Revert "passing file execution id from backend to tools" (#1071)

Revert "passing file execution id from backend to tools (#1065)"

This reverts commit 650c328.

backend/workflow_manager/endpoint_v2/source.py

@@ -34,7 +34,6 @@
     SourceConnectorNotConfigured,
 )
 from workflow_manager.endpoint_v2.models import WorkflowEndpoint
-from workflow_manager.file_execution.models import WorkflowFileExecution
 from workflow_manager.workflow_v2.execution import WorkflowExecutionServiceHelper
 from workflow_manager.workflow_v2.file_history_helper import FileHistoryHelper
 from workflow_manager.workflow_v2.models.workflow import Workflow
@@ -597,14 +596,11 @@ def _copy_file_to_destination(
                 # Update the seek position
                 seek_position += len(chunk)
 
-    def add_file_to_volume(
-        self, input_file_path: str, workflow_file_execution: WorkflowFileExecution
-    ) -> str:
+    def add_file_to_volume(self, input_file_path: str, file_hash: FileHash) -> str:
         """Add input file to execution directory.
 
         Args:
             input_file_path (str): source file
-            workflow_file_execution: WorkflowFileExecution model
 
         Raises:
             InvalidSource: _description_
@@ -618,20 +614,18 @@ def add_file_to_volume(
             file_content_hash = self.add_input_from_connector_to_volume(
                 input_file_path=input_file_path,
             )
-            if file_content_hash != workflow_file_execution.file_hash:
+            if file_content_hash != file_hash.file_hash:
                 raise FileHashMismatched()
         elif connection_type == WorkflowEndpoint.ConnectionType.API:
             self.add_input_from_api_storage_to_volume(input_file_path=input_file_path)
-            if file_name != workflow_file_execution.file_name:
+            if file_name != file_hash.file_name:
                 raise FileHashNotFound()
-            file_content_hash = workflow_file_execution.file_hash
+            file_content_hash = file_hash.file_hash
         else:
             raise InvalidSourceConnectionType()
 
         self.add_metadata_to_volume(
-            input_file_path=input_file_path,
-            file_execution_id=workflow_file_execution.id,
-            source_hash=file_content_hash,
+            input_file_path=input_file_path, source_hash=file_content_hash
         )
         return file_name
 

backend/workflow_manager/workflow_v2/workflow_helper.py

@@ -231,14 +231,14 @@ def _process_file(
         workflow_file_execution: WorkflowFileExecution,
     ) -> Optional[str]:
         error: Optional[str] = None
-        # Multiple run_ids are linked to an execution_id
-        # Each run_id corresponds to workflow runs for a single file
-        # It should e uuid of workflow_file_execution
-        file_execution_id = str(workflow_file_execution.id)
         file_name = source.add_file_to_volume(
-            input_file_path=input_file, workflow_file_execution=workflow_file_execution
+            input_file_path=input_file, file_hash=file_hash
         )
         try:
+            # Multiple run_ids are linked to an execution_id
+            # Each run_id corresponds to workflow runs for a single file
+            # It should e uuid of workflow_file_execution
+            file_execution_id = str(workflow_file_execution.id)
             execution_service.file_execution_id = file_execution_id
             execution_service.initiate_tool_execution(
                 current_file_idx, total_files, file_name, single_step

tools/classifier/requirements.txt

@@ -1,6 +1,6 @@
 # Add your dependencies here
 
 # Required for all unstract tools
-unstract-sdk~=v0.55.0rc2
+unstract-sdk~=0.54.0rc12
 # Required for remote storage support
 s3fs[boto3]==2024.6.0

tools/classifier/src/config/properties.json

@@ -2,7 +2,7 @@
   "schemaVersion": "0.0.1",
   "displayName": "File Classifier",
   "functionName": "classify",
-  "toolVersion": "0.0.45",
+  "toolVersion": "0.0.44",
   "description": "Classifies a file into a bin based on its contents",
   "input": {
     "description": "File to be classified"

tools/classifier/src/helper.py

@@ -4,7 +4,7 @@
 from typing import Any, Optional
 
 from unstract.sdk.cache import ToolCache
-from unstract.sdk.constants import LogLevel, MetadataKey, ToolEnv, UsageKwargs
+from unstract.sdk.constants import LogLevel, MetadataKey, ToolEnv
 from unstract.sdk.llm import LLM
 from unstract.sdk.tool.base import BaseTool
 from unstract.sdk.utils import ToolUtils
@@ -139,13 +139,7 @@ def _extract_from_adapter(self, file: str, adapter_id: str) -> Optional[str]:
         self.tool.stream_log(
             f"Creating text extraction adapter using adapter_id: {adapter_id}"
         )
-        usage_kwargs: dict[Any, Any] = dict()
-        usage_kwargs[UsageKwargs.FILE_NAME] = self.tool.source_file_name
-        usage_kwargs[UsageKwargs.RUN_ID] = self.tool.file_execution_id
-
-        x2text = X2Text(
-            tool=self.tool, adapter_instance_id=adapter_id, usage_kwargs=usage_kwargs
-        )
+        x2text = X2Text(tool=self.tool, adapter_instance_id=adapter_id)
 
         self.tool.stream_log("Text extraction adapter has been created successfully.")
 

tools/classifier/src/main.py

@@ -3,13 +3,7 @@
 
 from helper import ClassifierHelper  # type: ignore
 from helper import ReservedBins
-from unstract.sdk.constants import (
-    LogLevel,
-    LogState,
-    MetadataKey,
-    ToolSettingsKey,
-    UsageKwargs,
-)
+from unstract.sdk.constants import LogLevel, LogState, MetadataKey, ToolSettingsKey
 from unstract.sdk.exceptions import SdkError
 from unstract.sdk.llm import LLM
 from unstract.sdk.tool.base import BaseTool
@@ -86,10 +80,8 @@ def run(
         bins_with_quotes = [f"'{b}'" for b in bins]
 
         usage_kwargs: dict[Any, Any] = dict()
-        usage_kwargs[UsageKwargs.WORKFLOW_ID] = self.workflow_id
-        usage_kwargs[UsageKwargs.EXECUTION_ID] = self.execution_id
-        usage_kwargs[UsageKwargs.FILE_NAME] = self.source_file_name
-        usage_kwargs[UsageKwargs.RUN_ID] = self.file_execution_id
+        usage_kwargs["workflow_id"] = self.workflow_id
+        usage_kwargs["execution_id"] = self.execution_id
 
         try:
             llm = LLM(

tools/structure/requirements.txt

@@ -1,6 +1,6 @@
 # Add your dependencies here
 
 # Required for all unstract tools
-unstract-sdk~=v0.55.0rc2
+unstract-sdk~=0.54.0rc12
 # Required for remote storage support
 s3fs[boto3]==2024.6.0

tools/structure/src/config/properties.json

@@ -2,7 +2,7 @@
   "schemaVersion": "0.0.1",
   "displayName": "Structure Tool",
   "functionName": "structure_tool",
-  "toolVersion": "0.0.56",
+  "toolVersion": "0.0.55",
   "description": "This is a template tool which can answer set of input prompts designed in the Prompt Studio",
   "input": {
     "description": "File that needs to be indexed and parsed for answers"

tools/structure/src/main.py

@@ -6,12 +6,13 @@
 from typing import Any, Callable, Optional
 
 from constants import SettingsKeys  # type: ignore [attr-defined]
-from unstract.sdk.constants import LogLevel, LogState, MetadataKey, ToolEnv, UsageKwargs
+from unstract.sdk.constants import LogLevel, LogState, MetadataKey, ToolEnv
 from unstract.sdk.index import Index
 from unstract.sdk.prompt import PromptTool
 from unstract.sdk.tool.base import BaseTool
 from unstract.sdk.tool.entrypoint import ToolEntrypoint
 from unstract.sdk.utils import ToolUtils
+from unstract.sdk.utils.common_utils import CommonUtils
 from utils import json_to_markdown
 
 logger = logging.getLogger(__name__)
@@ -45,6 +46,7 @@ def run(
         )
         challenge_llm: str = settings.get(SettingsKeys.CHALLENGE_LLM_ADAPTER_ID, "")
         enable_highlight: bool = settings.get(SettingsKeys.ENABLE_HIGHLIGHT, False)
+        source_file_name = self.get_exec_metadata.get(MetadataKey.SOURCE_NAME)
         responder: PromptTool = PromptTool(
             tool=self,
             prompt_port=self.get_env_or_die(SettingsKeys.PROMPT_PORT),
@@ -72,8 +74,8 @@ def run(
             f"## Loaded '{ps_project_name}'\n{json_to_markdown(tool_metadata)}\n"
         )
         output_log = (
-            f"## Processing '{self.source_file_name}'\nThis might take a while and "
-            "involve...\n- Extracting text\n- Indexing\n- Retrieving answers "
+            f"## Processing '{source_file_name}'\nThis might take a while and involve"
+            "...\n- Extracting text\n- Indexing\n- Retrieving answers "
             f"for possibly '{total_prompt_count}' prompts"
         )
         self.stream_update(input_log, state=LogState.INPUT_UPDATE)
@@ -101,17 +103,17 @@ def run(
         execution_run_data_folder = Path(
             self.get_env_or_die(SettingsKeys.EXECUTION_RUN_DATA_FOLDER)
         )
-
+        run_id = CommonUtils.generate_uuid()
         index = Index(
             tool=self,
-            run_id=self.file_execution_id,
+            run_id=run_id,
             capture_metrics=True,
         )
         index_metrics = {}
         extracted_input_file = str(execution_run_data_folder / SettingsKeys.EXTRACT)
         # TODO : Resolve and pass log events ID
         payload = {
-            SettingsKeys.RUN_ID: self.file_execution_id,
+            SettingsKeys.RUN_ID: run_id,
             SettingsKeys.TOOL_SETTINGS: tool_settings,
             SettingsKeys.OUTPUTS: outputs,
             SettingsKeys.TOOL_ID: tool_id,
@@ -122,10 +124,10 @@ def run(
         }
         # TODO: Need to split extraction and indexing
         # to avoid unwanted indexing
-        self.stream_log(f"Indexing document '{self.source_file_name}'")
+        self.stream_log(f"Indexing document '{source_file_name}'")
         usage_kwargs: dict[Any, Any] = dict()
-        usage_kwargs[UsageKwargs.RUN_ID] = self.file_execution_id
-        usage_kwargs[UsageKwargs.FILE_NAME] = self.source_file_name
+        usage_kwargs[SettingsKeys.RUN_ID] = run_id
+        usage_kwargs[SettingsKeys.FILE_NAME] = source_file_name
 
         process_text: Optional[Callable[[str], str]] = None
         try:
@@ -248,7 +250,7 @@ def run(
         if SettingsKeys.METADATA in structured_output_dict:
             structured_output_dict[SettingsKeys.METADATA][
                 SettingsKeys.FILE_NAME
-            ] = self.source_file_name
+            ] = source_file_name
 
         if not summarize_as_source:
             metadata = structured_output_dict[SettingsKeys.METADATA]
@@ -283,7 +285,8 @@ def run(
         # Write the translated text to output file
         try:
             self.stream_log("Writing parsed output...")
-            output_path = Path(output_dir) / f"{Path(self.source_file_name).stem}.json"
+            source_name = self.get_exec_metadata.get(MetadataKey.SOURCE_NAME)
+            output_path = Path(output_dir) / f"{Path(source_name).stem}.json"
             if self.workflow_filestorage:
                 self.workflow_filestorage.json_dump(
                     path=output_path, data=structured_output_dict
@@ -326,7 +329,7 @@ def _summarize_and_index(
         vector_db_instance_id: str = tool_settings[SettingsKeys.VECTOR_DB]
         x2text_instance_id: str = tool_settings[SettingsKeys.X2TEXT_ADAPTER]
         summarize_prompt: str = tool_settings[SettingsKeys.SUMMARIZE_PROMPT]
-        run_id: str = usage_kwargs.get(UsageKwargs.RUN_ID)
+        run_id: str = usage_kwargs.get(SettingsKeys.RUN_ID)
         extract_file_path = tool_data_dir / SettingsKeys.EXTRACT
         summarize_file_path = tool_data_dir / SettingsKeys.SUMMARIZE
 

tools/text_extractor/requirements.txt

@@ -1,6 +1,6 @@
 # Add your dependencies here
 
 # Required for all unstract tools
-unstract-sdk~=v0.55.0rc2
+unstract-sdk~=0.54.0rc12
 # Required for remote storage support
 s3fs[boto3]==2024.6.0

tools/text_extractor/src/config/properties.json

@@ -2,7 +2,7 @@
   "schemaVersion": "0.0.1",
   "displayName": "Text Extractor",
   "functionName": "text_extractor",
-  "toolVersion": "0.0.43",
+  "toolVersion": "0.0.42",
   "description": "The Text Extractor is a powerful tool designed to convert documents to its text form or Extract texts from documents",
   "input": {
     "description": "Document"

tools/text_extractor/src/main.py

@@ -3,7 +3,7 @@
 from pathlib import Path
 from typing import Any
 
-from unstract.sdk.constants import LogState, UsageKwargs
+from unstract.sdk.constants import LogState, MetadataKey
 from unstract.sdk.tool.base import BaseTool
 from unstract.sdk.tool.entrypoint import ToolEntrypoint
 from unstract.sdk.x2txt import TextExtractionResult, X2Text
@@ -44,23 +44,18 @@ def run(
             None
         """
         text_extraction_adapter_id = settings["extractorId"]
+        source_name = self.get_exec_metadata.get(MetadataKey.SOURCE_NAME)
 
         self.stream_log(
             f"Extractor ID: {text_extraction_adapter_id} "
             "has been retrieved from settings."
         )
 
-        input_log = f"Processing file: \n\n`{self.source_file_name}`"
+        input_log = f"Processing file: \n\n`{source_name}`"
         self.stream_update(input_log, state=LogState.INPUT_UPDATE)
 
-        usage_kwargs: dict[Any, Any] = dict()
-        usage_kwargs[UsageKwargs.RUN_ID] = self.file_execution_id
-        usage_kwargs[UsageKwargs.FILE_NAME] = self.source_file_name
-
         text_extraction_adapter = X2Text(
-            tool=self,
-            adapter_instance_id=text_extraction_adapter_id,
-            usage_kwargs=usage_kwargs,
+            tool=self, adapter_instance_id=text_extraction_adapter_id
         )
         self.stream_log("Text extraction adapter has been created successfully.")
         if self.workflow_filestorage:
@@ -81,10 +76,8 @@ def run(
 
         try:
             self.stream_log("Preparing to write the extracted text.")
-            if self.source_file_name:
-                output_path = (
-                    Path(output_dir) / f"{Path(self.source_file_name).stem}.txt"
-                )
+            if source_name:
+                output_path = Path(output_dir) / f"{Path(source_name).stem}.txt"
                 if self.workflow_filestorage:
                     self.workflow_filestorage.write(
                         path=output_path, mode="w", data=extracted_text
@@ -96,7 +89,7 @@ def run(
                 self.stream_log("Tool output written successfully.")
             else:
                 self.stream_error_and_exit(
-                    "Error creating/writing output file: source_file_name not found"
+                    "Error creating/writing output file: source_name not found"
                 )
         except Exception as e:
             self.stream_error_and_exit(f"Error creating/writing output file: {e}")

unstract/workflow-execution/src/unstract/workflow_execution/constants.py

@@ -40,7 +40,6 @@ class MetaDataKey:
     SOURCE_HASH = "source_hash"
     WORKFLOW_ID = "workflow_id"
     EXECUTION_ID = "execution_id"
-    FILE_EXECUTION_ID = "file_execution_id"
     ORGANIZATION_ID = "organization_id"
     TOOL_METADATA = "tool_metadata"
 

unstract/workflow-execution/src/unstract/workflow_execution/execution_file_handler.py

@@ -103,17 +103,14 @@ def get_last_tool_metadata(self, metadata: dict[str, Any]) -> dict[str, Any]:
             raise ToolMetadataNotFound()
         return tool_metadata[-1]
 
-    def add_metadata_to_volume(
-        self, input_file_path: str, file_execution_id: str, source_hash: str
-    ) -> None:
+    def add_metadata_to_volume(self, input_file_path: str, source_hash: str) -> None:
         """Creating metadata for workflow. This method is responsible for
         creating metadata for the workflow. It takes the input file path and
         the source hash as parameters. The metadata is stored in a JSON file in
         the execution directory.
 
         Parameters:
             input_file_path (str): The path of the input file.
-            file_execution_id (str): Unique execution id for the file.
             source_hash (str): The hash value of the source/input file.
 
         Returns:
@@ -130,7 +127,6 @@ def add_metadata_to_volume(
             MetaDataKey.ORGANIZATION_ID: str(self.organization_id),
             MetaDataKey.WORKFLOW_ID: str(self.workflow_id),
             MetaDataKey.EXECUTION_ID: str(self.execution_id),
-            MetaDataKey.FILE_EXECUTION_ID: str(file_execution_id),
         }
         if check_feature_flag_status(FeatureFlag.REMOTE_FILE_STORAGE):
             file_system = FileSystem(FileStorageType.WORKFLOW_EXECUTION)