History
How it works
The History is a core component in the Autoflow system, responsible for managing the conversation history between users and the AI assistant. This information is used to provide context-aware and personalized responses. The history is designed to be efficient, scalable, and flexible to handle a variety of use cases and conversation patterns.
Key Features
- Conversation Management: The
Historyclass manages the flow of conversations, keeping track of the messages exchanged between the user and the assistant. It ensures that previous interactions are accessible for context retrieval. - Message Storage: The
Historycomponent is responsible for storing message data, including user inputs and assistant responses, along with timestamps and other relevant metadata. - Context Retrieval: The
Historyclass enables the efficient retrieval of past messages, allowing the AI assistant to understand the current conversation in relation to previous interactions.
Implementation Details
The History class utilizes a data structure to store the conversation history, with each entry representing a message. The data structure is designed to be efficient for both storage and retrieval operations. The specific data structure used might vary depending on the implementation and the complexity of the conversation history management.
Data Structure
The History data structure can be implemented using a variety of approaches, such as:
- List: A simple list data structure can be used to store messages in the order they were received.
- Queue: A queue can be used to maintain the order of messages while also providing efficient access to the oldest messages.
- Stack: A stack can be used if the system prioritizes access to the most recent messages.
- Hash Table: A hash table can be used for quick retrieval of messages based on specific keys, such as timestamps or message IDs.
Example
The following code snippet demonstrates a simple example of how the History class can be used to manage the conversation history.
class History:
def __init__(self):
self.messages = []
def add_message(self, message):
self.messages.append(message)
def get_messages(self):
return self.messages
# Example usage
history = History()
history.add_message("User: Hello!")
history.add_message("Assistant: Hi there!")
print(history.get_messages())
This example demonstrates how the History class can be used to store and retrieve messages from the conversation history.
Options and Examples
- Conversation Window: This option allows the
Historyclass to manage the number of recent messages stored. The user can specify the number of messages they want to keep in the history.
class History:
def __init__(self, max_messages=10):
self.messages = []
self.max_messages = max_messages
def add_message(self, message):
self.messages.append(message)
if len(self.messages) > self.max_messages:
self.messages = self.messages[-self.max_messages:]
def get_messages(self):
return self.messages
# Example usage
history = History(max_messages=5)
history.add_message("User: Hello!")
history.add_message("Assistant: Hi there!")
history.add_message("User: How are you?")
history.add_message("Assistant: I am doing well, thank you!")
print(history.get_messages())
This code demonstrates how the History class can manage the conversation window by limiting the number of messages stored.
- Message Filtering: This option allows the
Historyclass to filter the messages stored based on specific criteria, such as message type or content. This can be useful for optimizing the storage and retrieval process.
class History:
def __init__(self):
self.messages = []
def add_message(self, message):
if message.type == "user":
self.messages.append(message)
def get_messages(self):
return self.messages
# Example usage
history = History()
history.add_message("User: Hello!")
history.add_message("Assistant: Hi there!")
history.add_message("System: The system is ready.")
print(history.get_messages())
This code demonstrates how the History class can filter messages by message type. Only messages from the user are stored in the history.
- Contextual Retrieval: The
Historyclass can implement methods to efficiently retrieve relevant messages from the conversation history based on the current context. This can involve using keywords, timestamps, or other metadata to identify relevant messages.
class History:
def __init__(self):
self.messages = []
def add_message(self, message):
self.messages.append(message)
def get_context(self, keyword):
context = []
for message in reversed(self.messages):
if keyword in message.text:
context.append(message)
return context
# Example usage
history = History()
history.add_message("User: What is the weather like today?")
history.add_message("Assistant: The weather is sunny today.")
history.add_message("User: What is the temperature?")
print(history.get_context("weather"))
This code demonstrates how the History class can retrieve context-related messages from the history.
Conclusion
The History class is a fundamental component of the Autoflow system, enabling context-aware and personalized conversations. Its efficient design and flexible features allow for a wide range of applications and customizations. This document provides a basic overview of the History component and its key functionalities. Further details regarding specific implementation and optimizations can be found within the Autoflow codebase.
