248acf715e
- Introduced new browser automation tools in `browser_tool.py` for navigating, interacting with, and extracting content from web pages using the agent-browser CLI and Browserbase cloud execution. - Updated `.env.example` to include new configuration options for Browserbase API keys and session settings. - Enhanced `model_tools.py` and `toolsets.py` to integrate browser tools into the existing tool framework, ensuring consistent access across toolsets. - Updated `README.md` with setup instructions for browser tools and their usage examples. - Added new test script `test_modal_terminal.py` to validate Modal terminal backend functionality. - Improved `run_agent.py` to support browser tool integration and logging enhancements for better tracking of API responses.
884 lines
35 KiB
Python
884 lines
35 KiB
Python
#!/usr/bin/env python3
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"""
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Model Tools Module
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This module constructs tool schemas and handlers for AI model API calls.
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It imports tools from various toolset modules and provides a unified interface
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for defining tools and executing function calls.
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Currently supports:
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- Web tools (search, extract, crawl) from web_tools.py
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- Terminal tools (simple command execution, no session persistence) from simple_terminal_tool.py
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- Vision tools (image analysis) from vision_tools.py
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- Mixture of Agents tools (collaborative multi-model reasoning) from mixture_of_agents_tool.py
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- Image generation tools (text-to-image with upscaling) from image_generation_tool.py
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Usage:
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from model_tools import get_tool_definitions, handle_function_call
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# Get all available tool definitions for model API
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tools = get_tool_definitions()
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# Get specific toolsets
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web_tools = get_tool_definitions(enabled_toolsets=['web_tools'])
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# Handle function calls from model
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result = handle_function_call("web_search", {"query": "Python"})
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"""
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import json
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import asyncio
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from typing import Dict, Any, List, Optional
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from tools.web_tools import web_search_tool, web_extract_tool, web_crawl_tool, check_firecrawl_api_key
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from tools.terminal_tool import terminal_tool, check_terminal_requirements, TERMINAL_TOOL_DESCRIPTION, cleanup_vm
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# Hecate/MorphCloud terminal tool (cloud VMs) - available as alternative backend
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from tools.terminal_hecate import terminal_hecate_tool, check_hecate_requirements, TERMINAL_HECATE_DESCRIPTION
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from tools.vision_tools import vision_analyze_tool, check_vision_requirements
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from tools.mixture_of_agents_tool import mixture_of_agents_tool, check_moa_requirements
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from tools.image_generation_tool import image_generate_tool, check_image_generation_requirements
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# Browser automation tools (agent-browser + Browserbase)
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from tools.browser_tool import (
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browser_navigate,
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browser_snapshot,
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browser_click,
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browser_type,
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browser_scroll,
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browser_back,
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browser_press,
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browser_close,
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browser_get_images,
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browser_vision,
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cleanup_browser,
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check_browser_requirements,
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BROWSER_TOOL_SCHEMAS
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)
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from toolsets import (
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get_toolset, resolve_toolset, resolve_multiple_toolsets,
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get_all_toolsets, get_toolset_names, validate_toolset,
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get_toolset_info, print_toolset_tree
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)
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def get_web_tool_definitions() -> List[Dict[str, Any]]:
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"""
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Get tool definitions for web tools in OpenAI's expected format.
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Returns:
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List[Dict]: List of web tool definitions compatible with OpenAI API
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"""
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return [
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{
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"type": "function",
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"function": {
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"name": "web_search",
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"description": "Search the web for information on any topic. Returns up to 5 relevant results with titles and URLs. Uses advanced search depth for comprehensive results. PREFERRED over browser tools for finding information - faster and more cost-effective. Use browser tools only when you need to interact with pages (click, fill forms, handle dynamic content).",
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"parameters": {
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"type": "object",
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"properties": {
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"query": {
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"type": "string",
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"description": "The search query to look up on the web"
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}
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},
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"required": ["query"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "web_extract",
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"description": "Extract and read the full content from specific web page URLs. Useful for getting detailed information from webpages found through search. The content returned will be excerpts and key points summarized with an LLM to reduce impact on the context window. PREFERRED over browser tools for reading page content - faster and more cost-effective. Use browser tools only when pages require interaction or have dynamic content.",
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"parameters": {
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"type": "object",
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"properties": {
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"urls": {
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"type": "array",
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"items": {"type": "string"},
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"description": "List of URLs to extract content from (max 5 URLs per call)",
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"maxItems": 5
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}
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},
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"required": ["urls"]
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}
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}
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},
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]
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def get_terminal_tool_definitions() -> List[Dict[str, Any]]:
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"""
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Get tool definitions for terminal tools in OpenAI's expected format.
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Uses mini-swe-agent backend (local/docker/modal) by default.
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Returns:
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List[Dict]: List of terminal tool definitions compatible with OpenAI API
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"""
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return [
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{
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"type": "function",
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"function": {
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"name": "terminal",
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"description": TERMINAL_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 command to execute on the VM"
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},
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"background": {
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"type": "boolean",
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"description": "Whether to run the command in the background (default: false)",
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"default": False
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},
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"timeout": {
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"type": "integer",
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"description": "Command timeout in seconds (optional)",
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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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}
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]
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def get_vision_tool_definitions() -> List[Dict[str, Any]]:
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"""
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Get tool definitions for vision tools in OpenAI's expected format.
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Returns:
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List[Dict]: List of vision tool definitions compatible with OpenAI API
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"""
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return [
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{
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"type": "function",
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"function": {
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"name": "vision_analyze",
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"description": "Analyze images from URLs using AI vision. Provides comprehensive image description and answers specific questions about the image content. Perfect for understanding visual content, reading text in images, identifying objects, analyzing scenes, and extracting visual information.",
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"parameters": {
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"type": "object",
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"properties": {
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"image_url": {
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"type": "string",
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"description": "The URL of the image to analyze (must be publicly accessible HTTP/HTTPS URL)"
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},
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"question": {
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"type": "string",
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"description": "Your specific question or request about the image to resolve. The AI will automatically provide a complete image description AND answer your specific question."
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}
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},
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"required": ["image_url", "question"]
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}
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}
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}
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]
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def get_moa_tool_definitions() -> List[Dict[str, Any]]:
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"""
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Get tool definitions for Mixture-of-Agents tools in OpenAI's expected format.
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Returns:
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List[Dict]: List of MoA tool definitions compatible with OpenAI API
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"""
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return [
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{
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"type": "function",
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"function": {
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"name": "mixture_of_agents",
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"description": "Process extremely difficult problems requiring intense reasoning using a Mixture-of-Agents. This tool leverages multiple frontier language models to collaboratively solve complex tasks that single models struggle with. Uses a fixed 2-layer architecture: reference models generate diverse responses, then an aggregator synthesizes the best solution. Best for: complex mathematical proofs, advanced coding problems, multi-step analytical reasoning, precise and complex STEM problems, algorithm design, and problems requiring diverse domain expertise.",
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"parameters": {
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"type": "object",
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"properties": {
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"user_prompt": {
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"type": "string",
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"description": "The complex query or problem to solve using multiple AI models. Should be a challenging problem that benefits from diverse perspectives and collaborative reasoning."
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}
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},
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"required": ["user_prompt"]
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}
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}
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}
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]
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def get_image_tool_definitions() -> List[Dict[str, Any]]:
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"""
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Get tool definitions for image generation tools in OpenAI's expected format.
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Returns:
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List[Dict]: List of image generation tool definitions compatible with OpenAI API
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"""
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return [
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{
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"type": "function",
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"function": {
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"name": "image_generate",
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"description": "Generate high-quality images from text prompts using FLUX 2 Pro model with automatic 2x upscaling. Creates detailed, artistic images that are automatically upscaled for hi-rez results. Returns a single upscaled image URL that can be displayed using <img src=\"{URL}\"></img> tags.",
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"parameters": {
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"type": "object",
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"properties": {
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"prompt": {
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"type": "string",
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"description": "The text prompt describing the desired image. Be detailed and descriptive."
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},
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"aspect_ratio": {
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"type": "string",
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"enum": ["landscape", "square", "portrait"],
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"description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.",
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"default": "landscape"
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}
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},
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"required": ["prompt"]
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}
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}
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}
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]
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def get_browser_tool_definitions() -> List[Dict[str, Any]]:
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"""
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Get tool definitions for browser automation tools in OpenAI's expected format.
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Uses agent-browser CLI with Browserbase cloud execution.
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Returns:
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List[Dict]: List of browser tool definitions compatible with OpenAI API
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"""
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return [{"type": "function", "function": schema} for schema in BROWSER_TOOL_SCHEMAS]
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def get_all_tool_names() -> List[str]:
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"""
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Get the names of all available tools across all toolsets.
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Returns:
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List[str]: List of all tool names
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"""
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tool_names = []
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# Web tools
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if check_firecrawl_api_key():
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tool_names.extend(["web_search", "web_extract"])
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# Terminal tools (mini-swe-agent backend)
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if check_terminal_requirements():
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tool_names.extend(["terminal"])
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# Vision tools
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if check_vision_requirements():
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tool_names.extend(["vision_analyze"])
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# MoA tools
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if check_moa_requirements():
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tool_names.extend(["mixture_of_agents"])
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# Image generation tools
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if check_image_generation_requirements():
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tool_names.extend(["image_generate"])
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# Browser automation tools
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if check_browser_requirements():
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tool_names.extend([
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"browser_navigate", "browser_snapshot", "browser_click",
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"browser_type", "browser_scroll", "browser_back",
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"browser_press", "browser_close", "browser_get_images",
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"browser_vision"
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])
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return tool_names
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def get_toolset_for_tool(tool_name: str) -> str:
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"""
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Get the toolset that a tool belongs to.
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Args:
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tool_name (str): Name of the tool
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Returns:
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str: Name of the toolset, or "unknown" if not found
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"""
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toolset_mapping = {
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"web_search": "web_tools",
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"web_extract": "web_tools",
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"terminal": "terminal_tools",
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"vision_analyze": "vision_tools",
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"mixture_of_agents": "moa_tools",
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"image_generate": "image_tools",
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# Browser automation tools
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"browser_navigate": "browser_tools",
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"browser_snapshot": "browser_tools",
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"browser_click": "browser_tools",
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"browser_type": "browser_tools",
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"browser_scroll": "browser_tools",
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"browser_back": "browser_tools",
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"browser_press": "browser_tools",
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"browser_close": "browser_tools",
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"browser_get_images": "browser_tools",
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"browser_vision": "browser_tools"
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}
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return toolset_mapping.get(tool_name, "unknown")
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def get_tool_definitions(
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enabled_toolsets: List[str] = None,
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disabled_toolsets: List[str] = None
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) -> List[Dict[str, Any]]:
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"""
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Get tool definitions for model API calls with toolset-based filtering.
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This function aggregates tool definitions from available toolsets.
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All tools must be part of a toolset to be accessible. Individual tool
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selection is not supported - use toolsets to organize and select tools.
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Args:
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enabled_toolsets (List[str]): Only include tools from these toolsets.
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If None, all available tools are included.
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disabled_toolsets (List[str]): Exclude tools from these toolsets.
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Applied only if enabled_toolsets is None.
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Returns:
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List[Dict]: Filtered list of tool definitions
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Examples:
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# Use predefined toolsets
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tools = get_tool_definitions(enabled_toolsets=["research"])
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tools = get_tool_definitions(enabled_toolsets=["development"])
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# Combine multiple toolsets
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tools = get_tool_definitions(enabled_toolsets=["web", "vision"])
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# All tools except those in terminal toolset
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tools = get_tool_definitions(disabled_toolsets=["terminal"])
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# Default - all available tools
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tools = get_tool_definitions()
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"""
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# Collect all available tool definitions
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all_available_tools_map = {}
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# Map tool names to their definitions
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if check_firecrawl_api_key():
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for tool in get_web_tool_definitions():
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all_available_tools_map[tool["function"]["name"]] = tool
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if check_terminal_requirements():
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for tool in get_terminal_tool_definitions():
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all_available_tools_map[tool["function"]["name"]] = tool
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if check_vision_requirements():
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for tool in get_vision_tool_definitions():
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all_available_tools_map[tool["function"]["name"]] = tool
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if check_moa_requirements():
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for tool in get_moa_tool_definitions():
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all_available_tools_map[tool["function"]["name"]] = tool
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if check_image_generation_requirements():
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for tool in get_image_tool_definitions():
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all_available_tools_map[tool["function"]["name"]] = tool
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if check_browser_requirements():
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for tool in get_browser_tool_definitions():
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all_available_tools_map[tool["function"]["name"]] = tool
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# Determine which tools to include based on toolsets
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tools_to_include = set()
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if enabled_toolsets:
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# Only include tools from enabled toolsets
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for toolset_name in enabled_toolsets:
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if validate_toolset(toolset_name):
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resolved_tools = resolve_toolset(toolset_name)
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tools_to_include.update(resolved_tools)
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print(f"✅ Enabled toolset '{toolset_name}': {', '.join(resolved_tools) if resolved_tools else 'no tools'}")
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else:
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# Try legacy compatibility
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if toolset_name in ["web_tools", "terminal_tools", "vision_tools", "moa_tools", "image_tools", "browser_tools"]:
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# Map legacy names to new system
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legacy_map = {
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"web_tools": ["web_search", "web_extract"],
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"terminal_tools": ["terminal"],
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"vision_tools": ["vision_analyze"],
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"moa_tools": ["mixture_of_agents"],
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"image_tools": ["image_generate"],
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"browser_tools": [
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"browser_navigate", "browser_snapshot", "browser_click",
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"browser_type", "browser_scroll", "browser_back",
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"browser_press", "browser_close", "browser_get_images",
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"browser_vision"
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]
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}
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legacy_tools = legacy_map.get(toolset_name, [])
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tools_to_include.update(legacy_tools)
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print(f"✅ Enabled legacy toolset '{toolset_name}': {', '.join(legacy_tools)}")
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else:
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print(f"⚠️ Unknown toolset: {toolset_name}")
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elif disabled_toolsets:
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# Start with all tools from all toolsets, then remove disabled ones
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# Note: Only tools that are part of toolsets are accessible
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# We need to get all tools from all defined toolsets
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from toolsets import get_all_toolsets
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all_toolset_tools = set()
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for toolset_name in get_all_toolsets():
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resolved_tools = resolve_toolset(toolset_name)
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all_toolset_tools.update(resolved_tools)
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# Start with all tools from toolsets
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tools_to_include = all_toolset_tools
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# Remove tools from disabled toolsets
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for toolset_name in disabled_toolsets:
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if validate_toolset(toolset_name):
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resolved_tools = resolve_toolset(toolset_name)
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tools_to_include.difference_update(resolved_tools)
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print(f"🚫 Disabled toolset '{toolset_name}': {', '.join(resolved_tools) if resolved_tools else 'no tools'}")
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else:
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# Try legacy compatibility
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if toolset_name in ["web_tools", "terminal_tools", "vision_tools", "moa_tools", "image_tools", "browser_tools"]:
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legacy_map = {
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"web_tools": ["web_search", "web_extract"],
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"terminal_tools": ["terminal"],
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"vision_tools": ["vision_analyze"],
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"moa_tools": ["mixture_of_agents"],
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"image_tools": ["image_generate"],
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"browser_tools": [
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"browser_navigate", "browser_snapshot", "browser_click",
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"browser_type", "browser_scroll", "browser_back",
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"browser_press", "browser_close", "browser_get_images",
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"browser_vision"
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]
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}
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legacy_tools = legacy_map.get(toolset_name, [])
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tools_to_include.difference_update(legacy_tools)
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print(f"🚫 Disabled legacy toolset '{toolset_name}': {', '.join(legacy_tools)}")
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else:
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print(f"⚠️ Unknown toolset: {toolset_name}")
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else:
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# No filtering - include all tools from all defined toolsets
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from toolsets import get_all_toolsets
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for toolset_name in get_all_toolsets():
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resolved_tools = resolve_toolset(toolset_name)
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tools_to_include.update(resolved_tools)
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# Build final tool list (only include tools that are available)
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filtered_tools = []
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for tool_name in tools_to_include:
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if tool_name in all_available_tools_map:
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filtered_tools.append(all_available_tools_map[tool_name])
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# Sort tools for consistent ordering
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filtered_tools.sort(key=lambda t: t["function"]["name"])
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if filtered_tools:
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tool_names = [t["function"]["name"] for t in filtered_tools]
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print(f"🛠️ Final tool selection ({len(filtered_tools)} tools): {', '.join(tool_names)}")
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else:
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print("🛠️ No tools selected (all filtered out or unavailable)")
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return filtered_tools
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def handle_web_function_call(function_name: str, function_args: Dict[str, Any]) -> str:
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"""
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Handle function calls for web tools.
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Args:
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function_name (str): Name of the web function to call
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function_args (Dict): Arguments for the function
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|
Returns:
|
|
str: Function result as JSON string
|
|
"""
|
|
if function_name == "web_search":
|
|
query = function_args.get("query", "")
|
|
# Always use fixed limit of 5
|
|
limit = 5
|
|
return web_search_tool(query, limit)
|
|
|
|
elif function_name == "web_extract":
|
|
urls = function_args.get("urls", [])
|
|
# Limit URLs to prevent abuse
|
|
urls = urls[:5] if isinstance(urls, list) else []
|
|
# Run async function in event loop
|
|
return asyncio.run(web_extract_tool(urls, "markdown"))
|
|
|
|
else:
|
|
return json.dumps({"error": f"Unknown web function: {function_name}"}, ensure_ascii=False)
|
|
|
|
def handle_terminal_function_call(function_name: str, function_args: Dict[str, Any], task_id: Optional[str] = None) -> str:
|
|
"""
|
|
Handle function calls for terminal tools.
|
|
|
|
Uses mini-swe-agent backend (local/docker/modal) by default.
|
|
|
|
Args:
|
|
function_name (str): Name of the terminal function to call
|
|
function_args (Dict): Arguments for the function
|
|
task_id (str): Unique identifier for this task to isolate environments between concurrent tasks (optional)
|
|
|
|
Returns:
|
|
str: Function result as JSON string
|
|
"""
|
|
if function_name == "terminal":
|
|
command = function_args.get("command")
|
|
background = function_args.get("background", False)
|
|
timeout = function_args.get("timeout")
|
|
|
|
return terminal_tool(command=command, background=background, timeout=timeout, task_id=task_id)
|
|
|
|
else:
|
|
return json.dumps({"error": f"Unknown terminal function: {function_name}"}, ensure_ascii=False)
|
|
|
|
|
|
def handle_vision_function_call(function_name: str, function_args: Dict[str, Any]) -> str:
|
|
"""
|
|
Handle function calls for vision tools.
|
|
|
|
Args:
|
|
function_name (str): Name of the vision function to call
|
|
function_args (Dict): Arguments for the function
|
|
|
|
Returns:
|
|
str: Function result as JSON string
|
|
"""
|
|
if function_name == "vision_analyze":
|
|
image_url = function_args.get("image_url", "")
|
|
question = function_args.get("question", "")
|
|
|
|
full_prompt = f"Fully describe and explain everything about this image, then answer the following question:\n\n{question}"
|
|
|
|
# Run async function in event loop
|
|
return asyncio.run(vision_analyze_tool(image_url, full_prompt, "google/gemini-3-flash-preview"))
|
|
|
|
else:
|
|
return json.dumps({"error": f"Unknown vision function: {function_name}"}, ensure_ascii=False)
|
|
|
|
|
|
def handle_moa_function_call(function_name: str, function_args: Dict[str, Any]) -> str:
|
|
"""
|
|
Handle function calls for Mixture-of-Agents tools.
|
|
|
|
Args:
|
|
function_name (str): Name of the MoA function to call
|
|
function_args (Dict): Arguments for the function
|
|
|
|
Returns:
|
|
str: Function result as JSON string
|
|
"""
|
|
if function_name == "mixture_of_agents":
|
|
user_prompt = function_args.get("user_prompt", "")
|
|
|
|
if not user_prompt:
|
|
return json.dumps({"error": "user_prompt is required for MoA processing"}, ensure_ascii=False)
|
|
|
|
# Run async function in event loop
|
|
return asyncio.run(mixture_of_agents_tool(user_prompt=user_prompt))
|
|
|
|
else:
|
|
return json.dumps({"error": f"Unknown MoA function: {function_name}"}, ensure_ascii=False)
|
|
|
|
|
|
def handle_image_function_call(function_name: str, function_args: Dict[str, Any]) -> str:
|
|
"""
|
|
Handle function calls for image generation tools.
|
|
|
|
Args:
|
|
function_name (str): Name of the image generation function to call
|
|
function_args (Dict): Arguments for the function
|
|
|
|
Returns:
|
|
str: Function result as JSON string
|
|
"""
|
|
if function_name == "image_generate":
|
|
prompt = function_args.get("prompt", "")
|
|
|
|
if not prompt:
|
|
return json.dumps({"success": False, "image": None}, ensure_ascii=False)
|
|
|
|
aspect_ratio = function_args.get("aspect_ratio", "landscape")
|
|
|
|
# Use fixed internal defaults for all other parameters (not exposed to model)
|
|
num_inference_steps = 50
|
|
guidance_scale = 4.5
|
|
num_images = 1
|
|
output_format = "png"
|
|
seed = None
|
|
|
|
# Run async function in event loop with proper handling for multiprocessing
|
|
try:
|
|
# Try to get existing event loop
|
|
loop = asyncio.get_event_loop()
|
|
if loop.is_closed():
|
|
# If closed, create a new one
|
|
loop = asyncio.new_event_loop()
|
|
asyncio.set_event_loop(loop)
|
|
except RuntimeError:
|
|
# No event loop in current thread, create one
|
|
loop = asyncio.new_event_loop()
|
|
asyncio.set_event_loop(loop)
|
|
|
|
# Run the coroutine in the event loop
|
|
result = loop.run_until_complete(image_generate_tool(
|
|
prompt=prompt,
|
|
aspect_ratio=aspect_ratio,
|
|
num_inference_steps=num_inference_steps,
|
|
guidance_scale=guidance_scale,
|
|
num_images=num_images,
|
|
output_format=output_format,
|
|
seed=seed
|
|
))
|
|
|
|
return result
|
|
|
|
else:
|
|
return json.dumps({"error": f"Unknown image generation function: {function_name}"}, ensure_ascii=False)
|
|
|
|
|
|
# Browser tool handlers mapping
|
|
BROWSER_HANDLERS = {
|
|
"browser_navigate": browser_navigate,
|
|
"browser_click": browser_click,
|
|
"browser_type": browser_type,
|
|
"browser_scroll": browser_scroll,
|
|
"browser_back": browser_back,
|
|
"browser_press": browser_press,
|
|
"browser_close": browser_close,
|
|
"browser_get_images": browser_get_images,
|
|
"browser_vision": browser_vision,
|
|
}
|
|
|
|
|
|
def handle_browser_function_call(
|
|
function_name: str,
|
|
function_args: Dict[str, Any],
|
|
task_id: Optional[str] = None,
|
|
user_task: Optional[str] = None
|
|
) -> str:
|
|
"""
|
|
Handle function calls for browser automation tools.
|
|
|
|
Args:
|
|
function_name (str): Name of the browser function to call
|
|
function_args (Dict): Arguments for the function
|
|
task_id (str): Task identifier for session isolation
|
|
user_task (str): User's current task (for task-aware extraction in snapshots)
|
|
|
|
Returns:
|
|
str: Function result as JSON string
|
|
"""
|
|
# Special handling for browser_snapshot which needs user_task for extraction
|
|
if function_name == "browser_snapshot":
|
|
full = function_args.get("full", False)
|
|
return browser_snapshot(full=full, task_id=task_id, user_task=user_task)
|
|
|
|
# Handle other browser tools
|
|
if function_name in BROWSER_HANDLERS:
|
|
handler = BROWSER_HANDLERS[function_name]
|
|
# Add task_id to args
|
|
return handler(**function_args, task_id=task_id)
|
|
|
|
return json.dumps({"error": f"Unknown browser function: {function_name}"}, ensure_ascii=False)
|
|
|
|
|
|
def handle_function_call(
|
|
function_name: str,
|
|
function_args: Dict[str, Any],
|
|
task_id: Optional[str] = None,
|
|
user_task: Optional[str] = None
|
|
) -> str:
|
|
"""
|
|
Main function call dispatcher that routes calls to appropriate toolsets.
|
|
|
|
This function determines which toolset a function belongs to and dispatches
|
|
the call to the appropriate handler. This makes it easy to add new toolsets
|
|
without changing the main calling interface.
|
|
|
|
Args:
|
|
function_name (str): Name of the function to call
|
|
function_args (Dict): Arguments for the function
|
|
task_id (str): Unique identifier for this task to isolate VMs/sessions between concurrent tasks (optional)
|
|
user_task (str): The user's original task/query (used for task-aware content extraction) (optional)
|
|
|
|
Returns:
|
|
str: Function result as JSON string
|
|
|
|
Raises:
|
|
None: Returns error as JSON string instead of raising exceptions
|
|
"""
|
|
try:
|
|
# Route web tools
|
|
if function_name in ["web_search", "web_extract"]:
|
|
return handle_web_function_call(function_name, function_args)
|
|
|
|
# Route terminal tools
|
|
elif function_name in ["terminal"]:
|
|
return handle_terminal_function_call(function_name, function_args, task_id)
|
|
|
|
# Route vision tools
|
|
elif function_name in ["vision_analyze"]:
|
|
return handle_vision_function_call(function_name, function_args)
|
|
|
|
# Route MoA tools
|
|
elif function_name in ["mixture_of_agents"]:
|
|
return handle_moa_function_call(function_name, function_args)
|
|
|
|
# Route image generation tools
|
|
elif function_name in ["image_generate"]:
|
|
return handle_image_function_call(function_name, function_args)
|
|
|
|
# Route browser automation tools
|
|
elif function_name in [
|
|
"browser_navigate", "browser_snapshot", "browser_click",
|
|
"browser_type", "browser_scroll", "browser_back",
|
|
"browser_press", "browser_close", "browser_get_images",
|
|
"browser_vision"
|
|
]:
|
|
return handle_browser_function_call(function_name, function_args, task_id, user_task)
|
|
|
|
else:
|
|
error_msg = f"Unknown function: {function_name}"
|
|
print(f"❌ {error_msg}")
|
|
|
|
return json.dumps({"error": error_msg}, ensure_ascii=False)
|
|
|
|
except Exception as e:
|
|
error_msg = f"Error executing {function_name}: {str(e)}"
|
|
print(f"❌ {error_msg}")
|
|
return json.dumps({"error": error_msg}, ensure_ascii=False)
|
|
|
|
def get_available_toolsets() -> Dict[str, Dict[str, Any]]:
|
|
"""
|
|
Get information about all available toolsets and their status.
|
|
|
|
Returns:
|
|
Dict: Information about each toolset including availability and tools
|
|
"""
|
|
toolsets = {
|
|
"web_tools": {
|
|
"available": check_firecrawl_api_key(),
|
|
"tools": ["web_search_tool", "web_extract_tool"],
|
|
"description": "Web search and content extraction tools",
|
|
"requirements": ["FIRECRAWL_API_KEY environment variable"]
|
|
},
|
|
"terminal_tools": {
|
|
"available": check_terminal_requirements(),
|
|
"tools": ["terminal_tool"],
|
|
"description": "Execute commands using mini-swe-agent (local/docker/modal)",
|
|
"requirements": ["mini-swe-agent package, TERMINAL_ENV to select backend"]
|
|
},
|
|
"vision_tools": {
|
|
"available": check_vision_requirements(),
|
|
"tools": ["vision_analyze_tool"],
|
|
"description": "Analyze images from URLs using AI vision for comprehensive understanding",
|
|
"requirements": ["NOUS_API_KEY environment variable"]
|
|
},
|
|
"moa_tools": {
|
|
"available": check_moa_requirements(),
|
|
"tools": ["mixture_of_agents_tool"],
|
|
"description": "Process extremely difficult problems using Mixture-of-Agents methodology with multiple frontier models collaborating for enhanced reasoning. Best for complex math, coding, and analytical tasks.",
|
|
"requirements": ["NOUS_API_KEY environment variable"]
|
|
},
|
|
"image_tools": {
|
|
"available": check_image_generation_requirements(),
|
|
"tools": ["image_generate_tool"],
|
|
"description": "Generate high-quality images from text prompts using FAL.ai's FLUX.1 Krea model with automatic 2x upscaling for enhanced quality",
|
|
"requirements": ["FAL_KEY environment variable", "fal-client package"]
|
|
},
|
|
"browser_tools": {
|
|
"available": check_browser_requirements(),
|
|
"tools": [
|
|
"browser_navigate", "browser_snapshot", "browser_click",
|
|
"browser_type", "browser_scroll", "browser_back",
|
|
"browser_press", "browser_close", "browser_get_images",
|
|
"browser_vision"
|
|
],
|
|
"description": "Browser automation for web interaction using agent-browser CLI with Browserbase cloud execution",
|
|
"requirements": ["BROWSERBASE_API_KEY", "BROWSERBASE_PROJECT_ID", "agent-browser npm package"]
|
|
}
|
|
}
|
|
|
|
return toolsets
|
|
|
|
def check_toolset_requirements() -> Dict[str, bool]:
|
|
"""
|
|
Check if all requirements for available toolsets are met.
|
|
|
|
Returns:
|
|
Dict: Status of each toolset's requirements
|
|
"""
|
|
return {
|
|
"web_tools": check_firecrawl_api_key(),
|
|
"terminal_tools": check_terminal_requirements(),
|
|
"vision_tools": check_vision_requirements(),
|
|
"moa_tools": check_moa_requirements(),
|
|
"image_tools": check_image_generation_requirements(),
|
|
"browser_tools": check_browser_requirements()
|
|
}
|
|
|
|
if __name__ == "__main__":
|
|
"""
|
|
Simple test/demo when run directly
|
|
"""
|
|
print("🛠️ Model Tools Module")
|
|
print("=" * 40)
|
|
|
|
# Check toolset requirements
|
|
requirements = check_toolset_requirements()
|
|
print("📋 Toolset Requirements:")
|
|
for toolset, available in requirements.items():
|
|
status = "✅" if available else "❌"
|
|
print(f" {status} {toolset}: {'Available' if available else 'Missing requirements'}")
|
|
|
|
# Show all available tool names
|
|
all_tool_names = get_all_tool_names()
|
|
print(f"\n🔧 Available Tools ({len(all_tool_names)} total):")
|
|
for tool_name in all_tool_names:
|
|
toolset = get_toolset_for_tool(tool_name)
|
|
print(f" 📌 {tool_name} (from {toolset})")
|
|
|
|
# Show available tools with full definitions
|
|
tools = get_tool_definitions()
|
|
print(f"\n📝 Tool Definitions ({len(tools)} loaded):")
|
|
for tool in tools:
|
|
func_name = tool["function"]["name"]
|
|
desc = tool["function"]["description"]
|
|
print(f" 🔹 {func_name}: {desc[:60]}{'...' if len(desc) > 60 else ''}")
|
|
|
|
# Show toolset info
|
|
toolsets = get_available_toolsets()
|
|
print(f"\n📦 Toolset Information:")
|
|
for name, info in toolsets.items():
|
|
status = "✅" if info["available"] else "❌"
|
|
print(f" {status} {name}: {info['description']}")
|
|
if not info["available"]:
|
|
print(f" Requirements: {', '.join(info['requirements'])}")
|
|
|
|
print("\n💡 Usage Examples:")
|
|
print(" from model_tools import get_tool_definitions, handle_function_call")
|
|
print(" # All tools")
|
|
print(" tools = get_tool_definitions()")
|
|
print(" # Only web tools")
|
|
print(" tools = get_tool_definitions(enabled_toolsets=['web_tools'])")
|
|
print(" # Specific tools only")
|
|
print(" tools = get_tool_definitions(enabled_tools=['web_search', 'terminal'])")
|
|
print(" # All except terminal")
|
|
print(" tools = get_tool_definitions(disabled_tools=['terminal'])")
|
|
|
|
# Example filtering
|
|
print(f"\n🧪 Filtering Examples:")
|
|
web_only = get_tool_definitions(enabled_toolsets=["web_tools"])
|
|
print(f" Web tools only: {len(web_only)} tools")
|
|
|
|
if len(all_tool_names) > 1:
|
|
specific_tools = get_tool_definitions(enabled_tools=["web_search"])
|
|
print(f" Only web_search: {len(specific_tools)} tool(s)")
|
|
|
|
if "terminal" in all_tool_names:
|
|
no_terminal = get_tool_definitions(disabled_tools=["terminal"])
|
|
print(f" All except terminal: {len(no_terminal)} tools")
|