Indusagi
SDK & APIrpc

RPC Mode

RPC mode enables headless operation of the coding agent via a JSON protocol over stdin/stdout. This is useful for embedding the agent in other applications, IDEs, or custom UIs.

Note for Node.js/TypeScript users: If you're building a Node.js application, consider using AgentSession directly from indusagi-coding-agent instead of spawning a subprocess. See src/core/agent-session.ts for the API. For a subprocess-based TypeScript client, see src/modes/rpc/rpc-client.ts.

Starting RPC Mode

indusagi --mode rpc [options]

Common options:

  • --provider <name>: Set the LLM provider (anthropic, openai, google, etc.)
  • --model <id>: Set the model ID
  • --no-session: Disable session persistence
  • --session-dir <path>: Custom session storage directory

Protocol Overview

  • Commands: JSON objects sent to stdin, one per line
  • Responses: JSON objects with type: "response" indicating command success/failure
  • Events: Agent events streamed to stdout as JSON lines

All commands support an optional id field for request/response correlation. If provided, the corresponding response will include the same id.

Commands

Prompting

prompt

Send a user prompt to the agent. Returns immediately; events stream asynchronously.

{"id": "req-1", "type": "prompt", "message": "Hello, world!"}

With images:

{"type": "prompt", "message": "What's in this image?", "images": [{"type": "image", "source": {"type": "base64", "mediaType": "image/png", "data": "..."}}]}

During streaming: If the agent is already streaming, you must specify streamingBehavior to queue the message:

{"type": "prompt", "message": "New instruction", "streamingBehavior": "steer"}
  • "steer": Interrupt the agent mid-run. Message is delivered after current tool execution, remaining tools are skipped.
  • "followUp": Wait until the agent finishes. Message is delivered only when agent stops.

If the agent is streaming and no streamingBehavior is specified, the command returns an error.

Extension commands: If the message is an extension command (e.g., /mycommand), it executes immediately even during streaming. Extension commands manage their own LLM interaction via indusagi.sendMessage().

Input expansion: Skill commands (/skill:name) and prompt templates (/template) are expanded before sending/queueing.

Response:

{"id": "req-1", "type": "response", "command": "prompt", "success": true}

The images field is optional. Each image uses ImageContent format with base64 or URL source.

steer

Queue a steering message to interrupt the agent mid-run. Delivered after current tool execution, remaining tools are skipped. Skill commands and prompt templates are expanded. Extension commands are not allowed (use prompt instead).

{"type": "steer", "message": "Stop and do this instead"}

Response:

{"type": "response", "command": "steer", "success": true}

See set_steering_mode for controlling how steering messages are processed.

follow_up

Queue a follow-up message to be processed after the agent finishes. Delivered only when agent has no more tool calls or steering messages. Skill commands and prompt templates are expanded. Extension commands are not allowed (use prompt instead).

{"type": "follow_up", "message": "After you're done, also do this"}

Response:

{"type": "response", "command": "follow_up", "success": true}

See set_follow_up_mode for controlling how follow-up messages are processed.

abort

Abort the current agent operation.

{"type": "abort"}

Response:

{"type": "response", "command": "abort", "success": true}

new_session

Start a fresh session. Can be cancelled by a session_before_switch extension event handler.

{"type": "new_session"}

With optional parent session tracking:

{"type": "new_session", "parentSession": "/path/to/parent-session.jsonl"}

Response:

{"type": "response", "command": "new_session", "success": true, "data": {"cancelled": false}}

If an extension cancelled:

{"type": "response", "command": "new_session", "success": true, "data": {"cancelled": true}}

State

get_state

Get current session state.

{"type": "get_state"}

Response:

{
  "type": "response",
  "command": "get_state",
  "success": true,
  "data": {
    "model": {...},
    "thinkingLevel": "medium",
    "isStreaming": false,
    "isCompacting": false,
    "steeringMode": "all",
    "followUpMode": "one-at-a-time",
    "sessionFile": "/path/to/session.jsonl",
    "sessionId": "abc123",
    "autoCompactionEnabled": true,
    "messageCount": 5,
    "pendingMessageCount": 0
  }
}

The model field is a full Model object or null.

get_messages

Get all messages in the conversation.

{"type": "get_messages"}

Response:

{
  "type": "response",
  "command": "get_messages",
  "success": true,
  "data": {"messages": [...]}
}

Messages are AgentMessage objects (see Message Types).

Model

set_model

Switch to a specific model.

{"type": "set_model", "provider": "anthropic", "modelId": "claude-sonnet-4-20250514"}

Response contains the full Model object:

{
  "type": "response",
  "command": "set_model",
  "success": true,
  "data": {...}
}

cycle_model

Cycle to the next available model. Returns null data if only one model available.

{"type": "cycle_model"}

Response:

{
  "type": "response",
  "command": "cycle_model",
  "success": true,
  "data": {
    "model": {...},
    "thinkingLevel": "medium",
    "isScoped": false
  }
}

The model field is a full Model object.

get_available_models

List all configured models.

{"type": "get_available_models"}

Response contains an array of full Model objects:

{
  "type": "response",
  "command": "get_available_models",
  "success": true,
  "data": {
    "models": [...]
  }
}

Thinking

set_thinking_level

Set the reasoning/thinking level for models that support it.

{"type": "set_thinking_level", "level": "high"}

Levels: "off", "minimal", "low", "medium", "high", "xhigh"

Note: "xhigh" is only supported by OpenAI codex-max models.

Response:

{"type": "response", "command": "set_thinking_level", "success": true}

cycle_thinking_level

Cycle through available thinking levels. Returns null data if model doesn't support thinking.

{"type": "cycle_thinking_level"}

Response:

{
  "type": "response",
  "command": "cycle_thinking_level",
  "success": true,
  "data": {"level": "high"}
}

Queue Modes

set_steering_mode

Control how steering messages (from steer) are delivered.

{"type": "set_steering_mode", "mode": "one-at-a-time"}

Modes:

  • "all": Deliver all steering messages at the next interruption point
  • "one-at-a-time": Deliver one steering message per interruption (default)

Response:

{"type": "response", "command": "set_steering_mode", "success": true}

set_follow_up_mode

Control how follow-up messages (from follow_up) are delivered.

{"type": "set_follow_up_mode", "mode": "one-at-a-time"}

Modes:

  • "all": Deliver all follow-up messages when agent finishes
  • "one-at-a-time": Deliver one follow-up message per agent completion (default)

Response:

{"type": "response", "command": "set_follow_up_mode", "success": true}

Compaction

compact

Manually compact conversation context to reduce token usage.

{"type": "compact"}

With custom instructions:

{"type": "compact", "customInstructions": "Focus on code changes"}

Response:

{
  "type": "response",
  "command": "compact",
  "success": true,
  "data": {
    "summary": "Summary of conversation...",
    "firstKeptEntryId": "abc123",
    "tokensBefore": 150000,
    "details": {}
  }
}

set_auto_compaction

Enable or disable automatic compaction when context is nearly full.

{"type": "set_auto_compaction", "enabled": true}

Response:

{"type": "response", "command": "set_auto_compaction", "success": true}

Retry

set_auto_retry

Enable or disable automatic retry on transient errors (overloaded, rate limit, 5xx).

{"type": "set_auto_retry", "enabled": true}

Response:

{"type": "response", "command": "set_auto_retry", "success": true}

abort_retry

Abort an in-progress retry (cancel the delay and stop retrying).

{"type": "abort_retry"}

Response:

{"type": "response", "command": "abort_retry", "success": true}

Bash

bash

Execute a shell command and add output to conversation context.

{"type": "bash", "command": "ls -la"}

Response:

{
  "type": "response",
  "command": "bash",
  "success": true,
  "data": {
    "output": "total 48\ndrwxr-xr-x ...",
    "exitCode": 0,
    "cancelled": false,
    "truncated": false
  }
}

If output was truncated, includes fullOutputPath:

{
  "type": "response",
  "command": "bash",
  "success": true,
  "data": {
    "output": "truncated output...",
    "exitCode": 0,
    "cancelled": false,
    "truncated": true,
    "fullOutputPath": "/tmp/indusagi-bash-abc123.log"
  }
}

How bash results reach the LLM:

The bash command executes immediately and returns a BashResult. Internally, a BashExecutionMessage is created and stored in the agent's message state. This message does NOT emit an event.

When the next prompt command is sent, all messages (including BashExecutionMessage) are transformed before being sent to the LLM. The BashExecutionMessage is converted to a UserMessage with this format:

Ran `ls -la`
\`\`\`
total 48
drwxr-xr-x ...
\`\`\`

This means:

  1. Bash output is included in the LLM context on the next prompt, not immediately
  2. Multiple bash commands can be executed before a prompt; all outputs will be included
  3. No event is emitted for the BashExecutionMessage itself

abort_bash

Abort a running bash command.

{"type": "abort_bash"}

Response:

{"type": "response", "command": "abort_bash", "success": true}

Session

get_session_stats

Get token usage and cost statistics.

{"type": "get_session_stats"}

Response:

{
  "type": "response",
  "command": "get_session_stats",
  "success": true,
  "data": {
    "sessionFile": "/path/to/session.jsonl",
    "sessionId": "abc123",
    "userMessages": 5,
    "assistantMessages": 5,
    "toolCalls": 12,
    "toolResults": 12,
    "totalMessages": 22,
    "tokens": {
      "input": 50000,
      "output": 10000,
      "cacheRead": 40000,
      "cacheWrite": 5000,
      "total": 105000
    },
    "cost": 0.45
  }
}

export_html

Export session to an HTML file.

{"type": "export_html"}

With custom path:

{"type": "export_html", "outputPath": "/tmp/session.html"}

Response:

{
  "type": "response",
  "command": "export_html",
  "success": true,
  "data": {"path": "/tmp/session.html"}
}

switch_session

Load a different session file. Can be cancelled by a session_before_switch extension event handler.

{"type": "switch_session", "sessionPath": "/path/to/session.jsonl"}

Response:

{"type": "response", "command": "switch_session", "success": true, "data": {"cancelled": false}}

If an extension cancelled the switch:

{"type": "response", "command": "switch_session", "success": true, "data": {"cancelled": true}}

fork

Create a new fork from a previous user message. Can be cancelled by a session_before_fork extension event handler. Returns the text of the message being forked from.

{"type": "fork", "entryId": "abc123"}

Response:

{
  "type": "response",
  "command": "fork",
  "success": true,
  "data": {"text": "The original prompt text...", "cancelled": false}
}

If an extension cancelled the fork:

{
  "type": "response",
  "command": "fork",
  "success": true,
  "data": {"text": "The original prompt text...", "cancelled": true}
}

get_fork_messages

Get user messages available for forking.

{"type": "get_fork_messages"}

Response:

{
  "type": "response",
  "command": "get_fork_messages",
  "success": true,
  "data": {
    "messages": [
      {"entryId": "abc123", "text": "First prompt..."},
      {"entryId": "def456", "text": "Second prompt..."}
    ]
  }
}

get_last_assistant_text

Get the text content of the last assistant message.

{"type": "get_last_assistant_text"}

Response:

{
  "type": "response",
  "command": "get_last_assistant_text",
  "success": true,
  "data": {"text": "The assistant's response..."}
}

Returns {"text": null} if no assistant messages exist.

Events

Events are streamed to stdout as JSON lines during agent operation. Events do NOT include an id field (only responses do).

Event Types

Event Description
agent_start Agent begins processing
agent_end Agent completes (includes all generated messages)
turn_start New turn begins
turn_end Turn completes (includes assistant message and tool results)
message_start Message begins
message_update Streaming update (text/thinking/toolcall deltas)
message_end Message completes
tool_execution_start Tool begins execution
tool_execution_update Tool execution progress (streaming output)
tool_execution_end Tool completes
auto_compaction_start Auto-compaction begins
auto_compaction_end Auto-compaction completes
auto_retry_start Auto-retry begins (after transient error)
auto_retry_end Auto-retry completes (success or final failure)
extension_error Extension threw an error

agent_start

Emitted when the agent begins processing a prompt.

{"type": "agent_start"}

agent_end

Emitted when the agent completes. Contains all messages generated during this run.

{
  "type": "agent_end",
  "messages": [...]
}

turn_start / turn_end

A turn consists of one assistant response plus any resulting tool calls and results.

{"type": "turn_start"}

{
  "type": "turn_end",
  "message": {...},
  "toolResults": [...]
}

message_start / message_end

Emitted when a message begins and completes. The message field contains an AgentMessage.

{"type": "message_start", "message": {...}}
{"type": "message_end", "message": {...}}

message_update (Streaming)

Emitted during streaming of assistant messages. Contains both the partial message and a streaming delta event.

{
  "type": "message_update",
  "message": {...},
  "assistantMessageEvent": {
    "type": "text_delta",
    "contentIndex": 0,
    "delta": "Hello ",
    "partial": {...}
  }
}

The assistantMessageEvent field contains one of these delta types:

Type Description
start Message generation started
text_start Text content block started
text_delta Text content chunk
text_end Text content block ended
thinking_start Thinking block started
thinking_delta Thinking content chunk
thinking_end Thinking block ended
toolcall_start Tool call started
toolcall_delta Tool call arguments chunk
toolcall_end Tool call ended (includes full toolCall object)
done Message complete (reason: "stop", "length", "toolUse")
error Error occurred (reason: "aborted", "error")

Example streaming a text response:

{"type":"message_update","message":{...},"assistantMessageEvent":{"type":"text_start","contentIndex":0,"partial":{...}}}
{"type":"message_update","message":{...},"assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"Hello","partial":{...}}}
{"type":"message_update","message":{...},"assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" world","partial":{...}}}
{"type":"message_update","message":{...},"assistantMessageEvent":{"type":"text_end","contentIndex":0,"content":"Hello world","partial":{...}}}

tool_execution_start / tool_execution_update / tool_execution_end

Emitted when a tool begins, streams progress, and completes execution.

{
  "type": "tool_execution_start",
  "toolCallId": "call_abc123",
  "toolName": "bash",
  "args": {"command": "ls -la"}
}

During execution, tool_execution_update events stream partial results (e.g., bash output as it arrives):

{
  "type": "tool_execution_update",
  "toolCallId": "call_abc123",
  "toolName": "bash",
  "args": {"command": "ls -la"},
  "partialResult": {
    "content": [{"type": "text", "text": "partial output so far..."}],
    "details": {"truncation": null, "fullOutputPath": null}
  }
}

When complete:

{
  "type": "tool_execution_end",
  "toolCallId": "call_abc123",
  "toolName": "bash",
  "result": {
    "content": [{"type": "text", "text": "total 48\n..."}],
    "details": {...}
  },
  "isError": false
}

Use toolCallId to correlate events. The partialResult in tool_execution_update contains the accumulated output so far (not just the delta), allowing clients to simply replace their display on each update.

auto_compaction_start / auto_compaction_end

Emitted when automatic compaction runs (when context is nearly full).

{"type": "auto_compaction_start", "reason": "threshold"}

The reason field is "threshold" (context getting large) or "overflow" (context exceeded limit).

{
  "type": "auto_compaction_end",
  "result": {
    "summary": "Summary of conversation...",
    "firstKeptEntryId": "abc123",
    "tokensBefore": 150000,
    "details": {}
  },
  "aborted": false,
  "willRetry": false
}

If reason was "overflow" and compaction succeeds, willRetry is true and the agent will automatically retry the prompt.

If compaction was aborted, result is null and aborted is true.

If compaction failed (e.g., API quota exceeded), result is null, aborted is false, and errorMessage contains the error description.

auto_retry_start / auto_retry_end

Emitted when automatic retry is triggered after a transient error (overloaded, rate limit, 5xx).

{
  "type": "auto_retry_start",
  "attempt": 1,
  "maxAttempts": 3,
  "delayMs": 2000,
  "errorMessage": "529 {\"type\":\"error\",\"error\":{\"type\":\"overloaded_error\",\"message\":\"Overloaded\"}}"
}

{
  "type": "auto_retry_end",
  "success": true,
  "attempt": 2
}

On final failure (max retries exceeded):

{
  "type": "auto_retry_end",
  "success": false,
  "attempt": 3,
  "finalError": "529 overloaded_error: Overloaded"
}

extension_error

Emitted when an extension throws an error.

{
  "type": "extension_error",
  "extensionPath": "/path/to/extension.ts",
  "event": "tool_call",
  "error": "Error message..."
}

Error Handling

Failed commands return a response with success: false:

{
  "type": "response",
  "command": "set_model",
  "success": false,
  "error": "Model not found: invalid/model"
}

Parse errors:

{
  "type": "response",
  "command": "parse",
  "success": false,
  "error": "Failed to parse command: Unexpected token..."
}

Types

Source files:

Model

{
  "id": "claude-sonnet-4-20250514",
  "name": "Claude Sonnet 4",
  "api": "anthropic-messages",
  "provider": "anthropic",
  "baseUrl": "https://api.anthropic.com",
  "reasoning": true,
  "input": ["text", "image"],
  "contextWindow": 200000,
  "maxTokens": 16384,
  "cost": {
    "input": 3.0,
    "output": 15.0,
    "cacheRead": 0.3,
    "cacheWrite": 3.75
  }
}

UserMessage

{
  "role": "user",
  "content": "Hello!",
  "timestamp": 1733234567890,
  "attachments": []
}

The content field can be a string or an array of TextContent/ImageContent blocks.

AssistantMessage

{
  "role": "assistant",
  "content": [
    {"type": "text", "text": "Hello! How can I help?"},
    {"type": "thinking", "thinking": "User is greeting me..."},
    {"type": "toolCall", "id": "call_123", "name": "bash", "arguments": {"command": "ls"}}
  ],
  "api": "anthropic-messages",
  "provider": "anthropic",
  "model": "claude-sonnet-4-20250514",
  "usage": {
    "input": 100,
    "output": 50,
    "cacheRead": 0,
    "cacheWrite": 0,
    "cost": {"input": 0.0003, "output": 0.00075, "cacheRead": 0, "cacheWrite": 0, "total": 0.00105}
  },
  "stopReason": "stop",
  "timestamp": 1733234567890
}

Stop reasons: "stop", "length", "toolUse", "error", "aborted"

ToolResultMessage

{
  "role": "toolResult",
  "toolCallId": "call_123",
  "toolName": "bash",
  "content": [{"type": "text", "text": "total 48\ndrwxr-xr-x ..."}],
  "isError": false,
  "timestamp": 1733234567890
}

BashExecutionMessage

Created by the bash RPC command (not by LLM tool calls):

{
  "role": "bashExecution",
  "command": "ls -la",
  "output": "total 48\ndrwxr-xr-x ...",
  "exitCode": 0,
  "cancelled": false,
  "truncated": false,
  "fullOutputPath": null,
  "timestamp": 1733234567890
}

Attachment

{
  "id": "img1",
  "type": "image",
  "fileName": "photo.jpg",
  "mimeType": "image/jpeg",
  "size": 102400,
  "content": "base64-encoded-data...",
  "extractedText": null,
  "preview": null
}

Example: Basic Client (Python)

import subprocess
import json

proc = subprocess.Popen(
    ["indusagi", "--mode", "rpc", "--no-session"],
    stdin=subprocess.PIPE,
    stdout=subprocess.PIPE,
    text=True
)

def send(cmd):
    proc.stdin.write(json.dumps(cmd) + "\n")
    proc.stdin.flush()

def read_events():
    for line in proc.stdout:
        yield json.loads(line)

# Send prompt
send({"type": "prompt", "message": "Hello!"})

# Process events
for event in read_events():
    if event.get("type") == "message_update":
        delta = event.get("assistantMessageEvent", {})
        if delta.get("type") == "text_delta":
            print(delta["delta"], end="", flush=True)
    
    if event.get("type") == "agent_end":
        print()
        break

Example: Interactive Client (Node.js)

See test/rpc-example.ts for a complete interactive example, or src/modes/rpc/rpc-client.ts for a typed client implementation.

const { spawn } = require("child_process");
const readline = require("readline");

const agent = spawn("indusagi", ["--mode", "rpc", "--no-session"]);

readline.createInterface({ input: agent.stdout }).on("line", (line) => {
    const event = JSON.parse(line);
    
    if (event.type === "message_update") {
        const { assistantMessageEvent } = event;
        if (assistantMessageEvent.type === "text_delta") {
            process.stdout.write(assistantMessageEvent.delta);
        }
    }
});

// Send prompt
agent.stdin.write(JSON.stringify({ type: "prompt", message: "Hello" }) + "\n");

// Abort on Ctrl+C
process.on("SIGINT", () => {
    agent.stdin.write(JSON.stringify({ type: "abort" }) + "\n");
});
On This Page
Starting RPC ModeProtocol OverviewCommandsPromptingStateModelThinkingQueue ModesCompactionRetryBashSessionEventsEvent Typesagent_startagent_endturn_start / turn_endmessage_start / message_endmessage_update (Streaming)tool_execution_start / tool_execution_update / tool_execution_endauto_compaction_start / auto_compaction_endauto_retry_start / auto_retry_endextension_errorError HandlingTypesModelUserMessageAssistantMessageToolResultMessageBashExecutionMessageAttachmentExample: Basic Client (Python)Example: Interactive Client (Node.js)