How to EASILY Build Complete AI Agents (5 Steps)
AI Summary
Summary of the Video: Building a Complete Front-to-Backend Application with AI Agents
Step 1: Create the Front End
- Build a simple application to upload files.
- Deploy the app using Bolt to obtain a secure URL for file submission.
Step 2: Setup the Backend with FastAPI
- Create a FastAPI application with an endpoint to analyze uploaded files.
- Use the Dockling library for file format conversion to Markdown.
- Test the API with Swagger for functionality.
Step 3: Use Crew AI for Analysis
- Initialize Crew AI to analyze Markdown content.
- Set up a single agent and task for processing the uploaded files.
- Modify the main Python file to integrate Crew AI results into the FastAPI application.
Step 4: Connect Local FastAPI with a Public URL
- Use Enrock to forward requests from a public domain to the local FastAPI server.
- Set up the forwarding to ensure the FastAPI server can receive requests.
Step 5: Connect the Front End to the Backend
- Update the front-end application with the Enrock URL of the FastAPI backend.
- Test the complete application workflow from file upload to analysis results.
Conclusion
- Successfully created a full-stack application combining front-end and AI backend functionalities.
- Suggestions for troubleshooting common issues during setup are discussed.
Please refer to specific commands and the documentation mentioned in the video for detailed implementation steps and to resolve any errors.