agentic-reports 0.0.2

Agent Reporting using Exa.ai API.

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

1. Project Overview
2. Prerequisites
3. Folder and File Structure
4. Installation
5. Configuration
6. Modules and Functions
7. Testing
8. Running the Application
9. Application Uses
10. Features
11. 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

Running the Application

To start the Agentic Reports application, follow these steps:

1. Install the Package: Install the Agentic Reports package using pip:

   pip install agentic-reports
   

2. Run the Application: Use the following command to start the application:

   agentic-reports
   

This command will initialize the application and start the Uvicorn server on http://0.0.0.0:8000.

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/