update_session

lai.update_session(
    task: Optional[str] = None,
    session_eval: Optional[float] = None,
    session_eval_reason: Optional[str] = None,
    is_successful: Optional[bool] = None,
    is_successful_reason: Optional[str] = None
) -> None

import lucidicai as lai

# Start with general task
lai.init(
    session_name="Customer Support",
    task="Handle customer inquiry"
)

# After understanding the request
lai.update_session(
    task="Resolve billing dispute for premium account"
)

# Process the request...

# After resolution
lai.update_session(
    task="Resolved billing dispute - refunded $49.99 for duplicate charge",
    is_successful=True,
    is_successful_reason="Customer satisfied with resolution"
)

lai.end_session()

import lucidicai as lai

lai.init(session_name="Model Training")

# Initial phase
lai.update_session(
    session_eval=0.3,
    session_eval_reason="Data preprocessing completed"
)

# Training phase
train_model()
lai.update_session(
    session_eval=0.7,
    session_eval_reason="Model training completed, awaiting validation"
)

# Validation phase
accuracy = validate_model()
lai.update_session(
    session_eval=accuracy,
    session_eval_reason=f"Model achieved {accuracy:.2%} accuracy on validation set",
    is_successful=accuracy > 0.9,
    is_successful_reason="Met target accuracy threshold" if accuracy > 0.9 else "Below target accuracy"
)

lai.end_session()

import lucidicai as lai

lai.init(session_name="Document Processing Pipeline")

stages = [
    ("extraction", 0.25),
    ("validation", 0.50),
    ("analysis", 0.75),
    ("reporting", 1.00)
]

for stage_name, progress in stages:
    try:
        execute_stage(stage_name)
        
        lai.update_session(
            session_eval=progress,
            session_eval_reason=f"Completed {stage_name} stage"
        )
        
    except Exception as e:
        lai.update_session(
            session_eval=progress - 0.1,
            session_eval_reason=f"Failed at {stage_name}: {str(e)}",
            is_successful=False,
            is_successful_reason=f"Pipeline interrupted at {stage_name}"
        )
        break

lai.end_session()

import lucidicai as lai
import time

lai.init(session_name="Long Running Analysis")

# Track progress over time
start_time = time.time()
total_items = 1000

for i in range(0, total_items, 100):
    batch_result = process_batch(i, i + 100)
    
    progress = (i + 100) / total_items
    elapsed = time.time() - start_time
    eta = (elapsed / progress) - elapsed
    
    lai.update_session(
        task=f"Processing batch {i//100 + 1}/10",
        session_eval=progress,
        session_eval_reason=f"Processed {i+100}/{total_items} items. ETA: {eta:.0f}s"
    )

lai.update_session(
    is_successful=True,
    is_successful_reason="All batches processed successfully"
)

lai.end_session()

import lucidicai as lai

lai.init(session_name="Quality Assurance Check")

# Define success criteria
criteria = {
    "accuracy": (0.95, False),
    "latency": (100, False),  # ms
    "memory": (512, False)    # MB
}

# Run tests and update
test_results = run_qa_tests()

# Check each criterion
for metric, (threshold, passed) in criteria.items():
    value = test_results[metric]
    if metric == "accuracy":
        criteria[metric] = (threshold, value >= threshold)
    else:  # Lower is better for latency and memory
        criteria[metric] = (threshold, value <= threshold)

all_passed = all(passed for _, (_, passed) in criteria.items())
passed_count = sum(1 for _, (_, passed) in criteria.items() if passed)

lai.update_session(
    session_eval=passed_count / len(criteria),
    session_eval_reason=f"Passed {passed_count}/{len(criteria)} QA criteria",
    is_successful=all_passed,
    is_successful_reason=(
        "All QA criteria met" if all_passed 
        else f"Failed: {', '.join(k for k, (_, p) in criteria.items() if not p)}"
    )
)

lai.end_session()

try:
    lai.update_session(task="Updated task")
except Exception:
    print("No active session to update - call lai.init() first")