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SysPmt

Código Fuente de IA

v1.0.0

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Syspmt Readme

Descripción general

SYSPMT es una herramienta basada en Python diseñada para convertir el código de pseudo escrito en una sintaxis similar a Python en indicaciones de sistema precisas y procesables para modelos de lenguaje grandes (LLM). Esta herramienta está destinada a ayudar a los desarrolladores e ingenieros de inmediato que son expertos en programación, pero que pueden necesitar ayuda para elaborar indicaciones efectivas del sistema para LLM.

Cómo funciona

SYSPMT procesa un archivo de pseudo-código ( .pmt ) y un archivo de configuración ( .yaml ) para traducir el pseudocódigo en un indicador del sistema utilizando las asignaciones definidas en la configuración YAML. El texto generado se proporciona luego a un LLM (en nuestro caso, ChatGPT 4) para crear el mensaje final del sistema.

Instalación y configuración

Clon el repositorio:
```
git clone [repository-url]
```
Asegúrese de que Python 3.x esté instalado en su máquina.
Instalar dependencias requeridas:
```
pip install -r requirements.txt
```
Reemplace la tecla API del marcador de posición en el script con su tecla API OpenAI real.

Uso

Ejecute syspmt especificando las rutas a sus archivos de configuración y pseudo-código:

python3 syspmt.py --config path/to/config.yaml --prompt path/to/prompt.pmt

Archivo de configuración ( `config.yaml` )

El archivo de configuración define traducciones y formatos de mensaje para convertir el código de pseudo en indicaciones. Aquí hay una configuración de ejemplo:

 messages :
  assign : " The AI assistant's '{var}' is set to {value}. "
  if_condition : " If the condition '{condition}' is met, perform the following actions: "
  else_condition : " Otherwise, perform the following actions: "

translations :
  check_language : " check if the language is "
  mission : " set the mission to "
  context : " set the context to "
  reject : " reject with the message: "
  proceed : " Proceed with the request "

Pseudo-Code File ( `prompt.pmt` )

Este archivo contiene su pseudo-código personalizado. Ejemplo:

 mission = "travel agency support"
context = "travel discussion"
language = "English"
age = 28
gender = "Male"

if check_language ( language ):
    mission ( mission )
    context ( context )
elif check_language ( "French" ):
    mission ( "French travel consultant specializing in Paris" )
    context ( "discussion about travel offers in Paris" )
else :
    reject ( "We are sorry, we cannot assist you at the moment." )

if context ( "travel discussion" ):
    if check_language ( "English" ):
        mission ( "English travel specials" )
        context ( "exploring travel packages tailored for English speakers" )
    elif check_language ( "Spanish" ):
        mission ( "Spanish travel specials" )
        context ( "exploring travel packages tailored for Spanish speakers" )
    else :
        proceed ()
elif context ( "adventure tourism" ):
    mission ( "adventure tourism specialist" )
    context ( "providing information on adventure tourism packages" )
    if check_language ( "German" ):
        mission ( "German-speaking adventure tourism specialist" )
    else :
        proceed ()
else :
    reject ( "Unfortunately, we cannot provide assistance for this request. Please check your input and try again." )

Producción

Syspmt emite el sistema listos para el procesamiento de LLM. Ejemplo de salida basado en el código de pseudo anterior:

 As a 28-year-old male AI assistant set in the travel agency support mission, and operating in a travel discussion context, your task is to communicate in English. However, you need to attend to the user query dynamically according to the preferred language. If you detect that the user's language is English, you should continue providing assistance about travel discussions as an English travel specials consultant. But if the user shifts the language to French, your role must be changed to a French travel consultant specializing in Paris, discussing travel offers in that region. 

Nonetheless, if any other language than English or French is detected, you are supposed to inform the user with a message, stating, 'We are sorry, we cannot assist you at the moment.'. Also, it is important that you adjust the discussion context according to the user's command. If the context switches to 'travel discussion,' you should cater to the user in the language they are speaking, English or Spanish, exploring travel packages tailored for English or Spanish speakers, respectively. Still, if the user's language is different from these two, you should proceed with the initial settings. 

Conversely, if the context becomes 'adventure tourism,' modify your mission to an adventure tourism specialist, and if the user is speaking German, serve as a German-speaking adventure tourism specialist. But, should the language setting not be identified or if the context does not match any predefined settings, you should provide a message that states, 'Unfortunately, we cannot provide assistance for this request. Please check your input and try again.'.