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docs/DSPy/01_module___program.md

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+title: "Module & Program"
+parent: "DSPy"
+nav_order: 1
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 # Chapter 1: Modules and Programs: Building Blocks of DSPy
 
 Welcome to the first chapter of our journey into DSPy! We're excited to have you here.

docs/DSPy/02_signature.md

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+layout: default
+title: "Signature"
+parent: "DSPy"
+nav_order: 2
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 # Chapter 2: Signatures - Defining the Task
 
 In [Chapter 1: Modules and Programs](01_module___program.md), we learned that `Module`s are like Lego bricks that perform specific tasks, often using Language Models ([LM](05_lm__language_model_client_.md)). We saw how `Program`s combine these modules.

docs/DSPy/03_example.md

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+layout: default
+title: "Example"
+parent: "DSPy"
+nav_order: 3
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 # Chapter 3: Example - Your Data Points
 
 In [Chapter 2: Signature](02_signature.md), we learned how to define the *task* for a DSPy module using `Signatures` – specifying the inputs, outputs, and instructions. It's like writing a recipe card.

docs/DSPy/04_predict.md

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+layout: default
+title: "Predict"
+parent: "DSPy"
+nav_order: 4
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 # Chapter 4: Predict - The Basic LM Caller
 
 In [Chapter 3: Example](03_example.md), we learned how to create `dspy.Example` objects to represent our data points – like flashcards holding an input and its corresponding desired output. We also saw in [Chapter 2: Signature](02_signature.md) how to define the *task* itself using `dspy.Signature`.

docs/DSPy/05_lm__language_model_client_.md

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+layout: default
+title: "LM (Language Model Client)"
+parent: "DSPy"
+nav_order: 5
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 # Chapter 5: LM (Language Model Client) - The Engine Room
 
 In [Chapter 4: Predict](04_predict.md), we saw how `dspy.Predict` takes a [Signature](02_signature.md) and input data to magically generate an output. We used our `translator` example:

docs/DSPy/06_rm__retrieval_model_client_.md

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+layout: default
+title: "RM (Retrieval Model Client)"
+parent: "DSPy"
+nav_order: 6
+---
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 # Chapter 6: RM (Retrieval Model Client) - Your Program's Librarian
 
 In [Chapter 5: LM (Language Model Client)](05_lm__language_model_client_.md), we learned how to connect our DSPy programs to the powerful "brain" of a Language Model (LM) using the LM Client. The LM is great at generating creative text, answering questions based on its vast training data, and reasoning.

docs/DSPy/07_evaluate.md

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+title: "Evaluate"
+parent: "DSPy"
+nav_order: 7
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 # Chapter 7: Evaluate - Grading Your Program
 
 In the previous chapter, [Chapter 6: RM (Retrieval Model Client)](06_rm__retrieval_model_client_.md), we learned how to connect our DSPy program to external knowledge sources using Retrieval Models (RMs). We saw how combining RMs with Language Models (LMs) allows us to build sophisticated programs like Retrieval-Augmented Generation (RAG) systems.

docs/DSPy/08_teleprompter___optimizer.md

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+layout: default
+title: "Teleprompter & Optimizer"
+parent: "DSPy"
+nav_order: 8
+---
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 # Chapter 8: Teleprompter / Optimizer - Your Program's Coach
 
 Welcome to Chapter 8! In [Chapter 7: Evaluate](07_evaluate.md), we learned how to grade our DSPy programs using metrics and datasets to see how well they perform. That's great for knowing our score, but what if the score isn't high enough?

docs/DSPy/09_adapter.md

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+layout: default
+title: "Adapter"
+parent: "DSPy"
+nav_order: 9
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 # Chapter 9: Adapter - The Universal Translator
 
 Welcome to Chapter 9! In [Chapter 8: Teleprompter / Optimizer](08_teleprompter___optimizer.md), we saw how DSPy can automatically optimize our programs by finding better prompts or few-shot examples. We ended up with a `compiled_program` that should perform better.

docs/DSPy/10_settings.md

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+layout: default
+title: "Settings"
+parent: "DSPy"
+nav_order: 10
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 # Chapter 10: Settings - Your Program's Control Panel
 
 Welcome to the final chapter of our introductory DSPy tutorial! In [Chapter 9: Adapter](09_adapter.md), we saw how Adapters act as translators, allowing our DSPy programs to communicate seamlessly with different types of Language Models (LMs).