Headless Mode

Headless mode allows you to run Qwen Code programmatically from command line scripts and automation tools without any interactive UI. This is ideal for scripting, automation, CI/CD pipelines, and building AI-powered tools.

Overview

The headless mode provides a headless interface to Qwen Code that:

Accepts prompts via command line arguments or stdin
Returns structured output (text or JSON)
Supports file redirection and piping
Enables automation and scripting workflows
Provides consistent exit codes for error handling

Basic Usage

Direct Prompts

Use the --prompt (or -p) flag to run in headless mode:


qwen --prompt "What is machine learning?"

Stdin Input

Pipe input to Qwen Code from your terminal:


echo "Explain this code" | qwen

Combining with File Input

Read from files and process with Qwen Code:


cat README.md | qwen --prompt "Summarize this documentation"

Output Formats

Qwen Code supports multiple output formats for different use cases:

Text Output (Default)

Standard human-readable output:


qwen -p "What is the capital of France?"

Response format:


The capital of France is Paris.

JSON Output

Returns structured data as a JSON array. All messages are buffered and output together when the session completes. This format is ideal for programmatic processing and automation scripts.

The JSON output is an array of message objects. The output includes multiple message types: system messages (session initialization), assistant messages (AI responses), and result messages (execution summary).

Example Usage


qwen -p "What is the capital of France?" --output-format json

Output (at end of execution):


[
  {
    "type": "system",
    "subtype": "session_start",
    "uuid": "...",
    "session_id": "...",
    "model": "qwen3-coder-plus",
    ...
  },
  {
    "type": "assistant",
    "uuid": "...",
    "session_id": "...",
    "message": {
      "id": "...",
      "type": "message",
      "role": "assistant",
      "model": "qwen3-coder-plus",
      "content": [
        {
          "type": "text",
          "text": "The capital of France is Paris."
        }
      ],
      "usage": {...}
    },
    "parent_tool_use_id": null
  },
  {
    "type": "result",
    "subtype": "success",
    "uuid": "...",
    "session_id": "...",
    "is_error": false,
    "duration_ms": 1234,
    "result": "The capital of France is Paris.",
    "usage": {...}
  }
]

Stream-JSON Output

Stream-JSON format emits JSON messages immediately as they occur during execution, enabling real-time monitoring. This format uses line-delimited JSON where each message is a complete JSON object on a single line.


qwen -p "Explain TypeScript" --output-format stream-json

Output (streaming as events occur):


{"type":"system","subtype":"session_start","uuid":"...","session_id":"..."}
{"type":"assistant","uuid":"...","session_id":"...","message":{...}}
{"type":"result","subtype":"success","uuid":"...","session_id":"..."}

When combined with --include-partial-messages, additional stream events are emitted in real-time (message_start, content_block_delta, etc.) for real-time UI updates.


qwen -p "Write a Python script" --output-format stream-json --include-partial-messages

Input Format

The --input-format parameter controls how Qwen Code consumes input from standard input:

text (default): Standard text input from stdin or command-line arguments
stream-json: JSON message protocol via stdin for bidirectional communication

Note: Stream-json input mode is currently under construction and is intended for SDK integration. It requires --output-format stream-json to be set.

File Redirection

Save output to files or pipe to other commands:


# Save to file
qwen -p "Explain Docker" > docker-explanation.txt
qwen -p "Explain Docker" --output-format json > docker-explanation.json
 
# Append to file
qwen -p "Add more details" >> docker-explanation.txt
 
# Pipe to other tools
qwen -p "What is Kubernetes?" --output-format json | jq '.response'
qwen -p "Explain microservices" | wc -w
qwen -p "List programming languages" | grep -i "python"
 
# Stream-JSON output for real-time processing
qwen -p "Explain Docker" --output-format stream-json | jq '.type'
qwen -p "Write code" --output-format stream-json --include-partial-messages | jq '.event.type'

Configuration Options

Key command-line options for headless usage:

Option	Description	Example
`--prompt`, `-p`	Run in headless mode	`qwen -p "query"`
`--output-format`, `-o`	Specify output format (text, json, stream-json)	`qwen -p "query" --output-format json`
`--input-format`	Specify input format (text, stream-json)	`qwen --input-format text --output-format stream-json`
`--include-partial-messages`	Include partial messages in stream-json output	`qwen -p "query" --output-format stream-json --include-partial-messages`
`--debug`, `-d`	Enable debug mode	`qwen -p "query" --debug`
`--all-files`, `-a`	Include all files in context	`qwen -p "query" --all-files`
`--include-directories`	Include additional directories	`qwen -p "query" --include-directories src,docs`
`--yolo`, `-y`	Auto-approve all actions	`qwen -p "query" --yolo`
`--approval-mode`	Set approval mode	`qwen -p "query" --approval-mode auto_edit`

For complete details on all available configuration options, settings files, and environment variables, see the Configuration Guide.

Examples

Code review


cat src/auth.py | qwen -p "Review this authentication code for security issues" > security-review.txt

Generate commit messages


result=$(git diff --cached | qwen -p "Write a concise commit message for these changes" --output-format json)
echo "$result" | jq -r '.response'

API documentation


result=$(cat api/routes.js | qwen -p "Generate OpenAPI spec for these routes" --output-format json)
echo "$result" | jq -r '.response' > openapi.json

Batch code analysis


for file in src/*.py; do
    echo "Analyzing $file..."
    result=$(cat "$file" | qwen -p "Find potential bugs and suggest improvements" --output-format json)
    echo "$result" | jq -r '.response' > "reports/$(basename "$file").analysis"
    echo "Completed analysis for $(basename "$file")" >> reports/progress.log
done

PR code review


result=$(git diff origin/main...HEAD | qwen -p "Review these changes for bugs, security issues, and code quality" --output-format json)
echo "$result" | jq -r '.response' > pr-review.json

Log analysis


grep "ERROR" /var/log/app.log | tail -20 | qwen -p "Analyze these errors and suggest root cause and fixes" > error-analysis.txt

Release notes generation


result=$(git log --oneline v1.0.0..HEAD | qwen -p "Generate release notes from these commits" --output-format json)
response=$(echo "$result" | jq -r '.response')
echo "$response"
echo "$response" >> CHANGELOG.md

Model and tool usage tracking


result=$(qwen -p "Explain this database schema" --include-directories db --output-format json)
total_tokens=$(echo "$result" | jq -r '.stats.models // {} | to_entries | map(.value.tokens.total) | add // 0')
models_used=$(echo "$result" | jq -r '.stats.models // {} | keys | join(", ") | if . == "" then "none" else . end')
tool_calls=$(echo "$result" | jq -r '.stats.tools.totalCalls // 0')
tools_used=$(echo "$result" | jq -r '.stats.tools.byName // {} | keys | join(", ") | if . == "" then "none" else . end')
echo "$(date): $total_tokens tokens, $tool_calls tool calls ($tools_used) used with models: $models_used" >> usage.log
echo "$result" | jq -r '.response' > schema-docs.md
echo "Recent usage trends:"
tail -5 usage.log

Resources

CLI Configuration - Complete configuration guide
Authentication - Setup authentication
Commands - Interactive commands reference
Tutorials - Step-by-step automation guides