._opts.model
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@property
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def provider(self) -> str:
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return "Sarvam"
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def _get_api_key(key: NotGivenOr[str]) -> str:
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sarvam_api_key = key if is_given(key) else os.environ.get("SARVAM_API_KEY")
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if not sarvam_api_key:
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raise ValueError(
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"SARVAM_API_KEY is required, either as argument or set SARVAM_API_KEY environment variable"
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)
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return sarvam_api_key
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def _validate_model(model: str) -> str:
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if model not in _SUPPORTED_MODELS:
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raise ValueError(
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f"Unsupported Sarvam model '{model}'. Supported models: {sorted(_SUPPORTED_MODELS)}"
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)
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return model
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def _filter_extra_body(extra_body: dict[str, Any]) -> dict[str, Any]:
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return {k: v for k, v in extra_body.items() if k in _ALLOWED_EXTRA_BODY_PARAMS}
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