AI Statements

[aafent]

Idea for discusion.

What about the idea to add a library for the following statements and functions:

I know that yet there is no community to discuss the idea, but still is nice practice to place for discussion :-)

LLM BASIC Programming Reference

This hypothetical programming reference defines the statements and functions for interacting with multiple Large Language Models (LLMs) and providers using a classic BASIC programming style.

1. Core Communication & State

These statements manage the flow of interaction, sending prompts, and receiving replies.

Statement	Purpose	Example	Classic BASIC Analogy
LLMGET	Sends the prompt (first variable) to the active LLM and stores the AI's reply in the second variable.	LLMGET PROMPT, REPLY	INPUT / READ
LLMPROMPT	Declares the variable that will hold the main prompt string.	LLMPROMPT QUERY_TEXT	Variable declaration
LLMSET	Sets an AI configuration parameter, such as the model's 'TEMPERATURE' (creativity) or the 'SYSTEM' (persona) instruction.	LLMSET "TEMPERATURE", 0.7	Setting an environment variable
LLMRESET	Clears the session's conversation history or resets all AI parameters to defaults.	LLMRESET	CLEAR
LLMWAIT	Pauses the program's execution until the LLM has finished generating a reply.	LLMWAIT	Implicit wait on INPUT

2. Provider & Model Selection

These statements and functions allow for dynamic management and switching between different AI services and models.

Statement / Function	Purpose	Example
LLMADD	Registers a new AI provider (e.g., API key) for use in the program. Run this at startup.	LLMADD "PROVIDER_A", API_KEY_A
LLMUSE	Selects the active provider and model for subsequent LLMGET calls.	LLMUSE "PROVIDER_B", "MODEL_HIGH_RES"
LLMGETPROVIDER ( )	Returns the name of the currently active AI provider.	CURRENT_P = LLMGETPROVIDER()
LLMGETMODEL ( )	Returns the name of the currently active AI model.	CURRENT_M = LLMGETMODEL()
LLMCHECKMODEL ( )	Returns 1 if the specified model is available from the active provider, 0 otherwise.	IF LLMCHECKMODEL("MODEL_32K") THEN GOTO BIGTASK

3. Text & Data Analysis Functions

These functions inspect the prompt or reply, using LLM-specific analysis and classic BASIC string manipulation style.

Function	Purpose	Example	Classic BASIC Analogy
LLMLEN ( )	Returns the estimated number of tokens (LLM units of length) in the specified string.	PRINT LLMLEN(REPLY)	LEN
LLMLEFT ( , )	Returns the leftmost tokens/characters of the string up to the specified length.	TITLE = LLMLEFT(REPLY, TWENTY)	LEFT
LLMSUB ( , , )	Extracts a substring from the LLM's reply, starting at a given position for a specific length.	EXTRACT = LLMSUB(REPLY, TEN, FIFTEEN)	MID
LLMFIND ( , )	Returns the starting position of a specific word or phrase inside the string.	POS = LLMFIND(REPLY, "KEYWORD")	INSTR
LLMEXTRACT ( , )	Attempts to parse and return a specific structured data type (e.g., NUMBER, LIST) from the reply.	USERAGE = LLMEXTRACT(REPLY, "NUMBER")
LLMCHECK ( )	Returns 1 for a clean response, 0 if the content is flagged by safety filters.	IF LLMCHECK(REPLY) THEN GOTO PROCESS
LLMCOST ( )	Returns the estimated processing cost (in tokens or arbitrary units) for the text.	PRINT "TOTAL COST: "; LLMCOST(PROMPT)

Example Program: Task Switching

REM --- INITIALIZE PROVIDERS ---  
LLMADD "PROVIDER_A", API_KEY_A  
LLMADD "PROVIDER_B", API_KEY_B  

REM --- TASK 1: FAST, CHEAP QUERY ---  
LLMUSE "PROVIDER_A", "MODEL_FAST"  
LLMSET "TEMPERATURE", 0.1  
PROMPT_1 = "WHAT IS THE CAPITAL OF PERU?"  
LLMGET PROMPT_1, FACT_REPLY  
PRINT "FAST AI SAYS: "; FACT_REPLY  

REM --- TASK 2: HIGH-QUALITY CREATIVE TASK ---  
LLMUSE "PROVIDER_B"  
IF LLMCHECKMODEL("MODEL_CREATIVE") THEN GOTO USE_CREATIVE  
LLMUSE "MODEL_DEFAULT"  
GOTO CONTINUE  


USE_CREATIVE:  
LLMUSE "MODEL_CREATIVE"  
LLMSET "TEMPERATURE", 0.9  


CONTINUE:  
PROMPT_2 = "WRITE A TEN-WORD MOTTO FOR A SPACE EXPLORER"  
LLMGET PROMPT_2, MOTTO_REPLY  


REM CHECK THE REPLY LENGTH AND CONTENT  
TOKEN_L = LLMLEN(MOTTO_REPLY)  
IF LLMCHECK(MOTTO_REPLY) = 0 THEN 
    GOTO BAD_CONTENT  
ENDIF

PRINT "CREATIVE AI MOTTO (" + LLMGETMODEL() + "):"  
PRINT MOTTO_REPLY  
PRINT "TOTAL TOKENS: "; TOKEN_L  

GOTO END_PROG  


BAD_CONTENT:  
PRINT "WARNING: LLM REPLY VIOLATED CONTENT POLICY."  
LLMRESET  

END_PROG:  
END

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