biomni
Workspace-local entry point for the Biomni repository at /home/vimalinx/Projects/bio_studio/repositories/active/Biomni. The repo is present, the top-level Python package can be imported by adding the repo to sys.path, and the README documents both agent-style usage (A1) and a large biomedical tool tree under biomni/tool/.
Quick Start
- Repository:
/home/vimalinx/Projects/bio_studio/repositories/active/Biomni
- Primary workflow: activate
biomni_e1, configure API keys, then use from biomni.agent import A1
- Fast local check:
python -c "import sys; sys.path.insert(0, '/home/vimalinx/Projects/bio_studio/repositories/active/Biomni'); import biomni; print(biomni.__file__)"
When To Use This Tool
- Running Biomni as a biomedical agent from the local repo
- Inspecting Biomni's tool modules for genomics, molecular biology, protocols, literature, and related domains
- Following the repo's own quick-start, profile-switching, or Gradio demo flows
- Auditing whether the current workspace is actually ready for Biomni execution
Common Patterns
# Enter the local repository
cd /home/vimalinx/Projects/bio_studio/repositories/active/Biomni
# Minimal repo-based import check
import sys
sys.path.insert(0, "/home/vimalinx/Projects/bio_studio/repositories/active/Biomni")
import biomni
print(biomni.__file__)
# Agent-style usage from the README
from biomni.agent import A1
agent = A1(path="./data", llm="claude-sonnet-4-20250514")
agent.go("Perform scRNA-seq annotation at [PATH] and generate meaningful hypothesis")
Recommended Workflow
- Start in the local Biomni repo and follow its environment setup rather than assuming the current
bio env is enough.
- Configure API keys through
.env or shell environment variables before trying agent mode.
- Use the
A1 examples in the README for full agent workflows, or inspect biomni/tool/ if you only need module-level capabilities.
- If you want a GUI, follow the documented Gradio path only after the core Python environment is healthy.
Guardrails
- The repo is present and
import biomni works when the repo path is added to sys.path, but deeper tool imports failed locally because langchain_core is missing.
- The README expects a dedicated
biomni_e1 conda environment plus additional package installation; do not assume the current workspace Python is sufficient.
- Agent mode requires API-key configuration. The old autogenerated skill text incorrectly implied zero-key library use was generally turnkey.
- The README says the Biomni datalake can auto-download on first agent creation and may require roughly
11GB.
- The Gradio interface is documented as requiring
gradio>=5,<6.
---
name: biomni
description: Use when working from the local Biomni repository to run agent-style biomedical tasks or inspect Biomni's biomedical tool modules and examples.
---
# biomni
Workspace-local entry point for the Biomni repository at `/home/vimalinx/Projects/bio_studio/repositories/active/Biomni`. The repo is present, the top-level Python package can be imported by adding the repo to `sys.path`, and the README documents both agent-style usage (`A1`) and a large biomedical tool tree under `biomni/tool/`.
## Quick Start
- **Repository:** `/home/vimalinx/Projects/bio_studio/repositories/active/Biomni`
- **Primary workflow:** activate `biomni_e1`, configure API keys, then use `from biomni.agent import A1`
- **Fast local check:** `python -c "import sys; sys.path.insert(0, '/home/vimalinx/Projects/bio_studio/repositories/active/Biomni'); import biomni; print(biomni.__file__)"`
## When To Use This Tool
- Running Biomni as a biomedical agent from the local repo
- Inspecting Biomni's tool modules for genomics, molecular biology, protocols, literature, and related domains
- Following the repo's own quick-start, profile-switching, or Gradio demo flows
- Auditing whether the current workspace is actually ready for Biomni execution
## Common Patterns
```bash
# Enter the local repository
cd /home/vimalinx/Projects/bio_studio/repositories/active/Biomni
```
```python
# Minimal repo-based import check
import sys
sys.path.insert(0, "/home/vimalinx/Projects/bio_studio/repositories/active/Biomni")
import biomni
print(biomni.__file__)
```
```python
# Agent-style usage from the README
from biomni.agent import A1
agent = A1(path="./data", llm="claude-sonnet-4-20250514")
agent.go("Perform scRNA-seq annotation at [PATH] and generate meaningful hypothesis")
```
## Recommended Workflow
1. Start in the local Biomni repo and follow its environment setup rather than assuming the current `bio` env is enough.
2. Configure API keys through `.env` or shell environment variables before trying agent mode.
3. Use the `A1` examples in the README for full agent workflows, or inspect `biomni/tool/` if you only need module-level capabilities.
4. If you want a GUI, follow the documented Gradio path only after the core Python environment is healthy.
## Guardrails
- The repo is present and `import biomni` works when the repo path is added to `sys.path`, but deeper tool imports failed locally because `langchain_core` is missing.
- The README expects a dedicated `biomni_e1` conda environment plus additional package installation; do not assume the current workspace Python is sufficient.
- Agent mode requires API-key configuration. The old autogenerated skill text incorrectly implied zero-key library use was generally turnkey.
- The README says the Biomni datalake can auto-download on first agent creation and may require roughly `11GB`.
- The Gradio interface is documented as requiring `gradio>=5,<6`.
