botserver/templates/annoucements.gbai/annoucements.gbdialog/start.bas

TALK "Olá, estou preparando um resumo para você."
let x = LLM "Quando é 5+5?"
TALK x
SET_CONTEXT "Este é o documento que você deve usar para responder dúvidas: O céu é azul."

REM text = GET "default.pdf"
REM resume = LLM "Say Hello and present a a resume from " + text
REM TALK resume
- Database schema added. 2025-10-14 16:34:34 -03:00			`TALK "Olá, estou preparando um resumo para você."`
Refactor LLM flow, add prompts, fix UI streaming - Extract LLM generation into `execute_llm_generation` and simplify keyword handling. - Prepend system prompt and session context to LLM prompts in `BotOrchestrator`. - Parse incoming WebSocket messages as JSON and use the `content` field. - Add async `get_session_context` and stop injecting Redis context into conversation history. - Change default LLM URL to `http://48.217.66.81:8080` throughout the project. - Use the existing DB pool instead of creating a separate custom connection. - Update `start.bas` to call LLM and set a new context string. - Refactor web client message handling: separate event processing, improve streaming logic, reset streaming state on thinking end, and remove unused test functions. 2025-10-15 01:14:37 -03:00			`let x = LLM "Quando é 5+5?"`
			`TALK x`
			`SET_CONTEXT "Este é o documento que você deve usar para responder dúvidas: O céu é azul."`
- Database schema added. 2025-10-14 16:34:34 -03:00
Refactor server code and add auth API fixes 2025-10-14 13:51:27 -03:00			`REM text = GET "default.pdf"`
Refactor session handling and auth flow 2025-10-14 14:51:49 -03:00			`REM resume = LLM "Say Hello and present a a resume from " + text`
Refactor server code and add auth API fixes 2025-10-14 13:51:27 -03:00			`REM TALK resume`