ragnosis 0.1.5

LLM-retrieval based knowledge grounding

LLM-retrieval based knowledge grounding

ragnosis contains tools for extracting hypotheses from scientific paper PDFs, extracting entities according to a user model, and grounding entities to ontology terms.

Installation

This project relies on langchain-rdf which should be installed separately.

To install langchain-rdf run:

pip install git+https://github.com/vemonet/langchain-rdf.git

ragnosis can be installed using pip:

pip install ragnosis

Usage

Hypothesis extraction

Hypotheses can be extracted from PDF files by running:

ragnosis extract_hypothesis path/to/paper.pdf [--model MODEL] [--temperature TEMP] [--out_file OUTPUT.txt]

Creating ontology indices

Before grounding entities, vector store indices must be created from your ontology files. One or more OWL files can be provided to create a single index. force_create will overwrite an existing index. The index will be saved in the index_directory with the name merged_index unless index_name is specified:

ragnosis create_index index_directory path/to/ontology1.owl path/to/ontology2.owl [--force_create] [--index_name NAME]

Hypothesis grounding

To ground entities in an input text to ontology terms:

ragnosis ground_hypothesis "your hypothesis text" path/to/yaml_map.yaml [--model MODEL] [--temperature TEMP] [--out_md OUTPUT.md]

The YAML file should map entity extraction categories to pre-built vector store indices, for example:

bio_components: path/to/go_index
genes_proteins: path/to/protein_index
taxa: path/to/taxonomy_index
small_molecules: path/to/chebi_index

where the path/to/go_index refers to pre-built vector store files path/to/go_index.faiss and path/to/go_index.pkl. A sample YAML file can be found in the ragnosis repository.

LLM Model Selection

For all commands that accept a --model parameter, you can specify:

• OpenAI models with prefix openai/ (e.g., openai/gpt-4o)
• Ollama models with prefix ollama/ (e.g., ollama/llama3)

The default model is openai/gpt-4o. When using OpenAI models, make sure to set your OPENAI_API_KEY environment variable before running the commands. For Ollama, make sure to have ollama installed and running.

Output Files

Most commands support saving output in markdown format using the --out_md parameter. For hypothesis extraction, use --out_file to save the extracted hypothesis as plain text. If the out file parameter is not provided, no output file will be saved. The output will be printed to the console in all cases.