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Harrison/aleph alpha (#8735)

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Co-authored-by: PiotrMazurek <piotr.mazurek@aleph-alpha.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
Harrison Chase 2023-08-03 21:21:15 -07:00 committed by GitHub
parent 179a39954d
commit 6c3573e7f6
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3 changed files with 118 additions and 31 deletions
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28
docs/extras/integrations/text_embedding/aleph_alpha.ipynb
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@ -20,7 +20,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 1,
"id": "8a920a89",
"metadata": {},
"outputs": [],
@ -30,7 +30,7 @@
},
{
"cell_type": "code",
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"execution_count": 2,
"id": "f2d04da3",
"metadata": {},
"outputs": [],
@ -41,17 +41,17 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 3,
"id": "e6ecde96",
"metadata": {},
"outputs": [],
"source": [
"embeddings = AlephAlphaAsymmetricSemanticEmbedding()"
"embeddings = AlephAlphaAsymmetricSemanticEmbedding(normalize=True, compress_to_size=128)"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 4,
"id": "90e68411",
"metadata": {},
"outputs": [],
@ -61,7 +61,7 @@
},
{
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"id": "55903233",
"metadata": {},
"outputs": [],
@ -79,7 +79,7 @@
},
{
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"execution_count": null,
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"id": "eabb763a",
"metadata": {},
"outputs": [],
@ -89,7 +89,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
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"id": "0ad799f7",
"metadata": {},
"outputs": [],
@ -99,17 +99,17 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 8,
"id": "af86dc10",
"metadata": {},
"outputs": [],
"source": [
"embeddings = AlephAlphaSymmetricSemanticEmbedding()"
"embeddings = AlephAlphaSymmetricSemanticEmbedding(normalize=True, compress_to_size=128)"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 9,
"id": "d292536f",
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"outputs": [],
@ -119,7 +119,7 @@
},
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"cell_type": "code",
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@ -130,7 +130,7 @@
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"id": "33492471",
"id": "5d999f8f",
"metadata": {},
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@ -152,7 +152,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
"version": "3.9.13"
},
"vscode": {
"interpreter": {

67
libs/langchain/langchain/embeddings/aleph_alpha.py
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@ -16,10 +16,11 @@ class AlephAlphaAsymmetricSemanticEmbedding(BaseModel, Embeddings):
Example:
.. code-block:: python
from aleph_alpha import AlephAlphaAsymmetricSemanticEmbedding
embeddings = AlephAlphaSymmetricSemanticEmbedding()
embeddings = AlephAlphaAsymmetricSemanticEmbedding(
normalize=True, compress_to_size=128
)
document = "This is a content of the document"
query = "What is the content of the document?"
@ -30,24 +31,55 @@ class AlephAlphaAsymmetricSemanticEmbedding(BaseModel, Embeddings):
"""
client: Any #: :meta private:
"""Aleph Alpha client."""
model: Optional[str] = "luminous-base"
# Embedding params
model: str = "luminous-base"
"""Model name to use."""
hosting: Optional[str] = "https://api.aleph-alpha.com"
"""Optional parameter that specifies which datacenters may process the request."""
normalize: Optional[bool] = True
"""Should returned embeddings be normalized"""
compress_to_size: Optional[int] = 128
compress_to_size: Optional[int] = None
"""Should the returned embeddings come back as an original 5120-dim vector,
or should it be compressed to 128-dim."""
normalize: Optional[bool] = None
"""Should returned embeddings be normalized"""
contextual_control_threshold: Optional[int] = None
"""Attention control parameters only apply to those tokens that have
explicitly been set in the request."""
control_log_additive: Optional[bool] = True
control_log_additive: bool = True
"""Apply controls on prompt items by adding the log(control_factor)
to attention scores."""
# Client params
aleph_alpha_api_key: Optional[str] = None
"""API key for Aleph Alpha API."""
host: str = "https://api.aleph-alpha.com"
"""The hostname of the API host.
The default one is "https://api.aleph-alpha.com")"""
hosting: Optional[str] = None
"""Determines in which datacenters the request may be processed.
You can either set the parameter to "aleph-alpha" or omit it (defaulting to None).
Not setting this value, or setting it to None, gives us maximal flexibility
in processing your request in our
own datacenters and on servers hosted with other providers.
Choose this option for maximal availability.
Setting it to "aleph-alpha" allows us to only process the request
in our own datacenters.
Choose this option for maximal data privacy."""
request_timeout_seconds: int = 305
"""Client timeout that will be set for HTTP requests in the
`requests` library's API calls.
Server will close all requests after 300 seconds with an internal server error."""
total_retries: int = 8
"""The number of retries made in case requests fail with certain retryable
status codes. If the last
retry fails a corresponding exception is raised. Note, that between retries
an exponential backoff
is applied, starting with 0.5 s after the first retry and doubling for each
retry made. So with the
default setting of 8 retries a total wait time of 63.5 s is added between
the retries."""
nice: bool = False
"""Setting this to True, will signal to the API that you intend to be
nice to other users
by de-prioritizing your request below concurrent ones."""
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
@ -57,12 +89,21 @@ class AlephAlphaAsymmetricSemanticEmbedding(BaseModel, Embeddings):
)
try:
from aleph_alpha_client import Client
values["client"] = Client(
token=aleph_alpha_api_key,
host=values["host"],
hosting=values["hosting"],
request_timeout_seconds=values["request_timeout_seconds"],
total_retries=values["total_retries"],
nice=values["nice"],
)
except ImportError:
raise ValueError(
"Could not import aleph_alpha_client python package. "
"Please install it with `pip install aleph_alpha_client`."
)
values["client"] = Client(token=aleph_alpha_api_key)
return values
def embed_documents(self, texts: List[str]) -> List[List[float]]:
@ -152,7 +193,9 @@ class AlephAlphaSymmetricSemanticEmbedding(AlephAlphaAsymmetricSemanticEmbedding
from aleph_alpha import AlephAlphaSymmetricSemanticEmbedding
embeddings = AlephAlphaAsymmetricSemanticEmbedding()
embeddings = AlephAlphaAsymmetricSemanticEmbedding(
normalize=True, compress_to_size=128
)
text = "This is a test text"
doc_result = embeddings.embed_documents([text])

54
libs/langchain/langchain/llms/aleph_alpha.py
View File

@ -125,12 +125,43 @@ class AlephAlpha(LLM):
raw_completion: bool = False
"""Force the raw completion of the model to be returned."""
aleph_alpha_api_key: Optional[str] = None
"""API key for Aleph Alpha API."""
stop_sequences: Optional[List[str]] = None
"""Stop sequences to use."""
# Client params
aleph_alpha_api_key: Optional[str] = None
"""API key for Aleph Alpha API."""
host: str = "https://api.aleph-alpha.com"
"""The hostname of the API host.
The default one is "https://api.aleph-alpha.com")"""
hosting: Optional[str] = None
"""Determines in which datacenters the request may be processed.
You can either set the parameter to "aleph-alpha" or omit it (defaulting to None).
Not setting this value, or setting it to None, gives us maximal
flexibility in processing your request in our
own datacenters and on servers hosted with other providers.
Choose this option for maximal availability.
Setting it to "aleph-alpha" allows us to only process the
request in our own datacenters.
Choose this option for maximal data privacy."""
request_timeout_seconds: int = 305
"""Client timeout that will be set for HTTP requests in the
`requests` library's API calls.
Server will close all requests after 300 seconds with an internal server error."""
total_retries: int = 8
"""The number of retries made in case requests fail with certain retryable
status codes. If the last
retry fails a corresponding exception is raised. Note, that between retries
an exponential backoff
is applied, starting with 0.5 s after the first retry and doubling for
each retry made. So with the
default setting of 8 retries a total wait time of 63.5 s is added
between the retries."""
nice: bool = False
"""Setting this to True, will signal to the API that you intend to be
nice to other users
by de-prioritizing your request below concurrent ones."""
class Config:
"""Configuration for this pydantic object."""
@ -143,9 +174,16 @@ class AlephAlpha(LLM):
values, "aleph_alpha_api_key", "ALEPH_ALPHA_API_KEY"
)
try:
import aleph_alpha_client
from aleph_alpha_client import Client
values["client"] = aleph_alpha_client.Client(token=aleph_alpha_api_key)
values["client"] = Client(
token=aleph_alpha_api_key,
host=values["host"],
hosting=values["hosting"],
request_timeout_seconds=values["request_timeout_seconds"],
total_retries=values["total_retries"],
nice=values["nice"],
)
except ImportError:
raise ImportError(
"Could not import aleph_alpha_client python package. "
@ -241,3 +279,9 @@ class AlephAlpha(LLM):
if stop is not None or self.stop_sequences is not None:
text = enforce_stop_tokens(text, params["stop_sequences"])
return text
if __name__ == "__main__":
aa = AlephAlpha()
print(aa("How are you?"))