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0fb281f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | import sys, logging
sys.path.insert(0, ".")
logging.basicConfig(level=logging.WARNING)
from src.state import ResearchState, SessionContext
from src.agents.planner import planner_node
from src.memory import init_db
init_db()
print("=== Phase 4: Planner Agent ===\n")
# Test 1: Fresh query, no session context
state: ResearchState = {
"original_query": "What is the current state of speculative decoding in LLMs?",
"session_id": "test-session-001",
"session_context": None,
"sub_questions": [],
"retrieved_papers": [],
"citation_graph": {},
"web_results": [],
"critic_verdict": "",
"critic_notes": "",
"rewritten_questions": [],
"retry_count": 0,
"synthesized_position": "",
"claim_confidences": [],
"session_update": None,
"export_md": "",
"decay_config": "linear",
"calibration_bin": "",
"latency_ms": 0.0,
}
result = planner_node(state)
print("Query: What is the current state of speculative decoding in LLMs?")
print(f"Sub-questions generated: {len(result['sub_questions'])}")
for i, q in enumerate(result['sub_questions'], 1):
print(f" {i}. {q}")
# Test 2: Query with session context (should avoid repeating)
print("\n--- With session context ---")
ctx = SessionContext(
prior_queries=["What is the current state of speculative decoding in LLMs?"],
prior_positions=["Speculative decoding reduces latency by 2-3x..."],
flagged_contradictions=[]
)
state2 = {**state,
"original_query": "What are the limitations of speculative decoding?",
"session_context": ctx,
}
result2 = planner_node(state2)
print("Query: What are the limitations of speculative decoding?")
print(f"Sub-questions generated: {len(result2['sub_questions'])}")
for i, q in enumerate(result2['sub_questions'], 1):
print(f" {i}. {q}")
print("\n✅ Phase 4 complete") |