This commit resolves issue #1055 where LLM extraction was blocking async

execution, causing URLs to be processed sequentially instead of in parallel.

  Changes:
  - Added aperform_completion_with_backoff() using litellm.acompletion for async LLM calls
  - Implemented arun() method in ExtractionStrategy base class with thread pool fallback
  - Created async arun() and aextract() methods in LLMExtractionStrategy using asyncio.gather
  - Updated AsyncWebCrawler.arun() to detect and use arun() when available
  - Added comprehensive test suite to verify parallel execution

  Impact:
  - LLM extraction now runs truly in parallel across multiple URLs
  - Significant performance improvement for multi-URL crawls with LLM strategies
  - Backward compatible - existing extraction strategies continue to work
  - No breaking changes to public API

  Technical details:
  - Uses litellm.acompletion for non-blocking LLM calls
  - Leverages asyncio.gather for concurrent chunk processing
  - Maintains backward compatibility via asyncio.to_thread fallback
  - Works seamlessly with MemoryAdaptiveDispatcher and other dispatchers

crawl4ai/utils.py

@@ -1825,6 +1825,82 @@ def perform_completion_with_backoff(
             # ]
 
 
+async def aperform_completion_with_backoff(
+    provider,
+    prompt_with_variables,
+    api_token,
+    json_response=False,
+    base_url=None,
+    **kwargs,
+):
+    """
+    Async version: Perform an API completion request with exponential backoff.
+
+    How it works:
+    1. Sends an async completion request to the API.
+    2. Retries on rate-limit errors with exponential delays (async).
+    3. Returns the API response or an error after all retries.
+
+    Args:
+        provider (str): The name of the API provider.
+        prompt_with_variables (str): The input prompt for the completion request.
+        api_token (str): The API token for authentication.
+        json_response (bool): Whether to request a JSON response. Defaults to False.
+        base_url (Optional[str]): The base URL for the API. Defaults to None.
+        **kwargs: Additional arguments for the API request.
+
+    Returns:
+        dict: The API response or an error message after all retries.
+    """
+
+    from litellm import acompletion
+    from litellm.exceptions import RateLimitError
+    import asyncio
+
+    max_attempts = 3
+    base_delay = 2  # Base delay in seconds, you can adjust this based on your needs
+
+    extra_args = {"temperature": 0.01, "api_key": api_token, "base_url": base_url}
+    if json_response:
+        extra_args["response_format"] = {"type": "json_object"}
+
+    if kwargs.get("extra_args"):
+        extra_args.update(kwargs["extra_args"])
+
+    for attempt in range(max_attempts):
+        try:
+            response = await acompletion(
+                model=provider,
+                messages=[{"role": "user", "content": prompt_with_variables}],
+                **extra_args,
+            )
+            return response  # Return the successful response
+        except RateLimitError as e:
+            print("Rate limit error:", str(e))
+
+            if attempt == max_attempts - 1:
+                # Last attempt failed, raise the error.
+                raise
+
+            # Check if we have exhausted our max attempts
+            if attempt < max_attempts - 1:
+                # Calculate the delay and wait
+                delay = base_delay * (2**attempt)  # Exponential backoff formula
+                print(f"Waiting for {delay} seconds before retrying...")
+                await asyncio.sleep(delay)
+            else:
+                # Return an error response after exhausting all retries
+                return [
+                    {
+                        "index": 0,
+                        "tags": ["error"],
+                        "content": ["Rate limit error. Please try again later."],
+                    }
+                ]
+        except Exception as e:
+            raise e  # Raise any other exceptions immediately
+
+
 def extract_blocks(url, html, provider=DEFAULT_PROVIDER, api_token=None, base_url=None):
     """
     Extract content blocks from website HTML using an AI provider.