nl2sql

AnswerSynthesizerNode

Overview

• Summarizes aggregated results into a user‑facing response using an LLM.
• Exists to convert structured results into human‑readable output.
• Sits after EngineAggregatorNode at the end of the control graph.
• Class: AnswerSynthesizerNode
• Source: packages/nl2sql/src/nl2sql/pipeline/nodes/answer_synthesizer/node.py

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Responsibilities

• Serialize aggregated results for prompt input.
• Include unmapped sub‑queries in the response context.
• Invoke LLM with structured output schema.

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Position in Execution Graph

Upstream:

• EngineAggregatorNode

Downstream:

• Graph end.

Trigger conditions:

• Executed after aggregation completes.

flowchart LR
    Aggregator[EngineAggregatorNode] --> Synthesizer[AnswerSynthesizerNode] --> EndNode[PipelineEnd]

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Inputs

From GraphState:

• user_query (required)
• aggregator_response.terminal_results (required)
• decomposer_response.unmapped_subqueries (optional)

Validation performed:

• If no aggregated result is available, emits INVALID_STATE.

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Outputs

Mutations to GraphState:

• answer_synthesizer_response (AnswerSynthesizerResponse)
• reasoning summary
• errors on failure

Side effects:

• LLM invocation.

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Internal Flow (Step-by-Step)

1. Resolve aggregated result from aggregator_response.
2. If missing, emit INVALID_STATE error and stop.
3. Serialize results to JSON.
4. Serialize unmapped sub‑queries to JSON.
5. Invoke LLM chain with structured output.
6. Return AnswerSynthesizerResponse.
7. On exception, emit AGGREGATOR_FAILED.

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Contracts & Interfaces

Implements a LangGraph node callable:

def __call__(self, state: GraphState) -> Dict[str, Any]

Key contracts:

• AggregatedResponse
• AnswerSynthesizerResponse

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Determinism Guarantees

• Non‑deterministic unless LLM configured deterministically.

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Error Handling

Emits PipelineError with:

• INVALID_STATE (no aggregated result)
• AGGREGATOR_FAILED (LLM failure)

Logs failures via logger.error.

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Retry + Idempotency

• No internal retry logic.
• Idempotency depends on LLM determinism.

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Performance Characteristics

• LLM call dominates latency and cost.
• Serialization of aggregated results is in‑memory.

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Observability

• Logger: answer_synthesizer
• Adds reasoning summary to state.

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Configuration

• LLM configuration for agent name answer_synthesizer via llm.yaml.

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Extension Points

• Modify ANSWER_SYNTHESIZER_PROMPT.
• Replace node in build_graph() for custom synthesis.

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Known Limitations

• No deterministic summarization guarantees without LLM configuration.
• No fallback response when LLM fails.

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Related Code

• packages/nl2sql/src/nl2sql/pipeline/nodes/answer_synthesizer/node.py

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