# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

config:
  # Global configuration applied across all test cases unless overridden inside a specific test block.
  # This map directly extends the kwargs passed to the underlying cxas_scrapi.core.sessions.Sessions.run() method.
  modality: "TEXT" # Alternatively "AUDIO". Defaults to TEXT if omitted.

conversations:
  # ----------------------------------------------------------------------------
  # 1. Standard Event Trigger (e.g., testing implicit Welcome greetings)
  # ----------------------------------------------------------------------------
  - conversation: "Session Start Event Check"
    event: "session_start"
    expectations:
      - type: "contains"
        value: "Shopping Assistant"

  # ----------------------------------------------------------------------------
  # 2. Basic Text Input & Asserting Agent Transfers
  # ----------------------------------------------------------------------------
  - conversation: "Party Planner transfer"
    user: "Plan a party for my 4 year old"
    expectations:
      - type: "agent_transfer"
        value: "party_planner"

  # ----------------------------------------------------------------------------
  # 3. Validating Tool Calls, Inputs, and Outputs (with Context Variables)
  # ----------------------------------------------------------------------------
  - conversation: "Product search tool I/O"
    user: "cupcake decorations"
    variables:
      # Variables injected BEFORE the turn executes into the backend context
      first_turn: true 
    expectations:
      - type: "tool_called"
        value: "search_products"
      - type: "tool_input"
        # Tool inputs execute a boolean subset match. You only need to define the exact args you want verified.
        value:
          query: "cupcake decorations"
      - type: "tool_output"
        # Tool outputs execute a subset match against the returned JSON objects.
        # An empty dictionary {} validates that the key exists without restricting its value contents.
        value:
          search_products: {}

  # ----------------------------------------------------------------------------
  # 4. Strict Output Matching assuring No Backend Functions triggered
  # ----------------------------------------------------------------------------
  - conversation: "Direct Response Only"
    user: "Thank you!"
    expectations:
      - type: "no_tools_called"
        # Null value is sufficient here as the Type validates simply that the toolkit list is empty.
        value: null
      - type: "equals"
        # Checks for exact string equality (safely ignoring leading/trailing whitespaces automatically).
        value: "You're very welcome! Let me know if you need anything else."

  # ----------------------------------------------------------------------------
  # 5. Fetching Historic Context via Session ID String (With Turn Limits)
  # ----------------------------------------------------------------------------
  - conversation: "Dynamic Context Session Injection"
    user: "Does the policy cover that procedure?"
    # By providing a string session ID, TurnEvals invokes ConversationHistory to automatically 
    # fetch, format, and serialize the prior conversation trajectory.
    historical_contexts: "simulator-1d519e30-6521-4ca6-bc14-e1dd46d1d2c3"
    # We can configure Sessions.run via TurnEvals to only fetch a subset of the historical session's turns. 
    # (e.g., stopping the trace extraction after 5 turns to test the middle state of a conversation).
    # If turn_count is provided, historical_contexts must also be provided.
    turn_count: 5 
    expectations:
      - type: "contains"
        value: "Yes, that procedure is covered"

  # ----------------------------------------------------------------------------
  # 6. Hard-coding Static Dictionary Contexts manually
  # ----------------------------------------------------------------------------
  - conversation: "Static Dictionary Context Injection"
    user: "What did I ask about again?"
    # Alternatively, supply the exact conversational layout you specifically want applied instead of fetching it.
    historical_contexts:
      - user: "Hi, I need help finding my member ID."
      - agent: "I can help with that. What is your name and date of birth?"
        name: "Authentication Agent"
    expectations:
      - type: "contains"
        value: "member ID"