https://github.com/nicolay-r/nlp-thirdgate

A hub of third-party providers and tutorials to help you instantly apply various NLP techniques.
https://github.com/nicolay-r/nlp-thirdgate

api hub nlp openrouter-api providers python replicate-api third-party third-party-api translations

Last synced: 2 months ago
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A hub of third-party providers and tutorials to help you instantly apply various NLP techniques.

• Host: GitHub
• URL: https://github.com/nicolay-r/nlp-thirdgate
• Owner: nicolay-r
• License: mit
• Created: 2025-01-18T14:09:53.000Z (4 months ago)
• Default Branch: master
• Last Pushed: 2025-03-11T16:07:26.000Z (2 months ago)
• Last Synced: 2025-03-11T17:24:25.628Z (2 months ago)
• Topics: api, hub, nlp, openrouter-api, providers, python, replicate-api, third-party, third-party-api, translations
• Language: Jupyter Notebook
• Homepage:
• Size: 131 KB
• Stars: 4
• Watchers: 1
• Forks: 2
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# nlp-thirdgate [![twitter](https://img.shields.io/twitter/url/https/shields.io.svg?style=social)](https://x.com/nicolayr_/status/1900911458197623268)

[![twitter](https://img.shields.io/twitter/url/https/shields.io.svg?style=social)](https://x.com/nicolayr_/status/1900911458197623268)



    



A hub of [**third-party NLP providers**](#third-party-providers) and tutorials to help you instantly handle your [**data iterator**](#data-iterators) with [no-string dependency apps](#no-string-apps).

The purpose is of this project is to share **Third-party providers** that could be combined into a single [**pipeline**](#pipeline-formation).

# Third-Party Providers

* **LLM / [Mistral.AI](llm/mistralai_150.py)** [[🤖 models]](https://docs.mistral.ai/getting-started/models/models_overview/)

* **LLM / [OpenRouter.AI](llm/open_router.py)** [[🤖 models]](https://openrouter.ai/models)

* **LLM / [Replicate.IO](llm/replicate_104.py)** [[🤖 models]](https://replicate.com/pricing#language-models)

    * DeepSeek-R1

    * LLaMA-3-70B-Instruct

    * LLaMA-3-8B-Instruct

* **LLM / OpenAI**:

    * [ChatGPT](llm/openai_156.py)

    * [Qwen-2.5-Max](https://github.com/nicolay-r/nlp-thirdgate/blob/master/tutorials/llm_qwen_25_max_chat.sh)

    * [o1](llm/openai_o1.py)

* **LLM / Transformers**:

    * DeepSeek-R1-distill-7b [[📙 qwen-notebook]](tutorials/llm_deep_seek_7b_distill_qwen2.ipynb)

      [[📙 llama3-notebook]](tutorials/llm_deep_seek_7b_distill_llama3.ipynb)

    * [LLaMA-3](llm/transformers_llama.py)

    * [Qwen-2](llm/transformers_qwen2.py)

    * [Phi-4](llm/transformers_phi4.py)

    * [Gemma-3](llm/transformers_gemma3.py) [[📙 notebook]](tutorials/llm_gemma_3.ipynb)

    * [Flan-T5](llm/transformers_flan_t5.py)

    * [Mistral](llm/transformers_mistral.py)

* **NER / [DeepPavlov](ner/dp_130.py)** [[📙 notebook]](tutorials/ner_deeppavlov_130.ipynb)

* **NER / [Flair](ner/flair_0151.py)** [[bash-script]](tutorials/ner_flair_0151.sh) [[🤖 models]](https://huggingface.co/flair)

* **NER / [Spacy](ner/spacy_383.py)** [[bash-script]](tutorials/ner_spacy_383.sh) [[🤖 models]](https://huggingface.co/spacy)

* **Translation / [GoogleTranslator](text-translation/googletrans_310a.py)** [[📙 notebook]](tutorials/translate_texts_with_spans_via_googletrans.ipynb)

# Data Iterators

In this project we consider that each provider represent a wrapper over third-party app to handle iterator of data.

We consider `dict` python type for representing each record of the data.

# Pipeline Formation

If you wish to use several [third-party providers](#third-party-providers) all together for a 

[data-iterators](#data-iterators), it is recommented to adopt [`AREkit` framework](https://github.com/nicolay-r/AREkit) as a no-string solution for deploying pipeline that support batching mode.

# No-string Application

* [bulk-chain](https://github.com/nicolay-r/bulk-chain) -- framework for reasoning over your tabular data rows with any provided LLM

* [bulk-ner](https://github.com/nicolay-r/bulk-ner) -- framework for a quick third-party models binding for entities extraction from cells of long tabular data

* [bulk-translate](https://github.com/nicolay-r/bulk-translate) --  framework for translation of a massive stream of texts with native support of pre-annotated fixed-spans that are invariant for translator.

* [AREkit pipelines](https://github.com/nicolay-r/AREkit) -- toolkit for handling your textual data iterators with various NLP providers