AI Automation Workflows
Build automated AI workflows via inference.sh CLI.
Quick Start
curl -fsSL https://cli.inference.sh | sh && infsh login
Simple automation: Generate daily image
infsh app run falai/flux-dev --input '{ "prompt": "Inspirational quote background, minimalist design, date: '"$(date +%Y-%m-%d)"'" }'
Automation Patterns
Pattern 1: Batch Processing
Process multiple items with the same workflow.
#!/bin/bash
batch_images.sh - Generate images for multiple prompts
PROMPTS=( "Mountain landscape at sunrise" "Ocean waves at sunset" "Forest path in autumn" "Desert dunes at night" )
for prompt in "${PROMPTS[@]}"; do echo "Generating: $prompt" infsh app run falai/flux-dev --input "{ "prompt": "$prompt, professional photography, 4K" }" > "output_${prompt// /_}.json" sleep 2 # Rate limiting done
Pattern 2: Sequential Pipeline
Chain multiple AI operations.
#!/bin/bash
content_pipeline.sh - Full content creation pipeline
TOPIC="AI in healthcare"
Step 1: Research
echo "Researching..." RESEARCH=$(infsh app run tavily/search-assistant --input "{ "query": "$TOPIC latest developments" }")
Step 2: Write article
echo "Writing article..." ARTICLE=$(infsh app run openrouter/claude-sonnet-45 --input "{ "prompt": "Write a 500-word blog post about $TOPIC based on: $RESEARCH" }")
Step 3: Generate image
echo "Generating image..." IMAGE=$(infsh app run falai/flux-dev --input "{ "prompt": "Blog header image for article about $TOPIC, modern, professional" }")
Step 4: Generate social post
echo "Creating social post..." SOCIAL=$(infsh app run openrouter/claude-haiku-45 --input "{ "prompt": "Write a Twitter thread (5 tweets) summarizing: $ARTICLE" }")
echo "Pipeline complete!"
Pattern 3: Parallel Processing
Run multiple operations simultaneously.
#!/bin/bash
parallel_generation.sh - Generate multiple assets in parallel
Start all jobs in background
infsh app run falai/flux-dev --input '{"prompt": "Hero image..."}' > hero.json & PID1=$!
infsh app run falai/flux-dev --input '{"prompt": "Feature image 1..."}' > feature1.json & PID2=$!
infsh app run falai/flux-dev --input '{"prompt": "Feature image 2..."}' > feature2.json & PID3=$!
Wait for all to complete
wait $PID1 $PID2 $PID3 echo "All images generated!"
Pattern 4: Conditional Workflow
Branch based on results.
#!/bin/bash
conditional_workflow.sh - Process based on content analysis
INPUT_TEXT="$1"
Analyze content
ANALYSIS=$(infsh app run openrouter/claude-haiku-45 --input "{ "prompt": "Classify this text as: positive, negative, or neutral. Return only the classification.\n\n$INPUT_TEXT" }")
Branch based on result
case "$ANALYSIS" in positive) echo "Generating celebration image..." infsh app run falai/flux-dev --input '{"prompt": "Celebration, success, happy"}' ;; negative) echo "Generating supportive message..." infsh app run openrouter/claude-sonnet-45 --input "{ "prompt": "Write a supportive, encouraging response to: $INPUT_TEXT" }" ;; *) echo "Generating neutral acknowledgment..." ;; esac
Pattern 5: Retry with Fallback
Handle failures gracefully.
#!/bin/bash
retry_workflow.sh - Retry failed operations
generate_with_retry() { local prompt="$1" local max_attempts=3 local attempt=1
while [ $attempt -le $max_attempts ]; do echo "Attempt $attempt..."
result=$(infsh app run falai/flux-dev --input "{\"prompt\": \"$prompt\"}" 2>&1)
if [ $? -eq 0 ]; then
echo "$result"
return 0
fi
echo "Failed, retrying..."
((attempt++))
sleep $((attempt * 2)) # Exponential backoff
done
Fallback to different model
echo "Falling back to alternative model..." infsh app run google/imagen-3 --input "{"prompt": "$prompt"}" }
generate_with_retry "A beautiful sunset over mountains"
Scheduled Automation
Cron Job Setup
Edit crontab
crontab -e
Daily content generation at 9 AM
0 9 * * * /path/to/daily_content.sh >> /var/log/ai-automation.log 2>&1
Weekly report every Monday at 8 AM
0 8 * * 1 /path/to/weekly_report.sh >> /var/log/ai-automation.log 2>&1
Every 6 hours: social media content
0 */6 * * * /path/to/social_content.sh >> /var/log/ai-automation.log 2>&1
Daily Content Script
#!/bin/bash
daily_content.sh - Run daily at 9 AM
DATE=$(date +%Y-%m-%d) OUTPUT_DIR="/output/$DATE" mkdir -p "$OUTPUT_DIR"
Generate daily quote image
infsh app run falai/flux-dev --input '{ "prompt": "Motivational quote background, minimalist, morning vibes" }' > "$OUTPUT_DIR/quote_image.json"
Generate daily tip
infsh app run openrouter/claude-haiku-45 --input '{ "prompt": "Give me one actionable productivity tip for today. Be concise." }' > "$OUTPUT_DIR/daily_tip.json"
Post to social (optional)
infsh app run twitter/post-tweet --input "{...}"
echo "Daily content generated: $DATE"
Monitoring and Logging
Logging Wrapper
#!/bin/bash
logged_workflow.sh - With comprehensive logging
LOG_FILE="/var/log/ai-workflow-$(date +%Y%m%d).log"
log() { echo "[$(date '+%Y-%m-%d %H:%M:%S')] $1" | tee -a "$LOG_FILE" }
log "Starting workflow"
Track execution time
START_TIME=$(date +%s)
Run workflow
log "Generating image..." RESULT=$(infsh app run falai/flux-dev --input '{"prompt": "test"}' 2>&1) STATUS=$?
if [ $STATUS -eq 0 ]; then log "Success: Image generated" else log "Error: $RESULT" fi
END_TIME=$(date +%s) DURATION=$((END_TIME - START_TIME)) log "Completed in ${DURATION}s"
Error Alerting
#!/bin/bash
monitored_workflow.sh - With error alerts
run_with_alert() { local result result=$("$@" 2>&1) local status=$?
if [ $status -ne 0 ]; then
# Send alert (webhook, email, etc.)
curl -X POST "https://your-webhook.com/alert"
-H "Content-Type: application/json"
-d "{"error": "$result", "command": "$*"}"
fi
echo "$result" return $status }
run_with_alert infsh app run falai/flux-dev --input '{"prompt": "test"}'
Python SDK Automation
#!/usr/bin/env python3
automation.py - Python-based workflow
import subprocess import json from datetime import datetime from pathlib import Path
def run_infsh(app_id: str, input_data: dict) -> dict: """Run inference.sh app and return result.""" result = subprocess.run( ["infsh", "app", "run", app_id, "--input", json.dumps(input_data)], capture_output=True, text=True ) return json.loads(result.stdout) if result.returncode == 0 else None
def daily_content_pipeline(): """Generate daily content.""" date_str = datetime.now().strftime("%Y-%m-%d") output_dir = Path(f"output/{date_str}") output_dir.mkdir(parents=True, exist_ok=True)
# Generate image
image = run_infsh("falai/flux-dev", {
"prompt": f"Daily inspiration for {date_str}, beautiful, uplifting"
})
(output_dir / "image.json").write_text(json.dumps(image))
# Generate caption
caption = run_infsh("openrouter/claude-haiku-45", {
"prompt": "Write an inspiring caption for a daily motivation post. 2-3 sentences."
})
(output_dir / "caption.json").write_text(json.dumps(caption))
print(f"Generated content for {date_str}")
if name == "main": daily_content_pipeline()
Workflow Templates
Content Calendar Automation
#!/bin/bash
content_calendar.sh - Generate week of content
TOPICS=("productivity" "wellness" "technology" "creativity" "leadership") DAYS=("Monday" "Tuesday" "Wednesday" "Thursday" "Friday")
for i in "${!DAYS[@]}"; do DAY=${DAYS[$i]} TOPIC=${TOPICS[$i]}
echo "Generating $DAY content about $TOPIC..."
Image
infsh app run falai/flux-dev --input "{ "prompt": "$TOPIC theme, $DAY motivation, social media style" }" > "content/${DAY}_image.json"
Caption
infsh app run openrouter/claude-haiku-45 --input "{ "prompt": "Write a $DAY motivation post about $TOPIC. Include hashtags." }" > "content/${DAY}_caption.json" done
Data Processing Pipeline
#!/bin/bash
data_processing.sh - Process and analyze data files
INPUT_DIR="./data/raw" OUTPUT_DIR="./data/processed"
for file in "$INPUT_DIR"/*.txt; do filename=$(basename "$file" .txt)
Analyze content
infsh app run openrouter/claude-haiku-45 --input "{ "prompt": "Analyze this data and provide key insights in JSON format: $(cat $file)" }" > "$OUTPUT_DIR/${filename}_analysis.json"
done
Best Practices
-
Rate limiting - Add delays between API calls
-
Error handling - Always check return codes
-
Logging - Track all operations
-
Idempotency - Design for safe re-runs
-
Monitoring - Alert on failures
-
Backups - Save intermediate results
-
Timeouts - Set reasonable limits
Related Skills
Content pipelines
npx skills add inferencesh/skills@ai-content-pipeline
RAG pipelines
npx skills add inferencesh/skills@ai-rag-pipeline
Social media automation
npx skills add inferencesh/skills@ai-social-media-content
Full platform skill
npx skills add inferencesh/skills@inference-sh
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