# Full reference trajectory configuration - RecruitmentAssistant-H_A2A
#
# Version: ported from RecruitmentAssistant-A2A and adapted to the A2A_mix hybrid architecture
# Principle: keep business logic unchanged while adapting to the hybrid framework hierarchy
# (LangGraph + AutoGen + CrewAI).
#
# A2A_mix hybrid architecture notes:
# - Stage 1 (Job Analysis): LangGraph
#   * Use [Chain] LangGraph rather than CrewAI's Crew***.kickoff
#   * The AGENT name is simplified to "agent" rather than the full role name
#   * Tool calls appear under the [Chain] tools node and may run in batched mode
#   * LangGraph-specific Chain nodes: _should_continue and format_output
#
# - Stage 2 (Candidate Evaluation): CrewAI
#   * Keep the standard [Chain] Crew***.kickoff structure
#   * Use the full agent role name: "Senior Candidate Evaluator._execute_core"
#   * Tool calls are directly under AGENT (no intermediate Chain)
#
# - Stage 3 (Interview Communication): AutoGen
#   * AGENT pattern: create_agent + invoke_agent
#   * Ignore create_agent (excluded from evaluation)
#   * Focus on invoke_agent execution
#   * Tool call prefix: "execute_tool"
#
# Dynamic reference-trajectory design:
# 1. Choose 3x/4x variants based on the number of unified_web_search calls (consistent with A2A)
# 2. Dynamic matching for LangGraph tools batching:
#    - 3 searches: 1+1+1, 1+2, 2+1, or 3
#    - 4 searches: 1+1+1+1, 2+1+1, 1+2+1, 1+1+2, 3+1, 1+3, or 4
# 3. Dynamic matching for AutoGen Interview LLM/Tool patterns:
#    Rule: must start and end with LLM; between adjacent tools, there can be 0 or 1 LLM
#    - With 2 tools, possible patterns:
#      * LLM → Tool1 → Tool2 → LLM (0 LLM between tools)
#      * LLM → Tool1 → LLM → Tool2 → LLM (1 LLM between tools)
#    - Enumeration: for each adjacent tool pair, independently choose inserting 0 or 1 LLM
#      * 2 tools have 1 gap → 2^1 = 2 patterns
#      * 3 tools have 2 gaps → 2^2 = 4 patterns
# 4. Tool-order permutation optimization for Candidate Evaluation / Interview Communication:
#    - candidate_profile_analyzer ↔ candidate_evaluator_pro (2! = 2)
#    - comprehensive_interview_material_generator ↔ email_template_generator (2! = 2)
#    - Total permutations: 2 × 2 = 4
# During evaluation, all combinations (LangGraph × AutoGen LLM × tool permutations) are enumerated,
# and the variant with the highest score among exact_match / in_order_match / any_order_match is used.

# Project name
project_name: "RecruitmentAssistant-H_A2A"

# Extract types configuration
extract_types:
  - "SPAN" # multi-level SPAN structure
  - "Chain" # Chain nodes for LangGraph / CrewAI
  - "AGENT" # Agent nodes across frameworks (AutoGen extracts invoke_agent only)
  - "LLM" # LLM calls
  - "Tool" # Tool calls

# ============================================================================
# Reference Trajectory (Ground Truth) - A2A_mix Hybrid Architecture
# ============================================================================
#
# Graphical structure (ideal execution path, 3x version example):
# Graphical structure (ideal execution path, 3x version example):
#
# [SPAN] recruitment_orchestrator
# └─ [SPAN] crew_execution
#    ├─ [SPAN] analyze_job (LangGraph)
#    │  └─ [SPAN] a2a_call_job_analysis
#    │     └─ [SPAN] job_analysis_server_execution
#    │        └─ [Chain] LangGraph
#    │           ├─ [AGENT] agent
#    │           │  ├─ [LLM] *
#    │           │  └─ [Chain] _should_continue
#    │           ├─ [Chain] tools (batched execution with 3 searches; possible groupings: 1+1+1, 1+2, 2+1, 3)
#    │           │  ├─ [Tool] unified_web_search (1st)
#    │           │  ├─ [Tool] unified_web_search (2nd)
#    │           │  └─ [Tool] unified_web_search (3rd)
#    │           ├─ [AGENT] agent
#    │           │  ├─ [LLM] *
#    │           │  └─ [Chain] _should_continue
#    │           └─ [Chain] format_output
#    ├─ [SPAN] evaluate_candidates (CrewAI)
#    │  └─ [SPAN] a2a_call_candidate_evaluation
#    │     └─ [SPAN] candidate_evaluation_server_execution
#    │        └─ [Chain] Crew***.kickoff
#    │           └─ [AGENT] Senior Candidate Evaluator
#    │              ├─ [LLM] *
#    │              ├─ [Tool] candidate_profile_analyzer
#    │              ├─ [LLM] *
#    │              ├─ [Tool] candidate_evaluator_pro
#    │              └─ [LLM] *
#    └─ [SPAN] prepare_interviews (AutoGen)
#       └─ [SPAN] a2a_call_interview_communication
#          └─ [SPAN] interview_communication_server_execution
#             └─ [AGENT] invoke_agent interview_coordinator
#                ├─ [LLM] *
#                ├─ [Tool] execute_tool comprehensive_interview_material_generator
#                ├─ [Tool] execute_tool email_template_generator
#                └─ [LLM] *
#
# Notes:
# - Under LangGraph's [Chain] tools node, there may be multiple batched calls.
#   For example, 4 searches may be split into two batches: 2 + 2.
#   The evaluation script dynamically generates all possible grouping variants.
# - AutoGen's create_agent nodes are excluded from the reference trajectory.
# ============================================================================

# Default reference trajectory (compatibility; kept as the 3x version)
reference_trajectory:
  # ===== Top-level SPAN =====
  - "SPAN: recruitment_orchestrator"

  # ===== Second-level SPAN (includes 3 stages) =====
  - "SPAN: crew_execution"

  # ===== Stage 1: Job Analysis (LangGraph, 3 searches) =====
  - "SPAN: analyze_job"
  - "SPAN: a2a_call_job_analysis"
  - "SPAN: job_analysis_server_execution"
  - "Chain: LangGraph"
  - "AGENT: agent"
  - "LLM: *"
  - "Chain: _should_continue"
  - "Chain: tools"
  - "Tool: unified_web_search"
  - "Tool: unified_web_search"
  - "Tool: unified_web_search"
  - "AGENT: agent"
  - "LLM: *"
  - "Chain: _should_continue"
  - "Chain: format_output"

  # ===== Stage 2: Candidate Evaluation (CrewAI) =====
  - "SPAN: evaluate_candidates"
  - "SPAN: a2a_call_candidate_evaluation"
  - "SPAN: candidate_evaluation_server_execution"
  - "Chain: Crew***.kickoff"
  - "AGENT: Senior Candidate Evaluator"
  - "LLM: *"
  - "Tool: candidate_profile_analyzer"
  - "LLM: *"
  - "Tool: candidate_evaluator_pro"
  - "LLM: *"

  # ===== Stage 3: Interview Communication (AutoGen) =====
  - "SPAN: prepare_interviews"
  - "SPAN: a2a_call_interview_communication"
  - "SPAN: interview_communication_server_execution"
  - "AGENT: invoke_agent interview_coordinator"
  - "LLM: *"
  - "Tool: execute_tool comprehensive_interview_material_generator"
  - "Tool: execute_tool email_template_generator"
  - "LLM: *"

# ============================================================================
# Dynamic reference trajectory - Version 1: 3 unified_web_search calls
# ============================================================================
# This version serves as the base template for LangGraph tools batching.
# During evaluation, variants are generated dynamically based on the sample's tools grouping pattern.
reference_trajectory_3x:
  # ===== Top-level SPAN =====
  - "SPAN: recruitment_orchestrator"

  # ===== Second-level SPAN (includes 3 stages) =====
  - "SPAN: crew_execution"

  # ===== Stage 1: Job Analysis (LangGraph, 3-search base template) =====
  - "SPAN: analyze_job"
  - "SPAN: a2a_call_job_analysis"
  - "SPAN: job_analysis_server_execution"
  - "Chain: LangGraph"
  # First pass: agent decision
  - "AGENT: agent"
  - "LLM: *"
  - "Chain: _should_continue"
  # Tool groups (3 calls; may be split into 1-3 Chain: tools blocks)
  - "Chain: tools"
  - "Tool: unified_web_search"
  - "Tool: unified_web_search"
  - "Tool: unified_web_search"
  # Second pass: agent summary
  - "AGENT: agent"
  - "LLM: *"
  - "Chain: _should_continue"
  - "Chain: format_output"

  # ===== Stage 2: Candidate Evaluation (CrewAI) =====
  - "SPAN: evaluate_candidates"
  - "SPAN: a2a_call_candidate_evaluation"
  - "SPAN: candidate_evaluation_server_execution"
  - "Chain: Crew***.kickoff"
  - "AGENT: Senior Candidate Evaluator"
  - "LLM: *"
  - "Tool: candidate_profile_analyzer"
  - "LLM: *"
  - "Tool: candidate_evaluator_pro"
  - "LLM: *"

  # ===== Stage 3: Interview Communication (AutoGen) =====
  - "SPAN: prepare_interviews"
  - "SPAN: a2a_call_interview_communication"
  - "SPAN: interview_communication_server_execution"
  - "AGENT: invoke_agent interview_coordinator"
  - "LLM: *"
  - "Tool: execute_tool comprehensive_interview_material_generator"
  - "Tool: execute_tool email_template_generator"
  - "LLM: *"

# ============================================================================
# Dynamic reference trajectory - Version 2: 4 unified_web_search calls
# ============================================================================
reference_trajectory_4x:
  # ===== Top-level SPAN =====
  - "SPAN: recruitment_orchestrator"

  # ===== Second-level SPAN (includes 3 stages) =====
  - "SPAN: crew_execution"

  # ===== Stage 1: Job Analysis (LangGraph, 4-search base template) =====
  - "SPAN: analyze_job"
  - "SPAN: a2a_call_job_analysis"
  - "SPAN: job_analysis_server_execution"
  - "Chain: LangGraph"
  # First pass: agent decision
  - "AGENT: agent"
  - "LLM: *"
  - "Chain: _should_continue"
  # Tool groups (4 calls; may be split into 1-4 Chain: tools blocks)
  - "Chain: tools"
  - "Tool: unified_web_search"
  - "Tool: unified_web_search"
  - "Tool: unified_web_search"
  - "Tool: unified_web_search"
  # Second pass: agent summary
  - "AGENT: agent"
  - "LLM: *"
  - "Chain: _should_continue"
  - "Chain: format_output"

  # ===== Stage 2: Candidate Evaluation (CrewAI) =====
  - "SPAN: evaluate_candidates"
  - "SPAN: a2a_call_candidate_evaluation"
  - "SPAN: candidate_evaluation_server_execution"
  - "Chain: Crew***.kickoff"
  - "AGENT: Senior Candidate Evaluator"
  - "LLM: *"
  - "Tool: candidate_profile_analyzer"
  - "LLM: *"
  - "Tool: candidate_evaluator_pro"
  - "LLM: *"

  # ===== Stage 3: Interview Communication (AutoGen) =====
  - "SPAN: prepare_interviews"
  - "SPAN: a2a_call_interview_communication"
  - "SPAN: interview_communication_server_execution"
  - "AGENT: invoke_agent interview_coordinator"
  - "LLM: *"
  - "Tool: execute_tool comprehensive_interview_material_generator"
  - "Tool: execute_tool email_template_generator"
  - "LLM: *"

# Target tool list (for the single-tool use metric)
target_tools:
  - "Tool: unified_web_search"
  - "Tool: candidate_profile_analyzer"
  - "Tool: candidate_evaluator_pro"
  - "Tool: execute_tool comprehensive_interview_material_generator"
  - "Tool: execute_tool email_template_generator"

# Model list to evaluate
models:
  - "GPT-5"
  - "GPT-4o-mini"
  - "DeepSeek-V3-1"
  - "DeepSeek-R1"
  - "Gemini-2.5-flash"
  - "Gemini-2.5-flash-nothinking"
  - "Qwen3-235b"

# Permutable tool groups (for dynamic tool-order optimization)
permutable_tool_groups:
  # Candidate Evaluation stage tools can be in any order
  candidate_evaluation_tools:
    - "Tool: candidate_profile_analyzer"
    - "Tool: candidate_evaluator_pro"

  # Interview Communication stage tools can be in any order
  interview_communication_tools:
    - "Tool: execute_tool comprehensive_interview_material_generator"
    - "Tool: execute_tool email_template_generator"
# ============================================================================
# Usage notes - A2A_mix hybrid architecture version
# ============================================================================
#
# 1. Hybrid framework notes:
#    - Stage 1 (Job Analysis): LangGraph
#      * Chain name: LangGraph (not Crew***.kickoff)
#      * Simplified agent name: agent (not the full role name)
#      * Batched tool execution: [Chain] tools may contain multiple Tool nodes
#      * Special chain nodes: _should_continue and format_output
#
#    - Stage 2 (Candidate Evaluation): CrewAI
#      * Standard CrewAI structure: Crew***.kickoff → AGENT → LLM/Tool
#      * Full agent name: Senior Candidate Evaluator
#
#    - Stage 3 (Interview Communication): AutoGen
#      * Ignore create_agent (excluded from evaluation)
#      * Focus on invoke_agent interview_coordinator
#      * Tool prefix: execute_tool

# 2. LangGraph tools batching dynamic mode:
#    The evaluation script detects the tools grouping pattern in the sample and
#    dynamically generates corresponding reference variants for matching.
#
#    Possible groupings for 3 searches:
#    - [1,1,1]: 3 Chain: tools blocks, each with 1 Tool
#    - [1,2]:   2 blocks: first has 1 Tool, second has 2 Tools
#    - [2,1]:   2 blocks: first has 2 Tools, second has 1 Tool
#    - [3]:     1 block with 3 Tools
#
#    Possible groupings for 4 searches:
#    - [1,1,1,1]: 4 blocks, each with 1 Tool
#    - [2,1,1]:   3 blocks with 2,1,1 Tools
#    - [1,2,1]:   3 blocks with 1,2,1 Tools
#    - [1,1,2]:   3 blocks with 1,1,2 Tools
#    - [3,1]:     2 blocks with 3,1 Tools
#    - [1,3]:     2 blocks with 1,3 Tools
#    - [4]:       1 block with 4 Tools

# 3. AutoGen Interview LLM/Tool dynamic mode:
#    The evaluation script detects the LLM/Tool call pattern in the AutoGen part and
#    dynamically generates corresponding reference variants for matching.
#
#    Supported patterns:
#    - Compact: LLM → Tool1 → Tool2 → LLM (no LLM between tools)
#    - Interleaved: LLM → Tool1 → LLM → Tool2 → LLM (insert one LLM between tools)
#
#    Validation rules:
#    - Must start and end with LLM
#    - Must include the 2 target tools in the middle (fixed order)
#    - At most one LLM between tools

# 4. Dynamic reference selection strategy (enhanced):
#    For each sample:
#    a) Choose the 3x/4x base template by unified_web_search total count
#    b) Detect the LangGraph tools actual grouping pattern
#    c) Detect the AutoGen Interview actual LLM/Tool pattern
#    d) Enumerate all combinations (LangGraph pattern × AutoGen pattern)
#       - Example: 3 searches have 4 LangGraph patterns and 2 AutoGen patterns
#       - Total: 4 × 2 = 8 reference variants
#    e) Compute exact_match, in_order_match, and any_order_match for each variant
#    f) Select the variant with the best score as the final reference for the sample

# 5. Metric definitions (consistent with A2A):
#    - Exact Match: prediction equals reference
#    - In-order Match: reference is a subsequence of prediction
#    - Any-order Match: contains all required steps (order ignored)
#    - Precision: fraction of correct steps in prediction
#    - Recall: fraction of reference steps covered
#    - Single-tool Use: average usage rate of target tools
#    - unique_path_ratio: path diversity
#    - path_entropy: path entropy

# 6. Command:
#    cd /Users/wzr/TOSEM-2025/RESULTS/RQ-Failure_Breakdown/RecruitmentAssistant-H_A2A
#    python3 evaluate_trajectory.py --config reference_trajectory.yaml

# 7. Key differences vs the A2A version:
#    - LangGraph-specific Chain node structure
#    - Simplified agent name (LangGraph uses "agent")
#    - AutoGen invoke_agent pattern
#    - Dynamic handling of LangGraph tools batching
#    - Dynamic handling of AutoGen LLM/Tool patterns (new)
#    - AutoGen tool prefix: execute_tool (instead of CrewAI's ._use)
#    - Dual dynamic matching: supports LangGraph and AutoGen pattern combinations