Fix tqdm progress bar conflicts in concurrent RAG evaluation

• Add position pool for tqdm bars
• Serialize tqdm creation with lock
• Set leave=False to clear completed bars
• Pass position/lock to eval tasks
• Import tqdm.auto for better display
This commit is contained in:
yangdx 2025-11-05 02:04:13 +08:00
parent e5abe9dd3d
commit 2823f92fb6

View file

@ -82,7 +82,7 @@ try:
)
from ragas.llms import LangchainLLMWrapper
from langchain_openai import ChatOpenAI, OpenAIEmbeddings
from tqdm import tqdm
from tqdm.auto import tqdm
RAGAS_AVAILABLE = True
@ -351,6 +351,8 @@ class RAGEvaluator:
eval_semaphore: asyncio.Semaphore,
client: httpx.AsyncClient,
progress_counter: Dict[str, int],
position_pool: asyncio.Queue,
pbar_creation_lock: asyncio.Lock,
) -> Dict[str, Any]:
"""
Evaluate a single test case with two-stage pipeline concurrency control
@ -362,6 +364,8 @@ class RAGEvaluator:
eval_semaphore: Semaphore to control RAGAS evaluation concurrency (Stage 2)
client: Shared httpx AsyncClient for connection pooling
progress_counter: Shared dictionary for progress tracking
position_pool: Queue of available tqdm position indices
pbar_creation_lock: Lock to serialize tqdm creation and prevent race conditions
Returns:
Evaluation result dictionary
@ -407,9 +411,22 @@ class RAGEvaluator:
# concurrent state conflicts when multiple tasks run in parallel
async with eval_semaphore:
pbar = None
position = None
try:
# Create standard tqdm progress bar for RAGAS evaluation
pbar = tqdm(total=4, desc=f"Eval-{idx}", leave=True)
# Acquire a position from the pool for this tqdm progress bar
position = await position_pool.get()
# Serialize tqdm creation to prevent race conditions
# Multiple tasks creating tqdm simultaneously can cause display conflicts
async with pbar_creation_lock:
# Create tqdm progress bar with assigned position to avoid overlapping
# leave=False ensures the progress bar is cleared after completion,
# preventing accumulation of completed bars and allowing position reuse
pbar = tqdm(
total=4, desc=f"Eval-{idx}", position=position, leave=False
)
# Give tqdm time to initialize and claim its screen position
await asyncio.sleep(0.05)
eval_results = evaluate(
dataset=eval_dataset,
@ -424,9 +441,6 @@ class RAGEvaluator:
_pbar=pbar,
)
pbar.close()
pbar = None
# Convert to DataFrame (RAGAS v0.3+ API)
df = eval_results.to_pandas()
@ -487,6 +501,9 @@ class RAGEvaluator:
# Force close progress bar to ensure completion
if pbar is not None:
pbar.close()
# Release the position back to the pool for reuse
if position is not None:
await position_pool.put(position)
async def evaluate_responses(self) -> List[Dict[str, Any]]:
"""
@ -513,6 +530,16 @@ class RAGEvaluator:
# Create progress counter (shared across all tasks)
progress_counter = {"completed": 0}
# Create position pool for tqdm progress bars
# Positions range from 0 to max_async-1, ensuring no overlapping displays
position_pool = asyncio.Queue()
for i in range(max_async):
await position_pool.put(i)
# Create lock to serialize tqdm creation and prevent race conditions
# This ensures progress bars are created one at a time, avoiding display conflicts
pbar_creation_lock = asyncio.Lock()
# Create shared HTTP client with connection pooling and proper timeouts
# Timeout: 3 minutes for connect, 5 minutes for read (LLM can be slow)
timeout = httpx.Timeout(
@ -535,6 +562,8 @@ class RAGEvaluator:
eval_semaphore,
client,
progress_counter,
position_pool,
pbar_creation_lock,
)
for idx, test_case in enumerate(self.test_cases, 1)
]