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AItrika

Enhance your knowledge in medical research.

AItrika (formerly PubGPT) is a tool that can extract lots of relevant informations inside medical papers in an easy way:

  • Abstract
  • Full text (when available)
  • Genes
  • Diseases
  • Mutations
  • Associations between genes and diseases
  • MeSH terms
  • Other terms
  • Results
  • Bibliography

And so on!

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🚀 Run the demo app

You can try AItrika with the Streamlit app by running:

streamlit run app.py

Or you can use it a script by running:

python main.py

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📦 Install

To install everything, you need uv.

First of all, install uv with the command:

python main.py

After that, create a virtual environment with the command:

uv venv venv_name

Activate the virtual env:

source venv_name/bin/activate

And install dependencies:

uv pip install -r requirements.in

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🔑 Set LLM API Keys

In order to set API keys, insert your keys into the env.example file and rename it to .env.

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🔍 Usage

You can easily get informations of a paper by passing a PubMed ID:

from aitrika.engine.aitrika import OnlineAItrika
aitrika_engine = OnlineAItrika(pubmed_id=pubmed_id)
title = aitrika_engine.get_title()
print(title)

Or you can parse a local pdf:

from aitrika.engine.aitrika import LocalAItrika
aitrika_engine = LocalAItrika(pdf_path = pdf_path)
title = aitrika_engine.get_title()
print(title)

Breast cancer genes: beyond BRCA1 and BRCA2.

You can get other informations, like the associations between genes and diseases:

associations = aitrika_engine.get_associations()

[
  {
    "gene": "BRIP1",
    "disease": "Breast Neoplasms"
  },
  {
    "gene": "PTEN",
    "disease": "Breast Neoplasms"
  },
  {
    "gene": "CHEK2",
    "disease": "Breast Neoplasms"
  },
]
...

Or you can get a nice formatted DataFrame:

associations = aitrika_engine.associations(dataframe = True)

      gene                          disease
0    BRIP1                 Breast Neoplasms
1     PTEN                 Breast Neoplasms
2    CHEK2                 Breast Neoplasms
...

With the power of RAG, you can query your document:

## Prepare the documents
documents = generate_documents(content=abstract)

## Set the LLM
llm = GroqLLM(documents=documents, api_key=os.getenv("GROQ_API_KEY"))

## Query your document
query = "Is BRCA1 associated with breast cancer?"
print(llm.query(query=query))

The provided text suggests that BRCA1 is associated with breast cancer, as it is listed among the high-penetrance genes identified in family linkage studies as responsible for inherited syndromes of breast cancer.

Or you can extract other informations:

results = engine.extract_results(llm=llm)
print(results)

** RESULTS **

- High-penetrance genes - BRCA1, BRCA2, PTEN, TP53 - responsible for inherited syndromes
- Moderate-penetrance genes - CHEK2, ATM, BRIP1, PALB2, RAD51C - associated with moderate BC risk
- Low-penetrance alleles - common alleles - associated with slightly increased or decreased risk of BC
- Current clinical practice - high-penetrance genes - widely used
- Future prospect - all familial breast cancer genes - to be included in genetic test
- Research need - clinical management - of moderate and low-risk variants

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🚀 Run the API

To run the AItrika API, follow these steps:

  1. Ensure you have set up your environment and installed all dependencies as described in the Installation section.

  2. Run the API server using the following command:

python api.py

The API will start running on http://0.0.0.0:8000. You can now make requests to the various endpoints:

  • /associations: Get associations from a PubMed article
  • /abstract: Get abstract of a PubMed article
  • /query: Query a PubMed article
  • /results: Get results from a PubMed article
  • /participants: Get number of participants from a PubMed article
  • /outcomes: Get outcomes from a PubMed article

You can use tools like curl, Postman, or any HTTP client to interact with the API. For example:

curl -X POST "http://localhost:8000/abstract" -H "Content-Type: application/json" -d '{"pubmed_id": 12345678}'

The API documentation is automatically generated and saved to docs/api-reference/openapi.json. You can use this file with tools like Swagger UI for a more interactive API exploration experience.

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Support the Project

If you find this project useful, please consider supporting it:

  • 🌟 Star the project on GitHub
  • 🐛 Report bugs or suggest new features
  • 🤝 Contribute with pull requests
  • ☕️ Buy me a coffee or consider a sponsor.

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Commercial / Business use

If you’re using this project in a business or commercial context, please contact me.

I’m available for consulting, custom development, or commercial licensing.

Your support helps keep this project active and continuously improving. Thank you!

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License

AItrika is licensed under the Apache 2.0 License. See the LICENSE file for more details.

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Installation