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feat (new llm): add support for openrouter (#3042)
This commit is contained in:
Salem Korayem
GitHub
parent
e12a0c154c
commit
6b4c8e76e6
@ -6,6 +6,7 @@
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- cohere
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- bedrock
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- togetherai
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- openrouter
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- ollama
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- mistralai
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- groq
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</svg>
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After Width: | Height: | Size: 2.4 KiB |
46
api/core/model_runtime/model_providers/openrouter/llm/llm.py
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46
api/core/model_runtime/model_providers/openrouter/llm/llm.py
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from collections.abc import Generator
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from typing import Optional, Union
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from core.model_runtime.entities.llm_entities import LLMResult
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from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool
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from core.model_runtime.entities.model_entities import AIModelEntity
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from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel
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class OpenRouterLargeLanguageModel(OAIAPICompatLargeLanguageModel):
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def _update_endpoint_url(self, credentials: dict):
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credentials['endpoint_url'] = "https://openrouter.ai/api/v1"
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return credentials
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def _invoke(self, model: str, credentials: dict,
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prompt_messages: list[PromptMessage], model_parameters: dict,
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tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
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stream: bool = True, user: Optional[str] = None) \
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-> Union[LLMResult, Generator]:
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cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
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return super()._invoke(model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user)
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def validate_credentials(self, model: str, credentials: dict) -> None:
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cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
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return super().validate_credentials(model, cred_with_endpoint)
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def _generate(self, model: str, credentials: dict, prompt_messages: list[PromptMessage], model_parameters: dict,
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tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
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stream: bool = True, user: Optional[str] = None) -> Union[LLMResult, Generator]:
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cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
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return super()._generate(model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user)
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def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity:
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cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
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return super().get_customizable_model_schema(model, cred_with_endpoint)
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def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
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tools: Optional[list[PromptMessageTool]] = None) -> int:
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cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
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return super().get_num_tokens(model, cred_with_endpoint, prompt_messages, tools)
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import logging
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from core.model_runtime.model_providers.__base.model_provider import ModelProvider
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logger = logging.getLogger(__name__)
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class OpenRouterProvider(ModelProvider):
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def validate_provider_credentials(self, credentials: dict) -> None:
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pass
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@ -0,0 +1,75 @@
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provider: openrouter
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label:
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en_US: openrouter.ai
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icon_small:
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en_US: openrouter_square.svg
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icon_large:
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en_US: openrouter.svg
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background: "#F1EFED"
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help:
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title:
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en_US: Get your API key from openrouter.ai
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zh_Hans: 从 openrouter.ai 获取 API Key
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url:
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en_US: https://openrouter.ai/keys
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supported_model_types:
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- llm
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configurate_methods:
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- customizable-model
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model_credential_schema:
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model:
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label:
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en_US: Model Name
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zh_Hans: 模型名称
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placeholder:
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en_US: Enter full model name
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zh_Hans: 输入模型全称
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credential_form_schemas:
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- variable: api_key
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required: true
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label:
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en_US: API Key
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type: secret-input
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placeholder:
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zh_Hans: 在此输入您的 API Key
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en_US: Enter your API Key
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- variable: mode
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show_on:
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- variable: __model_type
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value: llm
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label:
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en_US: Completion mode
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type: select
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required: false
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default: chat
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placeholder:
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zh_Hans: 选择对话类型
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en_US: Select completion mode
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options:
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- value: completion
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label:
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en_US: Completion
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zh_Hans: 补全
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- value: chat
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label:
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en_US: Chat
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zh_Hans: 对话
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- variable: context_size
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label:
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zh_Hans: 模型上下文长度
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en_US: Model context size
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required: true
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type: text-input
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default: "4096"
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placeholder:
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zh_Hans: 在此输入您的模型上下文长度
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en_US: Enter your Model context size
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- variable: max_tokens_to_sample
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label:
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zh_Hans: 最大 token 上限
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en_US: Upper bound for max tokens
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show_on:
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- variable: __model_type
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value: llm
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default: "4096"
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type: text-input
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118
api/tests/integration_tests/model_runtime/openrouter/test_llm.py
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118
api/tests/integration_tests/model_runtime/openrouter/test_llm.py
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import os
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from typing import Generator
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import pytest
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from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
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from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessageTool,
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SystemPromptMessage, UserPromptMessage)
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from core.model_runtime.errors.validate import CredentialsValidateFailedError
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from core.model_runtime.model_providers.openrouter.llm.llm import OpenRouterLargeLanguageModel
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def test_validate_credentials():
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model = OpenRouterLargeLanguageModel()
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with pytest.raises(CredentialsValidateFailedError):
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model.validate_credentials(
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model='mistralai/mixtral-8x7b-instruct',
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credentials={
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'api_key': 'invalid_key',
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'mode': 'chat'
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}
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)
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model.validate_credentials(
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model='mistralai/mixtral-8x7b-instruct',
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credentials={
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'api_key': os.environ.get('TOGETHER_API_KEY'),
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'mode': 'chat'
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}
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)
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def test_invoke_model():
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model = OpenRouterLargeLanguageModel()
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response = model.invoke(
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model='mistralai/mixtral-8x7b-instruct',
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credentials={
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'api_key': os.environ.get('TOGETHER_API_KEY'),
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'mode': 'completion'
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},
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prompt_messages=[
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SystemPromptMessage(
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content='You are a helpful AI assistant.',
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),
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UserPromptMessage(
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content='Who are you?'
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)
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],
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model_parameters={
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'temperature': 1.0,
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'top_k': 2,
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'top_p': 0.5,
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},
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stop=['How'],
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stream=False,
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user="abc-123"
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)
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assert isinstance(response, LLMResult)
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assert len(response.message.content) > 0
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def test_invoke_stream_model():
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model = OpenRouterLargeLanguageModel()
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response = model.invoke(
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model='mistralai/mixtral-8x7b-instruct',
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credentials={
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'api_key': os.environ.get('TOGETHER_API_KEY'),
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'mode': 'chat'
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},
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prompt_messages=[
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SystemPromptMessage(
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content='You are a helpful AI assistant.',
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),
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UserPromptMessage(
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content='Who are you?'
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)
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],
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model_parameters={
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'temperature': 1.0,
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'top_k': 2,
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'top_p': 0.5,
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},
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stop=['How'],
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stream=True,
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user="abc-123"
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)
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assert isinstance(response, Generator)
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for chunk in response:
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assert isinstance(chunk, LLMResultChunk)
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assert isinstance(chunk.delta, LLMResultChunkDelta)
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assert isinstance(chunk.delta.message, AssistantPromptMessage)
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def test_get_num_tokens():
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model = OpenRouterLargeLanguageModel()
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num_tokens = model.get_num_tokens(
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model='mistralai/mixtral-8x7b-instruct',
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credentials={
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'api_key': os.environ.get('TOGETHER_API_KEY'),
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},
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prompt_messages=[
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SystemPromptMessage(
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content='You are a helpful AI assistant.',
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),
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UserPromptMessage(
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content='Hello World!'
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)
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]
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)
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assert isinstance(num_tokens, int)
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assert num_tokens == 21
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