Agent Reporting using Exa.ai API.
Project description
Agentic Reports
Comprehensive System Implementation with FastAPI, Pydantic, Pandas, Exa, and Pytest
Welcome to the comprehensive system implementation guide. This document will walk you through setting up and implementing a system using FastAPI, Pydantic, Pandas, Exa, and Pytest. We will also cover the creation of a bash installation script, .devcontainer configuration, requirements.txt, folder and file structure, and necessary modules.
Table of Contents
- Project Overview
- Prerequisites
- Folder and File Structure
- Installation
- Configuration
- Modules and Functions
- Testing
- Running the Application
- Application Uses
- Features
- References
Project Overview
This project aims to create a high-performance API using FastAPI, Pydantic for data validation, Pandas for data manipulation, Exa for search capabilities, and Pytest for testing. The system will generate comprehensive research reports based on user queries.
Prerequisites
Before you begin, ensure you have the following installed on your machine:
- Python 3.7+
- Docker
- Git
Folder and File Structure
The project structure is organized as follows:
project-root/
├── app/
│ ├── __init__.py
│ ├── main.py
│ ├── api/
│ │ ├── __init__.py
│ │ ├── endpoints.py
│ ├── core/
│ │ ├── __init__.py
│ │ ├── config.py
│ ├── models/
│ │ ├── __init__.py
│ │ ├── report.py
│ ├── services/
│ │ ├── __init__.py
│ │ ├── report_generator.py
│ ├── utils/
│ │ ├── __init__.py
│ │ ├── exa_search.py
├── tests/
│ ├── __init__.py
│ ├── test_main.py
│ ├── test_report_generator.py
├── .devcontainer/
│ ├── devcontainer.json
│ ├── Dockerfile
├── requirements.txt
├── install.sh
├── README.md
Installation
To get started with the Agentic Reports application, follow these simple steps:
- Clone the repository to your local machine.
- Run the provided installation script to set up your environment.
- Use Docker to build and run the application container.
Configuration
The application can be easily configured to suit your needs. Here are some ways you can customize your setup:
- Set API keys for Exa and OpenAI services in the
.env
file. - Adjust report generation parameters to fine-tune the output.
Modules and Functions
The application is structured around several key modules and functions:
- API Endpoints: Define the routes for generating reports.
- Report Generation: Utilizes AI and Exa search capabilities to create comprehensive reports.
- Data Validation and Manipulation: Ensures the integrity of input data and prepares it for processing.
Testing
Testing is an integral part of the development process. The application includes a suite of tests to ensure functionality and reliability.
Running the Application
To run the application, use the command:
uvicorn app.main:app --reload
Application Uses
The Agentic Reports application can be used in various scenarios, including but not limited to:
- Academic research to compile data on specific topics.
- Business intelligence to gather insights from vast datasets.
- Personal projects for learning and exploration.
Features
The application boasts several unique features:
- AI-Driven Report Generation: Leverages advanced AI models to create detailed reports.
- Integration with Exa: Utilizes Exa's powerful search capabilities for data retrieval.
- Customizable Reports: Offers options to tailor reports according to user preferences.
References
- FastAPI Documentation
- Pydantic Documentation
- Pandas Documentation
- Exa Documentation
- Pytest Documentation
This detailed plan should help you set up and implement the system effectively. If you have any questions or need further assistance, feel free to reach out.
Citations: [1] https://ppl-ai-file-upload.s3.amazonaws.com/web/direct-files/2592765/73f4bc8c-837f-4711-a4b5-d4dadd91f486/paste.txt [2] https://fastapi.tiangolo.com/tutorial/testing/ [3] https://www.youtube.com/watch?v=qNVsQ4R9Lsg [4] https://shuaib.org/python/fastapi/quickly-set-up-a-fastapi-app-with-this-script/ [5] https://www.youtube.com/watch?v=jM-zWp8dNQA [6] https://dev.to/timo_reusch/how-i-structure-big-fastapi-projects-260e [7] https://www.reddit.com/r/FastAPI/comments/uxnso3/fastapi_large_app_structure/ [8] https://stackoverflow.com/questions/70448668/passing-pandas-dataframe-to-fastapi [9] https://testdriven.io/blog/fastapi-crud/ [10] https://andypickup.com/developing-in-python-with-dev-containers-part-2-a-simple-fastapi-project-with-step-debugging-e52599b7ce61?gi=beae3ea2f4fd [11] https://fastapi.tiangolo.com/features/ [12] https://fastapi.tiangolo.com/tutorial/first-steps/ [13] https://github.com/rochacbruno/fastapi-project-template/blob/main/requirements.txt [14] https://fastapi.tiangolo.com/advanced/settings/ [15] https://plainenglish.io/blog/how-to-generate-requirements-txt-for-your-python-project-235183799d2f [16] https://pytest-with-eric.com/pytest-advanced/pytest-fastapi-testing/ [17] https://christophergs.com/tutorials/ultimate-fastapi-tutorial-pt-4-pydantic-schemas/ [18] https://fastapi.tiangolo.com/tutorial/schema-extra-example/ [19] https://www.reddit.com/r/FastAPI/comments/115en24/help_how_to_make_ml_predictions_of_a_pandas/ [20] https://fastapi.tiangolo.com/deployment/docker/
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