🧠
Search With Lepton model by leptonai
⭐ 45.9
🧠
Model

Search With Lepton

by leptonai gh-tool--leptonai--search_with_lepton
Nexus Index
45.9 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 68
R: Recency 74
Q: Quality 70
Tech Context
Vital Performance
0 DL / 30D
0.0%
Source →
Audited 45.9 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID gh-tool--leptonai--search_with_lepton
License Apache-2.0
Provider github
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{gh_tool__leptonai__search_with_lepton,
  author = {leptonai},
  title = {Search With Lepton Model},
  year = {2026},
  howpublished = {\url{https://github.com/leptonai/search_with_lepton}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
leptonai. (2026). Search With Lepton [Model]. Free2AITools. https://github.com/leptonai/search_with_lepton

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🐙 Git Clone
git clone https://github.com/leptonai/search_with_lepton

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
45.9
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 68
Recency (R) 74
Quality (Q) 70

đŸ’Ŧ Index Insight

FNI V2.0 for Search With Lepton: Semantic (S:50), Authority (A:0), Popularity (P:68), Recency (R:74), Quality (Q:70).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

📊

Find Training Datasets

Discover datasets compatible with this model

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Compare Benchmarks

See how this model ranks on standard tests

⚡

Deployment Guide

Understand deployment options

Technical Deep Dive

Search with Lepton

Build your own conversational search engine using less than 500 lines of code.
Live Demo

Features

  • Built-in support for LLM
  • Built-in support for search engine
  • Customizable pretty UI interface
  • Shareable, cached search results

Setup Search Engine API

There are two default supported search engines: Bing and Google.

To use the Bing Web Search API, please visit this link to obtain your Bing subscription key.

You have three options for Google Search: you can use the SearchApi Google Search API from SearchApi, Serper Google Search API from Serper, or opt for the Programmable Search Engine provided by Google.

Setup LLM and KV

[!NOTE] We recommend using the built-in llm and kv functions with Lepton. Running the following commands to set up them automatically.

shell 
pip install -U leptonai openai && lep login

Obtain Your Lepton AI Workspace Token

You can copy your workspace toke from the Lepton AI Dashboard → Settings → Tokens.

Build

  1. Set Bing subscription key
shell 
export BING_SEARCH_V7_SUBSCRIPTION_KEY=YOUR_BING_SUBSCRIPTION_KEY
  1. Set Lepton AI workspace token
shell 
export LEPTON_WORKSPACE_TOKEN=YOUR_LEPTON_WORKSPACE_TOKEN
  1. Build web
shell 
cd web && npm install && npm run build
  1. Run server
shell 
BACKEND=BING python search_with_lepton.py

For Google Search using SearchApi:

shell 
export SEARCHAPI_API_KEY=YOUR_SEARCHAPI_API_KEY
BACKEND=SEARCHAPI python search_with_lepton.py

For Google Search using Serper:

shell 
export SERPER_SEARCH_API_KEY=YOUR_SERPER_API_KEY
BACKEND=SERPER python search_with_lepton.py

For Google Search using Programmable Search Engine:

shell 
export GOOGLE_SEARCH_API_KEY=YOUR_GOOGLE_SEARCH_API_KEY
export GOOGLE_SEARCH_CX=YOUR_GOOGLE_SEARCH_ENGINE_ID
BACKEND=GOOGLE python search_with_lepton.py

Deploy

You can deploy this to Lepton AI with one click:

Deploy with Lepton AI

You can also deploy your own version via

shell 
lep photon run -n search-with-lepton-modified -m search_with_lepton.py --env BACKEND=BING --env BING_SEARCH_V7_SUBSCRIPTION_KEY=YOUR_BING_SUBSCRIPTION_KEY

Learn more about lep photon here.

🚀 Quick Start

bash 
pip install -U leptonai openai && lep login

⚠ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.
0
🐙 Data Source: GitHub ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on GitHub metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
gh-tool--leptonai--search_with_lepton
slug
leptonai--search_with_lepton
source
github
author
leptonai
license
Apache-2.0
tags
ai, ai-applications, leptonai, llm, typescript

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
other

📊 Engagement & Metrics

downloads
0
stars
0
forks
0

Data indexed from public sources. Updated daily.