Documentation Index
Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
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Thinking Module
The thinking module provides configurable thinking budgets for LLM reasoning, allowing control over token and time budgets for extended thinking.
Installation
pip install praisonaiagents
Features
- Token budgets for extended thinking
- Time budgets for reasoning
- Adaptive budget allocation
- Budget tracking and reporting
Quick Start
from praisonaiagents import Agent
from praisonaiagents.thinking import ThinkingBudget
# Create a thinking budget
budget = ThinkingBudget(
max_tokens=16000,
max_time_seconds=60,
adaptive=True
)
# Apply to agent
agent = Agent(
name="Reasoner",
instructions="You are a reasoning assistant.",
)
# Set thinking budget via property
agent.thinking_budget = budget
Classes
ThinkingBudget
Configure thinking budgets for agents.
from praisonaiagents.thinking import ThinkingBudget
budget = ThinkingBudget(
max_tokens=16000,
max_time_seconds=60,
adaptive=True
)
Constructor
| Parameter | Type | Default | Description |
|---|
max_tokens | int | 8000 | Maximum thinking tokens |
max_time_seconds | int | 30 | Maximum thinking time |
adaptive | bool | False | Adapt budget based on task |
ThinkingConfig
Configuration for thinking behavior.
from praisonaiagents.thinking import ThinkingConfig
config = ThinkingConfig(
enabled=True,
budget=budget,
show_thinking=False
)
Attributes
| Attribute | Type | Description |
|---|
enabled | bool | Whether thinking is enabled |
budget | ThinkingBudget | Budget configuration |
show_thinking | bool | Show thinking in output |
ThinkingUsage
Track thinking usage.
from praisonaiagents.thinking import ThinkingUsage
usage = ThinkingUsage(
tokens_used=5000,
time_seconds=15.5
)
Attributes
| Attribute | Type | Description |
|---|
tokens_used | int | Tokens used for thinking |
time_seconds | float | Time spent thinking |
budget_remaining | int | Remaining token budget |
ThinkingTracker
Track thinking across multiple calls.
from praisonaiagents.thinking import ThinkingTracker
tracker = ThinkingTracker()
tracker.record(usage)
print(tracker.total_tokens)
print(tracker.total_time)
Usage Examples
Basic Thinking Budget
from praisonaiagents import Agent
from praisonaiagents.thinking import ThinkingBudget
agent = Agent(
name="Analyst",
instructions="You are an analytical assistant.",
)
agent.thinking_budget = ThinkingBudget(max_tokens=16000)
# Agent will use extended thinking for complex tasks
result = agent.chat("Analyze the implications of quantum computing on cryptography")
Adaptive Budget
from praisonaiagents.thinking import ThinkingBudget
# Budget adapts based on task complexity
budget = ThinkingBudget(
max_tokens=32000,
adaptive=True # Automatically adjusts based on task
)
agent = Agent(
name="Researcher",
instructions="You are a research assistant.",
)
agent.thinking_budget = budget
Time-Limited Thinking
from praisonaiagents.thinking import ThinkingBudget
# Limit thinking time for faster responses
budget = ThinkingBudget(
max_tokens=16000,
max_time_seconds=30 # Stop thinking after 30 seconds
)
Track Usage
from praisonaiagents.thinking import ThinkingTracker
tracker = ThinkingTracker()
# After agent runs
usage = agent.get_thinking_usage()
tracker.record(usage)
print(f"Total thinking tokens: {tracker.total_tokens}")
print(f"Total thinking time: {tracker.total_time}s")
Best Practices
- Set appropriate budgets - Balance quality vs. cost
- Use adaptive mode - Let the system optimize for task complexity
- Monitor usage - Track thinking costs over time
- Time limits - Set time limits for time-sensitive applications
