office-assistant-ask.yaml

name: office-assistant-ask
description: >
  Answer a question from the meeting-notes knowledge base. Full-text search the
  Postgres KB for the most relevant notes, then have an LLM synthesize a grounded
  answer that cites the meetings it used. Pair with
  office-assistant-ingest-meeting.yaml. Run it and read the answer from the CLI
  output (mantle run office-assistant-ask --values q.yaml --output json).

inputs:
  question:
    type: string
    description: The question to answer from company meeting notes

steps:
  # 1. Retrieve the top matching notes via weighted full-text ranking.
  #    websearch_to_tsquery parses natural-language queries (quotes, OR, -term).
  - name: search
    action: postgres/query
    credential: kb-db
    timeout: "15s"
    params:
      query: >
        SELECT title,
               to_char(meeting_date, 'YYYY-MM-DD') AS meeting_date,
               attendees,
               summary,
               action_items
        FROM meeting_notes
        WHERE search @@ websearch_to_tsquery('english', $1)
        ORDER BY ts_rank(search, websearch_to_tsquery('english', $1)) DESC
        LIMIT 5
      args:
        - "{{ inputs.question }}"

  # 2. Synthesize an answer grounded strictly in the retrieved notes.
  - name: answer
    action: ai/completion
    credential: openai
    depends_on:
      - search
    timeout: "60s"
    params:
      model: gpt-4o
      system_prompt: >
        You answer questions using ONLY the provided meeting notes. Cite the
        meeting titles you draw from. If the notes do not contain the answer,
        say so plainly rather than guessing.
      prompt: >
        Question: {{ inputs.question }}

        Meeting notes (JSON array, most relevant first):
        {{ jsonEncode(steps['search'].output.rows) }}