diff --git a/README.md b/README.md
index a50fdc993..b67193df1 100644
--- a/README.md
+++ b/README.md
@@ -1,175 +1,128 @@
-# Quivr - Your GenerativeAI Second Brain
+# Quivr - Your Second Brain, Empowered by Generative AI
-
-
-
+
+
![Quivr-logo](./logo.png)
+
+
+
-Quivr is your GenerativeAI second brain, designed to easily store and retrieve unstructured information. It's like Obsidian but powered by generative AI.
+Quivr, your second brain, utilizes the power of GenerativeAI to store and retrieve unstructured information. Think of it as Obsidian, but turbocharged with AI capabilities.
+## Key Features 🎯
-## Features
+- **Universal Data Acceptance**: Quivr can handle almost any type of data you throw at it. Text, images, code snippets, we've got you covered.
+- **Generative AI**: Quivr employs advanced AI to assist you in generating and retrieving information.
+- **Fast and Efficient**: Designed with speed and efficiency at its core. Quivr ensures rapid access to your data.
+- **Secure**: Your data, your control. Always.
+- **File Compatibility**:
+ - Text
+ - Markdown
+ - PDF
+ - Powerpoint
+ - Excel
+ - Word
+ - Audio
+ - Video
+- **Open Source**: Freedom is beautiful, so is Quivr. Open source and free to use.
-- **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**
- - **PDF**
- - **Powerpoint**
- - **Excel**
- - **Word**
- - **Audio**
- - **Video**
-- **Open Source**: Quivr is open source and free to use.
+## Demo Highlights 🎥
+> **Please note: The DEMO WITH STREAMLIT IS USING AN OLD VERSION**
+> The new version showcases a fresh UI, however, it is not yet deployed as it lacks some features of the old version. Expected to go live before 25/05/23
-
-
-### 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
+### **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
-### Demo with Claude 100k context
-https://github.com/StanGirard/quivr/assets/5101573/9dba918c-9032-4c8d-9eea-94336d2c8bd4
-
-### Demo of new version - WIP
-
-
+### **Demo of the new version (Work in progress)**:
https://github.com/StanGirard/quivr/assets/19614572/a6463b73-76c7-4bc0-978d-70562dca71f5
+## Getting Started: New Version 🚀
+Follow these instructions to get a copy of the project up and running on your local machine for development and testing purposes.
-## 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](streamlit-demo/README.md)
+**Old version's readme** is located in the streamlit-demo folder [here](streamlit-demo/README.md)
-### Prerequisites
+### Prerequisites 📋
-Make sure you have the following installed before continuing:
+Before you proceed, ensure you have the following installed:
- Docker
- Docker Compose
-You'll also need a [Supabase](https://supabase.com/) account for:
+Additionally, you'll need a [Supabase](https://supabase.com/) account for:
-- A new Supabase project
+- Creating a new Supabase project
- Supabase Project API key
- Supabase Project URL
-### Installing
+### Installation Steps 💽
-- Clone the repository by running **one** of these commands:
+- **Step 1**: Clone the repository using **one** of these commands:
- 1. If you don't have an SSH key set up:
+ - If you don't have an SSH key set up:
+
```bash
git clone https://github.com/StanGirard/Quivr.git && cd Quivr
```
-
- 2. If you have an SSH key set up or want to add it (https://docs.github.com/en/authentication/connecting-to-github-with-ssh/adding-a-new-ssh-key-to-your-github-account)
-
+ - If you have an SSH key set up or want to add it ([guide here](https://docs.github.com/en/authentication/connecting-to-github-with-ssh/adding-a-new-ssh-key-to-your-github-account))
+
```bash
git clone git@github.com:StanGirard/Quivr.git && cd Quivr
```
-- Copy the `.XXXXX_env` files
+- **Step 2**: Copy the `.XXXXX_env` files
```bash
cp .backend_env.example .backend_env
cp .frontend_env.example .frontend_env
```
-- Update the `.backend_env` file
+- **Step 3**: 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._
+> _Your `supabase_service_key` can be found in your Supabase dashboard under Project Settings -> API. Use the `anon` `public` key found in the `Project API keys` section._
+- **Step 4**: Run the following migration scripts on the Supabase database via the web interface (SQL Editor -> `New query`)
-- Run the following migration scripts on the Supabase database via the web interface (SQL Editor -> `New query`)
+[Migration Script 1](scripts/supabase_vector_store_document.sql)
-```sql
--- Enable the pgvector extension to work with embedding vectors
- create extension vector;
+[Migration Script 2](scripts/supabase_usage_table.sql)
- -- 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
-
-```sql
-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
+- **Step 5**: Launch the app
```bash
docker compose build && docker compose up
```
-## Built With
+- **Step 6**: Navigate to `localhost:3000` in your browser
-* [Python](https://www.python.org/) - The programming language used.
-* [Supabase](https://supabase.io/) - The open source Firebase alternative.
-## Contributing
-Open a pull request and we'll review it as soon as possible.
-You can find all the subject we would like to tackle here -> https://github.com/users/StanGirard/projects/5
+## Contributors ✨
-Don't hesitate to come with new ones too :)
+Thanks goes to these wonderful people:
+
+
+
+
+## Contribute 🤝
+
+Got a pull request? Open it, and we'll review it as soon as possible. Check out our project board [here](https://github.com/users/StanGirard/projects/5) to see what we're currently focused on, and feel free to bring your fresh ideas to the table!
+
+
+- [Roadmap](https://github.com/users/StanGirard/projects/5)
+- [Open Issues](https://github.com/StanGirard/quivr/issues)
+- [Open Pull Requests](https://github.com/StanGirard/quivr/pulls)
+- [Good First Issues](https://github.com/StanGirard/quivr/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)
+- [Frontend Issues](https://github.com/StanGirard/quivr/issues?q=is%3Aopen+is%3Aissue+label%3Afrontend)
+- [Backend Issues](https://github.com/StanGirard/quivr/issues?q=is%3Aopen+is%3Aissue+label%3Abackend)
+
+## Star History 🌟
-## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=StanGirard/quivr&type=Date)](https://star-history.com/#StanGirard/quivr&Date)
diff --git a/logo.png b/logo.png
index f141fdb10..510115baf 100644
Binary files a/logo.png and b/logo.png differ
diff --git a/scripts/supabase_usage_table.sql b/scripts/supabase_usage_table.sql
new file mode 100644
index 000000000..4573ba9c5
--- /dev/null
+++ b/scripts/supabase_usage_table.sql
@@ -0,0 +1,12 @@
+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
+ );
\ No newline at end of file
diff --git a/scripts/supabase_vector_store_document.sql b/scripts/supabase_vector_store_document.sql
new file mode 100644
index 000000000..b832df1b4
--- /dev/null
+++ b/scripts/supabase_vector_store_document.sql
@@ -0,0 +1,36 @@
+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 $$
+ # variable_conflict use_column
+BEGIN
+ RETURN query
+ SELECT
+ id,
+ content,
+ metadata,
+ embedding,
+ 1 -(documents.embedding <=> query_embedding) AS similarity
+ FROM
+ documents
+ ORDER BY
+ documents.embedding <=> query_embedding
+ LIMIT match_count;
+END;
+$$;
\ No newline at end of file