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Add initial implementation of ask2api CLI tool
- Created `ask2api.py` for converting natural language prompts into structured JSON API responses using OpenAI's API. - Added `README.md` with usage instructions and examples. - Included `schema.json` for defining the expected JSON structure. - Introduced `.gitignore` to exclude unnecessary files and directories. - Added `.pre-commit-config.yaml` for code quality checks using Ruff. - Defined project metadata in `pyproject.toml` and `uv.lock` for dependency management.
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.gitignore

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.pre-commit-config.yaml

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repos:
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.8.4
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hooks:
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- id: ruff
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args: [--fix]
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types: [python]
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- id: ruff-format
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types: [python]
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README.md

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# ask2api
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`ask2api` is a minimal Python CLI tool that turns natural language prompts into structured API-style JSON responses using LLM.
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It allows you to define a JSON Schema and force the model to answer strictly in that format.
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## Why ask2api?
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Because LLMs are no longer just chatbots, they are also programmable API engines.
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`ask2api` lets you use them that way. 🚀
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Key features:
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- Minimal dependencies
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- CLI first
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- Prompt → API behavior
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- No markdown, no explanations, only valid JSON
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- Designed for automation pipelines and AI-driven backend workflows
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## Installation
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```bash
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pip install ask2api
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```
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Set your OpenAI key:
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```bash
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export OPENAI_API_KEY="your_api_key"
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```
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## Usage
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Instead of asking:
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> *“Where is the capital of France?”*
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and receiving free-form text, you can do this:
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```bash
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ask2api -p "Where is the capital of France?" -sf schema.json
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```
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And get a structured API response:
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```json
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{
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"country": "France",
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"city": "Paris"
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}
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```
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## How it works
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1. You define the desired output structure using a JSON Schema.
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2. The schema is passed to the model using OpenAI’s `json_schema` structured output format.
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3. The system prompt enforces strict JSON-only responses.
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4. The CLI prints the API-ready JSON output.
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The model is treated as a deterministic API function.
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## Example schema
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Create a file named `schema.json`:
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```json
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{
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"type": "object",
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"properties": {
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"country": { "type": "string" },
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"city": { "type": "string" }
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},
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"required": ["country", "city"]
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}
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```
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## Contributing
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Contributions are welcome! Please feel free to submit a Pull Request.
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## License
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MIT

ask2api.py

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import argparse
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import json
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import os
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import requests
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API_KEY = os.getenv("OPENAI_API_KEY")
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OPENAI_URL = "https://api.openai.com/v1/chat/completions"
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("-p", "--prompt", required=True)
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parser.add_argument("-sf", "--schema-file", required=True)
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args = parser.parse_args()
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with open(args.schema_file, "r", encoding="utf-8") as f:
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schema = json.load(f)
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system_prompt = """
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You are a JSON API engine.
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You must answer every user request as a valid API response that strictly
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follows the given JSON schema.
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Never return markdown, comments or extra text.
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"""
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payload = {
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"model": "gpt-4.1",
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": args.prompt},
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],
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"response_format": {
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"type": "json_schema",
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"json_schema": {"name": "ask2api_schema", "schema": schema},
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},
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"temperature": 0,
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}
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headers = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
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r = requests.post(OPENAI_URL, headers=headers, json=payload)
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r.raise_for_status()
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result = r.json()["choices"][0]["message"]["content"]
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parsed_result = json.loads(result)
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print(json.dumps(parsed_result, indent=2, ensure_ascii=False))
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if __name__ == "__main__":
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main()

pyproject.toml

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[project]
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name = "ask2api"
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version = "0.1.0"
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description = "A minimal CLI tool that turns natural language into instant APIs."
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readme = "README.md"
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authors = [
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{name = "Ahmet Atasoglu", email = "[email protected]"},
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]
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requires-python = ">=3.9"
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dependencies = [
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"requests",
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]
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[project.scripts]
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ask2api = "ask2api:main"
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[project.urls]
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Homepage = "https://github.com/atasoglu/ask2api"
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Repository = "https://github.com/atasoglu/ask2api.git"
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[project.optional-dependencies]
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dev = [
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"pre-commit",
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]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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