Using LLMs with Ebooks and texts, developing Prompts, Agents, and Code with LangChain, using a Vector DB and Embeddings
Go to file
2024-04-04 10:38:12 +00:00
.github/workflows Create code_quality.yml.yml 2024-03-08 09:54:23 +01:00
data moved from sqlite to faiss for concurrency reasons 2024-04-04 10:38:12 +00:00
3.txt publication of evening project 2024-03-03 17:30:28 +00:00
Ask_Phrack.ipynb publication of evening project 2024-03-03 17:31:37 +00:00
EverNote_To_OpenAI.ipynb moved from sqlite to faiss for concurrency reasons 2024-04-04 10:38:12 +00:00
LICENSE Initial commit 2024-03-03 18:22:24 +01:00
Local_CPU_LLM_Bling_Non_Interactive.ipynb Example Notebook with LLMware CPU LLM and LangChain 2024-03-17 11:30:55 +00:00
Local_CPU_LLM_Ollama_Mistral.ipynb LangChain, Mistral, Ollama, local LLM CPU-hosted 2024-03-21 08:54:28 +00:00
Readme.md Update Readme.md 2024-03-03 19:01:20 +01:00
requirements.txt First status of bookworm 2024-03-21 16:22:56 +00:00
sandbox.py sandbox 2024-03-08 09:04:10 +00:00
vss.db publication of evening project 2024-03-03 17:30:28 +00:00

Don't read this

Writeup

Follow the sub-pages for more.

Local install w conda

conda create --name lang_chain python=3.11 
source ~/miniconda3/bin/activate 
conda activate lang_chain
conda install --file requirements.txt

For the local SQlite VSS

pip install --upgrade --quiet  sqlite-vss

for Ubuntu Server 22.04 LTS minimal) specifically here:

sudo apt-get install libatlas-base-dev

Probably too much, but it works

pip install sentence-transformers