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authorNate Sesti <sestinj@gmail.com>2023-06-11 23:40:14 -0700
committerNate Sesti <sestinj@gmail.com>2023-06-11 23:40:14 -0700
commitc97aa52665bbe2152ec955b11c543fd17cce7273 (patch)
treeda03792d10243c3accb49b99014dc230a935289a /docs
parentdb3cf46933e180b1896b701185378e86b7bfca26 (diff)
parentc09e5e20986e6337a087dd18b30f08c4580cb389 (diff)
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Merge branch 'main' into dd-to-bq
Diffstat (limited to 'docs')
-rw-r--r--docs/docs/walkthroughs/create-a-recipe.md4
1 files changed, 1 insertions, 3 deletions
diff --git a/docs/docs/walkthroughs/create-a-recipe.md b/docs/docs/walkthroughs/create-a-recipe.md
index 60bfe9a8..3b80df8a 100644
--- a/docs/docs/walkthroughs/create-a-recipe.md
+++ b/docs/docs/walkthroughs/create-a-recipe.md
@@ -17,8 +17,6 @@ continue/continuedev/src/continuedev/recipes
## 1. Create a step
-
-
### a. Start by creating a subclass of Step
You should first consider what will be the parameters of your recipe. These are defined as attributes in the step, as with `input_file_path: str` below
@@ -33,7 +31,7 @@ If you'd like to override the default description of your steps, which is just t
- Return a static string
- Store state in a class attribute (prepend with a double underscore, which signifies (through Pydantic) that this is not a parameter for the Step, just internal state) during the run method, and then grab this in the describe method.
-- Use state in conjunction with the `models` parameter of the describe method to autogenerate a description with a language model. For example, if you'd used an attribute called `__code_written` to store a string representing some code that was written, you could implement describe as `return (await models.gpt35()).complete(f"{self.\_\_code_written}\n\nSummarize the changes made in the above code.")`.
+- Use state in conjunction with the `models` parameter of the describe method to autogenerate a description with a language model. For example, if you'd used an attribute called `__code_written` to store a string representing some code that was written, you could implement describe as `return models.gpt35.complete(f"{self.\_\_code_written}\n\nSummarize the changes made in the above code.")`.
## 2. Compose steps together into a complete recipe