import org.opensearch.action.index.IndexRequest;
import org.opensearch.action.index.IndexRequestBuilder;
import org.opensearch.index.query.QueryBuilder;
import org.opensearch.transport.client.Client;

/**
 * SuggestIndexWriter is an implementation of the SuggestWriter interface that provides methods to write, delete,
 * and delete by query suggest items in an OpenSearch index.
 */
public class SuggestIndexWriter implements SuggestWriter {
    /**

And it can return anything you want.

In this case, this dependency expects:

* An optional query parameter `q` that is a `str`.
* An optional query parameter `skip` that is an `int`, and by default is `0`.
* An optional query parameter `limit` that is an `int`, and by default is `100`.

And then it just returns a `dict` containing those values.

/// info

import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.List;

import org.dbflute.exception.InvalidQueryRegisteredException;
import org.opensearch.index.query.QueryBuilder;
import org.opensearch.search.aggregations.AbstractAggregationBuilder;
import org.opensearch.search.aggregations.AggregationBuilders;
import org.opensearch.search.aggregations.bucket.filter.FilterAggregationBuilder;

type ConnPool interface {
	PrepareContext(ctx context.Context, query string) (*sql.Stmt, error)
}

// New creates a new Stmt object for executing SQL queries.
// It caches the Stmt object for future use and handles preparation and error states.
// Parameters:
//
//	ctx: Context for the request, used to carry deadlines, cancellation signals, etc.
//	key: The key representing the SQL query, used for caching and preparing the statement.

{* ../../docs_src/schema_extra_example/tutorial002_py310.py hl[2,8:11] *}

## `examples` im JSON-Schema – OpenAPI { #examples-in-json-schema-openapi }

Bei Verwendung von:

* `Path()`
* `Query()`
* `Header()`
* `Cookie()`
* `Body()`
* `Form()`
* `File()`

Use `Annotated` for parameter declarations, including `Path`, `Query`, `Header`, etc.:

```python
from typing import Annotated

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_item(
    item_id: Annotated[int, Path(ge=1, description="The item ID")],
    q: Annotated[str | None, Query(max_length=50)] = None,
):
    return {"message": "Hello World"}
```

    }

    /**
     * Regenerates a search query when the previous query failed.
     *
     * @param userMessage the user's original message
     * @param failedQuery the query that failed
     * @param failureReason the reason for failure
     * @param history the conversation history
     * @return a new query string
     * @throws LlmException if LLM is not available
     */

from typing import Annotated

from fastapi import Depends, FastAPI, HTTPException, Query
from sqlmodel import Field, Session, SQLModel, create_engine, select


class HeroBase(SQLModel):
    name: str = Field(index=True)
    age: int | None = Field(default=None, index=True)


class Hero(HeroBase, table=True):
    id: int | None = Field(default=None, primary_key=True)
    secret_name: str


class HeroPublic(HeroBase):
    id: int

labels.num=Numero
labels.pn=Numero di pagina
labels.protocolScheme=Schema
labels.purgeByBots=Elimina per Bot
labels.logLevel=Livello di log
labels.purgeSearchLogDay=Elimina log di ricerca
labels.query=Query
labels.queryId=ID query
labels.rt=rt
labels.searchLog=Log di ricerca
labels.sort=Ordina
labels.start=Posizione iniziale
labels.loginRequired=Login richiesto
labels.loginLink=Mostra link di login
labels.threadName=Nome thread

    <description>
      Returns query parameters for More Like This.
    </description>
    <name>mltQuery</name>
    <function-class>org.codelibs.fess.taglib.FessFunctions</function-class>
    <function-signature>java.lang.String mltQuery()</function-signature>
    <example>
      ${fe:mltQuery()}
    </example>
  </function>

  <function>
    <description>
      Returns query parameters for Geo.
    </description>