tikos 0.2.4

Tikos Platform Library

Tikos Reasoning Platform

Tikos Reasoning Platform harnesses the power of empirically established 2nd-generation AI and statistical toolsets to offer its users advanced 3rd-generation AI capabilities.

Copyright 2024 (C) Tikos Technologies Limited

How to access the platform

To get Alpha API keys, please register your request via https://tikos.tech/

Licence

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Release Notes

1. v 0.0.7

   i. Added GetGraphStructure: Automatically extract graph Vertices and Edges that can be further refined by the user

   ii. Added GenerateGraph: Provide Tikos Reasoning Platform the refined graph Vertices and Edges to build the standard knowledge graph

   iii. Added GetGraph: Get the whole graph for an extraction request

   iv. Added GetGraphRelationships: Get relationships between two Vertexes

2. v 0.0.8

   i. Added GetGraphRetrieval: Retrieve query response along with the Graph relationships for the requested retrieve query

3. v 0.0.9

   i. Added GetGraphRetrievalWithDS: Retrieve query response along with the Graph relationships for the requested retrieve query with Graph Node data sets as JSON

4. v 0.1.0

   i. Added licence conditions

5. v 0.1.1

   i. Added ProcessExtractFile: Be able to extract data from a specific file and support JSON based extraction using jq based schemas

   ii. Modified ProcessExtract: Support JSON based extraction using jq based schemas

6. v0.1.1

   i. Added BuildSC: Generate the SequentialCollection knowledge structure for the associated graph Vertices from structured data sets

   ii. Added GetSimilarCase: Providing a Problem Space (PS) case, the Sequential collection will contact a basic binary (BIN, default) search or advanced binary (BINADV) search and return the most similar existing case. This does not perform any case adaptation

7. v0.1.4

   i. Added GetGraphStructurePerDoc: Accept a file names and generate NER JSON of the (submitted) file

   ii. Added GenerateGraphPerDoc: Accept a NER JSON object and create a graph of the (submitted) file

   iii. Added GenerateAutoGraph: Accept a list of file names, that will be used to generate the NER generation automatically and create a full graph

8. v0.1.6

   i. Amended GetGraphRetrieval: Accept optional file reference and base model reference

   ii. Amended GetGraphRetrievalWithDS: Accept optional file reference and base model reference

9. v0.1.7

   i. Added GetCustomerGraphRetrievalWithDS: Retrieve customer specific query with the Graph relationships for the requested retrieve query with Graph Node data sets as JSON

10. v0.1.8
    • Amended GenerateGraph, GenerateGraphPerDoc & GenerateAutoGraph: Accept graph generation Payload Configuration with the JSON format:

      {
        "overrideNER": "<True/False>",
        "filter": "<GRAPH CASE_TYPE ATTRIBUTE GENERATION CONFIG TEXT>"
      }
      

11. v0.1.9

    i. Amended GetGraphStructure, GetGraphStructurePerDoc, GenerateGraph, GenerateGraphPerDoc & GenerateAutoGraph: Accept the model-id configuration

12. v0.2.0

    i. Added GetReasoning: Generate Similarity Reasoning of a Solution for a given Sequential Collection Case

13. v0.2.1

    i. Added tikos.TikosClient, A generic client connector that orchestrates commonly used base functions. It has been developed to facilitate easy integration with other applications and supports multithreading.

    ii. Added addProcessFiles: Multithreading supported file processing function. Accepts: List of filenames and file paths as a tuple

    iii. Added addFileStreams: Multithreading supported file addition function. Accepts: List of filenames and file stream as a tuple

    iv. Added addProcessFileStreams: Multithreading supported combined file addition and processing function. Accepts: List of filenames and file stream as a tuple

    v. Added generateGraphStructures: Multithreading supported graph structure generation function. Accepts: List of filenames as contexes

    vi. Added createGraph: Multithreading supported graph creation function. Accepts: List of filenames as contexes

    vii. Added getGraph: Graph structure extraction function

    viii. Added getGraphRetrieval: Graph retrieval function, Accepts: Filenames as context and query

    ix. Added createSequentialCollection: Sequential Collection creation function. Accepts: Case-Type, Data File name as context and Weight Type

    x. Added generateReasoning: Sequential Collection reasoning function. Accepts: Case-Type, Data File name as context, problem space case as a JSON object string, Weight Type and Reasoning Type

14. v0.2.2

    i. Amended BuildSC: Accepts the Sequential Collection config (scConfig)

    ii. Amended tikos.TikosClient.createSequentialCollection: Accepts the Sequential Collection config (scConfig)

15. v0.2.3

    i. Added UploadModel: Upload trained Deep Neural Network model that need to embedded with TRP. PyTorch Based models are supported

    ii. Added UploadModelConfig: Upload of the configuration related to the Uploaded DNN model. Will accept the model param definition in JSON format as-well-as the model specification in YAML format

    iii. Added UploadModelCaseData: Upload of the selected Knowledge Cases (feature sets), that will build the initial Sequential Collection case base

    iv. Added ProcessModel: Process the upload DNN model with Synapses Logger embedding and dynamically creating the Sequential Collection case base

    v. Added tikos.TikosClient.uploadEmbeddingModel: Supports upload of the DNN model

    vi. Added tikos.TikosClient.uploadEmbeddingConfig: Supports upload of the DNN model configuration files

    vii. Added tikos.TikosClient.uploadModelCaseData: Upload of the selected Knowledge Cases (feature sets), that will build the initial Sequential Collection case base

    viii. Added tikos.TikosClient.processEmbeddedModel: Process the upload DNN model with Synapses Logger embedding and dynamically creating the Sequential Collection case base

16. v0.2.4

    i. Amended tikos.TikosClient.generateReasoning: Accepts base models' Neural Network Architecture types with param nType. Default is0.
    nType Types:
    0. Feedforward (deep) ANN
    1. Basic Transformer based ANN
    2. Modern Transformer based ANN