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
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1 changed files with 35 additions and 6 deletions
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@ -82,7 +82,7 @@ try:
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)
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from ragas.llms import LangchainLLMWrapper
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from langchain_openai import ChatOpenAI, OpenAIEmbeddings
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from tqdm import tqdm
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from tqdm.auto import tqdm
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RAGAS_AVAILABLE = True
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@ -351,6 +351,8 @@ class RAGEvaluator:
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eval_semaphore: asyncio.Semaphore,
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client: httpx.AsyncClient,
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progress_counter: Dict[str, int],
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position_pool: asyncio.Queue,
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pbar_creation_lock: asyncio.Lock,
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) -> Dict[str, Any]:
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"""
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Evaluate a single test case with two-stage pipeline concurrency control
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@ -362,6 +364,8 @@ class RAGEvaluator:
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eval_semaphore: Semaphore to control RAGAS evaluation concurrency (Stage 2)
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client: Shared httpx AsyncClient for connection pooling
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progress_counter: Shared dictionary for progress tracking
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position_pool: Queue of available tqdm position indices
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pbar_creation_lock: Lock to serialize tqdm creation and prevent race conditions
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Returns:
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Evaluation result dictionary
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@ -407,9 +411,22 @@ class RAGEvaluator:
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# concurrent state conflicts when multiple tasks run in parallel
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async with eval_semaphore:
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pbar = None
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position = None
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try:
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# Create standard tqdm progress bar for RAGAS evaluation
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pbar = tqdm(total=4, desc=f"Eval-{idx}", leave=True)
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# Acquire a position from the pool for this tqdm progress bar
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position = await position_pool.get()
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# Serialize tqdm creation to prevent race conditions
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# Multiple tasks creating tqdm simultaneously can cause display conflicts
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async with pbar_creation_lock:
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# Create tqdm progress bar with assigned position to avoid overlapping
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# leave=False ensures the progress bar is cleared after completion,
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# preventing accumulation of completed bars and allowing position reuse
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pbar = tqdm(
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total=4, desc=f"Eval-{idx}", position=position, leave=False
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)
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# Give tqdm time to initialize and claim its screen position
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await asyncio.sleep(0.05)
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eval_results = evaluate(
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dataset=eval_dataset,
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@ -424,9 +441,6 @@ class RAGEvaluator:
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_pbar=pbar,
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)
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pbar.close()
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pbar = None
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# Convert to DataFrame (RAGAS v0.3+ API)
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df = eval_results.to_pandas()
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@ -487,6 +501,9 @@ class RAGEvaluator:
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# Force close progress bar to ensure completion
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if pbar is not None:
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pbar.close()
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# Release the position back to the pool for reuse
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if position is not None:
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await position_pool.put(position)
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async def evaluate_responses(self) -> List[Dict[str, Any]]:
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"""
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@ -513,6 +530,16 @@ class RAGEvaluator:
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# Create progress counter (shared across all tasks)
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progress_counter = {"completed": 0}
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# Create position pool for tqdm progress bars
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# Positions range from 0 to max_async-1, ensuring no overlapping displays
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position_pool = asyncio.Queue()
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for i in range(max_async):
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await position_pool.put(i)
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# Create lock to serialize tqdm creation and prevent race conditions
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# This ensures progress bars are created one at a time, avoiding display conflicts
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pbar_creation_lock = asyncio.Lock()
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# Create shared HTTP client with connection pooling and proper timeouts
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# Timeout: 3 minutes for connect, 5 minutes for read (LLM can be slow)
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timeout = httpx.Timeout(
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@ -535,6 +562,8 @@ class RAGEvaluator:
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eval_semaphore,
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client,
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progress_counter,
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position_pool,
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pbar_creation_lock,
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)
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for idx, test_case in enumerate(self.test_cases, 1)
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]
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