.github/workflows | ||
.vscode | ||
backend | ||
frontend | ||
streamlit-demo | ||
.backend_env.example | ||
.frontend_env.example | ||
.gitignore | ||
docker-compose.yml | ||
LICENSE | ||
logo.png | ||
README.md |
Quivr - Your GenerativeAI Second Brain
Quivr is your GenerativeAI second brain, designed to easily store and retrieve unstructured information. It's like Obsidian but powered by generative AI.
Features
- Store Anything: Quivr can handle almost any type of data you throw at it. Text, images, code snippets, you name it.
- Generative AI: Quivr uses advanced AI to help you generate and retrieve information.
- Fast and Efficient: Designed with speed and efficiency in mind. Quivr makes sure you can access your data as quickly as possible.
- Secure: Your data is always under your control.
- Compatible Files:
- Text
- Markdown
- Powerpoint
- Excel
- Word
- Audio
- Video
- Open Source: Quivr is open source and free to use.
DEMO WITH STREAMLIT IS USING OLD VERSION
New version is using a new UI and is not yet deployed as it doesn't have all the features of the old version. Should be up and live before 25/05/23
Demo with GPT3.5
https://github.com/StanGirard/quivr/assets/19614572/80721777-2313-468f-b75e-09379f694653
Demo with Claude 100k context
https://github.com/StanGirard/quivr/assets/5101573/9dba918c-9032-4c8d-9eea-94336d2c8bd4
Getting Started with the new version
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. Old version readme is in the streamlit-demo folder here
Prerequisites
Make sure you have the following installed before continuing:
- Docker
- Docker Compose
You'll also need a Supabase account for:
- A new Supabase project
- Supabase Project API key
- Supabase Project URL
Installing
- Clone the repository
git clone git@github.com:StanGirard/Quivr.git && cd Quivr
- Copy the
.XXXXX_env
files
cp .backend_env.example .backend_env
cp .frontend_env.example .frontend_env
- Update the
.backend_env
file
Note that the supabase_service_key
is found in your Supabase dashboard under Project Settings -> API. Use the anon
public
key found in the Project API keys
section.
- Run the following migration scripts on the Supabase database via the web interface (SQL Editor ->
New query
)
-- Enable the pgvector extension to work with embedding vectors
create extension vector;
-- Create a table to store your documents
create table documents (
id bigserial primary key,
content text, -- corresponds to Document.pageContent
metadata jsonb, -- corresponds to Document.metadata
embedding vector(1536) -- 1536 works for OpenAI embeddings, change if needed
);
CREATE FUNCTION match_documents(query_embedding vector(1536), match_count int)
RETURNS TABLE(
id bigint,
content text,
metadata jsonb,
-- we return matched vectors to enable maximal marginal relevance searches
embedding vector(1536),
similarity float)
LANGUAGE plpgsql
AS $$
# variable_conflict use_column
BEGIN
RETURN query
SELECT
id,
content,
metadata,
embedding,
1 -(documents.embedding <=> query_embedding) AS similarity
FROM
documents
ORDER BY
documents.embedding <=> query_embedding
LIMIT match_count;
END;
$$;
and
create table
stats (
-- A column called "time" with data type "timestamp"
time timestamp,
-- A column called "details" with data type "text"
chat boolean,
embedding boolean,
details text,
metadata jsonb,
-- An "integer" primary key column called "id" that is generated always as identity
id integer primary key generated always as identity
);
- Run the app
docker compose build && docker compose up
Built With
Contributing
Open a pull request and we'll review it as soon as possible.