# Complete Reference Trajectory Configuration - SQLAssistant-H_A2A Project
#
# This configuration is ported from the SQLAssistant-A2A version, keeping the core consistent:
# - Still evaluates the same business stages, LLM calls, and database-related tools
# - Still uses the same 6 trajectory metrics + path diversity metrics
#
# Only adapted for A2A_mix trajectory hierarchy and framework differences:
# - Top-level SPAN: sql_assistant_workflow_a2a
# - Second-level SPAN: a2a_execution
# - Stage 1: generate_sql still executed by CrewAI (two Agents, same as A2A)
# - Stage 2: check_compliance changed to LangGraph orchestration graph (agent + tools + format_output)
# - Stage 3: interpret_results changed to AutoGen architecture (result_interpreter_autogen_execution + invoke_agent result_interpreter)
#
# Refer to actual execution samples in RESULTS/<model>/SQLAssistant-H_A2A/test_results/run_*/execution_path.md.

# Project name (determines trajectory collection from RESULTS/<model>/<project_name>/test_results)
project_name: "SQLAssistant-H_A2A"

# Trajectory extraction type configuration: consistent with A2A / MCP versions
extract_types:
  - "SPAN" # Multi-layer SPAN structure (including *_a2a, a2a_execution, generate_sql, etc.)
  - "Chain" # Chain nodes in CrewAI / LangGraph / AutoGen (e.g., Crew***.kickoff, LangGraph, RunnableSequence)
  - "Agent" # CrewAI Agents, AutoGen create/invoke Agents, LangGraph "agent" nodes
  - "LLM" # LLM calls
  - "Tool" # Tool calls (database schema / validation / query, etc.)

# A2A_mix version also has no chapter-style repeatable patterns
repeatable_patterns: []

# ==========================================================================
# Reference Trajectory (Ground Truth) - A2A_mix Architecture, based on code design + trajectory samples
# ==========================================================================
#
# Ideal execution path (no retries, no errors) hierarchical structure (abstracted from A2A_mix execution_path):
#
# [SPAN] sql_assistant_workflow_a2a
# └─ [SPAN] a2a_execution
#    ├─ [SPAN] generate_sql
#    │  └─ [SPAN] a2a_call_sql_generation
#    │     └─ [SPAN] sql_generation_server_execution
#    │        └─ [Chain] Crew***.kickoff
#    │           ├─ [AGENT] Expert SQL Query Generator
#    │           │  ├─ [LLM] *
#    │           │  ├─ [Tool] get_database_schema
#    │           │  └─ [LLM] *
#    │           └─ [AGENT] Senior SQL Code Reviewer
#    │              ├─ [LLM] *
#    │              ├─ [Tool] validate_sql_syntax
#    │              ├─ [LLM] *
#    │              ├─ [Tool] get_database_schema
#    │              └─ [LLM] *
#    ├─ [SPAN] check_compliance
#    │  └─ [SPAN] a2a_call_compliance_checker
#    │     └─ [SPAN] compliance_checker_server_execution
#    │        └─ [Chain] LangGraph
#    │           ├─ [AGENT] agent
#    │           │  ├─ [LLM] *
#    │           │  └─ [Chain] _should_continue
#    │           ├─ [Chain] tools
#    │           │  └─ [Tool] get_database_schema
#    │           ├─ [AGENT] agent
#    │           │  ├─ [LLM] *
#    │           │  └─ [Chain] _should_continue
#    │           └─ [Chain] format_output
#    └─ [SPAN] interpret_results
#       └─ [SPAN] a2a_call_result_interpreter
#          └─ [SPAN] result_interpreter_autogen_execution
#             └─ [AGENT] invoke_agent result_interpreter
#                ├─ [LLM] *
#                ├─ [Tool] run_sql_query
#                └─ [LLM] *
#
# Notes:
# - Business stages (generate_sql → check_compliance → interpret_results), key Agent roles, and core tools
#   remain consistent with SQLAssistant-A2A version, just with framework changed to CrewAI + LangGraph + AutoGen combination.
# - In LangGraph stage, ideal path uses get_database_schema as schema tool;
#   check_table_exists and other existence check tools are considered optional additional calls.
# - In AutoGen stage, result interpretation is completed through invoke_agent result_interpreter,
#   actual SQL execution is still handled by run_sql_query tool (still considered a core tool to cover in tool list).
# - Business retries (business_retry N) and orchestrator-level retries (retry N) are not written into reference trajectory,
#   evaluation allows extra steps and retries to exist according to in_order / any_order metrics.

reference_trajectory:
  # ===== Top-level SPAN (A2A_mix top-level workflow) =====
  - "SPAN: sql_assistant_workflow_a2a"

  # ===== Second-level SPAN (A2A_mix execution wrapper layer) =====
  - "SPAN: a2a_execution"

  # ===== Stage 1: Generate SQL (SQLGenerationCrew, CrewAI) =====
  - "SPAN: generate_sql"
  - "SPAN: a2a_call_sql_generation"
  - "SPAN: sql_generation_server_execution"
  - "Chain: Crew***.kickoff"
  # Agent 1: SQL Generator (uses key schema exploration tools)
  - "Agent: Expert SQL Query Generator"
  - "LLM: *" # Determine overall generation strategy
  - "Tool: get_database_schema" # Read complete schema
  - "LLM: *" # Generate candidate SQL based on schema
  # Other exploration tools (list_tables / get_table_sample / get_column_stats) are considered optional

  # Agent 2: SQL Reviewer (syntax and structure checking)
  - "Agent: Senior SQL Code Reviewer"
  - "LLM: *" # Read and understand generated SQL
  - "Tool: validate_sql_syntax" # Required: syntax check
  - "LLM: *" # Analyze syntax check results
  - "Tool: get_database_schema" # Required: verify table/column existence against schema
  - "LLM: *" # Correct SQL based on schema check results

  # ===== Stage 2: Check Compliance (LangGraph) =====
  - "SPAN: check_compliance"
  - "SPAN: a2a_call_compliance_checker"
  - "SPAN: compliance_checker_server_execution"
  - "Chain: LangGraph" # Top-level chain of LangGraph orchestration graph
  - "Agent: agent" # Compliance "agent" node in LangGraph
  - "LLM: *" # Preliminary reading of SQL and identifying potential risks
  - "Chain: _should_continue" # LangGraph internal flow control node
  # LangGraph's tools subchain should use schema / table existence related tools at least once
  - "Chain: tools"
  - "Tool: get_database_schema" # Evaluate sensitivity combined with schema (consistent with Reviewer/Compliance semantics)
  # check_table_exists is an equivalent existence check tool, can appear simultaneously in actual trajectory
  - "LLM: *" # Update compliance judgment combined with tool results
  - "Agent: agent" # Merge context again, generate final verdict
  - "LLM: *" # Give PASS/FAIL verdict
  - "Chain: _should_continue" # LangGraph internal flow control node
  - "Chain: format_output"

  # ===== Stage 3: Interpret Results (AutoGen) =====
  # Note: Only enters this stage if compliance passes
  - "SPAN: interpret_results"
  - "SPAN: a2a_call_result_interpreter"
  - "SPAN: result_interpreter_autogen_execution"
  - "Agent: invoke_agent result_interpreter" # Call result interpretation Agent to complete reasoning
  - "LLM: *" # Understand business question and reviewed SQL
  - "Tool: run_sql_query" # Required: execute SQL to get real data
  - "LLM: *" # Generate business interpretation based on real results (count_rows is optional statistics tool)
  # Actual SQL execution should still be completed through run_sql_query tool, see target_tools configuration

# Target tool list (used by single_tool_use metric)
# Consistent with A2A / MCP versions, covers all core tools (including some optional tools)
target_tools:
  # SQL Generation stage - Generator
  - "Tool: get_database_schema"
  - "Tool: get_table_sample"
  - "Tool: get_column_stats"
  - "Tool: list_tables"
  # SQL Generation stage - Reviewer
  - "Tool: validate_sql_syntax"
  - "Tool: check_table_exists"
  # Compliance stage (shares get_database_schema / check_table_exists, not repeated)
  # Result Interpretation stage
  - "Tool: run_sql_query"
  - "Tool: count_rows"

# List of models to evaluate (consistent with A2A / MCP versions, path only changed to SQLAssistant-H_A2A)
models:
  - "GPT-5"
  - "GPT-4o-mini"
  - "DeepSeek-V3-1"
  - "DeepSeek-R1"
  - "Gemini-2.5-flash"
  - "Gemini-2.5-flash-nothinking"
  - "Qwen3-235b"
# Usage instructions (simplified version):
# - Run path: Execute in RQ-Failure_Breakdown/SQLAssistant-H_A2A directory:
#     python3 evaluate_trajectory-Filter_Tools.py --config reference_trajectory.yaml
# - evaluate_trajectory-Filter_Tools.py will automatically read
#   RESULTS/<model>/SQLAssistant-H_A2A/test_results based on project_name for execution_path.md.