Kader Miyanyedi <******@****.***> 1768941243 +0300

Motov Yurii <******@****.***> 1773831336 +0100

public class LegacyPlexusInteractivity implements Prompter, InputHandler, OutputHandler {
    private final org.apache.maven.api.services.Prompter prompter;

    @Inject
    public LegacyPlexusInteractivity(org.apache.maven.api.services.Prompter prompter) {
        this.prompter = prompter;
    }

    @Override
    public String readLine() throws IOException {
        try {
            return prompter.prompt(null);

    }

    /**
     * Resolves the {{languageInstruction}} placeholder in a prompt.
     *
     * @param prompt the prompt template
     * @return the prompt with language instruction resolved
     */
    protected String resolveLanguageInstruction(final String prompt) {
        if (prompt == null) {
            return null;
        }

 */
@Experimental
public interface Prompter extends Service {
    /**
     * Prompts the user for a string.
     *
     * @param message the message to display to the user
     * @return the string entered by the user
     * @throws PrompterException if an exception occurs
     */
    @Nonnull
    default String prompt(@Nullable String message) throws PrompterException {
        return prompt(message, null, null);
    }

    /**

from fastapi.sse import EventSourceResponse, ServerSentEvent
from pydantic import BaseModel

app = FastAPI()


class Prompt(BaseModel):
    text: str


@app.post("/chat/stream", response_class=EventSourceResponse)
async def stream_chat(prompt: Prompt) -> AsyncIterable[ServerSentEvent]:
    words = prompt.text.split()
    for word in words:
        yield ServerSentEvent(data=word, event="token")

Instead of adding suggestions to the translation PR, make the suggestions to the LLM prompt file for that language, in a new PR. For example, for Spanish, the LLM prompt file is at: [`docs/es/llm-prompt.md`](https://github.com/fastapi/fastapi/blob/master/docs/es/llm-prompt.md).

/// tip

    display: inline-block;
    vertical-align: middle;
}

[data-ty="input"]:before,
[data-ty-prompt]:before {
    margin-right: 0.75em;
    color: var(--color-text-subtle);
}

[data-ty="input"]:before {
    content: '$';
}

[data-ty][data-ty-prompt]:before {
    content: attr(data-ty-prompt);
}

[data-ty-cursor]:after {
    content: attr(data-ty-cursor);
    font-family: monospace;

        this.finishReason = finishReason;
    }

    /**
     * Gets the number of prompt tokens.
     *
     * @return the prompt tokens count
     */
    public Integer getPromptTokens() {
        return promptTokens;
    }

    /**
     * Sets the number of prompt tokens.
     *
     * @param promptTokens the prompt tokens count
     */
    public void setPromptTokens(final Integer promptTokens) {

Tests added here will be seen by all designers of language specific prompts.

Use as follows:

* Have a language specific prompt - `docs/{language code}/llm-prompt.md`.