last minor fixes

episodes/2-code-generation-optimization.md

@@ -79,8 +79,6 @@ In Codeium, code lenses appear right above your function and class definitions,
 
 - **Docstring Generation**: For generating documentation, clicking the `Docstring` label automatically creates a docstring above your function header (or under the function header in Python). This AI-generated documentation will describe what the function does, helping you maintain well-documented, readable code. In Python, for example, the docstring will be correctly placed directly beneath the function header.
 
-![](episodes/fig/command.webp){alt='Command'}
-
 ![](episodes/fig/docstring_python.mp4){alt='Docstring generation'}
 
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@@ -108,8 +106,6 @@ Here are a few things to remember when using Command function of Codeium:
 
 - For effective use, try to give clear and detailed prompts. While simple requests like “Fix this” or “Refactor” can work well due to context awareness, more specific instructions like “Write a function that takes two inputs of type `Diffable` and implements the Myers diff algorithm” can yield even better results.
 
-![](episodes/fig/codeium_chat_best_practices.png){alt='Best Practices for Command'}
-
 ## Chat
 
 The Codeium Chat feature offers a powerful way to interact with an AI assistant directly within your coding environment, providing instant, contextual feedback on the code. Unlike the Command function, Codeium Chat is designed for a more conversational and responsive interaction, making it easy to discuss complex coding questions and solutions. The base Chat model is available to all Codeium users and it is based on Meta’s [Llama 3.1 70B](https://ai.meta.com/blog/meta-llama-3-1/).
@@ -146,6 +142,8 @@ Good: Refactor @func:rawDataTransform by turning the while loop into a for loop
 
 ![](episodes/fig/best practices chat.png){alt='Best Practices for Chat'}
 
+Note that these best practices apply to both Chat and Command modes, as they help Codeium understand your needs more effectively.
+
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 ### 💡 Prompting Best Practices
@@ -581,11 +579,8 @@ plt.show()
 **Comparison:**
 
 - Combined the `pd.to_datetime` conversion and filtering steps into one.
-
 - Removed the unnecessary `filtered_df['Year']` column and used the `dt.year` accessor to extract the year from the `'Date'` column.
-
 - Simplified the plotting code by using the `plot` method of the Series object and removing the unnecessary `plt.figure` call.
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 - Removed the `label` parameter from the `plot` function, as it is not necessary when using the `plot` method of the Series object.
 
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