Kellogg LLM Batch
User guide
Installation
Requirements
Clone and install
Contributor tools
Provider credentials
Next step
Basic workflow
1. Create a project
Optional: use the project builder
2. Validate locally
3. Prepare and inspect a pilot
4. Submit the pilot
5. Prepare the complete batch
6. Wait for and process the batch
7. Use the results
Project settings
Project identity
Input data
Task and response schema
Prompts and codebook
Providers and budget
openai_compatible
: self-hosted Ollama and vLLM servers
Evaluation and output
Grant-coding walkthrough
What the example does
1. Validate the project
2. Prepare a four-grant pilot
3. Inspect before submitting
4. Submit the pilot
5. Review the results
6. Continue to the complete batch
7. Run with Anthropic
8. Compare providers
Where to go next
Advanced workflows
Retry failed records and merge the results
Cancel and recover a run
Cancel and continue safely
Other recovery commands
Intentionally rerun or select specific records
Compare providers or repeated runs
Run against a local Ollama or vLLM server
Configure a project in depth
Input mappings
Prompts and context
Place individual columns in the prompt
Schema portability
Limits, models, and cost
Stage batch segments
Understand artifacts and provenance
Protect research data
Attach one PNG or PDF per prepared request
Use the checked-in helper scripts
CLI reference
Prepare options used most often
Command boundaries
Kellogg LLM Batch
Index
Index