reasoning 0.1.0

A reasoning framework for all LLMs

Reasoning Framework

A Python package that adds R1-style reasoning capabilities to any Language Model (LLM). This framework enables step-by-step reasoning and verification of responses using a two-step process:

1. Initial reasoning and response generation
2. Verification and refinement of the response

Installation

Basic installation:

pip install reasoning

With OpenAI support:

pip install "reasoning[openai]"

With Anthropic support:

pip install "reasoning[anthropic]"

With all supported APIs:

pip install "reasoning[openai,anthropic]"

Environment Variables

Depending on which API you're using, you'll need to set the appropriate environment variables:

• For OpenAI: OPENAI_API_KEY
• For Anthropic: ANTHROPIC_API_KEY
• For OpenRouter: OPENROUTER_API_KEY

You can set these in your shell:

export OPENAI_API_KEY='your-api-key'
export ANTHROPIC_API_KEY='your-api-key'
export OPENROUTER_API_KEY='your-api-key'

Or in Python:

import os
os.environ['OPENAI_API_KEY'] = 'your-api-key'

Quick Start

Using OpenAI

from reasoning import ReasoningFramework
from reasoning.examples.openai_example import create_openai_call

# Create model-specific callers
gpt4_call = create_openai_call("gpt-4")
gpt35_call = create_openai_call("gpt-3.5-turbo")

# Initialize the framework
framework = ReasoningFramework(
    reasoning_llm_call=gpt4_call,
    verification_llm_call=gpt35_call
)

# Process a question
response = framework.process(
    "What would be the implications of achieving AGI?",
    reasoning_kwargs={"temperature": 0.7},
    verification_kwargs={"temperature": 0.5}
)

print("Original Message:", response.message)
print("\nReasoning Process:", response.reasoning)
print("\nInitial Response:", response.initial_response)
print("\nVerified Response:", response.final_response)

Using Anthropic

from reasoning import ReasoningFramework
from reasoning.examples.anthropic_example import create_anthropic_call

# Create model-specific callers
sonnet_call = create_anthropic_call("claude-3-sonnet")
opus_call = create_anthropic_call("claude-3-opus")

# Initialize the framework
framework = ReasoningFramework(
    reasoning_llm_call=sonnet_call,
    verification_llm_call=opus_call
)

# Process a question
response = framework.process(
    "What would be the implications of achieving AGI?",
    reasoning_kwargs={"temperature": 0.7},
    verification_kwargs={"temperature": 0.5}
)

Using OpenRouter

from reasoning import ReasoningFramework
from reasoning.examples.openrouter_example import create_openrouter_call

# Create model-specific callers
r1_call = create_openrouter_call("deepseek/deepseek-r1")
claude_call = create_openrouter_call("anthropic/claude-3-sonnet")

# Initialize the framework
framework = ReasoningFramework(
    reasoning_llm_call=r1_call,
    verification_llm_call=claude_call
)

# Process a question
response = framework.process(
    "What would be the implications of achieving AGI?",
    reasoning_kwargs={"temperature": 0.7},
    verification_kwargs={"temperature": 0.5}
)

Features

• Flexible integration with any LLM through callback functions
• Built-in support for OpenAI, Anthropic, and OpenRouter APIs
• Structured reasoning process with verification
• Customizable system prompts for both reasoning and verification
• Type-safe implementation using Pydantic models
• Comprehensive logging for debugging

Advanced Usage

Custom System Prompts

framework = ReasoningFramework(
    reasoning_llm_call=my_llm_call,
    verification_llm_call=my_verification_call,
    reasoning_system_prompt="You are an expert at breaking down complex problems...",
    verification_system_prompt="You are a critical thinker who verifies conclusions..."
)

Error Handling

The framework includes built-in error handling and logging:

import logging
logging.basicConfig(level=logging.DEBUG)  # Set to see detailed logs

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.