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
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129 | class LlamafileEmbedding(BaseEmbedding):
"""用于llamafile嵌入的类。
llamafile允许您使用单个文件分发和运行大型语言模型。
要开始,请参阅:https://github.com/Mozilla-Ocho/llamafile
要使用此类,您首先需要:
1. 下载一个llamafile。
2. 使下载的文件可执行:`chmod +x path/to/model.llamafile`
3. 以启用嵌入的服务器模式启动llamafile:
`./path/to/model.llamafile --server --nobrowser --embedding`"""
base_url: str = Field(
description="base url of the llamafile server", default="http://localhost:8080"
)
request_timeout: float = Field(
default=DEFAULT_REQUEST_TIMEOUT,
description="The timeout for making http request to llamafile API server",
)
def __init__(
self,
base_url: str = "http://localhost:8080",
callback_manager: Optional[CallbackManager] = None,
**kwargs,
) -> None:
super().__init__(base_url=base_url, callback_manager=callback_manager, **kwargs)
@classmethod
def class_name(cls) -> str:
return "LlamafileEmbedding"
def _get_query_embedding(self, query: str) -> Embedding:
return self._get_text_embedding(query)
async def _aget_query_embedding(self, query: str) -> Embedding:
return await self._aget_text_embedding(query)
def _get_text_embedding(self, text: str) -> Embedding:
"""
同步嵌入输入文本。
"""
request_body = {
"content": text,
}
with httpx.Client(timeout=Timeout(self.request_timeout)) as client:
response = client.post(
url=f"{self.base_url}/embedding",
headers={"Content-Type": "application/json"},
json=request_body,
)
response.encoding = "utf-8"
response.raise_for_status()
return response.json()["embedding"]
async def _aget_text_embedding(self, text: str) -> Embedding:
"""
将输入文本异步嵌入。
"""
request_body = {
"content": text,
}
async with httpx.AsyncClient(timeout=Timeout(self.request_timeout)) as client:
response = await client.post(
url=f"{self.base_url}/embedding",
headers={"Content-Type": "application/json"},
json=request_body,
)
response.encoding = "utf-8"
response.raise_for_status()
return response.json()["embedding"]
def _get_text_embeddings(self, texts: List[str]) -> List[Embedding]:
"""
同步嵌入输入文本。
"""
request_body = {
"content": texts,
}
with httpx.Client(timeout=Timeout(self.request_timeout)) as client:
response = client.post(
url=f"{self.base_url}/embedding",
headers={"Content-Type": "application/json"},
json=request_body,
)
response.encoding = "utf-8"
response.raise_for_status()
return [output["embedding"] for output in response.json()["results"]]
async def _aget_text_embeddings(self, texts: List[str]) -> Embedding:
"""
将输入文本异步嵌入。
"""
request_body = {
"content": texts,
}
async with httpx.AsyncClient(timeout=Timeout(self.request_timeout)) as client:
response = await client.post(
url=f"{self.base_url}/embedding",
headers={"Content-Type": "application/json"},
json=request_body,
)
response.encoding = "utf-8"
response.raise_for_status()
return [output["embedding"] for output in response.json()["results"]]
|