Ai Automation Workflows

# AI Automation Workflows

通过 [inference.sh](https://inference.sh) CLI 构建自动化 AI 工作流。


## 快速开始

```bash 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)"'" }' ```

> **安装说明：** [安装脚本](https://cli.inference.sh) 仅检测您的操作系统/架构，从 `dist.inference.sh` 下载匹配的二进制文件，并验证其 SHA-256 校验和。不需要提权或后台进程。[手动安装与验证](https://dist.inference.sh/cli/checksums.txt) 也可用。

## 自动化模式

### 模式 1：批处理

使用同一工作流处理多个项目。

```bash #!/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 ```

### 模式 2：顺序流水线

链接多个 AI 操作。

```bash #!/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!" ```

### 模式 3：并行处理

同时运行多个操作。

```bash #!/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!" ```

### 模式 4：条件工作流

根据结果分支。

```bash #!/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 ```

### 模式 5：重试与回退

优雅地处理失败。

```bash #!/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" ```

## 定时自动化

### Cron 任务设置

```bash # 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 ```

### 每日内容脚本

```bash #!/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" ```

## 监控与日志

### 日志封装

```bash #!/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" ```

### 错误告警

```bash #!/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 自动化

```python #!/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() ```

## 工作流模板

### 内容日历自动化

```bash #!/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 ```

### 数据处理流水线

```bash #!/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 ```

## 最佳实践

1. **速率限制** - 在 API 调用之间添加延迟 2. **错误处理** - 始终检查返回码 3. **日志记录** - 跟踪所有操作 4. **幂等性** - 设计以支持安全重试 5. **监控** - 在失败时发出告警 6. **备份** - 保存中间结果 7. **超时** - 设置合理的限制

## 相关技能

```bash # Content pipelines npx skills add inference-sh/skills@ai-content-pipeline

# RAG pipelines npx skills add inference-sh/skills@ai-rag-pipeline

# Social media automation npx skills add inference-sh/skills@ai-social-media-content

# Full platform skill npx skills add inference-sh/skills@inference-sh ```

浏览所有应用：`infsh app list`