Enable app insights (#79)

backend/src/api/experimental.py

@@ -4,6 +4,7 @@
 import inspect
 import json
 import os
+import traceback
 from queue import Queue
 from threading import Thread
 
@@ -29,6 +30,7 @@ from src.api.common import (
 from src.api.query import _is_index_complete, _reformat_context_data
 from src.meta_agent.global_search.retrieve import GlobalSearchHelpers
 from src.models import GraphRequest
+from src.reporting import ReporterSingleton
 from src.utils import query as query_helper
 
 experimental_route = APIRouter(
@@ -188,6 +190,11 @@ async def global_search_streaming(request: GraphRequest):
             stream_response(report_df=report_df, query=request.query),
             media_type="application/json",
         )
-    except Exception:
-        # temporary logging of errors until reporters are in place
+    except Exception as e:
+        reporter = ReporterSingleton().get_instance()
+        reporter.on_error(
+            message="Error encountered while streaming global search response",
+            cause=e,
+            stack=traceback.format_exc(),
+        )
         raise HTTPException(status_code=500, detail=None)

backend/src/api/index.py

@@ -4,6 +4,7 @@
 import asyncio
 import inspect
 import os
+import traceback
 from typing import cast
 
 import yaml
@@ -98,7 +99,7 @@ async def setup_indexing_pipeline(
     if not _blob_service_client.get_container_client(sanitized_storage_name).exists():
         raise HTTPException(
             status_code=500,
-            detail=f"Data container '{storage_name}' does not exist.",
+            detail=f"Storage blob container {storage_name} does not exist",
         )
 
     # check for prompts
@@ -202,7 +203,7 @@ async def setup_indexing_pipeline(
                 status_code=500,
                 detail="exception when calling BatchV1Api->create_namespaced_job",
             )
-        return BaseResponse(status="indexing operation has been scheduled.")
+        return BaseResponse(status="Indexing operation scheduled")
     except Exception:
         reporter = ReporterSingleton().get_instance()
         job_details = {
@@ -215,7 +216,7 @@ async def setup_indexing_pipeline(
         )
         raise HTTPException(
             status_code=500,
-            detail=f"Error occurred during setup of indexing job for '{index_name}'.",
+            detail=f"Error occurred during setup of indexing job for index {index_name}",
         )
 
 
@@ -232,19 +233,6 @@ async def _start_indexing_pipeline(index_name: str):
     # download nltk dependencies
     bootstrap()
 
-    # create new reporters/callbacks just for this job
-    reporters = []
-    reporter_names = os.getenv("REPORTERS", Reporters.CONSOLE.name.upper()).split(",")
-    for reporter_name in reporter_names:
-        try:
-            reporters.append(Reporters[reporter_name.upper()])
-        except KeyError:
-            raise ValueError(f"Found unknown reporter: {reporter_name}")
-
-    workflow_callbacks = load_pipeline_reporter(
-        reporting_dir=sanitized_index_name, reporters=reporters
-    )
-
     # load custom pipeline settings
     this_directory = os.path.dirname(
         os.path.abspath(inspect.getfile(inspect.currentframe()))
@@ -295,7 +283,22 @@ async def _start_indexing_pipeline(index_name: str):
     for workflow in pipeline_config.workflows:
         pipeline_job.all_workflows.append(workflow.name)
 
-    # add pipeline_job callback to the callback manager
+    # create new reporters/callbacks just for this job
+    reporters = []
+    reporter_names = os.getenv("REPORTERS", Reporters.CONSOLE.name.upper()).split(",")
+    for reporter_name in reporter_names:
+        try:
+            reporters.append(Reporters[reporter_name.upper()])
+        except KeyError:
+            raise ValueError(f"Unknown reporter type: {reporter_name}")
+    workflow_callbacks = load_pipeline_reporter(
+        index_name=index_name,
+        num_workflow_steps=len(pipeline_job.all_workflows),
+        reporting_dir=sanitized_index_name,
+        reporters=reporters,
+    )
+
+    # add pipeline job callback to the callback manager
     cast(WorkflowCallbacksManager, workflow_callbacks).register(
         PipelineJobWorkflowCallbacks(pipeline_job)
     )
@@ -312,6 +315,7 @@ async def _start_indexing_pipeline(index_name: str):
                 # if the workflow failed, record the failure
                 pipeline_job.failed_workflows.append(workflow_result.workflow)
                 pipeline_job.update_db()
+                # TODO: exit early if a workflow fails and add more detailed error logging
 
         # if job is done, check if any workflow steps failed
         if len(pipeline_job.failed_workflows) > 0:
@@ -327,38 +331,43 @@ async def _start_indexing_pipeline(index_name: str):
         )
 
         workflow_callbacks.on_log(
-            f"Index Name: {index_name}, Container Name: {storage_name}\n",
-            details={"status_message": "Indexing pipeline complete."},
+            message=f"Indexing pipeline complete for index {index_name}.",
+            details={
+                "index": index_name,
+                "storage_name": storage_name,
+                "status_message": "indexing pipeline complete",
+            },
         )
 
         del workflow_callbacks  # garbage collect
         if pipeline_job.status == PipelineJobState.FAILED:
             exit(1)  # signal to AKS that indexing job failed
 
-    except Exception:
+    except Exception as e:
         pipeline_job.status = PipelineJobState.FAILED
 
         # update failed state in cosmos db
         error_details = {
-            "error_message": "Indexing pipeline failed.",
+            "index": index_name,
+            "storage_name": storage_name,
         }
         # log error in local index directory logs
         workflow_callbacks.on_error(
-            message=f"Index Name: {index_name}, Container Name: {storage_name}\n",
-            cause=None,
-            stack=None,
+            message=f"Indexing pipeline failed for index {index_name}.",
+            cause=e,
+            stack=traceback.format_exc(),
             details=error_details,
         )
         # log error in global index directory logs
         reporter.on_error(
-            f"Index Name: {index_name}, Container Name: {storage_name}\n {str(e)} \n",
-            cause=str(e),
-            stack=None,
+            message=f"Indexing pipeline failed for index {index_name}.",
+            cause=e,
+            stack=traceback.format_exc(),
             details=error_details,
         )
         raise HTTPException(
             status_code=500,
-            detail=f"Error occurred during indexing job for index '{index_name}'.",
+            detail=f"Error encountered during indexing job for index {index_name}.",
         )
 
 
@@ -437,8 +446,8 @@ def _delete_k8s_job(job_name: str, namespace: str) -> None:
         batch_v1.delete_namespaced_job(name=job_name, namespace=namespace)
     except Exception:
         reporter.on_error(
-            f"Error deleting k8s job {job_name}.",
-            details={"Container": job_name},
+            message=f"Error deleting k8s job {job_name}.",
+            details={"container": job_name},
         )
         pass
     try:
@@ -448,8 +457,8 @@ def _delete_k8s_job(job_name: str, namespace: str) -> None:
             core_v1.delete_namespaced_pod(job_pod, namespace=namespace)
     except Exception:
         reporter.on_error(
-            f"Error deleting k8s pod for job {job_name}.",
-            details={"Container": job_name},
+            message=f"Error deleting k8s pod for job {job_name}.",
+            details={"container": job_name},
         )
         pass
 

backend/src/api/query.py

@@ -3,6 +3,7 @@
 
 import inspect
 import os
+import traceback
 
 import pandas as pd
 import yaml
@@ -131,9 +132,13 @@ async def global_query(request: GraphRequest):
         ]
 
         return GraphResponse(result=result.response, context_data=result.context_data)
-    except Exception:
+    except Exception as e:
         reporter = ReporterSingleton().get_instance()
-        reporter.on_error("Could not perform global search.")
+        reporter.on_error(
+            message="Could not perform global search.",
+            cause=e,
+            stack=traceback.format_exc(),
+        )
         raise HTTPException(status_code=500, detail=None)
 
 
@@ -361,8 +366,6 @@ async def local_query(request: GraphRequest):
     result = await search_engine.asearch(request.query)
 
     # post-process the search results, mapping the index_name,index_id to allow for provenance tracking
-
-    # reformat context data
     result.context_data = _reformat_context_data(result.context_data)
 
     # map title into index_name, index_id and title for provenance tracking

backend/src/main.py

@@ -21,8 +21,23 @@ from src.api.index import index_route
 from src.api.index_configuration import index_configuration_route
 from src.api.query import query_route
 from src.api.source import source_route
+from src.reporting import ReporterSingleton
+
+
+async def catch_all_exceptions_middleware(request: Request, call_next):
+    """a function to globally catch all exceptions and return a 500 response with the exception message"""
+    try:
+        return await call_next(request)
+    except Exception as e:
+        reporter = ReporterSingleton().get_instance()
+        reporter.on_error(
+            message="Unexpected internal server error",
+            cause=e,
+            stack=traceback.format_exc(),
+        )
+        return Response("Unexpected internal server error.", status_code=500)
+
 
-url = os.getenv("APIM_GATEWAY_URL", "localhost")
 version = os.getenv("GRAPHRAG_VERSION", "undefined_version")
 
 app = FastAPI(
@@ -31,19 +46,6 @@ app = FastAPI(
     title="GraphRAG",
     version=version,
 )
-
-
-async def catch_all_exceptions_middleware(request: Request, call_next):
-    """a function to globally catch all exceptions and return a 500 response with the exception message"""
-    try:
-        return await call_next(request)
-    except Exception:
-        # only print stacktrace if developer has enabled debug mode
-        if os.getenv("DEBUG_MODE") == "on":  # possible values: on, off
-            print(traceback.format_exc())
-        return Response("Unexpected internal server error", status_code=500)
-
-
 app.middleware("http")(catch_all_exceptions_middleware)
 app.add_middleware(
     CORSMiddleware,
@@ -52,8 +54,6 @@ app.add_middleware(
     allow_methods=["*"],
     allow_headers=["*"],
 )
-
-
 app.include_router(data_route)
 app.include_router(index_route)
 app.include_router(query_route)

backend/src/reporting/application_insights_workflow_callbacks.py

@@ -19,11 +19,23 @@ from opencensus.ext.azure.log_exporter import AzureLogHandler
 class ApplicationInsightsWorkflowCallbacks(NoopWorkflowCallbacks):
     """A reporter that writes to an AppInsights Workspace."""
 
+    _logger: logging.Logger
+    _logger_name: str
+    _logger_level: int
+    _logger_level_name: str
+    _properties: Dict[str, Any]
+    _workflow_name: str
+    _index_name: str
+    _num_workflow_steps: int
+    _processed_workflow_steps: list[str] = []
+
     def __init__(
         self,
         connection_string: str,
         logger_name: str | None = None,
         logger_level: int = logging.INFO,
+        index_name: str = "",
+        num_workflow_steps: int = 0,
         properties: Dict[str, Any] = {},
     ):
         """
@@ -33,6 +45,8 @@ class ApplicationInsightsWorkflowCallbacks(NoopWorkflowCallbacks):
             connection_string (str): The connection string for the App Insights instance.
             logger_name (str | None, optional): The name of the logger. Defaults to None.
             logger_level (int, optional): The logging level. Defaults to logging.INFO.
+            index_name (str, optional): The name of an index. Defaults to "".
+            num_workflow_steps (int): A list of workflow names ordered by their execution. Defaults to [].
             properties (Dict[str, Any], optional): Additional properties to be included in the log. Defaults to {}.
         """
         self._logger: logging.Logger
@@ -40,9 +54,10 @@ class ApplicationInsightsWorkflowCallbacks(NoopWorkflowCallbacks):
         self._logger_level = logger_level
         self._logger_level_name: str = logging.getLevelName(logger_level)
         self._properties = properties
-
         self._workflow_name = "N/A"
-
+        self._index_name = index_name
+        self._num_workflow_steps = num_workflow_steps
+        self._processed_workflow_steps = []  # maintain a running list of workflow steps that get processed
         """Create a new logger with an AppInsights handler."""
         self.__init_logger(connection_string=connection_string)
 
@@ -64,12 +79,12 @@ class ApplicationInsightsWorkflowCallbacks(NoopWorkflowCallbacks):
                 self._logger.propagate = False
                 # remove any existing handlers
                 self._logger.handlers.clear()
-                # Set up Azure Monitor
+                # set up Azure Monitor
                 self._logger.addHandler(
                     AzureLogHandler(connection_string=connection_string)
                 )
-                # Set the logging level to INFO
-                self._logger.setLevel(logging.INFO)
+                # set logging level
+                self._logger.setLevel(logging.DEBUG)
 
             # reduce sentinel counter value
             max_retry -= 1
@@ -88,29 +103,44 @@ class ApplicationInsightsWorkflowCallbacks(NoopWorkflowCallbacks):
         """
         if not isinstance(details, dict) or (details is None):
             details = {}
-
         return {"custom_dimensions": {**self._properties, **unwrap_dict(details)}}
 
     def on_workflow_start(self, name: str, instance: object) -> None:
         """Execute this callback when a workflow starts."""
         self._workflow_name = name
-
-        message = f"Workflow {name} started."
+        self._processed_workflow_steps.append(name)
+        message = f"Index: {self._index_name} -- " if self._index_name else ""
+        workflow_progress = (
+            f" ({len(self._processed_workflow_steps)}/{self._num_workflow_steps})"
+            if self._num_workflow_steps
+            else ""
+        )  # will take the form "(1/4)"
+        message += f"Workflow{workflow_progress}: {name} started."
         details = {
             "workflow_name": name,
-            "workflow_instance": str(instance),
+            # "workflow_instance": str(instance),
         }
+        if self._index_name:
+            details["index_name"] = self._index_name
         self._logger.info(
             message, stack_info=False, extra=self._format_details(details=details)
         )
 
     def on_workflow_end(self, name: str, instance: object) -> None:
         """Execute this callback when a workflow ends."""
-        message = f"Workflow {name} completed."
+        message = f"Index: {self._index_name} -- " if self._index_name else ""
+        workflow_progress = (
+            f" ({len(self._processed_workflow_steps)}/{self._num_workflow_steps})"
+            if self._num_workflow_steps
+            else ""
+        )  # will take the form "(1/4)"
+        message += f"Workflow{workflow_progress}: {name} complete."
         details = {
             "workflow_name": name,
-            "workflow_instance": str(instance),
+            # "workflow_instance": str(instance),
         }
+        if self._index_name:
+            details["index_name"] = self._index_name
         self._logger.info(
             message, stack_info=False, extra=self._format_details(details=details)
         )
@@ -124,9 +154,12 @@ class ApplicationInsightsWorkflowCallbacks(NoopWorkflowCallbacks):
     ) -> None:
         """A call back handler for when an error occurs."""
         details = {} if details is None else details
-        details = {"cause": cause, "stack": stack, **details}
+        details = {"cause": str(cause), "stack": stack, **details}
         self._logger.error(
-            message, stack_info=True, extra=self._format_details(details=details)
+            message,
+            exc_info=True,
+            stack_info=False,
+            extra=self._format_details(details=details),
         )
 
     def on_warning(self, message: str, details: Optional[dict] = None) -> None:

backend/src/reporting/blob_workflow_callbacks.py

@@ -1,8 +1,6 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT License.
 
-import json
-
 # from dataclasses import asdict
 from datetime import datetime
 from typing import (
@@ -13,6 +11,7 @@ from typing import (
 from azure.identity import DefaultAzureCredential
 from azure.storage.blob import BlobServiceClient
 from datashaper import NoopWorkflowCallbacks
+from devtools import pformat
 
 
 class BlobWorkflowCallbacks(NoopWorkflowCallbacks):
@@ -20,23 +19,38 @@ class BlobWorkflowCallbacks(NoopWorkflowCallbacks):
 
     _blob_service_client: BlobServiceClient
     _container_name: str
+    _index_name: str
+    _num_workflow_steps: int
+    _processed_workflow_steps: list[str] = []
     _max_block_count: int = 25000  # 25k blocks per blob
 
     def __init__(
-        self, storage_account_blob_url: str, container_name: str, blob_name: str = ""
-    ):  # type: ignore
-        """Create a new instance of the BlobStorageReporter class."""
+        self,
+        storage_account_blob_url: str,
+        container_name: str,
+        blob_name: str = "",
+        index_name: str = "",
+        num_workflow_steps: int = 0,
+    ):
+        """Create a new instance of the BlobStorageReporter class.
+
+        Args:
+            storage_account_blob_url (str): The URL to the storage account.
+            container_name (str): The name of the container.
+            blob_name (str, optional): The name of the blob. Defaults to "".
+            index_name (str, optional): The name of the index. Defaults to "".
+            num_workflow_steps (int): A list of workflow names ordered by their execution. Defaults to [].
+        """
         self._storage_account_blob_url = storage_account_blob_url
         credential = DefaultAzureCredential()
         self._blob_service_client = BlobServiceClient(
             storage_account_blob_url, credential=credential
         )
-
-        if blob_name == "":
-            blob_name = (
-                f"report/{datetime.now().strftime('%Y-%m-%d-%H:%M:%S:%f')}.logs.json"
-            )
-
+        if not blob_name:
+            blob_name = f"{container_name}/{datetime.now().strftime('%Y-%m-%d-%H:%M:%S:%f')}.logs.txt"
+        self._index_name = index_name
+        self._num_workflow_steps = num_workflow_steps
+        self._processed_workflow_steps = []  # maintain a running list of workflow steps that get processed
         self._blob_name = blob_name
         self._container_name = container_name
         self._blob_client = self._blob_service_client.get_blob_client(
@@ -44,22 +58,16 @@ class BlobWorkflowCallbacks(NoopWorkflowCallbacks):
         )
         if not self._blob_client.exists():
             self._blob_client.create_append_blob()
-
         self._num_blocks = 0  # refresh block counter
 
     def _write_log(self, log: dict[str, Any]):
         # create a new file when block count hits close 25k
-        if (
-            self._num_blocks >= self._max_block_count
-        ):  # Check if block count exceeds 25k
+        if self._num_blocks >= self._max_block_count:
             self.__init__(self._storage_account_blob_url, self._container_name)
-
         blob_client = self._blob_service_client.get_blob_client(
             self._container_name, self._blob_name
         )
-        blob_client.append_block(json.dumps(log) + "\n")
-
-        # update the blob's block count
+        blob_client.append_block(pformat(log, indent=2) + "\n")
         self._num_blocks += 1
 
     def on_error(
@@ -83,23 +91,39 @@ class BlobWorkflowCallbacks(NoopWorkflowCallbacks):
     def on_workflow_start(self, name: str, instance: object) -> None:
         """Execute this callback when a workflow starts."""
         self._workflow_name = name
-
-        message = f"Workflow {name} started."
+        self._processed_workflow_steps.append(name)
+        message = f"Index: {self._index_name} -- " if self._index_name else ""
+        workflow_progress = (
+            f" ({len(self._processed_workflow_steps)}/{self._num_workflow_steps})"
+            if self._num_workflow_steps
+            else ""
+        )  # will take the form "(1/4)"
+        message += f"Workflow{workflow_progress}: {name} started."
         details = {
             "workflow_name": name,
-            "workflow_instance": str(instance),
+            # "workflow_instance": str(instance),
         }
+        if self._index_name:
+            details["index_name"] = self._index_name
         self._write_log(
             {"type": "on_workflow_start", "data": message, "details": details}
         )
 
     def on_workflow_end(self, name: str, instance: object) -> None:
         """Execute this callback when a workflow ends."""
-        message = f"Workflow {name} completed."
+        message = f"Index: {self._index_name} -- " if self._index_name else ""
+        workflow_progress = (
+            f" ({len(self._processed_workflow_steps)}/{self._num_workflow_steps})"
+            if self._num_workflow_steps
+            else ""
+        )  # will take the form "(1/4)"
+        message += f"Workflow{workflow_progress}: {name} complete."
         details = {
             "workflow_name": name,
-            "workflow_instance": str(instance),
+            # "workflow_instance": str(instance),
         }
+        if self._index_name:
+            details["index_name"] = self._index_name
         self._write_log(
             {"type": "on_workflow_end", "data": message, "details": details}
         )

backend/src/reporting/console_workflow_callbacks.py

@@ -17,10 +17,22 @@ from datashaper.workflow.workflow_callbacks import NoopWorkflowCallbacks
 class ConsoleWorkflowCallbacks(NoopWorkflowCallbacks):
     """A reporter that writes to a stream (sys.stdout)."""
 
+    _logger: logging.Logger
+    _logger_name: str
+    _logger_level: int
+    _logger_level_name: str
+    _properties: Dict[str, Any]
+    _workflow_name: str
+    _index_name: str
+    _num_workflow_steps: int
+    _processed_workflow_steps: list[str] = []
+
     def __init__(
         self,
         logger_name: str | None = None,
         logger_level: int = logging.INFO,
+        index_name: str = "",
+        num_workflow_steps: int = 0,
         properties: Dict[str, Any] = {},
     ):
         """
@@ -29,6 +41,8 @@ class ConsoleWorkflowCallbacks(NoopWorkflowCallbacks):
         Args:
             logger_name (str | None, optional): The name of the logger. Defaults to None.
             logger_level (int, optional): The logging level. Defaults to logging.INFO.
+            index_name (str, optional): The name of an index. Defaults to "".
+            num_workflow_steps (int): A list of workflow names ordered by their execution. Defaults to [].
             properties (Dict[str, Any], optional): Additional properties to be included in the log. Defaults to {}.
         """
         self._logger: logging.Logger
@@ -36,9 +50,10 @@ class ConsoleWorkflowCallbacks(NoopWorkflowCallbacks):
         self._logger_level = logger_level
         self._logger_level_name: str = logging.getLevelName(logger_level)
         self._properties = properties
-
         self._workflow_name = "N/A"
-
+        self._index_name = index_name
+        self._num_workflow_steps = num_workflow_steps
+        self._processed_workflow_steps = []  # maintain a running list of workflow steps that get processed
         """Create a new logger with an AppInsights handler."""
         self.__init_logger()
 
@@ -62,7 +77,7 @@ class ConsoleWorkflowCallbacks(NoopWorkflowCallbacks):
                 self._logger.handlers.clear()
                 # create a console handler
                 handler = logging.StreamHandler(stream=sys.stdout)
-                # Create a formatter and include 'extra_details' in the format string
+                # create a formatter and include 'extra_details' in the format string
                 handler.setFormatter(
                     # logging.Formatter(
                     #     "[%(levelname)s] %(asctime)s - %(message)s \n %(stack)s"
@@ -70,7 +85,7 @@ class ConsoleWorkflowCallbacks(NoopWorkflowCallbacks):
                     logging.Formatter("[%(levelname)s] %(asctime)s - %(message)s")
                 )
                 self._logger.addHandler(handler)
-                # Set the logging level to INFO
+                # set logging level
                 self._logger.setLevel(logging.INFO)
 
             # reduce sentinel counter value
@@ -90,29 +105,44 @@ class ConsoleWorkflowCallbacks(NoopWorkflowCallbacks):
         """
         if not isinstance(details, dict) or (details is None):
             details = {}
-
         return {**self._properties, **details}
 
     def on_workflow_start(self, name: str, instance: object) -> None:
         """Execute this callback when a workflow starts."""
         self._workflow_name = name
-
-        message = f"Workflow {name} started."
+        self._processed_workflow_steps.append(name)
+        message = f"Index: {self._index_name} -- " if self._index_name else ""
+        workflow_progress = (
+            f" ({len(self._processed_workflow_steps)}/{self._num_workflow_steps})"
+            if self._num_workflow_steps
+            else ""
+        )  # will take the form "(1/4)"
+        message += f"Workflow{workflow_progress}: {name} started."
         details = {
             "workflow_name": name,
-            "workflow_instance": str(instance),
+            # "workflow_instance": str(instance),
         }
+        if self._index_name:
+            details["index_name"] = self._index_name
         self._logger.info(
             message, stack_info=False, extra=self._format_details(details=details)
         )
 
     def on_workflow_end(self, name: str, instance: object) -> None:
         """Execute this callback when a workflow ends."""
-        message = f"Workflow {name} completed."
+        message = f"Index: {self._index_name} -- " if self._index_name else ""
+        workflow_progress = (
+            f" ({len(self._processed_workflow_steps)}/{self._num_workflow_steps})"
+            if self._num_workflow_steps
+            else ""
+        )  # will take the form "(1/4)"
+        message += f"Workflow{workflow_progress}: {name} complete."
         details = {
             "workflow_name": name,
-            "workflow_instance": str(instance),
+            # "workflow_instance": str(instance),
         }
+        if self._index_name:
+            details["index_name"] = self._index_name
         self._logger.info(
             message, stack_info=False, extra=self._format_details(details=details)
         )
@@ -126,9 +156,12 @@ class ConsoleWorkflowCallbacks(NoopWorkflowCallbacks):
     ) -> None:
         """A call back handler for when an error occurs."""
         details = {} if details is None else details
-        details = {"cause": cause, "stack": stack, **details}
+        details = {"cause": str(cause), "stack": stack, **details}
         self._logger.error(
-            message, stack_info=False, extra=self._format_details(details=details)
+            message,
+            exc_info=True,
+            stack_info=False,
+            extra=self._format_details(details=details),
         )
 
     def on_warning(self, message: str, details: Optional[dict] = None) -> None:

backend/src/reporting/load_reporter.py

@@ -4,15 +4,9 @@
 import os
 from datetime import datetime
 from pathlib import Path
-from typing import Any, Dict, List, cast
+from typing import List
 
 from datashaper import WorkflowCallbacks, WorkflowCallbacksManager
-from graphrag.index.config import (
-    PipelineBlobReportingConfig,
-    PipelineConsoleReportingConfig,
-    PipelineFileReportingConfig,
-    PipelineReportingConfig,
-)
 from graphrag.index.reporting import FileWorkflowCallbacks
 
 from src.api.azure_clients import BlobServiceClientSingleton
@@ -21,82 +15,63 @@ from src.reporting.application_insights_workflow_callbacks import (
 )
 from src.reporting.blob_workflow_callbacks import BlobWorkflowCallbacks
 from src.reporting.console_workflow_callbacks import ConsoleWorkflowCallbacks
-from src.reporting.typing import (
-    PipelineAppInsightsReportingConfig,
-    Reporters,
-)
+from src.reporting.typing import Reporters
 
 
-def load_pipeline_reporter_from_config(
-    root_dir: str | None, config: PipelineReportingConfig | None
-) -> WorkflowCallbacks:
-    """Create a reporter for the given pipeline config."""
-    reporting_config = config or PipelineConsoleReportingConfig(type="console")
-    if reporting_config.type == Reporters.FILE.name.lower():
-        reporting_config = cast(PipelineFileReportingConfig, reporting_config)
-        reporting_dir = os.path.join(root_dir or "", reporting_config.base_dir)
-        return FileWorkflowCallbacks(reporting_dir)
-    elif reporting_config.type == Reporters.CONSOLE.name.lower():
-        return ConsoleWorkflowCallbacks()
-    elif reporting_config.type == Reporters.BLOB.name.lower():
-        reporting_config = cast(PipelineBlobReportingConfig, reporting_config)
-        return BlobWorkflowCallbacks(
-            reporting_config.storage_account_blob_url, reporting_config.container_name
-        )
-    elif reporting_config.type == Reporters.APP_INSIGHTS.name.lower():
-        reporting_config = cast(PipelineAppInsightsReportingConfig, reporting_config)
-        return ApplicationInsightsWorkflowCallbacks(
-            connection_string=reporting_config.connection_string,
-            logger_name=reporting_config.logger_name,
-            logger_level=reporting_config.logger_level,
-        )
-    raise ValueError(f"Unknown reporting type: {reporting_config.type}")
-
-
-def load_pipeline_reporter_from_list(
+# def load_pipeline_reporter_from_list(
+def load_pipeline_reporter(
     reporting_dir: str | None,
     reporters: List[Reporters] | None = [],
+    index_name: str = "",
+    num_workflow_steps: int = 0,
 ) -> WorkflowCallbacks:
-    """Creates a reporter for the given a list of reporting enum."""
+    """Create a callback manager and register a list of reporters.
+    Reporters may be configured as generic loggers or associated with a specified indexing job.
+    """
     callback_manager = WorkflowCallbacksManager()
-    console = ConsoleWorkflowCallbacks()
     for reporter in reporters:
-        if reporter == Reporters.BLOB:
-            # create a dedicated container for the reporting logs
-            container_name = "reports"
-            if reporting_dir is not None:
-                container_name = os.path.join(reporting_dir, container_name)
-
-            # make sure the root directory exists; if not, create it
-            blob_service_client = BlobServiceClientSingleton.get_instance()
-            container_root = Path(container_name).parts[0]
-            if not blob_service_client.get_container_client(container_root).exists():
-                blob_service_client.create_container(container_root)
-
-            # register the blob reporter
-            callback_manager.register(
-                BlobWorkflowCallbacks(
-                    storage_account_blob_url=os.environ["STORAGE_ACCOUNT_BLOB_URL"],
-                    container_name=container_name,
-                    blob_name=f"{datetime.now().strftime('%Y-%m-%d-%H:%M:%S:%f')}.logs.json",
+        match reporter:
+            case Reporters.BLOB:
+                # create a dedicated container for logs
+                container_name = "logs"
+                if reporting_dir is not None:
+                    container_name = os.path.join(reporting_dir, container_name)
+                # ensure the root directory exists; if not, create it
+                blob_service_client = BlobServiceClientSingleton.get_instance()
+                container_root = Path(container_name).parts[0]
+                if not blob_service_client.get_container_client(
+                    container_root
+                ).exists():
+                    blob_service_client.create_container(container_root)
+                # register the blob reporter
+                callback_manager.register(
+                    BlobWorkflowCallbacks(
+                        storage_account_blob_url=os.environ["STORAGE_ACCOUNT_BLOB_URL"],
+                        container_name=container_name,
+                        blob_name=f"{datetime.now().strftime('%Y-%m-%d-%H:%M:%S:%f')}.logs.txt",
+                        index_name=index_name,
+                        num_workflow_steps=num_workflow_steps,
+                    )
                 )
-            )
-        elif reporter == Reporters.CONSOLE:
-            callback_manager.register(ConsoleWorkflowCallbacks())
-        elif reporter == Reporters.FILE:
-            callback_manager.register(FileWorkflowCallbacks(dir=reporting_dir))
-        else:
-            # use console reporter as default
-            callback_manager.register(console)
-            callback_manager.on_warning(f"Could not find reporter of type {reporter}")
+            case Reporters.FILE:
+                callback_manager.register(FileWorkflowCallbacks(dir=reporting_dir))
+            case Reporters.APP_INSIGHTS:
+                if os.getenv("APP_INSIGHTS_CONNECTION_STRING"):
+                    callback_manager.register(
+                        ApplicationInsightsWorkflowCallbacks(
+                            connection_string=os.environ[
+                                "APP_INSIGHTS_CONNECTION_STRING"
+                            ],
+                            index_name=index_name,
+                            num_workflow_steps=num_workflow_steps,
+                        )
+                    )
+            case _:
+                print(f"WARNING: unknown reporter type: {reporter}. Skipping.")
+    # always register the console reporter as a fallback
+    callback_manager.register(
+        ConsoleWorkflowCallbacks(
+            index_name=index_name, num_workflow_steps=num_workflow_steps
+        )
+    )
     return callback_manager
-
-
-def load_pipeline_reporter(
-    from_config=False,
-    config: PipelineReportingConfig | None = None,
-    **kwargs: Dict[str, Any],
-) -> WorkflowCallbacks:
-    if from_config:
-        return load_pipeline_reporter_from_config(config)
-    return load_pipeline_reporter_from_list(**kwargs)

backend/src/reporting/pipeline_job_workflow_callbacks.py

@@ -26,13 +26,13 @@ class PipelineJobWorkflowCallbacks(NoopWorkflowCallbacks):
         # if we are not already running, set the status to running
         if self._pipeline_job.status != PipelineJobState.RUNNING:
             self._pipeline_job.status = PipelineJobState.RUNNING
-        self._pipeline_job.progress = f"Workflow '{name}' started."
+        self._pipeline_job.progress = f"Workflow {name} started."
 
     def on_workflow_end(self, name: str, instance: object) -> None:
         """Execute this callback when a workflow ends."""
         self._pipeline_job.completed_workflows.append(name)
         self._pipeline_job.update_db()
-        self._pipeline_job.progress = f"Workflow '{name}' complete."
+        self._pipeline_job.progress = f"Workflow {name} complete."
         self._pipeline_job.percent_complete = (
             self._pipeline_job.calculate_percent_complete()
         )

backend/src/reporting/reporter_singleton.py

@@ -6,7 +6,7 @@ from urllib.parse import urlparse
 
 from datashaper import WorkflowCallbacks
 
-from src.reporting.load_reporter import load_pipeline_reporter_from_list
+from src.reporting.load_reporter import load_pipeline_reporter
 from src.reporting.typing import Reporters
 
 
@@ -16,7 +16,7 @@ class ReporterSingleton:
     @classmethod
     def get_instance(cls) -> WorkflowCallbacks:
         if cls._instance is None:
-            # Setting up reporters based on environment variable or defaults
+            # Set up reporters based on environment variable or defaults
             reporters = []
             for reporter_name in os.getenv(
                 "REPORTERS", Reporters.CONSOLE.name.upper()
@@ -25,8 +25,7 @@ class ReporterSingleton:
                     reporters.append(Reporters[reporter_name.upper()])
                 except KeyError:
                     raise ValueError(f"Found unknown reporter: {reporter_name}")
-
-            cls._instance = load_pipeline_reporter_from_list(
+            cls._instance = load_pipeline_reporter(
                 reporting_dir="", reporters=reporters
             )
         return cls._instance

backend/src/reporting/typing.py

@@ -16,15 +16,15 @@ class Reporters(Enum):
     BLOB = (1, "blob")
     CONSOLE = (2, "console")
     FILE = (3, "file")
-    APP_INSIGHTS = (4, "application_insights")
+    APP_INSIGHTS = (4, "app_insights")
 
 
 class PipelineAppInsightsReportingConfig(
-    PipelineReportingConfig[Literal["application_insights"]]
+    PipelineReportingConfig[Literal["app_insights"]]
 ):
     """Represents the ApplicationInsights reporting configuration for the pipeline."""
 
-    type: Literal["application_insights"] = Reporters.APP_INSIGHTS.name.lower()
+    type: Literal["app_insights"] = Reporters.APP_INSIGHTS.name.lower()
     """The type of reporting."""
 
     connection_string: str = pydantic_Field(

docs/DEPLOYMENT-GUIDE.md

@@ -91,8 +91,8 @@ In the `deploy.parameters.json` file, provide values for the following required
 `APIM_NAME`                            |                                           | No  | Hostname of the API. Must be a globally unique name. The API will be accessible at `https://<APIM_NAME>.azure-api.net`. If not provided a unique name will be generated.
 `RESOURCE_BASE_NAME`                   |                                           | No  | Suffix to apply to all azure resource names. If not provided a unique suffix will be generated.
 `AISEARCH_ENDPOINT_SUFFIX`             |                                           | No  | Suffix to apply to AI search endpoint. Will default to `search.windows.net` for Azure Commercial cloud but should be overridden for deployments in other Azure clouds.
-`AISEARCH_AUDIENCE`                    |                                           | No  | Audience for AAD for AI Search. Will default to `https://search.azure.com/` for Azure Commercial cloud but should be overridden for deployments in other Azure clouds.D
-`REPORTERS`                            |                                           | No  | The type of logging to enable. If not provided, logging will be saved to a file in Azure Storage and to the console in AKS.
+`AISEARCH_AUDIENCE`                    |                                           | No  | Audience for AAD for AI Search. Will default to `https://search.azure.com/` for Azure Commercial cloud but should be overridden for deployments in other Azure clouds.
+`REPORTERS`                            | blob,console,app_insights                 | No  | The type of logging to enable. A comma separated string containing at least one of the following `[blob,console,file,app_insights]`. Default value = `blob,console,app_insights`
 
 ### 5. Deploy solution accelerator to the resource group
 ```shell

infra/core/aks/aks.bicep

@@ -13,7 +13,7 @@ param logAnalyticsWorkspaceId string
 @description('The auto-upgrade profile.')
 param autoUpgradeProfile object = {
   nodeOsUpgradeChannel: 'NodeImage'
-  upgradeChannel: 'node-image'
+  upgradeChannel: 'stable'
 }
 
 @description('Optional DNS prefix to use with hosted Kubernetes API server FQDN.')

infra/core/apim/apim.bicep

@@ -28,6 +28,9 @@ param virtualNetworkName string = 'apimvnet'
 @description('Application Insights resource name')
 param appInsightsName string = 'apim-appi'
 
+@description('Application Insights public network access for ingestion')
+param appInsightsPublicNetworkAccessForIngestion string = 'Disabled'
+
 @description('Address prefix')
 param virtualNetworkAddressPrefix string = '10.0.0.0/12'
 
@@ -442,7 +445,7 @@ resource appInsights 'Microsoft.Insights/components@2020-02-02' = {
   properties: {
     Application_Type: 'web'
     WorkspaceResourceId: logAnalyticsWorkspaceId
-    publicNetworkAccessForIngestion: 'Disabled'
+    publicNetworkAccessForIngestion: appInsightsPublicNetworkAccessForIngestion
     publicNetworkAccessForQuery: 'Enabled'
   }
 }
@@ -451,6 +454,7 @@ output apimIPs array = apiManagementService.properties.publicIPAddresses
 output apimGatewayUrl string = apiManagementService.properties.gatewayUrl
 output appInsightsName string = appInsights.name
 output appInsightsId string = appInsights.id
+output appInsightsConnectionString string = appInsights.properties.ConnectionString
 output name string = apiManagementService.name
 output vnetName string = virtualNetwork.name
 output vnetId string = virtualNetwork.id

infra/core/log-analytics/log.bicep

@@ -7,12 +7,15 @@ param name string
 @description('The location of the Log Analytics resource.')
 param location string = resourceGroup().location
 
+@description('The public network access for ingestion.')
+param publicNetworkAccessForIngestion string = 'Disabled'
+
 resource logAnalyticsWorkspace 'Microsoft.OperationalInsights/workspaces@2022-10-01' = {
   name: name
   location: location
   properties: {
     retentionInDays: 30
-    publicNetworkAccessForIngestion: 'Disabled'
+    publicNetworkAccessForIngestion: publicNetworkAccessForIngestion
     publicNetworkAccessForQuery: 'Enabled'
     features: {
       immediatePurgeDataOn30Days: true

infra/deploy.sh

@@ -163,8 +163,8 @@ populateOptionalParams () {
         printf "\tsetting RESOURCE_BASE_NAME=$RESOURCE_BASE_NAME\n"
     fi
     if [ -z "$REPORTERS" ]; then
-        REPORTERS="blob,console"
-        printf "\tsetting REPORTERS=blob,console\n"
+        REPORTERS="blob,console,app_insights"
+        printf "\tsetting REPORTERS=blob,console,app_insights\n"
     fi
     if [ -z "$GRAPHRAG_COGNITIVE_SERVICES_ENDPOINT" ]; then
         GRAPHRAG_COGNITIVE_SERVICES_ENDPOINT="https://cognitiveservices.azure.com/.default"
@@ -325,8 +325,8 @@ installGraphRAGHelmChart () {
     local serviceAccountName=$(jq -r .azure_aks_service_account_name.value <<< $AZURE_OUTPUTS)
     exitIfValueEmpty "$serviceAccountName" "Unable to parse service account name from Azure outputs, exiting..."
 
-    local apimGatewayUrl=$(jq -r .azure_apim_url.value <<< $AZURE_OUTPUTS)
-    exitIfValueEmpty "$apimGatewayUrl" "Unable to parse APIM gateway url from Azure outputs, exiting..."
+    local appInsightsConnectionString=$(jq -r .azure_app_insights_connection_string.value <<< $AZURE_OUTPUTS)
+    exitIfValueEmpty "$appInsightsConnectionString" "Unable to parse app insights connection string from Azure outputs, exiting..."
 
     local aiSearchName=$(jq -r .azure_ai_search_name.value <<< $AZURE_OUTPUTS)
     exitIfValueEmpty "$aiSearchName" "Unable to parse AI search name from Azure outputs, exiting..."
@@ -370,7 +370,7 @@ installGraphRAGHelmChart () {
         --set "query.image.repository=$CONTAINER_REGISTRY_SERVER/$graphragImageName" \
         --set "query.image.tag=$graphragImageVersion" \
         --set "ingress.host=$graphragHostname" \
-        --set "graphragConfig.APIM_GATEWAY_URL=$apimGatewayUrl" \
+        --set "graphragConfig.APP_INSIGHTS_CONNECTION_STRING=$appInsightsConnectionString" \
         --set "graphragConfig.AI_SEARCH_URL=https://$aiSearchName.$AISEARCH_ENDPOINT_SUFFIX" \
         --set "graphragConfig.AI_SEARCH_AUDIENCE=$AISEARCH_AUDIENCE" \
         --set "graphragConfig.COSMOS_URI_ENDPOINT=$cosmosEndpoint" \

infra/helm/graphrag/values.yaml

@@ -28,7 +28,6 @@ ingress:
   tls: []
 
 graphragConfig:
-  APIM_GATEWAY_URL: ""
   COSMOS_URI_ENDPOINT: ""
   DEBUG_MODE: "off"
   GRAPHRAG_API_BASE: ""

infra/main.bicep

@@ -92,6 +92,7 @@ module log 'core/log-analytics/log.bicep' = {
   params:{
     name: '${abbrs.operationalInsightsWorkspaces}${resourceBaseNameFinal}'
     location: location
+    publicNetworkAccessForIngestion: enablePrivateEndpoints ? 'Disabled' : 'Enabled'
   }
 }
 
@@ -178,6 +179,7 @@ module apim 'core/apim/apim.bicep' = {
   params: {
     apiManagementName: !empty(apimName) ? apimName : '${abbrs.apiManagementService}${resourceBaseNameFinal}'
     appInsightsName: '${abbrs.insightsComponents}${resourceBaseNameFinal}'
+    appInsightsPublicNetworkAccessForIngestion: enablePrivateEndpoints ? 'Disabled' : 'Enabled'
     nsgName: '${abbrs.networkNetworkSecurityGroups}${resourceBaseNameFinal}'
     publicIpName: '${abbrs.networkPublicIPAddresses}${resourceBaseNameFinal}'
     virtualNetworkName: '${abbrs.networkVirtualNetworks}${resourceBaseNameFinal}'
@@ -326,6 +328,7 @@ output azure_storage_account_blob_url string = storage.outputs.primaryEndpoints.
 output azure_cosmosdb_endpoint string = cosmosdb.outputs.endpoint
 output azure_cosmosdb_name string = cosmosdb.outputs.name
 output azure_cosmosdb_id string = cosmosdb.outputs.id
+output azure_app_insights_connection_string string = apim.outputs.appInsightsConnectionString
 output azure_apim_name string = apim.outputs.name
 output azure_apim_url string = apim.outputs.apimGatewayUrl
 output azure_apim_vnet_name string = apim.outputs.vnetName

notebooks/2-Advanced_Getting_Started.ipynb

@@ -597,8 +597,9 @@
     "    community_prompt_filepath=community_prompt,\n",
     "    summarize_description_prompt_filepath=summarize_prompt,\n",
     ")\n",
-    "pprint(response.json())\n",
-    "if not response.ok:\n",
+    "if response.ok:\n",
+    "    pprint(response.json())\n",
+    "else:\n",
     "    print(f\"Failed to submit job.\\nStatus: {response.text}\")"
    ]
   },
@@ -631,7 +632,10 @@
    "source": [
     "response = index_status(index_name)\n",
     "print(response)\n",
-    "pprint(response.json())"
+    "if response.ok:\n",
+    "    pprint(response.json())\n",
+    "else:\n",
+    "    print(response.text)"
    ]
   },
   {

poetry.lock

@@ -612,13 +612,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2024.6.2"
+version = "2024.7.4"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2024.6.2-py3-none-any.whl", hash = "sha256:ddc6c8ce995e6987e7faf5e3f1b02b302836a0e5d98ece18392cb1a36c72ad56"},
-    {file = "certifi-2024.6.2.tar.gz", hash = "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516"},
+    {file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"},
+    {file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"},
 ]
 
 [[package]]
@@ -1094,13 +1094,13 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "dask"
-version = "2024.6.2"
+version = "2024.7.0"
 description = "Parallel PyData with Task Scheduling"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "dask-2024.6.2-py3-none-any.whl", hash = "sha256:81b80ee015b2e057b93bb2d1bf13a866136e762e2b24bf54b6b621e8b86b7708"},
-    {file = "dask-2024.6.2.tar.gz", hash = "sha256:d429d6b19e85fd1306ac37c188aaf99d03bbe69a6fe59d2b42882b2ac188686f"},
+    {file = "dask-2024.7.0-py3-none-any.whl", hash = "sha256:0f30f218a1fe1c8e9a6ba8add1207088ba9ff049098d4ea4ce045fd5ff7ca914"},
+    {file = "dask-2024.7.0.tar.gz", hash = "sha256:0060bae9a58b5b3ce7e0d97040e903b4d3db09ba49222101cfc40f9834a8a6bc"},
 ]
 
 [package.dependencies]
@@ -1111,32 +1111,32 @@ fsspec = ">=2021.09.0"
 importlib-metadata = {version = ">=4.13.0", markers = "python_version < \"3.12\""}
 numpy = {version = ">=1.21", optional = true, markers = "extra == \"array\""}
 packaging = ">=20.0"
-pandas = {version = ">=1.3", optional = true, markers = "extra == \"dataframe\""}
-partd = ">=1.2.0"
+pandas = {version = ">=2.0", optional = true, markers = "extra == \"dataframe\""}
+partd = ">=1.4.0"
 pyyaml = ">=5.3.1"
 toolz = ">=0.10.0"
 
 [package.extras]
 array = ["numpy (>=1.21)"]
 complete = ["dask[array,dataframe,diagnostics,distributed]", "lz4 (>=4.3.2)", "pyarrow (>=7.0)", "pyarrow-hotfix"]
-dataframe = ["dask-expr (>=1.1,<1.2)", "dask[array]", "pandas (>=1.3)"]
+dataframe = ["dask-expr (>=1.1,<1.2)", "dask[array]", "pandas (>=2.0)"]
 diagnostics = ["bokeh (>=2.4.2)", "jinja2 (>=2.10.3)"]
-distributed = ["distributed (==2024.6.2)"]
+distributed = ["distributed (==2024.7.0)"]
 test = ["pandas[test]", "pre-commit", "pytest", "pytest-cov", "pytest-rerunfailures", "pytest-timeout", "pytest-xdist"]
 
 [[package]]
 name = "dask-expr"
-version = "1.1.6"
+version = "1.1.7"
 description = "High Level Expressions for Dask"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "dask_expr-1.1.6-py3-none-any.whl", hash = "sha256:04e31cb941b7cbdce7b1384f2bcf17fd17e828e45e9c74491e28473095ee6891"},
-    {file = "dask_expr-1.1.6.tar.gz", hash = "sha256:ace366c6d9c248a7fa7b48f7a34140afae3b6a0ea14ee57743babe5a9d1ef43f"},
+    {file = "dask_expr-1.1.7-py3-none-any.whl", hash = "sha256:6f45468499b50839e9d9a43f599f7f70a50f50048bce93557c2dea24bfcad3bb"},
+    {file = "dask_expr-1.1.7.tar.gz", hash = "sha256:90a0afae1fcdc2071914daf8f32673d59ee027c12ae041941043bdede63c993c"},
 ]
 
 [package.dependencies]
-dask = "2024.6.2"
+dask = "2024.7.0"
 pandas = ">=2"
 pyarrow = ">=7.0.0"
 
@@ -1521,53 +1521,53 @@ pyflakes = ">=3.2.0,<3.3.0"
 
 [[package]]
 name = "fonttools"
-version = "4.53.0"
+version = "4.53.1"
 description = "Tools to manipulate font files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fonttools-4.53.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:52a6e0a7a0bf611c19bc8ec8f7592bdae79c8296c70eb05917fd831354699b20"},
-    {file = "fonttools-4.53.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:099634631b9dd271d4a835d2b2a9e042ccc94ecdf7e2dd9f7f34f7daf333358d"},
-    {file = "fonttools-4.53.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e40013572bfb843d6794a3ce076c29ef4efd15937ab833f520117f8eccc84fd6"},
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 [package.dependencies]
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 rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"format-nongpl\""}
 rpds-py = ">=0.7.1"
 uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
-webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-nongpl\""}
+webcolors = {version = ">=24.6.0", optional = true, markers = "extra == \"format-nongpl\""}
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
-format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"]
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 [[package]]
 name = "jsonschema-specifications"
@@ -2972,40 +2972,40 @@ tests = ["pytest", "pytz", "simplejson"]
 
 [[package]]
 name = "matplotlib"
-version = "3.9.0"
+version = "3.9.1"
 description = "Python plotting package"
 optional = false
 python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
@@ -3503,13 +3503,13 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 
 [[package]]
 name = "openai"
-version = "1.35.7"
+version = "1.35.13"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -3571,57 +3571,62 @@ requests = ">=2.19.0"
 
 [[package]]
 name = "orjson"
-version = "3.10.5"
+version = "3.10.6"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
@@ -5045,110 +5051,110 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 
 [[package]]
 name = "rpds-py"
-version = "0.18.1"
+version = "0.19.0"
 description = "Python bindings to Rust's persistent data structures (rpds)"
 optional = false
 python-versions = ">=3.8"
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+    {file = "scikit_learn-1.5.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1bd8d3a19d4bd6dc5a7d4f358c8c3a60934dc058f363c34c0ac1e9e12a31421d"},
+    {file = "scikit_learn-1.5.1-cp39-cp39-win_amd64.whl", hash = "sha256:5f57428de0c900a98389c4a433d4a3cf89de979b3aa24d1c1d251802aa15e44d"},
+    {file = "scikit_learn-1.5.1.tar.gz", hash = "sha256:0ea5d40c0e3951df445721927448755d3fe1d80833b0b7308ebff5d2a45e6414"},
 ]
 
 [package.dependencies]
@@ -5230,8 +5236,8 @@ threadpoolctl = ">=3.1.0"
 
 [package.extras]
 benchmark = ["matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "pandas (>=1.1.5)"]
-build = ["cython (>=3.0.10)", "meson-python (>=0.15.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)"]
-docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "polars (>=0.20.23)", "pooch (>=1.6.0)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)", "sphinx (>=6.0.0)", "sphinx-copybutton (>=0.5.2)", "sphinx-gallery (>=0.15.0)", "sphinx-prompt (>=1.3.0)", "sphinxext-opengraph (>=0.4.2)"]
+build = ["cython (>=3.0.10)", "meson-python (>=0.16.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)"]
+docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "polars (>=0.20.23)", "pooch (>=1.6.0)", "pydata-sphinx-theme (>=0.15.3)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)", "sphinx (>=7.3.7)", "sphinx-copybutton (>=0.5.2)", "sphinx-design (>=0.5.0)", "sphinx-gallery (>=0.16.0)", "sphinx-prompt (>=1.4.0)", "sphinx-remove-toctrees (>=1.0.0.post1)", "sphinxcontrib-sass (>=0.3.4)", "sphinxext-opengraph (>=0.9.1)"]
 examples = ["matplotlib (>=3.3.4)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "pooch (>=1.6.0)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)"]
 install = ["joblib (>=1.2.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)", "threadpoolctl (>=3.1.0)"]
 maintenance = ["conda-lock (==2.5.6)"]
@@ -5318,13 +5324,13 @@ win32 = ["pywin32"]
 
 [[package]]
 name = "setuptools"
-version = "70.2.0"
+version = "70.3.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "setuptools-70.2.0-py3-none-any.whl", hash = "sha256:b8b8060bb426838fbe942479c90296ce976249451118ef566a5a0b7d8b78fb05"},
-    {file = "setuptools-70.2.0.tar.gz", hash = "sha256:bd63e505105011b25c3c11f753f7e3b8465ea739efddaccef8f0efac2137bac1"},
+    {file = "setuptools-70.3.0-py3-none-any.whl", hash = "sha256:fe384da74336c398e0d956d1cae0669bc02eed936cdb1d49b57de1990dc11ffc"},
+    {file = "setuptools-70.3.0.tar.gz", hash = "sha256:f171bab1dfbc86b132997f26a119f6056a57950d058587841a0082e8830f9dc5"},
 ]
 
 [package.extras]
@@ -5562,13 +5568,13 @@ notebook = ["ipywidgets (>=7.0.0)"]
 
 [[package]]
 name = "tenacity"
-version = "8.4.2"
+version = "8.5.0"
 description = "Retry code until it succeeds"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tenacity-8.4.2-py3-none-any.whl", hash = "sha256:9e6f7cf7da729125c7437222f8a522279751cdfbe6b67bfe64f75d3a348661b2"},
-    {file = "tenacity-8.4.2.tar.gz", hash = "sha256:cd80a53a79336edba8489e767f729e4f391c896956b57140b5d7511a64bbd3ef"},
+    {file = "tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687"},
+    {file = "tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78"},
 ]
 
 [package.extras]