mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-01 05:15:17 +00:00
bf5193bb99
Upgrade to using a literal for specifying the extra which is the
recommended approach in pydantic 2.
This works correctly also in pydantic v1.
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel, extra="forbid"):
x: int
Foo(x=5, y=1)
```
And
```python
from pydantic.v1 import BaseModel
class Foo(BaseModel):
x: int
class Config:
extra = "forbid"
Foo(x=5, y=1)
```
## Enum -> literal using grit pattern:
```
engine marzano(0.1)
language python
or {
`extra=Extra.allow` => `extra="allow"`,
`extra=Extra.forbid` => `extra="forbid"`,
`extra=Extra.ignore` => `extra="ignore"`
}
```
Resorted attributes in config and removed doc-string in case we will
need to deal with going back and forth between pydantic v1 and v2 during
the 0.3 release. (This will reduce merge conflicts.)
## Sort attributes in Config:
```
engine marzano(0.1)
language python
function sort($values) js {
return $values.text.split(',').sort().join("\n");
}
class_definition($name, $body) as $C where {
$name <: `Config`,
$body <: block($statements),
$values = [],
$statements <: some bubble($values) assignment() as $A where {
$values += $A
},
$body => sort($values),
}
```
74 lines
2.2 KiB
Python
74 lines
2.2 KiB
Python
"""This file is for LLMRails Embedding"""
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from typing import Dict, List, Optional
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import requests
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from langchain_core.embeddings import Embeddings
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from langchain_core.pydantic_v1 import BaseModel, SecretStr
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from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
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class LLMRailsEmbeddings(BaseModel, Embeddings):
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"""LLMRails embedding models.
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To use, you should have the environment
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variable ``LLM_RAILS_API_KEY`` set with your API key or pass it
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as a named parameter to the constructor.
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Model can be one of ["embedding-english-v1","embedding-multi-v1"]
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Example:
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.. code-block:: python
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from langchain_community.embeddings import LLMRailsEmbeddings
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cohere = LLMRailsEmbeddings(
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model="embedding-english-v1", api_key="my-api-key"
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)
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"""
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model: str = "embedding-english-v1"
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"""Model name to use."""
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api_key: Optional[SecretStr] = None
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"""LLMRails API key."""
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class Config:
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extra = "forbid"
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@pre_init
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key exists in environment."""
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api_key = convert_to_secret_str(
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get_from_dict_or_env(values, "api_key", "LLM_RAILS_API_KEY")
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)
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values["api_key"] = api_key
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return values
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def embed_documents(self, texts: List[str]) -> List[List[float]]:
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"""Call out to Cohere's embedding endpoint.
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Args:
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texts: The list of texts to embed.
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Returns:
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List of embeddings, one for each text.
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"""
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response = requests.post(
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"https://api.llmrails.com/v1/embeddings",
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headers={"X-API-KEY": self.api_key.get_secret_value()}, # type: ignore[union-attr]
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json={"input": texts, "model": self.model},
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timeout=60,
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)
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return [item["embedding"] for item in response.json()["data"]]
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def embed_query(self, text: str) -> List[float]:
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"""Call out to Cohere's embedding endpoint.
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Args:
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text: The text to embed.
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Returns:
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Embeddings for the text.
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"""
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return self.embed_documents([text])[0]
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