Hey ya’ll So i am web scraping using Jina AI (HTTP request node) and a information extractor node.
The Jina AI node is accurately scraping all the comments from the 4 chan thread. However, when I test the information extractor node (w/ a json schema to extract for post_number, comment, date_time) it only gives me about 28 posts in the output (the 4chan thread clearly has much more than 28 posts), can anyone help me figure why the information extractor is only getting partial of the output from the input data (only about 28 comments rather than all the comments in the data from Jina)
I am using Gemini 2.0 pro exp 02 05 (free) chat model w/ open router as my chat model
It appears you’re encountering an issue where the Information Extractor node in your n8n workflow processes only a subset of the data retrieved from a 4chan thread via the Jina AI node. Let’s explore potential reasons and solutions for this behavior.
1. Input Data Structure:
Batch Processing: The Information Extractor node may process data in batches. If the incoming data exceeds a certain size, it might only handle the first batch, leading to partial extraction.
Solution: Ensure that the data from the Jina AI node is split into manageable chunks before feeding it into the Information Extractor node. You can use the Split In Batches node to achieve this.
2. Node Configuration:
Schema Definition: Verify that the JSON schema provided to the Information Extractor node accurately reflects the structure of the data from the Jina AI node. Misalignments can cause the node to skip entries.
Solution: Double-check and adjust the schema to ensure compatibility with the incoming data structure.
3. Resource Limitations:
Memory Constraints: Processing large datasets can be resource-intensive. If n8n or the underlying system lacks sufficient memory, it might result in incomplete processing.
Solution: Monitor system resources during workflow execution. Consider increasing available memory or optimizing the workflow to handle large datasets more efficiently.
4. Error Handling:
Silent Failures: If the Information Extractor node encounters errors with specific data entries, it might stop processing without explicit error messages.
Solution: Implement error handling mechanisms, such as the Error Trigger node, to catch and log errors, facilitating troubleshooting.
5. Alternative Approaches:
Custom Extraction: If challenges persist, consider using a Code node to write custom JavaScript functions tailored to your data extraction needs, offering greater control over the process.
By systematically addressing these areas, you should be able to enhance the completeness of data extraction in your workflow.
Hey Miquel_Colomer I appreciate your insightful and thoughtful recommendations. I want to try and Split In Batches node but I cannot find it in n8n, all that comes out is this Loop Node (Split in Bathces)
