https://github.com/willacosta/genai-langchain-api
This is an Express service that provides authorization functionality and includes gen-AI features using RAG and Redis.
https://github.com/willacosta/genai-langchain-api
ai artificial-intelligence docker docker-compose express langchain langchain-js llm nodejs rag redis redis-database vector-database
Last synced: about 2 months ago
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This is an Express service that provides authorization functionality and includes gen-AI features using RAG and Redis.
- Host: GitHub
- URL: https://github.com/willacosta/genai-langchain-api
- Owner: WillACosta
- Created: 2024-09-16T14:43:28.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-23T15:48:36.000Z (over 1 year ago)
- Last Synced: 2024-10-23T18:31:14.374Z (over 1 year ago)
- Topics: ai, artificial-intelligence, docker, docker-compose, express, langchain, langchain-js, llm, nodejs, rag, redis, redis-database, vector-database
- Language: TypeScript
- Homepage:
- Size: 521 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Gen-AI API with Langchain and NodeJS
This is an Express service written in [TypeScript](https://www.typescriptlang.org/) that provides authorization functionality and includes gen-AI features, using RAG concepts, vector database and implements AI memory history with Redis DB.
## Resources
- [Express](https://expressjs.com/) and [Node](https://nodejs.org/en/) for creating backend service.
- [LangChain](https://js.langchain.com/docs/introduction/) for handling LLM and RAG functionality.
- [JWT](https://jwt.io/) for handling authentication
- [GoogleGenAI langchain](https://v02.api.js.langchain.com/modules/_langchain_google_genai.html) plugin.
- [Google Gemini - API](https://ai.google.dev/)
- [Docker](https://docs.docker.com/) containers for setting up environment.
- [Redis](https://redis.io/) database for storing AI messages.
- [ZOD](https://zod.dev/) as body parameters validation.
- [PostgreSQL](https://www.postgresql.org/) database for store user data
- [Prisma ORM](https://www.prisma.io/) for managing the database
- Automated [OpenAPI](https://www.openapis.org/what-is-openapi) specifications using [JsDocs](https://jsdoc.app/) and [Swagger UI](https://swagger.io/tools/swagger-ui/) for generating documentation.
- [Role-Based Access Control (RBAC)](https://www.redhat.com/en/topics/security/what-is-role-based-access-control) for managing API resources
- Rotate Logs using [Winston](https://github.com/winstonjs/winston)
## Project Structure
```yaml
common: common code and utilities for all modules
di: dependency injection container
modules: application features
module_name:
adapters: class adapters for external resources
dataproviders:
services:
application: application layer for controllers and routes
controllers:
routes:
core: application core logic
entities:
usecases:
utils: class and constant utilities for this module
```
### Search In Documents Flow
To perform a search in documents and ask questions about them, we have two endpoints for that:
- `POST /resources/docs`
- `POST /genai/search-in-documents`
On `/resources/docs` the documents are uploaded to local system and then broke down into small chunks to be stored on a vector database.
The `/genai/search-in-documents` endpoint uses RAG concept, it's responsible to create an Embedding of the user question, and retrieve the most relevant chunks from vector database using it as context for follow-up questions. Also, it uses Redis to store and retrieve chat history during user's session.
Check this process on the diagram below:
## Prerequisites
Before running the application, make sure you have the following installed:
- NodeJS (v20.12.1)
- PNPM (v9.7.0)
- Docker (v27.2.0)
## Running the application
1. Clone this repository
```shell
git clone https://github.com/WillACosta/genai-langchain-api
```
> Copy the `.env.example` file to `.env` and fill it with your own credentials. Get here:
> [Google Gemini](https://ai.google.dev/) | [LangChain](https://js.langchain.com/docs/introduction/)
```shell
cp .env.example .env
```
2. You'll need [Docker](https://docs.docker.com/) to setup and running the application services
> From the app's root directory, run the following command to build and running docker containers:
```shell
make run
```
> The application will be available at `http://localhost:3000`.
For more commands see `Makefile` or run `make help`.
## Documentation
The documentation process is automated using `swagger-ui-express` and `swagger-jsdoc` libraries, on each application route definition you will find a comment with the necessary specifications for that route in particular.
During the build process the application will handle the route comments and generate the final `OpenApi` specification for the `Swagger UI`.
After that you will be able to access: `localhost:3000/docs` in your browser and see the docs.
> The application will be available at `http://localhost:3000`.
## Prisma ORM
This project uses Prisma ORM (Object-Relational Mapping), at every modifications related to the database schema,
a new migration is needed, create a new one running:
```shell
npx prisma migrate dev
```
After that generate a new prisma client instance with:
```shell
npx prisma generate
```
## Authenticating and RBAC
This project uses `jwt` for authenticating users and managing sessions. It also uses Role-Based Access Control to limit some aspects of the API, such as user management.
Current supported roles are: [`admin`, `user`]:
| Endpoint | Admin | User |
| ------------------------------ | ----- | ---- |
| GET users/ | [x] | [x] |
| PATCH users/ | [x] | [x] |
| PATCH users/change-role/:id | [x] | |
| GET users/all | [x] | |
| DELETE users/:id | [x] | |
| GET status/ | [x] | [x] |
| POST /genai/translate | [x] | [x] |
| POST /genai/search-in-document | [x] | [x] |
| GET /genai/chat-history | [x] | [x] |
| POST /resources/docs | [x] | [x] |
## Services Dashboards
Qdrant Dashboard: https://localhost:6333/dashboard
PostgreSQL via Prisma: `npx prisma studio`
Redis: Access via vs code extension [Redis for VS Code](https://redis.io/docs/latest/develop/tools/redis-for-vscode/)