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atliliw/langchainRustAgent

RAG-based conversational AI system with layered compression, multi-agent collection, and hybrid retrieval (BM25 + vector). Built with Rust/Axum.

🛠 AI-built ⚡ AI-using Rust GitHub ↗
★ 1
stars
75
AI relevance
50
solo dev
1
tool sigs

SUMMARY AI summary by gpt-5-mini

A Rust-based retrieval-augmented generation (RAG) conversational system supporting multiple retrieval modes and dialogue compression strategies. Intended for developers and teams building RAG chat apps or experimenting with retrieval + LLM workflows. Key features: - Three retrieval modes: vector (Qdrant), BM25 (MongoDB), and RRF hybrid; endpoint to compare all three. - Dialogue compression: hierarchical and summary compression with protection for important info. - Multi-format document ingestion: TXT, PDF, Markdown, JSON, CSV; file upload via single-page web UI. - Backend: Rust + Axum; vector DB: Qdrant; BM25: MongoDB; conversation store: SQLite. - Uses OpenAI embeddings (text-embedding-ada-002) and GPT-3.5/4 for LLMs. - APIs for chat (/api/chat), upload, search variants, stats; config via config.toml; run with cargo. MIT license.

AI Coding Tools Used

This repository contains config files from these AI coding tools, indicating AI-assisted development.

OpenAI Codex (AGENTS.md) AGENTS.md

DETECTED Detected AI stack

AI-related keywords found in this repo's description, topics, or README summary — grouped by category. Each badge links to the corresponding ranking detail page.

🧠 LLM providers (1)
OpenAI
🔢 Embedding models (1)
text-embedding-ada
💾 Databases (2)
MongoDB SQLite
🌐 Web frameworks (1)
Axum

Language breakdown (by bytes)

CSS
1.9%
HTML
6%
Rust
69.4%
Shell
1.1%
JavaScript
21.1%
PowerShell
0.5%

Owner

Account
atliliw
Type
User
Followers
0

Dates

Created on GitHub 2026-04-28
Last push 2026-05-09
First seen here 2026-05-09
Last fetched 2026-05-09 18:18

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