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
Can resume previous sessions scoped to the current project for multi-step automation

Basic Usage

Direct Prompts

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

bash

qwen --prompt "What is machine learning?"

Stdin Input

Pipe input to Qwen Code from your terminal:

bash

echo "Explain this code" | qwen

Combining with File Input

Read from files and process with Qwen Code:

bash

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

Resume Previous Sessions (Headless)

Reuse conversation context from the current project in headless scripts:

bash

# Continue the most recent session for this project and run a new prompt
qwen --continue -p "Run the tests again and summarize failures"

# Resume a specific session ID directly (no UI)
qwen --resume 123e4567-e89b-12d3-a456-426614174000 -p "Apply the follow-up refactor"

[!note]

Session data is project-scoped JSONL under ~/.qwen/projects/<sanitized-cwd>/chats.

Restores conversation history, tool outputs, and chat-compression checkpoints before sending the new prompt.

Customize the Main Session Prompt

You can change the main session system prompt for a single CLI run without editing shared memory files.

Override the Built-in System Prompt

Use --system-prompt to replace Qwen Code's built-in main-session prompt for the current run:

bash

qwen -p "Review this patch" --system-prompt "You are a terse release reviewer. Report only blocking issues."

Append Extra Instructions

Use --append-system-prompt to keep the built-in prompt and add extra instructions for this run:

bash

qwen -p "Review this patch" --append-system-prompt "Be terse and focus on concrete findings."

You can combine both flags when you want a custom base prompt plus an extra run-specific instruction:

bash

qwen -p "Summarize this repository" \
  --system-prompt "You are a migration planner." \
  --append-system-prompt "Return exactly three bullets."

[!note]

--system-prompt applies only to the current run's main session.

Loaded memory and context files such as QWEN.md are still appended after --system-prompt.

--append-system-prompt is applied after the built-in prompt and loaded memory, and can be used together with --system-prompt.

Output Formats

Qwen Code supports multiple output formats for different use cases:

Text Output (Default)

Standard human-readable output:

bash

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

bash

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

Output (at end of execution):

json

[
  {
    "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.

bash

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

Output (streaming as events occur):

json

{"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.

bash

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:

bash

# 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`
`--system-prompt`	Override the main session system prompt for this run	`qwen -p "query" --system-prompt "You are a terse reviewer."`
`--append-system-prompt`	Append extra instructions to the main session system prompt for this run	`qwen -p "query" --append-system-prompt "Focus on concrete findings."`
`--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`
`--continue`	Resume the most recent session for this project	`qwen --continue -p "Pick up where we left off"`
`--resume [sessionId]`	Resume a specific session (or choose interactively)	`qwen --resume 123e... -p "Finish the refactor"`

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

Examples

Code review

bash

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

Generate commit messages

bash

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

API documentation

bash

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

bash

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

bash

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

bash

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

bash

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

bash

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

Persistent Retry Mode

When Qwen Code runs in CI/CD pipelines or as a background daemon, a brief API outage (rate limiting or overload) should not kill a multi-hour task. Persistent retry mode makes Qwen Code retry transient API errors indefinitely until the service recovers.

How it works

Transient errors only: HTTP 429 (Rate Limit) and 529 (Overloaded) are retried indefinitely. Other errors (400, 500, etc.) still fail normally.
Exponential backoff with cap: Retry delays grow exponentially but are capped at 5 minutes per retry.
Heartbeat keepalive: During long waits, a status line is printed to stderr every 30 seconds to prevent CI runners from killing the process due to inactivity.
Graceful degradation: Non-transient errors and interactive mode are completely unaffected.

Activation

Set the QWEN_CODE_UNATTENDED_RETRY environment variable to true or 1 (strict match, case-sensitive):

bash

export QWEN_CODE_UNATTENDED_RETRY=1

[!important] Persistent retry requires an explicit opt-in. CI=true alone does not activate it — silently turning a fast-fail CI job into an infinite-wait job would be dangerous. Always set QWEN_CODE_UNATTENDED_RETRY explicitly in your pipeline configuration.

Examples

GitHub Actions

yaml

- name: Automated code review
  env:
    QWEN_CODE_UNATTENDED_RETRY: '1'
  run: |
    qwen -p "Review all files in src/ for security issues" \
      --output-format json \
      --yolo > review.json

Overnight batch processing

bash

export QWEN_CODE_UNATTENDED_RETRY=1
qwen -p "Migrate all callback-style functions to async/await in src/" --yolo

Background daemon

bash

QWEN_CODE_UNATTENDED_RETRY=1 nohup qwen -p "Audit all dependencies for known CVEs" \
  --output-format json > audit.json 2> audit.log &

Monitoring

During persistent retry, heartbeat messages are printed to stderr:

[qwen-code] Waiting for API capacity... attempt 3, retry in 45s
[qwen-code] Waiting for API capacity... attempt 3, retry in 15s

These messages keep CI runners alive and let you monitor progress. They do not appear in stdout, so JSON output piped to other tools remains clean.

Resources

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