package tei.v1

Get desktop application:
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• rpc Embed (EmbedRequest, EmbedResponse)

  tei.proto:14

  message EmbedRequest

  tei.proto:54

  • string inputs = 1

  • bool truncate = 2

  • bool normalize = 3

  message EmbedResponse

  tei.proto:60

  • repeated float embeddings = 1

  • optional Metadata metadata = 2

• rpc Info (InfoRequest, InfoResponse)

  tei.proto:8

  message InfoRequest

  tei.proto:21

  (message has no fields)

  message InfoResponse

  tei.proto:29

  • string version = 1

  • optional string sha = 2

  • optional string docker_label = 3

  • string model_id = 4

  • optional string model_sha = 5

  • string model_dtype = 6

  • ModelType model_type = 7

  • uint32 max_concurrent_requests = 8

  • uint32 max_input_length = 9

  • uint32 max_batch_tokens = 10

  • optional uint32 max_batch_requests = 11

  • uint32 max_client_batch_size = 12

  • uint32 tokenization_workers = 13

• rpc Tokenize (EncodeRequest, EncodeResponse)

  tei.proto:18

  message EncodeRequest

  tei.proto:65

  • string inputs = 1

  • bool add_special_tokens = 2

  message EncodeResponse

  tei.proto:78

  • repeated SimpleToken tokens = 1

Used in: EmbedResponse

• uint32 compute_chars = 1

• uint32 compute_tokens = 2

• uint64 total_time_ns = 3

• uint64 tokenization_time_ns = 4

• uint64 queue_time_ns = 5

• uint64 inference_time_ns = 6

Used in: InfoResponse

• MODEL_TYPE_EMBEDDING = 0

• MODEL_TYPE_CLASSIFIER = 1

• MODEL_TYPE_RERANKER = 2

Used in: EncodeResponse

• uint32 id = 1

• string text = 2

• bool special = 3

• optional uint32 start = 4

• optional uint32 stop = 5