feat: billing and credit management v2 (#429)

* feat: use mps generated correlation ID * chore: update pipecat submodule * feat: add credit purchase URL * feat: carve out billing page and show credit ledger * feat: deprecate dograh based quota tracking * fix: remove cost calculation from dograh codebase * fix: create mps account on migrate to v2 * chore: update pipecat
2026-06-13 08:15:21 +02:00 · 2026-06-12 14:55:30 +05:30 · 2026-06-12 14:55:30 +05:30 · 1f1149f4d5
commit 1f1149f4d5
parent 97d7103480
80 changed files with 3335 additions and 2057 deletions
--- a/api/tasks/workflow_completion.py
+++ b/api/tasks/workflow_completion.py
@ -0,0 +1,121 @@
+import os
+from typing import Optional
+
+from loguru import logger
+from pipecat.utils.run_context import set_current_run_id
+
+from api.db import db_client
+from api.services.storage import get_current_storage_backend, storage_fs
+from api.services.workflow_run_billing import (
+    report_completed_workflow_run_platform_usage,
+)
+from api.tasks.run_integrations import run_integrations_post_workflow_run
+
+
+async def process_workflow_completion(
+    _ctx,
+    workflow_run_id: int,
+    audio_temp_path: Optional[str] = None,
+    transcript_temp_path: Optional[str] = None,
+):
+    """Process workflow completion: upload artifacts and run integrations.
+
+    This task combines audio upload, transcript upload, and webhook integrations
+    into a single sequential task to ensure integrations run after uploads complete.
+
+    Args:
+        _ctx: ARQ context (unused)
+        workflow_run_id: The workflow run ID
+        audio_temp_path: Optional path to temp audio file
+        transcript_temp_path: Optional path to temp transcript file
+    """
+    run_id = str(workflow_run_id)
+    set_current_run_id(run_id)
+
+    logger.info(f"Processing workflow completion for run {workflow_run_id}")
+
+    storage_backend = get_current_storage_backend()
+
+    # Step 1: Upload audio if provided
+    if audio_temp_path:
+        try:
+            if os.path.exists(audio_temp_path):
+                file_size = os.path.getsize(audio_temp_path)
+                logger.debug(f"Audio file size: {file_size} bytes")
+
+                recording_url = f"recordings/{workflow_run_id}.wav"
+                logger.info(
+                    f"Uploading audio to {storage_backend.name} - workflow_run_id: {workflow_run_id}"
+                )
+
+                await storage_fs.aupload_file(audio_temp_path, recording_url)
+                await db_client.update_workflow_run(
+                    run_id=workflow_run_id,
+                    recording_url=recording_url,
+                    storage_backend=storage_backend.value,
+                )
+                logger.info(f"Successfully uploaded audio: {recording_url}")
+            else:
+                logger.warning(f"Audio temp file not found: {audio_temp_path}")
+        except Exception as e:
+            logger.error(f"Error uploading audio for workflow {workflow_run_id}: {e}")
+        finally:
+            if audio_temp_path and os.path.exists(audio_temp_path):
+                try:
+                    os.remove(audio_temp_path)
+                    logger.debug(f"Cleaned up temp audio file: {audio_temp_path}")
+                except Exception as e:
+                    logger.warning(f"Failed to clean up temp audio file: {e}")
+
+    # Step 2: Upload transcript if provided
+    if transcript_temp_path:
+        try:
+            if os.path.exists(transcript_temp_path):
+                file_size = os.path.getsize(transcript_temp_path)
+                logger.debug(f"Transcript file size: {file_size} bytes")
+
+                transcript_url = f"transcripts/{workflow_run_id}.txt"
+                logger.info(
+                    f"Uploading transcript to {storage_backend.name} - workflow_run_id: {workflow_run_id}"
+                )
+
+                await storage_fs.aupload_file(transcript_temp_path, transcript_url)
+                await db_client.update_workflow_run(
+                    run_id=workflow_run_id,
+                    transcript_url=transcript_url,
+                    storage_backend=storage_backend.value,
+                )
+                logger.info(f"Successfully uploaded transcript: {transcript_url}")
+            else:
+                logger.warning(
+                    f"Transcript temp file not found: {transcript_temp_path}"
+                )
+        except Exception as e:
+            logger.error(
+                f"Error uploading transcript for workflow {workflow_run_id}: {e}"
+            )
+        finally:
+            if transcript_temp_path and os.path.exists(transcript_temp_path):
+                try:
+                    os.remove(transcript_temp_path)
+                    logger.debug(
+                        f"Cleaned up temp transcript file: {transcript_temp_path}"
+                    )
+                except Exception as e:
+                    logger.warning(f"Failed to clean up temp transcript file: {e}")
+
+    # Step 3: Run integrations including QA analysis (after uploads are complete)
+    try:
+        await run_integrations_post_workflow_run(_ctx, workflow_run_id)
+    except Exception as e:
+        logger.error(f"Error running integrations for workflow {workflow_run_id}: {e}")
+
+    # Step 4: Notify MPS after completion. MPS owns credit accounting.
+    try:
+        await report_completed_workflow_run_platform_usage(workflow_run_id)
+    except Exception as e:
+        logger.error(
+            f"Error reporting platform usage for workflow {workflow_run_id}: {e}"
+        )
+
+    logger.info(f"Completed workflow completion processing for run {workflow_run_id}")