Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

feat(docs): Adds a logo #13

Merged
merged 1 commit into from
Mar 6, 2025
Merged

feat(docs): Adds a logo #13

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 7 additions & 5 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,8 +1,10 @@
# inception
Our microservice for generating embeddings from blocks of text
# Inception v2 - Text Embedding Service
<img align="right" src="https://github.com/user-attachments/assets/7ec21ced-43a3-4c72-995c-70c3832d594e" alt="A logo for the project showing a document and some AI sparkles.">

A high-performance FastAPI service for generating text embeddings using SentenceTransformers, specifically designed for processing legal documents and search queries. The service efficiently handles both short search queries and lengthy court opinions, generating semantic embeddings that can be used for document similarity matching and semantic search applications. It includes support for GPU acceleration when available.
# Inception

Inception is our microservice for generating embeddings from blocks of text.

It is a high-performance FastAPI service that generates text embeddings using SentenceTransformers, specifically designed for processing legal documents and search queries. The service efficiently handles both short search queries and lengthy court opinions, generating semantic embeddings that can be used for document similarity matching and semantic search applications. It includes support for GPU acceleration when available.

The service is optimized to handle two main use cases:
- Embedding search queries: Quick, CPU-based processing for short search queries
Expand Down Expand Up @@ -379,4 +381,4 @@ curl http://localhost:8005/metrics
## Requirements

- Python 3.12+
- CUDA-compatible GPU (highly recommended, for long texts embedding)
- CUDA-compatible GPU (highly recommended, for long texts embedding)