multimodal-rag-guide/prompts/02-ingest.md

Prompt 2: Ingest Your Files

Copy this into Claude Code after the project is set up and your .env file has your API keys.

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Now build the ingestion pipeline. I need a script that:

1. Reads each PDF in example-data/ and extracts the text content.
   Split long documents into chunks of roughly 500 words each.
   Keep track of which file and which section each chunk came from.

2. Reads the image descriptions from example-data/descriptions.md.
   Use the "Good description" for each image (ignore the "Bad" ones).
   Each image description becomes one chunk, linked to its image file.

3. For each chunk, generate an embedding using Google Gemini
   Embedding 2 (model: gemini-embedding-exp-03-07 or the latest
   available). Use task_type "RETRIEVAL_DOCUMENT" for all chunks.

4. Store each embedding in Pinecone along with metadata:
   - source_file: the original filename
   - content_type: "pdf" or "image"
   - text: the actual text content of the chunk
   - chunk_index: which chunk number within the file

5. After ingestion, print a summary: how many chunks were created,
   how many embeddings stored, and any errors.

Run the ingestion script after building it. Show me the output.

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What Claude Code will do

1. Build a script that reads PDFs and extracts text
2. Parse the descriptions.md file for image descriptions
3. Send each chunk to Google Gemini for embedding
4. Store everything in Pinecone with metadata
5. Run the script and show results

What to expect

You should see output like:

Processing solar-system-overview.pdf... 3 chunks
Processing jupiter-fact-sheet.pdf... 4 chunks
Processing solar-system-moons.pdf... 3 chunks
Processing earthrise.jpg (from descriptions)... 1 chunk
Processing aldrin-moon.jpg (from descriptions)... 1 chunk
Processing jupiter-great-red-spot.jpg (from descriptions)... 1 chunk
Processing iss-over-earth.jpg (from descriptions)... 1 chunk

Total: 14 chunks ingested, 14 embeddings stored in Pinecone.

The exact numbers may vary depending on how Claude Code splits the PDFs.

If something goes wrong

• "API key invalid": check your .env file
• "Index not found": make sure your Pinecone index name matches
• "Rate limit": wait a minute and run the script again