Academic Report AI Creator is a ground-breaking app that uses AI to generate customized, intricate academic reports. Users simply specify variables, and the AI compiles well-structured content, featuring abstract, introduction, literature review, methodology, results, discussion and conclusion around any research problem. Delivering analysis of past studies, clear research outlines, unbiased findings, comparisons to previous research, and potential implications, this comprehensive academic report stands in a class of its own. Ideal for the University & Academic industry, this unique tool specializes in complex academic language and concepts.
To run this app online: Academic Report AI Creator Online
To learn more about AI Apps for Researcher use-cases in the Academic & University industry, read How to Enhance Academic Research with AI Tools
HeroML is an AI Prompt Chain/Workflow interpreter for Apps built on https://hero.page
To see other apps, visit the Hero Apps page or explore AI Apps for all industries in the blog section
For more documentation, visit Hero docs, and learn about AI App Workflows
Download VSCode Syntax Highlighter Ext. here
To install the HeroML CLI tool, you need to have Node.js and npm (comes with Node.js) installed on your machine. If you don't have these, please install them first.
Then, run the following command in your terminal:
npm install -g heroml
This will install the HeroML CLI tool globally on your system, allowing you to use the hero
command from any directory.
If you don't want to install it globally, you can run:
npm install heroml
and use it like:
npx hero run ./academic_report_ai_creator.heroml
We'll be using hero run ...
in this tutorial for simplicity.
Before using the HeroML CLI tool, you need to configure your OpenAI API key.
Create a heroconfig.json
file in your home directory with the following content:
{
"openaiApiKey": "your-openai-api-key"
}
Replace "your-openai-api-key"
with your actual OpenAI API key.
To run a HeroML script, use the run
command followed by the path to your script:
hero run ./academic_report_ai_creator.heroml
You can provide initial variable values as command-line options. For example, if your script expects a variable named number_of_colors
, you can provide its value as follows:
hero run --number_of_colors 4 ./academic_report_ai_creator.heroml
If you do not provide a value for a variable, the HeroML CLI tool will prompt you to enter it interactively.
You can specify the output directory and the filename of the output file using command-line options:
- The
-o
or--output-dir
option allows you to specify the output directory. By default, it is./outputs/
.
hero run --output-dir /custom/output/directory ./academic_report_ai_creator.heroml
- The
-f
or--filename
option allows you to specify the filename of the output file. By default, it isresponse_TIMESTAMP.json
.
hero run --filename custom_filename.json ./academic_report_ai_creator.heroml
The CLI tool writes the output to a JSON file in the specified directory. It will print the path of the output file to the console:
Success! Output written to /custom/output/directory/custom_filename.json
To generate a "Data Analysis Report" in the "Academic & University" industry for a "Researcher", follow the steps outlined below:
Starting, let's write an informative abstract that provides an overview of the data analysis report, including the research problem, methodologies, major findings, and implications.
Here's some more context about the Data Analysis Report:
Abstract Overview: {{abstract_overview}}
Research Problem: {{research_problem}}
Literature Review: {{literature_review}}
Methodology: {{methodology}}
Data Findings: {{data_findings}}
Discussion Points: {{discussion_points}}
Conclusion Points: {{conclusion_points}}
Reference List: {{reference_list}}
->>>>
We have begun our Data Analysis Report with:
Abstract Overview:
{{step_1}}
Moving forward, let's develop an introduction that defines the research problem, explains its importance, and states the objectives of the research.
->>>>
We have crafted an Introduction for our Data Analysis Report that builds on the abstract:
Abstract Overview:
{{step_1}}
Introduction:
{{step_2}}
We need to incorporate a literature review section next. This section should summarize previous research studies related to your topic, providing context for our own research and emphasizing the need for our study.
->>>>
We now have an Introduction and a Literature review for our Data Analysis Report:
Introduction:
{{step_2}}
Literature Review:
{{step_3}}
Let's proceed with the methodology section that clearly outlines the procedures used in the research process, including data collection and analysis methods.
->>>>
Our Data Analysis Report now includes an Introduction, Literature review, and Methodology:
Introduction:
{{step_2}}
Literature Review:
{{step_3}}
Methodology:
{{step_4}}
In the results section, we should present the outcomes of our data analysis. Let's generate this section by summarizing the findings without interpretation.
->>>>
Our Data Analysis Report now includes the Results as well:
Methodology:
{{step_4}}
Results:
{{step_5}}
The next section is the Discussion, where we shall interpret the results, compare them with previous studies, and discuss implications for future research.
->>>>
Our Data Analysis Report now includes the Discussion derived from our Results:
Results:
{{step_5}}
Discussion:
{{step_6}}
We should now proceed to the conclusion of the report. Let's put together a conclusion that summarizes the main points of the research, data analysis, the implications of findings, and identifies opportunities for future research.
->>>>
Our Data Analysis Report now includes the Conclusion:
Discussion:
{{step_6}}
Conclusion:
{{step_7}}
To finish off, let's compile a list of references that mention all books, articles, and other resources used in the research.