adaptyv
🤖 AI Summary
This agent skill lets developers submit protein sequences via API to Adaptyv Bio’s automated cloud lab, which runs binding, thermostability, expression, and fluorescence assays and returns experimental results in ~21 days.
How to Install
Claude Code:
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git && cp scientific-agent-skills/skills/adaptyv ~/.claude/skills/adaptyv -r# Adaptyv Bio Foundry API
Adaptyv Bio is a cloud lab that turns protein sequences into experimental data. Users submit amino acid sequences via API or UI; Adaptyv's automated lab runs assays (binding, thermostability, expression, fluorescence) and delivers results in ~21 days.
**Official docs:** [docs.adaptyvbio.com/api-reference](https://docs.adaptyvbio.com/api-reference) · [llms.txt index](https://docs.adaptyvbio.com/llms.txt) · [OpenAPI spec](https://foundry-api-public.adaptyvbio.com/api/v1/openapi.json)
## Quick Start
**Base URL:** `https://foundry-api-public.adaptyvbio.com/api/v1`
**Authentication:** Bearer token in the `Authorization` header. Tokens are obtained from [foundry.adaptyvbio.com](https://foundry.adaptyvbio.com/) sidebar.
When writing code, always read the API key from the environment variable `ADAPTYV_API_KEY` or from a `.env` file — never hardcode tokens. Check for a `.env` file in the project root first; if one exists, use a library like `python-dotenv` to load it.
The [official API docs](https://docs.adaptyvbio.com/api-reference/api-introduction) use `FOUNDRY_API_TOKEN` in curl examples; that is the same bearer token — prefer `ADAPTYV_API_KEY` in Python and new shell scripts for consistency with the SDK.
```bash
export ADAPTYV_API_KEY="abs0_..."
curl https://foundry-api-public.adaptyvbio.com/api/v1/targets?limit=3 \
-H "Authorization: Bearer $ADAPTYV_API_KEY"
```
Every request except `GET /openapi.json` requires authentication. Store tokens in environment variables or `.env` files — never commit them to source control.
## Python SDK
**Version note:** `adaptyv-sdk` **0.1.0** (beta) is not yet on PyPI — install from GitHub:
```bash
uv pip install "git+https://github.com/adaptyvbio/adaptyv-sdk.git"
```
In a project with `pyproject.toml`:
```bash
uv add "adaptyv-sdk @ git+https://github.com/adaptyvbio/adaptyv-sdk.git"
```
**Environment variables** (set in shell or `.env` file):
```bash
ADAPTYV_API_KEY=your_api_key
ADAPTYV_API_URL=https://foundry-api-public.adaptyvbio.com/api/v1
ADAPTYV_ORGANIZATION_ID=your_org_id # optional
```
The `@lab.experiment` decorator and `FoundryClient` both read `ADAPTYV_API_KEY` and `ADAPTYV_API_URL` from the environment when not passed explicitly.
### Decorator Pattern
```python
from adaptyv import lab
@lab.experiment(target="PD-L1", experiment_type="screening", method="bli")
def design_binders():
return {"design_a": "MVKVGVNG...", "design_b": "MKVLVAG..."}
result = design_binders()
print(f"Experiment: {result.experiment_url}")
```
### Client Pattern
```python
import os
from adaptyv import FoundryClient
client = FoundryClient(
api_key=os.environ["ADAPTYV_API_KEY"],
base_url=os.environ.get(
"ADAPTYV_API_URL",
"https://foundry-api-public.adaptyvbio.com/api/v1",
),
)
# Browse targets
targets = client.targets.list(search="EGFR", selfservice_only=True)
# Estimate cost
estimate = client.experiments.cost_estimate({
"experiment_spec": {
Details
| Category | Coding → generation |
| Source | K-Dense-AI/scientific-agent-skills |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 29.2K |
| Est. per Skill | N/A (shared across 116 skills from this repo) |
| Difficulty | Intermediate |
| Risk Level | N/A |
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