Search Papers

curl -X GET "https://api.paperguide.ai/v1/search?query=large language models for scientific literature review&source=arxiv&field_of_study=computer_science&year=2024&limit=10&format=bibtex" \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY"

{
  "results": [
    {
      "id": "arxiv:2401.12345",
      "title": "Large Language Models for Scientific Literature Review",
      "authors": [
        "Jane Doe",
        "John Smith"
      ],
      "year": 2024,
      "source": "arxiv",
      "field_of_study": "computer_science",
      "abstract": "This paper explores how large language models can assist with scientific literature review through semantic retrieval and synthesis workflows.",
      "url": "https://arxiv.org/abs/2401.12345"
    },
    {
      "id": "s2:987654321",
      "title": "Semantic Search Methods for Scholarly Discovery",
      "authors": [
        "Alice Brown",
        "David Lee"
      ],
      "year": 2023,
      "source": "semantic_scholar",
      "field_of_study": "computer_science",
      "abstract": "We present semantic search techniques for discovering and ranking relevant scholarly papers across large academic corpora.",
      "url": "https://www.semanticscholar.org/paper/987654321"
    }
  ]
}

curl --request GET \
  --url "https://api.paperguide.ai/v1/search?query=retrieval%20augmented%20generation&field_of_study=computer_science&year=2024&limit=3" \
  --header "x-api-key: pg_api_example_9xmk7q2r"

{
  "results": [
    {
      "id": "649f2b7c1a2d4e8f9c0a1234",
      "title": "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks",
      "authors": [
        "Patrick Lewis",
        "Ethan Perez",
        "Aleksandara Piktus"
      ],
      "year": 2024,
      "source": "semantic_scholar",
      "field_of_study": "computer_science",
      "abstract": "This paper studies retrieval-augmented generation methods for knowledge-intensive natural language processing tasks.",
      "url": "https://api.paperguide.ai/papers/649f2b7c1a2d4e8f9c0a1234"
    },
    {
      "id": "649f2b7c1a2d4e8f9c0a5678",
      "title": "Efficient Indexing Strategies for Retrieval-Augmented Systems",
      "authors": [
        "Jane Chen",
        "Marcus Hill"
      ],
      "year": 2024,
      "source": "arxiv",
      "field_of_study": "computer_science",
      "abstract": "The paper evaluates indexing strategies that improve retrieval quality and latency in large-scale retrieval-augmented systems.",
      "url": "https://api.paperguide.ai/papers/649f2b7c1a2d4e8f9c0a5678"
    },
    {
      "id": "649f2b7c1a2d4e8f9c0a9012",
      "title": "Grounding Language Models with External Research Corpora",
      "authors": [
        "Sara Ahmed",
        "David Park"
      ],
      "year": 2024,
      "source": "pubmed",
      "field_of_study": "computer_science",
      "abstract": "This work explores retrieval pipelines that ground language model outputs in external research corpora.",
      "url": "https://api.paperguide.ai/papers/649f2b7c1a2d4e8f9c0a9012"
    }
  ]
}