feat: Changes to measure time taken in index

src/unstract/sdk/index.py

@@ -23,6 +23,7 @@
 from unstract.sdk.exceptions import IndexingError, SdkError
 from unstract.sdk.tool.base import BaseTool
 from unstract.sdk.utils import ToolUtils
+from unstract.sdk.utils.common_utils import log_elapsed
 from unstract.sdk.vector_db import VectorDB
 from unstract.sdk.x2txt import X2Text
 
@@ -104,6 +105,80 @@ def query_index(
         finally:
             vector_db.close()
 
+    @log_elapsed(operation="EXTRACTION")
+    def extract_text(
+        self,
+        x2text_instance_id: str,
+        file_path: str,
+        output_file_path: Optional[str] = None,
+        enable_highlight: bool = False,
+        usage_kwargs: dict[Any, Any] = {},
+        process_text: Optional[Callable[[str], str]] = None,
+    ) -> str:
+        """Extracts text from a document.
+
+        Uses the configured service to perform the extraction
+        - LLM Whisperer
+        - Unstructured IO Community / Enterprise
+        - Llama Parse
+
+        Args:
+            x2text_instance_id (str): UUID of the text extractor
+            file_path (str): Path to the file
+            output_file_path (Optional[str], optional): File path to write
+                the extracted contents into. Defaults to None.
+            enable_highlight (bool, optional): Flag to provide highlighting metadata.
+                Defaults to False.
+            usage_kwargs (dict[Any, Any], optional): Dict to capture usage.
+                Defaults to {}.
+            process_text (Optional[Callable[[str], str]], optional): Optional function
+                to post-process the text. Defaults to None.
+
+        Raises:
+            IndexingError: Errors during text extraction
+        """
+        self.tool.stream_log("Extracting text from input file")
+        extracted_text = ""
+        try:
+            x2text = X2Text(
+                tool=self.tool,
+                adapter_instance_id=x2text_instance_id,
+                usage_kwargs=usage_kwargs,
+            )
+            if enable_highlight and isinstance(x2text._x2text_instance, LLMWhisperer):
+                process_response: TextExtractionResult = x2text.process(
+                    input_file_path=file_path,
+                    output_file_path=output_file_path,
+                    enable_highlight=enable_highlight,
+                )
+                whisper_hash_value = process_response.extraction_metadata.whisper_hash
+
+                metadata = {X2TextConstants.WHISPER_HASH: whisper_hash_value}
+
+                self.tool.update_exec_metadata(metadata)
+
+            else:
+                process_response: TextExtractionResult = x2text.process(
+                    input_file_path=file_path,
+                    output_file_path=output_file_path,
+                )
+
+            extracted_text = process_response.extracted_text
+        except AdapterError as e:
+            # Wrapping AdapterErrors with SdkError
+            raise IndexingError(str(e)) from e
+        if process_text:
+            try:
+                result = process_text(extracted_text)
+                if isinstance(result, str):
+                    extracted_text = result
+                else:
+                    logger.warning("'process_text' is expected to return an 'str'")
+            except Exception as e:
+                logger.error(f"Error occured inside function 'process_text': {e}")
+        return extracted_text
+
+    @log_elapsed(operation="INDEXING(might include EXTRACTION)")
     def index(
         self,
         tool_id: str,
@@ -207,58 +282,23 @@ def index(
                 self.tool.stream_log(f"File was indexed already under {doc_id}")
                 return doc_id
 
-            # Extract text and index
-            self.tool.stream_log("Extracting text from input file")
-            full_text = []
-            extracted_text = ""
-            try:
-                x2text = X2Text(
-                    tool=self.tool,
-                    adapter_instance_id=x2text_instance_id,
-                    usage_kwargs=usage_kwargs,
-                )
-                if enable_highlight and isinstance(
-                    x2text._x2text_instance, LLMWhisperer
-                ):
-                    process_response: TextExtractionResult = x2text.process(
-                        input_file_path=file_path,
-                        output_file_path=output_file_path,
-                        enable_highlight=enable_highlight,
-                    )
-                    whisper_hash_value = (
-                        process_response.extraction_metadata.whisper_hash
-                    )
-
-                    metadata = {X2TextConstants.WHISPER_HASH: whisper_hash_value}
-
-                    self.tool.update_exec_metadata(metadata)
-
-                else:
-                    process_response: TextExtractionResult = x2text.process(
-                        input_file_path=file_path,
-                        output_file_path=output_file_path,
-                    )
+            extracted_text = self.extract_text(
+                x2text_instance_id=x2text_instance_id,
+                file_path=file_path,
+                output_file_path=output_file_path,
+                enable_highlight=enable_highlight,
+                usage_kwargs=usage_kwargs,
+                process_text=process_text,
+            )
+            if not extracted_text:
+                raise IndexingError("No text available to index")
 
-                extracted_text = process_response.extracted_text
-            except AdapterError as e:
-                # Wrapping AdapterErrors with SdkError
-                raise IndexingError(str(e)) from e
-            if process_text:
-                try:
-                    result = process_text(extracted_text)
-                    if isinstance(result, str):
-                        extracted_text = result
-                except Exception as e:
-                    logger.error(f"Error occured inside function 'process_text': {e}")
-            full_text.append(
+            full_text = [
                 {
                     "section": "full",
                     "text_contents": extracted_text,
                 }
-            )
-
-            if not extracted_text:
-                raise IndexingError("No text available to index")
+            ]
 
             # Check if chunking is required
             documents = []
@@ -324,7 +364,6 @@ def index(
                     level=LogLevel.ERROR,
                 )
                 raise IndexingError(str(e)) from e
-            self.tool.stream_log("Added nodes to vector db")
 
             self.tool.stream_log("File has been indexed successfully")
             return doc_id

src/unstract/sdk/utils/common_utils.py

@@ -1,4 +1,6 @@
+import functools
 import logging
+import time
 import uuid
 
 from unstract.sdk.constants import LogLevel
@@ -20,3 +22,27 @@ def generate_uuid() -> str:
     logging.WARNING: LogLevel.WARN,
     logging.ERROR: LogLevel.ERROR,
 }
+
+
+def log_elapsed(operation):
+    """Adds an elapsed time log.
+
+    Args:
+        operation (str): Operation being measured
+    """
+
+    def decorator(func):
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            start_time = time.time()
+            try:
+                result = func(*args, **kwargs)
+            finally:
+                end_time = time.time()
+                elapsed_time = end_time - start_time
+                logger.info(f"Time taken for '{operation}': {elapsed_time:.3f}s")
+            return result
+
+        return wrapper
+
+    return decorator