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Headless Mode

Headless mode allows you to run Perplexity CLI 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 Perplexity CLI 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:

perplexity --prompt "What is machine learning?"

Stdin Input

Pipe input to Perplexity CLI from your terminal:

echo "Explain this code" | perplexity

Combining with File Input

Read from files and process with Perplexity CLI:

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

Resume Previous Sessions (Headless)

Reuse conversation context from the current project in headless scripts:

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

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

Notes:

  • Session data is project-scoped JSONL under ~/.perplexity/projects/<sanitized-cwd>/chats.
  • Restores conversation history, tool outputs, and chat-compression checkpoints before sending the new prompt.

Output Formats

Perplexity CLI supports multiple output formats for different use cases:

Text Output (Default)

Standard human-readable output:

perplexity -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

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

Output (at end of execution):

[
  {
    "type": "system",
    "subtype": "session_start",
    "uuid": "...",
    "session_id": "...",
    "model": "perplexity3-coder-plus",
    ...
  },
  {
    "type": "assistant",
    "uuid": "...",
    "session_id": "...",
    "message": {
      "id": "...",
      "type": "message",
      "role": "assistant",
      "model": "perplexity3-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.

perplexity -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.

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

Input Format

The --input-format parameter controls how Perplexity CLI 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
perplexity -p "Explain Docker" > docker-explanation.txt
perplexity -p "Explain Docker" --output-format json > docker-explanation.json

# Append to file
perplexity -p "Add more details" >> docker-explanation.txt

# Pipe to other tools
perplexity -p "What is Kubernetes?" --output-format json | jq '.response'
perplexity -p "Explain microservices" | wc -w
perplexity -p "List programming languages" | grep -i "python"

# Stream-JSON output for real-time processing
perplexity -p "Explain Docker" --output-format stream-json | jq '.type'
perplexity -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 perplexity -p "query"
--output-format, -o Specify output format (text, json, stream-json) perplexity -p "query" --output-format json
--input-format Specify input format (text, stream-json) perplexity --input-format text --output-format stream-json
--include-partial-messages Include partial messages in stream-json output perplexity -p "query" --output-format stream-json --include-partial-messages
--debug, -d Enable debug mode perplexity -p "query" --debug
--all-files, -a Include all files in context perplexity -p "query" --all-files
--include-directories Include additional directories perplexity -p "query" --include-directories src,docs
--yolo, -y Auto-approve all actions perplexity -p "query" --yolo
--approval-mode Set approval mode perplexity -p "query" --approval-mode auto_edit
--continue Resume the most recent session for this project perplexity --continue -p "Pick up where we left off"
--resume [sessionId] Resume a specific session (or choose interactively) perplexity --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

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

Generate commit messages

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

API documentation

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

Batch code analysis

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

PR code review

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

Log analysis

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

Release notes generation

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

Model and tool usage tracking

result=$(perplexity -p "Explain this database schema" --include-directories db --output-format json)
total_tokens=$(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