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A free version of Generative AI powered package which augments search based on documents

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# freeGPT
A free version of Generative AI powered package brought to you by [AIGuruKul](https://www.aigurukul.dev/). It helps augment search based on documents and video files without any need for internet connection or any API key.

1. Chat_youtube.ipynb: This python notebook helps one search for answers from a youtube recording which has a transcript available. It also exports out the transcript as a docx file.

2. docGPT.ipynb: This python notebook helps one search for answers from files of multiple types (word, doc,  html, csv, ppt). It can be a great aid if you want to quickly get objective and fact backed answers from a file using a web User Interface.

3. Bhagwan_speaks.ipynb: This python notebook helps one talk to Bhagwan Sri Krishna and gets response/instructions similar to how Arjun got from Bhagwan Sri Krishna

# How to use Google Colab:

# How to use Git:

# Reading Resources and links
To understand LLM's, we must read books, related papers and practise codes to get a grip on them. 
Various books have been uploaded in the <a href="https://github.com/amaze18/freeGPT/tree/main/reading%20resources"> reading resources</a> folder.
 
## Papers to refer and read

| Date | keywords | Institute | Paper | Publication |
| :-----: | :------------------: | :--------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------: |
| 2017-06 | Transformers | Google | [Attention Is All You Need](https://arxiv.org/pdf/1706.03762.pdf) | NeurIPS ![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2F204e3073870fae3d05bcbc2f6a8e263d9b72e776%3Ffields%3DcitationCount&query=%24.citationCount&label=citation) |
| 2021-09 | FLAN | Google | [Finetuned Language Models are Zero-Shot Learners](https://openreview.net/forum?id=gEZrGCozdqR) | ICLR ![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2Fff0b2681d7b05e16c46dfb71d980cc2f605907cd%3Ffields%3DcitationCount&query=%24.citationCount&label=citation)|
| 2022-01 | Minerva | Google | [Solving Quantitative Reasoning Problems with Language Models](https://arxiv.org/abs/2206.14858) | NeurIPS ![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2Fab0e3d3e4d42369de5933a3b4c237780b41c0d77%3Ffields%3DcitationCount&query=%24.citationCount&label=citation) |
| 2022-03 | InstructGPT | OpenAI | [Training language models to follow instructions with human feedback](https://arxiv.org/pdf/2203.02155.pdf) |![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2Fd766bffc357127e0dc86dd69561d5aeb520d6f4c%3Ffields%3DcitationCount&query=%24.citationCount&label=citation)|
| 2022-04 | PaLM | Google | [PaLM: Scaling Language Modeling with Pathways](https://arxiv.org/pdf/2204.02311.pdf) |![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2F094ff971d6a8b8ff870946c9b3ce5aa173617bfb%3Ffields%3DcitationCount&query=%24.citationCount&label=citation)|
| 2023-03 | GPT 4 | OpenAI | [GPT-4 Technical Report](https://openai.com/research/gpt-4)|![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2F8ca62fdf4c276ea3052dc96dcfd8ee96ca425a48%3Ffields%3DcitationCount&query=%24.citationCount&label=citation)|
| 2023-07 | LLaMA 2 | Meta | [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://arxiv.org/pdf/2307.09288.pdf) |![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2F104b0bb1da562d53cbda87aec79ef6a2827d191a%3Ffields%3DcitationCount&query=%24.citationCount&label=citation)|

You can see more in <a href="https://github.com/amaze18/freeGPT/tree/main/reading%20resources/Papers%20and%20Readings">papers and readings</a> section in reading resources.

## GitHub repo's and resources
The following are links of various other resources to study about langachains, LLM's and AI models- 
- [LLMsPracticalGuide](https://github.com/Mooler0410/LLMsPracticalGuide) - A curated (still actively updated) list of practical guide resources of LLMs
- [Chain-of-Thoughts Papers](https://github.com/Timothyxxx/Chain-of-ThoughtsPapers) - A trend starts from "Chain of Thought Prompting Elicits Reasoning in Large Language Models.
- [LLMDatahub](https://github.com/Zjh-819/LLMDataHub) - a curated collection of datasets specifically designed for chatbot training, including links, size, language, usage, and a brief description of each dataset
- [Awesome-Code-LLM](https://github.com/huybery/Awesome-Code-LLM) - An awesome and curated list of best code-LLM for research.
- [Awesome-LLM-Inference](https://github.com/DefTruth/Awesome-LLM-Inference) - A curated list of Awesome LLM Inference Paper with codes.
- [llm-course](https://github.com/mlabonne/llm-course) - Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

## To know more about langchains
Visit their official repository <a href="https://github.com/langchain-ai/langchain"> langchain-ai</a> and read the book <a href="https://github.com/benman1/generative_ai_with_langchain"> Generative AI with langchains</a>. This will
give a basic insight on how langchains work and you will develop ability to code using langchains.

# Homeworks and Tasks For yourself
1) Build a chatbot which talks to PDF file using Langchain and OpenAI embeddings.

# Contributors
<a href="https://github.com/AnirudhG07/AnirudhG07/graphs/contributors"><img src="https://contrib.rocks/image?repo=AnirudhG07/AnirudhG07" /></a>
<a href="https://github.com/MrigankPawagi/GuardRails/graphs/contributors"><img src="https://contrib.rocks/image?repo=MrigankPawagi/GuardRails" /></a>
<a href="https://github.com/TheUltimateKeval/TheUltimateKeval/graphs/contributors"><img src="https://contrib.rocks/image?repo=TheUltimateKeval/TheUltimateKeval"/>
</a>
<a href="[https://avatars.githubusercontent.com/u/124491857?v=4](https://github.com/GB2k4/GB)"><img src="https://avatars.githubusercontent.com/u/124491857?v=4" alt="GB" height="60" width="60" /></a>
<a href="https://github.com/Koosh0610/Koosh0610/graphs/contributors"><img src="https://contrib.rocks/image?repo=Koosh0610/Koosh0610" /></a>
# Follow me, join my sessions

Check out my sessions in the `talks.md` and follow them on below discord link. 
Discord: https://discord.gg/rUrxKhTk

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