https://github.com/virtualpatientengine/aiagents4pharma
AI Agents for drug discovery, drug development, and other pharmaceutical R&D
https://github.com/virtualpatientengine/aiagents4pharma
ai-agents biomodels knowledge-graph langchain langgraph qsp-modeling semantic-scholar streamlit
Last synced: about 1 year ago
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AI Agents for drug discovery, drug development, and other pharmaceutical R&D
- Host: GitHub
- URL: https://github.com/virtualpatientengine/aiagents4pharma
- Owner: VirtualPatientEngine
- License: mit
- Created: 2024-10-30T15:02:16.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-28T21:19:25.000Z (about 1 year ago)
- Last Synced: 2025-04-06T22:05:57.568Z (about 1 year ago)
- Topics: ai-agents, biomodels, knowledge-graph, langchain, langgraph, qsp-modeling, semantic-scholar, streamlit
- Language: Python
- Homepage: https://virtualpatientengine.github.io/AIAgents4Pharma/
- Size: 154 MB
- Stars: 25
- Watchers: 1
- Forks: 35
- Open Issues: 62
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
Awesome Lists containing this project
README
[](https://github.com/VirtualPatientEngine/AIAgents4Pharma/actions/workflows/tests_talk2biomodels.yml)
[](https://github.com/VirtualPatientEngine/AIAgents4Pharma/actions/workflows/tests_talk2cells.yml)
[](https://github.com/VirtualPatientEngine/AIAgents4Pharma/actions/workflows/tests_talk2knowledgegraphs.yml)
[](https://github.com/VirtualPatientEngine/AIAgents4Pharma/actions/workflows/tests_talk2scholars.yml)
[](https://github.com/VirtualPatientEngine/AIAgents4Pharma/actions/workflows/tests_talk2aiagents4pharma.yml)
## Introduction
Welcome to **AIAgents4Pharma** – an open-source project by [Team VPE](https://github.com/VirtualPatientEngine) 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:
- **Talk2BioModels** _(v1 released; v2 in progress)_: Engage directly with mathematical models in systems biology.
- **Talk2KnowledgeGraphs** _(v1 in progress)_: Access and explore complex biological knowledge graphs for insightful data connections.
- **Talk2Scholars** _(v1 in progress)_: Get recommendations for articles related to your choice. Download, query, and write/retrieve them to your reference manager (currently supporting Zotero).
- **Talk2Cells** _(v1 in progress)_: Query and analyze sequencing data with ease.
- **Talk2AIAgents4Pharma** _(v1 in progress)_: Converse with all the agents above (currently supports T2B and T2KG)
## Getting Started
### Installation
_Please use version 1.26.2 or later for better support with NVIDIA NIM models._
#### Option 1: PyPI
```bash
pip install aiagents4pharma
```
Check out the tutorials on each agent for detailed instructions.
#### Option 2: Docker Hub
_We now have `Talk2AIAgents4Pharma`, `Talk2Biomodels`, and `Talk2Scholars` available on Docker Hub._
##### **Run Talk2AIAgents4Pharma and Talk2KnowledgeGraphs**
Talk2AIAgents4Pharma and Talk2KnowledgeGraphs require Ollama for embedding models, so Docker Compose is used to run both containers in the same network.
###### **Setup Environment Variables**
1. Choose the app you want to use:
```sh
# 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
```
2. Copy the `.env.example` file and rename it to `.env`:
```sh
cp .env.example .env
```
3. Open the `.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.
```
4. Save the file.
To start the containers, run the following command:
```sh
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:
- Pull the latest images if they are not already available.
- Start both Talk2AIAgents4Pharma or Talk2KnowledgeGraphs and Ollama containers in the same network.
- Ensure Ollama is running first before launching Talk2AIAgents4Pharma or Talk2KnowledgeGraphs.
To Access the web app, open your browser and go to:
```
http://localhost:8501
```
To stop the containers, run:
```sh
docker compose down
```
##### **Run Talk2Biomodels and Talk2Scholars**
1. **Run the containers**
```bash
docker run -d \
--name talk2biomodels \
-e OPENAI_API_KEY= \
-e NVIDIA_API_KEY= \
-p 8501:8501 \
virtualpatientengine/talk2biomodels
```
```bash
docker run -d \
--name talk2scholars \
-e OPENAI_API_KEY= \
-e ZOTERO_API_KEY= \
-e ZOTERO_USER_ID= \
-p 8501:8501 \
virtualpatientengine/talk2scholars
```
2. **Access the Web App**
Open your browser and go to:
```
http://localhost:8501
```
_You can create a free account at NVIDIA and apply for their
free credits [here](https://build.nvidia.com/explore/discover)._
#### **Notes**
- Ensure you **replace ``, ``, ``, and ``** with your actual credentials.
- Both applications use **port `8501`**, so run them on different ports if needed:
```bash
docker run -d -e OPENAI_API_KEY= -p 8501:8501 virtualpatientengine/talk2scholars
```
Then, access it via `http://localhost:8501`.
#### Option 3: git
1. **Clone the repository:**
```bash
git clone https://github.com/VirtualPatientEngine/AIAgents4Pharma
cd AIAgents4Pharma
```
2. **Install dependencies:**
```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](https://ollama.com/download)
As an alternative, use the following commands to install the library using terminal and to pull necessary model:
- Ubuntu:
```
curl -fsSL https://ollama.com/install.sh | sh
ollama pull nomic-embed-text
```
- Windows:
```
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
```
- macOS:
```
brew install ollama
ollama pull nomic-embed-text
```
A list of pulled Ollama models can be checked using the following command:
```
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](https://visualstudio.microsoft.com/visual-cpp-build-tools/).
3. **Initialize OPENAI_API_KEY and NVIDIA_API_KEY**
```bash
export OPENAI_API_KEY=....
export NVIDIA_API_KEY=....
```
_You can create a free account at NVIDIA and apply for their
free credits [here](https://build.nvidia.com/explore/discover)._
4. **Initialize ZOTERO_API_KEY and ZOTERO_USER_ID**
```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._
5. **[Optional] Initialize LANGSMITH_API_KEY**
```bash
export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_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._
6. **Launch the app:**
```bash
streamlit run app/frontend/streamlit_app_.py
```
_Replace with the agent name you are interested to launch._
For detailed instructions on each agent, please refer to their respective modules.
---
## Contributing
We welcome contributions to AIAgents4Pharma! Here’s how you can help:
1. **Fork the repository**
2. **Create a new branch** for your feature (`git checkout -b feat/feature-name`)
3. **Commit your changes** (`git commit -m 'feat: Add new feature'`)
4. **Push to the branch** (`git push origin feat/feature-name`)
5. **Open a pull request** and reach out to any one of us below via Discussions:
_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!_
- **Talk2Biomodels/Talk2Cells**: [@gurdeep330](https://github.com/gurdeep330) [@lilijap](https://github.com/lilijap) [@dmccloskey](https://github.com/dmccloskey)
- **Talk2KnowledgeGraphs**: [@awmulyadi](https://github.com/awmulyadi) [@dmccloskey](https://github.com/dmccloskey)
- **Talk2Scholars**: [@ansh-info](https://github.com/ansh-info) [@gurdeep330](https://github.com/gurdeep330) [@dmccloskey](https://github.com/dmccloskey)
### Current Needs
- **Beta testers** for Talk2BioModels and Talk2Scholars.
- **Developers** with experience in Python and Bioinformatics and/or knowledge graphs for contributions to AIAgents4Pharma.
Feel free to reach out to us via Discussions.
Check out our [CONTRIBUTING.md](CONTRIBUTING.md) for more information.
---
## Feedback
Questions/Bug reports/Feature requests/Comments/Suggestions? We welcome all. Please use `Issues` or `Discussions` 😀