File size: 3,029 Bytes
6628fd9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
import enum
import os

from core.helper import LifecycleHelper
from faq.robot_manager import FAQRobotManager, AzureFAQRobotManager

from multiprocessing import Lock

lock = Lock()


class FAQRobotRevision(enum.Enum):
    SIMPLE_OPENAI_VERSION_0 = 1
    HUGGINGFACE_VERSION_0 = 2


class FAQRobotManagerFactory:
    """
    CAPABLE: Dict[FAQRobotRevision, FAQManager] =
    {FAQRobotRevision.SIMPLE_OPENAI_VERSION_0: FAQRobotManager()}
    """

    CAPABLE = dict()  # type: dict[FAQRobotRevision, FAQRobotManager]

    @classmethod
    def get_or_create(cls, revision: FAQRobotRevision) -> FAQRobotManager:
        with lock:
            if cls.CAPABLE.get(revision) is not None:
                return cls.CAPABLE[revision]
            if revision == FAQRobotRevision.SIMPLE_OPENAI_VERSION_0:
                manager = cls.create_simple_openai_version_0()
            elif revision == FAQRobotRevision.HUGGINGFACE_VERSION_0:
                manager = cls.create_huggingface_version_0()
            cls.CAPABLE[revision] = manager
            return manager

    @classmethod
    def create_simple_openai_version_0(cls) -> AzureFAQRobotManager:
        from llama.service_context import AzureServiceContextManager
        from langchain_manager.manager import LangChainAzureManager

        service_context_manager = AzureServiceContextManager(
            lc_manager=LangChainAzureManager()
        )
        from llama.storage_context import LocalStorageContextManager

        dataset_path = os.getenv("FAQ_DATASET_PATH", "./dataset/faq")
        storage_context_manager = LocalStorageContextManager(
            dataset_path=dataset_path, service_context_manager=service_context_manager
        )

        robot_manager = AzureFAQRobotManager(
            service_context_manager=service_context_manager,
            storage_context_manager=storage_context_manager,
        )
        LifecycleHelper.initialize_if_possible(robot_manager)
        LifecycleHelper.start_if_possible(robot_manager)
        return robot_manager

    @classmethod
    def create_huggingface_version_0(cls) -> AzureFAQRobotManager:
        from llama.service_context import HuggingFaceChineseOptServiceContextManager
        from langchain_manager.manager import LangChainAzureManager

        service_context_manager = HuggingFaceChineseOptServiceContextManager(
            lc_manager=LangChainAzureManager()
        )

        from llama.storage_context import LocalStorageContextManager

        dataset_path = os.getenv("FAQ_DATASET_PATH", "./dataset/faq")
        storage_context_manager = LocalStorageContextManager(
            dataset_path=dataset_path, service_context_manager=service_context_manager
        )

        robot_manager = AzureFAQRobotManager(
            service_context_manager=service_context_manager,
            storage_context_manager=storage_context_manager,
        )
        LifecycleHelper.initialize_if_possible(robot_manager)
        LifecycleHelper.start_if_possible(robot_manager)
        return robot_manager