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.
357 lines
12 KiB
Python
357 lines
12 KiB
Python
#!/usr/bin/env python3
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"""
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Toolset Distributions Module
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This module defines distributions of toolsets for data generation runs.
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Each distribution specifies which toolsets should be used and their probability
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of being selected for any given prompt during the batch processing.
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A distribution is a dictionary mapping toolset names to their selection probability (%).
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Probabilities should sum to 100, but the system will normalize if they don't.
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Usage:
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from toolset_distributions import get_distribution, list_distributions
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# Get a specific distribution
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dist = get_distribution("image_gen")
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# List all available distributions
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all_dists = list_distributions()
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"""
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from typing import Dict, List, Optional
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import random
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from toolsets import validate_toolset
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# Distribution definitions
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# Each key is a distribution name, and the value is a dict of toolset_name: probability_percentage
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DISTRIBUTIONS = {
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# Default: All tools available 100% of the time
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"default": {
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"description": "All available tools, all the time",
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"toolsets": {
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"web": 100,
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"vision": 100,
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"image_gen": 100,
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"terminal": 100,
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"moa": 100,
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"browser": 100
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}
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},
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# Image generation focused distribution
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"image_gen": {
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"description": "Heavy focus on image generation with vision and web support",
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"toolsets": {
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"image_gen": 90, # 80% chance of image generation tools
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"vision": 90, # 60% chance of vision tools
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"web": 55, # 40% chance of web tools
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"terminal": 45,
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"moa": 10 # 20% chance of reasoning tools
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}
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},
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# Research-focused distribution
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"research": {
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"description": "Web research with vision analysis and reasoning",
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"toolsets": {
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"web": 90, # 90% chance of web tools
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"browser": 70, # 70% chance of browser tools for deep research
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"vision": 50, # 50% chance of vision tools
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"moa": 40, # 40% chance of reasoning tools
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"terminal": 10 # 10% chance of terminal tools
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}
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},
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# Scientific problem solving focused distribution
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"science": {
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"description": "Scientific research with web, terminal, and browser capabilities",
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"toolsets": {
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"web": 94, # 94% chance of web tools
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"terminal": 94, # 94% chance of terminal tools
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"vision": 65, # 65% chance of vision tools
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"browser": 50, # 50% chance of browser for accessing papers/databases
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"image_gen": 15, # 15% chance of image generation tools
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"moa": 10 # 10% chance of reasoning tools
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}
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},
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# Development-focused distribution
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"development": {
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"description": "Terminal and reasoning with occasional web lookup",
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"toolsets": {
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"terminal": 80, # 80% chance of terminal tools
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"moa": 60, # 60% chance of reasoning tools
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"web": 30, # 30% chance of web tools
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"vision": 10 # 10% chance of vision tools
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}
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},
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# Safe mode (no terminal)
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"safe": {
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"description": "All tools except terminal for safety",
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"toolsets": {
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"web": 80,
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"browser": 70, # Browser is safe (no local filesystem access)
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"vision": 60,
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"image_gen": 60,
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"moa": 50
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}
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},
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# Balanced distribution
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"balanced": {
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"description": "Equal probability of all toolsets",
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"toolsets": {
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"web": 50,
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"vision": 50,
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"image_gen": 50,
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"terminal": 50,
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"moa": 50,
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"browser": 50
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}
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},
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# Minimal (web only)
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"minimal": {
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"description": "Only web tools for basic research",
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"toolsets": {
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"web": 100
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}
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},
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# Terminal only
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"terminal_only": {
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"description": "Only terminal tool for code execution tasks",
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"toolsets": {
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"terminal": 100
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}
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},
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# Terminal + web (common for coding tasks that need docs)
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"terminal_web": {
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"description": "Terminal with web search for documentation lookup",
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"toolsets": {
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"terminal": 100,
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"web": 100
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}
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},
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# Creative (vision + image generation)
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"creative": {
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"description": "Image generation and vision analysis focus",
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"toolsets": {
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"image_gen": 90,
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"vision": 90,
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"web": 30
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}
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},
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# Reasoning heavy
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"reasoning": {
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"description": "Heavy mixture of agents usage with minimal other tools",
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"toolsets": {
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"moa": 90,
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"web": 30,
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"terminal": 20
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}
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},
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# Browser-based web interaction
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"browser_use": {
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"description": "Full browser-based web interaction with search, vision, and page control",
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"toolsets": {
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"browser": 100, # All browser tools always available
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"web": 80, # Web search for finding URLs and quick lookups
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"vision": 70 # Vision analysis for images found on pages
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}
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},
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# Browser only (no other tools)
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"browser_only": {
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"description": "Only browser automation tools for pure web interaction tasks",
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"toolsets": {
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"browser": 100
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}
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},
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# Browser-focused tasks distribution (for browser-use-tasks.jsonl)
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"browser_tasks": {
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"description": "Browser-focused distribution (browser toolset includes web_search for finding URLs since Google blocks direct browser searches)",
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"toolsets": {
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"browser": 97, # 97% - browser tools (includes web_search) almost always available
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"vision": 12, # 12% - vision analysis occasionally
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"terminal": 15 # 15% - terminal occasionally for local operations
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}
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},
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# Terminal-focused tasks distribution (for nous-terminal-tasks.jsonl)
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"terminal_tasks": {
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"description": "Terminal-focused distribution with high terminal availability, occasional other tools",
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"toolsets": {
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"terminal": 97, # 97% - terminal almost always available
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"web": 15, # 15% - web search/scrape for documentation
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"browser": 10, # 10% - browser occasionally for web interaction
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"vision": 8, # 8% - vision analysis rarely
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"image_gen": 3 # 3% - image generation very rarely
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}
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},
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# Mixed browser+terminal tasks distribution (for mixed-browser-terminal-tasks.jsonl)
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"mixed_tasks": {
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"description": "Mixed distribution with high browser and terminal availability for complex tasks",
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"toolsets": {
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"browser": 92, # 92% - browser tools highly available
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"terminal": 92, # 92% - terminal highly available
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"web": 35, # 35% - web search/scrape fairly common
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"vision": 15, # 15% - vision analysis occasionally
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"image_gen": 15 # 15% - image generation occasionally
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}
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}
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}
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def get_distribution(name: str) -> Optional[Dict[str, any]]:
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"""
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Get a toolset distribution by name.
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Args:
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name (str): Name of the distribution
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Returns:
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Dict: Distribution definition with description and toolsets
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None: If distribution not found
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"""
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return DISTRIBUTIONS.get(name)
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def list_distributions() -> Dict[str, Dict]:
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"""
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List all available distributions.
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Returns:
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Dict: All distribution definitions
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"""
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return DISTRIBUTIONS.copy()
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def sample_toolsets_from_distribution(distribution_name: str) -> List[str]:
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"""
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Sample toolsets based on a distribution's probabilities.
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Each toolset in the distribution has a % chance of being included.
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This allows multiple toolsets to be active simultaneously.
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Args:
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distribution_name (str): Name of the distribution to sample from
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Returns:
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List[str]: List of sampled toolset names
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Raises:
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ValueError: If distribution name is not found
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"""
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dist = get_distribution(distribution_name)
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if not dist:
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raise ValueError(f"Unknown distribution: {distribution_name}")
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# Sample each toolset independently based on its probability
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selected_toolsets = []
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for toolset_name, probability in dist["toolsets"].items():
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# Validate toolset exists
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if not validate_toolset(toolset_name):
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print(f"⚠️ Warning: Toolset '{toolset_name}' in distribution '{distribution_name}' is not valid")
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continue
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# Roll the dice - if random value is less than probability, include this toolset
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if random.random() * 100 < probability:
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selected_toolsets.append(toolset_name)
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# If no toolsets were selected (can happen with low probabilities),
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# ensure at least one toolset is selected by picking the highest probability one
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if not selected_toolsets and dist["toolsets"]:
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# Find toolset with highest probability
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highest_prob_toolset = max(dist["toolsets"].items(), key=lambda x: x[1])[0]
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if validate_toolset(highest_prob_toolset):
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selected_toolsets.append(highest_prob_toolset)
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return selected_toolsets
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def validate_distribution(distribution_name: str) -> bool:
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"""
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Check if a distribution name is valid.
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Args:
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distribution_name (str): Distribution name to validate
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Returns:
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bool: True if valid, False otherwise
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"""
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return distribution_name in DISTRIBUTIONS
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def print_distribution_info(distribution_name: str) -> None:
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"""
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Print detailed information about a distribution.
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Args:
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distribution_name (str): Distribution name
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"""
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dist = get_distribution(distribution_name)
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if not dist:
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print(f"❌ Unknown distribution: {distribution_name}")
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return
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print(f"\n📊 Distribution: {distribution_name}")
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print(f" Description: {dist['description']}")
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print(f" Toolsets:")
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for toolset, prob in sorted(dist["toolsets"].items(), key=lambda x: x[1], reverse=True):
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print(f" • {toolset:15} : {prob:3}% chance")
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if __name__ == "__main__":
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"""
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Demo and testing of the distributions system
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"""
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print("📊 Toolset Distributions Demo")
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print("=" * 60)
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# List all distributions
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print("\n📋 Available Distributions:")
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print("-" * 40)
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for name, dist in list_distributions().items():
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print(f"\n {name}:")
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print(f" {dist['description']}")
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toolset_list = ", ".join([f"{ts}({p}%)" for ts, p in dist["toolsets"].items()])
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print(f" Toolsets: {toolset_list}")
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# Demo sampling
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print("\n\n🎲 Sampling Examples:")
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print("-" * 40)
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test_distributions = ["image_gen", "research", "balanced", "default"]
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for dist_name in test_distributions:
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print(f"\n{dist_name}:")
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# Sample 5 times to show variability
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samples = []
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for _ in range(5):
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sampled = sample_toolsets_from_distribution(dist_name)
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samples.append(sorted(sampled))
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print(f" Sample 1: {samples[0]}")
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print(f" Sample 2: {samples[1]}")
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print(f" Sample 3: {samples[2]}")
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print(f" Sample 4: {samples[3]}")
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print(f" Sample 5: {samples[4]}")
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# Show detailed info
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print("\n\n📊 Detailed Distribution Info:")
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print("-" * 40)
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print_distribution_info("image_gen")
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print_distribution_info("research")
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