Functions — github.com/TIGER-AI-Lab/TheoremExplainAgent

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Functions142 in github.com/TIGER-AI-Lab/TheoremExplainAgent

⨍ Functions 142◇ Types & classes 12

Method__init__

Initialize the CodeGenerator. Args: scene_model: The model used for scene generation helper_model: The model used for

src/core/code_generator.py:32

Method__init__

(self, helper_model, output_dir, chroma_db_path, manim_docs_path, embedding_model, use_langfuse=True, session_

src/rag/rag_integration.py:33

Method__init__

(self, chroma_db_path: str = "chroma_db", manim_docs_path: str = "rag/manim

src/rag/vector_store.py:37

Method__init__

(self, embedding_model)

src/rag/vector_store.py:116

Function_extract_code

Helper to extract code block from model response, support Gemini style and OpenAI style

mllm_tools/utils.py:117

Function_extract_code

Extract code blocks from a text response. Extracts Python code blocks delimited by ```python markers. If no code blocks are found, returns th

src/utils/utils.py:28

Function_fix_unicode_to_latex

Convert Unicode symbols to LaTeX source code. Converts Unicode subscripts and superscripts to LaTeX format, with optional full Unicode parsing.

src/utils/utils.py:81

Method_generate_rag_queries_code

Generate RAG queries from implementation plan. Args: implementation_plan (str): Implementation plan text to generate queries from

src/rag/rag_integration.py:288

Method_generate_rag_queries_error_fix

Generate RAG queries for fixing code errors. Args: error (str): Error message to generate queries from code (str): Co

src/rag/rag_integration.py:334

Method_load_topic_session_id

Load session ID for a specific topic if it exists. Args: topic (str): The topic to load the session ID for Retu

generate_video.py:175

Function_prepare_text_audio_inputs

Converts text strings and audio file paths into the input format for the Agent model. Args: texts (Union[str, List[str]]): Text stri

mllm_tools/utils.py:88

Function_print_response

Print formatted responses from the video generation process. Prints a formatted response with separators and headers for readability. Args:

src/utils/utils.py:8

Function_upload_to_gemini

Uploads the given file or PIL image to Gemini. See https://ai.google.dev/gemini-api/docs/prompting_with_media

mllm_tools/utils.py:127

Methodadjust_time

(time_str, offset)

src/core/video_renderer.py:416

Methodcombine_videos

Combine all videos and subtitle files for a specific topic using ffmpeg. Args: topic (str): Topic name to combine videos for

src/core/video_renderer.py:203

Methodcreate_snapshot_scene

Create a snapshot of the video for a specific topic and scene using VideoRenderer. Args: topic (str): The topic of the v

generate_video.py:436

Methodembed_documents

(self, texts: list[str])

src/rag/vector_store.py:119

Methodembed_query

(self, text: str)

src/rag/vector_store.py:131

Functionextract_json

Extract and parse JSON content from a text response. Attempts to parse the response as JSON directly, then tries to extract JSON from code blocks

src/utils/utils.py:48

Functionextract_trasnscript

Extract transcript from video audio using Google Speech Recognition. Args: video_path (str): Path to the video file. Returns:

src/core/parse_video.py:165

Methodgenerate_from_text

(self, text: str, cache_dir: str = None, path: str = None)

src/utils/kokoro_voiceover.py:80

Methodgenerate_scene_implementation

Generate scene implementations using VideoPlanner. Args: topic (str): The topic of the video description (st

generate_video.py:211

Methodgenerate_scene_implementation

Generate detailed implementation plans for all scenes. Args: topic (str): The topic of the video description (str): D

src/core/video_planner.py:348

Methodgenerate_scene_implementation_concurrently

Generate scene implementations concurrently using VideoPlanner. Args: topic (str): The topic of the video de

generate_video.py:230

Methodgenerate_scene_implementation_concurrently

Generate detailed implementation plans for all scenes concurrently with controlled concurrency. Args: topic (str): The topic of t

src/core/video_planner.py:385

Methodgenerate_scene_outline

Generate a scene outline based on the topic and description. Args: topic (str): The topic of the video description (s

src/core/video_planner.py:135

Methodgenerate_single_scene_implementation

(i)

src/core/video_planner.py:408

Functionget_media_wrapper

Get appropriate wrapper for media handling based on model name

mllm_tools/utils.py:148

Functionget_prompt_animation

(topic: str, description: str, additional_context: Union[str, List[str]] = None)

task_generator/__init__.py:241

Functionget_prompt_animation_fix_error

Generate a prompt to fix errors in the given manim code. Args: text_explanation (str): The implementation plan of the scene.

task_generator/__init__.py:255

Functionget_prompt_animation_rag_query_generation

(topic: str, context: str, relevant_plugins: str)

task_generator/__init__.py:281

Functionget_prompt_animation_rag_query_generation_fix_error

(text_explanation: str, error: str, code: str)

task_generator/__init__.py:291

Functionget_prompt_context_learning_animation_narration

(examples: str)

task_generator/__init__.py:210

Functionget_prompt_context_learning_scene_plan

(examples: str)

task_generator/__init__.py:192

Functionget_prompt_context_learning_technical_implementation

(examples: str)

task_generator/__init__.py:204

Functionget_prompt_context_learning_vision_storyboard

(examples: str)

task_generator/__init__.py:198

Functionget_prompt_visual_fix_error

(implementation: str, generated_code: str)

task_generator/__init__.py:143

Functionprepare_media_messages

Prepare messages for media input based on model type

mllm_tools/utils.py:156

Methodrun_manim_process

Run manim on all generated manim code for a specific topic using VideoRenderer. Args: topic (str): The topic to render v

generate_video.py:426

Methodrun_manim_process

Run manim on all generated manim code for a specific topic. Args: topic (str): Topic name to process Returns:

src/core/video_renderer.py:128

Methodtext_to_speech

Generates speech from text using Kokoro ONNX and saves the audio file. Normalizes the audio to make it audible.

src/utils/kokoro_voiceover.py:55

Methodvisual_self_reflection

Use snapshot image or mp4 video to fix code. Args: code (str): Code to fix media_path (Union[str, Image.Image]): Path

src/core/code_generator.py:392

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