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RAG & Knowledge Bases
Analyze Pitch Decks and Chat via OpenAI and Qdrant
When you run it, a pitch deck PDF is split into page images, OpenAI vision converts them to text stored in Qdrant, and a chatbot answers questions.
What it does
## 4. Convert PDF Pages to Markdown Using Vision Model Learn more about using the Basic LLM node Pitch decks are fundamentally extravagant sales documents and as such, are incredibly varied in how they are styled, structured and presented. Traditional OCR has often struggled with parsing these kinds of documents as layers and graphical elements and when extracting their contents typically yields poor results; either garbled or missing texts. Multimodal LLMs are a solution as they use AI vision to "read" the pitch deck and can reason about it's layout and intent. Images can be understood and described with context and charts and graphs can also be interpreted. In this demonstration, we'll ask our LLM to transcribe each page in the pitch deck into markdown ensuring it also describes any images or charts it sees.
The steps
- When clicking ‘Test workflow’
- Sort Pages
- Split PDF into Images
- Extract Zip File
- Images To List
- Resize Images For AI
- Combine All Pages
- Default Data Loader
- Recursive Character Text Splitter
- OpenAI Chat Model
- OpenAI Chat Model2
- Embeddings OpenAI
- Delete Existing Vectors
- Continue With Pages Only
39 steps in total.
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