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Internship AI Agent Portfolio

This repository contains three sanitized, runnable demonstrations developed from internship prototypes for enterprise operations. The public version preserves the architecture, state logic, tests, and local setup while removing employer-specific infrastructure, customer material, internal documentation, deployment details, identifiers, and credentials.

Projects

Project Problem Main components
legal-review-bot Classify contracts and produce checklist-based risk reviews Flask, OpenAI-compatible LLM, embeddings, SQLite, Lark/Feishu output
financial-reporting-bot Normalize expense records and generate management-report summaries Flask, CSV/XLSX parsing, LLM classification, SQLite, reporting API
customer-service-bot Answer product questions after a human-response window and escalate high-risk cases State machine, retrieval, LLM response synthesis, cache, CSAT, tests

Shared design principles

  1. Human escalation before automation. Legal, billing, security, refund, and churn-risk messages are routed to staff instead of being answered automatically.
  2. Structured outputs. The model is constrained to classification or review schemas rather than free-form generation alone.
  3. Retrieval before response. Answers and reviews are grounded in an approved document collection or synthetic templates.
  4. Operational observability. Health endpoints, SQLite event records, latency tests, and explicit failure states make the prototypes inspectable.
  5. Secrets stay outside Git. All credentials are read from environment variables; example configuration files contain placeholders only.

Repository layout

intern/
├── legal-review-bot/
├── financial-reporting-bot/
├── customer-service-bot/
├── .gitignore
└── README.md

Each project has its own setup instructions, architecture notes, limitations, and test commands.

Sanitization performed

  • Removed real server addresses, ports, App IDs, chat IDs, employee names, customer records, internal repository URLs, and SSH deployment scripts.
  • Replaced organization-specific model gateways with generic OpenAI-compatible environment variables.
  • Removed historical customer-service QA and replaced real product branding with ExampleProduct.
  • Retained only synthetic contract and expense examples.

Scope and limitations

  • These are portfolio demonstrations, not production services.
  • The legal-review project is not legal advice and requires qualified human review.
  • The financial project is not an accounting or audit system.
  • The customer-service project requires an approved documentation corpus before use.
  • Reported demo accuracy is not presented as a general benchmark.

License

Code is released under the MIT License. Third-party trademarks and platform APIs remain the property of their respective owners. No employer or client data is included.

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Sanitized internship portfolio: legal review, financial reporting, and customer service AI agents

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