LangChain Extensions
class langchain_ext.embedding.NuPICEmbedding(url='localhost:8000', protocol='http', model='nupic-sbert.base-v3', max_batch_size=64, concurrency=4, tokenizer_config=None)
Bases: Embeddings
NuPICEmbedding is an Langchain Embeddings class.
Uses NuPIC Inference Server to embed documents and sentences.
- Parameters:
Embeddings (class) – The LangChain Embeddings class.
__init__(url='localhost:8000', protocol='http', model='nupic-sbert.base-v3', max_batch_size=64, concurrency=4, tokenizer_config=None)
Initialize the NuPIC Client.
- Parameters:
- url (str , optional) – The URL of the NuPIC Inference Server, defaults to “localhost:8000”
- protocol (str , optional) – The protocol to use, defaults to “http”. Can be “http”,
“https” or “grpc”. - model (str , optional) – The model to use, defaults to “nupic-sbert.base-v3”
- max_batch_size (int , optional) – The maximum batch size, defaults to 64
- concurrency (int , optional) – Number of concurrent connections to the server,
defaults to 4 - tokenizer_config (Optional [**Mapping [**str , Any ] ] , optional) – Tokenizer configuration dictionary, defaults to
None.
path (str): Path for the pretrained transformers tokenizer. Raise
TypeError or KeyError if not present.
max_tokens_per_string (int, optional): Maximum number of tokens the
tokenizer should return per string given to the tokenizer. Defaults
to 64.
batchsize : int | None_ = 64
embed_documents(documents: List[str])
Embed a list of documents.
- Parameters:
documents (List [**str ]) – The list of documents to embed. - Returns:
The list of embeddings. - Return type:
List[List[float]]
embed_query(query: str)
Embed a query.
- Parameters:
query (str) – The query to embed. - Returns:
Embedding of the query. - Return type:
List[float]
model : str | None = 'nupic-sbert.base-v3'
protocol : str | None = 'http'
url : str | None = 'localhost:8000'
class langchain_ext.llm.NuPICLLM(url='localhost:8000', protocol='http', model='nupic-gpt.7b-corti.v0', inference_parameters=None)
Bases: LLM
NuPICLLM is an Langchain LLM class.
Uses NuPIC Inference Server to call an GPT model with a prompt.
- Parameters:
LLM (class) – The LangChain LLM class.
__init__(url='localhost:8000', protocol='http', model='nupic-gpt.7b-corti.v0', inference_parameters=None)
Initialize the NuPIC Client.
- Parameters:
- url (str , optional) – The URL of the NuPIC Inference Server, defaults to “localhost:8000”
- protocol (str , optional) – The protocol to use, defaults to “http”. Can be “http”,
“https” or “grpc”. - model (str , optional) – The model to use, defaults to “nupic-gpt.7b-corti.v0”
- inference_parameters – Dictionary containing optional parameters
to be used,
: for inference by the model at the inference server.
min_new_tokens (int) = 0: Minimum number of tokens to generate by the
model
max_new_tokens (int) = 512: Maximum number of tokens to generate by
the model
do_sample (bool) = True: Whether or not to use sampling ; use greedy
decoding otherwise.
temperature (float) = 1.0: The value used to modulate the next token
probabilities.
top_k (int) = 50: The number of highest probability vocabulary tokens
to keep for top-k-filtering.
top_p (float) = 1.0: If set to float < 1, only the smallest set of
most probable tokens with probabilities that add up to top_p or higher
are kept for generation.
repetition_penalty (float) = 1.0: The parameter for repetition penalty.
1.0 meansno penalty.
client : Any | None
inferenceparameters : Mapping[str, Any] | None_
model : str | None
protocol : str | None
url : str | None
class langchain_ext.llm.NuPICLLMStreaming(url='localhost:8001', model='nupic-gpt.7b-corti.streaming.v0', inference_parameters=None, tokens_per_line=16)
Bases: LLM
NuPICLLM is an Langchain LLM class.
Uses NuPIC Inference Server to call an GPT model with a prompt.
- Parameters:
LLM (class) – The LangChain LLM class.
__init__(url='localhost:8001', model='nupic-gpt.7b-corti.streaming.v0', inference_parameters=None, tokens_per_line=16)
Initialize the NuPIC Client.
- Parameters:
- url (str , optional) – The URL of the NuPIC Inference Server, defaults to “localhost:8001”
- model (str , optional) – The model to use, defaults to “nupic-gpt.7b-corti.streaming.v0”
- inference_parameters (Optional [**Mapping [**str , Any ] ] , optional) – Dictionary containing optional parameters
to be used, for inference by the model at the inference server.
min_new_tokens (int) = 0: Minimum number of tokens to generate by the
model
max_new_tokens (int) = 512: Maximum number of tokens to generate by
the model
do_sample (bool) = True: Whether or not to use sampling ; use greedy
decoding otherwise.
temperature (float) = 1.0: The value used to modulate the next token
probabilities.
top_k (int) = 50: The number of highest probability vocabulary tokens
to keep for top-k-filtering.
top_p (float) = 1.0: If set to float < 1, only the smallest set of
most probable tokens with probabilities that add up to top_p or higher
are kept for generation.
repetition_penalty (float) = 1.0: The parameter for repetition penalty.
1.0 means no penalty. - tokens_per_line (int , optional) – Number of tokens per line, defaults to 16
client : Any | None
inferenceparameters : Mapping[str, Any] | None_
model : str | None
tokensin_cur_line : int_
tokensper_line : int_
url : str | None
Updated 2 months ago