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memefast/bash/webm_metadata.sh
2025-06-08 04:39:38 +08:00

281 lines
8.8 KiB
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#!/bin/bash
# Script to process .webm files and generate metadata using OpenAI API
# Requires: dotenv-cli, jq
# Usage: ./webm_metadata.sh [directory_path]
set -e # Exit on any error
# Get the directory where the script is located
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
# Get target directory (default to current directory)
TARGET_DIR="${1:-.}"
TARGET_DIR="$(cd "$TARGET_DIR" && pwd)" # Convert to absolute path
# Check dependencies
command -v dotenv >/dev/null 2>&1 || { echo "Error: dotenv-cli is required. Install with: npm install -g dotenv-cli" >&2; exit 1; }
command -v jq >/dev/null 2>&1 || { echo "Error: jq is required. Install with: apt-get install jq or brew install jq" >&2; exit 1; }
# Check if .env exists in script directory
ENV_FILE="$SCRIPT_DIR/.env"
if [ ! -f "$ENV_FILE" ]; then
echo "Error: .env file not found at $ENV_FILE"
echo "Please create one with OPENAI_API_KEY=your_key"
exit 1
fi
echo "Script directory: $SCRIPT_DIR"
echo "Target directory: $TARGET_DIR"
echo "Looking for .env at: $ENV_FILE"
echo ""
# Configuration
CSV_FILE="$TARGET_DIR/webm_metadata.csv"
DELAY_SECONDS=1
# Function to check if filename already processed
is_processed() {
local filename="$1"
grep -q "^\"$filename\"," "$CSV_FILE" 2>/dev/null
}
# Function to escape CSV field
escape_csv() {
local field="$1"
# Escape double quotes and wrap in quotes
echo "\"$(echo "$field" | sed 's/"/\"\"/g')\""
}
# Function to make API call and extract metadata
process_file() {
local filename="$1"
echo "Processing: $filename"
# Create the system prompt text
local system_prompt="You are an AI assistant that receives a meme filename. Based on the filename, your task is to generate detailed metadata describing the meme in a structured format.
The metadata should include these fields:
- **type**: either \`video\` or \`image\` depending on the file extension.
- **sub_type**: a classification such as \`background\` or \`overlay\` (choose \`overlay\` if it seems like an edit or reaction video/image).
- **name**: a concise, title-cased name derived from the filename (remove file extension and normalize, without the Meme word if exist).
- **description**: a short paragraph describing the meme content and context inferred from the name, and reaction
- **keywords**: a comma-separated list of relevant keywords extracted from the filename or meme context.
- **media_1_mime_type**: the MIME type derived from the file extension (e.g., \`video/webm\`, \`image/png\`).
Return the output as a JSON object containing these fields. Use null for any unknown or missing values.
---
#### Example input:
\`7th element oiiaa cat.webm\`
#### Example output:
\`\`\`json
{
\"type\": \"video\",
\"sub_type\": \"overlay\",
\"name\": \"7th Element Oiiaa Cat\",
\"description\": \"a cat edited to mimic or react to Vitas' bizarre vocals from the viral \\\"7th Element\\\" performance.\",
\"keywords\": \"cat, oiiaa, 7th element, vitas, webm, funny\",
\"media_1_mime_type\": \"video/webm\"
}
\`\`\`"
local assistant_example="\`\`\`json
{
\"type\": \"video\",
\"sub_type\": \"overlay\",
\"name\": \"Angry Cat\",
\"description\": \"A video meme featuring an angry-looking cat, typically used to express frustration, annoyance, or irritation in a humorous way.\",
\"keywords\": \"angry, cat, reaction, meme, webm, annoyed, frustration\",
\"media_1_mime_type\": \"video/webm\"
}
\`\`\`"
# Use jq to properly construct the JSON payload
local json_payload=$(jq -n \
--arg system_prompt "$system_prompt" \
--arg filename "$filename" \
--arg assistant_example "$assistant_example" \
'{
"model": "gpt-4.1-nano",
"input": [
{
"role": "system",
"content": [
{
"type": "input_text",
"text": $system_prompt
}
]
},
{
"role": "user",
"content": [
{
"type": "input_text",
"text": $filename
}
]
},
{
"role": "assistant",
"content": [
{
"type": "output_text",
"text": $assistant_example
}
]
}
],
"text": {
"format": {
"type": "json_object"
}
},
"reasoning": {},
"tools": [],
"temperature": 1,
"max_output_tokens": 2048,
"top_p": 1,
"store": true
}')
# Make the API call
local response=$(curl -s "https://api.openai.com/v1/responses" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d "$json_payload")
# Check for API errors
if echo "$response" | jq -e '.error' >/dev/null 2>&1; then
echo "API Error for $filename:"
echo "$response" | jq '.error'
return 1
fi
# Extract the response text from the correct path
local response_text=$(echo "$response" | jq -r '.output[0].content[0].text // empty')
if [ -z "$response_text" ]; then
echo "Error: Empty response for $filename"
return 1
fi
# With JSON mode enabled, response should always be direct JSON
local json_content="$response_text"
# Validate that it's valid JSON before parsing
if ! echo "$json_content" | jq . >/dev/null 2>&1; then
echo "Error: Invalid JSON response for $filename"
echo "Content: $json_content"
return 1
fi
# Parse individual fields
local type=$(echo "$json_content" | jq -r '.type // "unknown"')
local sub_type=$(echo "$json_content" | jq -r '.sub_type // "unknown"')
local name=$(echo "$json_content" | jq -r '.name // "unknown"')
local description=$(echo "$json_content" | jq -r '.description // "unknown"')
local keywords=$(echo "$json_content" | jq -r '.keywords // "unknown"')
local media_1_mime_type=$(echo "$json_content" | jq -r '.media_1_mime_type // "unknown"')
# Write to CSV
local csv_line="$(escape_csv "$filename"),$(escape_csv "$type"),$(escape_csv "$sub_type"),$(escape_csv "$name"),$(escape_csv "$description"),$(escape_csv "$keywords"),$(escape_csv "$media_1_mime_type")"
echo "$csv_line" >> "$CSV_FILE"
echo "✓ Successfully processed: $filename"
}
# Export functions so they're available in the dotenv subshell
export -f is_processed
export -f escape_csv
export -f process_file
export CSV_FILE
export DELAY_SECONDS
export TARGET_DIR
# Change to script directory so dotenv can find the .env file
cd "$SCRIPT_DIR"
# Use dotenv to run the main processing logic
dotenv -- bash -c '
# Check if OPENAI_API_KEY is loaded
if [ -z "$OPENAI_API_KEY" ]; then
echo "Error: OPENAI_API_KEY not found in environment variables"
exit 1
fi
echo "✓ OpenAI API key loaded successfully"
echo "CSV file will be: $CSV_FILE"
echo "Delay between requests: ${DELAY_SECONDS}s"
echo ""
# Create CSV with headers if it doesn'\''t exist
if [ ! -f "$CSV_FILE" ]; then
echo "filename,type,sub_type,name,description,keywords,media_1_mime_type" > "$CSV_FILE"
echo "Created $CSV_FILE with headers"
fi
echo "Starting processing of .webm files..."
# Count total files and processed files
total_files=$(ls -1 "$TARGET_DIR"/*.webm 2>/dev/null | wc -l)
processed_count=0
skipped_count=0
error_count=0
if [ "$total_files" -eq 0 ]; then
echo "No .webm files found in $TARGET_DIR"
exit 0
fi
echo "Found $total_files .webm files"
# Process each .webm file
for webm_file in "$TARGET_DIR"/*.webm; do
if [ ! -f "$webm_file" ]; then
continue
fi
# Get just the filename (not full path) for processing
filename=$(basename "$webm_file")
# Check if already processed
if is_processed "$filename"; then
echo "⏭️ Skipping (already processed): $filename"
((skipped_count++))
continue
fi
# Process the file
if process_file "$filename"; then
((processed_count++))
else
echo "❌ Failed to process: $filename"
((error_count++))
fi
# Progress update
total_done=$((processed_count + skipped_count + error_count))
echo "Progress: $total_done/$total_files (Processed: $processed_count, Skipped: $skipped_count, Errors: $error_count)"
echo ""
# Rate limiting delay (skip on last file)
if [ "$total_done" -lt "$total_files" ]; then
echo "Waiting ${DELAY_SECONDS}s before next request..."
sleep "$DELAY_SECONDS"
fi
done
echo "===================="
echo "Processing complete!"
echo "Total files: $total_files"
echo "Newly processed: $processed_count"
echo "Already processed (skipped): $skipped_count"
echo "Errors: $error_count"
echo "CSV file: $CSV_FILE"
echo "===================="
'