Merge remote-tracking branch 'upstream/main'

.env

@@ -1,40 +1,81 @@
-# ------------- IMAGE API CONFIG --------------
 # Supported values:
 # - VIDEOCHAIN
 # - REPLICATE
-RENDERING_ENGINE="REPLICATE"
-
-VIDEOCHAIN_API_URL="http://localhost:7860"
-VIDEOCHAIN_API_TOKEN=
-
-REPLICATE_API_TOKEN=
-REPLICATE_API_MODEL="stabilityai/sdxl"
-REPLICATE_API_MODEL_VERSION="da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf"
+# - INFERENCE_ENDPOINT
+# - INFERENCE_API
+RENDERING_ENGINE="INFERENCE_API"
 
-# ------------- LLM API CONFIG ----------------
 # Supported values:
 # - INFERENCE_ENDPOINT
 # - INFERENCE_API
-LLM_ENGINE="INFERENCE_ENDPOINT"
+# - OPENAI
+LLM_ENGINE="INFERENCE_API"
+
+# Not implemented for the Inference API yet - you can submit a PR if you have some ideas
+NEXT_PUBLIC_CAN_UPSCALE="false"
+
+# Not implemented for the Inference API yet - you can submit a PR if you have some ideas
+NEXT_PUBLIC_CAN_REDRAW="false"
+
+# Set to "true" to create artificial delays and smooth out traffic
+NEXT_PUBLIC_ENABLE_RATE_LIMITER="false"
+
+# ------------- PROVIDER AUTH ------------
+# You only need to configure the access token(s) for the provider(s) you want to use
+
+# HuggingFace.co token: available for the LLM engine and the RENDERING engine
+AUTH_HF_API_TOKEN=
+
+# Replicate.com token: available for the RENDERING engine
+AUTH_REPLICATE_API_TOKEN=
+
+# OpenAI.dom token: available for the LLM engine and the RENDERING engine
+AUTH_OPENAI_TOKEN=
 
-# Hugging Face token (if you choose to use a custom Inference Endpoint or an Inference API model)
-HF_API_TOKEN=
+# An experimental RENDERING engine (sorry it is not very documented yet, so you can use one of the other engines)
+AUTH_VIDEOCHAIN_API_TOKEN=
 
-# URL to a custom text-generation Inference Endpoint of your choice
-# -> You can leave it empty if you decide to use an Inference API Model instead
-HF_INFERENCE_ENDPOINT_URL=
+# ------------- RENDERING API CONFIG --------------
 
-# You can also use a model from the Inference API (not a custom inference endpoint)
-# -> You can leave it empty if you decide to use an Inference Endpoint URL instead
-HF_INFERENCE_API_MODEL="codellama/CodeLlama-7b-hf"
+# If you decided to use Replicate for the RENDERING engine
+RENDERING_REPLICATE_API_MODEL="stabilityai/sdxl"
+RENDERING_REPLICATE_API_MODEL_VERSION="da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf"
 
-# Not supported yet
-OPENAI_TOKEN=
+# If you decided to use a private Hugging Face Inference Endpoint for the RENDERING engine
+RENDERING_HF_INFERENCE_ENDPOINT_URL="https://XXXXXXXXXX.endpoints.huggingface.cloud"
+
+# If you decided to use a Hugging Face Inference API model for the RENDERING engine
+RENDERING_HF_INFERENCE_API_MODEL="stabilityai/stable-diffusion-xl-base-1.0"
+
+# An experimental RENDERING engine (sorry it is not very documented yet, so you can use one of the other engines)
+RENDERING_VIDEOCHAIN_API_URL="http://localhost:7860"
+
+# ------------- LLM API CONFIG ----------------
+
+# If you decided to use OpenAI for the LLM engine
+LLM_OPENAI_API_BASE_URL="https://api.openai.com/v1"
+LLM_OPENAI_API_MODEL="gpt-3.5-turbo"
+
+# If you decided to use a private Hugging Face Inference Endpoint for the LLM engine
+LLM_HF_INFERENCE_ENDPOINT_URL=""
+
+# If you decided to use a Hugging Face Inference API model for the LLM engine
+LLM_HF_INFERENCE_API_MODEL="meta-llama/Llama-2-70b-chat-hf"
 
 # ----------- COMMUNITY SHARING (OPTIONAL) -----------
-NEXT_PUBLIC_ENABLE_COMMUNITY_SHARING="false"
 # You don't need those community sharing options to run the AI Comic Factory
 # locally or on your own server (they are meant to be used by the Hugging Face team)
+NEXT_PUBLIC_ENABLE_COMMUNITY_SHARING="false"
 COMMUNITY_API_URL=
 COMMUNITY_API_TOKEN=
 COMMUNITY_API_ID=
+
+# ----------- CENSORSHIP (OPTIONAL) -----------
+# censorship is currently disabled, but will be required when we create a "community roll"
+# (a public repositoruy of user-generated comic strips)
+ENABLE_CENSORSHIP="false"
+
+# Due to the sensitive nature of some of keywords we want to ban (users try all kind of crazy illegal things)
+# the words are are not put in clear in the source code, but behind an encryption key
+# (I don't want the project to be flagged by an AI robot police on GitHub or something)
+SECRET_FINGERPRINT=""

CONTRIBUTORS.md

@@ -0,0 +1,9 @@
+This project was developed by Julian Bilcke (@jbilcke-hf), as part of his work at Hugging Face.
+
+------------------------------------------
+
+A huge thanks to external developers for their contributions! 
+
+艾逗笔 (@idoubi):
+- Added support for OpenAI: https://github.com/jbilcke-hf/ai-comic-factory/pull/6
+

LICENCE.md

@@ -0,0 +1,170 @@
+Apache License
+==============
+
+_Version 2.0, January 2004_  
+_&lt;<http://www.apache.org/licenses/>&gt;_
+
+### Terms and Conditions for use, reproduction, and distribution
+
+#### 1. Definitions
+
+“License” shall mean the terms and conditions for use, reproduction, and
+distribution as defined by Sections 1 through 9 of this document.
+
+“Licensor” shall mean the copyright owner or entity authorized by the copyright
+owner that is granting the License.
+
+“Legal Entity” shall mean the union of the acting entity and all other entities
+that control, are controlled by, or are under common control with that entity.
+For the purposes of this definition, “control” means **(i)** the power, direct or
+indirect, to cause the direction or management of such entity, whether by
+contract or otherwise, or **(ii)** ownership of fifty percent (50%) or more of the
+outstanding shares, or **(iii)** beneficial ownership of such entity.
+
+“You” (or “Your”) shall mean an individual or Legal Entity exercising
+permissions granted by this License.
+
+“Source” form shall mean the preferred form for making modifications, including
+but not limited to software source code, documentation source, and configuration
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+
+“Object” form shall mean any form resulting from mechanical transformation or
+translation of a Source form, including but not limited to compiled object code,
+generated documentation, and conversions to other media types.
+
+“Work” shall mean the work of authorship, whether in Source or Object form, made
+available under the License, as indicated by a copyright notice that is included
+in or attached to the work (an example is provided in the Appendix below).
+
+“Derivative Works” shall mean any work, whether in Source or Object form, that
+is based on (or derived from) the Work and for which the editorial revisions,
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+shall not include works that remain separable from, or merely link (or bind by
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+“Contribution” shall mean any work of authorship, including the original version
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+“Contributor” shall mean Licensor and any individual or Legal Entity on behalf
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+#### 2. Grant of Copyright License
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+Subject to the terms and conditions of this License, each Contributor hereby
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+#### 3. Grant of Patent License
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+* **(a)** You must give any other recipients of the Work or Derivative Works a copy of
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+* **(d)** If the Work includes a “NOTICE” text file as part of its distribution, then any
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+the NOTICE file are for informational purposes only and do not modify the
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+You distribute, alongside or as an addendum to the NOTICE text from the Work,
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+additional or different license terms and conditions for use, reproduction, or
+distribution of Your modifications, or for any such Derivative Works as a whole,
+provided Your use, reproduction, and distribution of the Work otherwise complies
+with the conditions stated in this License.
+
+#### 5. Submission of Contributions
+
+Unless You explicitly state otherwise, any Contribution intentionally submitted
+for inclusion in the Work by You to the Licensor shall be under the terms and
+conditions of this License, without any additional terms or conditions.
+Notwithstanding the above, nothing herein shall supersede or modify the terms of
+any separate license agreement you may have executed with Licensor regarding
+such Contributions.
+
+#### 6. Trademarks
+
+This License does not grant permission to use the trade names, trademarks,
+service marks, or product names of the Licensor, except as required for
+reasonable and customary use in describing the origin of the Work and
+reproducing the content of the NOTICE file.
+
+#### 7. Disclaimer of Warranty
+
+Unless required by applicable law or agreed to in writing, Licensor provides the
+Work (and each Contributor provides its Contributions) on an “AS IS” BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied,
+including, without limitation, any warranties or conditions of TITLE,
+NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are
+solely responsible for determining the appropriateness of using or
+redistributing the Work and assume any risks associated with Your exercise of
+permissions under this License.
+
+#### 8. Limitation of Liability
+
+In no event and under no legal theory, whether in tort (including negligence),
+contract, or otherwise, unless required by applicable law (such as deliberate
+and grossly negligent acts) or agreed to in writing, shall any Contributor be
+liable to You for damages, including any direct, indirect, special, incidental,
+or consequential damages of any character arising as a result of this License or
+out of the use or inability to use the Work (including but not limited to
+damages for loss of goodwill, work stoppage, computer failure or malfunction, or
+any and all other commercial damages or losses), even if such Contributor has
+been advised of the possibility of such damages.
+
+#### 9. Accepting Warranty or Additional Liability
+
+While redistributing the Work or Derivative Works thereof, You may choose to
+offer, and charge a fee for, acceptance of support, warranty, indemnity, or
+other liability obligations and/or rights consistent with this License. However,
+in accepting such obligations, You may act only on Your own behalf and on Your
+sole responsibility, not on behalf of any other Contributor, and only if You
+agree to indemnify, defend, and hold each Contributor harmless for any liability
+incurred by, or claims asserted against, such Contributor by reason of your
+accepting any such warranty or additional liability.
+
+_END OF TERMS AND CONDITIONS_

README.md

@@ -6,6 +6,7 @@ colorTo: yellow
 sdk: docker
 pinned: true
 app_port: 3000
+disable_embedding: true
 ---
 
 # AI Comic Factory
@@ -17,17 +18,29 @@ First, I would like to highlight that everything is open-source (see [here](http
 However the project isn't a monolithic Space that can be duplicated and ran immediately:
 it requires various components to run for the frontend, backend, LLM, SDXL etc.
 
-If you try to duplicate the project and open the `.env` you will see it requires some variables:
-
-- `LLM_ENGINE`: can be either "INFERENCE_API" or "INFERENCE_ENDPOINT"
-- `HF_API_TOKEN`: necessary if you decide to use an inference api model or a custom inference endpoint
-- `HF_INFERENCE_ENDPOINT_URL`: necessary if you decide to use a custom inference endpoint
-- `RENDERING_ENGINE`: can only be "VIDEOCHAIN" or "REPLICATE" for now, unless you code your custom solution
-- `VIDEOCHAIN_API_URL`: url to the VideoChain API server
-- `VIDEOCHAIN_API_TOKEN`: secret token to access the VideoChain API server
-- `REPLICATE_API_TOKEN`: in case you want to use Replicate.com
-- `REPLICATE_API_MODEL`: optional, defaults to "stabilityai/sdxl"
-- `REPLICATE_API_MODEL_VERSION`: optional, in case you want to change the version
+If you try to duplicate the project, open the `.env` you will see it requires some variables.
+
+Provider config:
+- `LLM_ENGINE`: can be one of: "INFERENCE_API", "INFERENCE_ENDPOINT", "OPENAI"
+- `RENDERING_ENGINE`: can be one of: "INFERENCE_API", "INFERENCE_ENDPOINT", "REPLICATE", "VIDEOCHAIN" for now, unless you code your custom solution
+
+Auth config:
+- `AUTH_HF_API_TOKEN`: only if you decide to use OpenAI for the LLM engine necessary if you decide to use an inference api model or a custom inference endpoint
+- `AUTH_OPENAI_TOKEN`: only if you decide to use OpenAI for the LLM engine
+- `AITH_VIDEOCHAIN_API_TOKEN`: secret token to access the VideoChain API server
+- `AUTH_REPLICATE_API_TOKEN`: in case you want to use Replicate.com
+
+Rendering config:
+- `RENDERING_HF_INFERENCE_ENDPOINT_URL`: necessary if you decide to use a custom inference endpoint
+- `RENDERING_REPLICATE_API_MODEL_VERSION`: url to the VideoChain API server
+- `RENDERING_HF_INFERENCE_ENDPOINT_URL`: optional, default to nothing
+- `RENDERING_HF_INFERENCE_API_MODEL`: optional, defaults to "stabilityai/stable-diffusion-xl-base-1.0"
+- `RENDERING_REPLICATE_API_MODEL`: optional, defaults to "stabilityai/sdxl"
+- `RENDERING_REPLICATE_API_MODEL_VERSION`: optional, in case you want to change the version
+
+Language model config:
+- `LLM_HF_INFERENCE_ENDPOINT_URL`: "https://llama-v2-70b-chat.ngrok.io"
+- `LLM_HF_INFERENCE_API_MODEL`: "codellama/CodeLlama-7b-hf"
 
 In addition, there are some community sharing variables that you can just ignore.
 Those variables are not required to run the AI Comic Factory on your own website or computer

package-lock.json

@@ -37,16 +37,19 @@
         "cmdk": "^0.2.0",
         "cookies-next": "^2.1.2",
         "date-fns": "^2.30.0",
+        "encoding": "^0.1.13",
         "eslint": "8.45.0",
         "eslint-config-next": "13.4.10",
         "html2canvas": "^1.4.1",
         "lucide-react": "^0.260.0",
         "next": "13.4.10",
+        "openai": "^4.10.0",
         "pick": "^0.0.1",
         "postcss": "8.4.26",
         "react": "18.2.0",
         "react-circular-progressbar": "^2.1.0",
         "react-dom": "18.2.0",
+        "react-icons": "^4.11.0",
         "react-virtualized-auto-sizer": "^1.0.20",
         "replicate": "^0.17.0",
         "sbd": "^1.0.19",
@@ -3691,6 +3694,15 @@
       "resolved": "https://registry.npmjs.org/@types/node/-/node-20.4.2.tgz",
       "integrity": "sha512-Dd0BYtWgnWJKwO1jkmTrzofjK2QXXcai0dmtzvIBhcA+RsG5h8R3xlyta0kGOZRNfL9GuRtb1knmPEhQrePCEw=="
     },
+    "node_modules/@types/node-fetch": {
+      "version": "2.6.6",
+      "resolved": "https://registry.npmjs.org/@types/node-fetch/-/node-fetch-2.6.6.tgz",
+      "integrity": "sha512-95X8guJYhfqiuVVhRFxVQcf4hW/2bCuoPwDasMf/531STFoNoWTT7YDnWdXHEZKqAGUigmpG31r2FE70LwnzJw==",
+      "dependencies": {
+        "@types/node": "*",
+        "form-data": "^4.0.0"
+      }
+    },
     "node_modules/@types/prop-types": {
       "version": "15.7.5",
       "resolved": "https://registry.npmjs.org/@types/prop-types/-/prop-types-15.7.5.tgz",
@@ -3847,6 +3859,17 @@
         "url": "https://opencollective.com/typescript-eslint"
       }
     },
+    "node_modules/abort-controller": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/abort-controller/-/abort-controller-3.0.0.tgz",
+      "integrity": "sha512-h8lQ8tacZYnR3vNQTgibj+tODHI5/+l06Au2Pcriv/Gmet0eaj4TwWH41sO9wnHDiQsEj19q0drzdWdeAHtweg==",
+      "dependencies": {
+        "event-target-shim": "^5.0.0"
+      },
+      "engines": {
+        "node": ">=6.5"
+      }
+    },
     "node_modules/abs-svg-path": {
       "version": "0.1.1",
       "resolved": "https://registry.npmjs.org/abs-svg-path/-/abs-svg-path-0.1.1.tgz",
@@ -3879,6 +3902,17 @@
         "node": ">=0.4.0"
       }
     },
+    "node_modules/agentkeepalive": {
+      "version": "4.5.0",
+      "resolved": "https://registry.npmjs.org/agentkeepalive/-/agentkeepalive-4.5.0.tgz",
+      "integrity": "sha512-5GG/5IbQQpC9FpkRGsSvZI5QYeSCzlJHdpBQntCsuTOxhKD8lqKhrleg2Yi7yvMIf82Ycmmqln9U8V9qwEiJew==",
+      "dependencies": {
+        "humanize-ms": "^1.2.1"
+      },
+      "engines": {
+        "node": ">= 8.0.0"
+      }
+    },
     "node_modules/ajv": {
       "version": "6.12.6",
       "resolved": "https://registry.npmjs.org/ajv/-/ajv-6.12.6.tgz",
@@ -4096,6 +4130,11 @@
         "has-symbols": "^1.0.3"
       }
     },
+    "node_modules/asynckit": {
+      "version": "0.4.0",
+      "resolved": "https://registry.npmjs.org/asynckit/-/asynckit-0.4.0.tgz",
+      "integrity": "sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q=="
+    },
     "node_modules/autoprefixer": {
       "version": "10.4.14",
       "resolved": "https://registry.npmjs.org/autoprefixer/-/autoprefixer-10.4.14.tgz",
@@ -4209,6 +4248,11 @@
       "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz",
       "integrity": "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="
     },
+    "node_modules/base-64": {
+      "version": "0.1.0",
+      "resolved": "https://registry.npmjs.org/base-64/-/base-64-0.1.0.tgz",
+      "integrity": "sha512-Y5gU45svrR5tI2Vt/X9GPd3L0HNIKzGu202EjxrXMpuc2V2CiKgemAbUUsqYmZJvPtCXoUKjNZwBJzsNScUbXA=="
+    },
     "node_modules/base64-arraybuffer": {
       "version": "1.0.2",
       "resolved": "https://registry.npmjs.org/base64-arraybuffer/-/base64-arraybuffer-1.0.2.tgz",
@@ -4430,6 +4474,14 @@
         "url": "https://github.com/chalk/chalk?sponsor=1"
       }
     },
+    "node_modules/charenc": {
+      "version": "0.0.2",
+      "resolved": "https://registry.npmjs.org/charenc/-/charenc-0.0.2.tgz",
+      "integrity": "sha512-yrLQ/yVUFXkzg7EDQsPieE/53+0RlaWTs+wBrvW36cyilJ2SaDWfl4Yj7MtLTXleV9uEKefbAGUPv2/iWSooRA==",
+      "engines": {
+        "node": "*"
+      }
+    },
     "node_modules/chokidar": {
       "version": "3.5.3",
       "resolved": "https://registry.npmjs.org/chokidar/-/chokidar-3.5.3.tgz",
@@ -4795,6 +4847,17 @@
         "simple-swizzle": "^0.2.2"
       }
     },
+    "node_modules/combined-stream": {
+      "version": "1.0.8",
+      "resolved": "https://registry.npmjs.org/combined-stream/-/combined-stream-1.0.8.tgz",
+      "integrity": "sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg==",
+      "dependencies": {
+        "delayed-stream": "~1.0.0"
+      },
+      "engines": {
+        "node": ">= 0.8"
+      }
+    },
     "node_modules/command-score": {
       "version": "0.1.2",
       "resolved": "https://registry.npmjs.org/command-score/-/command-score-0.1.2.tgz",
@@ -4879,6 +4942,14 @@
         "node": ">= 8"
       }
     },
+    "node_modules/crypt": {
+      "version": "0.0.2",
+      "resolved": "https://registry.npmjs.org/crypt/-/crypt-0.0.2.tgz",
+      "integrity": "sha512-mCxBlsHFYh9C+HVpiEacem8FEBnMXgU9gy4zmNC+SXAZNB/1idgp/aulFJ4FgCi7GPEVbfyng092GqL2k2rmow==",
+      "engines": {
+        "node": "*"
+      }
+    },
     "node_modules/crypto-js": {
       "version": "4.1.1",
       "resolved": "https://registry.npmjs.org/crypto-js/-/crypto-js-4.1.1.tgz",
@@ -5012,6 +5083,14 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/delayed-stream": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/delayed-stream/-/delayed-stream-1.0.0.tgz",
+      "integrity": "sha512-ZySD7Nf91aLB0RxL4KGrKHBXl7Eds1DAmEdcoVawXnLD7SDhpNgtuII2aAkg7a7QS41jxPSZ17p4VdGnMHk3MQ==",
+      "engines": {
+        "node": ">=0.4.0"
+      }
+    },
     "node_modules/dequal": {
       "version": "2.0.3",
       "resolved": "https://registry.npmjs.org/dequal/-/dequal-2.0.3.tgz",
@@ -5051,6 +5130,15 @@
         "node": ">=0.3.1"
       }
     },
+    "node_modules/digest-fetch": {
+      "version": "1.3.0",
+      "resolved": "https://registry.npmjs.org/digest-fetch/-/digest-fetch-1.3.0.tgz",
+      "integrity": "sha512-CGJuv6iKNM7QyZlM2T3sPAdZWd/p9zQiRNS9G+9COUCwzWFTs0Xp8NF5iePx7wtvhDykReiRRrSeNb4oMmB8lA==",
+      "dependencies": {
+        "base-64": "^0.1.0",
+        "md5": "^2.3.0"
+      }
+    },
     "node_modules/dir-glob": {
       "version": "3.0.1",
       "resolved": "https://registry.npmjs.org/dir-glob/-/dir-glob-3.0.1.tgz",
@@ -5139,6 +5227,14 @@
       "resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-10.2.1.tgz",
       "integrity": "sha512-97g6QgOk8zlDRdgq1WxwgTMgEWGVAQvB5Fdpgc1MkNy56la5SKP9GsMXKDOdqwn90/41a8yPwIGk1Y6WVbeMQA=="
     },
+    "node_modules/encoding": {
+      "version": "0.1.13",
+      "resolved": "https://registry.npmjs.org/encoding/-/encoding-0.1.13.tgz",
+      "integrity": "sha512-ETBauow1T35Y/WZMkio9jiM0Z5xjHHmJ4XmjZOq1l/dXz3lr2sRn87nJy20RupqSh1F2m3HHPSp8ShIPQJrJ3A==",
+      "dependencies": {
+        "iconv-lite": "^0.6.2"
+      }
+    },
     "node_modules/end-of-stream": {
       "version": "1.4.4",
       "resolved": "https://registry.npmjs.org/end-of-stream/-/end-of-stream-1.4.4.tgz",
@@ -5697,6 +5793,14 @@
         "node": ">=0.10.0"
       }
     },
+    "node_modules/event-target-shim": {
+      "version": "5.0.1",
+      "resolved": "https://registry.npmjs.org/event-target-shim/-/event-target-shim-5.0.1.tgz",
+      "integrity": "sha512-i/2XbnSz/uxRCU6+NdVJgKWDTM427+MqYbkQzD321DuCQJUqOuJKIA0IM2+W2xtYHdKOmZ4dR6fExsd4SXL+WQ==",
+      "engines": {
+        "node": ">=6"
+      }
+    },
     "node_modules/events": {
       "version": "3.3.0",
       "resolved": "https://registry.npmjs.org/events/-/events-3.3.0.tgz",
@@ -5846,6 +5950,36 @@
         "is-callable": "^1.1.3"
       }
     },
+    "node_modules/form-data": {
+      "version": "4.0.0",
+      "resolved": "https://registry.npmjs.org/form-data/-/form-data-4.0.0.tgz",
+      "integrity": "sha512-ETEklSGi5t0QMZuiXoA/Q6vcnxcLQP5vdugSpuAyi6SVGi2clPPp+xgEhuMaHC+zGgn31Kd235W35f7Hykkaww==",
+      "dependencies": {
+        "asynckit": "^0.4.0",
+        "combined-stream": "^1.0.8",
+        "mime-types": "^2.1.12"
+      },
+      "engines": {
+        "node": ">= 6"
+      }
+    },
+    "node_modules/form-data-encoder": {
+      "version": "1.7.2",
+      "resolved": "https://registry.npmjs.org/form-data-encoder/-/form-data-encoder-1.7.2.tgz",
+      "integrity": "sha512-qfqtYan3rxrnCk1VYaA4H+Ms9xdpPqvLZa6xmMgFvhO32x7/3J/ExcTd6qpxM0vH2GdMI+poehyBZvqfMTto8A=="
+    },
+    "node_modules/formdata-node": {
+      "version": "4.4.1",
+      "resolved": "https://registry.npmjs.org/formdata-node/-/formdata-node-4.4.1.tgz",
+      "integrity": "sha512-0iirZp3uVDjVGt9p49aTaqjk84TrglENEDuqfdlZQ1roC9CWlPk6Avf8EEnZNcAqPonwkG35x4n3ww/1THYAeQ==",
+      "dependencies": {
+        "node-domexception": "1.0.0",
+        "web-streams-polyfill": "4.0.0-beta.3"
+      },
+      "engines": {
+        "node": ">= 12.20"
+      }
+    },
     "node_modules/fraction.js": {
       "version": "4.2.1",
       "resolved": "https://registry.npmjs.org/fraction.js/-/fraction.js-4.2.1.tgz",
@@ -6197,11 +6331,30 @@
         "entities": "^4.4.0"
       }
     },
+    "node_modules/humanize-ms": {
+      "version": "1.2.1",
+      "resolved": "https://registry.npmjs.org/humanize-ms/-/humanize-ms-1.2.1.tgz",
+      "integrity": "sha512-Fl70vYtsAFb/C06PTS9dZBo7ihau+Tu/DNCk/OyHhea07S+aeMWpFFkUaXRa8fI+ScZbEI8dfSxwY7gxZ9SAVQ==",
+      "dependencies": {
+        "ms": "^2.0.0"
+      }
+    },
     "node_modules/hyphen": {
       "version": "1.6.6",
       "resolved": "https://registry.npmjs.org/hyphen/-/hyphen-1.6.6.tgz",
       "integrity": "sha512-XtqmnT+b9n5MX+MsqluFAVTIenbtC25iskW0Z+jLd+awfhA+ZbWKWQMIvLJccGoa2bM1R6juWJ27cZxIFOmkWw=="
     },
+    "node_modules/iconv-lite": {
+      "version": "0.6.3",
+      "resolved": "https://registry.npmjs.org/iconv-lite/-/iconv-lite-0.6.3.tgz",
+      "integrity": "sha512-4fCk79wshMdzMp2rH06qWrJE4iolqLhCUH+OiuIgU++RB0+94NlDL81atO7GX55uUKueo0txHNtvEyI6D7WdMw==",
+      "dependencies": {
+        "safer-buffer": ">= 2.1.2 < 3.0.0"
+      },
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
     "node_modules/idb-keyval": {
       "version": "6.2.1",
       "resolved": "https://registry.npmjs.org/idb-keyval/-/idb-keyval-6.2.1.tgz",
@@ -6366,6 +6519,11 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/is-buffer": {
+      "version": "1.1.6",
+      "resolved": "https://registry.npmjs.org/is-buffer/-/is-buffer-1.1.6.tgz",
+      "integrity": "sha512-NcdALwpXkTm5Zvvbk7owOUSvVvBKDgKP5/ewfXEznmQFfs4ZRmanOeKBTjRVjka3QFoN6XJ+9F3USqfHqTaU5w=="
+    },
     "node_modules/is-callable": {
       "version": "1.2.7",
       "resolved": "https://registry.npmjs.org/is-callable/-/is-callable-1.2.7.tgz",
@@ -6851,6 +7009,16 @@
       "resolved": "https://registry.npmjs.org/make-error/-/make-error-1.3.6.tgz",
       "integrity": "sha512-s8UhlNe7vPKomQhC1qFelMokr/Sc3AgNbso3n74mVPA5LTZwkB9NlXf4XPamLxJE8h0gh73rM94xvwRT2CVInw=="
     },
+    "node_modules/md5": {
+      "version": "2.3.0",
+      "resolved": "https://registry.npmjs.org/md5/-/md5-2.3.0.tgz",
+      "integrity": "sha512-T1GITYmFaKuO91vxyoQMFETst+O71VUPEU3ze5GNzDm0OWdP8v1ziTaAEPUr/3kLsY3Sftgz242A1SetQiDL7g==",
+      "dependencies": {
+        "charenc": "0.0.2",
+        "crypt": "0.0.2",
+        "is-buffer": "~1.1.6"
+      }
+    },
     "node_modules/media-engine": {
       "version": "1.0.3",
       "resolved": "https://registry.npmjs.org/media-engine/-/media-engine-1.0.3.tgz",
@@ -6876,6 +7044,25 @@
         "node": ">=8.6"
       }
     },
+    "node_modules/mime-db": {
+      "version": "1.52.0",
+      "resolved": "https://registry.npmjs.org/mime-db/-/mime-db-1.52.0.tgz",
+      "integrity": "sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg==",
+      "engines": {
+        "node": ">= 0.6"
+      }
+    },
+    "node_modules/mime-types": {
+      "version": "2.1.35",
+      "resolved": "https://registry.npmjs.org/mime-types/-/mime-types-2.1.35.tgz",
+      "integrity": "sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw==",
+      "dependencies": {
+        "mime-db": "1.52.0"
+      },
+      "engines": {
+        "node": ">= 0.6"
+      }
+    },
     "node_modules/mimic-response": {
       "version": "3.1.0",
       "resolved": "https://registry.npmjs.org/mimic-response/-/mimic-response-3.1.0.tgz",
@@ -7050,6 +7237,24 @@
       "resolved": "https://registry.npmjs.org/node-addon-api/-/node-addon-api-6.1.0.tgz",
       "integrity": "sha512-+eawOlIgy680F0kBzPUNFhMZGtJ1YmqM6l4+Crf4IkImjYrO/mqPwRMh352g23uIaQKFItcQ64I7KMaJxHgAVA=="
     },
+    "node_modules/node-domexception": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/node-domexception/-/node-domexception-1.0.0.tgz",
+      "integrity": "sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ==",
+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/jimmywarting"
+        },
+        {
+          "type": "github",
+          "url": "https://paypal.me/jimmywarting"
+        }
+      ],
+      "engines": {
+        "node": ">=10.5.0"
+      }
+    },
     "node_modules/node-fetch": {
       "version": "2.7.0",
       "resolved": "https://registry.npmjs.org/node-fetch/-/node-fetch-2.7.0.tgz",
@@ -7223,6 +7428,29 @@
         "wrappy": "1"
       }
     },
+    "node_modules/openai": {
+      "version": "4.10.0",
+      "resolved": "https://registry.npmjs.org/openai/-/openai-4.10.0.tgz",
+      "integrity": "sha512-II4b5/7qzwYkqA9MSjgqdofCc798EW+dtF2h6qNaVLet+qO7FShAJTWnoyzb50J4ZH1rPxRFAsmDLIhY3PT6DQ==",
+      "dependencies": {
+        "@types/node": "^18.11.18",
+        "@types/node-fetch": "^2.6.4",
+        "abort-controller": "^3.0.0",
+        "agentkeepalive": "^4.2.1",
+        "digest-fetch": "^1.3.0",
+        "form-data-encoder": "1.7.2",
+        "formdata-node": "^4.3.2",
+        "node-fetch": "^2.6.7"
+      },
+      "bin": {
+        "openai": "bin/cli"
+      }
+    },
+    "node_modules/openai/node_modules/@types/node": {
+      "version": "18.17.19",
+      "resolved": "https://registry.npmjs.org/@types/node/-/node-18.17.19.tgz",
+      "integrity": "sha512-+pMhShR3Or5GR0/sp4Da7FnhVmTalWm81M6MkEldbwjETSaPalw138Z4KdpQaistvqQxLB7Cy4xwYdxpbSOs9Q=="
+    },
     "node_modules/opencollective-postinstall": {
       "version": "2.0.3",
       "resolved": "https://registry.npmjs.org/opencollective-postinstall/-/opencollective-postinstall-2.0.3.tgz",
@@ -7681,6 +7909,14 @@
         "loose-envify": "^1.1.0"
       }
     },
+    "node_modules/react-icons": {
+      "version": "4.11.0",
+      "resolved": "https://registry.npmjs.org/react-icons/-/react-icons-4.11.0.tgz",
+      "integrity": "sha512-V+4khzYcE5EBk/BvcuYRq6V/osf11ODUM2J8hg2FDSswRrGvqiYUYPRy4OdrWaQOBj4NcpJfmHZLNaD+VH0TyA==",
+      "peerDependencies": {
+        "react": "*"
+      }
+    },
     "node_modules/react-is": {
       "version": "16.13.1",
       "resolved": "https://registry.npmjs.org/react-is/-/react-is-16.13.1.tgz",
@@ -8043,6 +8279,11 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/safer-buffer": {
+      "version": "2.1.2",
+      "resolved": "https://registry.npmjs.org/safer-buffer/-/safer-buffer-2.1.2.tgz",
+      "integrity": "sha512-YZo3K82SD7Riyi0E1EQPojLz7kpepnSQI9IyPbHHg1XXXevb5dJI7tpyN2ADxGcQbHG7vcyRHk0cbwqcQriUtg=="
+    },
     "node_modules/sanitize-html": {
       "version": "2.11.0",
       "resolved": "https://registry.npmjs.org/sanitize-html/-/sanitize-html-2.11.0.tgz",
@@ -9067,6 +9308,14 @@
         "node": ">=10.13.0"
       }
     },
+    "node_modules/web-streams-polyfill": {
+      "version": "4.0.0-beta.3",
+      "resolved": "https://registry.npmjs.org/web-streams-polyfill/-/web-streams-polyfill-4.0.0-beta.3.tgz",
+      "integrity": "sha512-QW95TCTaHmsYfHDybGMwO5IJIM93I/6vTRk+daHTWFPhwh+C8Cg7j7XyKrwrj8Ib6vYXe0ocYNrmzY4xAAN6ug==",
+      "engines": {
+        "node": ">= 14"
+      }
+    },
     "node_modules/webidl-conversions": {
       "version": "3.0.1",
       "resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz",

package.json

@@ -38,6 +38,7 @@
     "cmdk": "^0.2.0",
     "cookies-next": "^2.1.2",
     "date-fns": "^2.30.0",
+    "encoding": "^0.1.13",
     "eslint": "8.45.0",
     "eslint-config-next": "13.4.10",
     "html2canvas": "^1.4.1",
@@ -49,6 +50,7 @@
     "react": "18.2.0",
     "react-circular-progressbar": "^2.1.0",
     "react-dom": "18.2.0",
+    "react-icons": "^4.11.0",
     "react-virtualized-auto-sizer": "^1.0.20",
     "replicate": "^0.17.0",
     "sbd": "^1.0.19",

src/app/engine/caption.ts

@@ -2,7 +2,7 @@
 
 import { ImageAnalysisRequest, ImageAnalysisResponse } from "@/types"
 
-const apiUrl = `${process.env.VIDEOCHAIN_API_URL || ""}`
+const apiUrl = `${process.env.RENDERING_VIDEOCHAIN_API_URL || ""}`
 
 export async function see({
   prompt,
@@ -33,7 +33,7 @@ export async function see({
       headers: {
         Accept: "application/json",
         "Content-Type": "application/json",
-        // Authorization: `Bearer ${process.env.VIDEOCHAIN_API_TOKEN}`,
+        // Authorization: `Bearer ${videochainApi}`,
       },
       body: JSON.stringify(request),
       cache: 'no-store',

src/app/engine/censorship.ts

@@ -1,39 +1,184 @@
 
-
-// unfortunately due to abuse by some users, I have to add this NSFW filter
-const secretSalt = `${process.env.SECRET_CENSORSHIP_KEY || ""}`
-
-// TODO the censorship is not implement yet actually
-
 // I don't want to be banned by Replicate because bad actors are asking
 // for some naked anime stuff or whatever
 // I also want to avoid a PR scandal due to some bad user generated content
 
-const forbiddenWords = [
-  // those keywords have been generated by looking at the logs of the AI Comic Factory
-  // those are real requests some users tried to attempt.. :|
-  "nazi",
-  "hitler",
-  "boob",
-  "boobs",
-  "boobies",
-  "nipple",
-  "nipples",
-  "nude",
-  "nudes",
-  "naked",
-  "pee",
-  "peeing",
-  "erotic",
-  "sexy"
+import { computeSecretFingerprint } from "@/lib/computeSecretFingerprint"
+
+// those keywords have been generated by looking at the logs of the panorama and the AI Comic Factory
+// those are real requests some users tried to attempt.. :|
+
+const chickens = [
+  "fcb4dacbd99b21368c50f29c1d47071c87cf2225ab9192282c785460391cd365",
+  "68840b60ac27eacaa7afe17e898d3c4a2dc71acff8c74d6782c1bcaafd14963d",
+  "67f745224fd6e1a7a3a244514d5807fcc994cbb62ca4ec8fa44cd14244a515ae",
+  "681fea565117808c6dbe002520d2cfeeb3e5c67e68630afb4a453449a9da587b",
+  "2f3d913b3db9e15a930aac43eb2d6fe8817db8e4bcf37794bf0227b06b718d1b",
+  "922a700b807e4994df82eba2b48a6ac131fe8d8d1035d06b3592d622fb232161",
+  "cb69ee6774eafcc720adb1f689d28acbb9f47998cbea0299ec66a58dedf91c37"
+]
+
+const ducks = [
+  "1c52cb20c0cbc76349fa63232b982bd394cf0850ebc17240dcf33c19fb15a26d",
+  "e1d4de9b8d464d7da07c276b63a42c1c9922224f0a6cab6b0826427ce4a7461a",
+  "0be3174bfb1a48a65875c2f035b1ae14fbc8f232f55785018de0cfe2132fa952",
+  "0f174769641b2e5d2c79b5a83e8ef91e004f6f3e62531cd70cfdff02159268cb",
+  "e9fb8ae8ff720acd91025229478a21e43e8e976e30119a76c293201adf572736",
+  "f65a0dc0e07b5d084ff24c69dcdb953f7b57101d2ebb716d4dfb5963076ef807",
+  "2bf38af1646489c2c086f811d082054cd29e23fa7bb5c525396bec01b3ab688e"
+]
+
+const cats = [
+  "fcffc3e997d952007d1b902a9cf40b750ba4a410ac65bfd95475996bf51359e4",
+  "3172a5fa159754d703489dfba5af520b8ace107cdf170f4c4cb38a6797aa163f",
+  "500012dbff4498a9c4513369d6b9b373fab9330ffd2cb1e622294043cc21b610",
+  "84e3a8d34ee7d0c8e7a2926dd1acad46a0b66b9d27725b3a7e5053550f490301"
+]
+
+const roasted = [
+  "a2bfbce0046c9a52a0eabf98f73e0f8e09959970431fc892ebdb4e1c97031b50",
+  "6eca1adf06851f99e9cdfbb496c27d46ff81106903d11f3346a146e96082b016",
+  "49a124c9ed6fbbad4105b3657dc25de369bcafb9d6787f610c08f584cd607d0f",
+  "c3afb59420c812cbc7c8f57ad3e8d79407f10106a99f829aa65316c99d0b29c4",
+  "2b808858836a5c205080f5b93201ef92e098cff931d8de6d9f20dc722997d077",
+  "07bef89d1a7d63c9c5ed64ba0f73d6cff689811847c2e20c8b3fbfb060e1d64e",
+  "baeb994922d5473f534aa54322d83effe74c6c4dac807e6b523a677d7acdc17b",
+  "ea4735a879edd5cc94ca7db26edd5a970df69a41f0009d3444486647e44175af",
+  "f2412249030454cd13ac6f7965871d924c16daacda0123de81892adb19ce49ac",
+  "9958c56e12bab8549cf752bcd8bec4ac36cf79c404b1faf5611f057bb71bc0e1",
+  "76cdade0b3d4caf0888f60318a5cbca00f830a3b0bf37735fc64fdaeb67c34d3",
+  "1bf53c97869e1ea89bda19da64a9173d48fe4ec823e949e2c898f8abb3fbf457",
+  "1bf53c97869e1ea89bda19da64a9173d48fe4ec823e949e2c898f8abb3fbf457",
+  "3d7f973fab8f4a19c0a3e59efe970ed7bd55a1cb795752d9cbe3c19e8a7d81ec"
 ]
 
-// temporary utility to make sure Replicate doesn't ban my account 
-// because of what users do in their prompt
+const banned = [
+  "8a05d4869d9d6ce388c6cd2db13ca12b88097b90f9be027d5ffaaa467c7a6e5e",
+  "0c475212a608138244c5fc150b1563e5ef79c516234fd78dcd5993f726c359a0",
+  "df17388805f99f2ff3e5ae97a0f55e5c927eb47f17ca65822bf8c88f02bac3dd",
+  "86c3355d1bd581cdf7306729d8dd0ee9b7a317b9cfd6d7a6f5fad9c0dafe2167",
+  "23a2484cd420c9ffbfcc2c0075a9b330664450ced1fc64ab6a65e278086b8c6e",
+  "fb4cabe709b62eea1b4cc0030c76f5e4a43ee677ce19124e8e7bafa86c78ab66",
+  "d99c26daee85f7dc81c46c061a5874cff7179ed72d884d2316d664d36ffe7ab5",
+  "b93c38af5aa221d76c60ee3eb762efee0cdb0daf29ceb235b7dda6d46c06490d",
+  "8cf6c8765dc757319461dd9a785e77c201b8e5a604d36b817cd987c6a5e62500",
+  "f4a1cb290745717f86c3cee30fc324c0d80a9945fcbc7bbeb010579f58792f1e",
+  "7c87c47c42fc983119551342be9ddd5b32e530c0504ccdbbaa1e12b1d9f1bbcb",
+  "d04fad4f21d030da7a1301afbf480ef6246eb7bbf0f26e31865b2e015a25f747",
+  "d685ff22fb9da01ee949db212770729603989850864ef7a7085e1f086cfa7deb",
+  "533b90588d9ccf7967da54691f575e9fd4926c6e0b5fd94a47b932bcea270bee",
+  "9c2d61f28f5bb7f3f1dc9122be64cda8a428b46ce68b70120da4c41dba96ba4c",
+  "5d4b1a3eebe64dfa631d0e3b084bd96ee9364c3669269f838ca17a4900276264",
+  "d56f56413b9679fc0820a2c0237224ded8554c61fab8959c174123c8b68ba029",
+  "323a9ab60739726070d615ff3a05d7ff6bb6e3c4dd9ff16ce24f253ecd7b8851",
+  "975c6739de7d4999db15972f707f5f4e95649275f1c0c48e895b8c537e8638ec",
+  "67ee26eb9e1c1c7124797321b02bca90a19c18171782917cd4a487b722484dce",
+  "6df5aa7b72a4e6e3fb726489ff1437daa5752047507f4da912680b1d6647c7d6",
+  "b0864805364359e8c5810c233b1bf2c74dedce9055ae5f7680ba05b4e39db8e2",
+  "a8f841472ecffdd6266151148320c8e36847a24ead9d3338e0313b075c16649d",
+  "f9b127cd90e85b0ff68dd220361671663f0154b2b827f1f7ea797b020ca0018c",
+  "d5c20e9a1ecf01c82da24c514d867498b3e5f522adc1523ce29404a6563641d5",
+  "241022b49d7c0aba24a61eea1137a804f36e4bcb47af42950275baac9b4e7aac",
+  "fc99a70e17b6c86ef1b537654b0f50353567a7b59912c3ba955f3fca4d1ea696",
+  "255306e968009003d295cb2a7256f27bfcdb5d1743bf4d9f2aa4b8adf1a7734d",
+  "048c7b709763dd9c43794d241c369f0abcb079d546ddcbbba9968a1ed1da7ed7",
+  "520cbfeef3e4c405d79478eedccb97a4d476be585626dd2b1c53292797491bc7",
+  "f9f28a7ae7e8b1719b350a04dc087a4b8e33478d109ceeef6ba892b32d1105c9",
+  "d177f1bfe603647ef4c1c0e6f1a7172081fb9bbc2ea859705949f2c5aa5d4f22",
+  "302feef2c09247fbd23789581f7f5e2219f88ae0a937880954938573c2a52a84",
+  "99edd6f57b864873835f16f19c805dd94bed9da8967b84e3a62782f106d9ebcc",
+  "e75e5f01dcd8351c9553e89558085bd68e6feb295dee5d8da0c9b43ee303ce36",
+  "135e52a026aea9d2e12de358a85e05cf21121a18269269b7c62678c3bc846f5b",
+  "28e5b2d3eb5f1ef4cc7b570878b03acf303a6ca4ca95893591e0fb943b0beab0",
+  "a26b26340f8d0363633490556d20bcc250726d10e1431eb8c22d6b1ff3f2b14a",
+  "27e4ddde96ec6a1dbe1cf12d79448b3e72f144944c15b299629542d1b65fbabf",
+  "efd9c0a391ee93251046a58326d1b21b33fe21d71a3fb1855b9048ade53df77c",
+  "6d505fcce416c26a606878aab4d249a034ba2a9846cb1f883e0f9e3fb76ba6da",
+  "3a37b8a1b72f9bca51233536d50f9c8d33a787434684787871e0049c82347cda",
+  "16f9b451184a7c3148344c7d0315f5312ca20553d2271912ecaad91810d977e6",
+  "7406537eb74d1885bd05e191228de313b13702a64d90ae1736c6377b25ab579a",
+  "7e4d1395ae18980015cab16c85ffa20b4cb90a2db594126e893d0f7ac6eecaa8",
+  "ba813ee6c25698f0f68a07121d38bb47c9aa404c1ab0a6e767595cb75e1747b8",
+  "6586c93f3ece83e01ecc1eb84a7711e7975826a388d478a009468ea0ed9dc03e",
+  "8960174c74d86e03ae88fb6774580170e49952f2286d960be08c556bbd0dda95",
+  "4d611454369aa1a4e2b7eed1734fac5d480f08fb86b87a162967e416370f2a8e",
+  "59d48440f85eabf565fe8d3bc6b973ba64c70df3b36b0511e0e67ceca91762b3",
+  "cd926926e2af74e43d1a6a420a7e1933b78662320477a3c018b2711d8765e339",
+  "80e90057df6a59823f51aafac36ed5bc4e5ac26d675d9c1467501590c82f12d4",
+  "a9cf28b869b70e258adde5639a048f866ec86f8f3f3d53bfc960b86aa6da9239",
+  "cc2adbf8ac0cddeefa304d7b20f14a7e047a4b2299cc5e8f898f5c59660bd964",
+  "92a150a46146e9d3f84899cf15e12514af684e7ee18d7add782ddd4f4a15ef18",
+  "d9b2e84ef6dc0ce449357d52c9095f69b173a1b848ea2921199d33b0ec10024a",
+  "a9329a7e4d367a0135c1ca86c6ce5ecabcc26529235229d71b6bf991f7689e21",
+  "8f160c6fd8ccc3fb2a371a4b52748f0bd030766627c4322e2911fe82f6b10497",
+  "620e96eae4f3e88cbe0770292b33724c5df3866d83f39df6380441f7271c80e2",
+  "cafa3481fa3c45ed1e55cd0129c12b477eeab5aa3d6da20cae6d6292f19b0e6d",
+  "be07994e9a83aa3689e79b6e96123676ccc4fa29f523c28c750c6d60505531ee",
+  "f6498069768cd3aa79b2b0c91879694f05a259c8ee4a6bb343f0435f74eb1b53",
+  "c9b6b26cb3a694eb78fcac0a14ad18d46d50907186a9add41022d31d191b2b65"
+]
+
+const young = [
+  "ffdf66787b4a33b78b18c18822e334cfe2c8406caf442851deef451bd43140a1",
+  "858f22219afc4b32a7ba9a27a213d7f495e77c3cceed8147eae5282bf3e23d39",
+  "8c3c46df84ace3d58d4ce0fbc513017986b33c6002ae369d9f7dd1f892a898cb",
+  "66caa22b9483fdf026ce67de61067d81535a7c9b3169cbc5c2a455ac8dcc7bec",
+  "76893047b1eff9fadc7be07b13adb5aaed9c73bcdeea46ee07098605e2c7ff76",
+  "526cb848754e2baaa17376a5693d90ba3f69f71fd2a866f22876ac8a075849a7",
+  "f59c38e31d0f64dc1bfcdf34451723bc1a65570e209e5496c8d1d7f6d3d649db",
+  "e013a67e275c62c1402ccbbb11ad14afb8b8a82318a44c07d67599ed5ac874de",
+  "3bef34219fb07f867ecbff4d6748f598d6cc0761e17dd0d431ee1f4ec3281374",
+  "8211bf5f613fac06cd5d074d34c16dfacc9367c8afaa6ad3aff99d145e5221be"
+]
+
+const getFingerprint = (word: string) => {
+  return computeSecretFingerprint(
+    word.toLocaleLowerCase().replaceAll(/[^a-zA-Z0-9]/gi, "")
+    )
+}
+
+const encode = (list: string[]) => {
+  console.log(JSON.stringify(
+    list.sort((a, b) => (b.length - a.length))
+    .map(item => getFingerprint(item)), null, 2))
+}
+
+// encode([ "badword" ])
+
 export const filterOutBadWords = (sentence: string) => {
-  const words = sentence.split(" ")
-  return words.filter(word => {
-    const lowerCase = word.toLocaleLowerCase()
-    return !forbiddenWords.includes(lowerCase)
-  }).join(" ")
+  if (process.env.ENABLE_CENSORSHIP !== "true") { return sentence }
+
+  let requireCensorship = false
+
+  const words = sentence.replaceAll(/[^a-zA-Z0-9]/gi, " ").replaceAll(/\s+/gi, " ").trim().split(" ")
+  
+  const sanitized = words.map(word => {
+    const fingerprint = getFingerprint(word)
+  
+    let result: string = word
+    // some users want to play it smart and bypass our system so let's play too
+    if (chickens.includes(fingerprint)) {
+      result = "large chicken"
+    } else if (ducks.includes(fingerprint)) {
+      result = "big duck"
+    } else if (cats.includes(fingerprint)) {
+      result = "cat"
+    } else if (roasted.includes(fingerprint)) {
+      result = "roasted chicken"
+    } else if (young.includes(fingerprint)) {
+      result = "adult"
+    } else if (banned.includes(fingerprint)) {
+      result = "_BANNED_"
+    }
+
+    if (result !== word) {
+      requireCensorship = true
+    }
+    return result
+  }).filter(item => item !== "_BANNED_").join(" ")
+
+  // if the user didn't try to use a bad word, we leave it untouched 
+  // he words array has been degraded by the replace operation, but it removes commas etc which isn't great
+  // so if the request was genuine and SFW, it's best to return the original prompt
+  return requireCensorship ? sanitized : sentence
 }

src/app/engine/render.ts

@@ -1,6 +1,7 @@
 "use server"
 
-import Replicate, { Prediction } from "replicate"
+import { v4 as uuidv4 } from "uuid"
+import Replicate from "replicate"
 
 import { RenderRequest, RenderedScene, RenderingEngine } from "@/types"
 import { generateSeed } from "@/lib/generateSeed"
@@ -8,13 +9,17 @@ import { sleep } from "@/lib/sleep"
 
 const renderingEngine = `${process.env.RENDERING_ENGINE || ""}` as RenderingEngine
 
-const replicateToken = `${process.env.REPLICATE_API_TOKEN || ""}`
-const replicateModel = `${process.env.REPLICATE_API_MODEL || ""}`
-const replicateModelVersion = `${process.env.REPLICATE_API_MODEL_VERSION || ""}`
+// TODO: we should split Hugging Face and Replicate backends into separate files
+const huggingFaceToken = `${process.env.AUTH_HF_API_TOKEN || ""}`
+const huggingFaceInferenceEndpointUrl = `${process.env.RENDERING_HF_INFERENCE_ENDPOINT_URL || ""}`
+const huggingFaceInferenceApiModel = `${process.env.RENDERING_HF_INFERENCE_API_MODEL || ""}`
 
-// note: there is no / at the end in the variable
-// so we have to add it ourselves if needed
-const apiUrl = process.env.VIDEOCHAIN_API_URL
+const replicateToken = `${process.env.AUTH_REPLICATE_API_TOKEN || ""}`
+const replicateModel = `${process.env.RENDERING_REPLICATE_API_MODEL || ""}`
+const replicateModelVersion = `${process.env.RENDERING_REPLICATE_API_MODEL_VERSION || ""}`
+
+const videochainToken = `${process.env.AUTH_VIDEOCHAIN_API_TOKEN || ""}`
+const videochainApiUrl = `${process.env.RENDERING_VIDEOCHAIN_API_URL || ""}`
 
 export async function newRender({
   prompt,
@@ -27,10 +32,10 @@ export async function newRender({
   width: number
   height: number
 }) {
-  // console.log(`newRender(${prompt})`)
   if (!prompt) {
-    console.error(`cannot call the rendering API without a prompt, aborting..`)
-    throw new Error(`cannot call the rendering API without a prompt, aborting..`)
+    const error = `cannot call the rendering API without a prompt, aborting..`
+    console.error(error)
+    throw new Error(error)
   }
 
   let defaulResult: RenderedScene = {
@@ -61,12 +66,23 @@ export async function newRender({
       const seed = generateSeed()
       const prediction = await replicate.predictions.create({
         version: replicateModelVersion,
-        input: { prompt, seed }
+        input: {
+          prompt: [
+            "beautiful",
+            "intricate details",
+            prompt,
+            "award winning",
+            "high resolution"
+          ].join(", "),
+          width,
+          height,
+          seed
+        }
       })
       
       // console.log("prediction:", prediction)
 
-      // no need to reply straight away: good things take time
+      // no need to reply straight away as images take time to generate, this isn't instantaneous
       // also our friends at Replicate won't like it if we spam them with requests
       await sleep(4000)
 
@@ -79,14 +95,88 @@ export async function newRender({
         maskUrl: "",
         segments: []
       } as RenderedScene
+    } if (renderingEngine === "INFERENCE_ENDPOINT" || renderingEngine === "INFERENCE_API") {
+      if (!huggingFaceToken) {
+        throw new Error(`you need to configure your HF_API_TOKEN in order to use the ${renderingEngine} rendering engine`)
+      }
+      if (renderingEngine === "INFERENCE_ENDPOINT" && !huggingFaceInferenceEndpointUrl) {
+        throw new Error(`you need to configure your RENDERING_HF_INFERENCE_ENDPOINT_URL in order to use the INFERENCE_ENDPOINT rendering engine`)
+      }
+      if (renderingEngine === "INFERENCE_API" && !huggingFaceInferenceApiModel) {
+        throw new Error(`you need to configure your RENDERING_HF_INFERENCE_API_MODEL in order to use the INFERENCE_API rendering engine`)
+      }
+
+      const url = renderingEngine === "INFERENCE_ENDPOINT"
+        ? huggingFaceInferenceEndpointUrl
+        : `https://api-inference.huggingface.co/models/${huggingFaceInferenceApiModel}`
+
+      /*
+      console.log(`calling ${url} with params: `, {
+        num_inference_steps: 25,
+        guidance_scale: 8,
+        width,
+        height,
+      })
+      */
+
+      const res = await fetch(url, {
+        method: "POST",
+        headers: {
+          "Content-Type": "application/json",
+          Authorization: `Bearer ${huggingFaceToken}`,
+        },
+        body: JSON.stringify({
+          inputs: [
+            "beautiful",
+            "intricate details",
+            prompt,
+            "award winning",
+            "high resolution"
+          ].join(", "),
+          parameters: {
+            num_inference_steps: 25,
+            guidance_scale: 8,
+            width,
+            height,
+          },
+          use_cache: false,
+        }),
+        cache: "no-store",
+        // we can also use this (see https://vercel.com/blog/vercel-cache-api-nextjs-cache)
+        // next: { revalidate: 1 }
+      })
+  
+  
+      // Recommendation: handle errors
+      if (res.status !== 200) {
+        const content = await res.text()
+        console.error(content)
+        // This will activate the closest `error.js` Error Boundary
+        throw new Error('Failed to fetch data')
+      }
+
+      const blob = await res.arrayBuffer()
+
+      const contentType = res.headers.get('content-type')
+
+      const assetUrl = `data:${contentType};base64,${Buffer.from(blob).toString('base64')}`
+      
+      return {
+        renderId: uuidv4(),
+        status: "completed",
+        assetUrl, 
+        alt: prompt,
+        error: "",
+        maskUrl: "",
+        segments: []
+      } as RenderedScene
     } else {
-      // console.log(`calling POST ${apiUrl}/render with prompt: ${prompt}`)
-      const res = await fetch(`${apiUrl}/render`, {
+      const res = await fetch(`${videochainApiUrl}/render`, {
         method: "POST",
         headers: {
           Accept: "application/json",
           "Content-Type": "application/json",
-          Authorization: `Bearer ${process.env.VIDEOCHAIN_API_TOKEN}`,
+          Authorization: `Bearer ${videochainToken}`,
         },
         body: JSON.stringify({
           prompt,
@@ -114,14 +204,7 @@ export async function newRender({
       // next: { revalidate: 1 }
       })
 
-
-      // console.log("res:", res)
-      // The return value is *not* serialized
-      // You can return Date, Map, Set, etc.
-      
-      // Recommendation: handle errors
       if (res.status !== 200) {
-        // This will activate the closest `error.js` Error Boundary
         throw new Error('Failed to fetch data')
       }
       
@@ -136,8 +219,9 @@ export async function newRender({
 
 export async function getRender(renderId: string) {
   if (!renderId) {
-    console.error(`cannot call the rendering API without a renderId, aborting..`)
-    throw new Error(`cannot call the rendering API without a renderId, aborting..`)
+    const error = `cannot call the rendering API without a renderId, aborting..`
+    console.error(error)
+    throw new Error(error)
   }
 
   let defaulResult: RenderedScene = {
@@ -153,24 +237,15 @@ export async function getRender(renderId: string) {
   try {
     if (renderingEngine === "REPLICATE") {
       if (!replicateToken) {
-        throw new Error(`you need to configure your REPLICATE_API_TOKEN in order to use the REPLICATE rendering engine`)
+        throw new Error(`you need to configure your AUTH_REPLICATE_API_TOKEN in order to use the REPLICATE rendering engine`)
       }
       if (!replicateModel) {
-        throw new Error(`you need to configure your REPLICATE_API_MODEL in order to use the REPLICATE rendering engine`)
+        throw new Error(`you need to configure your RENDERING_REPLICATE_API_MODEL in order to use the REPLICATE rendering engine`)
       }
 
-      // const replicate = new Replicate({ auth: replicateToken })
-
-      // console.log("Calling replicate..")
-      // const prediction = await replicate.predictions.get(renderId)
-      // console.log("Prediction:", prediction)
-
-       // console.log(`calling GET https://api.replicate.com/v1/predictions/${renderId}`)
        const res = await fetch(`https://api.replicate.com/v1/predictions/${renderId}`, {
         method: "GET",
         headers: {
-          // Accept: "application/json",
-          // "Content-Type": "application/json",
           Authorization: `Token ${replicateToken}`,
         },
         cache: 'no-store',
@@ -178,10 +253,6 @@ export async function getRender(renderId: string) {
       // next: { revalidate: 1 }
       })
     
-      // console.log("res:", res)
-      // The return value is *not* serialized
-      // You can return Date, Map, Set, etc.
-      
       // Recommendation: handle errors
       if (res.status !== 200) {
         // This will activate the closest `error.js` Error Boundary
@@ -189,7 +260,6 @@ export async function getRender(renderId: string) {
       }
       
       const response = (await res.json()) as any
-      // console.log("response:", response)
 
       return  {
         renderId,
@@ -202,41 +272,31 @@ export async function getRender(renderId: string) {
       } as RenderedScene
     } else {
       // console.log(`calling GET ${apiUrl}/render with renderId: ${renderId}`)
-      const res = await fetch(`${apiUrl}/render/${renderId}`, {
+      const res = await fetch(`${videochainApiUrl}/render/${renderId}`, {
         method: "GET",
         headers: {
           Accept: "application/json",
           "Content-Type": "application/json",
-          Authorization: `Bearer ${process.env.VIDEOCHAIN_API_TOKEN}`,
+          Authorization: `Bearer ${videochainToken}`,
         },
         cache: 'no-store',
       // we can also use this (see https://vercel.com/blog/vercel-cache-api-nextjs-cache)
       // next: { revalidate: 1 }
       })
-
-      // console.log("res:", res)
-      // The return value is *not* serialized
-      // You can return Date, Map, Set, etc.
       
-      // Recommendation: handle errors
       if (res.status !== 200) {
-        // This will activate the closest `error.js` Error Boundary
         throw new Error('Failed to fetch data')
       }
       
       const response = (await res.json()) as RenderedScene
-      // console.log("response:", response)
       return response
     }
   } catch (err) {
     console.error(err)
     defaulResult.status = "error"
     defaulResult.error = `${err}`
-    // Gorgon.clear(cacheKey)
     return defaulResult
   }
-
-  // }, cacheDurationInSec * 1000)
 }
 
 export async function upscaleImage(image: string): Promise<{
@@ -244,8 +304,9 @@ export async function upscaleImage(image: string): Promise<{
   error: string
 }> {
   if (!image) {
-    console.error(`cannot call the rendering API without an image, aborting..`)
-    throw new Error(`cannot call the rendering API without an image, aborting..`)
+    const error = `cannot call the rendering API without an image, aborting..`
+    console.error(error)
+    throw new Error(error)
   }
 
   let defaulResult = {
@@ -255,12 +316,12 @@ export async function upscaleImage(image: string): Promise<{
 
   try {
     // console.log(`calling GET ${apiUrl}/render with renderId: ${renderId}`)
-    const res = await fetch(`${apiUrl}/upscale`, {
+    const res = await fetch(`${videochainApiUrl}/upscale`, {
       method: "POST",
       headers: {
         Accept: "application/json",
         "Content-Type": "application/json",
-        Authorization: `Bearer ${process.env.VIDEOCHAIN_API_TOKEN}`,
+        Authorization: `Bearer ${videochainToken}`,
       },
       cache: 'no-store',
       body: JSON.stringify({ image, factor: 3 })
@@ -268,13 +329,7 @@ export async function upscaleImage(image: string): Promise<{
     // next: { revalidate: 1 }
     })
 
-    // console.log("res:", res)
-    // The return value is *not* serialized
-    // You can return Date, Map, Set, etc.
-    
-    // Recommendation: handle errors
     if (res.status !== 200) {
-      // This will activate the closest `error.js` Error Boundary
       throw new Error('Failed to fetch data')
     }
     
@@ -282,13 +337,9 @@ export async function upscaleImage(image: string): Promise<{
       assetUrl: string
       error: string
     }
-    // console.log("response:", response)
     return response
   } catch (err) {
     console.error(err)
-    // Gorgon.clear(cacheKey)
     return defaulResult
   }
-
-  // }, cacheDurationInSec * 1000)
 }

src/app/interface/bottom-bar/index.tsx

@@ -101,11 +101,13 @@ ${uploadUrl
       `print:hidden`,
       `fixed bottom-2 md:bottom-4 left-2 right-0 md:left-3 md:right-1`,
       `flex flex-row`,
-      `justify-between`
+      `justify-between`,
+      `pointer-events-none`
     )}>
       <div className={cn(
         `flex flex-row`,
         `items-end`,
+        `pointer-events-auto`,
         `animation-all duration-300 ease-in-out`,
         isGeneratingStory ? `scale-0 opacity-0` : ``,
         `space-x-3`,
@@ -115,12 +117,16 @@ ${uploadUrl
       </div>
       <div className={cn(
       `flex flex-row`,
+      `pointer-events-auto`,
       `animation-all duration-300 ease-in-out`,
       isGeneratingStory ? `scale-0 opacity-0` : ``,
       `space-x-3`,
       `scale-[0.9]`
     )}>
       <div>
+        {
+       // there is an issue, this env check doesn't work..
+        // process.env.NEXT_PUBLIC_CAN_UPSCALE === "true" ?
         <Button
           onClick={handleUpscale}
           disabled={!prompt?.length || remainingImages > 0 || isUpscaling || !Object.values(upscaleQueue).length}
@@ -129,6 +135,8 @@ ${uploadUrl
             ? `${allStatus.length - Object.values(upscaleQueue).length}/${allStatus.length} ⌛`
             : "Upscale"}
         </Button>
+        // : null
+      }
       </div>
         <div>
           <Button
@@ -152,6 +160,9 @@ ${uploadUrl
            </Button>
         </div>
         <div>
+          {
+          // there is an issue, this env check doesn't work..
+          // process.env.NEXT_PUBLIC_ENABLE_COMMUNITY_SHARING === "true" ? 
           <Button
             onClick={handleShare}
             disabled={!prompt?.length}
@@ -162,7 +173,9 @@ ${uploadUrl
               <span className="hidden md:inline">Share to community</span>
               <span className="inline md:hidden">Share</span>
             </div>
-          </Button>
+          </Button> 
+          //: null
+        }
         </div>
       </div>
     </div>

src/app/interface/panel/index.tsx

@@ -1,7 +1,7 @@
 "use client"
 
 import { useEffect, useRef, useState, useTransition } from "react"
-// import AutoSizer from "react-virtualized-auto-sizer"
+import { RxReload } from "react-icons/rx"
 
 import { RenderedScene } from "@/types"
 
@@ -12,9 +12,6 @@ import { cn } from "@/lib/utils"
 import { getInitialRenderedScene } from "@/lib/getInitialRenderedScene"
 import { Progress } from "@/app/interface/progress"
 
-// import { see } from "@/app/engine/caption"
-// import { replaceTextInSpeechBubbles } from "@/lib/replaceTextInSpeechBubbles"
-
 export function Panel({
   panel,
   className = "",
@@ -28,13 +25,13 @@ export function Panel({
  }) {
   const panelId = `${panel}`
 
+  const [mouseOver, setMouseOver] = useState(false)
   const ref = useRef<HTMLImageElement>(null)
   const font = useStore(state => state.font)
   const preset = useStore(state => state.preset)
 
   const setGeneratingImages = useStore(state => state.setGeneratingImages)
 
-  const [imageWithText, setImageWithText] = useState("")
   const panels = useStore(state => state.panels)
   const prompt = panels[panel] || ""
 
@@ -59,11 +56,12 @@ export function Panel({
 
   const timeoutRef = useRef<any>(null)
 
-  const delay = 3000 + (1000 * panel)
+  const enableRateLimiter = `${process.env.NEXT_PUBLIC_ENABLE_RATE_LIMITER}`  === "true"
 
-  // since this run in its own loop, we need to use references everywhere
-  // but perhaps this could be refactored
-  useEffect(() => {
+  const delay = enableRateLimiter ? (3000 + (1000 * panel)) : 1000
+
+
+  const startImageGeneration = ({ prompt, width, height }: { prompt: string, width: number, height: number}) => {
     // console.log("Panel prompt: "+ prompt)
     if (!prompt?.length) { return }
 
@@ -76,36 +74,47 @@ export function Panel({
     setTimeout(() => {
       startTransition(async () => {
 
-      // console.log(`Loading panel ${panel}..`)
-    
-      let newRendered: RenderedScene
-      try {
-        newRendered = await newRender({ prompt, width, height })
-      } catch (err) {
-        // "Failed to load the panel! Don't worry, we are retrying..")
-        newRendered = await newRender({ prompt, width, height })
-      }
+        // console.log(`Loading panel ${panel}..`)
+      
+        let newRendered: RenderedScene
+        try {
+          newRendered = await newRender({ prompt, width, height })
+        } catch (err) {
+          // "Failed to load the panel! Don't worry, we are retrying..")
+          newRendered = await newRender({ prompt, width, height })
+        }
 
-      if (newRendered) {
-        // console.log("newRendered:", newRendered)
-        setRendered(panelId, newRendered)
-
-        // but we are still loading!
-      } else {
-        setRendered(panelId, {
-          renderId: "",
-          status: "pending",
-          assetUrl: "",
-          alt: "",
-          maskUrl: "",
-          error: "",
-          segments: []
-        })
-        setGeneratingImages(panelId, false)
-        return
-      }
-    })
-  }, 2000 * panel)
+        if (newRendered) {
+          // console.log("newRendered:", newRendered)
+          setRendered(panelId, newRendered)
+
+          if (newRendered.status === "completed") {
+            setGeneratingImages(panelId, false)
+            addToUpscaleQueue(panelId, newRendered)
+          }
+
+          // but we are still loading!
+        } else {
+          setRendered(panelId, {
+            renderId: "",
+            status: "pending",
+            assetUrl: "",
+            alt: "",
+            maskUrl: "",
+            error: "",
+            segments: []
+          })
+          setGeneratingImages(panelId, false)
+          return
+        }
+      })
+    }, enableRateLimiter ? 2000 * panel : 0)
+  }
+
+  // since this run in its own loop, we need to use references everywhere
+  // but perhaps this could be refactored
+  useEffect(() => {
+    startImageGeneration({ prompt, width, height })
   }, [prompt, width, height])
 
 
@@ -208,27 +217,10 @@ export function Panel({
     `print:border-[1.5px] print:shadow-none`,
   )
 
-
-  /*
-  text detection (doesn't work)
-  useEffect(() => {
-    const fn = async () => {
-      if (!rendered.assetUrl || !ref.current) {
-        return
-      }
-
-      const result = await replaceTextInSpeechBubbles(
-        rendered.assetUrl,
-        "Lorem ipsum dolor sit amet, dolor ipsum. Sit amet? Ipsum! Dolor!!!"
-      )
-      if (result) {
-        setImageWithText(result)
-      }
-    }
-    fn()
-
-  }, [rendered.assetUrl, ref.current])
-  */
+  const handleReload = () => {
+    console.log(`Asked to reload panel ${panelId}`)
+    startImageGeneration({ prompt, width, height })
+  }
 
   if (prompt && !rendered.assetUrl) {
     return (
@@ -247,9 +239,11 @@ export function Panel({
       frameClassName,
       { "grayscale": preset.color === "grayscale" },
       className
-    )}>
+    )}
+    onMouseEnter={() => setMouseOver(true)}
+    onMouseLeave={() => setMouseOver(false)}
+    >
         <div className={cn(
-        ``,
         `bg-stone-50`,
         `border-stone-800`,
         `transition-all duration-200 ease-in-out`,
@@ -289,7 +283,7 @@ export function Panel({
         {rendered.assetUrl &&
         <img
           ref={ref}
-          src={imageWithText || rendered.assetUrl}
+          src={rendered.assetUrl}
           width={width}
           height={height}
           alt={rendered.alt}
@@ -298,6 +292,31 @@ export function Panel({
             // showCaptions ? `-mt-11` : ''
             )}
         />}
+        {
+          // there is an issue, this env check doesn't work..
+        // process.env.NEXT_PUBLIC_CAN_REDRAW === "true" ?
+         <div
+        className={cn(`relative -mt-14 ml-4`,)}>
+          <div className="flex flex-row">
+            <div
+              onClick={rendered.status === "completed" ? handleReload : undefined}
+              className={cn(
+                `bg-stone-100 rounded-lg`,
+                `flex flex-row space-x-2 items-center`,
+                `py-2 px-3 cursor-pointer`,
+                `transition-all duration-200 ease-in-out`,
+                rendered.status === "completed" ? "opacity-95" : "opacity-50",
+                mouseOver && rendered.assetUrl ? `scale-95 hover:scale-100 hover:opacity-100`: `scale-0`
+              )}>
+              <RxReload
+                className="w-5 h-5"
+              />
+              <span className="text-base">Redraw</span>
+            </div>
+          </div>
+        </div> 
+        //: null
+      }
     </div>
   )
 }

src/app/interface/top-menu/index.tsx

@@ -50,7 +50,7 @@ export function TopMenu() {
   const isGeneratingStory = useStore(state => state.isGeneratingStory)
   const atLeastOnePanelIsBusy = useStore(state => state.atLeastOnePanelIsBusy)
   const isBusy = isGeneratingStory || atLeastOnePanelIsBusy
-
+  
   const searchParams = useSearchParams()
 
   const requestedPreset = (searchParams.get('preset') as PresetName) || defaultPreset

src/app/main.tsx

@@ -38,6 +38,8 @@ export default function Main() {
       setWaitABitMore(false)
       setGeneratingStory(true)
 
+      const enableRateLimiter = `${process.env.NEXT_PUBLIC_ENABLE_RATE_LIMITER}`  === "true"
+
       try {
 
         const llmResponse = await getStory({ preset, prompt })
@@ -72,7 +74,7 @@ export default function Main() {
         setTimeout(() => {
           setGeneratingStory(false)
           setWaitABitMore(false)
-        }, 12000)
+        }, enableRateLimiter ? 12000 : 0)
       }
     })
   }, [prompt, preset?.label]) // important: we need to react to preset changes too

src/app/queries/getStory.ts

@@ -37,15 +37,15 @@ export const getStory = async ({
   let result = ""
 
   try {
-    result = await predict(query)
-    if (!result.trim().length) {
+    result = `${await predict(query) || ""}`.trim()
+    if (!result.length) {
       throw new Error("empty result!")
     }
   } catch (err) {
     console.log(`prediction of the story failed, trying again..`)
     try {
-      result = await predict(query+".")
-      if (!result.trim().length) {
+      result = `${await predict(query+".") || ""}`.trim()
+      if (!result.length) {
         throw new Error("empty result!")
       }
     } catch (err) {

src/app/queries/getStyle.ts

@@ -30,15 +30,15 @@ export const getStory = async ({
 
   let result = ""
   try {
-    result = await predict(query)
-    if (!result.trim().length) {
+    result = `${await predict(query) || ""}`.trim()
+    if (!result.length) {
       throw new Error("empty result!")
     }
   } catch (err) {
     console.log(`prediction of the story failed, trying again..`)
     try {
-      result = await predict(query+".")
-      if (!result.trim().length) {
+      result = `${await predict(query+".") || ""}`.trim()
+      if (!result.length) {
         throw new Error("empty result!")
       }
     } catch (err) {

src/app/queries/predict.ts

@@ -1,140 +1,9 @@
 "use server"
 
-import { HfInference, HfInferenceEndpoint } from "@huggingface/inference"
-
-import type { ChatCompletionMessage } from "openai/resources/chat"
 import { LLMEngine } from "@/types"
-import OpenAI from "openai"
-
-const hf = new HfInference(process.env.HF_API_TOKEN)
+import { predictWithHuggingFace } from "./predictWithHuggingFace"
+import { predictWithOpenAI } from "./predictWithOpenAI"
 
-
-// note: we always try "inference endpoint" first
 const llmEngine = `${process.env.LLM_ENGINE || ""}` as LLMEngine
-const inferenceEndpoint = `${process.env.HF_INFERENCE_ENDPOINT_URL || ""}`
-const inferenceModel = `${process.env.HF_INFERENCE_API_MODEL || ""}`
-const openaiApiKey = `${process.env.OPENAI_API_KEY || ""}`
-
-let hfie: HfInferenceEndpoint
-
-switch (llmEngine) {
-  case "INFERENCE_ENDPOINT":
-    if (inferenceEndpoint) {
-      console.log("Using a custom HF Inference Endpoint")
-      hfie = hf.endpoint(inferenceEndpoint)
-    } else {
-      const error = "No Inference Endpoint URL defined"
-      console.error(error)
-      throw new Error(error)
-    }
-    break;
-  
-  case "INFERENCE_API":
-    if (inferenceModel) {
-      console.log("Using an HF Inference API Model")
-    } else {
-      const error = "No Inference API model defined"
-      console.error(error)
-      throw new Error(error)
-    }
-    break;
-
-  case "OPENAI":
-    if (openaiApiKey) {
-      console.log("Using an OpenAI API Key")
-    } else {
-      const error = "No OpenAI API key defined"
-      console.error(error)
-      throw new Error(error)
-    }
-    break;
-  
-  default:
-    const error = "No Inference Endpoint URL or Inference API Model defined"
-    console.error(error)
-    throw new Error(error)
-}
-
-export async function predict(inputs: string) {
-
-  console.log(`predict: `, inputs)
-  
-  if (llmEngine==="OPENAI") {
-    return predictWithOpenAI(inputs)
-  } 
-  
-  const api = llmEngine ==="INFERENCE_ENDPOINT" ? hfie : hf
-
-  let instructions = ""
-  try {
-    for await (const output of api.textGenerationStream({
-      model: llmEngine ==="INFERENCE_ENDPOINT" ? undefined : (inferenceModel || undefined),
-      inputs,
-      parameters: {
-        do_sample: true,
-        // we don't require a lot of token for our task
-        // but to be safe, let's count ~110 tokens per panel
-        max_new_tokens: 450, // 1150,
-        return_full_text: false,
-      }
-    })) {
-      instructions += output.token.text
-      process.stdout.write(output.token.text)
-      if (
-        instructions.includes("</s>") || 
-        instructions.includes("<s>") ||
-        instructions.includes("[INST]") ||
-        instructions.includes("[/INST]") ||
-        instructions.includes("<SYS>") ||
-        instructions.includes("</SYS>") ||
-        instructions.includes("<|end|>") ||
-        instructions.includes("<|assistant|>")
-      ) {
-        break
-      }
-    }
-  } catch (err) {
-    console.error(`error during generation: ${err}`)
-  }
-
-  // need to do some cleanup of the garbage the LLM might have gave us
-  return (
-    instructions
-    .replaceAll("<|end|>", "")
-    .replaceAll("<s>", "")
-    .replaceAll("</s>", "")
-    .replaceAll("[INST]", "")
-    .replaceAll("[/INST]", "") 
-    .replaceAll("<SYS>", "")
-    .replaceAll("</SYS>", "")
-    .replaceAll("<|assistant|>", "")
-    .replaceAll('""', '"')
-  )
-}
-
-async function predictWithOpenAI(inputs: string) {
-  const openaiApiBaseUrl = `${process.env.OPENAI_API_BASE_URL || "https://api.openai.com/v1"}`
-  const openaiApiModel = `${process.env.OPENAI_API_MODEL || "gpt-3.5-turbo"}`
-  
-  const openai = new OpenAI({
-    apiKey: openaiApiKey,
-    baseURL: openaiApiBaseUrl,
-  })
-
-  const messages: ChatCompletionMessage[] = [
-    { role: "system", content: inputs },
-  ]
-
-  try {
-    const res = await openai.chat.completions.create({
-      messages: messages,
-      stream: false,
-      model: openaiApiModel,
-      temperature: 0.8
-    })
 
-    return res.choices[0].message.content
-  } catch (err) {
-    console.error(`error during generation: ${err}`)
-  }
-}
+export const predict = llmEngine === "OPENAI" ? predictWithOpenAI : predictWithHuggingFace

src/app/queries/predictWithHuggingFace.ts

@@ -0,0 +1,90 @@
+"use server"
+
+import { HfInference, HfInferenceEndpoint } from "@huggingface/inference"
+import { LLMEngine } from "@/types"
+
+const hf = new HfInference(process.env.AUTH_HF_API_TOKEN)
+
+const llmEngine = `${process.env.LLM_ENGINE || ""}` as LLMEngine
+const inferenceEndpoint = `${process.env.LLM_HF_INFERENCE_ENDPOINT_URL || ""}`
+const inferenceModel = `${process.env.LLM_HF_INFERENCE_API_MODEL || ""}`
+
+let hfie: HfInferenceEndpoint = hf
+
+switch (llmEngine) {
+  case "INFERENCE_ENDPOINT":
+    if (inferenceEndpoint) {
+      console.log("Using a custom HF Inference Endpoint")
+      hfie = hf.endpoint(inferenceEndpoint)
+    } else {
+      const error = "No Inference Endpoint URL defined"
+      console.error(error)
+      throw new Error(error)
+    }
+    break;
+  
+  case "INFERENCE_API":
+    if (inferenceModel) {
+      console.log("Using an HF Inference API Model")
+    } else {
+      const error = "No Inference API model defined"
+      console.error(error)
+      throw new Error(error)
+    }
+    break;
+
+  default:
+    const error = "Please check your Hugging Face Inference API or Inference Endpoint settings"
+    console.error(error)
+    throw new Error(error)
+}
+  
+const api = llmEngine === "INFERENCE_ENDPOINT" ? hfie : hf
+
+export async function predictWithHuggingFace(inputs: string) {
+  let instructions = ""
+  try {
+    for await (const output of api.textGenerationStream({
+      model: llmEngine === "INFERENCE_ENDPOINT" ? undefined : (inferenceModel || undefined),
+      inputs,
+      parameters: {
+        do_sample: true,
+        // we don't require a lot of token for our task
+        // but to be safe, let's count ~110 tokens per panel
+        max_new_tokens: 450, // 1150,
+        return_full_text: false,
+      }
+    })) {
+      instructions += output.token.text
+      process.stdout.write(output.token.text)
+      if (
+        instructions.includes("</s>") || 
+        instructions.includes("<s>") ||
+        instructions.includes("[INST]") ||
+        instructions.includes("[/INST]") ||
+        instructions.includes("<SYS>") ||
+        instructions.includes("</SYS>") ||
+        instructions.includes("<|end|>") ||
+        instructions.includes("<|assistant|>")
+      ) {
+        break
+      }
+    }
+  } catch (err) {
+    console.error(`error during generation: ${err}`)
+  }
+
+  // need to do some cleanup of the garbage the LLM might have gave us
+  return (
+    instructions
+    .replaceAll("<|end|>", "")
+    .replaceAll("<s>", "")
+    .replaceAll("</s>", "")
+    .replaceAll("[INST]", "")
+    .replaceAll("[/INST]", "") 
+    .replaceAll("<SYS>", "")
+    .replaceAll("</SYS>", "")
+    .replaceAll("<|assistant|>", "")
+    .replaceAll('""', '"')
+  )
+}

src/app/queries/predictWithOpenAI.ts

@@ -0,0 +1,33 @@
+"use server"
+
+import type { ChatCompletionMessage } from "openai/resources/chat"
+import OpenAI from "openai"
+
+const openaiApiKey = `${process.env.AUTH_OPENAI_API_KEY || ""}`
+
+export async function predictWithOpenAI(inputs: string) {
+  const openaiApiBaseUrl = `${process.env.LLM_OPENAI_API_BASE_URL || "https://api.openai.com/v1"}`
+  const openaiApiModel = `${process.env.LLM_OPENAI_API_MODEL || "gpt-3.5-turbo"}`
+  
+  const openai = new OpenAI({
+    apiKey: openaiApiKey,
+    baseURL: openaiApiBaseUrl,
+  })
+
+  const messages: ChatCompletionMessage[] = [
+    { role: "system", content: inputs },
+  ]
+
+  try {
+    const res = await openai.chat.completions.create({
+      messages: messages,
+      stream: false,
+      model: openaiApiModel,
+      temperature: 0.8
+    })
+
+    return res.choices[0].message.content
+  } catch (err) {
+    console.error(`error during generation: ${err}`)
+  }
+}

src/types.ts

@@ -91,6 +91,8 @@ export type RenderingEngine =
   | "VIDEOCHAIN"
   | "OPENAI"
   | "REPLICATE"
+  | "INFERENCE_API"
+  | "INFERENCE_ENDPOINT"
 
 export type PostVisibility =
   | "featured" // featured by admins