Compare commits

..
Author SHA1 Message Date
bflatastic 50a1d3801f copy paste bug fixes 2025-08-08 20:27:57 +07:00
Brandon Thomas 0d67b81f5f mark intermediate files 2025-08-08 01:59:24 -04:00
Brandon Thomas 24addb0a49 track seconds elapsed since server startup 2025-08-08 01:26:40 -04:00
Brandon Thomas 041cfc5460 background removal with event plumbing (#755) 2025-08-08 01:07:56 -04:00
Brandon Thomas 693b8c36be cleanup 2025-08-03 17:03:06 -04:00
Brandon Thomas 8c2e37cad7 wire up flux inpainting (#753) 2025-08-03 16:16:50 -04:00
Tanish Manku 5a30046efa Implement all inpainting UI (#752)
Actual backend integration pending
2025-08-01 16:40:48 -07:00
Tanish Manku 2d9773100e 3D: Do only one render pass to consume less memory (#699) 2025-08-01 16:32:05 -07:00
Tanish Manku 1ad16c1d87 3D cache only on editor load (#694) 2025-08-01 16:31:57 -07:00
bflatastic a531448611 modal/popover conflict fix - using radix dialog instead 2025-08-01 13:05:05 +07:00
Brandon Thomas dba5b095c4 flux inpaint + kontext in tauri, kontext end-to-end in UI (#751) 2025-07-31 20:45:31 -04:00
Brandon Thomas d4323da8de nearly end-to-end Flux Kontext and Flux Inpainting (#750) 2025-07-31 15:46:04 -04:00
bflatastic 7eb2a3cdba reposition outliner above model selector 2025-07-31 20:47:17 +07:00
BFlatandBrandon Thomas 708930dfb4 number of generation dropdown for text to image prompt box (#748)
Co-authored-by: Brandon Thomas <echelon@gmail.com>
2025-07-29 21:15:10 -04:00
Brandon Thomas 4f0916edb7 enqueue multiple images (#749) 2025-07-29 20:14:10 -04:00
bflatastic c36e88d8ce expandable lightbox to fullscreen 2025-07-29 20:11:04 +07:00
Brandon Thomas 233f60acf6 stop double alerting on events 2025-07-28 22:50:02 -04:00
Brandon Thomas a3e16e491a unlikely we'll need old frontend configuration "editor2d_studio_OAI" 2025-07-28 20:04:27 -04:00
Brandon Thomas 3d521fec79 roll forward with new build (07.28) 2025-07-28 10:16:14 -04:00
BFlat 6c8979123f 3d: fixed saving and new scene (#747) 2025-07-28 14:12:56 +07:00
BFlat 8d4edcfafd lightbox context images, generation details, canvas snapshot bug fix (#746)
- canvas snapshot aspect ratio is fixed (it was snapshotting only as
squared images)
- added reference/context images in the lightbox under prompt, hovering
shows a larger preview
- added generation details: model used with logo and provider
2025-07-28 13:28:17 +07:00
Brandon Thomas b53e138dab include prompt details in api docs 2025-07-26 19:10:48 -04:00
Brandon Thomas dc1b038ffa only serve image references for prompts (future proofing) 2025-07-26 18:59:08 -04:00
Brandon Thomas 418a9f92c0 insert prompt images, serve additional metadata (#745) 2025-07-26 18:53:09 -04:00
Brandon Thomas d671f7f951 record prompts on all generate/* andpoints (#744) 2025-07-25 18:29:44 -04:00
bflatastic e97e5c239e lightbox and download button fixes 2025-07-24 17:23:10 +07:00
bflatastic a7270f4685 lightbox prompt fetching 2025-07-24 16:21:21 +07:00
Brandon Thomas a6fb661fbe codegen db 2025-07-24 02:15:22 -04:00
Brandon Thomas e5f5a06b6b prompts code (#743) 2025-07-24 02:01:34 -04:00
Brandon Thomas 48a6b1a046 more migrations (#742) 2025-07-23 17:35:10 -04:00
Brandon Thomas 7791b9b6cc Bt prompts schema (#741) 2025-07-23 16:22:13 -04:00
Brandon Thomas ff30213af8 more GA instrumentation (#740) 2025-07-22 21:12:52 -04:00
Brandon Thomas 766f726dc1 Google Analytics package and events (#739) 2025-07-22 19:12:14 -04:00
Brandon Thomas 76d7d4c100 add microsoft clarity (#738) 2025-07-22 10:58:56 -04:00
BFlat 2902db074e Upload asset ux update (#737)
- image upload modal added
- everything under + button popover
<img width="393" height="263" alt="image"
src="https://github.com/user-attachments/assets/9f6bda8d-10c0-460f-8eab-227ad8155e68"
/>
2025-07-22 20:25:07 +07:00
Brandon Thomas b8ee03f1b7 load glb assets without cors (#736) 2025-07-22 08:43:38 -04:00
Brandon Thomas 2cf300588e inference job query reaper (#735) 2025-07-21 19:42:27 -04:00
BFlat d2720d0a62 services icons for the models list (#733)
added model service icons:
- google
- black forest labs
- bytedance
- kling
- midjourney
- openai
2025-07-21 14:51:15 +07:00
BFlat 69ed3ec48b bug fix: added z index to scene state (#734)
layers z-index now are persisted in scene state
2025-07-21 14:49:23 +07:00
bflatastic 81f5797e2f removed download link from completed card 2025-07-21 13:28:45 +07:00
Brandon Thomas a80c69ab1e update download links (#732) 2025-07-17 22:05:56 -04:00
816 changed files with 13714 additions and 47585 deletions
@@ -1,12 +1,12 @@
{
"db_name": "MySQL",
"query": "\nINSERT INTO generic_inference_jobs\nSET\n token = ?,\n uuid_idempotency_token = ?,\n\n job_type = ?,\n\n maybe_external_third_party = ?,\n maybe_external_third_party_id = ?,\n\n product_category = ?,\n inference_category = ?,\n\n maybe_model_type = NULL,\n maybe_model_token = NULL,\n\n maybe_input_source_token = NULL,\n maybe_input_source_token_type = NULL,\n\n maybe_download_url = NULL,\n maybe_cover_image_media_file_token = NULL,\n\n maybe_raw_inference_text = NULL,\n\n maybe_inference_args = ?,\n\n maybe_creator_user_token = ?,\n maybe_creator_anonymous_visitor_token = ?,\n creator_ip_address = ?,\n creator_set_visibility = ?,\n\n priority_level = 0,\n is_keepalive_required = FALSE,\n max_duration_seconds = 0,\n\n is_debug_request = FALSE,\n maybe_routing_tag = NULL,\n\n status = ?\n ",
"query": "\nINSERT INTO generic_inference_jobs\nSET\n token = ?,\n uuid_idempotency_token = ?,\n\n job_type = ?,\n\n maybe_external_third_party = ?,\n maybe_external_third_party_id = ?,\n\n product_category = ?,\n inference_category = ?,\n\n maybe_model_type = NULL,\n maybe_model_token = NULL,\n\n maybe_input_source_token = NULL,\n maybe_input_source_token_type = NULL,\n\n maybe_download_url = NULL,\n maybe_cover_image_media_file_token = NULL,\n \n maybe_prompt_token = ?,\n\n maybe_raw_inference_text = NULL,\n\n maybe_inference_args = ?,\n\n maybe_creator_user_token = ?,\n maybe_creator_anonymous_visitor_token = ?,\n creator_ip_address = ?,\n creator_set_visibility = ?,\n\n priority_level = 0,\n is_keepalive_required = FALSE,\n max_duration_seconds = 0,\n\n is_debug_request = FALSE,\n maybe_routing_tag = NULL,\n\n status = ?\n ",
"describe": {
"columns": [],
"parameters": {
"Right": 13
"Right": 14
},
"nullable": []
},
"hash": "0fa824822cd94024dce21243f41e69e4a3e8685c4de676834a7c0ee14982c976"
"hash": "002cdb3d086f3b4181e2997befa54bd8516cb1d3d3bb6e389862695318d5c299"
}
@@ -0,0 +1,12 @@
{
"db_name": "SQLite",
"query": "\n INSERT INTO tasks (\n id,\n task_status,\n task_type,\n model_type,\n provider,\n provider_job_id,\n frontend_caller,\n frontend_subscriber_id,\n frontend_subscriber_payload\n )\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)\n ",
"describe": {
"columns": [],
"parameters": {
"Right": 9
},
"nullable": []
},
"hash": "01a0bf33e8331c19dc73f064c54eaa863bec158ef7713450a06c75e246f5f08c"
}
@@ -0,0 +1,12 @@
{
"db_name": "MySQL",
"query": "\nINSERT INTO prompts\nSET\n token = ?,\n prompt_type = ?,\n\n maybe_creator_user_token = ?,\n \n maybe_model_type = ?,\n maybe_generation_provider = ?,\n\n maybe_positive_prompt = ?,\n maybe_negative_prompt = ?,\n \n maybe_other_args = ?,\n\n creator_ip_address = ?\n ",
"describe": {
"columns": [],
"parameters": {
"Right": 9
},
"nullable": []
},
"hash": "08f52f15acf6afc7091a525e3dc88f706c71c3579e5e81aa9903807d85f469ef"
}
@@ -0,0 +1,69 @@
{
"db_name": "MySQL",
"query": "\nSELECT\n pci.media_token as `media_token: tokens::tokens::media_files::MediaFileToken`,\n pci.context_semantic_type as `context_semantic_type: enums::by_table::prompt_context_items::prompt_context_semantic_type::PromptContextSemanticType`,\n\n m.public_bucket_directory_hash,\n m.maybe_public_bucket_prefix,\n m.maybe_public_bucket_extension\n\nFROM prompt_context_items pci\nJOIN media_files m\nON\n pci.media_token = m.token\nWHERE\n pci.prompt_token = ?\nORDER BY pci.id ASC\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "media_token: tokens::tokens::media_files::MediaFileToken",
"type_info": {
"type": "VarString",
"flags": "NOT_NULL | MULTIPLE_KEY | BINARY | NO_DEFAULT_VALUE",
"char_set": 224,
"max_size": 128
}
},
{
"ordinal": 1,
"name": "context_semantic_type: enums::by_table::prompt_context_items::prompt_context_semantic_type::PromptContextSemanticType",
"type_info": {
"type": "VarString",
"flags": "NOT_NULL | BINARY | NO_DEFAULT_VALUE",
"char_set": 224,
"max_size": 64
}
},
{
"ordinal": 2,
"name": "public_bucket_directory_hash",
"type_info": {
"type": "VarString",
"flags": "NOT_NULL | BINARY | NO_DEFAULT_VALUE",
"char_set": 224,
"max_size": 128
}
},
{
"ordinal": 3,
"name": "maybe_public_bucket_prefix",
"type_info": {
"type": "VarString",
"flags": "BINARY",
"char_set": 224,
"max_size": 64
}
},
{
"ordinal": 4,
"name": "maybe_public_bucket_extension",
"type_info": {
"type": "VarString",
"flags": "BINARY",
"char_set": 224,
"max_size": 64
}
}
],
"parameters": {
"Right": 1
},
"nullable": [
false,
false,
false,
true,
true
]
},
"hash": "094eb099cde85835db0662c2700c6b82644b51bf9b3609391ed4d2945fe5e98f"
}
@@ -1,12 +0,0 @@
{
"db_name": "MySQL",
"query": "\nINSERT INTO prompts\nSET\n token = ?,\n prompt_type = ?,\n\n maybe_creator_user_token = ?,\n\n maybe_positive_prompt = ?,\n maybe_negative_prompt = ?,\n maybe_other_args = ?,\n\n creator_ip_address = ?\n ",
"describe": {
"columns": [],
"parameters": {
"Right": 7
},
"nullable": []
},
"hash": "13ca06bcbb4a576f8a2229a8554b7488d379baa381d8d5cb60972750e81b2173"
}
@@ -0,0 +1,12 @@
{
"db_name": "MySQL",
"query": "\nUPDATE generic_inference_jobs\nSET\n status = 'cancelled_by_system',\n retry_at = NULL,\n internal_debugging_failure_reason = 'reap_stale_fakeyou_jobs'\nWHERE\n job_type != 'fal_queue'\n AND status IN (\n 'pending',\n 'started',\n 'attempt_failed'\n )\n AND created_at > NOW() - INTERVAL 30 MINUTE\nLIMIT 5000\n ",
"describe": {
"columns": [],
"parameters": {
"Right": 0
},
"nullable": []
},
"hash": "19708db99f2b3c6283d2115a511e0eb1c99fab396ad0effd9eb2dd79926e9c93"
}
@@ -1,12 +0,0 @@
{
"db_name": "SQLite",
"query": "\n INSERT INTO tasks (\n id,\n task_status,\n task_type,\n model_type,\n provider,\n provider_job_id,\n frontend_subscriber_id,\n frontend_subscriber_payload\n )\n VALUES (?, ?, ?, ?, ?, ?, ?, ?)\n ",
"describe": {
"columns": [],
"parameters": {
"Right": 8
},
"nullable": []
},
"hash": "22b91a21cbb88abc9bc17b338cf2f9418e08e414667d44476623eb141ab17b87"
}
@@ -1,6 +1,6 @@
{
"db_name": "MySQL",
"query": "\nSELECT\n p.token as `token: tokens::tokens::prompts::PromptToken`,\n\n p.prompt_type as `prompt_type: enums::by_table::prompts::prompt_type::PromptType`,\n\n p.maybe_creator_user_token as `maybe_creator_user_token: tokens::tokens::users::UserToken`,\n\n p.maybe_positive_prompt,\n p.maybe_negative_prompt,\n p.maybe_other_args,\n\n p.creator_ip_address,\n p.created_at\n\nFROM prompts as p\nWHERE\n p.token = ?\n ",
"query": "\nSELECT\n p.token as `token: tokens::tokens::prompts::PromptToken`,\n\n p.prompt_type as `prompt_type: enums::by_table::prompts::prompt_type::PromptType`,\n\n p.maybe_model_type as `maybe_model_type: enums::common::model_type::ModelType`,\n p.maybe_generation_provider as `maybe_generation_provider: enums::common::generation_provider::GenerationProvider`,\n\n p.maybe_creator_user_token as `maybe_creator_user_token: tokens::tokens::users::UserToken`,\n\n p.maybe_positive_prompt,\n p.maybe_negative_prompt,\n p.maybe_other_args,\n\n p.creator_ip_address,\n p.created_at\n\nFROM prompts as p\nWHERE\n p.token = ?\n ",
"describe": {
"columns": [
{
@@ -25,6 +25,26 @@
},
{
"ordinal": 2,
"name": "maybe_model_type: enums::common::model_type::ModelType",
"type_info": {
"type": "VarString",
"flags": "BINARY",
"char_set": 224,
"max_size": 128
}
},
{
"ordinal": 3,
"name": "maybe_generation_provider: enums::common::generation_provider::GenerationProvider",
"type_info": {
"type": "VarString",
"flags": "BINARY",
"char_set": 224,
"max_size": 64
}
},
{
"ordinal": 4,
"name": "maybe_creator_user_token: tokens::tokens::users::UserToken",
"type_info": {
"type": "VarString",
@@ -34,7 +54,7 @@
}
},
{
"ordinal": 3,
"ordinal": 5,
"name": "maybe_positive_prompt",
"type_info": {
"type": "Blob",
@@ -44,7 +64,7 @@
}
},
{
"ordinal": 4,
"ordinal": 6,
"name": "maybe_negative_prompt",
"type_info": {
"type": "Blob",
@@ -54,7 +74,7 @@
}
},
{
"ordinal": 5,
"ordinal": 7,
"name": "maybe_other_args",
"type_info": {
"type": "Blob",
@@ -64,7 +84,7 @@
}
},
{
"ordinal": 6,
"ordinal": 8,
"name": "creator_ip_address",
"type_info": {
"type": "VarString",
@@ -74,7 +94,7 @@
}
},
{
"ordinal": 7,
"ordinal": 9,
"name": "created_at",
"type_info": {
"type": "Timestamp",
@@ -94,9 +114,11 @@
true,
true,
true,
true,
true,
false,
false
]
},
"hash": "61744bbf83f7cf00348bcc21e868d9c506fec46da4a33ac50d63c6d9e00c0cec"
"hash": "b46b0d022790f4e10f6e47126df0fdc55172bf8cda77d4e0b2afac9e6ebd1630"
}
@@ -1,6 +1,6 @@
{
"db_name": "MySQL",
"query": "\nSELECT\n jobs.token as `job_token: tokens::tokens::generic_inference_jobs::InferenceJobToken`,\n\n jobs.status as `status: enums::common::job_status_plus::JobStatusPlus`,\n \n jobs.maybe_external_third_party as `external_third_party: enums::by_table::generic_inference_jobs::inference_job_external_third_party::InferenceJobExternalThirdParty`,\n jobs.maybe_external_third_party_id as `external_third_party_id`,\n\n jobs.maybe_creator_user_token as `maybe_creator_user_token: tokens::tokens::users::UserToken`,\n jobs.maybe_creator_anonymous_visitor_token as `maybe_creator_anonymous_visitor_token: tokens::tokens::anonymous_visitor_tracking::AnonymousVisitorTrackingToken`,\n jobs.creator_ip_address,\n\n jobs.created_at,\n jobs.updated_at\n\nFROM generic_inference_jobs as jobs\n\nWHERE jobs.maybe_external_third_party = ?\nAND jobs.maybe_external_third_party_id = ?\n ",
"query": "\nSELECT\n jobs.token as `job_token: tokens::tokens::generic_inference_jobs::InferenceJobToken`,\n\n jobs.status as `status: enums::common::job_status_plus::JobStatusPlus`,\n \n jobs.maybe_external_third_party as `external_third_party: enums::by_table::generic_inference_jobs::inference_job_external_third_party::InferenceJobExternalThirdParty`,\n jobs.maybe_external_third_party_id as `external_third_party_id`,\n\n jobs.maybe_creator_user_token as `maybe_creator_user_token: tokens::tokens::users::UserToken`,\n jobs.maybe_creator_anonymous_visitor_token as `maybe_creator_anonymous_visitor_token: tokens::tokens::anonymous_visitor_tracking::AnonymousVisitorTrackingToken`,\n jobs.creator_ip_address,\n \n jobs.maybe_prompt_token as `maybe_prompt_token: tokens::tokens::prompts::PromptToken`,\n\n jobs.created_at,\n jobs.updated_at\n\nFROM generic_inference_jobs as jobs\n\nWHERE jobs.maybe_external_third_party = ?\nAND jobs.maybe_external_third_party_id = ?\n ",
"describe": {
"columns": [
{
@@ -75,6 +75,16 @@
},
{
"ordinal": 7,
"name": "maybe_prompt_token: tokens::tokens::prompts::PromptToken",
"type_info": {
"type": "VarString",
"flags": "BINARY",
"char_set": 224,
"max_size": 128
}
},
{
"ordinal": 8,
"name": "created_at",
"type_info": {
"type": "Timestamp",
@@ -84,7 +94,7 @@
}
},
{
"ordinal": 8,
"ordinal": 9,
"name": "updated_at",
"type_info": {
"type": "Timestamp",
@@ -105,9 +115,10 @@
true,
true,
false,
true,
false,
false
]
},
"hash": "64dfacc1f0552d539f009fea91e902a2fe296c06ad539808596bbf2c8fc9eaa0"
"hash": "fbe482c8987231c3b5d75f2e792d0fdd033de8a7eb821428fa034752c73edfb7"
}
Generated
+1
View File
@@ -663,6 +663,7 @@ dependencies = [
"futures 0.3.31",
"idempotency",
"image",
"images",
"indexmap 2.9.0",
"log",
"memory_store",
@@ -4,17 +4,43 @@
-- tasks_v2.sqlite - added model_type (nullable)
CREATE TABLE tasks (
-- Task auto-incrementing primary key.
-- We don't use this.
id TEXT NOT NULL PRIMARY KEY,
-- TaskStatus enum
-- This is how the job system manages job states.
-- e.g. pending, started, complete_success, dead, etc.
task_status TEXT NOT NULL,
-- TaskType enum
-- e.g. image_generation, video_generation, etc.
task_type TEXT NOT NULL,
-- TaskModelType enum
-- e.g. flux_1_dev, veo_2, etc.
model_type TEXT,
-- GenerationProvider enum
-- Together with `provider_job_id`, this creates a foreign key lookup to the job.
-- e.g. 'artcraft', 'fal', 'sora', etc.
provider TEXT,
-- The primary key for the job in the provider's system.
provider_job_id TEXT,
-- OPTIONAL.
-- Tell the job system which caller initiated the task.
-- e.g. 'canvas'
frontend_caller TEXT,
-- OPTIONAL.
-- An arbitrary opaque identifier that frontend can set.
frontend_subscriber_id TEXT,
-- OPTIONAL.
-- An opaque JSON payload set by the frontend subscriber that
-- will be re-emitted back to the frontend.
frontend_subscriber_payload TEXT,
created_at INTEGER NOT NULL DEFAULT (unixepoch('now')),
@@ -0,0 +1,5 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE prompts DROP COLUMN maybe_model_type;
@@ -0,0 +1,6 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE prompts
ADD COLUMN maybe_model_type VARCHAR(32) DEFAULT NULL;
@@ -0,0 +1,5 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE prompts DROP COLUMN maybe_generation_provider;
@@ -0,0 +1,6 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE prompts
ADD COLUMN maybe_generation_provider VARCHAR(16) DEFAULT NULL;
@@ -0,0 +1,5 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE prompts DROP COLUMN maybe_anonymous_visitor_token;
@@ -0,0 +1,6 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE prompts
ADD COLUMN maybe_anonymous_visitor_token VARCHAR(32) DEFAULT NULL;
@@ -0,0 +1,5 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
DROP TABLE prompt_context_items;
@@ -0,0 +1,30 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
-- An n:m join table between prompts and media_files.
-- This associates mostly image media files with prompts, though we could conceivably
-- also store 3D sets, etc.
CREATE TABLE prompt_context_items (
-- Not used for anything except replication.
id BIGINT(20) NOT NULL AUTO_INCREMENT,
-- The semantic type of context.
context_semantic_type VARCHAR(16) NOT NULL,
-- Foreign key, many-to-many
-- There is no uniqueness constraint for (prompt_token, media_token) because a user
-- might attach many duplicate images to the same prompt.
prompt_token VARCHAR(32) NOT NULL,
-- Foreign key to the media token
-- There is no uniqueness constraint for (prompt_token, media_token) because a user
-- might attach many duplicate images to the same prompt.
media_token VARCHAR(32) NOT NULL,
-- INDICES --
PRIMARY KEY (id),
KEY index_prompt_token (prompt_token),
KEY index_media_token (media_token)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin;
@@ -0,0 +1,5 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE generic_inference_jobs DROP COLUMN maybe_prompt_token;
@@ -0,0 +1,6 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE generic_inference_jobs
ADD COLUMN maybe_prompt_token VARCHAR(32) DEFAULT NULL;
@@ -0,0 +1,5 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE media_files DROP COLUMN maybe_generation_provider;
@@ -0,0 +1,6 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
ALTER TABLE media_files
ADD COLUMN maybe_generation_provider VARCHAR(16) DEFAULT NULL;
@@ -21,6 +21,8 @@ CREATE TABLE generic_inference_jobs (
-- The new enum for the type of job, which will eventually replace `inference_category` and `maybe_model_type`.
-- This isn't fully supported yet in the inference-job, but we'll start populating it and adding logic around it.
-- We'll start this out as nullable, then migrate the old rows with a default column value.
--
-- Fal jobs have the type `fal_queue`.
job_type VARCHAR(32) DEFAULT NULL,
-- There is an index on this column.
@@ -103,6 +105,11 @@ CREATE TABLE generic_inference_jobs (
-- And furthermore, not all download URLs have a cover image.
maybe_cover_image_media_file_token VARCHAR(32) DEFAULT NULL,
-- If we pre-constructed a prompt, this will be copied to the resultant media generated.
-- This is especially important for Fal-related jobs and endpoints. We need this for keeping
-- track of all the prompt details, context images, etc.
maybe_prompt_token VARCHAR(30) DEFAULT NULL,
-- A migration flag we can control from the backend API service which will tell
-- the worker where to store the results. If false, GCP. If true, AWS.
store_in_aws BOOLEAN NOT NULL DEFAULT FALSE,
+3
View File
@@ -61,6 +61,9 @@ CREATE TABLE media_files (
-- * 'workflow' (DEPRECATED)
origin_product_category VARCHAR(16) NOT NULL DEFAULT "unknown",
-- What service provided the generation (if any).
maybe_generation_provider VARCHAR(16) DEFAULT NULL,
-- For inference that can be tied back to a model, the type of model.
-- There are multiple indices on this column!
-- DO NOT EXPOSE THIS TO USERS VIA THE API, as we may leak secrets in doing so.
@@ -15,9 +15,9 @@ CREATE TABLE batch_generations (
-- The type of record this is attached to
-- Currently supported values:
-- * 'model_weight'
-- * 'model_weight' (deprecated)
-- * 'comment' (deprecated)
-- * 'media_file'
-- * 'comment'
entity_type VARCHAR(32) NOT NULL,
-- The token for the record.
@@ -37,6 +37,4 @@ CREATE TABLE batch_generations (
-- NB: Realistically, we probably don't need this index until we have a lot of entity types, and the entity_token
-- entropy is probably sufficient enough as-is.
-- KEY index_entity_type_and_token (entity_type, entity_token),
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin;
@@ -0,0 +1,30 @@
-- noinspection SqlDialectInspectionForFile
-- noinspection SqlNoDataSourceInspectionForFile
-- noinspection SqlResolveForFile
-- An n:m join table between prompts and media_files.
-- This associates mostly image media files with prompts, though we could conceivably
-- also store 3D sets, etc.
CREATE TABLE prompt_context_items (
-- Not used for anything except replication.
id BIGINT(20) NOT NULL AUTO_INCREMENT,
-- Foreign key, many-to-many
-- There is no uniqueness constraint for (prompt_token, media_token) because a user
-- might attach many duplicate images to the same prompt.
prompt_token VARCHAR(32) NOT NULL,
-- Foreign key to the media token
-- There is no uniqueness constraint for (prompt_token, media_token) because a user
-- might attach many duplicate images to the same prompt.
media_token VARCHAR(32) NOT NULL,
-- The semantic type of context.
context_semantic_type VARCHAR(16) NOT NULL,
-- INDICES --
PRIMARY KEY (id),
KEY index_prompt_token (prompt_token),
KEY index_media_token (media_token)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin;
@@ -19,13 +19,25 @@ CREATE TABLE prompts (
-- Original product to which the prompt applied.
-- Prompts may or may not be compatible across products.
-- Possible values:
-- * 'stable_diffusion'
-- * 'comfy_ui'
-- * 'artcraft_app'
-- * 'stable_diffusion' (legacy)
-- * 'comfy_ui' (legacy)
prompt_type VARCHAR(16) NOT NULL,
-- Whomever created the prompt
-- What type of model was used to generate the result.
-- NB: We're conflating prompts with outputs, but in a
-- sense the model is inextricably part of the prompt.
maybe_model_type VARCHAR(32) DEFAULT NULL,
-- What service provided the generation.
maybe_generation_provider VARCHAR(16) NOT NULL,
-- Whoever created the prompt
maybe_creator_user_token VARCHAR(32) DEFAULT NULL,
-- Whoever created the prompt (anonymous user tracking)
maybe_anonymous_visitor_token VARCHAR(32) DEFAULT NULL,
-- ========== PROMPT DETAILS ==========
-- The positive prompt (optional)
@@ -0,0 +1,89 @@
use crate::creds::fal_api_key::FalApiKey;
use crate::error::classify_fal_error::classify_fal_error;
use crate::error::fal_error_plus::FalErrorPlus;
use fal::prelude::fal_ai::flux_pro::kontext::max::{max, FluxProKontextMaxInput};
use fal::webhook::WebhookResponse;
use reqwest::IntoUrl;
pub struct FluxProKontextMaxArgs<'a, U: IntoUrl, R: IntoUrl> {
// Request
pub prompt: &'a str,
pub image_url: U,
pub num_images: FluxProKontextMaxNumImages,
// Fulfillment
pub webhook_url: R,
pub api_key: &'a FalApiKey,
}
#[derive(Copy, Clone, Debug)]
pub enum FluxProKontextMaxNumImages {
One, // Default
Two,
Three,
Four,
}
pub async fn enqueue_flux_pro_kontext_max_edit_webhook<U: IntoUrl, R: IntoUrl>(
args: FluxProKontextMaxArgs<'_, U, R>
) -> Result<WebhookResponse, FalErrorPlus> {
let num_images = match args.num_images {
FluxProKontextMaxNumImages::One => 1,
FluxProKontextMaxNumImages::Two => 2,
FluxProKontextMaxNumImages::Three => 3,
FluxProKontextMaxNumImages::Four => 4,
};
let request = FluxProKontextMaxInput {
prompt: args.prompt.to_string(),
image_url: args.image_url.as_str().to_string(),
num_images: Some(num_images),
// Maybe expose
aspect_ratio: None,
safety_tolerance: Some("5".to_string()), // NB: 5 is most tolerant
output_format: Some("png".to_string()), // png or jpeg
seed: None,
// Constants
sync_mode: None, // Synchronous / slow
};
let result = max(request)
.with_api_key(&args.api_key.0)
.queue_webhook(args.webhook_url)
.await;
result.map_err(|err| classify_fal_error(err))
}
#[cfg(test)]
mod tests {
use crate::creds::fal_api_key::FalApiKey;
use crate::requests::webhook::image::edit::enqueue_flux_pro_kontext_max_edit_webhook::{enqueue_flux_pro_kontext_max_edit_webhook, FluxProKontextMaxArgs, FluxProKontextMaxNumImages};
use errors::AnyhowResult;
use std::fs::read_to_string;
use test_data::web::image_urls::TALL_MOCHI_WITH_GLASSES_IMAGE_URL;
#[tokio::test]
#[ignore]
async fn test() -> AnyhowResult<()> {
// XXX: Don't commit secrets!
let secret = read_to_string("/Users/bt/Artcraft/credentials/fal_api_key.txt")?;
let api_key = FalApiKey::from_str(&secret);
let args = FluxProKontextMaxArgs {
image_url: TALL_MOCHI_WITH_GLASSES_IMAGE_URL,
prompt: "turn the glasses into sunglasses, make them sleek sunglasses with black rims, square shaped",
api_key: &api_key,
webhook_url: "https://example.com/webhook",
num_images: FluxProKontextMaxNumImages::One,
};
let result = enqueue_flux_pro_kontext_max_edit_webhook(args).await?;
Ok(())
}
}
@@ -0,0 +1 @@
pub mod enqueue_flux_pro_kontext_max_edit_webhook;
@@ -0,0 +1,123 @@
use crate::creds::fal_api_key::FalApiKey;
use crate::creds::open_ai_api_key::OpenAiApiKey;
use crate::error::classify_fal_error::classify_fal_error;
use crate::error::fal_error_plus::FalErrorPlus;
use fal::prelude::fal_ai::gpt_image_1::edit_image::byok::{gpt_text_to_image, GptTextToImageRequest};
use fal::webhook::WebhookResponse;
use reqwest::IntoUrl;
pub struct GptTextToImageByokArgs<'a, V: IntoUrl> {
// Request
pub prompt: &'a str,
pub image_size: GptTextToImageSize,
pub num_images: GptTextToImageNumImages,
pub quality: GptTextToImageQuality,
// Fulfillment
pub api_key: &'a FalApiKey,
pub openai_api_key: &'a OpenAiApiKey,
pub webhook_url: V,
}
#[derive(Copy, Clone, Debug)]
pub enum GptTextToImageSize{
Auto,
Square,
Horizontal,
Vertical,
}
#[derive(Copy, Clone, Debug)]
pub enum GptTextToImageQuality {
Auto,
Low,
Medium,
High,
}
#[derive(Copy, Clone, Debug)]
pub enum GptTextToImageNumImages{
One,
Two,
Three,
Four,
}
pub async fn enqueue_gpt_image_1_text_to_image_webhook<V: IntoUrl>(
args: GptTextToImageByokArgs<'_, V>
) -> Result<WebhookResponse, FalErrorPlus> {
// auto, 1024x1024, 1536x1024, 1024x1536
let image_size = match args.image_size {
GptTextToImageSize::Auto => "auto",
GptTextToImageSize::Square => "1024x1024",
GptTextToImageSize::Horizontal => "1536x1024",
GptTextToImageSize::Vertical => "1024x1536",
};
let quality = match args.quality {
GptTextToImageQuality::Auto => "auto",
GptTextToImageQuality::Low => "low",
GptTextToImageQuality::Medium => "medium",
GptTextToImageQuality::High => "high",
};
let num_images = match args.num_images {
GptTextToImageNumImages::One => 1,
GptTextToImageNumImages::Two => 2,
GptTextToImageNumImages::Three => 3,
GptTextToImageNumImages::Four => 4,
};
let request = GptTextToImageRequest {
prompt: args.prompt.to_string(),
image_size: image_size.to_string(),
num_images,
quality: quality.to_string(),
openai_api_key: args.openai_api_key.0.to_string(),
};
let result = gpt_text_to_image(request)
.with_api_key(&args.api_key.0)
.queue_webhook(args.webhook_url)
.await;
result.map_err(|err| classify_fal_error(err))
}
#[cfg(test)]
mod tests {
use crate::creds::fal_api_key::FalApiKey;
use crate::creds::open_ai_api_key::OpenAiApiKey;
use crate::requests::webhook::image::enqueue_gpt_image_1_text_to_image_webhook::{enqueue_gpt_image_1_text_to_image_webhook, GptTextToImageByokArgs, GptTextToImageNumImages, GptTextToImageQuality, GptTextToImageSize};
use errors::AnyhowResult;
use std::fs::read_to_string;
#[tokio::test]
#[ignore]
async fn test_gpt_image_1_edit_image() -> AnyhowResult<()> {
// XXX: Don't commit secrets!
let secret = read_to_string("/Users/bt/Artcraft/credentials/fal_api_key.txt")?;
let fal_api_key = FalApiKey::from_str(&secret);
let secret = read_to_string("/Users/bt/Artcraft/credentials/openai_api_key.txt")?;
let open_ai_api_key = OpenAiApiKey::from_str(&secret);
let args = GptTextToImageByokArgs {
prompt: "put the man and the ghost on the grassy hill. the man is scared of the friendly ghost.",
api_key: &fal_api_key,
openai_api_key: &open_ai_api_key,
webhook_url: "https://example.com/webhook",
image_size: GptTextToImageSize::Horizontal,
num_images: GptTextToImageNumImages::One,
quality: GptTextToImageQuality::High,
};
let result = enqueue_gpt_image_1_text_to_image_webhook(args).await?;
Ok(())
}
}
@@ -0,0 +1,92 @@
use crate::creds::fal_api_key::FalApiKey;
use crate::error::classify_fal_error::classify_fal_error;
use crate::error::fal_error_plus::FalErrorPlus;
use fal::prelude::fal_ai::flux_pro::v1::fill::fill;
use fal::prelude::fal_ai::flux_pro::v1::fill::FluxProFillInput;
use fal::webhook::WebhookResponse;
use reqwest::IntoUrl;
pub struct FluxPro1InfillArgs<'a, U: IntoUrl, R: IntoUrl, L: IntoUrl> {
// Request
pub prompt: &'a str,
pub image_url: U,
pub mask_url: R,
pub num_images: FluxPro1InfillNumImages,
// Fulfillment
pub webhook_url: L,
pub api_key: &'a FalApiKey,
}
#[derive(Copy, Clone, Debug)]
pub enum FluxPro1InfillNumImages {
One, // Default
Two,
Three,
Four,
}
pub async fn enqueue_flux_pro_1_infill_webhook<U: IntoUrl, R: IntoUrl, L: IntoUrl>(
args: FluxPro1InfillArgs<'_, U, R, L>
) -> Result<WebhookResponse, FalErrorPlus> {
let num_images = match args.num_images {
FluxPro1InfillNumImages::One => 1,
FluxPro1InfillNumImages::Two => 2,
FluxPro1InfillNumImages::Three => 3,
FluxPro1InfillNumImages::Four => 4,
};
let request = FluxProFillInput {
prompt: args.prompt.to_string(),
image_url: args.image_url.as_str().to_string(),
mask_url: args.mask_url.as_str().to_string(),
num_images: Some(num_images),
// Maybe expose
safety_tolerance: Some("5".to_string()), // NB: 5 is most tolerant
output_format: Some("png".to_string()), // png or jpeg
seed: None,
// Constants
sync_mode: None, // Synchronous / slow
};
let result = fill(request)
.with_api_key(&args.api_key.0)
.queue_webhook(args.webhook_url)
.await;
result.map_err(|err| classify_fal_error(err))
}
#[cfg(test)]
mod tests {
use crate::creds::fal_api_key::FalApiKey;
use crate::requests::webhook::image::infill::enqueue_flux_pro_1_infill_webhook::{enqueue_flux_pro_1_infill_webhook, FluxPro1InfillArgs, FluxPro1InfillNumImages};
use errors::AnyhowResult;
use std::fs::read_to_string;
use test_data::web::image_urls::{TALL_MOCHI_WITH_GLASSES_GLASSES_MASK_IMAGE_URL, TALL_MOCHI_WITH_GLASSES_IMAGE_URL};
#[tokio::test]
#[ignore]
async fn test() -> AnyhowResult<()> {
// XXX: Don't commit secrets!
let secret = read_to_string("/Users/bt/Artcraft/credentials/fal_api_key.txt")?;
let api_key = FalApiKey::from_str(&secret);
let args = FluxPro1InfillArgs {
image_url: TALL_MOCHI_WITH_GLASSES_IMAGE_URL,
mask_url: TALL_MOCHI_WITH_GLASSES_GLASSES_MASK_IMAGE_URL,
prompt: "slick sunglasses, cool glasses, reflection in glasses lenses",
api_key: &api_key,
webhook_url: "https://example.com/webhook",
num_images: FluxPro1InfillNumImages::One,
};
let result = enqueue_flux_pro_1_infill_webhook(args).await?;
Ok(())
}
}
@@ -0,0 +1 @@
pub mod enqueue_flux_pro_1_infill_webhook;
@@ -1,6 +1,9 @@
pub mod edit;
pub mod enqueue_flux_1_dev_text_to_image_webhook;
pub mod enqueue_flux_1_schnell_text_to_image_webhook;
pub mod enqueue_flux_pro_11_text_to_image_webhook;
pub mod enqueue_flux_pro_11_ultra_text_to_image_webhook;
pub mod enqueue_gpt_image_1_edit_image_webhook;
pub mod enqueue_gpt_image_1_text_to_image_webhook;
pub mod infill;
pub mod remove_background_rembg_webhook;
@@ -0,0 +1,19 @@
use crate::credentials::storyteller_credential_set::StorytellerCredentialSet;
use crate::error::storyteller_error::StorytellerError;
use crate::utils::api_host::ApiHost;
use crate::utils::basic_json_post_request::basic_json_post_request;
use artcraft_api_defs::generate::image::edit::flux_pro_kontext_max_edit_image::{FluxProKontextMaxEditImageRequest, FluxProKontextMaxEditImageResponse, FLUX_PRO_KONTEXT_MAX_EDIT_IMAGE_PATH};
pub async fn flux_pro_kontext_max_edit_image(
api_host: &ApiHost,
maybe_creds: Option<&StorytellerCredentialSet>,
request: FluxProKontextMaxEditImageRequest,
) -> Result<FluxProKontextMaxEditImageResponse, StorytellerError> {
Ok(basic_json_post_request(
api_host,
FLUX_PRO_KONTEXT_MAX_EDIT_IMAGE_PATH,
maybe_creds,
request,
).await?)
}
@@ -1 +1,2 @@
pub mod flux_pro_kontext_max_edit_image;
pub mod gpt_image_1_edit_image;
@@ -0,0 +1,19 @@
use crate::credentials::storyteller_credential_set::StorytellerCredentialSet;
use crate::error::storyteller_error::StorytellerError;
use crate::utils::api_host::ApiHost;
use crate::utils::basic_json_post_request::basic_json_post_request;
use artcraft_api_defs::generate::image::generate_gpt_image_1_text_to_image::{GenerateGptImage1TextToImageRequest, GenerateGptImage1TextToImageResponse, GPT_IMAGE_1_TEXT_TO_IMAGE_PATH};
pub async fn generate_gpt_image_1_text_to_image(
api_host: &ApiHost,
maybe_creds: Option<&StorytellerCredentialSet>,
request: GenerateGptImage1TextToImageRequest,
) -> Result<GenerateGptImage1TextToImageResponse, StorytellerError> {
Ok(basic_json_post_request(
api_host,
GPT_IMAGE_1_TEXT_TO_IMAGE_PATH,
maybe_creds,
request,
).await?)
}
@@ -0,0 +1,18 @@
use crate::credentials::storyteller_credential_set::StorytellerCredentialSet;
use crate::error::storyteller_error::StorytellerError;
use crate::utils::api_host::ApiHost;
use crate::utils::basic_json_post_request::basic_json_post_request;
use artcraft_api_defs::generate::image::inpaint::flux_pro_1_inpaint_image::{FluxPro1InpaintImageRequest, FluxPro1InpaintImageResponse, FLUX_PRO_1_INPAINT_PATH};
pub async fn flux_pro_1_inpaint_image(
api_host: &ApiHost,
maybe_creds: Option<&StorytellerCredentialSet>,
request: FluxPro1InpaintImageRequest,
) -> Result<FluxPro1InpaintImageResponse, StorytellerError> {
Ok(basic_json_post_request(
api_host,
FLUX_PRO_1_INPAINT_PATH,
maybe_creds,
request,
).await?)
}
@@ -0,0 +1 @@
pub mod flux_pro_1_inpaint_image;
@@ -3,4 +3,6 @@ pub mod generate_flux_1_dev_text_to_image;
pub mod generate_flux_1_schnell_text_to_image;
pub mod generate_flux_pro_11_text_to_image;
pub mod generate_flux_pro_11_ultra_text_to_image;
pub mod generate_gpt_image_1_text_to_image;
pub mod inpaint;
pub mod remove_image_background;
@@ -1,4 +1,5 @@
pub mod get_media_file;
pub mod upload_image_media_file_from_bytes;
pub mod upload_image_media_file_from_file;
pub mod upload_new_engine_asset_from_file;
pub mod upload_video_media_file_from_file;
@@ -0,0 +1,138 @@
use crate::credentials::storyteller_credential_set::StorytellerCredentialSet;
use crate::error::api_error::ApiError;
use crate::error::client_error::ClientError;
use crate::error::storyteller_error::StorytellerError;
use crate::shared_response_types::media_file_cover_image_details::MediaFileCoverImageDetails;
use crate::shared_response_types::media_links::MediaLinks;
use crate::shared_response_types::simple_entity_stats::SimpleEntityStats;
use crate::shared_response_types::user_details_light::UserDetailsLight;
use crate::utils::api_host::ApiHost;
use crate::utils::constants::{APPLICATION_JSON, USER_AGENT};
use crate::utils::filter_bad_response::filter_bad_response;
use crate::utils::http_get_anonymous::http_get_anonymous;
use chrono::{DateTime, Utc};
use enums::by_table::media_files::media_file_animation_type::MediaFileAnimationType;
use enums::by_table::media_files::media_file_class::MediaFileClass;
use enums::by_table::media_files::media_file_engine_category::MediaFileEngineCategory;
use enums::by_table::media_files::media_file_type::MediaFileType;
use enums::by_table::model_weights::weights_category::WeightsCategory;
use enums::common::visibility::Visibility;
use enums::no_table::style_transfer::style_transfer_name::StyleTransferName;
use enums_public::by_table::model_weights::public_weights_types::PublicWeightsType;
use idempotency::uuid::generate_random_uuid;
use log::debug;
use reqwest::multipart::{Form, Part};
use reqwest::Client;
use serde_derive::{Deserialize, Serialize};
use std::fs::File;
use std::io::Read;
use std::path::Path;
use tokens::tokens::batch_generations::BatchGenerationToken;
use tokens::tokens::media_files::MediaFileToken;
use tokens::tokens::model_weights::ModelWeightToken;
use tokens::tokens::prompts::PromptToken;
use uuid::uuid;
pub struct UploadImageBytesArgs<'a> {
pub api_host: &'a ApiHost,
pub maybe_creds: Option<&'a StorytellerCredentialSet>,
// NB: Bytes need to be owned for the request.
pub image_bytes: Vec<u8>,
pub image_type: ImageType,
/// If true, we should hide the image from the user's gallery.
pub is_intermediate_system_file: bool,
}
#[derive(Clone, Copy, Debug)]
pub enum ImageType {
Png,
Jpeg,
Gif,
}
impl ImageType {
pub fn mime_type(&self) -> &str {
match self {
ImageType::Png => "image/png",
ImageType::Jpeg => "image/jpeg",
ImageType::Gif => "image/gif",
}
}
pub fn file_extension(&self) -> &str {
match self {
ImageType::Png => "png",
ImageType::Jpeg => "jpg",
ImageType::Gif => "gif",
}
}
}
/// Upload an image media file from a file.
/// NB: File type is not checked, so caller needs to enforce.
/// NB: We need owned bytes for the request.
pub async fn upload_image_media_file_from_bytes(
args: UploadImageBytesArgs<'_>
) -> Result<UploadImageMediaFileSuccessResponse, StorytellerError> {
let url = get_route(args.api_host);
debug!("Requesting {:?}", &url);
let client = Client::builder()
.gzip(true)
.build()
.map_err(|err| StorytellerError::Client(ClientError::from(err)))?;
let part = Part::bytes(args.image_bytes)
.file_name(format!("image.{}", args.image_type.file_extension()))
.mime_str(args.image_type.mime_type())
.map_err(|err| StorytellerError::Client(ClientError::from(err)))?;
let mut form = Form::new()
.text("uuid_idempotency_token", generate_random_uuid())
.part("file", part);
if args.is_intermediate_system_file {
form = form.text("is_intermediate_system_file", "true");
}
let mut request_builder = client.post(url)
.header("User-Agent", USER_AGENT)
.header("Accept", APPLICATION_JSON);
if let Some(creds) = args.maybe_creds {
if let Some(header) = &creds.maybe_as_cookie_header() {
request_builder = request_builder.header("Cookie", header);
}
}
let response = request_builder
.multipart(form)
.send()
.await
.map_err(|err| StorytellerError::Api(ApiError::from(err)))?;
let response = filter_bad_response(response).await?;
let response_body = &response.text().await
.map_err(|err| StorytellerError::Api(ApiError::from(err)))?;
let media_file = serde_json::from_str(&response_body)
.map_err(|err| StorytellerError::Api(ApiError::from(err)))?;
Ok(media_file)
}
fn get_route(api_host: &ApiHost) -> String {
let api_hostname_and_scheme = api_host.to_api_hostname_and_scheme();
format!("{}/v1/media_files/upload/image", api_hostname_and_scheme)
}
// TODO(bt,2025-04-22): Share API definitions between client and server in common crate.
#[derive(Deserialize, Debug)]
pub struct UploadImageMediaFileSuccessResponse {
pub success: bool,
pub media_file_token: MediaFileToken,
}
@@ -33,14 +33,24 @@ use tokens::tokens::model_weights::ModelWeightToken;
use tokens::tokens::prompts::PromptToken;
use uuid::uuid;
pub struct UploadImageFromFileArgs<'a, P: AsRef<Path>> {
pub api_host: &'a ApiHost,
pub maybe_creds: Option<&'a StorytellerCredentialSet>,
// NB: Path needs to be owned for the request.
pub path: P,
/// If true, we should hide the image from the user's gallery.
pub is_intermediate_system_file: bool,
}
/// Upload an image media file from a file.
pub async fn upload_image_media_file_from_file<P: AsRef<Path>>(
api_host: &ApiHost,
maybe_creds: Option<&StorytellerCredentialSet>,
path: P,
args: UploadImageFromFileArgs<'_, P>,
) -> Result<UploadImageMediaFileSuccessResponse, StorytellerError> {
let url = get_route(api_host);
let url = get_route(args.api_host);
debug!("Requesting {:?}", &url);
@@ -51,17 +61,21 @@ pub async fn upload_image_media_file_from_file<P: AsRef<Path>>(
.build()
.map_err(|err| StorytellerError::Client(ClientError::from(err)))?;
let form = Form::new()
let mut form = Form::new()
.text("uuid_idempotency_token", generate_random_uuid())
.file("file", path)
.file("file", args.path)
.await
.map_err(|err| StorytellerError::Client(ClientError::from(err)))?;
if args.is_intermediate_system_file {
form = form.text("is_intermediate_system_file", "true");
}
let mut request_builder = client.post(url)
.header("User-Agent", USER_AGENT)
.header("Accept", APPLICATION_JSON);
if let Some(creds) = maybe_creds {
if let Some(creds) = args.maybe_creds {
if let Some(header) = &creds.maybe_as_cookie_header() {
request_builder = request_builder.header("Cookie", header);
}
@@ -1,7 +1,7 @@
use crate::credentials::storyteller_credential_set::StorytellerCredentialSet;
use crate::error::client_error::ClientError;
use crate::error::storyteller_error::StorytellerError;
use crate::media_files::upload_image_media_file_from_file::upload_image_media_file_from_file;
use crate::media_files::upload_image_media_file_from_file::{upload_image_media_file_from_file, UploadImageFromFileArgs};
use crate::media_files::upload_new_engine_asset_from_file::upload_new_engine_asset_from_file;
use crate::media_files::upload_video_media_file_from_file::upload_video_media_file_from_file;
use crate::utils::api_host::ApiHost;
@@ -49,7 +49,13 @@ pub async fn upload_media_file_from_file<P: AsRef<Path>>(
}
}
Some(FileExtension::Png) | Some(FileExtension::Jpg) | Some(FileExtension::Gif) | Some(FileExtension::Webp) => {
match upload_image_media_file_from_file(api_host, maybe_creds, path).await {
let result = upload_image_media_file_from_file(UploadImageFromFileArgs {
api_host,
maybe_creds,
path,
is_intermediate_system_file: false,
}).await;
match result {
Ok(result) => Ok(UploadMediaFileSuccessResponse {
success: result.success,
media_file_token: result.media_file_token,
+1
View File
@@ -33,6 +33,7 @@ errors = { workspace = true }
fal_client = { workspace = true }
filesys = { workspace = true }
idempotency = { workspace = true }
images = { workspace = true }
memory_store = { workspace = true }
mimetypes = { workspace = true }
openai_sora_client = { workspace = true }
@@ -1,6 +1,7 @@
use crate::core::commands::enqueue::image::generic::handle_image_artcraft::handle_image_artcraft;
use crate::core::commands::enqueue::image::generic::handle_image_fal::handle_image_fal;
use crate::core::commands::enqueue::image::gpt_image_1::handle_image_sora::handle_image_sora;
use crate::core::commands::enqueue::image::gpt_image_1::handle_gpt_image_1::handle_gpt_image_1;
use crate::core::commands::enqueue::image::gpt_image_1::handle_gpt_image_1_sora::handle_gpt_image_1_sora;
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::commands::response::failure_response_wrapper::{CommandErrorResponseWrapper, CommandErrorStatus};
@@ -39,6 +40,9 @@ pub struct EnqueueTextToImageRequest {
/// Aspect ratio.
pub aspect_ratio: Option<TextToImageSize>,
/// The number of images to generate.
pub number_images: Option<u32>,
}
// TODO(bt,2025-07-14): Support other aspect ratios / resolutions -
@@ -224,7 +228,16 @@ pub async fn dispatch_request(
return Err(InternalImageError::NoModelSpecified);
}
Some(ImageModel::GptImage1) => {
return handle_image_sora(&app, request, sora_creds_manager, sora_task_queue).await;
return handle_gpt_image_1(
request,
app,
app_data_root,
app_env_configs,
provider_priority_store,
storyteller_creds_manager,
sora_creds_manager,
sora_task_queue,
).await;
}
_ => {
// Fall-through
@@ -9,10 +9,10 @@ use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use anyhow::anyhow;
use artcraft_api_defs::generate::image::generate_flux_1_dev_text_to_image::{GenerateFlux1DevTextToImageAspectRatio, GenerateFlux1DevTextToImageRequest};
use artcraft_api_defs::generate::image::generate_flux_1_schnell_text_to_image::{GenerateFlux1SchnellTextToImageAspectRatio, GenerateFlux1SchnellTextToImageRequest};
use artcraft_api_defs::generate::image::generate_flux_pro_11_text_to_image::{GenerateFluxPro11TextToImageAspectRatio, GenerateFluxPro11TextToImageRequest};
use artcraft_api_defs::generate::image::generate_flux_pro_11_ultra_text_to_image::{GenerateFluxPro11UltraTextToImageAspectRatio, GenerateFluxPro11UltraTextToImageRequest};
use artcraft_api_defs::generate::image::generate_flux_1_dev_text_to_image::{GenerateFlux1DevTextToImageAspectRatio, GenerateFlux1DevTextToImageNumImages, GenerateFlux1DevTextToImageRequest};
use artcraft_api_defs::generate::image::generate_flux_1_schnell_text_to_image::{GenerateFlux1SchnellTextToImageAspectRatio, GenerateFlux1SchnellTextToImageNumImages, GenerateFlux1SchnellTextToImageRequest};
use artcraft_api_defs::generate::image::generate_flux_pro_11_text_to_image::{GenerateFluxPro11TextToImageAspectRatio, GenerateFluxPro11TextToImageNumImages, GenerateFluxPro11TextToImageRequest};
use artcraft_api_defs::generate::image::generate_flux_pro_11_ultra_text_to_image::{GenerateFluxPro11UltraTextToImageAspectRatio, GenerateFluxPro11UltraTextToImageNumImages, GenerateFluxPro11UltraTextToImageRequest};
use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_type::TaskType;
use fal_client::requests::queue::image_gen::enqueue_flux_pro_11_ultra_text_to_image::{enqueue_flux_pro_11_ultra_text_to_image, FluxPro11UltraTextToImageArgs};
@@ -58,7 +58,7 @@ pub async fn handle_image_artcraft(
return Err(InternalImageError::NoModelSpecified);
}
Some(ImageModel::GptImage1) => {
return Err(InternalImageError::AnyhowError(anyhow!("wrong logic: artcraft is handling sora images")));
return Err(InternalImageError::AnyhowError(anyhow!("wrong logic: an earlier branch should have handled gpt-image-1 images for Artcraft")));
}
Some(ImageModel::Recraft3) => {
return Err(InternalImageError::AnyhowError(anyhow!("not yet implemented in Artcraft")));
@@ -66,19 +66,25 @@ pub async fn handle_image_artcraft(
Some(ImageModel::Flux1Dev) => {
info!("enqueue Flux 1 Dev");
selected_model = GenerationModel::Flux1Dev;
let aspect_ratio = request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFlux1DevTextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFlux1DevTextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Auto => GenerateFlux1DevTextToImageAspectRatio::SquareHd,
TextToImageSize::Square => GenerateFlux1DevTextToImageAspectRatio::SquareHd,
});
let request = GenerateFlux1DevTextToImageRequest {
uuid_idempotency_token,
prompt: request.prompt,
aspect_ratio,
num_images: None,
aspect_ratio: request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFlux1DevTextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFlux1DevTextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Auto => GenerateFlux1DevTextToImageAspectRatio::SquareHd,
TextToImageSize::Square => GenerateFlux1DevTextToImageAspectRatio::SquareHd,
}),
num_images: request.number_images
.and_then(|num| match num {
1 => Some(GenerateFlux1DevTextToImageNumImages::One),
2 => Some(GenerateFlux1DevTextToImageNumImages::Two),
3 => Some(GenerateFlux1DevTextToImageNumImages::Three),
4 => Some(GenerateFlux1DevTextToImageNumImages::Four),
_ => None, // NB: use service defaults
}),
};
let result = generate_flux_1_dev_text_to_image(
&app_env_configs.storyteller_host,
@@ -99,19 +105,25 @@ pub async fn handle_image_artcraft(
Some(ImageModel::Flux1Schnell) => {
info!("enqueue Flux 1 Schnell");
selected_model = GenerationModel::Flux1Schnell;
let aspect_ratio = request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFlux1SchnellTextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFlux1SchnellTextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Auto => GenerateFlux1SchnellTextToImageAspectRatio::SquareHd,
TextToImageSize::Square => GenerateFlux1SchnellTextToImageAspectRatio::SquareHd,
});
let request = GenerateFlux1SchnellTextToImageRequest {
uuid_idempotency_token,
prompt: request.prompt,
aspect_ratio,
num_images: None,
aspect_ratio: request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFlux1SchnellTextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFlux1SchnellTextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Square => GenerateFlux1SchnellTextToImageAspectRatio::SquareHd,
TextToImageSize::Auto => GenerateFlux1SchnellTextToImageAspectRatio::SquareHd,
}),
num_images: request.number_images
.and_then(|num| match num {
1 => Some(GenerateFlux1SchnellTextToImageNumImages::One),
2 => Some(GenerateFlux1SchnellTextToImageNumImages::Two),
3 => Some(GenerateFlux1SchnellTextToImageNumImages::Three),
4 => Some(GenerateFlux1SchnellTextToImageNumImages::Four),
_ => None, // NB: use service defaults
}),
};
let result = generate_flux_1_schnell_text_to_image(
&app_env_configs.storyteller_host,
@@ -132,19 +144,25 @@ pub async fn handle_image_artcraft(
Some(ImageModel::FluxPro11) => {
info!("enqueue Flux Pro 1.1");
selected_model = GenerationModel::FluxPro11;
let aspect_ratio = request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFluxPro11TextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFluxPro11TextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Auto => GenerateFluxPro11TextToImageAspectRatio::Square,
TextToImageSize::Square => GenerateFluxPro11TextToImageAspectRatio::Square,
});
let request = GenerateFluxPro11TextToImageRequest {
uuid_idempotency_token,
prompt: request.prompt,
aspect_ratio,
num_images: None,
aspect_ratio: request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFluxPro11TextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFluxPro11TextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Square => GenerateFluxPro11TextToImageAspectRatio::Square,
TextToImageSize::Auto => GenerateFluxPro11TextToImageAspectRatio::Square,
}),
num_images: request.number_images
.and_then(|num| match num {
1 => Some(GenerateFluxPro11TextToImageNumImages::One),
2 => Some(GenerateFluxPro11TextToImageNumImages::Two),
3 => Some(GenerateFluxPro11TextToImageNumImages::Three),
4 => Some(GenerateFluxPro11TextToImageNumImages::Four),
_ => None, // NB: use service defaults
}),
};
let result = generate_flux_pro_11_text_to_image(
&app_env_configs.storyteller_host,
@@ -165,19 +183,25 @@ pub async fn handle_image_artcraft(
Some(ImageModel::FluxPro11Ultra) => {
info!("enqueue Flux Pro 1.1 Ultra");
selected_model = GenerationModel::FluxPro11Ultra;
let aspect_ratio = request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFluxPro11UltraTextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFluxPro11UltraTextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Auto => GenerateFluxPro11UltraTextToImageAspectRatio::Square,
TextToImageSize::Square => GenerateFluxPro11UltraTextToImageAspectRatio::Square,
});
let request = GenerateFluxPro11UltraTextToImageRequest {
uuid_idempotency_token,
prompt: request.prompt,
aspect_ratio,
num_images: None,
aspect_ratio: request.aspect_ratio
.map(|aspect| match aspect {
// TODO(bt,2025-07-14): Support other aspect ratios.
TextToImageSize::Tall => GenerateFluxPro11UltraTextToImageAspectRatio::PortraitNineBySixteen,
TextToImageSize::Wide => GenerateFluxPro11UltraTextToImageAspectRatio::LandscapeSixteenByNine,
TextToImageSize::Square => GenerateFluxPro11UltraTextToImageAspectRatio::Square,
TextToImageSize::Auto => GenerateFluxPro11UltraTextToImageAspectRatio::Square,
}),
num_images: request.number_images
.and_then(|num| match num {
1 => Some(GenerateFluxPro11UltraTextToImageNumImages::One),
2 => Some(GenerateFluxPro11UltraTextToImageNumImages::Two),
3 => Some(GenerateFluxPro11UltraTextToImageNumImages::Three),
4 => Some(GenerateFluxPro11UltraTextToImageNumImages::Four),
_ => None, // NB: use service defaults
}),
};
let result = generate_flux_pro_11_ultra_text_to_image(
&app_env_configs.storyteller_host,
@@ -0,0 +1,75 @@
use crate::core::commands::enqueue::image::enqueue_text_to_image_command::{EnqueueTextToImageRequest, TextToImageSize};
use crate::core::commands::enqueue::image::gpt_image_1::handle_gpt_image_1_artcraft::handle_gpt_image_1_artcraft;
use crate::core::commands::enqueue::image::gpt_image_1::handle_gpt_image_1_sora::handle_gpt_image_1_sora;
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_artcraft::handle_gpt_image_1_edit_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_sora::handle_gpt_image_1_edit_sora;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use crate::core::events::generation_events::generation_enqueue_failure_event::GenerationEnqueueFailureEvent;
use crate::core::model::image_models::ImageModel;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::core::state::provider_priority::{Provider, ProviderPriorityStore};
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_type::TaskType;
use fal_client::requests::queue::image_gen::enqueue_flux_pro_11_ultra_text_to_image::{enqueue_flux_pro_11_ultra_text_to_image, FluxPro11UltraTextToImageArgs};
use log::{error, info};
use openai_sora_client::recipes::maybe_upgrade_or_renew_session::maybe_upgrade_or_renew_session;
use openai_sora_client::recipes::simple_image_gen_with_session_auto_renew::{simple_image_gen_with_session_auto_renew, SimpleImageGenAutoRenewRequest};
use openai_sora_client::requests::image_gen::common::{ImageSize, NumImages};
use std::time::Duration;
use tauri::AppHandle;
pub async fn handle_gpt_image_1(
request: EnqueueTextToImageRequest,
app: &AppHandle,
app_data_root: &AppDataRoot,
app_env_configs: &AppEnvConfigs,
provider_priority_store: &ProviderPriorityStore,
storyteller_creds_manager: &StorytellerCredentialManager,
sora_creds_manager: &SoraCredentialManager,
sora_task_queue: &SoraTaskQueue,
) -> Result<TaskEnqueueSuccess, InternalImageError> {
let priority = provider_priority_store.get_priority()?;
// TODO: Check if providers are available before proceeding.
info!("Providers by priority: {:?}", priority);
for provider in priority.iter() {
match provider {
Provider::Fal => {
// Fallthrough
// If in the future we support OpenAI API keys, it's worth considering whether we
// send those requests ourselves, or if we use FAL as an intermediary. FAL makes
// the API nicer to deal with, but the user needs an additional key.
}
Provider::Artcraft => {
info!("Dispatching gpt-image-1 via Artcraft...");
return handle_gpt_image_1_artcraft(
request,
app_env_configs,
storyteller_creds_manager
).await;
}
Provider::Sora => {
info!("Dispatching gpt-image-1 via Sora...");
return handle_gpt_image_1_sora(
request,
app,
sora_creds_manager,
sora_task_queue,
).await;
}
}
}
Err(InternalImageError::NoProviderAvailable)
}
@@ -0,0 +1,115 @@
use crate::core::commands::enqueue::image::enqueue_text_to_image_command::{EnqueueTextToImageRequest, TextToImageSize};
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::{EditImageQuality, EditImageSize};
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use crate::core::events::generation_events::generation_enqueue_failure_event::GenerationEnqueueFailureEvent;
use crate::core::model::image_models::ImageModel;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::core::state::provider_priority::ProviderPriorityStore;
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use artcraft_api_defs::generate::image::generate_gpt_image_1_text_to_image::{GenerateGptImage1TextToImageImageQuality, GenerateGptImage1TextToImageImageSize, GenerateGptImage1TextToImageNumImages, GenerateGptImage1TextToImageRequest};
use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_type::TaskType;
use fal_client::requests::queue::image_gen::enqueue_flux_pro_11_ultra_text_to_image::{enqueue_flux_pro_11_ultra_text_to_image, FluxPro11UltraTextToImageArgs};
use idempotency::uuid::generate_random_uuid;
use log::{error, info};
use openai_sora_client::recipes::maybe_upgrade_or_renew_session::maybe_upgrade_or_renew_session;
use openai_sora_client::recipes::simple_image_gen_with_session_auto_renew::{simple_image_gen_with_session_auto_renew, SimpleImageGenAutoRenewRequest};
use openai_sora_client::requests::image_gen::common::{ImageSize, NumImages};
use std::time::Duration;
use storyteller_client::generate::image::edit::gpt_image_1_edit_image::gpt_image_1_edit_image;
use storyteller_client::generate::image::generate_gpt_image_1_text_to_image::generate_gpt_image_1_text_to_image;
use tauri::AppHandle;
pub async fn handle_gpt_image_1_artcraft(
request: EnqueueTextToImageRequest,
app_env_configs: &AppEnvConfigs,
storyteller_creds_manager: &StorytellerCredentialManager,
) -> Result<TaskEnqueueSuccess, InternalImageError> {
let creds = match storyteller_creds_manager.get_credentials()? {
Some(creds) => creds,
None => {
return Err(InternalImageError::NeedsStorytellerCredentials);
},
};
info!("Calling Artcraft gpt-image-1 ...");
let uuid_idempotency_token = generate_random_uuid();
let image_quality = Some(GenerateGptImage1TextToImageImageQuality::High);
//let image_quality = request.image_quality
// .map(|quality| match quality {
// EditImageQuality::Auto => GenerateGptImage1TextToImageImageQuality::Auto,
// EditImageQuality::High => GenerateGptImage1TextToImageImageQuality::High,
// EditImageQuality::Medium => GenerateGptImage1TextToImageImageQuality::Medium,
// EditImageQuality::Low => GenerateGptImage1TextToImageImageQuality::Low,
// });
let image_size = request.aspect_ratio
.map(|size| match size {
TextToImageSize::Auto => GenerateGptImage1TextToImageImageSize::Square,
TextToImageSize::Square => GenerateGptImage1TextToImageImageSize::Square,
TextToImageSize::Tall => GenerateGptImage1TextToImageImageSize::Vertical,
TextToImageSize::Wide => GenerateGptImage1TextToImageImageSize::Horizontal,
});
let num_images = match request.number_images {
None => None,
Some(1) => Some(GenerateGptImage1TextToImageNumImages::One),
Some(2) => Some(GenerateGptImage1TextToImageNumImages::Two),
Some(3) => Some(GenerateGptImage1TextToImageNumImages::Three),
Some(4) => Some(GenerateGptImage1TextToImageNumImages::Four),
// TODO: Error
//Some(other) => {
// return Err(InternalImageError::InvalidNumberOfRequestedImages {
// min: 1,
// max: 4,
// requested: other,
// });
//},
_ => Some(GenerateGptImage1TextToImageNumImages::One), // Default to one image if invalid number
};
let request = GenerateGptImage1TextToImageRequest {
uuid_idempotency_token,
prompt: request.prompt.clone(),
image_size,
num_images,
image_quality,
};
let result = generate_gpt_image_1_text_to_image(
&app_env_configs.storyteller_host,
Some(&creds),
request,
).await;
let job_id = match result {
Ok(enqueued) => {
// TODO(bt,2025-07-05): Enqueue job token?
info!("Successfully enqueued Artcraft gpt-image-1. Job token: {}",
enqueued.inference_job_token);
enqueued.inference_job_token
}
Err(err) => {
error!("Failed to use Artcraft gpt-image-1: {:?}", err);
return Err(InternalImageError::StorytellerError(err));
}
};
Ok(TaskEnqueueSuccess {
provider: GenerationProvider::Artcraft,
model: Some(GenerationModel::GptImage1),
provider_job_id: Some(job_id.to_string()),
task_type: TaskType::ImageGeneration,
})
}
@@ -19,9 +19,9 @@ use tauri::AppHandle;
const SORA_SIMPLE_IMAGE_GEN_TIMEOUT : Duration = Duration::from_millis(1000 * 30); // 30 seconds
pub async fn handle_image_sora(
app: &AppHandle,
pub async fn handle_gpt_image_1_sora(
request: EnqueueTextToImageRequest,
app: &AppHandle,
sora_creds_manager: &SoraCredentialManager,
sora_task_queue: &SoraTaskQueue,
) -> Result<TaskEnqueueSuccess, InternalImageError> {
@@ -55,10 +55,19 @@ pub async fn handle_image_sora(
Some(TextToImageSize::Wide) => ImageSize::Wide,
};
let num_images = match request.number_images {
None => NumImages::One,
Some(1) => NumImages::One,
Some(2) => NumImages::Two,
Some(3) => NumImages::Two, // NB: There is no option for three images!
Some(4) => NumImages::Four,
_ => NumImages::One,
};
let result =
simple_image_gen_with_session_auto_renew(SimpleImageGenAutoRenewRequest {
prompt: prompt.to_string(),
num_images: NumImages::One,
num_images,
image_size: size,
credentials: &creds,
request_timeout: Some(SORA_SIMPLE_IMAGE_GEN_TIMEOUT),
@@ -1 +1,3 @@
pub mod handle_image_sora;
pub (crate) mod handle_gpt_image_1_artcraft;
pub (crate) mod handle_gpt_image_1_sora;
pub (super) mod handle_gpt_image_1;
@@ -3,7 +3,7 @@ use crate::core::commands::enqueue::image::internal_image_error::InternalImageEr
use crate::core::commands::enqueue::image_bg_removal::errors::InternalBgRemovalError;
use crate::core::commands::enqueue::image_bg_removal::generic::handle_generic_bg_removal::handle_generic_bg_removal;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1::handle_gpt_image_1;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit::handle_gpt_image_1_edit;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::commands::response::failure_response_wrapper::{CommandErrorResponseWrapper, CommandErrorStatus};
use crate::core::commands::response::shorthand::{Response, ResponseOrErrorType};
@@ -43,6 +43,7 @@ use storyteller_client::error::storyteller_error::StorytellerError;
use storyteller_client::media_files::get_media_file::get_media_file;
use storyteller_client::utils::api_host::ApiHost;
use tauri::{AppHandle, Manager, State};
use enums::tauri::ux::tauri_command_caller::TauriCommandCaller;
use tokens::tokens::media_files::MediaFileToken;
#[derive(Deserialize, Debug)]
@@ -55,6 +56,21 @@ pub struct EnqueueImageBgRemovalCommand {
/// Base64-encoded image
pub base64_image: Option<String>,
/// OPTIONAL.
/// Name of the frontend caller.
/// We'll use this to selectively trigger events.
pub frontend_caller: Option<TauriCommandCaller>,
/// OPTIONAL.
/// A frontend-defined identifier that we'll send back to the frontend
/// as a Tauri event on task completion.
pub frontend_subscriber_id: Option<String>,
/// OPTIONAL.
/// A frontend-defined payload that we'll send back to the frontend
/// as a Tauri event on task completion.
pub frontend_subscriber_payload: Option<String>,
}
#[derive(Serialize, Debug)]
@@ -169,7 +185,12 @@ pub async fn handle_request(
).await?;
let result = success_event
.insert_into_task_database(task_database)
.insert_into_task_database_with_frontend_payload(
task_database,
request.frontend_caller,
request.frontend_subscriber_id.as_deref(),
request.frontend_subscriber_payload.as_deref()
)
.await;
if let Err(err) = result {
@@ -4,8 +4,8 @@ use crate::core::commands::enqueue::image_bg_removal::generic::handle_generic_bg
use crate::core::commands::enqueue::image_bg_removal::generic::handle_generic_bg_removal_fal::handle_generic_bg_removal_fal;
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::EnqueueContextualEditImageCommand;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_artcraft::handle_gpt_image_1_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_sora::handle_gpt_image_1_sora;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_artcraft::handle_gpt_image_1_edit_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_sora::handle_gpt_image_1_edit_sora;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
@@ -39,7 +39,7 @@ use storyteller_client::generate::image::generate_flux_1_schnell_text_to_image::
use storyteller_client::generate::image::generate_flux_pro_11_text_to_image::generate_flux_pro_11_text_to_image;
use storyteller_client::generate::image::generate_flux_pro_11_ultra_text_to_image::generate_flux_pro_11_ultra_text_to_image;
use storyteller_client::generate::image::remove_image_background::remove_image_background;
use storyteller_client::media_files::upload_image_media_file_from_file::upload_image_media_file_from_file;
use storyteller_client::media_files::upload_image_media_file_from_file::{upload_image_media_file_from_file, UploadImageFromFileArgs};
use tauri::AppHandle;
use tokens::tokens::media_files::MediaFileToken;
@@ -123,9 +123,13 @@ async fn upload_image_from_base64_bytes(
info!("Uploading image media file from temp file: {:?}", temp_file.path());
let result =
upload_image_media_file_from_file(&app_env_configs.storyteller_host, Some(&creds), temp_file)
.await
let result =
upload_image_media_file_from_file(UploadImageFromFileArgs {
api_host: &app_env_configs.storyteller_host,
maybe_creds: Some(&creds),
path: temp_file,
is_intermediate_system_file: true, // NB: Probably not essential to keep this.
}).await
.map_err(|err| {
error!("Failed to upload image media file: {:?}", err);
InternalBgRemovalError::StorytellerError(err)
@@ -1,7 +1,7 @@
use crate::core::commands::enqueue::image::enqueue_text_to_image_command::{EnqueueTextToImageRequest, EnqueueTextToImageSuccessResponse};
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1::handle_gpt_image_1;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit::handle_gpt_image_1_edit;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::commands::response::failure_response_wrapper::{CommandErrorResponseWrapper, CommandErrorStatus};
use crate::core::commands::response::shorthand::{Response, ResponseOrErrorType};
@@ -43,6 +43,7 @@ use storyteller_client::media_files::get_media_file::get_media_file;
use storyteller_client::utils::api_host::ApiHost;
use tauri::{AppHandle, Manager, State};
use tokens::tokens::media_files::MediaFileToken;
use crate::core::commands::enqueue::image_edit::flux_kontext::handle_flux_kontext_edit::handle_flux_kontext_edit;
#[derive(Deserialize, Debug)]
pub struct EnqueueContextualEditImageCommand {
@@ -207,8 +208,22 @@ pub async fn handle_request(
None => {
return Err(InternalContextualEditImageError::NoModelSpecified)
}
Some(ContextualImageEditModel::FluxProKontextMax) => {
handle_flux_kontext_edit(
request,
app,
app_data_root,
app_env_configs,
provider_priority_store,
storyteller_creds_manager,
fal_creds_manager,
fal_task_queue,
sora_creds_manager,
sora_task_queue,
).await?
}
Some(ContextualImageEditModel::GptImage1) => {
handle_gpt_image_1(
handle_gpt_image_1_edit(
request,
app,
app_data_root,
@@ -221,7 +236,6 @@ pub async fn handle_request(
sora_task_queue,
).await?
}
// TODO(bt,2025-07-05): Flux Kontext, etc.
};
let result = success_event
@@ -30,6 +30,12 @@ pub enum InternalContextualEditImageError {
requested: u32,
},
// TODO: Maybe just reuse the other error enum variant
/// An invalid number of input images was requested for Flux Kontext.
InvalidNumberOfInputImagesForFluxKontext {
message: String,
},
/// No sora credentials are set.
NeedsSoraCredentials,
@@ -84,6 +90,11 @@ impl InternalContextualEditImageError {
error_type = EnqueueContextualEditImageErrorType::BadRequest;
error_message = format!("Invalid number of input images ({}). Must be between {} and {}", requested, min, max);
}
InternalContextualEditImageError::InvalidNumberOfInputImagesForFluxKontext { message } => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueContextualEditImageErrorType::BadRequest;
error_message = message.clone();
}
InternalContextualEditImageError::SoraError(_) => {}
InternalContextualEditImageError::AnyhowError(_) => {}
InternalContextualEditImageError::StorytellerError(_) => {}
@@ -0,0 +1,59 @@
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::EnqueueContextualEditImageCommand;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::flux_kontext::handle_flux_kontext_edit_artcraft::handle_flux_kontext_edit_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_artcraft::handle_gpt_image_1_edit_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_sora::handle_gpt_image_1_edit_sora;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::core::state::provider_priority::{Provider, ProviderPriorityStore};
use crate::services::fal::state::fal_credential_manager::FalCredentialManager;
use crate::services::fal::state::fal_task_queue::FalTaskQueue;
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use log::info;
use tauri::AppHandle;
pub async fn handle_flux_kontext_edit(
request: &EnqueueContextualEditImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
app_env_configs: &AppEnvConfigs,
provider_priority_store: &ProviderPriorityStore,
storyteller_creds_manager: &StorytellerCredentialManager,
fal_creds_manager: &FalCredentialManager,
fal_task_queue: &FalTaskQueue,
sora_creds_manager: &SoraCredentialManager,
sora_task_queue: &SoraTaskQueue,
) -> Result<TaskEnqueueSuccess, InternalContextualEditImageError> {
let priority = provider_priority_store.get_priority()?;
// TODO: Check if providers are available before proceeding.
info!("Providers by priority: {:?}", priority);
for provider in priority.iter() {
match provider {
Provider::Fal => {
// Fallthrough (TODO)
}
Provider::Sora => {
// Fallthrough
}
Provider::Artcraft => {
info!("Dispatching gpt-image-1 (edit) via Artcraft...");
return handle_flux_kontext_edit_artcraft(
request,
app,
app_data_root,
app_env_configs,
storyteller_creds_manager
).await;
}
}
}
Err(InternalContextualEditImageError::NoProviderAvailable)
}
@@ -0,0 +1,148 @@
use crate::core::commands::enqueue::image::enqueue_text_to_image_command::EnqueueTextToImageRequest;
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::{EditImageQuality, EditImageSize, EnqueueContextualEditImageCommand};
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use crate::core::events::generation_events::generation_enqueue_failure_event::GenerationEnqueueFailureEvent;
use crate::core::model::contextual_image_edit_models::ContextualImageEditModel;
use crate::core::model::image_models::ImageModel;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::core::state::provider_priority::ProviderPriorityStore;
use crate::services::fal::state::fal_credential_manager::FalCredentialManager;
use crate::services::fal::state::fal_task_queue::FalTaskQueue;
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use anyhow::anyhow;
use artcraft_api_defs::generate::image::edit::flux_pro_kontext_max_edit_image::{FluxProKontextMaxEditImageNumImages, FluxProKontextMaxEditImageRequest};
use artcraft_api_defs::generate::image::edit::gpt_image_1_edit_image::{GptImage1EditImageImageQuality, GptImage1EditImageImageSize, GptImage1EditImageNumImages, GptImage1EditImageRequest};
use artcraft_api_defs::generate::image::generate_flux_1_dev_text_to_image::GenerateFlux1DevTextToImageRequest;
use artcraft_api_defs::generate::image::generate_flux_1_schnell_text_to_image::GenerateFlux1SchnellTextToImageRequest;
use artcraft_api_defs::generate::image::generate_flux_pro_11_text_to_image::GenerateFluxPro11TextToImageRequest;
use artcraft_api_defs::generate::image::generate_flux_pro_11_ultra_text_to_image::GenerateFluxPro11UltraTextToImageRequest;
use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_type::TaskType;
use fal_client::requests::queue::image_gen::enqueue_flux_pro_11_ultra_text_to_image::{enqueue_flux_pro_11_ultra_text_to_image, FluxPro11UltraTextToImageArgs};
use fal_client::requests::webhook::image::edit::enqueue_flux_pro_kontext_max_edit_webhook::FluxProKontextMaxNumImages;
use fal_client::requests::webhook::image::enqueue_gpt_image_1_edit_image_webhook::GptEditImageQuality;
use idempotency::uuid::generate_random_uuid;
use log::{error, info};
use storyteller_client::generate::image::edit::flux_pro_kontext_max_edit_image::flux_pro_kontext_max_edit_image;
use storyteller_client::generate::image::edit::gpt_image_1_edit_image::gpt_image_1_edit_image;
use storyteller_client::generate::image::generate_flux_1_dev_text_to_image::generate_flux_1_dev_text_to_image;
use storyteller_client::generate::image::generate_flux_1_schnell_text_to_image::generate_flux_1_schnell_text_to_image;
use storyteller_client::generate::image::generate_flux_pro_11_text_to_image::generate_flux_pro_11_text_to_image;
use storyteller_client::generate::image::generate_flux_pro_11_ultra_text_to_image::generate_flux_pro_11_ultra_text_to_image;
use tauri::AppHandle;
pub async fn handle_flux_kontext_edit_artcraft(
request: &EnqueueContextualEditImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
app_env_configs: &AppEnvConfigs,
storyteller_creds_manager: &StorytellerCredentialManager,
) -> Result<TaskEnqueueSuccess, InternalContextualEditImageError> {
let creds = match storyteller_creds_manager.get_credentials()? {
Some(creds) => creds,
None => {
return Err(InternalContextualEditImageError::NeedsStorytellerCredentials);
},
};
info!("Calling Artcraft flux kontext max edit (edit) ...");
let uuid_idempotency_token = generate_random_uuid();
let num_images = match request.image_count {
None => None,
Some(1) => Some(FluxProKontextMaxEditImageNumImages::One),
Some(2) => Some(FluxProKontextMaxEditImageNumImages::Two),
Some(3) => Some(FluxProKontextMaxEditImageNumImages::Three),
Some(4) => Some(FluxProKontextMaxEditImageNumImages::Four),
Some(other) => {
return Err(InternalContextualEditImageError::InvalidNumberOfRequestedImages {
min: 1,
max: 4,
requested: other,
});
},
};
let mut maybe_media_token = None;
let list_count = request.image_media_tokens
.as_ref()
.map(|tokens| tokens.len())
.unwrap_or(0);
if request.scene_image_media_token.is_some() && list_count > 0 {
return Err(InternalContextualEditImageError::InvalidNumberOfInputImagesForFluxKontext {
message: "Cannot specify both scene_image_media_token and image_media_tokens for Flux Kontext Max".to_string()
});
}
if list_count > 1 {
return Err(InternalContextualEditImageError::InvalidNumberOfInputImagesForFluxKontext {
message: "Cannot specify more than one image in image_media_tokens for Flux Kontext Max".to_string()
});
}
if let Some(media_token) = &request.scene_image_media_token {
maybe_media_token = Some(media_token.clone());
}
let maybe_list_media_token = request.image_media_tokens
.as_ref()
.map(|tokens| tokens.first())
.flatten();
if let Some(media_token) = maybe_list_media_token {
maybe_media_token = Some(media_token.clone());
}
let media_token = match maybe_media_token {
Some(token) => token,
None => {
return Err(InternalContextualEditImageError::InvalidNumberOfInputImagesForFluxKontext {
message: "No input image specified for Flux Kontext Max edit".to_string(),
});
},
};
let request = FluxProKontextMaxEditImageRequest {
uuid_idempotency_token,
prompt: Some(request.prompt.clone()),
image_media_token: media_token,
num_images,
};
let result = flux_pro_kontext_max_edit_image(
&app_env_configs.storyteller_host,
Some(&creds),
request,
).await;
let job_id = match result {
Ok(enqueued) => {
// TODO(bt,2025-07-05): Enqueue job token?
info!("Successfully enqueued Artcraft gpt-image-1. Job token: {}",
enqueued.inference_job_token);
enqueued.inference_job_token
}
Err(err) => {
error!("Failed to use Artcraft gpt-image-1: {:?}", err);
return Err(InternalContextualEditImageError::StorytellerError(err));
}
};
Ok(TaskEnqueueSuccess {
provider: GenerationProvider::Artcraft,
model: Some(GenerationModel::FluxProKontextMax),
provider_job_id: Some(job_id.to_string()),
task_type: TaskType::ImageGeneration,
})
}
@@ -0,0 +1,2 @@
pub (super) mod handle_flux_kontext_edit;
mod handle_flux_kontext_edit_artcraft;
@@ -1,7 +1,7 @@
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::EnqueueContextualEditImageCommand;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_artcraft::handle_gpt_image_1_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_sora::handle_gpt_image_1_sora;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_artcraft::handle_gpt_image_1_edit_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_sora::handle_gpt_image_1_edit_sora;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
@@ -16,7 +16,7 @@ use tauri::AppHandle;
pub(super) const MAX_IMAGES: usize = 10;
pub async fn handle_gpt_image_1(
pub async fn handle_gpt_image_1_edit(
request: &EnqueueContextualEditImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
@@ -44,8 +44,8 @@ pub async fn handle_gpt_image_1(
// the API nicer to deal with, but the user needs an additional key.
}
Provider::Artcraft => {
info!("Dispatching gpt-image-1 via Artcraft...");
return handle_gpt_image_1_artcraft(
info!("Dispatching gpt-image-1 (edit) via Artcraft...");
return handle_gpt_image_1_edit_artcraft(
request,
app,
app_data_root,
@@ -54,8 +54,8 @@ pub async fn handle_gpt_image_1(
).await;
}
Provider::Sora => {
info!("Dispatching gpt-image-1 via Sora...");
return handle_gpt_image_1_sora(
info!("Dispatching gpt-image-1 (edit) via Sora...");
return handle_gpt_image_1_edit_sora(
request,
app,
app_data_root,
@@ -2,7 +2,7 @@ use crate::core::commands::enqueue::image::enqueue_text_to_image_command::Enqueu
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::{EditImageQuality, EditImageSize, EnqueueContextualEditImageCommand};
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1::MAX_IMAGES;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit::MAX_IMAGES;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
@@ -36,7 +36,7 @@ use tauri::AppHandle;
use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_type::TaskType;
pub async fn handle_gpt_image_1_artcraft(
pub async fn handle_gpt_image_1_edit_artcraft(
request: &EnqueueContextualEditImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
@@ -51,7 +51,7 @@ pub async fn handle_gpt_image_1_artcraft(
},
};
info!("Calling Artcraft gpt-image-1 ...");
info!("Calling Artcraft gpt-image-1 (edit) ...");
let uuid_idempotency_token = generate_random_uuid();
@@ -2,7 +2,7 @@ use crate::core::commands::enqueue::image::enqueue_text_to_image_command::Enqueu
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::{EditImageSize, EnqueueContextualEditImageCommand, EnqueueContextualEditImageErrorType};
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1::MAX_IMAGES;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit::MAX_IMAGES;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::commands::response::failure_response_wrapper::{CommandErrorResponseWrapper, CommandErrorStatus};
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
@@ -48,7 +48,7 @@ const SORA_IMAGE_REMIX_TIMEOUT: Duration = Duration::from_millis(1000 * 30); //
const DEFAULT_ASPECT_RATIO : EditImageSize = EditImageSize::Square;
pub async fn handle_gpt_image_1_sora(
pub async fn handle_gpt_image_1_edit_sora(
request: &EnqueueContextualEditImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
@@ -1,3 +1,3 @@
pub mod handle_gpt_image_1;
pub mod handle_gpt_image_1_artcraft;
pub mod handle_gpt_image_1_sora;
pub mod handle_gpt_image_1_edit;
pub mod handle_gpt_image_1_edit_artcraft;
pub mod handle_gpt_image_1_edit_sora;
@@ -1,3 +1,4 @@
pub mod enqueue_contextual_edit_image_command;
pub mod errors;
pub mod gpt_image_1;
pub mod gpt_image_1;
mod flux_kontext;
@@ -0,0 +1,249 @@
use crate::core::commands::enqueue::image::enqueue_text_to_image_command::{EnqueueTextToImageRequest, EnqueueTextToImageSuccessResponse};
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit::handle_gpt_image_1_edit;
use crate::core::commands::enqueue::image_inpaint::errors::InternalImageInpaintError;
use crate::core::commands::enqueue::image_inpaint::flux_pro_1_inpaint::handle_flux_pro_1_inpaint::handle_flux_pro_1_inpaint;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::commands::response::failure_response_wrapper::{CommandErrorResponseWrapper, CommandErrorStatus};
use crate::core::commands::response::shorthand::{Response, ResponseOrErrorType};
use crate::core::commands::response::success_response_wrapper::SerializeMarker;
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
use crate::core::events::generation_events::common::{GenerationAction, GenerationServiceProvider};
use crate::core::events::generation_events::generation_enqueue_failure_event::GenerationEnqueueFailureEvent;
use crate::core::events::generation_events::generation_enqueue_success_event::GenerationEnqueueSuccessEvent;
use crate::core::events::sendable_event_trait::SendableEvent;
use crate::core::model::contextual_image_edit_models::ContextualImageEditModel;
use crate::core::model::image_models::ImageModel;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::core::state::data_dir::trait_data_subdir::DataSubdir;
use crate::core::state::provider_priority::ProviderPriorityStore;
use crate::core::state::task_database::TaskDatabase;
use crate::core::utils::get_url_file_extension::get_url_file_extension;
use crate::core::utils::simple_http_download::simple_http_download;
use crate::services::fal::state::fal_credential_manager::FalCredentialManager;
use crate::services::fal::state::fal_task_queue::FalTaskQueue;
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_status::TaskStatus;
use enums::tauri::tasks::task_type::TaskType;
use enums::tauri::ux::tauri_command_caller::TauriCommandCaller;
use errors::AnyhowError;
use log::{error, info, warn};
use openai_sora_client::recipes::image_remix_with_session_auto_renew::{image_remix_with_session_auto_renew, ImageRemixAutoRenewRequest};
use openai_sora_client::recipes::image_upload_from_file_with_session_auto_renew::{image_upload_from_file_with_session_auto_renew, ImageUploadFromFileAutoRenewRequest};
use openai_sora_client::recipes::maybe_upgrade_or_renew_session::maybe_upgrade_or_renew_session;
use openai_sora_client::requests::image_gen::common::{ImageSize, NumImages};
use openai_sora_client::sora_error::SoraError;
use serde_derive::{Deserialize, Serialize};
use sqlite_tasks::queries::create_task::{create_task, CreateTaskArgs};
use std::time::Duration;
use storyteller_client::error::storyteller_error::StorytellerError;
use storyteller_client::media_files::get_media_file::get_media_file;
use storyteller_client::utils::api_host::ApiHost;
use tauri::{AppHandle, Manager, State};
use tokens::tokens::media_files::MediaFileToken;
#[derive(Deserialize, Debug, Copy, Clone)]
#[serde(rename_all = "snake_case")]
pub enum ImageInpaintModel {
#[serde(rename = "flux_pro_1")]
FluxPro1,
}
#[derive(Deserialize, Debug)]
pub struct EnqueueInpaintImageCommand {
/// REQUIRED (Option<T> is just for error messages).
/// The model to use.
pub model: Option<ImageInpaintModel>,
/// REQUIRED (Option<T> is just for error messages).
/// The source image to edit.
pub image_media_token: Option<MediaFileToken>,
/// REQUIRED: Supply this *XOR* `mask_image_raw_bytes`.
/// The mask to focus the edit (already uploaded).
pub mask_image_media_token: Option<MediaFileToken>,
/// REQUIRED: Supply this *XOR* `mask_image_media_token`.
/// The mask to focus the edit (raw bytes).
pub mask_image_raw_bytes: Option<Vec<u8>>,
/// REQUIRED.
/// The user's image generation prompt.
pub prompt: String,
/// Number of images to generate.
pub image_count: Option<u32>,
/// If true, force the dimensions of the source image and mask image to match.
pub require_matching_dimensions: Option<bool>,
/// OPTIONAL.
/// Name of the frontend caller.
/// We'll use this to selectively trigger events.
pub frontend_caller: Option<TauriCommandCaller>,
/// OPTIONAL.
/// A frontend-defined identifier that we'll send back to the frontend
/// as a Tauri event on task completion.
pub frontend_subscriber_id: Option<String>,
/// OPTIONAL.
/// A frontend-defined payload that we'll send back to the frontend
/// as a Tauri event on task completion.
pub frontend_subscriber_payload: Option<String>,
}
#[derive(Serialize, Debug)]
#[serde(rename_all = "snake_case")]
pub enum EnqueueInpaintImageErrorType {
/// Caller didn't specify a model
ModelNotSpecified,
/// No model available for image generation
NoProviderAvailable,
/// No source image was supplied.
NoSourceImageSpecified,
/// No mask image was supplied.
NoMaskImageSpecified,
/// Too many mask images were supplied.
MultipleMaskImagesSpecified,
/// Bad mask image was supplied.
BadMaskImage,
/// Generic bad request error
BadRequest,
/// Generic server error
ServerError,
}
#[derive(Serialize)]
pub struct EnqueueImageInpaintSuccessResponse {
}
impl SerializeMarker for EnqueueImageInpaintSuccessResponse {}
#[tauri::command]
pub async fn enqueue_image_inpaint_command(
app: AppHandle,
request: EnqueueInpaintImageCommand,
app_data_root: State<'_, AppDataRoot>,
app_env_configs: State<'_, AppEnvConfigs>,
provider_priority_store: State<'_, ProviderPriorityStore>,
task_database: State<'_, TaskDatabase>,
storyteller_creds_manager: State<'_, StorytellerCredentialManager>,
fal_creds_manager: State<'_, FalCredentialManager>,
fal_task_queue: State<'_, FalTaskQueue>,
sora_creds_manager: State<'_, SoraCredentialManager>,
sora_task_queue: State<'_, SoraTaskQueue>,
) -> ResponseOrErrorType<EnqueueImageInpaintSuccessResponse, EnqueueInpaintImageErrorType> {
info!("enqueue_image_inpaint_command called; model: {:?}, image_media_token: {:?}, prompt: {:?}",
&request.model, &request.image_media_token, &request.prompt);
let result = handle_request(
&request,
&app,
&app_data_root,
&app_env_configs,
&provider_priority_store,
&task_database,
&storyteller_creds_manager,
&fal_creds_manager,
&fal_task_queue,
&sora_creds_manager,
&sora_task_queue,
).await;
match result {
Err(err) => {
error!("Error enqueuing inpaint image: {:?}", err);
// TODO: Derive from err. Make service provider optional.
let event = GenerationEnqueueFailureEvent {
action: GenerationAction::GenerateImage,
service: GenerationServiceProvider::Artcraft, // FIXME: This is wrong.
model: None,
reason: None,
};
if let Err(err) = event.send(&app) {
error!("Failed to emit event: {:?}", err); // Fail open.
}
Err(err.to_tauri_response())
}
Ok(event) => {
let event = GenerationEnqueueSuccessEvent {
action: event.to_frontend_event_action(),
service: event.to_frontend_event_service(),
model: event.model,
};
if let Err(err) = event.send(&app) {
error!("Failed to emit event: {:?}", err); // Fail open.
}
Ok(EnqueueImageInpaintSuccessResponse {}.into())
}
}
}
pub async fn handle_request(
request: &EnqueueInpaintImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
app_env_configs: &AppEnvConfigs,
provider_priority_store: &ProviderPriorityStore,
task_database: &TaskDatabase,
storyteller_creds_manager: &StorytellerCredentialManager,
fal_creds_manager: &FalCredentialManager,
fal_task_queue: &FalTaskQueue,
sora_creds_manager: &SoraCredentialManager,
sora_task_queue: &SoraTaskQueue,
) -> Result<TaskEnqueueSuccess, InternalImageInpaintError> {
let success_event= match request.model {
None => {
return Err(InternalImageInpaintError::NoModelSpecified)
}
Some(ImageInpaintModel::FluxPro1) => {
handle_flux_pro_1_inpaint(
request,
app,
app_data_root,
app_env_configs,
provider_priority_store,
storyteller_creds_manager,
fal_creds_manager,
fal_task_queue,
sora_creds_manager,
sora_task_queue,
).await?
}
};
let result = success_event
.insert_into_task_database_with_frontend_payload(
task_database,
request.frontend_caller,
request.frontend_subscriber_id.as_deref(),
request.frontend_subscriber_payload.as_deref()
)
.await;
if let Err(err) = result {
error!("Failed to create task in database: {:?}", err);
// NB: Fail open, but find a way to flag this.
}
Ok(success_event)
}
@@ -0,0 +1,128 @@
use crate::core::commands::enqueue::image_inpaint::enqueue_image_inpaint_command::EnqueueInpaintImageErrorType;
use crate::core::commands::response::failure_response_wrapper::{CommandErrorResponseWrapper, CommandErrorStatus};
use errors::AnyhowError;
use serde::Serialize;
use storyteller_client::error::storyteller_error::StorytellerError;
#[derive(Debug)]
pub enum InternalImageInpaintError {
/// Request did not specify a model.
NoModelSpecified,
/// No provider is configured for the model type.
NoProviderAvailable,
/// A source image was not provided
NoSourceImageSpecified,
/// A mask image was not provided
NoMaskImageSpecified,
/// Both mask image media token and raw bytes were supplied.
MaskMediaTokenAndBytesSupplied,
/// Mask image has an unknown MIME type.
CouldNotDetermineMaskMimeType,
/// Could not encode the mask image to PNG.
CouldNotEncodeMask,
/// No storyteller credentials are set.
NeedsStorytellerCredentials,
/// An invalid number of images was requested.
InvalidNumberOfRequestedImages {
min: u32,
max: u32,
requested: u32,
},
/// An invalid number of input images was requested.
InvalidNumberOfInputImages {
min: u32,
max: u32,
requested: u32,
},
AnyhowError(AnyhowError),
StorytellerError(StorytellerError),
}
impl From<AnyhowError> for InternalImageInpaintError {
fn from(value: AnyhowError) -> Self {
Self::AnyhowError(value)
}
}
impl From<StorytellerError> for InternalImageInpaintError {
fn from(value: StorytellerError) -> Self {
Self::StorytellerError(value)
}
}
impl InternalImageInpaintError {
pub fn to_tauri_response<E: Serialize>(&self) -> CommandErrorResponseWrapper<EnqueueInpaintImageErrorType, E> {
let mut status = CommandErrorStatus::ServerError;
let mut error_type = EnqueueInpaintImageErrorType::ServerError;
let mut error_message = "A server error occurred. Please try again. If it continues, please tell our staff about the problem.".to_string();
match self {
InternalImageInpaintError::NoModelSpecified => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::ModelNotSpecified;
error_message = "No model specified for image generation".to_string();
}
InternalImageInpaintError::NoProviderAvailable => {
status = CommandErrorStatus::ServerError;
error_type = EnqueueInpaintImageErrorType::NoProviderAvailable;
error_message = "No configured provider available for image generation".to_string();
}
InternalImageInpaintError::NoSourceImageSpecified => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::NoSourceImageSpecified;
error_message = "No source image was provided".to_string();
}
InternalImageInpaintError::NoMaskImageSpecified => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::NoMaskImageSpecified;
error_message = "No mask image was provided".to_string();
}
InternalImageInpaintError::MaskMediaTokenAndBytesSupplied => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::MultipleMaskImagesSpecified;
error_message = "multiple mask images provided".to_string();
}
InternalImageInpaintError::CouldNotDetermineMaskMimeType => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::BadMaskImage;
error_message = "bad mask image (mime)".to_string();
}
InternalImageInpaintError::CouldNotEncodeMask => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::BadMaskImage;
error_message = "bad mask image (encode)".to_string();
}
InternalImageInpaintError::InvalidNumberOfRequestedImages { min, max, requested } => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::BadRequest;
error_message = format!("Invalid number of images requested ({}). Must be between {} and {}", requested, min, max);
}
InternalImageInpaintError::InvalidNumberOfInputImages { min, max, requested } => {
status = CommandErrorStatus::BadRequest;
error_type = EnqueueInpaintImageErrorType::BadRequest;
error_message = format!("Invalid number of input images ({}). Must be between {} and {}", requested, min, max);
}
InternalImageInpaintError::AnyhowError(_) => {}
InternalImageInpaintError::StorytellerError(_) => {}
InternalImageInpaintError::NeedsStorytellerCredentials => {}
}
CommandErrorResponseWrapper {
status,
error_message: Some(error_message.to_string()),
error_type: Some(error_type),
error_details: None,
}
}
}
@@ -0,0 +1,63 @@
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::EnqueueContextualEditImageCommand;
use crate::core::commands::enqueue::image_edit::errors::InternalContextualEditImageError;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_artcraft::handle_gpt_image_1_edit_artcraft;
use crate::core::commands::enqueue::image_edit::gpt_image_1::handle_gpt_image_1_edit_sora::handle_gpt_image_1_edit_sora;
use crate::core::commands::enqueue::image_inpaint::enqueue_image_inpaint_command::EnqueueInpaintImageCommand;
use crate::core::commands::enqueue::image_inpaint::errors::InternalImageInpaintError;
use crate::core::commands::enqueue::image_inpaint::flux_pro_1_inpaint::handle_flux_pro_1_inpaint_artcraft::handle_flux_pro_1_inpaint_artcraft;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::core::state::provider_priority::{Provider, ProviderPriorityStore};
use crate::services::fal::state::fal_credential_manager::FalCredentialManager;
use crate::services::fal::state::fal_task_queue::FalTaskQueue;
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use log::info;
use tauri::AppHandle;
pub(super) const MAX_IMAGES: usize = 10;
pub async fn handle_flux_pro_1_inpaint(
request: &EnqueueInpaintImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
app_env_configs: &AppEnvConfigs,
provider_priority_store: &ProviderPriorityStore,
storyteller_creds_manager: &StorytellerCredentialManager,
fal_creds_manager: &FalCredentialManager,
fal_task_queue: &FalTaskQueue,
sora_creds_manager: &SoraCredentialManager,
sora_task_queue: &SoraTaskQueue,
) -> Result<TaskEnqueueSuccess, InternalImageInpaintError> {
let priority = provider_priority_store.get_priority()?;
// TODO: Check if providers are available before proceeding.
info!("Providers by priority: {:?}", priority);
for provider in priority.iter() {
match provider {
Provider::Fal => {
// Fallthrough (for now)
}
Provider::Sora => {
// Fallthrough
}
Provider::Artcraft => {
info!("Dispatching flux pro 1 inpaint via Artcraft...");
return handle_flux_pro_1_inpaint_artcraft(
request,
app,
app_data_root,
app_env_configs,
storyteller_creds_manager
).await;
}
}
}
Err(InternalImageInpaintError::NoProviderAvailable)
}
@@ -0,0 +1,181 @@
use crate::core::commands::enqueue::image::enqueue_text_to_image_command::EnqueueTextToImageRequest;
use crate::core::commands::enqueue::image::internal_image_error::InternalImageError;
use crate::core::commands::enqueue::image_bg_removal::enqueue_image_bg_removal_command::EnqueueImageBgRemovalCommand;
use crate::core::commands::enqueue::image_bg_removal::errors::InternalBgRemovalError;
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::{EditImageQuality, EditImageSize, EnqueueContextualEditImageCommand};
use crate::core::commands::enqueue::image_inpaint::enqueue_image_inpaint_command::EnqueueInpaintImageCommand;
use crate::core::commands::enqueue::image_inpaint::errors::InternalImageInpaintError;
use crate::core::commands::enqueue::task_enqueue_success::TaskEnqueueSuccess;
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use crate::core::events::generation_events::generation_enqueue_failure_event::GenerationEnqueueFailureEvent;
use crate::core::model::contextual_image_edit_models::ContextualImageEditModel;
use crate::core::model::image_models::ImageModel;
use crate::core::state::app_env_configs::app_env_configs::AppEnvConfigs;
use crate::core::state::data_dir::app_data_root::AppDataRoot;
use crate::core::state::provider_priority::ProviderPriorityStore;
use crate::core::utils::save_base64_image_to_temp_dir::save_base64_image_to_temp_dir;
use crate::services::fal::state::fal_credential_manager::FalCredentialManager;
use crate::services::fal::state::fal_task_queue::FalTaskQueue;
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use anyhow::anyhow;
use artcraft_api_defs::generate::image::edit::gpt_image_1_edit_image::{GptImage1EditImageImageQuality, GptImage1EditImageImageSize, GptImage1EditImageNumImages, GptImage1EditImageRequest};
use artcraft_api_defs::generate::image::generate_flux_1_dev_text_to_image::GenerateFlux1DevTextToImageRequest;
use artcraft_api_defs::generate::image::generate_flux_1_schnell_text_to_image::GenerateFlux1SchnellTextToImageRequest;
use artcraft_api_defs::generate::image::generate_flux_pro_11_text_to_image::GenerateFluxPro11TextToImageRequest;
use artcraft_api_defs::generate::image::generate_flux_pro_11_ultra_text_to_image::GenerateFluxPro11UltraTextToImageRequest;
use artcraft_api_defs::generate::image::inpaint::flux_pro_1_inpaint_image::{FluxPro1InpaintImageNumImages, FluxPro1InpaintImageRequest};
use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_type::TaskType;
use fal_client::requests::queue::image_gen::enqueue_flux_pro_11_ultra_text_to_image::{enqueue_flux_pro_11_ultra_text_to_image, FluxPro11UltraTextToImageArgs};
use fal_client::requests::webhook::image::enqueue_gpt_image_1_edit_image_webhook::GptEditImageQuality;
use idempotency::uuid::generate_random_uuid;
use images::encoding::image_bytes_to_png_bytes::image_bytes_to_png_bytes;
use images::encoding::image_bytes_to_png_bytes_with_dimensions::image_bytes_to_png_bytes_with_dimensions;
use images::mask_images::normalize_image_bytes_to_flux_mask::normalize_image_bytes_to_flux_mask;
use log::{error, info};
use mimetypes::mimetype_info::mimetype_info::MimetypeInfo;
use storyteller_client::credentials::storyteller_credential_set::StorytellerCredentialSet;
use storyteller_client::generate::image::edit::gpt_image_1_edit_image::gpt_image_1_edit_image;
use storyteller_client::generate::image::generate_flux_1_dev_text_to_image::generate_flux_1_dev_text_to_image;
use storyteller_client::generate::image::generate_flux_1_schnell_text_to_image::generate_flux_1_schnell_text_to_image;
use storyteller_client::generate::image::generate_flux_pro_11_text_to_image::generate_flux_pro_11_text_to_image;
use storyteller_client::generate::image::generate_flux_pro_11_ultra_text_to_image::generate_flux_pro_11_ultra_text_to_image;
use storyteller_client::generate::image::inpaint::flux_pro_1_inpaint_image::flux_pro_1_inpaint_image;
use storyteller_client::media_files::get_media_file::get_media_file;
use storyteller_client::media_files::upload_image_media_file_from_bytes::{upload_image_media_file_from_bytes, ImageType, UploadImageBytesArgs};
use storyteller_client::media_files::upload_image_media_file_from_file::upload_image_media_file_from_file;
use tauri::AppHandle;
use tokens::tokens::media_files::MediaFileToken;
pub async fn handle_flux_pro_1_inpaint_artcraft(
request: &EnqueueInpaintImageCommand,
app: &AppHandle,
app_data_root: &AppDataRoot,
app_env_configs: &AppEnvConfigs,
storyteller_creds_manager: &StorytellerCredentialManager,
) -> Result<TaskEnqueueSuccess, InternalImageInpaintError> {
let creds = match storyteller_creds_manager.get_credentials()? {
Some(creds) => creds,
None => {
return Err(InternalImageInpaintError::NeedsStorytellerCredentials);
},
};
let image_media_token = match &request.image_media_token {
Some(token) => token.clone(),
None => {
return Err(InternalImageInpaintError::NoSourceImageSpecified);
},
};
//let image_media_file = get_media_file(
// &app_env_configs.storyteller_host,
// &image_media_token,
//).await.map_err(|err| {
// error!("Failed to get media file for image: {:?}", err);
// InternalImageInpaintError::StorytellerError(err)
//})?;
let mask_media_token = get_mask(
request,
app_env_configs,
&creds,
).await?;
info!("Calling Artcraft flux pro 1 inpaint ...");
let uuid_idempotency_token = generate_random_uuid();
let num_images = match request.image_count {
None => None,
Some(1) => Some(FluxPro1InpaintImageNumImages::One),
Some(2) => Some(FluxPro1InpaintImageNumImages::Two),
Some(3) => Some(FluxPro1InpaintImageNumImages::Three),
Some(4) => Some(FluxPro1InpaintImageNumImages::Four),
Some(other) => {
return Err(InternalImageInpaintError::InvalidNumberOfRequestedImages {
min: 1,
max: 4,
requested: other,
});
},
};
let request = FluxPro1InpaintImageRequest {
uuid_idempotency_token,
prompt: Some(request.prompt.clone()),
image_media_token,
mask_media_token,
num_images,
};
let result = flux_pro_1_inpaint_image(
&app_env_configs.storyteller_host,
Some(&creds),
request,
).await;
let job_id = match result {
Ok(enqueued) => {
// TODO(bt,2025-07-05): Enqueue job token?
info!("Successfully enqueued Artcraft flux pro 1 inpaint. Job token: {}",
enqueued.inference_job_token);
enqueued.inference_job_token
}
Err(err) => {
error!("Failed to use Artcraft flux pro 1 inpaint: {:?}", err);
return Err(InternalImageInpaintError::StorytellerError(err));
}
};
Ok(TaskEnqueueSuccess {
provider: GenerationProvider::Artcraft,
model: Some(GenerationModel::FluxProKontextMax),
provider_job_id: Some(job_id.to_string()),
task_type: TaskType::ImageGeneration,
})
}
async fn get_mask(
request: &EnqueueInpaintImageCommand,
app_env_configs: &AppEnvConfigs,
storyteller_creds: &StorytellerCredentialSet,
) -> Result<MediaFileToken, InternalImageInpaintError> {
if request.mask_image_media_token.is_some() && request.mask_image_raw_bytes.is_some() {
return Err(InternalImageInpaintError::MaskMediaTokenAndBytesSupplied);
}
if let Some(token) = request.mask_image_media_token.as_ref() {
return Ok(token.clone());
};
let image_bytes = request.mask_image_raw_bytes.as_ref()
.ok_or(InternalImageInpaintError::NoMaskImageSpecified)?;
let image_bytes = normalize_image_bytes_to_flux_mask(image_bytes)
.map_err(|err| {
error!("Failed to convert image bytes to png: {:?}", err);
InternalImageInpaintError::CouldNotEncodeMask
})?;
info!("Uploading image media file from bytes...");
let result = upload_image_media_file_from_bytes(UploadImageBytesArgs {
api_host: &app_env_configs.storyteller_host,
maybe_creds: Some(&storyteller_creds),
image_bytes: image_bytes.0,
image_type: ImageType::Png,
is_intermediate_system_file: true,
}).await
.map_err(|err| {
error!("Failed to upload image media file: {:?}", err);
InternalImageInpaintError::StorytellerError(err)
})?;
Ok(result.media_file_token)
}
@@ -0,0 +1,2 @@
pub (super) mod handle_flux_pro_1_inpaint;
mod handle_flux_pro_1_inpaint_artcraft;
@@ -0,0 +1,3 @@
pub mod enqueue_image_inpaint_command;
pub mod errors;
mod flux_pro_1_inpaint;
@@ -1,6 +1,7 @@
pub mod image;
pub mod image_bg_removal;
pub mod image_edit;
pub mod task_enqueue_success;
pub mod image_inpaint;
pub mod object;
pub mod task_enqueue_success;
pub mod video;
@@ -4,6 +4,7 @@ use enums::common::generation_provider::GenerationProvider;
use enums::tauri::tasks::task_model_type::TaskModelType;
use enums::tauri::tasks::task_status::TaskStatus;
use enums::tauri::tasks::task_type::TaskType;
use enums::tauri::ux::tauri_command_caller::TauriCommandCaller;
use sqlite_tasks::error::SqliteTasksError;
use sqlite_tasks::queries::create_task::{create_task, CreateTaskArgs};
use tokens::tokens::sqlite::tasks::TaskId;
@@ -35,13 +36,31 @@ impl TaskEnqueueSuccess{
}
pub async fn insert_into_task_database(&self, task_database: &TaskDatabase) -> Result<TaskId, SqliteTasksError> {
self.insert_into_task_database_with_frontend_payload(
task_database,
None,
None,
None,
).await
}
// TODO: This belongs somewhere else, not as a method of an event struct.
pub async fn insert_into_task_database_with_frontend_payload(
&self,
task_database: &TaskDatabase,
frontend_caller: Option<TauriCommandCaller>,
frontend_subscriber_id: Option<&str>,
frontend_subscriber_payload: Option<&str>,
) -> Result<TaskId, SqliteTasksError> {
// TODO: Move this mapping elsewhere, or remove the other models.
let model_type = match self.model {
None => None,
Some(GenerationModel::Flux1Dev) => Some(TaskModelType::Flux1Dev),
Some(GenerationModel::Flux1Schnell) => Some(TaskModelType::Flux1Schnell),
Some(GenerationModel::FluxPro1) => Some(TaskModelType::FluxPro1), // NB: This is for inpainting.
Some(GenerationModel::FluxPro11) => Some(TaskModelType::FluxPro11),
Some(GenerationModel::FluxPro11Ultra) => Some(TaskModelType::FluxPro11Ultra),
Some(GenerationModel::FluxProKontextMax) => Some(TaskModelType::FluxProKontextMax),
Some(GenerationModel::GptImage1) => Some(TaskModelType::GptImage1),
Some(GenerationModel::Recraft3) => Some(TaskModelType::Recraft3),
Some(GenerationModel::Kling21Pro) => Some(TaskModelType::Kling21Pro),
@@ -61,23 +80,12 @@ impl TaskEnqueueSuccess{
db: task_database.get_connection(),
status: TaskStatus::Pending,
task_type: self.task_type,
model_type: model_type,
model_type,
provider: self.provider,
provider_job_id: self.provider_job_id.as_deref(),
frontend_subscriber_id: None,
frontend_subscriber_payload: None,
frontend_caller,
frontend_subscriber_id,
frontend_subscriber_payload,
}).await
}
// pub fn tauri_event_model(&self) -> GenerationModel {
// match self.model {
// ImageModel::Flux1Dev => GenerationModel::Flux1Dev,
// ImageModel::Flux1Schnell => GenerationModel::Flux1Schnell,
// ImageModel::FluxPro11 => GenerationModel::FluxPro11,
// ImageModel::FluxPro11Ultra => GenerationModel::FluxPro11Ultra,
// ImageModel::GptImage1 => GenerationModel::GptImage1,
// ImageModel::Recraft3 => GenerationModel::Recraft3,
// }
// }
}
@@ -0,0 +1,43 @@
use futures::TryFutureExt;
use log::{error, info};
use reqwest::Client;
use tauri::ipc::Response;
/// Request a URL and load it without worrying about CORS.
#[tauri::command]
pub async fn load_without_cors_command(url: String) -> Result<Response, String> {
info!("load_without_cors_command for URL: {}", url);
// TODO(bt,2025-07-22): Make sure the URL is valid and safe to fetch. Check an allowlist.
// TODO(bt,2025-07-22): Should we cache clients so we don't need to SSL handshake every time?
let client = Client::builder()
.gzip(true)
.build()
.map_err(|e| {
error!("Failed to create HTTP client: {:?}", e);
format!("Failed to create HTTP client: {:?}", e)
})?;
let response = client.get(url.clone())
.send()
.await
.map_err(|e| {
error!("Failed to send HTTP request: {:?}", e);
format!("Failed to send HTTP request: {:?}", e)
})?;
if response.status() != 200 {
return Err(format!("Failed to fetch URL: {}. Status: {}", url, response.status()));
}
let bytes = response.bytes()
.await
.map_err(|e| {
error!("Failed to read response bytes: {:?}", e);
format!("Failed to read response bytes: {:?}", e)
})?;
Ok(Response::new(bytes.to_vec()))
}
@@ -2,6 +2,7 @@ pub mod app_preferences;
pub mod enqueue;
pub mod flip_image;
pub mod get_app_info_command;
pub mod load_without_cors_command;
pub mod platform_info_command;
pub mod providers;
pub mod response;
@@ -1,4 +1,5 @@
use crate::core::events::sendable_event_error::SendableEventError;
use enums::tauri::ux::tauri_event_name::TauriEventName;
use log::info;
use serde::Serialize;
use std::fmt::Debug;
@@ -29,7 +30,7 @@ struct BasicEventWrapper<T: Serialize + Debug> {
pub trait BasicSendableEvent : Clone + Debug + Serialize {
/// This is the name of the event that the frontend subscribes to.
const FRONTEND_EVENT_NAME: &'static str;
const FRONTEND_EVENT_NAME: TauriEventName;
/// This is the status of the event: Success, Failure, etc.
const EVENT_STATUS: BasicEventStatus;
@@ -41,8 +42,8 @@ pub trait BasicSendableEvent : Clone + Debug + Serialize {
status: Self::EVENT_STATUS,
data: self.clone(),
};
info!("Sending event to frontend: {} ; payload = {:?}", Self::FRONTEND_EVENT_NAME, wrapped);
let result = app.emit(Self::FRONTEND_EVENT_NAME, wrapped);
info!("Sending event to frontend: {} ; payload = {:?}", Self::FRONTEND_EVENT_NAME.to_str(), wrapped);
let result = app.emit(Self::FRONTEND_EVENT_NAME.to_str(), wrapped);
if let Err(err) = result {
return Err(SendableEventError::from(err));
}
@@ -0,0 +1,19 @@
use crate::core::events::basic_sendable_event_trait::{BasicEventStatus, BasicSendableEvent};
use enums::tauri::ux::tauri_event_name::TauriEventName;
use serde_derive::Serialize;
use tokens::tokens::media_files::MediaFileToken;
use url::Url;
#[derive(Clone, Debug, Serialize)]
#[serde(rename_all = "snake_case")]
pub struct CanvasBackgroundRemovalCompleteEvent {
pub media_token: MediaFileToken,
pub image_cdn_url: Url,
pub maybe_frontend_subscriber_id: Option<String>,
pub maybe_frontend_subscriber_payload: Option<String>,
}
impl BasicSendableEvent for CanvasBackgroundRemovalCompleteEvent {
const FRONTEND_EVENT_NAME: TauriEventName = TauriEventName::CanvasBgRemovedEvent;
const EVENT_STATUS: BasicEventStatus = BasicEventStatus::Success;
}
@@ -0,0 +1 @@
pub mod canvas_background_removal_complete_event;
@@ -15,10 +15,14 @@ pub enum GenerationModel {
Flux1Dev,
#[serde(rename = "flux_1_schnell")]
Flux1Schnell,
#[serde(rename = "flux_pro_1")]
FluxPro1,
#[serde(rename = "flux_pro_1.1")]
FluxPro11,
#[serde(rename = "flux_pro_1.1_ultra")]
FluxPro11Ultra,
#[serde(rename = "flux_pro_kontext_max")]
FluxProKontextMax,
#[serde(rename = "gpt_image_1")]
GptImage1,
#[serde(rename = "hunyuan_3d_2_0")]
@@ -1,5 +1,6 @@
use crate::core::events::basic_sendable_event_trait::{BasicEventStatus, BasicSendableEvent};
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use enums::tauri::ux::tauri_event_name::TauriEventName;
use serde_derive::Serialize;
#[derive(Clone, Debug, Serialize)]
@@ -11,6 +12,6 @@ pub struct GenerationCompleteEvent {
}
impl BasicSendableEvent for GenerationCompleteEvent {
const FRONTEND_EVENT_NAME: &'static str = "generation-complete-event";
const FRONTEND_EVENT_NAME: TauriEventName = TauriEventName::GenerationCompleteEvent;
const EVENT_STATUS: BasicEventStatus = BasicEventStatus::Success;
}
@@ -1,5 +1,6 @@
use crate::core::events::basic_sendable_event_trait::{BasicEventStatus, BasicSendableEvent};
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use enums::tauri::ux::tauri_event_name::TauriEventName;
use serde_derive::Serialize;
#[derive(Clone, Debug, Serialize)]
@@ -14,7 +15,7 @@ pub struct GenerationEnqueueFailureEvent {
}
impl BasicSendableEvent for GenerationEnqueueFailureEvent {
const FRONTEND_EVENT_NAME: &'static str = "generation-enqueue-failure-event";
const FRONTEND_EVENT_NAME: TauriEventName = TauriEventName::GenerationEnqueueFailureEvent;
const EVENT_STATUS: BasicEventStatus = BasicEventStatus::Failure;
}
@@ -1,5 +1,6 @@
use crate::core::events::basic_sendable_event_trait::{BasicEventStatus, BasicSendableEvent};
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use enums::tauri::ux::tauri_event_name::TauriEventName;
use serde_derive::Serialize;
#[derive(Clone, Debug, Serialize)]
@@ -11,6 +12,6 @@ pub struct GenerationEnqueueSuccessEvent {
}
impl BasicSendableEvent for GenerationEnqueueSuccessEvent {
const FRONTEND_EVENT_NAME: &'static str = "generation-enqueue-success-event";
const FRONTEND_EVENT_NAME: TauriEventName = TauriEventName::GenerationEnqueueSuccessEvent;
const EVENT_STATUS: BasicEventStatus = BasicEventStatus::Success;
}
@@ -1,5 +1,6 @@
use crate::core::events::basic_sendable_event_trait::{BasicEventStatus, BasicSendableEvent};
use crate::core::events::generation_events::common::{GenerationAction, GenerationModel, GenerationServiceProvider};
use enums::tauri::ux::tauri_event_name::TauriEventName;
use serde_derive::Serialize;
#[derive(Clone, Debug, Serialize)]
@@ -14,6 +15,6 @@ pub struct GenerationFailedEvent {
}
impl BasicSendableEvent for GenerationFailedEvent {
const FRONTEND_EVENT_NAME: &'static str = "generation-failed-event";
const FRONTEND_EVENT_NAME: TauriEventName = TauriEventName::GenerationFailedEvent;
const EVENT_STATUS: BasicEventStatus = BasicEventStatus::Failure;
}
@@ -1,4 +1,5 @@
pub mod basic_sendable_event_trait;
pub mod generation_events;
pub mod sendable_event_error;
pub mod sendable_event_trait;
pub mod sendable_event_trait;
pub mod functional_events;
@@ -7,6 +7,9 @@ use serde_derive::Deserialize;
pub enum ContextualImageEditModel {
#[serde(rename = "gpt_image_1")]
GptImage1,
#[serde(rename = "flux_pro_kontext_max")]
FluxProKontextMax,
// TODO: Flux Kontext models.
}
+4
View File
@@ -7,11 +7,13 @@ use crate::core::commands::app_preferences::get_app_preferences_command::get_app
use crate::core::commands::app_preferences::update_app_preference_command::update_app_preferences_command;
use crate::core::commands::enqueue::image::enqueue_text_to_image_command::enqueue_text_to_image_command;
use crate::core::commands::enqueue::image_bg_removal::enqueue_image_bg_removal_command::enqueue_image_bg_removal_command;
use crate::core::commands::enqueue::image_inpaint::enqueue_image_inpaint_command::enqueue_image_inpaint_command;
use crate::core::commands::enqueue::image_edit::enqueue_contextual_edit_image_command::enqueue_contextual_edit_image_command;
use crate::core::commands::enqueue::object::enqueue_image_to_3d_object_command::enqueue_image_to_3d_object_command;
use crate::core::commands::enqueue::video::enqueue_image_to_video_command::enqueue_image_to_video_command;
use crate::core::commands::flip_image::flip_image;
use crate::core::commands::get_app_info_command::get_app_info_command;
use crate::core::commands::load_without_cors_command::load_without_cors_command;
use crate::core::commands::platform_info_command::platform_info_command;
use crate::core::commands::providers::get_provider_order_command::get_provider_order_command;
use crate::core::commands::providers::set_provider_order_command::set_provider_order_command;
@@ -143,6 +145,7 @@ pub fn run() {
check_sora_session_command,
enqueue_contextual_edit_image_command,
enqueue_image_bg_removal_command,
enqueue_image_inpaint_command,
enqueue_image_to_3d_object_command,
enqueue_image_to_video_command,
enqueue_text_to_image_command,
@@ -154,6 +157,7 @@ pub fn run() {
get_app_preferences_command,
get_fal_api_key_command,
get_provider_order_command,
load_without_cors_command,
open_sora_login_command,
platform_info_command,
set_fal_api_key_command,
@@ -29,7 +29,7 @@ use reqwest::Url;
use serde_derive::{Deserialize, Serialize};
use storyteller_client::error::storyteller_error::StorytellerError;
use storyteller_client::media_files::get_media_file::{get_media_file, GetMediaFileSuccessResponse};
use storyteller_client::media_files::upload_image_media_file_from_file::upload_image_media_file_from_file;
use storyteller_client::media_files::upload_image_media_file_from_file::{upload_image_media_file_from_file, UploadImageFromFileArgs};
use storyteller_client::utils::api_host::ApiHost;
use tauri::{AppHandle, Manager, State};
use tokens::tokens::media_files::MediaFileToken;
@@ -256,11 +256,12 @@ pub async fn remove_background(
info!("Uploading image media file...");
let upload_result = upload_image_media_file_from_file(
&app_env_configs.storyteller_host,
Some(&creds),
result_filename,
).await?;
let upload_result = upload_image_media_file_from_file(UploadImageFromFileArgs {
api_host: &app_env_configs.storyteller_host,
maybe_creds: Some(&creds),
path: result_filename,
is_intermediate_system_file: true, // NB: Probably not essential to keep this.
}).await?;
// TODO: Don't re-request to simply build MediaLinks (or CDN URL). Get those from the upload API in one turn.
info!("Re-requesting media file...");
@@ -17,7 +17,7 @@ use reqwest::Url;
use std::fs::File;
use std::io::Write;
use std::path::PathBuf;
use storyteller_client::media_files::upload_image_media_file_from_file::upload_image_media_file_from_file;
use storyteller_client::media_files::upload_image_media_file_from_file::{upload_image_media_file_from_file, UploadImageFromFileArgs};
use tauri::AppHandle;
use tempdir::TempDir;
@@ -134,12 +134,14 @@ async fn polling_loop(
let download_path = download_generation(generation, &app_data_root).await?;
info!("Uploading to backend...");
let result = upload_image_media_file_from_file(
&app_env_configs.storyteller_host,
Some(&creds),
download_path
).await?;
let result = upload_image_media_file_from_file(UploadImageFromFileArgs {
api_host: &app_env_configs.storyteller_host,
maybe_creds: Some(&creds),
path: download_path,
is_intermediate_system_file: false,
}).await?;
info!("Uploaded to API backend: {:?}", result.media_file_token);
let event = GenerationCompleteEvent {
@@ -0,0 +1,48 @@
use crate::core::events::basic_sendable_event_trait::BasicSendableEvent;
use crate::core::events::functional_events::canvas_background_removal_complete_event::CanvasBackgroundRemovalCompleteEvent;
use crate::core::events::generation_events::generation_complete_event::GenerationCompleteEvent;
use artcraft_api_defs::jobs::list_session_jobs::ListSessionJobsItem;
use enums::tauri::tasks::task_type::TaskType;
use enums::tauri::ux::tauri_command_caller::TauriCommandCaller;
use errors::AnyhowResult;
use log::error;
use sqlite_tasks::queries::list_tasks_by_provider_and_tokens::{list_tasks_by_provider_and_tokens, ListTasksArgs, Task};
use tokens::tokens::media_files::MediaFileToken;
pub async fn maybe_send_background_removal_complete_event(
app: &tauri::AppHandle,
task: &Task,
job: &ListSessionJobsItem,
) -> AnyhowResult<()> {
match task.task_type {
TaskType::BackgroundRemoval => {} // NB: Fall-through
_ => return Ok(()),
}
match task.frontend_caller {
Some(TauriCommandCaller::Canvas) => {} // NB: Fall-through
_ => return Ok(()),
}
let result = match job.maybe_result {
Some(ref res) => res,
None => {
error!("Job result is None for task: {:?}", task);
return Ok(()); // No result, nothing to do
},
};
let event = CanvasBackgroundRemovalCompleteEvent {
media_token: MediaFileToken::new_from_str(&result.entity_token),
image_cdn_url: result.media_links.cdn_url.clone(),
maybe_frontend_subscriber_id: task.frontend_subscriber_id.clone(),
maybe_frontend_subscriber_payload: task.frontend_subscriber_payload.clone(),
};
if let Err(err) = event.send(&app) {
error!("Failed to send CanvasBackgroundRemovalCompleteEvent: {:?}", err); // Fail open
}
Ok(())
}
@@ -0,0 +1 @@
pub mod maybe_send_background_removal_complete_event;
@@ -1 +1,2 @@
pub mod events;
pub mod storyteller_task_polling_thread;
@@ -12,10 +12,12 @@ use crate::core::utils::enum_conversion::task_type::to_generation_action;
use crate::services::sora::state::sora_credential_manager::SoraCredentialManager;
use crate::services::sora::state::sora_task_queue::SoraTaskQueue;
use crate::services::storyteller::state::storyteller_credential_manager::StorytellerCredentialManager;
use crate::services::storyteller::threads::events::maybe_send_background_removal_complete_event::maybe_send_background_removal_complete_event;
use anyhow::anyhow;
use enums::common::generation_provider::GenerationProvider;
use enums::common::job_status_plus::JobStatusPlus;
use enums::tauri::tasks::task_status::TaskStatus;
use enums::tauri::tasks::task_type::TaskType;
use errors::AnyhowResult;
use log::{error, info};
use reqwest::Url;
@@ -137,7 +139,17 @@ async fn polling_loop(
if !updated {
continue; // If anything breaks with queries, don't spam events.
}
let result = maybe_send_background_removal_complete_event(
&app_handle,
&task,
&job,
).await;
if let Err(err) = result {
error!("Failed to send background removal complete event: {:?}", err);
}
let service = to_generation_service_provider(task.provider);
let action = to_generation_action(task.task_type);
+1 -1
View File
@@ -26,7 +26,7 @@ errors = { workspace = true}
mimetypes = { workspace = true }
# External
image = "0.25.6"
image = { version = "0.25.6" , features = ["jpeg", "png", "tiff", "webp"] }
[dev-dependencies]
anyhow = { workspace = true }
@@ -0,0 +1,18 @@
use crate::error::ImagesError;
use image::{ImageFormat, ImageReader};
use std::io::Cursor;
pub fn image_bytes_to_png_bytes(
arbitrary_image_bytes: &[u8],
) -> Result<Vec<u8>, ImagesError> {
let reader = ImageReader::new(Cursor::new(arbitrary_image_bytes));
let image = reader
.with_guessed_format()? // NB: Can raise IoError.
.decode()?;
let mut output_bytes: Vec<u8> = Vec::new();
image.write_to(&mut Cursor::new(&mut output_bytes), ImageFormat::Png)?;
Ok(output_bytes)
}
@@ -0,0 +1,29 @@
use std::io::Cursor;
use image::{ImageFormat, ImageReader};
use crate::error::ImagesError;
pub struct PngBytesWithDimensions {
pub png_bytes: Vec<u8>,
pub width: u32,
pub height: u32,
}
pub fn image_bytes_to_png_bytes_with_dimensions(
arbitrary_image_bytes: &[u8],
) -> Result<PngBytesWithDimensions, ImagesError> {
let reader = ImageReader::new(Cursor::new(arbitrary_image_bytes));
let image = reader
.with_guessed_format()? // NB: Can raise IoError.
.decode()?;
let mut output_bytes: Vec<u8> = Vec::new();
image.write_to(&mut Cursor::new(&mut output_bytes), ImageFormat::Png)?;
Ok(PngBytesWithDimensions {
png_bytes: output_bytes,
width: image.width(),
height: image.height(),
})
}
@@ -0,0 +1,3 @@
pub mod image_bytes_to_png_bytes;
pub mod image_bytes_to_png_bytes_with_dimensions;
pub mod webp_bytes_to_png_bytes;
@@ -0,0 +1,21 @@
use crate::error::ImagesError;
use image::{ImageFormat, ImageReader};
use std::io::Cursor;
pub fn webp_bytes_to_png_bytes(
webp_bytes: &[u8],
) -> Result<Vec<u8>, ImagesError> {
let mut reader = ImageReader::new(Cursor::new(webp_bytes));
reader.set_format(ImageFormat::WebP); // Default to WebP format (as fallback).
let image = reader
.with_guessed_format()? // NB: Can raise IoError.
.decode()?;
let mut output_bytes: Vec<u8> = Vec::new();
image.write_to(&mut Cursor::new(&mut output_bytes), ImageFormat::Png)?;
Ok(output_bytes)
}
+31
View File
@@ -0,0 +1,31 @@
use std::error::Error;
use std::fmt::{Display, Formatter};
#[derive(Debug)]
pub enum ImagesError {
IoError(std::io::Error),
ImageError(image::ImageError),
}
impl Error for ImagesError {}
impl Display for ImagesError {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
match self {
ImagesError::IoError(err) => write!(f, "IO Error: {}", err),
ImagesError::ImageError(err) => write!(f, "Image Error: {}", err),
}
}
}
impl From<std::io::Error> for ImagesError {
fn from(err: std::io::Error) -> Self {
ImagesError::IoError(err)
}
}
impl From<image::ImageError> for ImagesError {
fn from(err: image::ImageError) -> Self {
ImagesError::ImageError(err)
}
}
+3
View File
@@ -23,7 +23,10 @@
// Re-export image to everyone importing this library
pub use image;
pub mod encoding;
pub mod error;
pub mod image_info;
pub mod mask_images;
pub mod resize_image_file_preserving_aspect;
pub mod resize_preserving_aspect;
@@ -0,0 +1 @@
pub mod normalize_image_bytes_to_flux_mask;
@@ -0,0 +1,40 @@
use crate::error::ImagesError;
use image::{GenericImage, GenericImageView, ImageFormat, ImageReader, Rgba};
use std::io::Cursor;
pub struct PngBytes(pub Vec<u8>);
/// Normalize arbitrary image bytes to a PNG format image.
/// Make sure the bitmap is in the correct mask format.
pub fn normalize_image_bytes_to_flux_mask(
arbitrary_image_bytes: &[u8],
) -> Result<PngBytes, ImagesError> {
let reader = ImageReader::new(Cursor::new(arbitrary_image_bytes));
let mut image = reader
.with_guessed_format()? // NB: Can raise IoError.
.decode()?;
let (width, height) = image.dimensions();
for y in 0..height {
for x in 0..width {
let rgba_pixel = image.get_pixel(x, y);
if rgba_pixel[3] == 0 {
// Alpha pixel is transparent
// Set to black. Mask ignore region.
image.put_pixel(x, y, Rgba([0, 0, 0, 255]));
} else {
// Set to white. Mask interest region.
image.put_pixel(x, y, Rgba([255, 255, 255, 255]));
}
}
}
let mut output_bytes: Vec<u8> = Vec::new();
image.write_to(&mut Cursor::new(&mut output_bytes), ImageFormat::Png)?;
Ok(PngBytes(output_bytes))
}

Some files were not shown because too many files have changed in this diff Show More