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#!/usr/bin/env python3
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"""
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Inference.sh Tool Module
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A simple tool for running AI apps via the inference.sh CLI (infsh).
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Provides two functions:
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- infsh_install: Install the infsh CLI
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- infsh: Run any infsh command
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This is a lightweight wrapper that gives agents direct access to 150+ AI apps
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including image generation (FLUX, Reve), video (Veo, Wan), LLMs, search, and more.
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Usage:
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from tools.infsh_tool import infsh_tool, infsh_install
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# Install the CLI
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result = infsh_install()
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# Search for apps first (always do this!)
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result = infsh_tool("app list --search flux")
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# Run an app
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result = infsh_tool("app run falai/flux-dev-lora --input '{\"prompt\": \"a cat\"}' --json")
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"""
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import json
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import logging
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import os
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import shutil
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import subprocess
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from typing import Optional
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logger = logging.getLogger(__name__)
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# ---------------------------------------------------------------------------
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# Configuration
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# ---------------------------------------------------------------------------
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DEFAULT_TIMEOUT = 300 # 5 minutes for long-running AI tasks
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INSTALL_TIMEOUT = 60
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# ---------------------------------------------------------------------------
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# Availability check
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# ---------------------------------------------------------------------------
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def check_infsh_requirements() -> bool:
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"""Check if infsh is available in PATH."""
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return shutil.which("infsh") is not None
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def _get_infsh_path() -> Optional[str]:
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"""Get the path to infsh binary."""
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return shutil.which("infsh")
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# ---------------------------------------------------------------------------
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# Install function
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# ---------------------------------------------------------------------------
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def infsh_install() -> str:
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"""
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Install the inference.sh CLI.
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Downloads and installs the infsh binary using the official installer script.
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The installer detects OS/arch, downloads the correct binary, verifies checksum,
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and places it in PATH.
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Returns:
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JSON string with success/error status
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"""
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try:
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# Check if already installed
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if check_infsh_requirements():
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infsh_path = _get_infsh_path()
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# Get version
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version_result = subprocess.run(
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["infsh", "--version"],
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capture_output=True,
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text=True,
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timeout=10
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)
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version = version_result.stdout.strip() if version_result.returncode == 0 else "unknown"
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return json.dumps({
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"success": True,
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"message": f"infsh is already installed at {infsh_path}",
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"version": version,
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"already_installed": True
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})
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# Run the installer
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result = subprocess.run(
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["sh", "-c", "curl -fsSL https://cli.inference.sh | sh"],
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capture_output=True,
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text=True,
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timeout=INSTALL_TIMEOUT,
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env={**os.environ, "NONINTERACTIVE": "1"}
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)
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if result.returncode != 0:
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return json.dumps({
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"success": False,
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"error": f"Installation failed: {result.stderr}",
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"stdout": result.stdout
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})
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# Verify installation
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if not check_infsh_requirements():
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return json.dumps({
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"success": False,
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"error": "Installation completed but infsh not found in PATH. You may need to restart your shell or add ~/.local/bin to PATH.",
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"stdout": result.stdout
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})
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return json.dumps({
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"success": True,
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"message": "infsh installed successfully",
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"stdout": result.stdout,
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"next_step": "Run 'infsh login' to authenticate, or set INFSH_API_KEY environment variable"
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})
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except subprocess.TimeoutExpired:
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return json.dumps({
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"success": False,
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"error": f"Installation timed out after {INSTALL_TIMEOUT}s"
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})
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except Exception as e:
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logger.exception("infsh_install error: %s", e)
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return json.dumps({
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"success": False,
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"error": f"Installation error: {type(e).__name__}: {e}"
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})
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# ---------------------------------------------------------------------------
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# Main tool function
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# ---------------------------------------------------------------------------
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def infsh_tool(
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command: str,
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timeout: Optional[int] = None,
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) -> str:
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"""
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Execute an infsh CLI command.
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Args:
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command: The infsh command to run (without the 'infsh' prefix).
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Examples: "app list", "app run falai/flux-schnell --input '{}'"
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timeout: Command timeout in seconds (default: 300)
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Returns:
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JSON string with output, exit_code, and error fields
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"""
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try:
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effective_timeout = timeout or DEFAULT_TIMEOUT
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# Check if infsh is installed
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if not check_infsh_requirements():
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return json.dumps({
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"success": False,
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"error": "infsh CLI is not installed. Use infsh_install to install it first.",
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"hint": "Call the infsh_install tool to set up the CLI"
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})
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# Build the full command
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full_command = f"infsh {command}"
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# Execute
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result = subprocess.run(
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full_command,
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shell=True,
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capture_output=True,
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text=True,
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timeout=effective_timeout,
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env=os.environ
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)
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output = result.stdout
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error = result.stderr
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# Try to parse JSON output if present
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parsed_output = None
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if output.strip():
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try:
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parsed_output = json.loads(output)
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except json.JSONDecodeError:
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pass # Not JSON, keep as string
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response = {
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"success": result.returncode == 0,
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"exit_code": result.returncode,
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"output": parsed_output if parsed_output is not None else output,
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}
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if error:
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response["stderr"] = error
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return json.dumps(response, indent=2)
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except subprocess.TimeoutExpired:
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return json.dumps({
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"success": False,
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"error": f"Command timed out after {effective_timeout}s",
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"hint": "For long-running tasks, consider using --no-wait flag"
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})
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except Exception as e:
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logger.exception("infsh_tool error: %s", e)
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return json.dumps({
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"success": False,
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"error": f"Execution error: {type(e).__name__}: {e}"
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})
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# ---------------------------------------------------------------------------
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# Registry
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# ---------------------------------------------------------------------------
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from tools.registry import registry
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INFSH_TOOL_DESCRIPTION = """Run AI apps via inference.sh CLI. Access 150+ apps for image generation, video, LLMs, search, 3D, and more.
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One API key for everything - manage all AI services (FLUX, Veo, Claude, Tavily, etc.) with a single inference.sh account. You can also bring your own API keys.
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IMPORTANT: Always use 'app list --search <query>' first to find the exact app ID before running. App names change frequently.
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Commands:
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- app list --search <query>: Find apps (ALWAYS DO THIS FIRST)
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- app run <app-id> --input '<json>' --json: Run an app
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- app get <app-id>: Get app schema before running
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Verified app examples (use --search to confirm current names):
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- Image: google/nano-banana, google/nano-banana-pro, google/nano-banana-2, falai/flux-dev-lora, bytedance/seedream-5-lite, falai/reve, xai/grok-imagine-image
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- Video: google/veo-3-1-fast, bytedance/seedance-1-5-pro, falai/wan-2-5
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- Upscale: falai/topaz-image-upscaler
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- Search: tavily/search-assistant, exa/search
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- LLM: openrouter/claude-sonnet-45
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Workflow: ALWAYS search first, then run:
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1. app list --search image
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2. app run falai/flux-dev-lora --input '{"prompt": "a sunset"}' --json"""
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INFSH_SCHEMA = {
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"name": "infsh",
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"description": INFSH_TOOL_DESCRIPTION,
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"parameters": {
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"type": "object",
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"properties": {
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"command": {
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"type": "string",
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"description": "The infsh command (without 'infsh' prefix). ALWAYS use 'app list --search <query>' first to find correct app IDs, then 'app run <id> --input <json> --json'"
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},
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"timeout": {
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"type": "integer",
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"description": "Max seconds to wait (default: 300). AI tasks like video generation may take 1-2 minutes.",
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"minimum": 1
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}
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},
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"required": ["command"]
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}
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}
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INFSH_INSTALL_SCHEMA = {
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"name": "infsh_install",
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"description": "Install the inference.sh CLI (infsh). Downloads and installs the binary. Run this first if infsh is not available.",
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"parameters": {
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"type": "object",
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"properties": {},
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"required": []
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}
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}
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def _handle_infsh(args, **kw):
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return infsh_tool(
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command=args.get("command", ""),
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timeout=args.get("timeout"),
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)
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def _handle_infsh_install(args, **kw):
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return infsh_install()
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# Register both tools under the "inference" toolset
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registry.register(
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name="infsh",
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toolset="inference",
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schema=INFSH_SCHEMA,
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handler=_handle_infsh,
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check_fn=check_infsh_requirements,
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requires_env=[],
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)
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registry.register(
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name="infsh_install",
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toolset="inference",
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schema=INFSH_INSTALL_SCHEMA,
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handler=_handle_infsh_install,
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check_fn=lambda: True, # Always available - it's the installer
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requires_env=[],
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)
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