Bring the README back in step with the commands it gives
Four things had drifted. It told you to run `fluksio login` two lines above saying `serve` signs you in — one of the two had to go, and it is the login. It ran `fluksio sync` before `fluksio run`, which `run` now does itself. The pipeline snippet passed `prepare` and `evaluate` to `Flow` without importing them, so copying it got a NameError on the one example that matters. And the site link was relative, which resolves to nothing on the page this file exists to be — pypi.org. Added one sentence, on installing into the environment you already work in, because it is the reason a reader's own imports keep working and there is nowhere else on this page they would learn it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012ue1tkFWB1bcGy3aWhCKpU
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@@ -9,17 +9,14 @@ pip install fluksio
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fluksio serve
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fluksio serve
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```
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```
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Then login once (the token is stored on your device) with the credentials shown after the previous command
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and you're ready to go — `serve` signs you in itself and says where it put the
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token, so there is no login step. (`fluksio login` is for an engine somewhere
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else.)
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```sh
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Install it into the environment you already work in and your nodes run on that
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fluksio login --url http://127.0.0.1:8000
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one, so everything you had imported is still importable. Fluksio keeps a SQLite
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```
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database, a git repository of your flows and an artifact store in a `.fluksio`
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beside your code — one installation per project, found the way `.git` is.
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and you're ready to go!
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Fluksio keeps a SQLite database, a git repository of your flows and an artifact
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store in a `.fluksio` beside your code — one installation per project, found
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the way `.git` is. It prints an admin password once, and signs you in itself.
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## For data science
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## For data science
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@@ -47,6 +44,8 @@ def fit(dataset, lr, epochs=25):
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```python
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```python
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# myresearch/pipeline.py
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# myresearch/pipeline.py
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from fluksio import Flow, Port
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from fluksio import Flow, Port
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from myresearch.data import prepare
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from myresearch.evaluate import evaluate
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from myresearch.train import fit
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from myresearch.train import fit
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train = Flow("train", nodes=[prepare, fit, evaluate],
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train = Flow("train", nodes=[prepare, fit, evaluate],
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@@ -57,10 +56,12 @@ Fluksio will automatically infer the order of nodes based on the inputs and outp
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When everything is set, you can launch your first run as follows:
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When everything is set, you can launch your first run as follows:
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```sh
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```sh
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fluksio sync myresearch
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fluksio run train --lr 0.05 --wait
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fluksio run train --lr 0.05 --wait
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```
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```
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That syncs your code and then runs it, so after an edit the command is the same
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one again.
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Checkout our [documentation](https://docs.fluksio.com/getting-started/data-science/) for more infos.
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Checkout our [documentation](https://docs.fluksio.com/getting-started/data-science/) for more infos.
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## Some other features
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## Some other features
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@@ -75,7 +76,7 @@ Checkout our [documentation](https://docs.fluksio.com/getting-started/data-scien
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*out* over one websocket, so nothing there has to be reachable.
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*out* over one websocket, so nothing there has to be reachable.
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Fluksio can also be used for facility automation.
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Fluksio can also be used for facility automation.
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Visit us on [Fluksio.com](fluksio.com) or go straight to our [documentation](https://docs.fluksio.com).
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Visit us on [fluksio.com](https://fluksio.com) or go straight to our [documentation](https://docs.fluksio.com).
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## License
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## License
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