💡📚 Research Proposal Generator API

🎓 AI Research Proposal Generator 🤖Transform your research ideas into professionally formatted, publication-ready proposals — in minutes! ✨ Key Highlights:📄

• •Id: widget_254
• •Price: Ƀ 5 a run, plus the Call Price, Ƀ 0.1 an API run. Your first 100 API runs carry no Call Price.
• •Widget page: Run it in your browser
• •Docs: Call Abyss from your code

Input

Send these Fields as input. A Field not listed here is refused.

research_title

Research Title

• •Type: string
• •Required: yes
• •Length in characters: 1 to 1000

research_question

Research Question / Problem Statement

• •Type: string
• •Required: yes
• •Length in characters: 1 to 30000

methodology

Methodology

• •Type: string
• •Required: yes
• •Length in characters: 1 to 10000

expected_outcomes

Expected Outcomes / Significance

• •Type: string
• •Required: yes
• •Length in characters: 1 to 30000

researcher_name

Researcher Name (Optional)

• •Type: string
• •Required: no
• •Length in characters: at most 1000

field_of_study

Field of Study (Optional)

• •Type: string
• •Required: no
• •Allowed values: Sciences, Social Sciences, Humanities, Engineering, Medical, Business

duration_months

Project Duration in Months (Optional)

• •Type: number
• •Required: no

Run it

One call presses the Widget and answers the run once its status is succeeded or failed, however long it takes. The key is read from ABYSS_API_KEY. Install the library with npm install abysshub or pip install abysshub; cURL sends the Fields as a form.

JavaScript

Copy// index.mjs
import Abyss from "abysshub";

const abyss = new Abyss();

const run = await abyss.run("widget_254", {
  research_title: "Named Entity recognition",
  research_question: "reducing labeled data need",
  methodology: "implementing active learning for reducing labeled data need in NER models for low resource languages",
  expected_outcomes: "reducing workhours and expense",
  researcher_name: "Ismat Samadov",
  field_of_study: "Engineering",
  duration_months: 5,
});

for (const path of await run.save("output")) {
  console.log(path);
}

Python

Copyfrom abysshub import Abyss

abyss = Abyss()

run = abyss.run("widget_254", {
    "research_title": "Named Entity recognition",
    "research_question": "reducing labeled data need",
    "methodology": "implementing active learning for reducing labeled data need in NER models for low resource languages",
    "expected_outcomes": "reducing workhours and expense",
    "researcher_name": "Ismat Samadov",
    "field_of_study": "Engineering",
    "duration_months": 5,
})

for path in run.save("output"):
    print(path)

cURL

Copycurl https://api.abysshub.com/v1/widgets/widget_254/runs \
  -H "Authorization: Bearer $ABYSS_API_KEY" \
  -F 'research_title=Named Entity recognition' \
  -F 'research_question=reducing labeled data need' \
  -F 'methodology=implementing active learning for reducing labeled data need in NER models for low resource languages' \
  -F 'expected_outcomes=reducing workhours and expense' \
  -F 'researcher_name=Ismat Samadov' \
  -F field_of_study=Engineering \
  -F duration_months=5

A succeeded run carries its result and its output_files. Their URLs are signed for each read: re-read the run, never store a URL. A run still queued or running in the answer (after an hour, or when the API is busy) is read again at its Location with ?wait=true.

More

Keys, files, errors and limits: API access.