mirror of
https://github.com/kennethreitz/instructor.git
synced 2026-06-05 22:50:18 +00:00
Jason Liu
138 lines
3.6 KiB
Python
138 lines
3.6 KiB
Python
import openai
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from typing import List
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from pydantic import Field
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from instructor import OpenAISchema
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class File(OpenAISchema):
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"""
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Correctly named file with contents.
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"""
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file_name: str = Field(
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..., description="The name of the file including the extension"
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)
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body: str = Field(..., description="Correct contents of a file")
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def save(self):
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with open(self.file_name, "w") as f:
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f.write(self.body)
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class Program(OpenAISchema):
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"""
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Set of files that represent a complete and correct program
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"""
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files: List[File] = Field(..., description="List of files")
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def develop(data: str) -> Program:
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completion = openai.ChatCompletion.create(
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model="gpt-3.5-turbo-0613",
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temperature=0.1,
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functions=[Program.openai_schema],
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function_call={"name": Program.openai_schema["name"]},
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messages=[
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{
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"role": "system",
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"content": "You are a world class programming AI capable of writing correct python scripts and modules. You will name files correct, include __init__.py files and write correct python code. with correct imports.",
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},
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{
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"role": "user",
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"content": data,
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},
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],
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max_tokens=1000,
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)
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return Program.from_response(completion)
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if __name__ == "__main__":
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program = develop(
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"""
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Create a fastapi app with a readme.md file and a main.py file with
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some basic math functions. the datamodels should use pydantic and
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the main.py should use fastapi. the readme.md should have a title
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and a description. The readme should contain some helpful infromation
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and a curl example"""
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)
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for file in program.files:
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print(file.file_name)
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print("-")
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print(file.body)
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print("\n\n\n")
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"""
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readme.md
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-
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# FastAPI App
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This is a FastAPI app that provides some basic math functions.
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## Usage
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To use this app, follow the instructions below:
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1. Install the required dependencies by running `pip install -r requirements.txt`.
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2. Start the app by running `uvicorn main:app --reload`.
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3. Open your browser and navigate to `http://localhost:8000/docs` to access the Swagger UI documentation.
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## Example
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To perform a basic math operation, you can use the following curl command:
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```bash
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curl -X POST -H "Content-Type: application/json" -d '{"operation": "add", "operands": [2, 3]}' http://localhost:8000/calculate
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```
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main.py
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-
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from fastapi import FastAPI
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from pydantic import BaseModel
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app = FastAPI()
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class Operation(BaseModel):
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operation: str
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operands: list
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@app.post('/calculate')
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async def calculate(operation: Operation):
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if operation.operation == 'add':
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result = sum(operation.operands)
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elif operation.operation == 'subtract':
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result = operation.operands[0] - sum(operation.operands[1:])
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elif operation.operation == 'multiply':
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result = 1
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for operand in operation.operands:
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result *= operand
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elif operation.operation == 'divide':
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result = operation.operands[0]
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for operand in operation.operands[1:]:
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result /= operand
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else:
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result = None
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return {'result': result}
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requirements.txt
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-
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fastapi
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uvicorn
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pydantic
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"""
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with open("program.json", "w") as f:
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f.write(Program.parse_obj(program).json())
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