У ламы2 галлюцинации ⇐ C#

[Anonymous]

Я пытаюсь получить ответ из базы данных, но у llama2 галлюцинации. Иногда он дает половинчатый ответ. Например, когда я задал вопрос, перечислите все таблицы, присутствующие в базе данных. В ансе не хватает одной-двух таблиц

Код: Выделить всё

using Microsoft.SemanticKernel.ChatCompletion;
using Microsoft.SemanticKernel;
using MySql.Data.MySqlClient;

namespace AI_SQL_Integration
class Program
{
// Define the connection string for MySQL
private static readonly string connectionString = ""; // MySQL Database Connection

static async Task Main(string[] args)
{
//var completionConfig = new OpenAIChatCompletionConfig
//{
//    Temperature = 0.5 // Set the temperature here

//};
// Configure the Semantic Kernel
var kernelBuilder = Kernel.CreateBuilder();
#pragma warning disable SKEXP0010
var kernel = kernelBuilder
.AddOpenAIChatCompletion(
modelId: "llama2",
apiKey: "",
endpoint: new Uri("") //endpoint

)
.Build();

// Create the chat service
var aiModel = kernel.GetRequiredService();

using var connection = new MySqlConnection(connectionString);
try
{
await connection.OpenAsync();
Console.WriteLine("Connection to the database was successful.");
}
catch (Exception ex)
{
Console.WriteLine($"Error connecting to the database: {ex.Message}");
return;
}

// Conversation loop
while (true)
{
Console.Write("Your question: ");
var question = Console.ReadLine();

try
{
// Get the schema of the database
var schema = await GetDatabaseSchemaAsync(connection);

// Generate the SQL query based on the user's question
var sqlQuery = await GenerateSQLQueryAsync(aiModel, question, schema);

// Execute the SQL query and get the results
var sqlResult = await ExecuteSQLQueryAsync(connection, sqlQuery);

// Generate a natural language response based on the SQL result
var naturalResponse = await GenerateNaturalResponseAsync(aiModel, question, schema, sqlQuery, sqlResult);
Console.WriteLine(naturalResponse);
}
catch (Exception ex)
{
Console.WriteLine($"Sorry, it seems there was an issue with my previous response.  {ex.Message}");
Console.WriteLine("To answer your question accurately, I would need to see the actual SQL query you are using and the structure of your database.");
Console.WriteLine("Could you please provide me with that information so I can assist you better?");
}
}
}

private static async Task GetDatabaseSchemaAsync(MySqlConnection connection)
{
var schemaQuery = "SELECT TABLE_NAME, COLUMN_NAME, DATA_TYPE FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_SCHEMA = 'new_fegime'";
var schemaInfo = string.Empty;

using (var command = new MySqlCommand(schemaQuery, connection))
using (var reader = await command.ExecuteReaderAsync())
{
while (await reader.ReadAsync())
{
schemaInfo += $"Table: {reader["TABLE_NAME"]}, Column: {reader["COLUMN_NAME"]}, Type: {reader["DATA_TYPE"]}\n";
}
}

return schemaInfo;
}

private static async Task GenerateSQLQueryAsync(IChatCompletionService aiModel, string question, string schema)
{
var prompt = $@"
Based on the table schema below, write a SQL query that would answer the user's question:
{schema}

Question: {question}
SQL Query:";

var response = string.Empty;
await foreach (var message in aiModel.GetStreamingChatMessageContentsAsync(prompt))
{
response += message;
}
return response.Trim();
}

private static async Task ExecuteSQLQueryAsync(MySqlConnection connection, string sqlQuery)
{
var result = string.Empty;
try
{
var command = new MySqlCommand(sqlQuery, connection);
using var reader = await command.ExecuteReaderAsync();

while (await reader.ReadAsync())
{
for (int i = 0; i < reader.FieldCount; i++)
{
result += $"{reader.GetName(i)}: {reader.GetValue(i)}\t";
}
result += "\n";
}
}
catch (Exception ex)
{
result = $"Error executing query: {ex.Message}";
}
return result;
}

private static async Task GenerateNaturalResponseAsync(IChatCompletionService aiModel, string question, string schema, string sqlQuery, string sqlResult)
{
var prompt = $@"
Based on the table schema below, question, sql query, and sql response, write     a natural language response:
{schema}

Question: {question}
SQL Query: {sqlQuery}
SQL Response: {sqlResult}
Response:";

var response = string.Empty;
await foreach (var message in aiModel.GetStreamingChatMessageContentsAsync(prompt))
{
response += message;
}
return response.Trim();
}
}
}

Я взял ссылку с https://github.com/ollama/ollama/issues ... 1954700235

Подробнее здесь: https://stackoverflow.com/questions/787 ... llicunated