Based on the the multi-agent concept created by Llama Index.
This notebook presents an advanced, modular multi-agent conversational system designed to navigate complex task trees within a financial system. The system leverages multiple specialized agents, each responsible for handling distinct tasks such as stock lookup, user authentication, account balance inquiries, money transfers, and overall orchestration of the conversation flow. The architecture is built to be highly customizable, allowing for the seamless integration of new agents and functionalities as needed.
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Stock Lookup Agent:
- Handles requests for stock price information.
- Can assist users in searching for stock symbols based on company names and retrieving current trading prices.
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Authentication Agent:
- Manages user login processes by validating credentials and storing session tokens.
- Ensures that sensitive operations, such as balance checks or money transfers, are only accessible to authenticated users.
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Account Balance Agent:
- Provides users with information on their account balances.
- Requires authentication to ensure security and privacy.
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Money Transfer Agent:
- Facilitates secure transfers of funds between user accounts.
- Verifies sufficient balance and user authentication before proceeding with transactions.
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Orchestration Agent:
- Acts as the central decision-making unit.
- Determines which agent should handle the next step in the conversation based on the current user state and input.
The system is designed to be highly flexible, allowing for extensive customization and expansion:
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Adding New Agents:
- The architecture supports the easy addition of new agents. Developers can define new agent behaviors, tools, and system prompts, then integrate them into the orchestration logic.
- Example: You might add an agent for handling investment portfolio analysis, with tools for calculating portfolio performance, assessing risk, and providing recommendations.
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Customization of Agent Behaviors:
- Each agent's behavior can be customized through the use of configurable parameters. For instance, you can adjust the stock lookup agent to fetch real-time data from different financial APIs, or modify the authentication agent to use multi-factor authentication.
- Configuration UI: Google Colab’s inline UI elements can be used to create interactive forms that allow users to customize agent parameters dynamically before running the notebook.
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Interactive Configuration:
- Users can define and modify agent labels, task descriptions, tool parameters, and even the system prompt directly from the Colab interface, without altering the core codebase.
- This feature is particularly useful for experimenting with different configurations or adapting the system to different financial environments.
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Error Handling and Graceful Exit:
- The system is built with robust error handling to manage unexpected inputs and user interruptions.
- For example, the main loop includes a mechanism to gracefully handle user-initiated exits (e.g., via
Ctrl+C), ensuring that the notebook exits cleanly without displaying unnecessary error messages.
- User Interaction: The user initiates the conversation by selecting an agent or inputting a query. The orchestration agent interprets the input and routes the request to the appropriate agent.
- Task Execution: The selected agent processes the request, whether it’s looking up a stock price, checking an account balance, or transferring funds.
- State Management: The system maintains the current state of the user, including session details and task progress, ensuring that each step of the conversation is informed by the user’s previous actions.
- Dynamic Decision-Making: Based on the outcomes of each interaction, the orchestration agent decides the next step, keeping the conversation focused and efficient.
This notebook is a powerful tool for building and managing a multi-agent conversational system tailored to complex financial tasks. With its modular design, customizable features, and robust handling of interactions, it offers a flexible framework for creating sophisticated AI-driven financial assistants. Whether you’re managing simple inquiries or navigating intricate financial workflows, this system provides the tools and structure needed to develop a responsive and intelligent conversational experience.