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import os
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import re
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from typing import Union
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import pytest
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from _pytest.monkeypatch import MonkeyPatch
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from requests import Response
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from requests.exceptions import ConnectionError
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from requests.sessions import Session
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from xinference_client.client.restful.restful_client import (
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Client,
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RESTfulChatglmCppChatModelHandle,
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RESTfulChatModelHandle,
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RESTfulEmbeddingModelHandle,
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RESTfulGenerateModelHandle,
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RESTfulRerankModelHandle,
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)
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from xinference_client.types import Embedding, EmbeddingData, EmbeddingUsage
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class MockXinferenceClass:
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def get_chat_model(self: Client, model_uid: str) -> Union[RESTfulChatglmCppChatModelHandle, RESTfulGenerateModelHandle, RESTfulChatModelHandle]:
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if not re.match(r'https?:\/\/[^\s\/$.?#].[^\s]*$', self.base_url):
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raise RuntimeError('404 Not Found')
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if 'generate' == model_uid:
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return RESTfulGenerateModelHandle(model_uid, base_url=self.base_url, auth_headers={})
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if 'chat' == model_uid:
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return RESTfulChatModelHandle(model_uid, base_url=self.base_url, auth_headers={})
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if 'embedding' == model_uid:
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return RESTfulEmbeddingModelHandle(model_uid, base_url=self.base_url, auth_headers={})
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if 'rerank' == model_uid:
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return RESTfulRerankModelHandle(model_uid, base_url=self.base_url, auth_headers={})
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raise RuntimeError('404 Not Found')
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def get(self: Session, url: str, **kwargs):
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response = Response()
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if 'v1/models/' in url:
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model_uid = url.split('/')[-1] or ''
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if not re.match(r'[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}', model_uid) and \
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model_uid not in ['generate', 'chat', 'embedding', 'rerank']:
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response.status_code = 404
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response._content = b'{}'
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return response
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if not re.match(r'^(https?):\/\/[^\s\/$.?#].[^\s]*$', url):
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response.status_code = 404
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response._content = b'{}'
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return response
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if model_uid in ['generate', 'chat']:
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response.status_code = 200
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response._content = b'''{
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"model_type": "LLM",
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"address": "127.0.0.1:43877",
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"accelerators": [
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"0",
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"1"
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],
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"model_name": "chatglm3-6b",
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"model_lang": [
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"en"
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],
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"model_ability": [
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"generate",
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"chat"
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],
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"model_description": "latest chatglm3",
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"model_format": "pytorch",
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"model_size_in_billions": 7,
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"quantization": "none",
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"model_hub": "huggingface",
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"revision": null,
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"context_length": 2048,
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"replica": 1
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}'''
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return response
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elif model_uid == 'embedding':
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response.status_code = 200
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response._content = b'''{
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"model_type": "embedding",
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"address": "127.0.0.1:43877",
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"accelerators": [
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"0",
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"1"
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],
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"model_name": "bge",
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"model_lang": [
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"en"
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],
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"revision": null,
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"max_tokens": 512
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}'''
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return response
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elif 'v1/cluster/auth' in url:
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response.status_code = 200
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response._content = b'''{
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"auth": true
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}'''
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return response
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def _check_cluster_authenticated(self):
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self._cluster_authed = True
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def rerank(self: RESTfulRerankModelHandle, documents: list[str], query: str, top_n: int) -> dict:
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if not re.match(r'[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}', self._model_uid) and \
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self._model_uid != 'rerank':
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raise RuntimeError('404 Not Found')
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if not re.match(r'^(https?):\/\/[^\s\/$.?#].[^\s]*$', self._base_url):
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raise RuntimeError('404 Not Found')
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if top_n is None:
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top_n = 1
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return {
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'results': [
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{
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'index': i,
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'document': doc,
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'relevance_score': 0.9
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}
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for i, doc in enumerate(documents[:top_n])
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]
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}
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def create_embedding(
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self: RESTfulGenerateModelHandle,
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input: Union[str, list[str]],
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**kwargs
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) -> dict:
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if not re.match(r'[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}', self._model_uid) and \
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self._model_uid != 'embedding':
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raise RuntimeError('404 Not Found')
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if isinstance(input, str):
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input = [input]
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ipt_len = len(input)
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embedding = Embedding(
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object="list",
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model=self._model_uid,
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data=[
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EmbeddingData(
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index=i,
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object="embedding",
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embedding=[1919.810 for _ in range(768)]
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)
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for i in range(ipt_len)
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],
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usage=EmbeddingUsage(
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prompt_tokens=ipt_len,
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total_tokens=ipt_len
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)
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)
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return embedding
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MOCK = os.getenv('MOCK_SWITCH', 'false').lower() == 'true'
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@pytest.fixture
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def setup_xinference_mock(request, monkeypatch: MonkeyPatch):
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if MOCK:
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monkeypatch.setattr(Client, 'get_model', MockXinferenceClass.get_chat_model)
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monkeypatch.setattr(Client, '_check_cluster_authenticated', MockXinferenceClass._check_cluster_authenticated)
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monkeypatch.setattr(Session, 'get', MockXinferenceClass.get)
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monkeypatch.setattr(RESTfulEmbeddingModelHandle, 'create_embedding', MockXinferenceClass.create_embedding)
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monkeypatch.setattr(RESTfulRerankModelHandle, 'rerank', MockXinferenceClass.rerank)
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yield
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if MOCK:
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monkeypatch.undo() |