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4 changes: 4 additions & 0 deletions README.md
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Expand Up @@ -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.

<img src="./images/structured-qa-diagram.png" width="1200" alt="structure-qa Diagram" />

📘 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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2 changes: 1 addition & 1 deletion docs/index.md
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@@ -1,7 +1,7 @@
# **Structured-QA Blueprint**

<div style="text-align: center;">
<img src="images/document-to-podcast-diagram.png" alt="Project Logo" style="width: 100%; margin-bottom: 1px; margin-top: 1px;">
<img src="images/structured-qa-diagram.png" alt="Project Logo" style="width: 100%; margin-bottom: 1px; margin-top: 1px;">
</div>

Blueprints empower developers to easily integrate AI capabilities into their projects using open-source models and tools.
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11 changes: 4 additions & 7 deletions docs/step-by-step-guide.md
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Expand Up @@ -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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