From 53751a235989df70d4d6ac81b90a85de6ff0d47c Mon Sep 17 00:00:00 2001 From: Kye Date: Thu, 2 Nov 2023 17:14:51 -0400 Subject: [PATCH] flow example and flow walkthrough guide --- positive_med.py => demos/positive_med.py | 4 - docs/examples/flow.md | 449 +++++++++++ errors.txt | 22 - flow.py | 21 +- groupchat.py | 113 ++- mkdocs.yml | 1 + stacked_worker.py | 134 ---- swarms/structs/flow.py | 33 +- swarms/tools/developer.py | 925 ----------------------- swarms/tools/file_mangagement.py | 17 - 10 files changed, 592 insertions(+), 1127 deletions(-) rename positive_med.py => demos/positive_med.py (99%) create mode 100644 docs/examples/flow.md delete mode 100644 errors.txt delete mode 100644 stacked_worker.py delete mode 100644 swarms/tools/developer.py delete mode 100644 swarms/tools/file_mangagement.py diff --git a/positive_med.py b/demos/positive_med.py similarity index 99% rename from positive_med.py rename to demos/positive_med.py index 25ecfe73..e8f879c9 100644 --- a/positive_med.py +++ b/demos/positive_med.py @@ -397,7 +397,3 @@ distribution_agent_out = print( "magenta", ) ) - - - - diff --git a/docs/examples/flow.md b/docs/examples/flow.md new file mode 100644 index 00000000..3403d55b --- /dev/null +++ b/docs/examples/flow.md @@ -0,0 +1,449 @@ +# Walkthrough Guide: Getting Started with Swarms Module's Flow Feature + +## Introduction + +Welcome to the walkthrough guide for beginners on using the "Flow" feature within the Swarms module. This guide is designed to help you understand and utilize the capabilities of the Flow class for seamless interactions with AI language models. + +**Target Audience:** + +- This guide is primarily intended for beginners who want to learn how to use the Flow feature in the Swarms module to interact with AI language models effectively. + +## Table of Contents + +1\. **Understanding the Flow Feature** + +   - 1.1 What is the Flow Feature? + +   - 1.2 Key Concepts + +2\. **Setting Up the Environment** + +   - 2.1 Prerequisites + +   - 2.2 Installing Required Libraries + +   - 2.3 Importing Necessary Modules + +3\. **Creating a Flow Instance** + +   - 3.1 Importing the Required Modules + +   - 3.2 Initializing the Language Model + +   - 3.3 Creating a Flow Instance + +4\. **Running a Flow** + +   - 4.1 Defining the Task + +   - 4.2 Running the Flow + +   - 4.3 Interacting with the AI + +   - 4.4 Dynamic Temperature Handling + +5\. **Customizing Flow Behavior** + +   - 5.1 Stopping Conditions + +   - 5.2 Retry Mechanism + +   - 5.3 Loop Interval + +   - 5.4 Interactive Mode + +6\. **Saving and Loading Flows** + +   - 6.1 Saving a Flow + +   - 6.2 Loading a Saved Flow + +7\. **Analyzing Feedback and Undoing Actions** + +   - 7.1 Providing Feedback + +   - 7.2 Undoing the Last Action + +   - 7.3 Response Filtering + +8\. **Advanced Features** + +   - 8.1 Streamed Generation + +   - 8.2 Real-time Token Generation + +9\. **Best Practices** + +   - 9.1 Conciseness and Clarity + +   - 9.2 Active Voice + +   - 9.3 Highlighting Important Points + +   - 9.4 Consistent Style + +10\. **Conclusion** + +--- + +## 1. Understanding the Flow Feature + +### 1.1 What is the Flow Feature? + +The Flow feature is a powerful component of the Swarms framework that allows developers to create a sequential, conversational interaction with AI language models. It enables developers to build multi-step conversations, generate long-form content, and perform complex tasks using AI. The Flow class provides autonomy to language models, enabling them to generate responses in a structured manner. + +### 1.2 Key Concepts + +Before diving into the practical aspects, let's clarify some key concepts related to the Flow feature: + +- **Flow:** A Flow is an instance of the Flow class that represents an ongoing interaction with an AI language model. It consists of a series of steps and responses. + +- **Stopping Condition:** A stopping condition is a criterion that, when met, allows the Flow to stop generating responses. This can be user-defined and can depend on the content of the responses. + +- **Loop Interval:** The loop interval specifies the time delay between consecutive interactions with the AI model. + +- **Retry Mechanism:** In case of errors or failures during AI model interactions, the Flow can be configured to make multiple retry attempts with a specified interval. + +- **Interactive Mode:** Interactive mode allows developers to have a back-and-forth conversation with the AI model, making it suitable for real-time interactions. + +## 2. Setting Up the Environment + +### 2.1 Prerequisites + +Before you begin, ensure that you have the following prerequisites in place: + +- Basic understanding of Python programming. + +- Access to an AI language model or API key for language model services. + +### 2.2 Installing Required Libraries + +To use the Flow feature, you'll need to install the required libraries. Make sure you have these libraries installed: + +- `termcolor`: For colorful console output. + +- `inspects`: For introspecting the language model. + +- `random`: For handling dynamic temperature. + +- Other dependencies as needed for your specific environment. + +You can install these libraries using pip: + +```bash + +pip install termcolor inspects + +``` + +### 2.3 Importing Necessary Modules + +In your Python script or environment, import the necessary modules from the Swarms framework: + +```python + +import json + +import logging + +import time + +from typing import Any, Callable, Dict, List, Optional, Tuple, Generator + +from termcolor import colored + +import inspect + +import random + +``` + +Ensure that you have these modules imported to proceed with the guide. + +## 3. Creating a Flow Instance + +To use the Flow feature, you need to create an instance of the Flow class. This instance will allow you to interact with the AI language model. + +### 3.1 Importing the Required Modules + +In your script, import the required modules for the Flow class: + +```python + +from swarms.structs import Flow + +from swarms.models import OpenAIChat  # Adjust this import according to your specific language model. + +``` + +### 3.2 Initializing the Language Model + +Initialize the language model you want to use for interactions. In this example, we're using the `OpenAIChat` model: + +```python + +# Replace 'api_key' with your actual API key or configuration. + +llm = OpenAIChat( + +    openai_api_key='your_api_key', + +    temperature=0.5, + +    max_tokens=3000, + +) + +``` + +Make sure to provide the necessary configuration, such as your API key and any model-specific parameters. + +### 3.3 Creating a Flow Instance + +Now, create an instance of the Flow class by passing the initialized language model: + +```python + +flow = Flow( + +    llm=llm, + +    max_loops=5, + +    dashboard=True, + +    stopping_condition=None,  # You can define a stopping condition as needed. + +    loop_interval=1, + +    retry_attempts=3, + +    retry_interval=1, + +    interactive=False,  # Set to 'True' for interactive mode. + +    dynamic_temperature=False,  # Set to 'True' for dynamic temperature handling. + +) + +``` + +This sets up your Flow instance with the specified parameters. Adjust these parameters based on your requirements. + +## 4. Running a Flow + +Now that you have created a Flow instance, let's run a simple interaction with the AI model using the Flow. + +### 4.1 Defining the Task + +Define the task you want the AI model to perform. This can be any prompt or question you have in mind. For example: + +```python + +task = "Generate a 10,000 word blog on health and wellness." + +``` + +### 4.2 Running the Flow + +Run the Flow by providing the task you defined: + +```python + +out = flow.run(task) + +``` + +The Flow will interact with the AI model, generate responses, and store the conversation history. + +### 4.3 Interacting with the AI + +Depending on whether you set the `interactive` parameter to `True` or `False` during Flow initialization, you can interact with the AI in real-time or simply receive the generated responses in sequence. + +If `interactive` is set to `True`, you'll have a back-and-forth conversation with the AI, where you provide input after each AI response. + +### 4.4 Dynamic Temperature Handling + +If you set the `dynamic_temperature + +` parameter to `True` during Flow initialization, the Flow class will handle temperature dynamically. Temperature affects the randomness of responses generated by the AI model. The dynamic temperature feature allows the temperature to change randomly within a specified range, enhancing response diversity. + +## 5. Customizing Flow Behavior + +The Flow feature provides various customization options to tailor its behavior to your specific use case. + +### 5.1 Stopping Conditions + +You can define custom stopping conditions that instruct the Flow to stop generating responses based on specific criteria. For example, you can stop when a certain keyword appears in the response: + +```python + +def custom_stopping_condition(response: str) -> bool: + +    return "Stop" in response.lower() + +# Set the custom stopping condition when creating the Flow instance. + +flow = Flow( + +    llm=llm, + +    max_loops=5, + +    stopping_condition=custom_stopping_condition, + +    # Other parameters... + +) + +``` + +### 5.2 Retry Mechanism + +In case of errors or issues during AI model interactions, you can configure a retry mechanism. Specify the number of retry attempts and the interval between retries: + +```python + +flow = Flow( + +    llm=llm, + +    max_loops=5, + +    retry_attempts=3, + +    retry_interval=1, + +    # Other parameters... + +) + +``` + +### 5.3 Loop Interval + +The `loop_interval` parameter determines the time delay between consecutive interactions with the AI model. Adjust this value based on your desired pace of conversation. + +### 5.4 Interactive Mode + +Set the `interactive` parameter to `True` if you want to have real-time conversations with the AI model. In interactive mode, you provide input after each AI response. + +## 6. Saving and Loading Flows + +You can save and load Flow instances to maintain conversation history or switch between different tasks. + +### 6.1 Saving a Flow + +To save a Flow instance along with its conversation history: + +```python + +flow.save("path/flow_history.json") + +``` + +This stores the conversation history as a JSON file for future reference. + +### 6.2 Loading a Saved Flow + +To load a previously saved Flow instance: + +```python + +loaded_flow = Flow(llm=llm, max_loops=5) + +loaded_flow.load("path/flow_history.json") + +``` + +This loads the conversation history into the new Flow instance, allowing you to continue the conversation or analyze past interactions. + +## 7. Analyzing Feedback and Undoing Actions + +The Flow feature supports feedback collection and the ability to undo actions. + +### 7.1 Providing Feedback + +You can provide feedback on AI responses within the Flow. Feedback can be used to analyze the quality of responses or highlight issues: + +```python + +flow.provide_feedback("The response was unclear.") + +``` + +### 7.2 Undoing the Last Action + +If you want to undo the last action taken within the Flow and revert to the previous state, you can use the `undo_last` method: + +```python + +previous_state, message = flow.undo_last() + +``` + +This helps you correct or modify previous interactions. + +### 7.3 Response Filtering + +The Flow feature allows you to add response filters to filter out specific words or content from AI responses. This can be useful for content moderation or filtering sensitive information: + +```python + +flow.add_response_filter("sensitive_word") + +``` + +The response filters will replace filtered words with placeholders, ensuring that sensitive content is not displayed. + +## 8. Advanced Features + +### 8.1 Streamed Generation + +Streamed generation allows you to generate responses token by token in real-time. This can be useful for creating interactive and dynamic conversations: + +```python + +response = flow.streamed_generation("Generate a report on finance") + +``` + +This function streams each token of the response with a slight delay, simulating real-time conversation. + +### 8.2 Real-time Token Generation + +For even finer control over token generation, you can use the `streamed_token_generation` method. This generates tokens one by one, allowing you to have precise control over the conversation pace: + +```python + +for token in flow.streamed_token_generation("Generate a report on finance"): + +    print(token, end="") + +``` + +## 9. Best Practices + +To create effective and user-friendly interactions with the AI model using the Flow feature, consider the following best practices: + +### 9.1 Conciseness and Clarity + +Ensure that your prompts and responses are concise and to the point. Avoid unnecessary verbosity. + +### 9.2 Active Voice + +Use an active voice when giving instructions or prompts. For example, say, "Generate a report" instead of "A report should be generated." + +### 9.3 Highlighting Important Points + +Use formatting options like bold text, italics, or color highlights to draw attention to important points within the conversation. + +### 9.4 Consistent Style + +Maintain a consistent tone and style throughout the conversation. If there is a style guide or specific formatting conventions, adhere to them. + +## 10. Conclusion + +In conclusion, the Flow feature in the Swarms module provides a versatile and interactive way to interact with AI language models. By following this walkthrough guide and considering the best practices, you can effectively harness the power of Flow for a wide range of applications, from generating content to performing complex tasks. + +Start creating your own interactive conversations and enjoy the benefits of seamless AI interactions with the Flow feature. Happy coding! \ No newline at end of file diff --git a/errors.txt b/errors.txt deleted file mode 100644 index 3ab96b03..00000000 --- a/errors.txt +++ /dev/null @@ -1,22 +0,0 @@ -message='Request to OpenAI API' method=post path=https://api.openai.com/v1/chat/completions -api_version=None data='{"messages": [{"role": "user", "content": "Generate a 10,000 word blog on health and wellness."}], "model": "gpt-3.5-turbo", "temperature": 0.5, "max_tokens": 3000}' message='Post details' -Converted retries value: 2 -> Retry(total=2, connect=None, read=None, redirect=None, status=None) -Starting new HTTPS connection (1): api.openai.com:443 -https://api.openai.com:443 "POST /v1/chat/completions HTTP/1.1" 200 None -message='OpenAI API response' path=https://api.openai.com/v1/chat/completions processing_ms=13516 request_id=971b8437917cf6e46e5fe1340060f0e4 response_code=200 -message='Request to OpenAI API' method=post path=https://api.openai.com/v1/chat/completions -api_version=None data='{"messages": [{"role": "user", "content": "Title: The Ultimate Guide to Health and Wellness: Unlocking Your Full Potential\\n\\nIntroduction (Word Count: 500)\\nHealth and wellness are essential aspects of our lives that directly impact our overall well-being. In this comprehensive guide, we will explore various dimensions of health and wellness, providing valuable insights, practical tips, and evidence-based strategies to help you achieve optimal physical, mental, and emotional well-being. From nutrition and exercise to stress management and self-care, we will delve into every aspect of leading a healthy and fulfilling life. So, let\'s embark on this transformative journey together!\\n\\nTable of Contents:\\n\\n1. Understanding Health and Wellness (Word Count: 800)\\n1.1 Defining Health and Wellness\\n1.2 The Importance of Health and Wellness\\n1.3 The Connection between Physical, Mental, and Emotional Well-being\\n1.4 The Role of Lifestyle Choices in Health and Wellness\\n\\n2. Nourishing Your Body (Word Count: 1,200)\\n2.1 The Fundamentals of a Balanced Diet\\n2.2 The Power of Whole Foods and Nutrient Density\\n2.3 Understanding Macronutrients and Micronutrients\\n2.4 The Role of Hydration in Health\\n2.5 Exploring Different Dietary Approaches\\n\\n3. Moving Towards Fitness (Word Count: 1,200)\\n3.1 The Benefits of Regular Physical Activity\\n3.2 Designing an Effective Exercise Routine\\n3.3 Cardiovascular Exercise and Its Impact on Health\\n3.4 Strength Training for Optimal Fitness\\n3.5 The Importance of Flexibility and Balance\\n\\n4. Prioritizing Mental and Emotional Well-being (Word Count: 1,500)\\n4.1 Understanding Mental Health and Emotional Well-being\\n4.2 Stress Management Techniques and Coping Strategies\\n4.3 The Power of Mindfulness and Meditation\\n4.4 Building Resilience and Emotional Intelligence\\n4.5 Seeking Professional Help and Support\\n\\n5. Cultivating Healthy Habits (Word Count: 1,500)\\n5.1 The Science of Habit Formation\\n5.2 The Role of Sleep in Health and Wellness\\n5.3 Strategies for Effective Time Management\\n5.4 Creating a Healthy Home Environment\\n5.5 The Importance of Social Connections and Relationships\\n\\n6. Embracing Self-Care (Word Count: 1,000)\\n6.1 Understanding Self-Care and Its Impact on Well-being\\n6.2 Developing a Personalized Self-Care Routine\\n6.3 The Benefits of Regular Relaxation and Recreation\\n6.4 Exploring Creative Outlets for Self-Expression\\n6.5 Practicing Gratitude and Positive Thinking\\n\\n7. Navigating Common Health Concerns (Word Count: 1,800)\\n7.1 Preventing and Managing Chronic Diseases\\n7.2 Mental Health Disorders: Causes, Symptoms, and Treatments\\n7.3 Women\'s Health: From Menstruation to Menopause\\n7.4 Maintaining a Healthy Heart and Cardiovascular System\\n7.5 Strategies for Boosting Immune Function\\n\\n8. Holistic Approaches to Health and Wellness (Word Count: 1,000)\\n8.1 Traditional Medicine and Integrative Health Practices\\n8.2 The Benefits of Herbal Medicine and Natural Remedies\\n8.3 Exploring Alternative Therapies: Acupuncture, Ayurveda, and more\\n8.4 Harnessing the Power of Energy Healing and Chakra Balancing\\n8.5 The Role of Spirituality and Mind-Body Connection\\n\\nConclusion (Word Count: 300)\\nIn this extensive guide, we have covered a wide range of topics related to health and wellness, equipping you with the knowledge and tools to embark on your personal journey towards optimal well-being. Remember, true health and wellness are not achieved overnight but require consistent effort, commitment, and self-care. By implementing the strategies outlined in this guide, you can unlock your full potential and live a vibrant, fulfilling life. So, embrace the power of health and wellness and start your transformative journey today!\\n\\nWord Count: 10,000"}], "model": "gpt-3.5-turbo", "temperature": 0.5, "max_tokens": 3000}' message='Post details' -https://api.openai.com:443 "POST /v1/chat/completions HTTP/1.1" 200 None -message='OpenAI API response' path=https://api.openai.com/v1/chat/completions processing_ms=14472 request_id=351166c14151ef9e628dcd036573e36e response_code=200 -message='Request to OpenAI API' method=post path=https://api.openai.com/v1/chat/completions -api_version=None data='{"messages": [{"role": "user", "content": "Note: The word count provided is an estimation and may vary slightly.\\n\\nTitle: The Ultimate Guide to Health and Wellness: Unlocking Your Full Potential\\n\\nIntroduction (Word Count: 500)\\nHealth and wellness are essential aspects of our lives that directly impact our overall well-being. In this comprehensive guide, we will explore various dimensions of health and wellness, providing valuable insights, practical tips, and evidence-based strategies to help you achieve optimal physical, mental, and emotional well-being. From nutrition and exercise to stress management and self-care, we will delve into every aspect of leading a healthy and fulfilling life. So, let\'s embark on this transformative journey together!\\n\\nTable of Contents:\\n\\n1. Understanding Health and Wellness (Word Count: 800)\\n1.1 Defining Health and Wellness\\n1.2 The Importance of Health and Wellness\\n1.3 The Connection between Physical, Mental, and Emotional Well-being\\n1.4 The Role of Lifestyle Choices in Health and Wellness\\n\\n2. Nourishing Your Body (Word Count: 1,200)\\n2.1 The Fundamentals of a Balanced Diet\\n2.2 The Power of Whole Foods and Nutrient Density\\n2.3 Understanding Macronutrients and Micronutrients\\n2.4 The Role of Hydration in Health\\n2.5 Exploring Different Dietary Approaches\\n\\n3. Moving Towards Fitness (Word Count: 1,200)\\n3.1 The Benefits of Regular Physical Activity\\n3.2 Designing an Effective Exercise Routine\\n3.3 Cardiovascular Exercise and Its Impact on Health\\n3.4 Strength Training for Optimal Fitness\\n3.5 The Importance of Flexibility and Balance\\n\\n4. Prioritizing Mental and Emotional Well-being (Word Count: 1,500)\\n4.1 Understanding Mental Health and Emotional Well-being\\n4.2 Stress Management Techniques and Coping Strategies\\n4.3 The Power of Mindfulness and Meditation\\n4.4 Building Resilience and Emotional Intelligence\\n4.5 Seeking Professional Help and Support\\n\\n5. Cultivating Healthy Habits (Word Count: 1,500)\\n5.1 The Science of Habit Formation\\n5.2 The Role of Sleep in Health and Wellness\\n5.3 Strategies for Effective Time Management\\n5.4 Creating a Healthy Home Environment\\n5.5 The Importance of Social Connections and Relationships\\n\\n6. Embracing Self-Care (Word Count: 1,000)\\n6.1 Understanding Self-Care and Its Impact on Well-being\\n6.2 Developing a Personalized Self-Care Routine\\n6.3 The Benefits of Regular Relaxation and Recreation\\n6.4 Exploring Creative Outlets for Self-Expression\\n6.5 Practicing Gratitude and Positive Thinking\\n\\n7. Navigating Common Health Concerns (Word Count: 1,800)\\n7.1 Preventing and Managing Chronic Diseases\\n7.2 Mental Health Disorders: Causes, Symptoms, and Treatments\\n7.3 Women\'s Health: From Menstruation to Menopause\\n7.4 Maintaining a Healthy Heart and Cardiovascular System\\n7.5 Strategies for Boosting Immune Function\\n\\n8. Holistic Approaches to Health and Wellness (Word Count: 1,000)\\n8.1 Traditional Medicine and Integrative Health Practices\\n8.2 The Benefits of Herbal Medicine and Natural Remedies\\n8.3 Exploring Alternative Therapies: Acupuncture, Ayurveda, and more\\n8.4 Harnessing the Power of Energy Healing and Chakra Balancing\\n8.5 The Role of Spirituality and Mind-Body Connection\\n\\nConclusion (Word Count: 300)\\nIn this extensive guide, we have covered a wide range of topics related to health and wellness, equipping you with the knowledge and tools to embark on your personal journey towards optimal well-being. Remember, true health and wellness are not achieved overnight but require consistent effort, commitment, and self-care. By implementing the strategies outlined in this guide, you can unlock your full potential and live a vibrant, fulfilling life. So, embrace the power of health and wellness and start your transformative journey today!\\n\\nWord Count: 10,000"}], "model": "gpt-3.5-turbo", "temperature": 0.5, "max_tokens": 3000}' message='Post details' -https://api.openai.com:443 "POST /v1/chat/completions HTTP/1.1" 200 None -message='OpenAI API response' path=https://api.openai.com/v1/chat/completions processing_ms=13492 request_id=adff9627a295fd94fb7d164f9f67acbe response_code=200 -message='Request to OpenAI API' method=post path=https://api.openai.com/v1/chat/completions -api_version=None data='{"messages": [{"role": "user", "content": "Disclaimer: The word count provided is an estimation and may vary slightly.\\n\\nTitle: The Ultimate Guide to Health and Wellness: Unlocking Your Full Potential\\n\\nIntroduction (Word Count: 500)\\nHealth and wellness are essential aspects of our lives that directly impact our overall well-being. In this comprehensive guide, we will explore various dimensions of health and wellness, providing valuable insights, practical tips, and evidence-based strategies to help you achieve optimal physical, mental, and emotional well-being. From nutrition and exercise to stress management and self-care, we will delve into every aspect of leading a healthy and fulfilling life. So, let\'s embark on this transformative journey together!\\n\\nTable of Contents:\\n\\n1. Understanding Health and Wellness (Word Count: 800)\\n1.1 Defining Health and Wellness\\n1.2 The Importance of Health and Wellness\\n1.3 The Connection between Physical, Mental, and Emotional Well-being\\n1.4 The Role of Lifestyle Choices in Health and Wellness\\n\\n2. Nourishing Your Body (Word Count: 1,200)\\n2.1 The Fundamentals of a Balanced Diet\\n2.2 The Power of Whole Foods and Nutrient Density\\n2.3 Understanding Macronutrients and Micronutrients\\n2.4 The Role of Hydration in Health\\n2.5 Exploring Different Dietary Approaches\\n\\n3. Moving Towards Fitness (Word Count: 1,200)\\n3.1 The Benefits of Regular Physical Activity\\n3.2 Designing an Effective Exercise Routine\\n3.3 Cardiovascular Exercise and Its Impact on Health\\n3.4 Strength Training for Optimal Fitness\\n3.5 The Importance of Flexibility and Balance\\n\\n4. Prioritizing Mental and Emotional Well-being (Word Count: 1,500)\\n4.1 Understanding Mental Health and Emotional Well-being\\n4.2 Stress Management Techniques and Coping Strategies\\n4.3 The Power of Mindfulness and Meditation\\n4.4 Building Resilience and Emotional Intelligence\\n4.5 Seeking Professional Help and Support\\n\\n5. Cultivating Healthy Habits (Word Count: 1,500)\\n5.1 The Science of Habit Formation\\n5.2 The Role of Sleep in Health and Wellness\\n5.3 Strategies for Effective Time Management\\n5.4 Creating a Healthy Home Environment\\n5.5 The Importance of Social Connections and Relationships\\n\\n6. Embracing Self-Care (Word Count: 1,000)\\n6.1 Understanding Self-Care and Its Impact on Well-being\\n6.2 Developing a Personalized Self-Care Routine\\n6.3 The Benefits of Regular Relaxation and Recreation\\n6.4 Exploring Creative Outlets for Self-Expression\\n6.5 Practicing Gratitude and Positive Thinking\\n\\n7. Navigating Common Health Concerns (Word Count: 1,800)\\n7.1 Preventing and Managing Chronic Diseases\\n7.2 Mental Health Disorders: Causes, Symptoms, and Treatments\\n7.3 Women\'s Health: From Menstruation to Menopause\\n7.4 Maintaining a Healthy Heart and Cardiovascular System\\n7.5 Strategies for Boosting Immune Function\\n\\n8. Holistic Approaches to Health and Wellness (Word Count: 1,000)\\n8.1 Traditional Medicine and Integrative Health Practices\\n8.2 The Benefits of Herbal Medicine and Natural Remedies\\n8.3 Exploring Alternative Therapies: Acupuncture, Ayurveda, and more\\n8.4 Harnessing the Power of Energy Healing and Chakra Balancing\\n8.5 The Role of Spirituality and Mind-Body Connection\\n\\nConclusion (Word Count: 300)\\nIn this extensive guide, we have covered a wide range of topics related to health and wellness, equipping you with the knowledge and tools to embark on your personal journey towards optimal well-being. Remember, true health and wellness are not achieved overnight but require consistent effort, commitment, and self-care. By implementing the strategies outlined in this guide, you can unlock your full potential and live a vibrant, fulfilling life. So, embrace the power of health and wellness and start your transformative journey today!\\n\\nWord Count: 10,000"}], "model": "gpt-3.5-turbo", "temperature": 0.5, "max_tokens": 3000}' message='Post details' -https://api.openai.com:443 "POST /v1/chat/completions HTTP/1.1" 200 None -message='OpenAI API response' path=https://api.openai.com/v1/chat/completions processing_ms=334 request_id=d29d279c03c16a49192a468a6de16400 response_code=200 -message='Request to OpenAI API' method=post path=https://api.openai.com/v1/chat/completions -api_version=None data='{"messages": [{"role": "user", "content": "Disclaimer: The word count provided is an estimation and may vary slightly."}], "model": "gpt-3.5-turbo", "temperature": 0.5, "max_tokens": 3000}' message='Post details' -https://api.openai.com:443 "POST /v1/chat/completions HTTP/1.1" 200 None -message='OpenAI API response' path=https://api.openai.com/v1/chat/completions processing_ms=704 request_id=a3c58cd690f5bd4d88ac37d8cd64a540 response_code=200 diff --git a/flow.py b/flow.py index 05b361b5..fd7a02b2 100644 --- a/flow.py +++ b/flow.py @@ -3,9 +3,7 @@ from swarms.structs import Flow api_key = "" - -# Initialize the language model, -# This model can be swapped out with Anthropic, ETC, Huggingface Models like Mistral, ETC +# Initialize the language model, this model can be swapped out with Anthropic, ETC, Huggingface Models like Mistral, ETC llm = OpenAIChat( openai_api_key=api_key, temperature=0.5, @@ -13,8 +11,21 @@ llm = OpenAIChat( ) # Initialize the flow -flow = Flow(llm=llm, max_loops=5, dashboard=True) +flow = Flow(llm=llm, max_loops=5, dashboard=True,) + +flow = Flow( + llm=llm, + max_loops=5, + dashboard=True, + # stopping_condition=None, # You can define a stopping condition as needed. + # loop_interval=1, + # retry_attempts=3, + # retry_interval=1, + # interactive=False, # Set to 'True' for interactive mode. + # dynamic_temperature=False, # Set to 'True' for dynamic temperature handling. +) + out = flow.run("Generate a 10,000 word blog on health and wellness.") -print(out) +print(out) \ No newline at end of file diff --git a/groupchat.py b/groupchat.py index c004b266..6694d71f 100644 --- a/groupchat.py +++ b/groupchat.py @@ -1,24 +1,109 @@ -from swarms.structs import Flow +# from swarms.structs import Flow +# from swarms.models import OpenAIChat +# from swarms.swarms.groupchat import GroupChat +# from swarms.agents import SimpleAgent + +# api_key = "" + +# llm = OpenAIChat( +# openai_api_key=api_key, +# ) + +# agent1 = SimpleAgent("Captain Price", Flow(llm=llm, max_loops=4)) +# agent2 = SimpleAgent("John Mactavis", Flow(llm=llm, max_loops=4)) + +# # Create a groupchat with the 2 agents +# chat = GroupChat([agent1, agent2]) + +# # Assign duties to the agents +# chat.assign_duty(agent1.name, "Buy the groceries") +# chat.assign_duty(agent2.name, "Clean the house") + +# # Initate a chat +# response = chat.run("Captain Price", "Hello, how are you John?") +# print(response) + + from swarms.models import OpenAIChat -from swarms.swarms.groupchat import GroupChat -from swarms.agents import SimpleAgent +from swarms.structs import Flow +import random + +api_key = "" # Your API Key here + + +class GroupChat: + """ + GroupChat class that facilitates agent-to-agent communication using multiple instances of the Flow class. + """ + + def __init__(self, agents: list): + self.agents = {f"agent_{i}": agent for i, agent in enumerate(agents)} + self.message_log = [] + + def add_agent(self, agent: Flow): + agent_id = f"agent_{len(self.agents)}" + self.agents[agent_id] = agent + + def remove_agent(self, agent_id: str): + if agent_id in self.agents: + del self.agents[agent_id] + + def send_message(self, sender_id: str, recipient_id: str, message: str): + if sender_id not in self.agents or recipient_id not in self.agents: + raise ValueError("Invalid sender or recipient ID.") + formatted_message = f"{sender_id} to {recipient_id}: {message}" + self.message_log.append(formatted_message) + recipient_agent = self.agents[recipient_id] + recipient_agent.run(message) + + def broadcast_message(self, sender_id: str, message: str): + for agent_id, agent in self.agents.items(): + if agent_id != sender_id: + self.send_message(sender_id, agent_id, message) + + def get_message_log(self): + return self.message_log + + +class EnhancedGroupChatV2(GroupChat): + def __init__(self, agents: list): + super().__init__(agents) + + def multi_round_conversation(self, rounds: int = 5): + """ + Initiate a multi-round conversation between agents. + + Args: + rounds (int): The number of rounds of conversation. + """ + for _ in range(rounds): + # Randomly select a sender and recipient agent for the conversation + sender_id = random.choice(list(self.agents.keys())) + recipient_id = random.choice(list(self.agents.keys())) + while recipient_id == sender_id: # Ensure the recipient is not the sender + recipient_id = random.choice(list(self.agents.keys())) + + # Generate a message (for simplicity, a generic message is used) + message = f"Hello {recipient_id}, how are you today?" + self.send_message(sender_id, recipient_id, message) -api_key = "" +# Sample usage with EnhancedGroupChatV2 +# Initialize the language model llm = OpenAIChat( openai_api_key=api_key, + temperature=0.5, + max_tokens=3000, ) -agent1 = SimpleAgent("Captain Price", Flow(llm=llm, max_loops=4)) -agent2 = SimpleAgent("John Mactavis", Flow(llm=llm, max_loops=4)) +# Initialize two Flow agents +agent1 = Flow(llm=llm, max_loops=5, dashboard=True) +agent2 = Flow(llm=llm, max_loops=5, dashboard=True) -# Create a groupchat with the 2 agents -chat = GroupChat([agent1, agent2]) +# Create an enhanced group chat with the two agents +enhanced_group_chat_v2 = EnhancedGroupChatV2(agents=[agent1, agent2]) -# Assign duties to the agents -chat.assign_duty(agent1.name, "Buy the groceries") -chat.assign_duty(agent2.name, "Clean the house") +# Simulate multi-round agent to agent communication +enhanced_group_chat_v2.multi_round_conversation(rounds=5) -# Initate a chat -response = chat.run("Captain Price", "Hello, how are you John?") -print(response) +enhanced_group_chat_v2.get_message_log() # Get the conversation log diff --git a/mkdocs.yml b/mkdocs.yml index 8b948587..4f5134a7 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -118,6 +118,7 @@ nav: - PdfChunker: "swarms/chunkers/pdf_chunker.md" - Examples: - Overview: "examples/index.md" + - Flow: "examples/flow.md" - Agents: - OmniAgent: "examples/omni_agent.md" - Worker: diff --git a/stacked_worker.py b/stacked_worker.py deleted file mode 100644 index 2930c51b..00000000 --- a/stacked_worker.py +++ /dev/null @@ -1,134 +0,0 @@ -import os - -import interpreter - -from swarms.agents.hf_agents import HFAgent -from swarms.agents.omni_modal_agent import OmniModalAgent -from swarms.models import OpenAIChat -from swarms.tools.autogpt import tool -from swarms.workers import Worker -from swarms.prompts.task_assignment_prompt import task_planner_prompt - - -# Initialize API Key -api_key = "" - - -# Initialize the language model, -# This model can be swapped out with Anthropic, ETC, Huggingface Models like Mistral, ETC -llm = OpenAIChat( - openai_api_key=api_key, - temperature=0.5, - max_tokens=200, -) - - -# wrap a function with the tool decorator to make it a tool, then add docstrings for tool documentation -@tool -def hf_agent(task: str = None): - """ - An tool that uses an openai model to call and respond to a task by search for a model on huggingface - It first downloads the model then uses it. - - Rules: Don't call this model for simple tasks like generating a summary, only call this tool for multi modal tasks like generating images, videos, speech, etc - - """ - agent = HFAgent(model="text-davinci-003", api_key=api_key) - response = agent.run(task, text="¡Este es un API muy agradable!") - return response - - -@tool -def task_planner_worker_agent(task: str): - """ - Task planner tool that creates a plan for a given task. - Input: an objective to create a todo list for. Output: a todo list for that objective. - - """ - task = task_planner_prompt(task) - return llm(task) - - -# wrap a function with the tool decorator to make it a tool -@tool -def omni_agent(task: str = None): - """ - An tool that uses an openai Model to utilize and call huggingface models and guide them to perform a task. - - Rules: Don't call this model for simple tasks like generating a summary, only call this tool for multi modal tasks like generating images, videos, speech - The following tasks are what this tool should be used for: - - Tasks omni agent is good for: - -------------- - document-question-answering - image-captioning - image-question-answering - image-segmentation - speech-to-text - summarization - text-classification - text-question-answering - translation - huggingface-tools/text-to-image - huggingface-tools/text-to-video - text-to-speech - huggingface-tools/text-download - huggingface-tools/image-transformation - """ - agent = OmniModalAgent(llm) - response = agent.run(task) - return response - - -# Code Interpreter -@tool -def compile(task: str): - """ - Open Interpreter lets LLMs run code (Python, Javascript, Shell, and more) locally. - You can chat with Open Interpreter through a ChatGPT-like interface in your terminal - by running $ interpreter after installing. - - This provides a natural-language interface to your computer's general-purpose capabilities: - - Create and edit photos, videos, PDFs, etc. - Control a Chrome browser to perform research - Plot, clean, and analyze large datasets - ...etc. - ⚠️ Note: You'll be asked to approve code before it's run. - - Rules: Only use when given to generate code or an application of some kind - """ - task = interpreter.chat(task, return_messages=True) - interpreter.chat() - interpreter.reset(task) - - os.environ["INTERPRETER_CLI_AUTO_RUN"] = True - os.environ["INTERPRETER_CLI_FAST_MODE"] = True - os.environ["INTERPRETER_CLI_DEBUG"] = True - - -# Append tools to an list -# tools = [hf_agent, omni_agent, compile] -tools = [task_planner_worker_agent] - - -# Initialize a single Worker node with previously defined tools in addition to it's -# predefined tools -node = Worker( - llm=llm, - ai_name="Optimus Prime", - openai_api_key=api_key, - ai_role="Worker in a swarm", - external_tools=tools, - human_in_the_loop=False, - temperature=0.5, -) - -# Specify task -task = "Use the task planner to agent to create a plan to Locate 5 trending topics on healthy living, locate a website like NYTimes, and then generate an image of people doing those topics." - -# Run the node on the task -response = node.run(task) - -# Print the response -print(response) diff --git a/swarms/structs/flow.py b/swarms/structs/flow.py index bc11522b..8d7a09ed 100644 --- a/swarms/structs/flow.py +++ b/swarms/structs/flow.py @@ -3,7 +3,6 @@ TODO: - Add a retry mechanism - Add prompt injection letting the agent know it's in a flow, Flow prompt - Dynamic temperature handling -- Add """ @@ -14,15 +13,27 @@ from typing import Any, Callable, Dict, List, Optional, Tuple, Generator from termcolor import colored import inspect import random +from swarms.tools.tool import BaseTool # Constants FLOW_SYSTEM_PROMPT = """ -You are a language model operating within a flow class. +You are an autonomous agent granted autonomy from a Flow structure. Your role is to engage in multi-step conversations with your self or the user, generate long-form content like blogs, screenplays, or SOPs, and accomplish tasks. You can have internal dialogues with yourself or can interact with the user to aid in these complex tasks. Your responses should be coherent, contextually relevant, and tailored to the task at hand. + + +When you have finished the task, and you feel as if you are done: output a special token: +This will enable you to leave the flow loop. + +""" + + +DYNAMIC_STOP_PROMPT = """ +When you have finished the task, and you feel as if you are done: output a special token: +This will enable you to leave the flow loop. """ @@ -92,6 +103,7 @@ class Flow: retry_interval: int = 1, interactive: bool = False, dashboard: bool = False, + tools: List[BaseTool] = None, dynamic_temperature: bool = False, **kwargs: Any, ): @@ -109,6 +121,7 @@ class Flow: self.interactive = interactive self.dashboard = dashboard self.dynamic_temperature = dynamic_temperature + self.tools = tools def provide_feedback(self, feedback: str) -> None: """Allow users to provide feedback on the responses.""" @@ -196,7 +209,7 @@ class Flow: print(dashboard) - def run(self, task: str): + def run(self, task: str, **kwargs): """ Run the autonomous agent loop @@ -221,7 +234,7 @@ class Flow: for i in range(self.max_loops): print(colored(f"\nLoop {i+1} of {self.max_loops}", "blue")) print("\n") - if self._check_stopping_condition(response): + if self._check_stopping_condition(response) or parse_done_token(response): break # Adjust temperature, comment if no work @@ -231,10 +244,18 @@ class Flow: attempt = 0 while attempt < self.retry_attempts: try: - response = self.llm(response) + response = self.llm( + f""" + SYSTEM_PROMPT: + {FLOW_SYSTEM_PROMPT} + + + History: {response} + + """, **kwargs + ) # print(f"Next query: {response}") # break - if self.interactive: print(f"AI: {response}") history.append(f"AI: {response}") diff --git a/swarms/tools/developer.py b/swarms/tools/developer.py deleted file mode 100644 index 04e4b30a..00000000 --- a/swarms/tools/developer.py +++ /dev/null @@ -1,925 +0,0 @@ -import os -import re -import signal -import subprocess -import time -from datetime import datetime -from pathlib import Path -from typing import Callable, Dict, List, Literal, Optional, Tuple, Union - -from langchain.tools import tool -from ptrace.debugger import ( - NewProcessEvent, - ProcessExecution, - ProcessExit, - ProcessSignal, - PtraceDebugger, - PtraceProcess, -) -from ptrace.func_call import FunctionCallOptions -from ptrace.syscall import PtraceSyscall -from ptrace.tools import signal_to_exitcode - -from swarms.tools.base import BaseToolSet, SessionGetter, ToolScope, tool -from swarms.utils.logger import logger -from swarms.utils.main import ANSI, Color, Style # test - -# helpers -PipeType = Union[Literal["stdout"], Literal["stderr"]] - - -def verify(func): - def wrapper(*args, **kwargs): - try: - filepath = args[0].filepath - except AttributeError: - raise Exception("This tool doesn't have filepath. Please check your code.") - if not str(Path(filepath).resolve()).startswith(str(Path().resolve())): - return "You can't access file outside of playground." - return func(*args, **kwargs) - - return wrapper - - -class SyscallTimeoutException(Exception): - def __init__(self, pid: int, *args) -> None: - super().__init__(f"deadline exceeded while waiting syscall for {pid}", *args) - - -class SyscallTracer: - def __init__(self, pid: int): - self.debugger: PtraceDebugger = PtraceDebugger() - self.pid: int = pid - self.process: PtraceProcess = None - - def is_waiting(self, syscall: PtraceSyscall) -> bool: - if syscall.name.startswith("wait"): - return True - return False - - def attach(self): - self.process = self.debugger.addProcess(self.pid, False) - - def detach(self): - self.process.detach() - self.debugger.quit() - - def set_timer(self, timeout: int): - def handler(signum, frame): - raise SyscallTimeoutException(self.process.pid) - - signal.signal(signal.SIGALRM, handler) - signal.alarm(timeout) - - def reset_timer(self): - signal.alarm(0) - - def wait_syscall_with_timeout(self, timeout: int): - self.set_timer(timeout) - self.process.waitSyscall() - self.reset_timer() - - def wait_until_stop_or_exit(self) -> Tuple[Optional[int], str]: - self.process.syscall() - exitcode = None - reason = "" - while True: - if not self.debugger: - break - - try: - self.wait_syscall_with_timeout(30) - except ProcessExit as event: - if event.exitcode is not None: - exitcode = event.exitcode - continue - except ProcessSignal as event: - event.process.syscall(event.signum) - exitcode = signal_to_exitcode(event.signum) - reason = event.reason - continue - except NewProcessEvent: - continue - except ProcessExecution: - continue - except Exception as e: - reason = str(e) - break - - syscall = self.process.syscall_state.event( - FunctionCallOptions( - write_types=False, - write_argname=False, - string_max_length=300, - replace_socketcall=True, - write_address=False, - max_array_count=20, - ) - ) - - self.process.syscall() - - if syscall is None: - continue - - if syscall.result: - continue - - self.reset_timer() - - return exitcode, reason - - -class StdoutTracer: - def __init__( - self, - process: subprocess.Popen, - timeout: int = 30, - interval: int = 0.1, - on_output: Callable[[PipeType, str], None] = lambda: None, - ): - self.process: subprocess.Popen = process - self.timeout: int = timeout - self.interval: int = interval - self.last_output: datetime = None - self.on_output: Callable[[PipeType, str], None] = on_output - - def nonblock(self): - os.set_blocking(self.process.stdout.fileno(), False) - os.set_blocking(self.process.stderr.fileno(), False) - - def get_output(self, pipe: PipeType) -> str: - output = None - if pipe == "stdout": - output = self.process.stdout.read() - elif pipe == "stderr": - output = self.process.stderr.read() - - if output: - decoded = output.decode() - self.on_output(pipe, decoded) - self.last_output = datetime.now() - return decoded - return "" - - def last_output_passed(self, seconds: int) -> bool: - return (datetime.now() - self.last_output).seconds > seconds - - def wait_until_stop_or_exit(self) -> Tuple[Optional[int], str]: - self.nonblock() - self.last_output = datetime.now() - output = "" - exitcode = None - while True: - new_stdout = self.get_output("stdout") - if new_stdout: - output += new_stdout - - new_stderr = self.get_output("stderr") - if new_stderr: - output += new_stderr - - if self.process.poll() is not None: - exitcode = self.process.poll() - break - - if self.last_output_passed(self.timeout): - self.process.kill() - break - - time.sleep(self.interval) - - return (exitcode, output) - - -class Terminal(BaseToolSet): - def __init__(self): - self.sessions: Dict[str, List[SyscallTracer]] = {} - - @tool( - name="Terminal", - description="Executes commands in a terminal." - "If linux errno occurs, we have to solve the problem with the terminal. " - "Input must be one valid command. " - "Output will be any output from running that command.", - scope=ToolScope.SESSION, - ) - def execute(self, commands: str, get_session: SessionGetter) -> str: - session, _ = get_session() - - try: - process = subprocess.Popen( - commands, - shell=True, - stdout=subprocess.PIPE, - stderr=subprocess.PIPE, - ) - logger.info(ANSI("Realtime Terminal Output").to(Color.magenta()) + ": ") - - output = "" - tracer = StdoutTracer( - process, - on_output=lambda p, o: logger.info( - ANSI(p).to(Style.dim()) + " " + o.strip("\n") - ), - ) - exitcode, output = tracer.wait_until_stop_or_exit() - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed Terminal, Input Commands: {commands} " - f"Output Answer: {output}" - ) - return output - - -############# - - -@tool( - name="Terminal", - description="Executes commands in a terminal." - "If linux errno occurs, we have to solve the problem with the terminal. " - "Input must be one valid command. " - "Output will be any output from running that command.", - scope=ToolScope.SESSION, -) -def terminal_execute(self, commands: str, get_session: SessionGetter) -> str: - session, _ = get_session() - - try: - process = subprocess.Popen( - commands, - shell=True, - stdout=subprocess.PIPE, - stderr=subprocess.PIPE, - ) - logger.info(ANSI("Realtime Terminal Output").to(Color.magenta()) + ": ") - - output = "" - tracer = StdoutTracer( - process, - on_output=lambda p, o: logger.info( - ANSI(p).to(Style.dim()) + " " + o.strip("\n") - ), - ) - exitcode, output = tracer.wait_until_stop_or_exit() - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed Terminal, Input Commands: {commands} " f"Output Answer: {output}" - ) - return output - - -""" -write protocol: - - - -""" - - -class WriteCommand: - separator = "\n" - - def __init__(self, filepath: str, content: int): - self.filepath: str = filepath - self.content: str = content - self.mode: str = "w" - - def with_mode(self, mode: str) -> "WriteCommand": - self.mode = mode - return self - - @verify - def execute(self) -> str: - dir_path = os.path.dirname(self.filepath) - if dir_path: - os.makedirs(dir_path, exist_ok=True) - with open(self.filepath, self.mode) as f: - f.write(self.content) - return self.content - - @staticmethod - def from_str(command: str) -> "WriteCommand": - filepath = command.split(WriteCommand.separator)[0] - return WriteCommand(filepath, command[len(filepath) + 1 :]) - - -class CodeWriter: - @staticmethod - def write(command: str) -> str: - return WriteCommand.from_str(command).with_mode("w").execute() - - @staticmethod - def append(command: str) -> str: - return WriteCommand.from_str(command).with_mode("a").execute() - - -""" -read protocol: - -|- -""" - - -class Line: - def __init__(self, content: str, line_number: int, depth: int): - self.__content: str = content - self.__line_number: int = line_number - self.__depth: int = depth - self.__children: List[Line] = [] - - def get_content(self) -> str: - return self.__content - - def get_depth(self) -> int: - return self.__depth - - def append_child(self, child: "Line") -> None: - self.__children.append(child) - - def find_by_lte_depth(self, depth: int) -> List["Line"]: - if self.__depth > depth: - return [] - - lines: List[Line] = [self] - for child in self.__children: - lines += child.find_by_lte_depth(depth) - return lines - - def find_by_content(self, content: str) -> List["Line"]: - if content in self.__content: - return [self] - - lines: List[Line] = [] - for child in self.__children: - lines += child.find_by_content(content) - return lines - - def find_last_lines(self) -> List["Line"]: - if len(self.__children) == 0: - return [self] - else: - return [self, *self.__children[-1].find_last_lines()] - - def print(self, depth: int = 0) -> None: - print(f"{' ' * depth}{self}", end="") - for child in self.__children: - child.print(depth + 1) - - def __repr__(self): - return f"{self.__line_number}: {self.__content}" - - -class CodeTree: - def __init__(self): - self.root: Line = Line("\n", -1, -1) - - def append(self, content: str, line_number: int) -> None: - last_lines: List[Line] = self.root.find_last_lines() - new_leading_spaces: int = self.__get_leading_spaces(content) - - previous_line: Line = self.root - previous_leading_spaces: int = -1 - for line in last_lines: - leading_spaces = self.__get_leading_spaces(line.get_content()) - if ( - previous_leading_spaces < new_leading_spaces - and new_leading_spaces <= leading_spaces - ): - break - previous_line, previous_leading_spaces = line, leading_spaces - - new_line_depth: int = previous_line.get_depth() + 1 - previous_line.append_child(Line(content, line_number, new_line_depth)) - - def find_from_root(self, depth: int) -> List[Line]: - return self.root.find_by_lte_depth(depth) - - def find_from_parent(self, depth: int, parent_content: str) -> List[Line]: - lines: List[Line] = self.root.find_by_content(parent_content) - if len(lines) == 0: - return [] - parent = lines[0] - return parent.find_by_lte_depth(depth + parent.get_depth()) - - def print(self): - print("Code Tree:") - print("=================================") - self.root.print() - print("=================================") - - def __get_leading_spaces(self, content: str) -> int: - return len(content) - len(content.lstrip()) - - -class ReadCommand: - separator = "|" - - def __init__(self, filepath: str, start: int, end: int): - self.filepath: str = filepath - self.start: int = start - self.end: int = end - - @verify - def execute(self) -> str: - with open(self.filepath, "r") as f: - code = f.readlines() - - if self.start == self.end: - code = code[self.start - 1] - else: - code = "".join(code[self.start - 1 : self.end]) - return code - - @staticmethod - def from_str(command: str) -> "ReadCommand": - filepath, line = command.split(ReadCommand.separator) - start, end = line.split("-") - return ReadCommand(filepath, int(start), int(end)) - - -class SummaryCommand: - separator = "|" - - def __init__(self, filepath: str, depth: int, parent_content: Optional[str] = None): - self.filepath: str = filepath - self.depth: int = depth - self.parent_content: Optional[str] = parent_content - - @verify - def execute(self) -> str: - with open(self.filepath, "r") as f: - code = f.readlines() - - code_tree = CodeTree() - for i, line in enumerate(code): - if line.strip() != "": - code_tree.append(line, i + 1) - - if self.parent_content is None: - lines = code_tree.find_from_root(self.depth) - else: - lines = code_tree.find_from_parent(self.depth, self.parent_content) - return "".join([str(line) for line in lines]) - - @staticmethod - def from_str(command: str) -> "SummaryCommand": - command_list: List[str] = command.split(SummaryCommand.separator) - filepath: str = command_list[0] - depth: int = int(command_list[1]) - parent_content: str | None = command_list[2] if len(command_list) == 3 else None - return SummaryCommand( - filepath=filepath, depth=depth, parent_content=parent_content - ) - - -class CodeReader: - @staticmethod - def read(command: str) -> str: - return ReadCommand.from_str(command).execute() - - @staticmethod - def summary(command: str) -> str: - return SummaryCommand.from_str(command).execute() - - -""" -patch protocol: - -|,|,| ----~~~+++===+++~~~--- -|,|,| ----~~~+++===+++~~~--- -... ----~~~+++===+++~~~--- - -let say original code is: -``` -import requests - -def crawl_news(keyword): - url = f"https://www.google.com/search?q={keyword}+news" - response = requests.get(url) - - news = [] - for result in response: - news.append(result.text) - - return news -``` - -and we want to change it to: -``` -import requests -from bs4 import BeautifulSoup - -def crawl_news(keyword): - url = f"https://www.google.com/search?q={keyword}+news" - html = requests.get(url).text - soup = BeautifulSoup(html, "html.parser") - news_results = soup.find_all("div", class_="BNeawe vvjwJb AP7Wnd") - - news_titles = [] - for result in news_results: - news_titles.append(result.text) - - return news_titles -``` - -then the command will be: -test.py|2,1|2,1|from bs4 import BeautifulSoup - ----~~~+++===+++~~~--- -test.py|5,5|5,33|html = requests.get(url).text - soup = BeautifulSoup(html, "html.parser") - news_results = soup.find_all("div", class_="BNeawe vvjwJb AP7Wnd") ----~~~+++===+++~~~--- -test.py|7,5|9,13|news_titles = [] - for result in news_results: - news_titles ----~~~+++===+++~~~--- -test.py|11,16|11,16|_titles -""" - - -class Position: - separator = "," - - def __init__(self, line: int, col: int): - self.line: int = line - self.col: int = col - - def __str__(self): - return f"(Ln {self.line}, Col {self.col})" - - @staticmethod - def from_str(pos: str) -> "Position": - line, col = pos.split(Position.separator) - return Position(int(line) - 1, int(col) - 1) - - -class PatchCommand: - separator = "|" - - def __init__(self, filepath: str, start: Position, end: Position, content: str): - self.filepath: str = filepath - self.start: Position = start - self.end: Position = end - self.content: str = content - - def read_lines(self) -> list[str]: - with open(self.filepath, "r") as f: - lines = f.readlines() - return lines - - def write_lines(self, lines: list[str]) -> int: - with open(self.filepath, "w") as f: - f.writelines(lines) - return sum([len(line) for line in lines]) - - @verify - def execute(self) -> Tuple[int, int]: - lines = self.read_lines() - before = sum([len(line) for line in lines]) - - lines[self.start.line] = ( - lines[self.start.line][: self.start.col] - + self.content - + lines[self.end.line][self.end.col :] - ) - lines = lines[: self.start.line + 1] + lines[self.end.line + 1 :] - - after = self.write_lines(lines) - - written = len(self.content) - deleted = before - after + written - - return written, deleted - - @staticmethod - def from_str(command: str) -> "PatchCommand": - match = re.search( - r"(.*)\|([0-9]*),([0-9]*)\|([0-9]*),([0-9]*)(\||\n)(.*)", - command, - re.DOTALL, - ) - filepath = match.group(1) - start_line = match.group(2) - start_col = match.group(3) - end_line = match.group(4) - end_col = match.group(5) - content = match.group(7) - return PatchCommand( - filepath, - Position.from_str(f"{start_line},{start_col}"), - Position.from_str(f"{end_line},{end_col}"), - content, - ) - - -class CodePatcher: - separator = "\n---~~~+++===+++~~~---\n" - - @staticmethod - def sort_commands(commands: list[PatchCommand]) -> list[PatchCommand]: - return sorted(commands, key=lambda c: c.start.line, reverse=True) - - @staticmethod - def patch(bulk_command: str) -> Tuple[int, int]: - commands = [ - PatchCommand.from_str(command) - for command in bulk_command.split(CodePatcher.separator) - if command != "" - ] - commands = CodePatcher.sort_commands(commands) - - written, deleted = 0, 0 - for command in commands: - if command: - w, d = command.execute() - written += w - deleted += d - return written, deleted - - -class CodeEditor(BaseToolSet): - @tool( - name="CodeEditor.READ", - description="Read and understand code. " - "Input should be filename and line number group. ex. test.py|1-10 " - "and the output will be code. ", - ) - def read(self, inputs: str) -> str: - try: - output = CodeReader.read(inputs) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.READ, Input Commands: {inputs} " - f"Output Answer: {output}" - ) - return output - - @tool( - name="CodeEditor.SUMMARY", - description="Summary code. " - "Read the code structured into a tree. " - "If you set specific line, it will show the code from the specific line. " - "Input should be filename, depth, and specific line if you want. ex. test.py|2 or test.py|3|print('hello world') " - "and the output will be list of (line number: code). ", - ) - def summary(self, inputs: str) -> str: - try: - output = CodeReader.summary(inputs) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.SUMMARY, Input Commands: {inputs} " - f"Output Answer: {output}" - ) - return output - - @tool( - name="CodeEditor.APPEND", - description="Append code to the existing file. " - "If the code is completed, use the Terminal tool to execute it, if not, append the code through the this tool. " - "Input should be filename and code to append. " - "Input code must be the code that should be appended, NOT whole code. " - "ex. test.py\nprint('hello world')\n " - "and the output will be last 3 lines.", - ) - def append(self, inputs: str) -> str: - try: - code = CodeWriter.append(inputs) - output = "Last 3 line was:\n" + "\n".join(code.split("\n")[-3:]) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.APPEND, Input: {inputs} " - f"Output Answer: {output}" - ) - return output - - @tool( - name="CodeEditor.WRITE", - description="Write code to create a new tool. " - "If the code is completed, use the Terminal tool to execute it, if not, append the code through the CodeEditor.APPEND tool. " - "Input should be formatted like: " - "\n\n\n" - "Here is an example: " - "test.py\nmessage = 'hello world'\nprint(message)\n" - "\n" - "The output will be last 3 lines you wrote.", - ) - def write(self, inputs: str) -> str: - try: - code = CodeWriter.write(inputs.lstrip()) - output = "Last 3 line was:\n" + "\n".join(code.split("\n")[-3:]) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.WRITE, Input: {inputs} " f"Output Answer: {output}" - ) - return output - - @tool( - name="CodeEditor.PATCH", - description="Patch the code to correct the error if an error occurs or to improve it. " - "Input is a list of patches. The patch is separated by {seperator}. ".format( - seperator=CodePatcher.separator.replace("\n", "\\n") - ) - + "Each patch has to be formatted like below.\n" - "|,|,|" - "Here is an example. If the original code is:\n" - "print('hello world')\n" - "and you want to change it to:\n" - "print('hi corca')\n" - "then the patch should be:\n" - "test.py|1,8|1,19|hi corca\n" - "Code between start and end will be replaced with new_code. " - "The output will be written/deleted bytes or error message. ", - ) - def patch(self, patches: str) -> str: - try: - w, d = CodePatcher.patch(patches) - output = f"successfully wrote {w}, deleted {d}" - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.PATCH, Input Patch: {patches} " - f"Output Answer: {output}" - ) - return output - - @tool( - name="CodeEditor.DELETE", - description="Delete code in file for a new start. " - "Input should be filename." - "ex. test.py " - "Output will be success or error message.", - ) - def delete(self, inputs: str, filepath: str) -> str: - try: - with open(filepath, "w") as f: - f.write("") - output = "success" - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.DELETE, Input filename: {inputs} " - f"Output Answer: {output}" - ) - return output - - -# ---------------- end - - -@tool( - name="CodeEditor.READ", - description="Read and understand code. " - "Input should be filename and line number group. ex. test.py|1-10 " - "and the output will be code. ", -) -def code_editor_read(self, inputs: str) -> str: - try: - output = CodeReader.read(inputs) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.READ, Input Commands: {inputs} " - f"Output Answer: {output}" - ) - return output - - -@tool( - name="CodeEditor.SUMMARY", - description="Summary code. " - "Read the code structured into a tree. " - "If you set specific line, it will show the code from the specific line. " - "Input should be filename, depth, and specific line if you want. ex. test.py|2 or test.py|3|print('hello world') " - "and the output will be list of (line number: code). ", -) -def code_editor_summary(self, inputs: str) -> str: - try: - output = CodeReader.summary(inputs) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.SUMMARY, Input Commands: {inputs} " - f"Output Answer: {output}" - ) - return output - - -@tool( - name="CodeEditor.APPEND", - description="Append code to the existing file. " - "If the code is completed, use the Terminal tool to execute it, if not, append the code through the this tool. " - "Input should be filename and code to append. " - "Input code must be the code that should be appended, NOT whole code. " - "ex. test.py\nprint('hello world')\n " - "and the output will be last 3 lines.", -) -def code_editor_append(self, inputs: str) -> str: - try: - code = CodeWriter.append(inputs) - output = "Last 3 line was:\n" + "\n".join(code.split("\n")[-3:]) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.APPEND, Input: {inputs} " f"Output Answer: {output}" - ) - return output - - -@tool( - name="CodeEditor.WRITE", - description="Write code to create a new tool. " - "If the code is completed, use the Terminal tool to execute it, if not, append the code through the CodeEditor.APPEND tool. " - "Input should be formatted like: " - "\n\n\n" - "Here is an example: " - "test.py\nmessage = 'hello world'\nprint(message)\n" - "\n" - "The output will be last 3 lines you wrote.", -) -def code_editor_write(self, inputs: str) -> str: - try: - code = CodeWriter.write(inputs.lstrip()) - output = "Last 3 line was:\n" + "\n".join(code.split("\n")[-3:]) - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.WRITE, Input: {inputs} " f"Output Answer: {output}" - ) - return output - - -@tool( - name="CodeEditor.PATCH", - description="Patch the code to correct the error if an error occurs or to improve it. " - "Input is a list of patches. The patch is separated by {seperator}. ".format( - seperator=CodePatcher.separator.replace("\n", "\\n") - ) - + "Each patch has to be formatted like below.\n" - "|,|,|" - "Here is an example. If the original code is:\n" - "print('hello world')\n" - "and you want to change it to:\n" - "print('hi corca')\n" - "then the patch should be:\n" - "test.py|1,8|1,19|hi corca\n" - "Code between start and end will be replaced with new_code. " - "The output will be written/deleted bytes or error message. ", -) -def code_editor_patch(self, patches: str) -> str: - try: - w, d = CodePatcher.patch(patches) - output = f"successfully wrote {w}, deleted {d}" - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.PATCH, Input Patch: {patches} " - f"Output Answer: {output}" - ) - return output - - -@tool( - name="CodeEditor.DELETE", - description="Delete code in file for a new start. " - "Input should be filename." - "ex. test.py " - "Output will be success or error message.", -) -def code_editor_delete(self, inputs: str, filepath: str) -> str: - try: - with open(filepath, "w") as f: - f.write("") - output = "success" - except Exception as e: - output = str(e) - - logger.debug( - f"\nProcessed CodeEditor.DELETE, Input filename: {inputs} " - f"Output Answer: {output}" - ) - return output diff --git a/swarms/tools/file_mangagement.py b/swarms/tools/file_mangagement.py deleted file mode 100644 index b9c2041a..00000000 --- a/swarms/tools/file_mangagement.py +++ /dev/null @@ -1,17 +0,0 @@ -from langchain.agents.agent_toolkits import FileManagementToolkit -from tempfile import TemporaryDirectory - -# We'll make a temporary directory to avoid clutter -working_directory = TemporaryDirectory() - -toolkit = FileManagementToolkit( - root_dir=str(working_directory.name) -) # If you don't provide a root_dir, operations will default to the current working directory -toolkit.get_tools() - -file_management_tools = FileManagementToolkit( - root_dir=str(working_directory.name), - selected_tools=["read_file", "write_file", "list_directory"], -).get_tools() - -read_tool, write_tool, list_tool = file_management_tools