Deep Life Sci

A LangChain Deep Agent assistant for biologists, bioinformaticians, and clinical researchers.

Capabilities

• Literature question-answering - scan hundreds of papers and trial records at once to perform deep literature searches

• Data analysis via code execution - generate and execute code in a safely contained sandbox to perform almost any data analysis

• File and figure generation - create CSV and Excel files of data, Word docs such as clinical or lab protocols, and data visualizations and plots

Data sources

• PubMed - over 40 million scientific abstracts

• PMC full texts - full text of over 8 million open-access papers

• ClinicalTrials.gov - records from over 600,000 trials

• Web search - agentic search over the entire open web

• CSV/Excel upload - upload your data files and let the agent do analyses on them

Quickstart

1. Get LangSmith

You need a LangSmith account. Setup will prompt you to add your LANGSMITH_API_KEY.

Model calls go through the LangSmith LLM gateway, so your workspace also needs the provider key behind them, added once under Settings → Integrations → Provider Secrets as OPENAI_API_KEY and/or ANTHROPIC_API_KEY. Add whichever providers the models you run use (the default is OpenAI).

LangSmith Sandboxes must also be enabled. Enable them from the Sandboxes tab in your LangSmith console. On a personal account on the free Developer tier you will need to add a credit card to use sandboxes, but you get free 5 LangSmith Compute Units (LCUs) per month, enough for ~650 agent runs.

2. Get the code

In the terminal:

git clone https://github.com/langchain-samples/deep-life-sci.git

cd deep-life-sci

Needs git, which setup also uses to fetch the chat UI.

3. Get uv

uv is a widely-used package manager for Python that allows the setup script to install the necessary libraries.

On macOS / Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

On Windows:

irm https://astral.sh/uv/install.ps1 | iex

4. Run the setup script

uv run scripts/setup.py

5. Run the agent

uv run scripts/dev.py                        # opens the chat UI in your browser (recommended)

# or

uv run agent "which papers base-edit PCSK9?" # runs headlessly in CLI

Ctrl-C to stop the running server.

Layout

scripts/              setup.py (one-time setup), dev.py (chat stack), build_snapshot.py
research_agent/       the agent: assembly, entry points, tools, prompts, middleware
evals/                LangSmith datasets + evaluators
ui/                   artifact components rendered by the chat frontend

Disclaimer

This is a demonstration project, intended for research and educational use. Its answers are generated by language models from published literature and trial registries, and may be incomplete, outdated, or wrong. It is not medical advice, and must not be used for clinical decision-making, diagnosis, or treatment.

Notes

The UI is a modified clone of agent-chat-ui in .chat-ui/.

Full text journal articles are only available if present in PMC's open-access subset. Only abstracts are available for paywalled papers.

MIT Licensed