Show HN: Geniusrise, a framework and ecosystem for AI agents

• geniusrise

  5 56 9.4 Python

  Geniusrise: Framework for building geniuses

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• geniusrise-huggingface

  2 1 10.0 Python

  Discontinued Bolts interfacing with the huggingface ecosystem

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• geniusrise-openai

  2 2 7.2 Python

  Bolts interfacing with the openai ecosystem

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• geniusrise-listeners

  2 2 8.1 Python

  A collection of Spouts that listen to events

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• geniusrise-databases

  2 2 5.4 Python

  A collection of Spouts that query databases

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• geniusrise-prompt-actions

  2 3 5.4 Python

  Bolts that read data and perform chains of actions with prompts

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• geniusrise-indexing

  3 0 2.6

  A collection of bolts for Retieval-augmented Generation (RAG) usecases

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• SaaSHub

  www.saashub.com featured

  SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

  

• geniusrise-exit-proxy

  2 0 10.0

  LLM proxy with single interface, caching & MITM audit logging.

  

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

• Category_Theory_Machine_Learning

  10 1,127 6.7 Python

  List of papers studying machine learning through the lens of category theory

## More Links

1. https://github.com/geniusrise/geniusrise - core framework

2. https://github.com/geniusrise/geniusrise-huggingface - hf modules

3. https://github.com/geniusrise/geniusrise-openai - openai modules

4. https://github.com/geniusrise/geniusrise-listeners - streaming data input

5. https://github.com/geniusrise/geniusrise-databases - database input

6. https://github.com/geniusrise/geniusrise-prompt-actions - functional integrations (RAG-able and GPT function call-able, WIP)

7. https://github.com/geniusrise/geniusrise-indexing - vectorizing for RAG usecases (WIP)

8. https://github.com/geniusrise/geniusrise-exit-proxy - cached LLM interface with MITM-auditing (WIP)

## Asides

I think the core framework can be AGPL but the modules must be MIT / Apachev2.

I really wanted to create an elaborate example in the guides but could not find time, - something like load and vectorize SNOMED-CT or UMLS and use it to NER / RAG EHR docs. Or maybe a usecase of doctor communicating to patient in another language (a major problem in India), with reverse translation verifying translated output using the KG. These kinds of stuff are soon to come. Or discourse segmentation for better chunking for RAG usecases.

I'm not sure if I should add cyberpunk-ed scientists as banner images. I tried with mathematicians like Voevodsky to Andre Joyal to John Baez, but couldn't. Actual geniuses tend to not be famous, hence SDXL fails I guess.

I plan to also write this framework in scala. The category-theorizing of neural networks is amazing!!! https://github.com/bgavran/Category_Theory_Machine_Learning. I hope Bartosz Milewski approves.

I love Alan Turing, but cuz of "The Chemical Basis of Morphogenesis". It introduced me to the wonderful world of complex systems. Hence, his image as banner.

I'm also working on a cli library called "isomorphic", wraps over argparse and provides cli, api, yaml, json interfaces.

Yes, gradio integration is also underway.

Finally, to huggingface.

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