wehub-resource-sync
116 lines
4.4 KiB
Markdown
116 lines
4.4 KiB
Markdown
# Loan Approval Conversational Agent with Parlant
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A compliance-driven conversational AI agent built with [Parlant](https://github.com/emcie-co/parlant) that guides customers through a structured loan approval process.
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## Overview
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This project demonstrates a financial services chatbot that helps customers navigate the loan application process. The agent uses a state-based journey to guide users through eligibility checks, document collection, and approval workflows while maintaining compliance with financial service standards using deterministic and rule-based behavioral patterns.
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## Installation
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1. **Prerequisites**:
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- Python 3.12 +
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2. **Install dependencies:**
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First, install `uv` and set up the environment:
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```bash
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# MacOS/Linux
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curl -LsSf https://astral.sh/uv/install.sh | sh
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# Windows
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powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
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```
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Install dependencies:
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```bash
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# Create a new directory for our project
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uv init research-assistant
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cd research-assistant
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# Create virtual environment and activate it
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uv venv
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source .venv/bin/activate # MacOS/Linux
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.venv\Scripts\activate # Windows
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# Install dependencies
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uv sync
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```
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3. Set up environment variables:
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```bash
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# Create a .env file with your configuration
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cp .env.example .env
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```
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## Usage
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Run the main application:
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```bash
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uv run loan_approval.py
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```
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This will start the Parlant server locally on port 8800 with the loan approval agent configured and ready to handle customer interactions.
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## Loan Approval Flow
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The agent follows a structured conversational journey for processing loan applications:
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```mermaid
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stateDiagram-v2
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N0: Determine the type of loan user is interested in
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N1: Ask them to provide income and loan related details
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N2: Use the tool check_eligibility
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N3: Inform them that they are not qualified for the loan and ask them if they are interested in other types of loans
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N4: Ask them to provide their tax returns and recent pay stubs
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N5: Use the tool process_documents
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N6: Ask them to use our Online Portal to submit their documents, or contact a Loan Specialist at our Customer Care Phone Number for assistance
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N7: Inform them that their application has been approved and a Loan Specialist will review their information and contact them shortly
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[*] --> N0
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N0 --> N1: The customer specified the type of loan
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N1 --> N2
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N2 --> N3: The customer is not eligible for the loan
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N2 --> N4: The customer is eligible for the loan
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N4 --> N5
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N5 --> N6: The documents are either invalid, missing or not uploaded correctly
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N5 --> N7: Documents are successfully uploaded
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N7 --> [*]
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N6 --> [*]
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N3 --> [*]
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style N0 fill:#006e53,stroke:#ffffff,stroke-width:2px,color:#ffffff
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style N1 fill:#006e53,stroke:#ffffff,stroke-width:2px,color:#ffffff
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style N2 fill:#ffeeaa,stroke:#ffeeaa,stroke-width:2px,color:#dd6600
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style N3 fill:#006e53,stroke:#ffffff,stroke-width:2px,color:#ffffff
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style N4 fill:#006e53,stroke:#ffffff,stroke-width:2px,color:#ffffff
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style N5 fill:#ffeeaa,stroke:#ffeeaa,stroke-width:2px,color:#dd6600
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style N6 fill:#006e53,stroke:#ffffff,stroke-width:2px,color:#ffffff
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style N7 fill:#006e53,stroke:#ffffff,stroke-width:2px,color:#ffffff
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```
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## Key Components
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### Tools
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- **`check_eligibility`**: Validates customer creditworthiness based on credit score, income, and loan amount
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- **`process_documents`**: Simulates document validation for tax returns and pay stubs
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- **`get_current_rates`**: Fetches current interest rates by location
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- **`get_loan_types`**: Returns available loan products
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### Agent Capabilities
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- Domain-specific terminology understanding
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- Compliance guidelines for financial advice limitations
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- Structured conversation flow management
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- Human handoff protocols
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## 📬 Stay Updated with Our Newsletter!
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**Get a FREE Data Science eBook** 📖 with 150+ essential lessons in Data Science when you subscribe to our newsletter! Stay in the loop with the latest tutorials, insights, and exclusive resources. [Subscribe now!](https://join.dailydoseofds.com)
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[](https://join.dailydoseofds.com)
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---
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## Contribution
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Contributions are welcome! Please fork the repository and submit a pull request with your improvements.
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