Welcome to AIAgents4Pharma – an open-source project by Team VPE that brings together AI-driven tools to help researchers and pharma interact seamlessly with complex biological data.
Our toolkit currently consists of the following agents:
Please use version 1.26.2 or later for better support with NVIDIA NIM models.
pip install aiagents4pharma
Check out the tutorials on each agent for detailed instructions.
We now have Talk2AIAgents4Pharma
, Talk2Biomodels
, and Talk2Scholars
available on Docker Hub.
Talk2AIAgents4Pharma and Talk2KnowledgeGraphs require Ollama for embedding models, so Docker Compose is used to run both containers in the same network.
# Navigate to the correct directory before setting up environment variables.
# Use one of the following commands based on the agent you want to use:
cd AIAgents4Pharma/aiagents4pharma/talk2aiagents4pharma
cd AIAgents4Pharma/aiagents4pharma/talk2knowledgegraphs
.env.example
file and rename it to .env
:sh
cp .env.example .env
.env
file and add your API keys:plaintext
OPENAI_API_KEY=your_openai_api_key
NVIDIA_API_KEY=your_nvidia_api_key
OLLAMA_HOST=http://ollama:11434
LANGCHAIN_TRACING_V2=true
LANGCHAIN_API_KEY=your_langchain_api_key_here
# Notes:
# The API endpoint for Ollama is already set in env.example.
# Both API keys (OPENAI_API_KEY and NVIDIA_API_KEY) are required for Talk2AIAgents4Pharma.
# If using Talk2KnowledgeGraphs separately, only the OPENAI_API_KEY is needed.
# Langsmith API for tracing is optional for both, set it in env.example if required.
To start the containers, run the following command:
docker compose --profile cpu up # for CPU mode
docker compose --profile nvidia up # for GPU mode
docker compose --profile amd up # for AMD mode
This will:
To Access the web app, open your browser and go to:
http://localhost:8501
To stop the containers, run:
docker compose down
bash
docker run -d \
--name talk2biomodels \
-e OPENAI_API_KEY=<your_openai_api_key> \
-e NVIDIA_API_KEY=<your_nvidia_api_key> \
-p 8501:8501 \
virtualpatientengine/talk2biomodels
bash
docker run -d \
--name talk2scholars \
-e OPENAI_API_KEY=<your_openai_api_key> \
-e ZOTERO_API_KEY=<your_zotero_api_key> \
-e ZOTERO_USER_ID=<your_zotero_user_id> \
-p 8501:8501 \
virtualpatientengine/talk2scholars
http://localhost:8501
You can create a free account at NVIDIA and apply for their
free credits here.
<your_openai_api_key>
, <your_nvidia_api_key>
, <your_zotero_api_key>
, and <your_zotero_user_id>
with your actual credentials.8501
, so run them on different ports if needed:bash
docker run -d -e OPENAI_API_KEY=<your_openai_api_key> -p 8501:8501 virtualpatientengine/talk2scholars
http://localhost:8501
.bash
git clone https://github.com/VirtualPatientEngine/AIAgents4Pharma
cd AIAgents4Pharma
bash
pip install -r requirements.txt
⚠️ The current version of T2KG requires additional Ollama library to be installed.
Ollama can be easily downloaded and installed from the following link: https://ollama.com/download
As an alternative, use the following commands to install the library using terminal and to pull necessary model:
curl -fsSL https://ollama.com/install.sh | sh
ollama pull nomic-embed-text
curl -L https://ollama.com/download/ollama-windows-amd64.zip -o ollama-windows-amd64.zip
tar -xzf .\ollama-windows-amd64.zip
start ollama serve
ollama pull nomic-embed-text
brew install ollama
ollama pull nomic-embed-text
ollama list
⚠️ pcst_fast 1.0.10
library requires Microsoft Visual C++ 14.0
or greater to be installed.
You can download Microsoft C++ Build Tools
from here.
bash
export OPENAI_API_KEY=....
export NVIDIA_API_KEY=....
You can create a free account at NVIDIA and apply for their
free credits here.
bash
export ZOTERO_API_KEY=....
export ZOTERO_USER_ID=....
Please note that ZOTERO keys are requried only if you want to launch Talk2Scholars. For all the other agents, please ignore this step.
bash
export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
Please note that this will create a new tracing project in your Langsmith
account with the name T2X-xxxx
, where X
can be AA4P
(Main Agent),
B
(Biomodels), S
(Scholars), KG
(KnowledgeGraphs), or C
(Cells).
If you skip the previous step, it will default to the name default
.
xxxx
will be the 4-digit ID created for the session.
bash
streamlit run app/frontend/streamlit_app_<agent>.py
For detailed instructions on each agent, please refer to their respective modules.
We welcome contributions to AIAgents4Pharma! Here’s how you can help:
git checkout -b feat/feature-name
)git commit -m 'feat: Add new feature'
)git push origin feat/feature-name
)Note: We welcome all contributions, not just programming-related ones. Feel free to open bug reports, suggest new features, or participate as a beta tester. Your support is greatly appreciated!
Feel free to reach out to us via Discussions.
Check out our CONTRIBUTING.md for more information.
Questions/Bug reports/Feature requests/Comments/Suggestions? We welcome all. Please use Issues
or Discussions
😀