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# =================== Lord Of Large Language Multimodal Systems Configuration file ===========================
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version: 159
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version: 160
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# video viewing and news recovering
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last_viewed_video: null
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@ -31,7 +31,7 @@ host: localhost
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port: 9600
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app_custom_logo: ""
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app_custom_name: "LoLLMS"
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app_custom_name: ""
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app_show_changelogs: true
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app_custom_welcome_message: ""
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app_custom_slogan: ""
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@ -1,5 +1,5 @@
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# =================== Lord Of Large Language Multimodal Systems Configuration file ===========================
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version: 159
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version: 160
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# video viewing and news recovering
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last_viewed_video: null
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@ -31,7 +31,7 @@ host: localhost
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port: 9600
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app_custom_logo: ""
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app_custom_name: "LoLLMS"
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app_custom_name: ""
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app_show_changelogs: true
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app_custom_welcome_message: ""
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app_custom_slogan: ""
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@ -1,5 +1,5 @@
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# =================== Lord Of Large Language Multimodal Systems Configuration file ===========================
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version: 159
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version: 160
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# video viewing and news recovering
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last_viewed_video: null
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@ -31,7 +31,7 @@ host: localhost
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port: 9600
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app_custom_logo: ""
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app_custom_name: "LoLLMS"
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app_custom_name: ""
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app_show_changelogs: true
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app_custom_welcome_message: ""
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app_custom_slogan: ""
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@ -42,6 +42,13 @@ class LollmsNovitaAITextToVideo(LollmsTTV):
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self.model_name = self.service_config.model_name
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self.base_url = "https://api.novita.ai/v3/async"
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models = self.getModels()
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service_config.config_template["model_name"]["options"] = models
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def settings_updated(self):
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models = self.getModels()
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self.service_config.config_template["model_name"]["options"] = models
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def getModels(self):
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"""
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Gets the list of models
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@ -96,6 +103,8 @@ class LollmsNovitaAITextToVideo(LollmsTTV):
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model_name = self.model_name
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if output_dir is None:
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output_dir = self.output_folder
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url = f"{self.base_url}/txt2video"
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headers = {
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"Authorization": f"Bearer {self.service_config.api_key}",
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@ -153,8 +162,6 @@ class LollmsNovitaAITextToVideo(LollmsTTV):
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return file_name
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return None
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def settings_updated(self):
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pass
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def generate_video_by_frames(self, prompts: List[str], frames: List[int], negative_prompt: str, fps: int = 8,
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num_inference_steps: int = 50, guidance_scale: float = 6.0,
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