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adaptyv

★ 29K repogenerationN/AIntermediateClaude
🤖 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
SourceK-Dense-AI/scientific-agent-skills
SKILL.mdView on GitHub →
Repo Stars★ 29.2K
Est. per SkillN/A (shared across 116 skills from this repo)
DifficultyIntermediate
Risk LevelN/A

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