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Remove the background from an input image. Accepts PNG/JPG/JPEG. Returns a transparent PNG file. Args: image (FilePath): User-uploaded image path. Returns: str: Path to the output PNG file with background removed.

Remove the background from an input image. Accepts PNG/JPG/JPEG. Returns a transparent PNG file. Just upload your photo

Smartly detect and clean duplicates from your dataset (CSV or Excel). This function scans your data to find: 🔁 Exact duplicates — identical rows or repeated entries. 🤖 Fuzzy duplicates — similar rows with small differences (typos, spacing, casing, or minor text variations).

Generate randomized function ideas as CSV. Args: n_results (int): Number of ideas to generate (max 100000). Returns: str: Path to generated CSV file containing columns: id, idea_name, description, category, tags.

Smartly detect and clean duplicates from your dataset (CSV or Excel). This function scans your data to find: - 🔁 **Exact duplicates** — identical rows or repeated entries. - 🤖 **Fuzzy duplicates** — similar rows with small differences (typos, spacing, casing, or minor text variations). It automatically keeps the **first valid occurrence** of each duplicate and exports everything neatly organized in a single downloadable ZIP. 📦 Inside the ZIP you’ll get: 1. `deduplicated_<name>.csv` — your cleaned dataset (duplicates removed) 2. `duplicates_removed_<name>.csv` — all duplicate rows that were dropped 3. `fuzzy_pairs_<name>.csv` — pairs of rows that look alike (based on similarity) Args: file (FilePath): The uploaded CSV or Excel file to analyze. subset (str): Optional — comma-separated list of column names to check. If left empty, all columns are analyzed. similarity_threshold (int): Optional — how strict fuzzy matching should be (0–100). Higher = only very similar values are flagged. Default = 90 (good balance). Returns: str: Generated ZIP archive containing the cleaned dataset and detailed duplicate reports.

Remove rows containing NaN values from a CSV or Excel file. The cleaned file is saved in the same format (CSV or XLSX). Args: file (FilePath): Input CSV or Excel file. Returns: str: Path to the cleaned file (same format as input).

Generate a synthetic CSV file with random data and some NaN values. Args: rows (int): Number of rows to generate. nan_ratio (float): Approximate fraction of cells to replace with NaN (0–1). Returns: str: Path to the generated CSV file.

Generates 10 white noise tracks (16-bit mono WAV) with random durations between user-defined limits, smooth fade-in/out, and packages them into a ZIP file. ⚙️ Inputs min_duration (int) — minimum duration of each noise file, in seconds. max_duration (int) — maximum duration of each noise file, in seconds. sample_rate (int) — number of samples per second (e.g., 44100 for CD quality). amplitude (float) — overall loudness from 0.0 (silent) to 1.0 (maximum volume). fade_duration (float) — fade-in and fade-out time in seconds for smoother transitions. 📦 Output Returns a .zip file containing all generated white noise WAV tracks.

Generates a white noise sound (16-bit mono WAV) of customizable duration, sample rate, and amplitude, then returns the file. ⚙️ Inputs duration_seconds (int) — total duration of the generated noise in seconds. sample_rate (int) — number of samples per second (e.g., 44100 for CD quality). amplitude (float) — loudness from 0.0 (silent) to 1.0 (max volume). 📦 Output Returns the .wav file containing the generated white noise.

Download any TikTok video with no watermark

You can simply generate and download a testfile for other functions