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deepxiv-cli
// Access academic papers (arXiv, PMC, and coming soon bioRxiv, medRxiv) via CLI with hybrid search and intelligent content extraction
// Access academic papers (arXiv, PMC, and coming soon bioRxiv, medRxiv) via CLI with hybrid search and intelligent content extraction
Build a markdown baseline table for a research topic using deepxiv search, brief, head, and experiment-section reads, extracting paper title, URL, open-source status, datasets, benchmark scores, and other comparison-ready details.
Summarize recent hot academic papers using deepxiv trending, brief, head, and section reads, then produce a markdown digest highlighting what each paper is about and which papers deserve deeper reading.
| name | deepxiv-cli |
| version | 0.2.0 |
| description | Access academic papers (arXiv, PMC, and coming soon bioRxiv, medRxiv) via CLI with hybrid search and intelligent content extraction |
| frameworks | ["codex","langchain","claude-code","custom-agents"] |
| use_cases | ["literature-search","paper-analysis","knowledge-synthesis","research-assistant"] |
What: Access open access academic papers (arXiv, PMC, bioRxiv, medRxiv) through a powerful CLI tool.
What you can do:
When to use: User wants to search, read, or analyze academic papers
I want to... → Use this command
| Goal | Command | Example |
|---|---|---|
| Find papers on a topic | deepxiv search | deepxiv search "agent memory" --limit 5 |
| Quickly understand a paper | deepxiv paper <id> --brief | deepxiv paper 2409.05591 --brief |
| Read specific section | deepxiv paper <id> --section | deepxiv paper 2409.05591 --section Introduction |
| See paper structure | deepxiv paper <id> --head | deepxiv paper 2409.05591 --head |
| Preview first 10k chars | deepxiv paper <id> --preview | deepxiv paper 2409.05591 --preview |
| Get full text | deepxiv paper <id> | deepxiv paper 2409.05591 |
| Access biomedical paper | deepxiv pmc <id> | deepxiv pmc PMC544940 |
| Intelligent analysis | deepxiv agent query | deepxiv agent query "analyze this paper" |
deepxiv search)When to use: Finding relevant papers on a topic
# Basic search (quick)
deepxiv search "agent memory" --limit 5
# Advanced search with filters
deepxiv search "transformer" --mode bm25 --format json
deepxiv search "LLM" --categories cs.AI,cs.CL --min-citations 100
# Date range
deepxiv search "vision models" --date-from 2024-01-01 --date-to 2024-12-31
Expected output: List of papers with title, arxiv_id, score, citation count Token cost: ~500-1000 tokens per search Tips:
--limit 3-5 for quick overview--format json for downstream processingbm25_weight and vector_weight for different search stylesdeepxiv paper)When to use: Understanding specific papers (choose format by depth needed)
deepxiv paper 2409.05591 --brief
# ✓ Best for: Quick understanding
# → Title, TLDR, keywords, citation count
# Token cost: ~500 tokens
# Use when: "What's this paper about?"
deepxiv paper 2409.05591 --head
# ✓ Best for: Understanding paper organization
# → Metadata, all sections with summaries
# Token cost: ~1-2k tokens
# Use when: "What does this paper contain?"
deepxiv paper 2409.05591 --preview
# ✓ Best for: Fast preview without full read
# → First ~10k characters
# Token cost: ~2k tokens
# Use when: "Let me scan the introduction"
deepxiv paper 2409.05591 --section Introduction
# ✓ Best for: Reading one section in detail
# → Full section content
# Token cost: ~1-5k tokens (varies by section)
# Use when: "I only need the introduction"
deepxiv paper 2409.05591
# or explicitly: deepxiv paper 2409.05591 --raw
# ✓ Best for: Full text analysis
# → Complete paper in markdown
# Token cost: ~10-50k tokens
# Use when: "I need to thoroughly analyze this"
deepxiv pmc)When to use: Need medical, biology, or biomedical research
# Quick metadata
deepxiv pmc PMC544940 --head
# Full paper
deepxiv pmc PMC544940
Expected output: Paper metadata or complete paper JSON Token cost: ~1-2k tokens (metadata), ~10-30k tokens (full)
deepxiv token)When to use: Check your API token status
deepxiv token
# Shows current token and daily limit info
Note: Token auto-registers on first use, saves to ~/.env
deepxiv agent)When to use: Need analysis beyond simple retrieval
# One-time query
deepxiv agent query "What are key innovations in this paper?"
# Multi-turn reasoning
deepxiv agent query "Compare these two approaches" --max-turn 10 --verbose
# First time setup
deepxiv agent config
# Configure your LLM (OpenAI, DeepSeek, OpenRouter, etc.)
Token cost: Varies by reasoning depth Requirements: Requires langgraph and langchain-core
# Step 1: Get brief info
deepxiv paper 2409.05591 --brief
# Step 2: Read introduction
deepxiv paper 2409.05591 --section Introduction
# Step 3: Check results (optional)
deepxiv paper 2409.05591 --section Results
Total tokens: ~2-3k | Use case: Quick assessment before deciding to read fully
# Step 1: Understand structure
deepxiv paper 2409.05591 --head
# Step 2: Read key sections
deepxiv paper 2409.05591 --section Introduction
deepxiv paper 2409.05591 --section Methods
deepxiv paper 2409.05591 --section Results
# Step 3: AI analysis
deepxiv agent query "Summarize the main contributions"
Total tokens: ~10-15k | Use case: Thorough understanding
# Step 1: Find relevant papers
deepxiv search "agent memory" --limit 5
# Step 2: Quick assess each
for id in results; do
deepxiv paper $id --brief
done
# Step 3: Deep read top 2
deepxiv paper <top_id_1>
deepxiv paper <top_id_2>
Total tokens: ~5-10k | Use case: Literature review
| Capability | Details |
|---|---|
| Hybrid Search | BM25 + Vector search across 2M+ arXiv papers |
| Smart Summaries | AI-generated TLDRs and keywords |
| Section Access | Read specific sections without loading full text |
| Biomedical Access | PubMed Central (PMC) papers |
| Open Access Only | arXiv, PMC, bioRxiv (coming), medRxiv (coming) |
| Intelligent Analysis | ReAct agent with multi-turn reasoning |
| Multiple LLMs | Compatible with OpenAI, DeepSeek, OpenRouter, etc. |
| Limitation | Note |
|---|---|
| Subscription Journals | Only open access papers (by design) |
| Real-time Updates | arXiv has ~1-2 day delay |
| Paywalled Content | Cannot access IEEE, ACM, etc. journals |
| Daily Limits | 10,000 requests/day free (email for more) |
| Proprietary Data | Only academic papers, not internal docs |
deepxiv paper invalid_id
# Error: NotFoundError: Paper not found
Solution:
2409.05591)deepxiv search "topic"
# Error: RateLimitError: Daily limit reached
Solution:
tommy@chien.io with name, email, phone for higher limitdeepxiv paper 2409.05591
# Error: AuthenticationError: Invalid or expired token
Solution:
deepxiv config --token YOUR_NEW_TOKEN~/.env to auto-register new tokendeepxiv agent query "analyze"
# Error: langgraph not installed
Solution:
pip install deepxiv-sdk[agent]
deepxiv paper <large_paper_id>
# Error: Request timed out
Solution:
--brief or --head instead of full paper--section to read specific partsReader(timeout=180)Format: Show title, arxiv_id, brief context
1. Title of Paper (2409.05591)
- Field: Computer Science / AI
- Citations: 150
- Key idea: Brief 1-line summary of main contribution
Always mention what command was used:
From `deepxiv paper 2409.05591 --brief`:
- Title: MemGPT: Towards LLMs as Operating Systems
- TLDR: Introduces hierarchical memory management for extended context
- Key concepts: agent memory, context management, LLM systems
- (~500 tokens)
Use JSON format when:
deepxiv search "topic" --format json # Pipe to other tools
When planning queries, consider token costs:
Quick Summary: 500 tokens
Metadata (--head): 1-2k tokens
One Section: 1-5k tokens (depends on section)
Full Paper: 10-50k tokens
Search Query: 0.5-1k tokens
Agent Analysis: 5-20k tokens (reasoning depth)
Recommendation: For general use, stick to --brief and --section to keep tokens under 5k per query.
for id in 2409.05591 2504.21776 2503.04975; do
echo "=== $id ==="
deepxiv paper $id --brief
done
deepxiv search "topic" --format json | jq '.results[] | .arxiv_id'
from deepxiv_sdk import Reader
reader = Reader(token="YOUR_TOKEN", timeout=120, max_retries=5)
Command not working?
deepxiv <command> --help
Need a higher daily limit?
Email: tommy@chien.io with name, email, phone
Found a bug? GitHub Issues
Learn more? Full Documentation
--brief - Always start with brief overviewdeepxiv token before large batches--format json for piping, plain text for humansLast Updated: 2024 | Version: 0.2.0 | Status: Production Ready