Merge remote-tracking branch 'origin/main' into 001-agentic-ai-corrector

Author: beveradb

.github/workflows/test-and-publish.yml

@@ -17,7 +17,18 @@ jobs:
 
     steps:
       - uses: actions/checkout@v3
-      
+
+      - name: Free Disk Space
+        uses: jlumbroso/free-disk-space@main
+        with:
+          tool-cache: false
+          android: true
+          dotnet: false
+          haskell: false
+          large-packages: false
+          docker-images: false
+          swap-storage: false
+
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v4
         with:

lyrics_transcriber/transcribers/audioshake.py

@@ -14,9 +14,9 @@ class AudioShakeConfig:
     """Configuration for AudioShake transcription service."""
 
     api_token: Optional[str] = None
-    base_url: str = "https://groovy.audioshake.ai"
+    base_url: str = "https://api.audioshake.ai"
     output_prefix: Optional[str] = None
-    timeout_minutes: int = 10  # Added timeout configuration
+    timeout_minutes: int = 20  # Added timeout configuration
 
 
 class AudioShakeAPI:
@@ -34,46 +34,52 @@ def _validate_config(self) -> None:
     def _get_headers(self) -> Dict[str, str]:
         """Get headers for API requests."""
         self._validate_config()  # Validate before making any API calls
-        return {"Authorization": f"Bearer {self.config.api_token}", "Content-Type": "application/json"}
+        return {"x-api-key": self.config.api_token, "Content-Type": "application/json"}
 
     def upload_file(self, filepath: str) -> str:
-        """Upload audio file and return asset ID."""
+        """Upload audio file and return file URL."""
         self.logger.info(f"Uploading {filepath} to AudioShake")
         self._validate_config()  # Validate before making API call
 
         url = f"{self.config.base_url}/upload/"
         with open(filepath, "rb") as file:
             files = {"file": (os.path.basename(filepath), file)}
-            response = requests.post(url, headers={"Authorization": self._get_headers()["Authorization"]}, files=files)
+            response = requests.post(url, headers={"x-api-key": self.config.api_token}, files=files)
 
         self.logger.debug(f"Upload response: {response.status_code} - {response.text}")
         response.raise_for_status()
-        return response.json()["id"]
+        return response.json()["link"]
 
-    def create_job(self, asset_id: str) -> str:
-        """Create transcription job and return job ID."""
-        self.logger.info(f"Creating job for asset {asset_id}")
+    def create_task(self, file_url: str) -> str:
+        """Create transcription task and return task ID."""
+        self.logger.info(f"Creating task for file {file_url}")
 
-        url = f"{self.config.base_url}/job/"
+        url = f"{self.config.base_url}/tasks"
         data = {
-            "metadata": {"format": "json", "name": "alignment", "language": "en"},
-            "callbackUrl": "https://example.com/webhook/alignment",
-            "assetId": asset_id,
+            "url": file_url,
+            "targets": [
+                {
+                    "model": "alignment",
+                    "formats": ["json"],
+                    "language": "en"
+                }
+            ],
         }
         response = requests.post(url, headers=self._get_headers(), json=data)
         response.raise_for_status()
-        return response.json()["job"]["id"]
+        return response.json()["id"]
 
-    def wait_for_job_result(self, job_id: str) -> Dict[str, Any]:
-        """Poll for job completion and return results."""
-        self.logger.info(f"Getting job result for job {job_id}")
+    def wait_for_task_result(self, task_id: str) -> Dict[str, Any]:
+        """Poll for task completion and return results."""
+        self.logger.info(f"Getting task result for task {task_id}")
 
-        url = f"{self.config.base_url}/job/{job_id}"
+        # Use the list endpoint which has fresh data, not the individual task endpoint which caches
+        url = f"{self.config.base_url}/tasks"
         start_time = time.time()
         last_status_log = start_time
         timeout_seconds = self.config.timeout_minutes * 60
 
-        # Add initial retry logic for 404 errors (job ID not yet available)
+        # Add initial retry logic for when task is not found yet
         initial_retry_count = 0
         max_initial_retries = 5
         initial_retry_delay = 2  # seconds
@@ -94,28 +100,57 @@ def wait_for_job_result(self, job_id: str) -> Dict[str, Any]:
             try:
                 response = requests.get(url, headers=self._get_headers())
                 response.raise_for_status()
-                job_data = response.json()["job"]
+                tasks_list = response.json()
+                
+                # Find our specific task in the list
+                task_data = None
+                for task in tasks_list:
+                    if task.get("id") == task_id:
+                        task_data = task
+                        break
+                
+                if not task_data:
+                    # Task not found in list yet
+                    if initial_retry_count < max_initial_retries:
+                        initial_retry_count += 1
+                        self.logger.info(f"Task not found in list yet (attempt {initial_retry_count}/{max_initial_retries}), retrying in {initial_retry_delay} seconds...")
+                        time.sleep(initial_retry_delay)
+                        continue
+                    else:
+                        raise TranscriptionError(f"Task {task_id} not found in task list after {max_initial_retries} retries")
+                
+                # Log the full response for debugging
+                self.logger.debug(f"Task status response: {task_data}")
 
-                if job_data["status"] == "completed":
-                    return job_data
-                elif job_data["status"] == "failed":
-                    raise TranscriptionError(f"Job failed: {job_data.get('error', 'Unknown error')}")
+                # Check status of targets (not the task itself)
+                targets = task_data.get("targets", [])
+                if not targets:
+                    raise TranscriptionError("No targets found in task response")
+                
+                # Check if all targets are completed or if any failed
+                all_completed = True
+                for target in targets:
+                    target_status = target.get("status")
+                    target_model = target.get("model")
+                    self.logger.debug(f"Target {target_model} status: {target_status}")
+                    
+                    if target_status == "failed":
+                        error_msg = target.get("error", "Unknown error")
+                        raise TranscriptionError(f"Target {target_model} failed: {error_msg}")
+                    elif target_status != "completed":
+                        all_completed = False
+                
+                if all_completed:
+                    self.logger.info("All targets completed successfully")
+                    return task_data
 
                 # Reset retry count on successful response
                 initial_retry_count = 0
 
             except requests.exceptions.HTTPError as e:
-                if e.response.status_code == 404 and initial_retry_count < max_initial_retries:
-                    # Job ID not yet available, retry with delay
-                    initial_retry_count += 1
-                    self.logger.info(f"Job ID not yet available (attempt {initial_retry_count}/{max_initial_retries}), retrying in {initial_retry_delay} seconds...")
-                    time.sleep(initial_retry_delay)
-                    continue
-                else:
-                    # Re-raise the error if it's not a 404 or we've exceeded retries
-                    raise
+                raise
 
-            time.sleep(5)  # Wait before next poll
+            time.sleep(30)  # Wait before next poll
 
 
 class AudioShakeTranscriber(BaseTranscriber):
@@ -142,13 +177,13 @@ def _perform_transcription(self, audio_filepath: str) -> TranscriptionData:
         self.logger.info(f"Starting transcription for {audio_filepath}")
 
         try:
-            # Start job and get results
+            # Start task and get results
             self.logger.debug("Calling start_transcription()")
-            job_id = self.start_transcription(audio_filepath)
-            self.logger.debug(f"Got job_id: {job_id}")
+            task_id = self.start_transcription(audio_filepath)
+            self.logger.debug(f"Got task_id: {task_id}")
 
             self.logger.debug("Calling get_transcription_result()")
-            result = self.get_transcription_result(job_id)
+            result = self.get_transcription_result(task_id)
             self.logger.debug("Got transcription result")
 
             return result
@@ -157,46 +192,61 @@ def _perform_transcription(self, audio_filepath: str) -> TranscriptionData:
             raise
 
     def start_transcription(self, audio_filepath: str) -> str:
-        """Starts the transcription job and returns the job ID."""
+        """Starts the transcription task and returns the task ID."""
         self.logger.debug(f"Entering start_transcription() for {audio_filepath}")
 
-        # Upload file and create job
-        asset_id = self.api.upload_file(audio_filepath)
-        self.logger.debug(f"File uploaded successfully. Asset ID: {asset_id}")
+        # Upload file and create task
+        file_url = self.api.upload_file(audio_filepath)
+        self.logger.debug(f"File uploaded successfully. File URL: {file_url}")
 
-        job_id = self.api.create_job(asset_id)
-        self.logger.debug(f"Job created successfully. Job ID: {job_id}")
+        task_id = self.api.create_task(file_url)
+        self.logger.debug(f"Task created successfully. Task ID: {task_id}")
 
-        return job_id
+        return task_id
 
-    def get_transcription_result(self, job_id: str) -> Dict[str, Any]:
-        """Gets the raw results for a previously started job."""
-        self.logger.debug(f"Entering get_transcription_result() for job ID: {job_id}")
+    def get_transcription_result(self, task_id: str) -> Dict[str, Any]:
+        """Gets the raw results for a previously started task."""
+        self.logger.debug(f"Entering get_transcription_result() for task ID: {task_id}")
 
-        # Wait for job completion
-        job_data = self.api.wait_for_job_result(job_id)
-        self.logger.debug("Job completed. Getting results...")
+        # Wait for task completion
+        task_data = self.api.wait_for_task_result(task_id)
+        self.logger.debug("Task completed. Getting results...")
 
-        output_asset = next((asset for asset in job_data.get("outputAssets", []) if asset["name"] == "alignment.json"), None)
-        if not output_asset:
-            raise TranscriptionError("Required output not found in job results")
+        # Find the alignment target output
+        alignment_target = None
+        for target in task_data.get("targets", []):
+            if target.get("model") == "alignment":
+                alignment_target = target
+                break
+        
+        if not alignment_target:
+            raise TranscriptionError("Required output not found in task results")
+        
+        # Get the output file URL
+        output = alignment_target.get("output", [])
+        if not output:
+            raise TranscriptionError("No output found in alignment target")
+        
+        output_url = output[0].get("link")
+        if not output_url:
+            raise TranscriptionError("Output link not found in alignment target")
 
         # Fetch transcription data
-        response = requests.get(output_asset["link"])
+        response = requests.get(output_url)
         response.raise_for_status()
 
         # Return combined raw data
-        raw_data = {"job_data": job_data, "transcription": response.json()}
+        raw_data = {"task_data": task_data, "transcription": response.json()}
 
         self.logger.debug("Raw results retrieved successfully")
         return raw_data
 
     def _convert_result_format(self, raw_data: Dict[str, Any]) -> TranscriptionData:
         """Process raw Audioshake API response into standard format."""
-        self.logger.debug(f"Processing result for job {raw_data['job_data']['id']}")
+        self.logger.debug(f"Processing result for task {raw_data['task_data']['id']}")
 
         transcription_data = raw_data["transcription"]
-        job_data = raw_data["job_data"]
+        task_data = raw_data["task_data"]
 
         segments = []
         all_words = []  # Collect all words across segments
@@ -230,8 +280,8 @@ def _convert_result_format(self, raw_data: Dict[str, Any]) -> TranscriptionData:
             source=self.get_name(),
             metadata={
                 "language": transcription_data.get("metadata", {}).get("language"),
-                "job_id": job_data["id"],
-                "duration": job_data.get("statusInfo", {}).get("duration"),
+                "task_id": task_data["id"],
+                "duration": task_data.get("duration"),
             },
         )