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try using foreach activity

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This commit is contained in:
Ryan Sweet
2023-07-12 20:39:21 -07:00
parent 7a901fab44
commit 6b2c2af03a
2 changed files with 97 additions and 44 deletions
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104
Elsa.SemanticKernel/Activities/SemanticKernel.cs
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@@ -53,6 +53,12 @@ public class SemanticKernelSkill : CodeActivity<string>
DefaultValue = "ChatCompletion")]
public Input<string> FunctionName { get; set; }
/* [Input(
Description = "Mockup - don't actually call the AI, just output the prompts",
UIHint = InputUIHints.Checkbox,
DefaultValue = false)]
public Input<bool> Mockup { get; set; } */
/// <inheritdoc />
protected override async ValueTask ExecuteAsync(ActivityExecutionContext workflowContext)
{
@@ -62,56 +68,68 @@ public class SemanticKernelSkill : CodeActivity<string>
var systemPrompt = SysPrompt.Get(workflowContext);
var maxRetries = MaxRetries.Get(workflowContext);
var prompt = Prompt.Get(workflowContext);
var kernelSettings = KernelSettings.LoadSettings();
var kernelConfig = new KernelConfig();
//var mockup = Mockup.Get(workflowContext);
var mockup = false;
using ILoggerFactory loggerFactory = LoggerFactory.Create(builder =>
string info = ($"#################\nSkill: {skillName}\nFunction: {functionName}\nPrompt: {prompt}\n#################\n\n");
if (mockup)
{
builder
.SetMinimumLevel(kernelSettings.LogLevel ?? LogLevel.Warning);
});
/* var memoryStore = new QdrantMemoryStore(new QdrantVectorDbClient("http://qdrant", 1536, port: 6333));
var embedingGeneration = new AzureTextEmbeddingGeneration(kernelSettings.EmbeddingDeploymentOrModelId, kernelSettings.Endpoint, kernelSettings.ApiKey);
var semanticTextMemory = new SemanticTextMemory(memoryStore, embedingGeneration);
*/
var kernel = new KernelBuilder()
.WithLogger(loggerFactory.CreateLogger<IKernel>())
.WithAzureChatCompletionService(kernelSettings.DeploymentOrModelId, kernelSettings.Endpoint, kernelSettings.ApiKey, true, kernelSettings.ServiceId, true)
//.WithMemory(semanticTextMemory)
.WithConfiguration(kernelConfig)
.Configure(c => c.SetDefaultHttpRetryConfig(new HttpRetryConfig
workflowContext.SetResult(info);
}
else
{
MaxRetryCount = maxRetries,
UseExponentialBackoff = true,
// MinRetryDelay = TimeSpan.FromSeconds(2),
// MaxRetryDelay = TimeSpan.FromSeconds(8),
MaxTotalRetryTime = TimeSpan.FromSeconds(300),
// RetryableStatusCodes = new[] { HttpStatusCode.TooManyRequests, HttpStatusCode.RequestTimeout },
// RetryableExceptions = new[] { typeof(HttpRequestException) }
}))
.Build();
var kernelSettings = KernelSettings.LoadSettings();
var kernelConfig = new KernelConfig();
/* var interestingMemories = kernel.Memory.SearchAsync("ImportedMemories", prompt, 2);
var wafContext = "Consider the following contextual snippets:";
await foreach (var memory in interestingMemories)
{
wafContext += $"\n {memory.Metadata.Text}";
} */
using ILoggerFactory loggerFactory = LoggerFactory.Create(builder =>
{
builder
.SetMinimumLevel(kernelSettings.LogLevel ?? LogLevel.Warning);
});
/* var memoryStore = new QdrantMemoryStore(new QdrantVectorDbClient("http://qdrant", 1536, port: 6333));
var embedingGeneration = new AzureTextEmbeddingGeneration(kernelSettings.EmbeddingDeploymentOrModelId, kernelSettings.Endpoint, kernelSettings.ApiKey);
var semanticTextMemory = new SemanticTextMemory(memoryStore, embedingGeneration);
*/
var kernel = new KernelBuilder()
.WithLogger(loggerFactory.CreateLogger<IKernel>())
.WithAzureChatCompletionService(kernelSettings.DeploymentOrModelId, kernelSettings.Endpoint, kernelSettings.ApiKey, true, kernelSettings.ServiceId, true)
//.WithMemory(semanticTextMemory)
.WithConfiguration(kernelConfig)
.Configure(c => c.SetDefaultHttpRetryConfig(new HttpRetryConfig
{
MaxRetryCount = maxRetries,
UseExponentialBackoff = true,
// MinRetryDelay = TimeSpan.FromSeconds(2),
// MaxRetryDelay = TimeSpan.FromSeconds(8),
MaxTotalRetryTime = TimeSpan.FromSeconds(300),
// RetryableStatusCodes = new[] { HttpStatusCode.TooManyRequests, HttpStatusCode.RequestTimeout },
// RetryableExceptions = new[] { typeof(HttpRequestException) }
}))
.Build();
var skillConfig = SemanticFunctionConfig.ForSkillAndFunction(skillName, functionName);
var function = kernel.CreateSemanticFunction(skillConfig.PromptTemplate, skillConfig.Name, skillConfig.SkillName,
skillConfig.Description, skillConfig.MaxTokens, skillConfig.Temperature,
skillConfig.TopP, skillConfig.PPenalty, skillConfig.FPenalty);
/* var interestingMemories = kernel.Memory.SearchAsync("ImportedMemories", prompt, 2);
var wafContext = "Consider the following contextual snippets:";
await foreach (var memory in interestingMemories)
{
wafContext += $"\n {memory.Metadata.Text}";
} */
var context = new ContextVariables();
context.Set("input", prompt);
//context.Set("wafContext", wafContext);
var skillConfig = SemanticFunctionConfig.ForSkillAndFunction(skillName, functionName);
var function = kernel.CreateSemanticFunction(skillConfig.PromptTemplate, skillConfig.Name, skillConfig.SkillName,
skillConfig.Description, skillConfig.MaxTokens, skillConfig.Temperature,
skillConfig.TopP, skillConfig.PPenalty, skillConfig.FPenalty);
SKContext answer = await kernel.RunAsync(context, function).ConfigureAwait(false);
string result = answer.Result;
var context = new ContextVariables();
context.Set("input", prompt);
//context.Set("wafContext", wafContext);
//debug output to console
Console.WriteLine($"Skill: {skillName}\nFunction: {functionName}\nPrompt: {prompt}Answer: {result}");
workflowContext.SetResult(result);
SKContext answer = await kernel.RunAsync(context, function).ConfigureAwait(false);
string result = answer.Result;
Console.WriteLine(info);
workflowContext.SetResult(result);
}
}
}