Python, LangChain, OpenAI API
Education
Autonomous AI Agent with Tool Use
United States
About The Project
Operations teams handle many repetitive tasks every day. These tasks include collecting data, running calculations, updating systems, and checking results. Each task is simple, but the number of steps makes the work time-consuming.
TaskPilot was built to reduce this manual effort. Users can give a goal in plain language. The system breaks the goal into steps, selects the tools needed, and completes the work automatically. It also remembers the conversation so users can continue where they left off.
The system was designed to do more than answer questions. It performs actions using tools and APIs in a controlled way.
Key Project Deliverables
We delivered a system that can plan tasks, use tools, store context, and complete actions in a structured flow.
Goal-Based Planning
The system breaks a user’s goal into smaller steps and decides how to complete them.
Tool and Function Calling
It connects to tools such as APIs, calculators, and search services to perform tasks.
Conversational Memory
The system stores conversation history so users can continue tasks without repeating details.
Safety Controls
We added rules to control what the system can do and block unsafe actions.
Chat Interface
Users interact with the system through a simple chat interface connected to the backend.
Action Logging
Every action taken by the system is recorded for review and tracking.
Major Project Challenges
The main challenge was keeping the system on track when handling multi-step tasks. It needed to follow each step correctly without losing context.
Safety posed as another significant hurdle. The system can perform real actions, so every tool needed restrictions and input checks to prevent incorrect operations. Tool integration also needed careful design. Each tool had to follow a clear format so the system could use it without errors.
Memory management required a delicate balance. The system needed to store useful context without using too much space or slowing down performance.
Scalability was vital, with the addition of more tools, the system needed to remain efficient without degrading performance. We designed the architecture to support modular expansion and easy integration of new capabilities.
Solutions & Impact
We built TaskPilot using LangChain and LangGraph with a structured flow for planning and execution. This reduced random outputs and made the system more stable.
Each tool was provided with a fixed interface and validation rules. This ensured that the system only performed allowed actions with correct inputs. Redis was used to store session data and short-term memory. This allowed the system to remember previous steps during a session.
FastAPI was used to expose the system as a simple chat service.
- Built a step-based task planning system
- Added controlled tool execution with validation
- Stored session memory using Redis
- Added safety rules for all actions
- Built a chat interface using FastAPI
- Added logging for all actions
After deployment, tasks that previously required manual switching between tools were completed automatically. Work that involved multiple steps became faster and easier. Every action could also be tracked, which helped teams understand what the system did.
Build AI Agents That Can Execute Real Work!
Automate multi-step tasks, connect tools, and reduce manual effort with custom AI agents.
Project in Figures
3
Months
1,150
Hours
4
Team Size
Applied Technologies
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