Langchain-Projects-LLM

(★ 120)

Various projects using Large Language Model (GPT & LLAMA) other open source model from HuggingFace and OpenAI. OpenAI API required for running various model

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- basic.txt
- ChainCOT.py
- index_retriever.py
- my_file.txt
- prompting_tec.py
- Text_splitter_langchain.ipynb
- vector_embeddings_lang.ipynb
- youtube_langchain.ipynb
- Advanced_RAG_6.ipynb
- Advanced_RAG_Part4.ipynb
- Advanced_RAG_part_2.ipynb
- Advanced_RAG_Part_3.ipynb
- Advanced_RAG_Part_5.ipynb
- Advances_RAG_Part_1.ipynb
- basic.txt
- chat-with-website-chroma.py
- chat-with-website-FAISS.py
- app.py
- chatpdf.txt
- ChatPDFGoogle.py
- constant.py
- csv_file_agentchat.py
- Fine-Tune Your Own Llama 2 Model in a Colab Notebook _ Towards Data Science.pdf
- GOOGLE_PALM_PDF.ipynb
- HuggingFace_PDFS.ipynb
- Langchain101.ipynb
- llamaindex.py
- main.py
- Medium_blog_analyzer.py
- summarize.py
- summary_PDF_ANY.ipynb
- Tokens_Huggingface.ipynb
- chatbot.txt
- constant.py
- HTMLTemplate.py
- llama_chatbot.py
- main.py
- URL_Chatbot.ipynb
- website_chatbot.py
- main.py
- qrcode1.png
- aim.py
- semefinal.txt
- test_example.py
- testing_pro.py
- RAGAS.ipynb
- api.py
- Fine_Tune_LLAMA2.ipynb
- llama2.txt
- Test_FINE_TUNE_MODEL.ipynb
- Text_to_SQL.ipynb
- basix.txt
- mistral_finetuning.ipynb
- MistralOrca_7B_+_HuggingFace.ipynb
- - .env
  - app.py
  - basic.txt
  - requirement.txt
- - .env
  - Readme.md
  - requirement.txt
  - sql.py
  - sqlite.py
  - student.db
  - students.db
- Gemini.ipynb
- Gemini_&_Langchain.ipynb
- Gemini_chromadb.ipynb
- multiple_PDFS.py
- qachat.py
- - all-data (1).csv
  - Basic.txt
  - Gemma_model.ipynb
- Gemma_+_HuggingFace.ipynb
- - __init__.py
  - core.py
- .env
- ingestion.py
- main.py
- Readme.md
- requirement.txt
- LCEL-Part2.py
- LCEL-part3.py
- LCEL-Part4.py
- LCEL_Part1.py
- section1.py
- section2.py
- section3.py
- section4.py
- basic.txt
- LlamaIndex_+_Llama_2.ipynb
- LLamaIndex_+_Openai.ipynb
- Understanding.png
- - basix.txt
  - prompEngineering_part_2.ipynb
  - promptingEngineering_part1.ipynb
- LLMops.pdf
- Mesop+Langchain+GroQ.ipynb
- MOA.ipynb
- fine_tuning.py
- fine_tuning_data.jsonl
- fine_tuning_data_val.jsonl
- main.py
- medical.py
- reports.csv
- cricket.ipynb
- ind vs eng.csv
- pandasAI + Cricket.ipynb
- callbacks.py
- ReAct.pdf
- react.py
- react.txt
- data.xlsx
- Similar_words_app.ipynb
- TEXT_EMBEDDINGS.ipynb
- - .env
  - calculator_tools.py
  - search_tools.py
- .env
- AgentCreationIdea.txt
- agents.py
- main.py
- poetry.lock
- pyproject.toml
- TaskCreationIdea.txt
- tasks.py
- youtube_langchain.ipynb
- constant.py
- Langchain.txt
- mainYT.py
- summary.py
- YT_summary.py
attention all you need.pdf
LICENSE
prompts-linkedin.md
README.md

# Installation Guide

1. Get the code

git clone https://github.com/ananthanarayanan431/Langchain-Projects-LLM

Downloads the entire project code from GitHub to your computer.

cd Langchain-Projects-LLM

Moves into the project folder you just downloaded.

2. Python

Easy Recommended

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install .

Installs the package published on PyPI directly — no need to clone the source.

jupyter notebook

Launches Jupyter in your browser so you can open and run the notebook (.ipynb) files.

✅ If it runs without errors and prints output in the terminal, it worked.