diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -13,6 +13,10 @@ This Blueprint demonstrates how to use open-source models and a simple LLM workf
It is designed to showcase a simpler alternative to more complex and/or resource demanding alternatives, such as RAG systems that rely on vectorDBs and/or long-context models with large token windows.
+
+
+📘 To explore this project further and discover other Blueprints, visit the [**Blueprints Hub**](https://developer-hub.mozilla.ai/blueprints/query-structured-documents-using-a-lightweight-llm-workflow).
+
### 👉 📖 For more detailed guidance on using this project, please visit our [Docs here](https://mozilla-ai.github.io/structured-qa/).
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diff --git a/docs/index.md b/docs/index.md
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--- a/docs/index.md
+++ b/docs/index.md
@@ -1,7 +1,7 @@
# **Structured-QA Blueprint**
-

+
Blueprints empower developers to easily integrate AI capabilities into their projects using open-source models and tools.
diff --git a/docs/step-by-step-guide.md b/docs/step-by-step-guide.md
index 6f7d06f..3e28975 100644
--- a/docs/step-by-step-guide.md
+++ b/docs/step-by-step-guide.md
@@ -9,17 +9,14 @@ This system has the following core stages:
Prepare the input document by extracting the different sections that compose the structure of the document.
Split the sections and save them to separate files.
-🔎 **2. Find Relevant Section**
- Given a list of sections and the input question, use the LLM to identify the section that looks more relevant.
+🔎 **2. Find Relevant and Retrieve Section**
+ Given a list of sections and the input question, use the LLM to identify the section that looks more relevant. Load the individual section to be passed to the next step.
-📄 **3. Retrieve Section**
- Load the individual section to be passed to the next step.
-
-📗 **4. Answer Question**
+📗 **3. Answer Question**
Use the LLM to answer the question based on the information available in the retrieved section.
-In case the LLM can't find an answer to the question, the stages 2 to 4 run on a loop until the LLM finds the answer.
+In case the LLM can't find an answer to the question, the stages 2 to 3 run on a loop until the LLM finds the answer.
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