-
Notifications
You must be signed in to change notification settings - Fork 279
/
Copy pathevents.py
69 lines (48 loc) · 1.94 KB
/
events.py
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
# Copyright 2025 © BeeAI a Series of LF Projects, LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from collections.abc import Callable
from types import NoneType
from pydantic import BaseModel, InstanceOf
from beeai_framework.backend.types import ChatModelInput, ChatModelOutput, EmbeddingModelInput, EmbeddingModelOutput
from beeai_framework.errors import FrameworkError
class ChatModelNewTokenEvent(BaseModel):
value: InstanceOf[ChatModelOutput]
abort: Callable[[], None]
class ChatModelSuccessEvent(BaseModel):
value: InstanceOf[ChatModelOutput]
class ChatModelStartEvent(BaseModel):
input: InstanceOf[ChatModelInput]
class ChatModelErrorEvent(BaseModel):
input: InstanceOf[ChatModelInput]
error: InstanceOf[FrameworkError]
chat_model_event_types: dict[str, type] = {
"new_token": ChatModelNewTokenEvent,
"success": ChatModelSuccessEvent,
"start": ChatModelStartEvent,
"error": ChatModelErrorEvent,
"finish": NoneType,
}
class EmbeddingModelSuccessEvent(BaseModel):
value: InstanceOf[EmbeddingModelOutput]
class EmbeddingModelStartEvent(BaseModel):
input: InstanceOf[EmbeddingModelInput]
class EmbeddingModelErrorEvent(BaseModel):
input: InstanceOf[EmbeddingModelInput]
error: InstanceOf[FrameworkError]
embedding_model_event_types: dict[str, type] = {
"success": EmbeddingModelSuccessEvent,
"start": EmbeddingModelStartEvent,
"error": EmbeddingModelErrorEvent,
"finish": NoneType,
}