scaffold for bvh -> workflow job

crates/_types/enums/src/by_table/generic_inference_jobs/inference_category.rs

@@ -41,6 +41,10 @@ pub enum InferenceCategory {
   /// A job that turns "FBX" game engine files into "GLTF" files (Bevy-compatible).
   #[serde(rename = "convert_fbx_gltf")]
   ConvertFbxToGltf,
+
+
+  #[serde(rename = "convert_bvh_to_workflow")]
+  ConvertBvhToWorkflow,
 }
 
 // TODO(bt, 2022-12-21): This desperately needs MySQL integration tests!
@@ -59,6 +63,7 @@ impl InferenceCategory {
       Self::Mocap => "mocap",
       Self::Workflow => "workflow",
       Self::ConvertFbxToGltf => "convert_fbx_gltf",
+      Self::ConvertBvhToWorkflow => "convert_bvh_to_workflow",
     }
   }
 
@@ -72,6 +77,7 @@ impl InferenceCategory {
       "mocap" => Ok(Self::Mocap),
       "workflow" => Ok(Self::Workflow),
       "convert_fbx_gltf" => Ok(Self::ConvertFbxToGltf),
+      "convert_bvh_to_workflow" => Ok(Self::ConvertBvhToWorkflow),
       _ => Err(format!("invalid value: {:?}", value)),
     }
   }
@@ -88,6 +94,7 @@ impl InferenceCategory {
       Self::Mocap,
       Self::Workflow,
       Self::ConvertFbxToGltf,
+      Self::ConvertBvhToWorkflow,
     ])
   }
 }
@@ -110,6 +117,7 @@ mod tests {
       assert_serialization(InferenceCategory::Mocap, "mocap");
       assert_serialization(InferenceCategory::Workflow, "workflow");
       assert_serialization(InferenceCategory::ConvertFbxToGltf, "convert_fbx_gltf");
+      assert_serialization(InferenceCategory::ConvertBvhToWorkflow, "convert_bvh_to_workflow");
     }
 
     #[test]
@@ -122,6 +130,7 @@ mod tests {
       assert_eq!(InferenceCategory::Mocap.to_str(), "mocap");
       assert_eq!(InferenceCategory::Workflow.to_str(), "workflow");
       assert_eq!(InferenceCategory::ConvertFbxToGltf.to_str(), "convert_fbx_gltf");
+      assert_eq!(InferenceCategory::ConvertBvhToWorkflow.to_str(), "convert_bvh_to_workflow");
     }
 
     #[test]
@@ -134,6 +143,7 @@ mod tests {
       assert_eq!(InferenceCategory::from_str("mocap").unwrap(), InferenceCategory::Mocap);
       assert_eq!(InferenceCategory::from_str("workflow").unwrap(), InferenceCategory::Workflow);
       assert_eq!(InferenceCategory::from_str("convert_fbx_gltf").unwrap(), InferenceCategory::ConvertFbxToGltf);
+      assert_eq!(InferenceCategory::from_str("convert_bvh_to_workflow").unwrap(), InferenceCategory::ConvertBvhToWorkflow);
     }
 
     #[test]
@@ -149,6 +159,7 @@ mod tests {
       assert_eq!(variants.pop_first(), Some(InferenceCategory::Mocap));
       assert_eq!(variants.pop_first(), Some(InferenceCategory::Workflow));
       assert_eq!(variants.pop_first(), Some(InferenceCategory::ConvertFbxToGltf));
+      assert_eq!(variants.pop_first(), Some(InferenceCategory::ConvertBvhToWorkflow));
       assert_eq!(variants.pop_first(), None);
 
       // Generated check

crates/_types/enums/src/by_table/generic_inference_jobs/inference_model_type.rs

@@ -41,6 +41,8 @@ pub enum InferenceModelType {
   ComfyUi,
   #[serde(rename = "styletts2")]
   StyleTTS2,
+  #[serde(rename = "bvh_to_workflow")]
+  BvhToWorkflow
 }
 
 // TODO(bt, 2022-12-21): This desperately needs MySQL integration tests!
@@ -62,6 +64,7 @@ impl InferenceModelType {
       Self::MocapNet => "mocap_net",
       Self::StyleTTS2 => "styletts2",
       Self::ComfyUi => "comfy_ui",
+      Self::BvhToWorkflow => "bvh_to_workflow",
     }
   }
 
@@ -78,6 +81,7 @@ impl InferenceModelType {
       "mocap_net" => Ok(Self::MocapNet),
       "styletts2" => Ok(Self::StyleTTS2),
       "comfy_ui" => Ok(Self::ComfyUi),
+      "bvh_to_workflow" => Ok(Self::BvhToWorkflow),
       _ => Err(format!("invalid value: {:?}", value)),
     }
   }
@@ -97,6 +101,7 @@ impl InferenceModelType {
       InferenceModelType::MocapNet,
       InferenceModelType::StyleTTS2,
       InferenceModelType::ComfyUi,
+      InferenceModelType::BvhToWorkflow,
     ])
   }
 }
@@ -122,6 +127,7 @@ mod tests {
       assert_serialization(InferenceModelType::MocapNet, "mocap_net");
       assert_serialization(InferenceModelType::ComfyUi, "comfy_ui");
       assert_serialization(InferenceModelType::StyleTTS2, "styletts2");
+      assert_serialization(InferenceModelType::BvhToWorkflow, "bvh_to_workflow");
     }
 
     #[test]
@@ -137,6 +143,7 @@ mod tests {
       assert_eq!(InferenceModelType::MocapNet.to_str(), "mocap_net");
       assert_eq!(InferenceModelType::StyleTTS2.to_str(), "styletts2");
       assert_eq!(InferenceModelType::ComfyUi.to_str(), "comfy_ui");
+      assert_eq!(InferenceModelType::BvhToWorkflow.to_str(), "bvh_to_workflow");
     }
 
     #[test]
@@ -152,13 +159,14 @@ mod tests {
       assert_eq!(InferenceModelType::from_str("mocap_net").unwrap(), InferenceModelType::MocapNet);
       assert_eq!(InferenceModelType::from_str("styletts2").unwrap(), InferenceModelType::StyleTTS2);
       assert_eq!(InferenceModelType::from_str("comfy_ui").unwrap(), InferenceModelType::ComfyUi);
+      assert_eq!(InferenceModelType::from_str("bvh_to_workflow").unwrap(), InferenceModelType::BvhToWorkflow);
     }
 
     #[test]
     fn all_variants() {
       // Static check
       let mut variants = InferenceModelType::all_variants();
-      assert_eq!(variants.len(), 11);
+      assert_eq!(variants.len(), 12);
       assert_eq!(variants.pop_first(), Some(InferenceModelType::RvcV2));
       assert_eq!(variants.pop_first(), Some(InferenceModelType::SadTalker));
       assert_eq!(variants.pop_first(), Some(InferenceModelType::SoVitsSvc));
@@ -170,6 +178,7 @@ mod tests {
       assert_eq!(variants.pop_first(), Some(InferenceModelType::MocapNet));
       assert_eq!(variants.pop_first(), Some(InferenceModelType::ComfyUi));
       assert_eq!(variants.pop_first(), Some(InferenceModelType::StyleTTS2));
+      assert_eq!(variants.pop_first(), Some(InferenceModelType::BvhToWorkflow));
       assert_eq!(variants.pop_first(), None);
 
       // Generated check

crates/lib/mysql_queries/src/payloads/generic_inference_args/generic_inference_args.rs

@@ -58,6 +58,10 @@ pub enum InferenceCategoryAbbreviated {
   #[serde(rename = "fg")] // NB: DO NOT CHANGE. It could break live jobs. Renamed to be fewer bytes.
   #[serde(alias = "convert_fbx_gltf")]
   ConvertFbxToGltf,
+
+  #[serde(rename = "bw")] // NB: DO NOT CHANGE. It could break live jobs. Renamed to be fewer bytes.
+  #[serde(alias = "convert_bvh_to_workflow")]
+  ConvertBvhToWorkflow,
 }
 
 #[derive(Serialize, Deserialize, Clone, Copy, Debug)]
@@ -143,6 +147,7 @@ impl InferenceCategoryAbbreviated {
       InferenceCategory::Mocap => Self::Mocap,
       InferenceCategory::Workflow => Self::Workflow,
       InferenceCategory::ConvertFbxToGltf => Self::ConvertFbxToGltf,
+      InferenceCategory::ConvertBvhToWorkflow => Self::ConvertBvhToWorkflow,
     }
   }
 
@@ -156,6 +161,7 @@ impl InferenceCategoryAbbreviated {
       Self::Mocap => InferenceCategory::Mocap,
       Self::Workflow => InferenceCategory::Workflow,
       Self::ConvertFbxToGltf => InferenceCategory::ConvertFbxToGltf,
+      Self::ConvertBvhToWorkflow => InferenceCategory::ConvertBvhToWorkflow,
     }
   }
 }

crates/lib/mysql_queries/src/queries/generic_inference/web/get_inference_job_status.rs

@@ -183,6 +183,7 @@ fn raw_record_to_public_result(record: RawGenericInferenceJobStatus) -> GenericI
     InferenceCategory::Mocap => Some("Mocap"),
     InferenceCategory::Workflow => Some("Workflow"),
     InferenceCategory::ConvertFbxToGltf => Some("FBX to GLTF"),
+    InferenceCategory::ConvertBvhToWorkflow => Some("BVH to Workflow"),
   };
 
   // NB: A bit of a hack. We store TTS results with a full path.
@@ -196,6 +197,7 @@ fn raw_record_to_public_result(record: RawGenericInferenceJobStatus) -> GenericI
     InferenceCategory::Mocap => (true, record.maybe_media_file_public_bucket_directory_hash.as_deref()),
     InferenceCategory::Workflow => (true, record.maybe_media_file_public_bucket_directory_hash.as_deref()),
     InferenceCategory::ConvertFbxToGltf => (true, record.maybe_media_file_public_bucket_directory_hash.as_deref()),
+    InferenceCategory::ConvertBvhToWorkflow => (true, record.maybe_media_file_public_bucket_directory_hash.as_deref()),
   };
 
   // NB: We've moved voice conversion out of their own table and into media_files

crates/service/job/inference_job/src/job/job_loop/process_single_job.rs

@@ -13,6 +13,7 @@ use redis_common::redis_keys::RedisKeys;
 use crate::job::job_loop::determine_dependency_status::determine_dependency_status;
 use crate::job::job_loop::process_single_job_error::ProcessSingleJobError;
 use crate::job::job_loop::process_single_job_success_case::ProcessSingleJobSuccessCase;
+use crate::job::job_types::bevy_to_workflow::process_single_bevy_to_workflow_conversion_job::process_single_bevy_to_workflow_conversion_job;
 use crate::job::job_types::format_conversion::process_single_format_conversion_job::{FormatConversionType, process_single_format_conversion_job};
 use crate::job::job_types::image_generation::process_single_ig_job::process_single_ig_job;
 use crate::job::job_types::lipsync::process_single_lipsync_job::process_single_lipsync_job;
@@ -202,6 +203,9 @@ async fn do_process_single_job(
     InferenceCategory::ConvertFbxToGltf => {
       process_single_format_conversion_job(job_dependencies, job, FormatConversionType::FbxToGltf).await?
     }
+    InferenceCategory::ConvertBvhToWorkflow => {
+      process_single_bevy_to_workflow_conversion_job(job_dependencies, job).await?
+    }
   };
 
   let maybe_entity_type = job_success_result.maybe_result_entity

crates/service/job/inference_job/src/job/job_types/bevy_to_workflow/bvh_to_workflow/mod.rs

@@ -0,0 +1 @@
+pub mod process_job;

crates/service/job/inference_job/src/job/job_types/bevy_to_workflow/bvh_to_workflow/process_job.rs

@@ -0,0 +1,318 @@
+use std::time::Instant;
+
+use anyhow::anyhow;
+use log::info;
+
+use buckets::public::media_uploads::bucket_file_path::MediaUploadOriginalFilePath;
+use mysql_queries::queries::generic_inference::job::list_available_generic_inference_jobs::AvailableInferenceJob;
+use mysql_queries::queries::media_files::get_media_file_for_inference::MediaFileForInference;
+
+use crate::job::job_loop::job_success_result::JobSuccessResult;
+use crate::job::job_loop::process_single_job_error::ProcessSingleJobError;
+use crate::job_dependencies::JobDependencies;
+use crate::util::maybe_download_file_from_bucket::{maybe_download_file_from_bucket, MaybeDownloadArgs};
+
+const BUCKET_FILE_EXTENSION : &str = ".gltf";
+
+pub struct BvhToWorkflowJobArgs<'a> {
+  pub job_dependencies: &'a JobDependencies,
+  pub job: &'a AvailableInferenceJob,
+  pub media_file: &'a MediaFileForInference,
+}
+
+pub async fn process_job(args: BvhToWorkflowJobArgs<'_>) -> Result<JobSuccessResult, ProcessSingleJobError> {
+  let job = args.job;
+  let media_file = args.media_file;
+
+  let mut job_progress_reporter = args.job_dependencies
+      .clients
+      .job_progress_reporter
+      .new_generic_inference(job.inference_job_token.as_str())
+      .map_err(|e| ProcessSingleJobError::Other(anyhow!(e)))?;
+
+  // ==================== TEMP DIR ==================== //
+
+  let work_temp_dir = format!("temp_file_convert_{}", job.id.0);
+
+  // NB: TempDir exists until it goes out of scope, at which point it should delete from filesystem.
+  let work_temp_dir = args.job_dependencies
+      .fs
+      .scoped_temp_dir_creator_for_work
+      .new_tempdir(&work_temp_dir)
+      .map_err(|e| ProcessSingleJobError::from_io_error(e))?;
+
+  // ==================== DOWNLOAD MEDIA FILE ==================== //
+
+  info!("Download media for conversion...");
+
+  //TODO(KS): update to match correct paths & extensions
+  let original_media_upload_fs_path = {
+    let original_media_upload_fs_path = work_temp_dir.path().join("original.fbx");
+
+    let media_upload_bucket_path =
+        MediaUploadOriginalFilePath::from_object_hash(&media_file.public_bucket_directory_hash);
+
+    let bucket_object_path = media_upload_bucket_path.to_full_object_pathbuf();
+
+    info!("Downloading media to bucket path: {:?}", &bucket_object_path);
+
+    maybe_download_file_from_bucket(MaybeDownloadArgs {
+      name_or_description_of_file: "media upload (original file)",
+      final_filesystem_file_path: &original_media_upload_fs_path,
+      bucket_object_path: &bucket_object_path,
+      bucket_client: &args.job_dependencies.buckets.public_bucket_client,
+      job_progress_reporter: &mut job_progress_reporter,
+      job_progress_update_description: "downloading",
+      job_id: job.id.0,
+      scoped_tempdir_creator: &args.job_dependencies.fs.scoped_temp_dir_creator_for_work,
+      maybe_existing_file_minimum_size_required: None,
+    }).await?;
+
+    original_media_upload_fs_path
+  };
+
+  // TODO: No duration. Replace this.
+  let inference_duration = Instant::now().duration_since(Instant::now());
+
+  /* // TODO
+
+  // ==================== SETUP FOR CONVERSION ==================== //
+
+  job_progress_reporter.log_status("running conversion")
+      .map_err(|e| ProcessSingleJobError::Other(e))?;
+
+  //let config_path = PathBuf::from("/models/voice_conversion/so-vits-svc/example_config.json"); // TODO: This could be variable.
+  let input_wav_path = original_media_upload_fs_path;
+
+  let output_audio_fs_path = work_temp_dir.path().join("output.wav");
+
+  let stderr_output_file = work_temp_dir.path().join("stderr.txt");
+
+  info!("Running VC inference...");
+
+  info!("Expected output audio filename: {:?}", &output_audio_fs_path);
+
+  // TODO: Limit output length for premium.
+
+  let maybe_args = job.maybe_inference_args
+      .as_ref()
+      .map(|args| args.args.as_ref())
+      .flatten();
+
+  // If not specified by the user, turn off auto prediction. It sounds awful.
+  let auto_predict_f0 = maybe_args
+      .map(|args| match args {
+        PolymorphicInferenceArgs::Tts { .. } => None,
+        PolymorphicInferenceArgs::La(_) => None,
+        PolymorphicInferenceArgs::Vc { auto_predict_f0, .. } => *auto_predict_f0,
+        PolymorphicInferenceArgs::Rr(_) => None,
+        PolymorphicInferenceArgs::Ig(_) => None,
+        PolymorphicInferenceArgs::Mc(_) => None,
+        PolymorphicInferenceArgs::Cu(_) => None,
+      })
+      .flatten()
+      .unwrap_or(false);
+
+  let maybe_transpose = maybe_args
+      .map(|args| match args {
+        PolymorphicInferenceArgs::Tts { .. } => None,
+        PolymorphicInferenceArgs::La(_) => None,
+        PolymorphicInferenceArgs::Vc { transpose, .. } => *transpose,
+        PolymorphicInferenceArgs::Rr(_) => None,
+        PolymorphicInferenceArgs::Ig(_) => None,
+        PolymorphicInferenceArgs::Mc(_) => None,
+        PolymorphicInferenceArgs::Cu(_) => None,
+      })
+      .flatten();
+
+  // ==================== RUN INFERENCE SCRIPT ==================== //
+
+  let inference_start_time = Instant::now();
+
+  let command_exit_status = model_dependencies
+      .inference_command
+      .execute_inference(InferenceArgs {
+        model_path: &so_vits_svc_fs_path,
+        input_path: &input_wav_path,
+        output_path: &output_audio_fs_path,
+        stderr_output_file: &stderr_output_file,
+        maybe_config_path: None,
+        device: Device::Cuda,
+        auto_predict_f0,
+        maybe_transpose,
+      });
+
+  let inference_duration = Instant::now().duration_since(inference_start_time);
+
+  info!("Inference took duration to complete: {:?}", &inference_duration);
+
+  if !command_exit_status.is_success() {
+    error!("Inference failed: {:?}", command_exit_status);
+
+    let error = ProcessSingleJobError::Other(anyhow!("CommandExitStatus: {:?}", command_exit_status));
+
+    if let Ok(contents) = read_to_string(&stderr_output_file) {
+      warn!("Captured stderr output: {}", contents);
+
+      //match categorize_error(&contents)  {
+      //  Some(ProcessSingleJobError::FaceDetectionFailure) => {
+      //    warn!("Face not detected in source image");
+      //    error = ProcessSingleJobError::FaceDetectionFailure;
+      //  }
+      //  _ => {}
+      //}
+    }
+
+    safe_delete_temp_file(&input_wav_path);
+    safe_delete_temp_file(&output_audio_fs_path);
+    safe_delete_temp_directory(&work_temp_dir);
+
+    return Err(error);
+  }
+
+  // ==================== CHECK ALL FILES EXIST AND GET METADATA ==================== //
+
+  info!("Checking that output files exist...");
+
+  check_file_exists(&output_audio_fs_path).map_err(|e| ProcessSingleJobError::Other(e))?;
+
+  info!("Interrogating result file properties...");
+
+  let file_size_bytes = file_size(&output_audio_fs_path)
+      .map_err(|err| ProcessSingleJobError::Other(err))?;
+
+  let maybe_mimetype = get_mimetype_for_file(&output_audio_fs_path)
+      .map_err(|err| ProcessSingleJobError::from_io_error(err))?
+      .map(|mime| mime.to_string());
+
+  let audio_info = decode_basic_audio_file_info(&output_audio_fs_path, maybe_mimetype.as_deref(), None)
+      .map_err(|err| ProcessSingleJobError::Other(err))?;
+
+  if audio_info.required_full_decode {
+    warn!("Required a full decode of the output data to get duration! That's inefficient!");
+  }
+
+  info!("Calculating sha256...");
+
+  let file_checksum = sha256_hash_file(&output_audio_fs_path)
+      .map_err(|err| {
+        ProcessSingleJobError::Other(anyhow!("Error hashing file: {:?}", err))
+      })?;
+
+  let file_metadata = FileMetadata {
+    duration_millis: audio_info.duration_millis,
+    mimetype: maybe_mimetype.clone(),
+    file_size_bytes,
+  };
+
+  // ==================== UPLOAD AUDIO TO BUCKET ==================== //
+
+  job_progress_reporter.log_status("uploading result")
+      .map_err(|e| ProcessSingleJobError::Other(e))?;
+
+//  let result_bucket_location = VoiceConversionResultOriginalFilePath::generate_new();
+//
+//  let result_bucket_object_pathbuf = result_bucket_location.to_full_object_pathbuf();
+//
+//  info!("Audio destination bucket path: {:?}", &result_bucket_object_pathbuf);
+
+  let result_bucket_location = MediaFileBucketPath::generate_new(
+    Some(BUCKET_FILE_PREFIX),
+    Some(BUCKET_FILE_EXTENSION));
+
+  let result_bucket_object_pathbuf = result_bucket_location.to_full_object_pathbuf();
+
+  info!("Audio destination bucket path: {:?}", &result_bucket_object_pathbuf);
+
+  info!("Uploading audio media file...");
+
+  args.job_dependencies.buckets.public_bucket_client.upload_filename_with_content_type(
+    &result_bucket_object_pathbuf,
+    &output_audio_fs_path,
+    "audio/wav")
+      .await
+      .map_err(|e| ProcessSingleJobError::Other(e))?;
+
+  safe_delete_temp_file(&output_audio_fs_path);
+
+  // ==================== DELETE DOWNLOADED FILE ==================== //
+
+  // NB: We should be using a tempdir, but to make absolutely certain we don't overflow the disk...
+  safe_delete_temp_directory(&work_temp_dir);
+
+  // ==================== SAVE RECORDS ==================== //
+
+  info!("Saving vc inference record...");
+
+//  let (inference_result_token, id) = insert_voice_conversion_result(InsertArgs {
+//    pool: &args.job_dependencies.mysql_pool,
+//    job: &job,
+//    public_bucket_hash: result_bucket_location.get_object_hash(),
+//    file_size_bytes: file_metadata.file_size_bytes,
+//    duration_millis: file_metadata.duration_millis.unwrap_or(0),
+//    is_on_prem: args.job_dependencies.container.is_on_prem,
+//    worker_hostname: &args.job_dependencies.container.hostname,
+//    worker_cluster: &args.job_dependencies.container.cluster_name,
+//    is_debug_worker: args.job_dependencies.worker_details.is_debug_worker
+//  })
+//      .await
+//      .map_err(|e| ProcessSingleJobError::Other(e))?;
+
+  let (inference_result_token, id) = insert_media_file_from_voice_conversion(InsertMediaFileArgs {
+    pool: &args.job_dependencies.db.mysql_pool,
+    job: &job,
+    voice_conversion_type: VoiceConversionModelType::SoVitsSvc,
+    maybe_mime_type: maybe_mimetype.as_deref(),
+    file_size_bytes: file_metadata.file_size_bytes,
+    duration_millis: file_metadata.duration_millis.unwrap_or(0),
+    sha256_checksum: &file_checksum,
+    public_bucket_directory_hash: result_bucket_location.get_object_hash(),
+    maybe_public_bucket_prefix: Some(BUCKET_FILE_PREFIX),
+    maybe_public_bucket_extension: Some(BUCKET_FILE_EXTENSION),
+    is_on_prem: args.job_dependencies.job.info.container.is_on_prem,
+    worker_hostname: &args.job_dependencies.job.info.container.hostname,
+    worker_cluster: &args.job_dependencies.job.info.container.cluster_name,
+  })
+      .await
+      .map_err(|e| ProcessSingleJobError::Other(e))?;
+
+  info!("VC Done.");
+
+  // TODO: Update upstream to be strongly typed
+  let maybe_user_token = job.maybe_creator_user_token.as_deref()
+      .map(|token| UserToken::new_from_str(token));
+
+  args.job_dependencies.clients.firehose_publisher.vc_inference_finished(
+    maybe_user_token.as_ref(),
+    &job.inference_job_token,
+    inference_result_token.as_str())
+      .await
+      .map_err(|e| {
+        error!("error publishing event: {:?}", e);
+        ProcessSingleJobError::Other(anyhow!("error publishing event"))
+      })?;
+
+  job_progress_reporter.log_status("done")
+      .map_err(|e| ProcessSingleJobError::Other(e))?;
+
+  info!("Job {:?} complete success! Downloaded, ran inference, and uploaded. Saved model record: {}, Result Token: {}",
+        job.id, id, &inference_result_token);
+
+   */
+
+  Ok(JobSuccessResult {
+    //maybe_result_entity: Some(ResultEntity {
+    //  entity_type: InferenceResultType::MediaFile,
+    //  entity_token: inference_result_token.to_string(),
+    //}),
+    maybe_result_entity: None,
+    inference_duration,
+  })
+}
+
+#[derive(Deserialize, Default)]
+struct FileMetadata {
+  pub duration_millis: Option<u64>,
+  pub mimetype: Option<String>,
+  pub file_size_bytes: u64,
+}

crates/service/job/inference_job/src/job/job_types/bevy_to_workflow/mod.rs

@@ -0,0 +1,2 @@
+pub mod bvh_to_workflow;
+pub mod process_single_bevy_to_workflow_conversion_job;

crates/service/job/inference_job/src/job/job_types/bevy_to_workflow/process_single_bevy_to_workflow_conversion_job.rs

@@ -0,0 +1,50 @@
+use anyhow::anyhow;
+use log::error;
+
+use mysql_queries::queries::generic_inference::job::list_available_generic_inference_jobs::AvailableInferenceJob;
+use mysql_queries::queries::media_files::get_media_file_for_inference::get_media_file_for_inference;
+use tokens::tokens::media_files::MediaFileToken;
+
+use crate::job::job_loop::job_success_result::JobSuccessResult;
+use crate::job::job_loop::process_single_job_error::ProcessSingleJobError;
+use crate::job::job_types::bevy_to_workflow::bvh_to_workflow;
+use crate::job::job_types::bevy_to_workflow::bvh_to_workflow::process_job::BvhToWorkflowJobArgs;
+use crate::job_dependencies::JobDependencies;
+
+
+pub async fn process_single_bevy_to_workflow_conversion_job(job_dependencies: &JobDependencies, job: &AvailableInferenceJob) -> Result<JobSuccessResult, ProcessSingleJobError> {
+
+  let maybe_media_file_token = job.maybe_input_source_token
+      .as_deref()
+      .map(|token| MediaFileToken::new_from_str(token));
+
+  let media_file_token = match maybe_media_file_token {
+    None => return Err(ProcessSingleJobError::Other(anyhow!("no associated media file for format conversion job: {:?}", job.inference_job_token))),
+    Some(token) => token,
+  };
+
+  let maybe_media_file_result =
+      get_media_file_for_inference(&media_file_token, &job_dependencies.db.mysql_pool).await;
+
+  let media_file = match maybe_media_file_result {
+    Ok(Some(media_file)) => media_file,
+    Ok(None) => {
+      error!("no media file record found for token: {:?}", media_file_token);
+      return Err(ProcessSingleJobError::Other(anyhow!("no media file record found for token: {:?}", media_file_token)));
+    }
+    Err(err) => {
+      error!("error fetching media file record from db: {:?}", err);
+      return Err(ProcessSingleJobError::Other(err));
+    }
+  };
+
+  let job_success_result = bvh_to_workflow::process_job::process_job(BvhToWorkflowJobArgs {
+        job_dependencies,
+        job,
+        media_file: &media_file,
+      }).await?;
+
+  Ok(job_success_result)
+}
+
+

crates/service/job/inference_job/src/job/job_types/mod.rs

@@ -6,3 +6,4 @@ pub mod image_generation;
 pub(crate) mod mocap;
 pub(crate) mod workflow;
 pub mod format_conversion;
+pub mod bevy_to_workflow;