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Llm Enrich
Enrich documents with LLM-generated fields using natural language prompts
Note: This playground provides simulated output to showcase functionality. No data is processed on our servers. Use this demo to explore the stage's configuration options before integrating it into your retriever pipeline.
Configuration
string | null
LLM provider: 'openai', 'google', or 'anthropic'. Auto-inferred from model_name.
string | null
Specific LLM model. Examples: gemini-3.1-flash-lite, gpt-4o-mini, claude-3-5-haiku-20241022.
string
Required
REQUIRED. Prompt template. Supports {{DOC.field}} and {{INPUT.field}} variables.
string
Required
REQUIRED. Dot-path where generated content is stored.
integer
Documents per LLM request batch.
object | null
JSON schema for structured LLM output.
number
Sampling temperature (0-1).
object | null
OPTIONAL. Conditional filter for selective enrichment (CRITICAL FOR COST SAVINGS).
Output
No output yet
Configure the stage parameters and click "Run Stage" to see the simulated output.