bump

package-lock.json

@@ -8,9 +8,9 @@
       "name": "@aitube/website",
       "version": "0.0.0",
       "dependencies": {
-        "@aitube/clap": "0.0.15",
-        "@aitube/client": "0.0.20",
-        "@aitube/engine": "0.0.5",
+        "@aitube/clap": "0.0.16",
+        "@aitube/client": "0.0.21",
+        "@aitube/engine": "0.0.6",
         "@huggingface/hub": "0.12.3-oauth",
         "@huggingface/inference": "^2.6.7",
         "@jcoreio/async-throttle": "^1.6.0",
@@ -118,9 +118,9 @@
       }
     },
     "node_modules/@aitube/clap": {
-      "version": "0.0.15",
-      "resolved": "https://registry.npmjs.org/@aitube/clap/-/clap-0.0.15.tgz",
-      "integrity": "sha512-mhCbUOMQscr37kb5d5A6QGsw1Bi7W+NdyoGg48CHXpyH6NKP24K3nxx75d6nhwiL8MTQG9+fkYKMhIsZBXOwfQ==",
+      "version": "0.0.16",
+      "resolved": "https://registry.npmjs.org/@aitube/clap/-/clap-0.0.16.tgz",
+      "integrity": "sha512-EcBu4gbc8Kx58rkMmLjh0uyCWVR4cSgWqALlQ50C1GbHRg/r81gDET6faWeos14ZGrtg4B0CJv8WUTIDE54pjg==",
       "dependencies": {
         "pure-uuid": "^1.8.1",
         "yaml": "^2.4.1"
@@ -130,22 +130,22 @@
       }
     },
     "node_modules/@aitube/client": {
-      "version": "0.0.20",
-      "resolved": "https://registry.npmjs.org/@aitube/client/-/client-0.0.20.tgz",
-      "integrity": "sha512-MiWsRSdqr4ucDhBwBAOLsns2BrmC3/eMjqle/E1fu5dI7F4StPmiYLs6uPX6CUlTTl1h3wcJI8e82Ue1Bb76sQ==",
+      "version": "0.0.21",
+      "resolved": "https://registry.npmjs.org/@aitube/client/-/client-0.0.21.tgz",
+      "integrity": "sha512-Nw/K4j024ffYiw1WipLDU7M29L+4cM4cQwrjvSxWW8zF4/1NLrPSKTlF6Gak5Qd/ZFWq/D8GbMiGQ5W3lQb8mA==",
       "dependencies": {
         "query-string": "^9.0.0"
       },
       "peerDependencies": {
-        "@aitube/clap": "0.0.15"
+        "@aitube/clap": "0.0.16"
       }
     },
     "node_modules/@aitube/engine": {
-      "version": "0.0.5",
-      "resolved": "https://registry.npmjs.org/@aitube/engine/-/engine-0.0.5.tgz",
-      "integrity": "sha512-bylUmulNprGpyFwLVlHa+REKHu0IwIRihh5VkLeTc+2QNluPiVbUb1UD7w+I7lTPvpXMG2rJG0z98Ip3Yl1ogg==",
+      "version": "0.0.6",
+      "resolved": "https://registry.npmjs.org/@aitube/engine/-/engine-0.0.6.tgz",
+      "integrity": "sha512-Li+yE6MCIvD32Kyn43I7GHyQkmxtc/1/lrt3xPKMuFrWuc2FP9JR1ZYRlKqodmWqrSmhWCRBOt3Z6f62QpEvIQ==",
       "peerDependencies": {
-        "@aitube/clap": "0.0.15"
+        "@aitube/clap": "0.0.16"
       }
     },
     "node_modules/@alloc/quick-lru": {

package.json

@@ -10,9 +10,9 @@
     "lint": "next lint"
   },
   "dependencies": {
-    "@aitube/clap": "0.0.15",
-    "@aitube/client": "0.0.20",
-    "@aitube/engine": "0.0.5",
+    "@aitube/clap": "0.0.16",
+    "@aitube/client": "0.0.21",
+    "@aitube/engine": "0.0.6",
     "@huggingface/hub": "0.12.3-oauth",
     "@huggingface/inference": "^2.6.7",
     "@jcoreio/async-throttle": "^1.6.0",

src/app/api/utils/dataUriToBlob.ts

@@ -10,11 +10,14 @@ export function dataUriToBlob(dataURI = "", defaultContentType = ""): Blob {
   for (let i = 0; i < base64.length; i++) {
     typedArray[i] = base64.charCodeAt(i);
   }
+
+  /*
   console.log("dataUriToBlob DEBUG:", {
     type,
     base64: base64.slice(0, 80),
     arrayBuffer
   })
+  */
 
   return new Blob([arrayBuffer], { type });
 }

src/app/api/v1/edit/entities/generateEntityPrompts.ts

@@ -1,7 +1,7 @@
 "use server"
 
 import YAML from "yaml"
-import { generateSeed } from "@aitube/clap"
+import { ClapSegmentCategory, generateSeed } from "@aitube/clap"
 import { ClapEntityPrompt } from "@aitube/client"
 
 import { sleep } from "@/lib/utils/sleep"
@@ -100,7 +100,14 @@ Now please generate the output entities:`
   }
 
   if (maybeEntities.length) {
-    results = await Promise.all(maybeEntities.map(async ({
+    results = await Promise.all(
+      maybeEntities
+
+      // the LLM generates unrelated catrgories unfortunately,
+      // that we still turn into image.. so we fix that by filtering
+      .filter(({ category }) => category !== ClapSegmentCategory.CHARACTER)
+
+      .map(async ({
       name,
       category,
       image,

src/app/api/v1/edit/storyboards/route.ts

@@ -55,6 +55,8 @@ export async function POST(req: NextRequest) {
     })
   ))
 
+  // console.log("DEBUG:", newerClap.segments)
+
   // console.log(`[api/v1/edit/storyboards] returning the clap augmented with storyboards`)
 
   return new NextResponse(await serializeClap(newerClap), {

src/app/api/v1/export/route.ts

@@ -20,6 +20,8 @@ export async function POST(req: NextRequest, res: NextResponse) {
   // or rather, the non-turbo mode could be the one where we upscale
 
   // let's call our micro-service, which is currently open bar.
+  console.log("[api/v1/export] sending blob to ai-tube-clap-exporter.hf.space")
+
   const result = await fetch(
     `https://jbilcke-hf-ai-tube-clap-exporter.hf.space?f=${format}`,
     { method: "POST", body: await req.blob() }

src/app/state/useCurrentUser.ts

@@ -148,22 +148,24 @@ export function useCurrentUser({
       console.log("no pending oauth flow to finish")
     }
 
-    console.log("useCurrentUser()")
+    // console.log("useCurrentUser()")
     const searchParams = new URLSearchParams(window.location.search);
 
+    /*
     console.log("debug:", {
       "window.location.search:": window.location.search,
       searchParams,
     })
+    */
  
     const fn = async () => {
       try {
         const res = await oauthHandleRedirectIfPresent()
-        console.log("result of oauthHandleRedirectIfPresent:", res)
+        // console.log("result of oauthHandleRedirectIfPresent:", res)
         if (res) {
-          console.log("oauthHandleRedirectIfPresent returned something!", res)
+          // console.log("oauthHandleRedirectIfPresent returned something!", res)
           setOauthResult(res)
-          console.log("debug:", { accessToken: res.accessToken })
+          // console.log("debug:", { accessToken: res.accessToken })
           setHuggingfaceTemporaryApiKey(res.accessToken)
           startTransition(async () => {
             console.log("TODO julian do something, eg. reload the page, remove the things in the URL etc")

src/components/interface/latent-engine/core/useLatentEngine.ts

@@ -381,6 +381,8 @@ export const useLatentEngine = create<LatentEngineStore>((set, get) => ({
     // TODO julian: this is an approximation
     // to grab the max number of segments
     const maxBufferDurationInMs = positionInMs + (videoDurationInMs * 4)
+    
+    
     console.log(`DEBUG: `, {
       positionInMs,
       videoModelDurationInSec,