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39
.claude/settings.local.json
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.dockerignore
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# Git
.git
.gitignore
.gitattributes
# Docker
docker-compose*.yml
Dockerfile
.dockerignore
.env
.env.*
# IDE
.vs
.vscode
.idea
*.user
*.suo
# Build outputs
**/bin/
**/obj/
**/out/
artifacts/
# NuGet
*.nupkg
*.snupkg
packages/
# Tests
**/TestResults/
# Documentation
# *.md (commented out - needed for build)
docs/
.github/
# Rider
.idea/
# OS
.DS_Store
Thumbs.db
# Scripts (not needed in container)
scripts/
# Docker configs (not needed in container)
docker/

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.env
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@ -1,30 +0,0 @@
# Langfuse API Keys (placeholder - will be generated after Langfuse UI setup)
# IMPORTANT: After running docker-compose up, go to http://localhost:3000
# Create an account, create a project, and copy the API keys here
LANGFUSE_PUBLIC_KEY=pk-lf-placeholder-replace-after-setup
LANGFUSE_SECRET_KEY=sk-lf-placeholder-replace-after-setup
# Langfuse Internal Configuration (auto-generated)
NEXTAUTH_SECRET=R3+DOKWiSpojMFKmD2/b0vNRedfWUaxantjEb/HVfQM=
SALT=xAuyPdjUGep0WRfVXqLDrU9TTELiWOr3AgmyIiS4STQ=
ENCRYPTION_KEY=91acdacf6b22ba4ad4dc5bec2a5fd0961ca89f161613a6b273162e0b5faaaffa
# Database Configuration
POSTGRES_USER=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_DB=postgres
# Connection Strings
CONNECTION_STRING_SVRNTY=Host=postgres;Database=svrnty;Username=postgres;Password=postgres;Include Error Detail=true
CONNECTION_STRING_LANGFUSE=postgresql://postgres:postgres@postgres:5432/langfuse
# Ollama Configuration
OLLAMA_BASE_URL=http://ollama:11434
OLLAMA_MODEL=qwen2.5-coder:7b
# API Configuration
ASPNETCORE_ENVIRONMENT=Production
ASPNETCORE_URLS=http://+:6001;http://+:6000
# Langfuse Endpoint
LANGFUSE_OTLP_ENDPOINT=http://langfuse:3000/api/public/otel/v1/traces

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.env.example
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@ -1,32 +0,0 @@
# Langfuse API Keys (placeholder - will be generated after Langfuse UI setup)
# IMPORTANT: After running docker-compose up, go to http://localhost:3000
# Create an account, create a project, and copy the API keys here
LANGFUSE_PUBLIC_KEY=pk-lf-placeholder-replace-after-setup
LANGFUSE_SECRET_KEY=sk-lf-placeholder-replace-after-setup
# Langfuse Internal Configuration (auto-generated)
# Generate these using: openssl rand -base64 32
NEXTAUTH_SECRET=REPLACE_WITH_RANDOM_SECRET
SALT=REPLACE_WITH_RANDOM_SALT
# Generate this using: openssl rand -hex 32
ENCRYPTION_KEY=REPLACE_WITH_RANDOM_ENCRYPTION_KEY
# Database Configuration
POSTGRES_USER=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_DB=postgres
# Connection Strings
CONNECTION_STRING_SVRNTY=Host=postgres;Database=svrnty;Username=postgres;Password=postgres;Include Error Detail=true
CONNECTION_STRING_LANGFUSE=postgresql://postgres:postgres@postgres:5432/langfuse
# Ollama Configuration
OLLAMA_BASE_URL=http://ollama:11434
OLLAMA_MODEL=qwen2.5-coder:7b
# API Configuration
ASPNETCORE_ENVIRONMENT=Production
ASPNETCORE_URLS=http://+:6001;http://+:6000
# Langfuse Endpoint
LANGFUSE_OTLP_ENDPOINT=http://langfuse:3000/api/public/otel/v1/traces

2
.gitea/workflows/publish-nugets.yaml
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@ -25,7 +25,7 @@ jobs:
- name: Setup .NET
uses: actions/setup-dotnet@v3
with:
dotnet-version: 10.x
dotnet-version: 8.x
- name: Restore dependencies
run: dotnet restore

38
.github/workflows/publish-nugets.yml vendored Normal file
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@ -0,0 +1,38 @@
# This workflow will build a .NET project
# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-net
name: Publish NuGets
on:
release:
types:
- published
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Extract Release Version
id: extract_version
run: echo "RELEASE_VERSION=${{ github.event.release.tag_name }}" >> $GITHUB_ENV
- name: Debug Release Version
run: echo "RELEASE_VERSION=${{ env.RELEASE_VERSION }}"
- name: Setup .NET
uses: actions/setup-dotnet@v3
with:
dotnet-version: 8.x
- name: Restore dependencies
run: dotnet restore
- name: Build and Pack NuGet Package
run: dotnet pack -c Release -o ./artifacts -p:Version=${{ env.RELEASE_VERSION }}
- name: Publish to NuGet.org
run: |
dotnet nuget push ./artifacts/*.nupkg --source https://api.nuget.org/v3/index.json --api-key ${{ secrets.NUGET_API_KEY }}

3
.gitignore vendored
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@ -5,9 +5,6 @@
.research/
# Environment variables with secrets
.env
# User-specific files
*.rsuser
*.suo

51
Dockerfile
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@ -1,51 +0,0 @@
# Build stage
FROM mcr.microsoft.com/dotnet/sdk:10.0-preview AS build
WORKDIR /src
# Copy solution file
COPY *.sln ./
# Copy all project files
COPY Svrnty.CQRS.Abstractions/*.csproj ./Svrnty.CQRS.Abstractions/
COPY Svrnty.CQRS/*.csproj ./Svrnty.CQRS/
COPY Svrnty.CQRS.MinimalApi/*.csproj ./Svrnty.CQRS.MinimalApi/
COPY Svrnty.CQRS.FluentValidation/*.csproj ./Svrnty.CQRS.FluentValidation/
COPY Svrnty.CQRS.DynamicQuery.Abstractions/*.csproj ./Svrnty.CQRS.DynamicQuery.Abstractions/
COPY Svrnty.CQRS.DynamicQuery/*.csproj ./Svrnty.CQRS.DynamicQuery/
COPY Svrnty.CQRS.DynamicQuery.MinimalApi/*.csproj ./Svrnty.CQRS.DynamicQuery.MinimalApi/
COPY Svrnty.CQRS.Grpc.Abstractions/*.csproj ./Svrnty.CQRS.Grpc.Abstractions/
COPY Svrnty.CQRS.Grpc/*.csproj ./Svrnty.CQRS.Grpc/
COPY Svrnty.CQRS.Grpc.Generators/*.csproj ./Svrnty.CQRS.Grpc.Generators/
COPY Svrnty.Sample/*.csproj ./Svrnty.Sample/
# Restore dependencies
RUN dotnet restore
# Copy all source files
COPY . .
# Build and publish
WORKDIR /src/Svrnty.Sample
RUN dotnet publish -c Release -o /app/publish --no-restore
# Runtime stage
FROM mcr.microsoft.com/dotnet/aspnet:10.0-preview AS runtime
WORKDIR /app
# Install curl for health checks
RUN apt-get update && \
apt-get install -y --no-install-recommends curl && \
rm -rf /var/lib/apt/lists/*
# Copy published application
COPY --from=build /app/publish .
# Expose ports
EXPOSE 6000 6001
# Set environment variables
ENV ASPNETCORE_URLS=http://+:6001;http://+:6000
ENV ASPNETCORE_ENVIRONMENT=Production
# Run the application
ENTRYPOINT ["dotnet", "Svrnty.Sample.dll"]

205
README.md
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@ -3,6 +3,7 @@
# CQRS
Our implementation of query and command responsibility segregation (CQRS).
## Getting Started
> Install nuget package to your awesome project.
@ -11,9 +12,10 @@ Our implementation of query and command responsibility segregation (CQRS).
|-----------------------------------------| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |-----------------------------------------------------------------------:|
| Svrnty.CQRS | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS/) | ```dotnet add package Svrnty.CQRS ``` |
| Svrnty.CQRS.MinimalApi | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.MinimalApi.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.MinimalApi/) | ```dotnet add package Svrnty.CQRS.MinimalApi ``` |
| Svrnty.CQRS.AspNetCore | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.AspNetCore.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.AspNetCore/) | ```dotnet add package Svrnty.CQRS.AspNetCore ``` |
| Svrnty.CQRS.FluentValidation | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.FluentValidation.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.FluentValidation/) | ```dotnet add package Svrnty.CQRS.FluentValidation ``` |
| Svrnty.CQRS.DynamicQuery | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.DynamicQuery.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.DynamicQuery/) | ```dotnet add package Svrnty.CQRS.DynamicQuery ``` |
| Svrnty.CQRS.DynamicQuery.MinimalApi | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.DynamicQuery.MinimalApi.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.DynamicQuery.MinimalApi/) | ```dotnet add package Svrnty.CQRS.DynamicQuery.MinimalApi ``` |
| Svrnty.CQRS.DynamicQuery.AspNetCore | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.DynamicQuery.AspNetCore.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.DynamicQuery.AspNetCore/) | ```dotnet add package Svrnty.CQRS.DynamicQuery.AspNetCore ``` |
| Svrnty.CQRS.Grpc | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.Grpc.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.Grpc/) | ```dotnet add package Svrnty.CQRS.Grpc ``` |
| Svrnty.CQRS.Grpc.Generators | [![NuGet](https://img.shields.io/nuget/v/Svrnty.CQRS.Grpc.Generators.svg?style=flat-square&label=nuget)](https://www.nuget.org/packages/Svrnty.CQRS.Grpc.Generators/) | ```dotnet add package Svrnty.CQRS.Grpc.Generators ``` |
@ -29,33 +31,28 @@ Our implementation of query and command responsibility segregation (CQRS).
## Sample of startup code for gRPC (Recommended)
```csharp
using Svrnty.CQRS;
using Svrnty.CQRS.FluentValidation;
using Svrnty.CQRS.Grpc;
var builder = WebApplication.CreateBuilder(args);
// Register your commands with validators
builder.Services.AddCommand<AddUserCommand, int, AddUserCommandHandler, AddUserCommandValidator>();
builder.Services.AddCommand<RemoveUserCommand, RemoveUserCommandHandler>();
// Register CQRS core services
builder.Services.AddSvrntyCQRS();
builder.Services.AddDefaultCommandDiscovery();
builder.Services.AddDefaultQueryDiscovery();
// Register your queries
builder.Services.AddQuery<FetchUserQuery, User, FetchUserQueryHandler>();
// Add your commands and queries
AddQueries(builder.Services);
AddCommands(builder.Services);
// Configure CQRS with gRPC support
builder.Services.AddSvrntyCqrs(cqrs =>
{
// Enable gRPC endpoints with reflection
cqrs.AddGrpc(grpc =>
{
grpc.EnableReflection();
});
});
// Add gRPC support
builder.Services.AddGrpc();
var app = builder.Build();
// Map all configured CQRS endpoints
app.UseSvrntyCqrs();
// Map auto-generated gRPC service implementations
app.MapGrpcService<CommandServiceImpl>();
app.MapGrpcService<QueryServiceImpl>();
// Enable gRPC reflection for tools like grpcurl
app.MapGrpcReflectionService();
app.Run();
```
@ -78,9 +75,31 @@ dotnet add package Grpc.StatusProto # For Rich Error Model validation
dotnet add package Svrnty.CQRS.Grpc.Generators
```
The source generator is automatically configured as an analyzer when installed via NuGet and will generate both the `.proto` files and gRPC service implementations at compile time.
The source generator is automatically configured as an analyzer when installed via NuGet and will generate the gRPC service implementations at compile time.
#### 3. Define your C# commands and queries:
#### 3. Define your proto files in `Protos/` directory:
```protobuf
syntax = "proto3";
import "google/protobuf/empty.proto";
service CommandService {
rpc AddUser(AddUserCommandRequest) returns (AddUserCommandResponse);
rpc RemoveUser(RemoveUserCommandRequest) returns (google.protobuf.Empty);
}
message AddUserCommandRequest {
string name = 1;
string email = 2;
int32 age = 3;
}
message AddUserCommandResponse {
int32 result = 1;
}
```
#### 4. Define your C# commands matching the proto structure:
```csharp
public record AddUserCommand
@ -97,38 +116,28 @@ public record RemoveUserCommand
```
**Notes:**
- The source generator automatically creates:
- `.proto` files in the `Protos/` directory from your C# commands and queries
- `CommandServiceImpl` and `QueryServiceImpl` implementations
- The source generator automatically creates `CommandServiceImpl` and `QueryServiceImpl` implementations
- Property names in C# commands must match proto field names (case-insensitive)
- FluentValidation is automatically integrated with **Google Rich Error Model** for structured validation errors
- Validation errors return `google.rpc.Status` with `BadRequest` containing `FieldViolations`
- Use `record` types for commands/queries (immutable, value-based equality, more concise)
- No need for protobuf-net attributes - just define your C# types
- No need for protobuf-net attributes
## Sample of startup code for Minimal API (HTTP)
For HTTP scenarios (web browsers, public APIs), you can use the Minimal API approach:
```csharp
using Svrnty.CQRS;
using Svrnty.CQRS.FluentValidation;
using Svrnty.CQRS.MinimalApi;
var builder = WebApplication.CreateBuilder(args);
// Register your commands with validators
builder.Services.AddCommand<CreatePersonCommand, CreatePersonCommandHandler, CreatePersonCommandValidator>();
builder.Services.AddCommand<EchoCommand, string, EchoCommandHandler, EchoCommandValidator>();
// Register CQRS core services
builder.Services.AddSvrntyCQRS();
builder.Services.AddDefaultCommandDiscovery();
builder.Services.AddDefaultQueryDiscovery();
// Register your queries
builder.Services.AddQuery<PersonQuery, IQueryable<Person>, PersonQueryHandler>();
// Configure CQRS with Minimal API support
builder.Services.AddSvrntyCqrs(cqrs =>
{
// Enable Minimal API endpoints
cqrs.AddMinimalApi();
});
// Add your commands and queries
AddQueries(builder.Services);
AddCommands(builder.Services);
// Add Swagger (optional)
builder.Services.AddEndpointsApiExplorer();
@ -142,8 +151,9 @@ if (app.Environment.IsDevelopment())
app.UseSwaggerUI();
}
// Map all configured CQRS endpoints (automatically creates POST /api/command/* and POST/GET /api/query/*)
app.UseSvrntyCqrs();
// Map CQRS endpoints - automatically creates routes for all commands and queries
app.MapSvrntyCommands(); // Creates POST /api/command/{commandName} endpoints
app.MapSvrntyQueries(); // Creates POST/GET /api/query/{queryName} endpoints
app.Run();
```
@ -159,32 +169,19 @@ app.Run();
You can enable both gRPC and traditional HTTP endpoints simultaneously, allowing clients to choose their preferred protocol:
```csharp
using Svrnty.CQRS;
using Svrnty.CQRS.FluentValidation;
using Svrnty.CQRS.Grpc;
using Svrnty.CQRS.MinimalApi;
var builder = WebApplication.CreateBuilder(args);
// Register your commands with validators
builder.Services.AddCommand<AddUserCommand, int, AddUserCommandHandler, AddUserCommandValidator>();
builder.Services.AddCommand<RemoveUserCommand, RemoveUserCommandHandler>();
// Register CQRS core services
builder.Services.AddSvrntyCQRS();
builder.Services.AddDefaultCommandDiscovery();
builder.Services.AddDefaultQueryDiscovery();
// Register your queries
builder.Services.AddQuery<FetchUserQuery, User, FetchUserQueryHandler>();
// Add your commands and queries
AddQueries(builder.Services);
AddCommands(builder.Services);
// Configure CQRS with both gRPC and Minimal API support
builder.Services.AddSvrntyCqrs(cqrs =>
{
// Enable gRPC endpoints with reflection
cqrs.AddGrpc(grpc =>
{
grpc.EnableReflection();
});
// Enable Minimal API endpoints
cqrs.AddMinimalApi();
});
// Add gRPC support
builder.Services.AddGrpc();
// Add HTTP support with Swagger
builder.Services.AddEndpointsApiExplorer();
@ -198,8 +195,14 @@ if (app.Environment.IsDevelopment())
app.UseSwaggerUI();
}
// Map all configured CQRS endpoints (both gRPC and HTTP)
app.UseSvrntyCqrs();
// Map gRPC endpoints
app.MapGrpcService<CommandServiceImpl>();
app.MapGrpcService<QueryServiceImpl>();
app.MapGrpcReflectionService();
// Map HTTP endpoints
app.MapSvrntyCommands();
app.MapSvrntyQueries();
app.Run();
```
@ -211,10 +214,47 @@ app.Run();
- Same commands, queries, and validation logic for both protocols
- Swagger UI available for HTTP endpoints, gRPC reflection for gRPC clients
> Example how to add your queries and commands.
```csharp
private void AddCommands(IServiceCollection services)
{
services.AddCommand<CreatePersonCommand, CreatePersonCommandHandler>();
services.AddTransient<IValidator<CreatePersonCommand>, CreatePersonCommandValidator>();
services.AddCommand<EchoCommand, string, EchoCommandHandler>();
services.AddTransient<IValidator<EchoCommand>, EchoCommandValidator>();
}
private void AddQueries(IServiceCollection services)
{
services.AddQuery<PersonQuery, IQueryable<Person>, PersonQueryHandler>();
}
```
# Fluent Validation
FluentValidation is optional but recommended for command and query validation. The `Svrnty.CQRS.FluentValidation` package provides extension methods to simplify validator registration.
## Without Svrnty.CQRS.FluentValidation
You need to register commands and validators separately:
```csharp
using Microsoft.Extensions.DependencyInjection;
using FluentValidation;
using Svrnty.CQRS;
private void AddCommands(IServiceCollection services)
{
// Register command handler
services.AddCommand<EchoCommand, string, EchoCommandHandler>();
// Manually register validator
services.AddTransient<IValidator<EchoCommand>, EchoCommandValidator>();
}
```
## With Svrnty.CQRS.FluentValidation (Recommended)
The package exposes extension method overloads that accept the validator as a generic parameter:
@ -224,13 +264,17 @@ dotnet add package Svrnty.CQRS.FluentValidation
```
```csharp
using Microsoft.Extensions.DependencyInjection;
using Svrnty.CQRS.FluentValidation; // Extension methods for validator registration
// Command with result - validator as last generic parameter
builder.Services.AddCommand<EchoCommand, string, EchoCommandHandler, EchoCommandValidator>();
private void AddCommands(IServiceCollection services)
{
// Command without result - validator included in generics
services.AddCommand<EchoCommand, string, EchoCommandHandler, EchoCommandValidator>();
// Command without result - validator included in generics
builder.Services.AddCommand<CreatePersonCommand, CreatePersonCommandHandler, CreatePersonCommandValidator>();
// Command with result - validator as last generic parameter
services.AddCommand<CreatePersonCommand, CreatePersonCommandHandler, CreatePersonCommandValidator>();
}
```
**Benefits:**
@ -239,21 +283,6 @@ builder.Services.AddCommand<CreatePersonCommand, CreatePersonCommandHandler, Cre
- **Less boilerplate** - No need for separate `AddTransient<IValidator<T>>()` calls
- **Cleaner code** - Clear intent that validation is part of command pipeline
## Without Svrnty.CQRS.FluentValidation
If you prefer not to use the FluentValidation package, you need to register commands and validators separately:
```csharp
using FluentValidation;
using Svrnty.CQRS;
// Register command handler
builder.Services.AddCommand<EchoCommand, string, EchoCommandHandler>();
// Manually register validator
builder.Services.AddTransient<IValidator<EchoCommand>, EchoCommandValidator>();
```
# 2024-2025 Roadmap
| Task | Description | Status |

2
Svrnty.CQRS.Abstractions/Svrnty.CQRS.Abstractions.csproj
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@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>true</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

2
Svrnty.CQRS.DynamicQuery.Abstractions/Svrnty.CQRS.DynamicQuery.Abstractions.csproj
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@ -3,7 +3,7 @@
<TargetFrameworks>netstandard2.1;net10.0</TargetFrameworks>
<IsAotCompatible Condition="$([MSBuild]::IsTargetFrameworkCompatible('$(TargetFramework)', 'net10.0'))">true</IsAotCompatible>
<Nullable>enable</Nullable>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Company>Svrnty</Company>
<Authors>David Lebee, Mathias Beaulieu-Duncan</Authors>

2
Svrnty.CQRS.DynamicQuery.MinimalApi/Svrnty.CQRS.DynamicQuery.MinimalApi.csproj
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@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>false</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

2
Svrnty.CQRS.DynamicQuery/Svrnty.CQRS.DynamicQuery.csproj
View File

@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>true</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

2
Svrnty.CQRS.FluentValidation/Svrnty.CQRS.FluentValidation.csproj
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@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>true</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

2
Svrnty.CQRS.Grpc.Abstractions/Svrnty.CQRS.Grpc.Abstractions.csproj
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@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>true</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

35
Svrnty.CQRS.Grpc.Generators/Svrnty.CQRS.Grpc.Generators.csproj
View File

@ -1,16 +1,13 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>netstandard2.0</TargetFramework>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<IsRoslynComponent>true</IsRoslynComponent>
<EnforceExtendedAnalyzerRules>true</EnforceExtendedAnalyzerRules>
<IsPackable>true</IsPackable>
<DevelopmentDependency>true</DevelopmentDependency>
<!-- Don't include build output in lib/ - this is an analyzer/generator package -->
<IncludeBuildOutput>false</IncludeBuildOutput>
<NoPackageAnalysis>true</NoPackageAnalysis>
<NoWarn>$(NoWarn);NU5128</NoWarn>
<SuppressDependenciesWhenPacking>true</SuppressDependenciesWhenPacking>
<Company>Svrnty</Company>
@ -23,8 +20,11 @@
<PackageLicenseExpression>MIT</PackageLicenseExpression>
<Description>Source Generator for Svrnty.CQRS.Grpc - generates .proto files and gRPC service implementations from commands and queries</Description>
<!-- Disable symbol packages for analyzer/generator packages (prevents NU5017 error) -->
<IncludeSymbols>false</IncludeSymbols>
<DebugType>portable</DebugType>
<DebugSymbols>true</DebugSymbols>
<IncludeSymbols>true</IncludeSymbols>
<IncludeSource>true</IncludeSource>
<SymbolPackageFormat>snupkg</SymbolPackageFormat>
</PropertyGroup>
<ItemGroup>
@ -39,24 +39,11 @@
</ItemGroup>
<ItemGroup>
<!-- Include targets and props files in both build and buildTransitive for proper dependency flow -->
<!-- Package as analyzer -->
<None Include="$(OutputPath)\$(AssemblyName).dll" Pack="true" PackagePath="analyzers/dotnet/cs" Visible="false" />
<!-- Also package as build task -->
<None Include="$(OutputPath)\$(AssemblyName).dll" Pack="true" PackagePath="build" Visible="false" />
<None Include="build\Svrnty.CQRS.Grpc.Generators.targets" Pack="true" PackagePath="build" />
<None Include="build\Svrnty.CQRS.Grpc.Generators.targets" Pack="true" PackagePath="buildTransitive" />
<None Include="build\Svrnty.CQRS.Grpc.Generators.props" Pack="true" PackagePath="build" />
<None Include="build\Svrnty.CQRS.Grpc.Generators.props" Pack="true" PackagePath="buildTransitive" />
</ItemGroup>
<!-- Use the recommended pattern to include the generator DLL in the package -->
<PropertyGroup>
<TargetsForTfmSpecificContentInPackage>$(TargetsForTfmSpecificContentInPackage);IncludeGeneratorAssemblyInPackage</TargetsForTfmSpecificContentInPackage>
</PropertyGroup>
<Target Name="IncludeGeneratorAssemblyInPackage">
<ItemGroup>
<!-- Include in analyzers folder for Roslyn source generator -->
<TfmSpecificPackageFile Include="$(OutputPath)$(AssemblyName).dll" PackagePath="analyzers/dotnet/cs" />
<!-- Include in build folder for MSBuild task (WriteProtoFileTask) -->
<TfmSpecificPackageFile Include="$(OutputPath)$(AssemblyName).dll" PackagePath="build" />
</ItemGroup>
</Target>
</Project>

6
Svrnty.CQRS.Grpc.Generators/build/Svrnty.CQRS.Grpc.Generators.props
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@ -1,6 +0,0 @@
<Project>
<PropertyGroup>
<!-- Marker to indicate Svrnty.CQRS.Grpc.Generators is referenced -->
<SvrntyCqrsGrpcGeneratorsVersion>$(SvrntyCqrsGrpcGeneratorsVersion)</SvrntyCqrsGrpcGeneratorsVersion>
</PropertyGroup>
</Project>

2
Svrnty.CQRS.Grpc/Svrnty.CQRS.Grpc.csproj
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@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>false</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

2
Svrnty.CQRS.MinimalApi/Svrnty.CQRS.MinimalApi.csproj
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@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>false</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

2
Svrnty.CQRS/Svrnty.CQRS.csproj
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@ -2,7 +2,7 @@
<PropertyGroup>
<TargetFramework>net10.0</TargetFramework>
<IsAotCompatible>true</IsAotCompatible>
<LangVersion>preview</LangVersion>
<LangVersion>14</LangVersion>
<Nullable>enable</Nullable>
<Company>Svrnty</Company>

17
Svrnty.Sample/AI/Commands/ExecuteAgentCommand.cs
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@ -1,17 +0,0 @@
using Svrnty.CQRS.Grpc.Abstractions.Attributes;
namespace Svrnty.Sample.AI.Commands;
/// <summary>
/// Command to execute an AI agent with a user prompt
/// </summary>
/// <param name="Prompt">The user's input prompt for the AI agent</param>
[GrpcIgnore] // MVP: HTTP-only endpoint, gRPC support can be added later
public record ExecuteAgentCommand(string Prompt);
/// <summary>
/// Response from the AI agent execution
/// </summary>
/// <param name="Content">The AI agent's response content</param>
/// <param name="ConversationId">Unique identifier for this conversation</param>
public record AgentResponse(string Content, Guid ConversationId);

245
Svrnty.Sample/AI/Commands/ExecuteAgentCommandHandler.cs
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@ -1,245 +0,0 @@
using System.Text.Json;
using Microsoft.Extensions.AI;
using Svrnty.CQRS.Abstractions;
using Svrnty.Sample.AI.Tools;
using Svrnty.Sample.Data;
using Svrnty.Sample.Data.Entities;
namespace Svrnty.Sample.AI.Commands;
/// <summary>
/// Handler for executing AI agent commands with function calling support and Langfuse HTTP observability
/// </summary>
public class ExecuteAgentCommandHandler(
IChatClient chatClient,
AgentDbContext dbContext,
MathTool mathTool,
DatabaseQueryTool dbTool,
ILogger<ExecuteAgentCommandHandler> logger,
LangfuseHttpClient langfuseClient) : ICommandHandler<ExecuteAgentCommand, AgentResponse>
{
private const int MaxFunctionCallIterations = 10; // Prevent infinite loops
public async Task<AgentResponse> HandleAsync(
ExecuteAgentCommand command,
CancellationToken cancellationToken = default)
{
var conversationId = Guid.NewGuid();
// Start Langfuse trace (if enabled)
LangfuseTrace? trace = null;
if (langfuseClient.IsEnabled)
{
trace = await langfuseClient.CreateTraceAsync("agent-execution", "system");
trace.SetInput(command.Prompt);
trace.SetMetadata(new Dictionary<string, object>
{
["conversation_id"] = conversationId.ToString(),
["model"] = "qwen2.5-coder:7b"
});
}
try
{
var messages = new List<ChatMessage>
{
new(ChatRole.User, command.Prompt)
};
// Register available tools
var tools = new List<AIFunction>
{
AIFunctionFactory.Create(mathTool.Add),
AIFunctionFactory.Create(mathTool.Multiply),
AIFunctionFactory.Create(dbTool.GetMonthlyRevenue),
AIFunctionFactory.Create(dbTool.GetRevenueRange),
AIFunctionFactory.Create(dbTool.CountCustomersByState),
AIFunctionFactory.Create(dbTool.CountCustomersByTier),
AIFunctionFactory.Create(dbTool.GetCustomers)
};
// Log tool registration to Langfuse
if (trace != null)
{
using var toolSpan = trace.CreateSpan("tools-register");
toolSpan.SetMetadata(new Dictionary<string, object>
{
["tools_count"] = tools.Count,
["tools_names"] = string.Join(",", tools.Select(t => t.Metadata.Name))
});
}
var options = new ChatOptions
{
ModelId = "qwen2.5-coder:7b",
Tools = tools.Cast<AITool>().ToList()
};
var functionLookup = tools.ToDictionary(
f => f.Metadata.Name,
f => f,
StringComparer.OrdinalIgnoreCase
);
// Initial AI completion
ChatCompletion completion;
try
{
catch { }
if (trace != null)
{
using var generation = trace.CreateGeneration("llm-completion-0");
generation.SetInput(command.Prompt);
completion = await chatClient.CompleteAsync(messages, options, cancellationToken);
messages.Add(completion.Message);
generation.SetOutput(completion.Message.Text ?? "");
generation.SetMetadata(new Dictionary<string, object>
{
["iteration"] = 0,
["has_function_calls"] = completion.Message.Contents.OfType<FunctionCallContent>().Any()
});
}
else
{
completion = await chatClient.CompleteAsync(messages, options, cancellationToken);
messages.Add(completion.Message);
}
try
{
catch { }
// Function calling loop
var iterations = 0;
while (completion.Message.Contents.OfType<FunctionCallContent>().Any()
&& iterations < MaxFunctionCallIterations)
{
iterations++;
foreach (var functionCall in completion.Message.Contents.OfType<FunctionCallContent>())
{
object? funcResult = null;
string? funcError = null;
try
{
if (!functionLookup.TryGetValue(functionCall.Name, out var function))
{
throw new InvalidOperationException($"Function '{functionCall.Name}' not found");
}
funcResult = await function.InvokeAsync(functionCall.Arguments, cancellationToken);
var toolMessage = new ChatMessage(ChatRole.Tool, funcResult?.ToString() ?? "null");
toolMessage.Contents.Add(new FunctionResultContent(functionCall.CallId, functionCall.Name, funcResult));
messages.Add(toolMessage);
}
catch (Exception ex)
{
funcError = ex.Message;
var errorMessage = new ChatMessage(ChatRole.Tool, $"Error: {ex.Message}");
errorMessage.Contents.Add(new FunctionResultContent(functionCall.CallId, functionCall.Name, $"Error: {ex.Message}"));
messages.Add(errorMessage);
}
// Log function call to Langfuse
if (trace != null)
{
using var funcSpan = trace.CreateSpan($"function-{functionCall.Name}");
funcSpan.SetMetadata(new Dictionary<string, object>
{
["function_name"] = functionCall.Name,
["arguments"] = JsonSerializer.Serialize(functionCall.Arguments),
["result"] = funcResult?.ToString() ?? "null",
["success"] = funcError == null,
["error"] = funcError ?? ""
});
}
}
// Next LLM completion after function calls
if (trace != null)
{
using var nextGeneration = trace.CreateGeneration($"llm-completion-{iterations}");
nextGeneration.SetInput(JsonSerializer.Serialize(messages.TakeLast(5)));
completion = await chatClient.CompleteAsync(messages, options, cancellationToken);
messages.Add(completion.Message);
nextGeneration.SetOutput(completion.Message.Text ?? "");
nextGeneration.SetMetadata(new Dictionary<string, object>
{
["iteration"] = iterations,
["has_function_calls"] = completion.Message.Contents.OfType<FunctionCallContent>().Any()
});
}
else
{
completion = await chatClient.CompleteAsync(messages, options, cancellationToken);
messages.Add(completion.Message);
}
}
// Store conversation in database
var conversation = new Conversation
{
Id = conversationId,
Messages = messages.Select(m => new ConversationMessage
{
Role = m.Role.ToString(),
Content = m.Text ?? string.Empty,
Timestamp = DateTime.UtcNow
}).ToList()
};
dbContext.Conversations.Add(conversation);
await dbContext.SaveChangesAsync(cancellationToken);
// Update trace with final output and flush to Langfuse
if (trace != null)
{
trace.SetOutput(completion.Message.Text ?? "No response");
trace.SetMetadata(new Dictionary<string, object>
{
["success"] = true,
["iterations"] = iterations,
["conversation_id"] = conversationId.ToString()
});
await trace.FlushAsync();
}
logger.LogInformation("Agent executed successfully for conversation {ConversationId}", conversationId);
try
{
catch { }
return new AgentResponse(
Content: completion.Message.Text ?? "No response",
ConversationId: conversationId
);
}
catch (Exception ex)
{
try
{
catch { }
// Update trace with error and flush to Langfuse
if (trace != null)
{
trace.SetOutput($"Error: {ex.Message}");
trace.SetMetadata(new Dictionary<string, object>
{
["success"] = false,
["error_type"] = ex.GetType().Name,
["error_message"] = ex.Message
});
await trace.FlushAsync();
}
logger.LogError(ex, "Agent execution failed for conversation {ConversationId}", conversationId);
throw;
}
}
}

336
Svrnty.Sample/AI/LangfuseHttpClient.cs
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@ -1,336 +0,0 @@
using System.Text;
using System.Text.Json;
using System.Text.Json.Serialization;
namespace Svrnty.Sample.AI;
/// <summary>
/// Simple HTTP client for sending traces directly to Langfuse ingestion API
/// </summary>
public class LangfuseHttpClient
{
private readonly HttpClient _httpClient;
private readonly string _publicKey;
private readonly string _secretKey;
private readonly bool _enabled;
public LangfuseHttpClient(HttpClient httpClient, IConfiguration configuration)
{
_httpClient = httpClient;
_publicKey = configuration["Langfuse:PublicKey"] ?? "";
_secretKey = configuration["Langfuse:SecretKey"] ?? "";
_enabled = !string.IsNullOrEmpty(_publicKey) && !string.IsNullOrEmpty(_secretKey);
_ = Console.Out.WriteLineAsync($"[Langfuse] Initialized: Enabled={_enabled}, PublicKey={(_publicKey.Length > 0 ? "present" : "missing")}, SecretKey={(_secretKey.Length > 0 ? "present" : "missing")}");
}
public bool IsEnabled => _enabled;
public async Task<LangfuseTrace> CreateTraceAsync(string name, string userId = "system")
{
return new LangfuseTrace(this, name, userId);
}
internal async Task SendBatchAsync(List<LangfuseEvent> events)
{
// File-based debug logging
try
{
await File.AppendAllTextAsync("/tmp/langfuse_debug.log",
$"{DateTime.UtcNow:O} [SendBatchAsync] Called: Enabled={_enabled}, Events={events.Count}\n");
}
catch { }
if (!_enabled || events.Count == 0) return;
try
{
var batch = new { batch = events };
var json = JsonSerializer.Serialize(batch, new JsonSerializerOptions
{
PropertyNamingPolicy = JsonNamingPolicy.CamelCase,
DefaultIgnoreCondition = JsonIgnoreCondition.WhenWritingNull
});
_ = Console.Out.WriteLineAsync($"[Langfuse] Sending {events.Count} events to {_httpClient.BaseAddress}/api/public/ingestion");
var request = new HttpRequestMessage(HttpMethod.Post, "/api/public/ingestion")
{
Content = new StringContent(json, Encoding.UTF8, "application/json")
};
// Basic Auth with public/secret keys
var authBytes = Encoding.UTF8.GetBytes($"{_publicKey}:{_secretKey}");
request.Headers.Authorization = new System.Net.Http.Headers.AuthenticationHeaderValue(
"Basic", Convert.ToBase64String(authBytes));
var response = await _httpClient.SendAsync(request);
response.EnsureSuccessStatusCode();
_ = Console.Out.WriteLineAsync($"[Langfuse] Successfully sent batch, status: {response.StatusCode}");
}
catch (Exception ex)
{
// Log but don't throw - tracing shouldn't break the application
_ = Console.Out.WriteLineAsync($"[Langfuse] Failed to send trace: {ex.Message}");
_ = Console.Out.WriteLineAsync($"[Langfuse] Stack trace: {ex.StackTrace}");
}
}
}
/// <summary>
/// Represents a Langfuse trace that can contain multiple observations
/// </summary>
public class LangfuseTrace
{
private readonly LangfuseHttpClient _client;
private readonly string _traceId;
private readonly List<LangfuseEvent> _events = new();
private string? _input;
private string? _output;
private Dictionary<string, object>? _metadata;
internal LangfuseTrace(LangfuseHttpClient client, string name, string userId)
{
_client = client;
_traceId = Guid.NewGuid().ToString();
_events.Add(new LangfuseEvent
{
Id = _traceId,
Type = "trace-create",
Timestamp = DateTime.UtcNow,
Body = new Dictionary<string, object>
{
["id"] = _traceId,
["name"] = name,
["userId"] = userId,
["timestamp"] = DateTime.UtcNow
}
});
}
public string TraceId => _traceId;
public void SetInput(object input)
{
_input = input is string s ? s : JsonSerializer.Serialize(input);
}
public void SetOutput(object output)
{
_output = output is string s ? s : JsonSerializer.Serialize(output);
}
public void SetMetadata(Dictionary<string, object> metadata)
{
_metadata = metadata;
}
public LangfuseSpan CreateSpan(string name)
{
return new LangfuseSpan(this, name);
}
public LangfuseGeneration CreateGeneration(string name, string model = "qwen2.5-coder:7b")
{
return new LangfuseGeneration(this, name, model);
}
internal void AddEvent(LangfuseEvent evt)
{
_events.Add(evt);
}
public async Task FlushAsync()
{
// File-based debug logging
try
{
await File.AppendAllTextAsync("/tmp/langfuse_debug.log",
$"{DateTime.UtcNow:O} [FlushAsync] Called: Events={_events.Count}, HasInput={_input != null}, HasOutput={_output != null}, Enabled={_client.IsEnabled}\n");
}
catch { }
// Update trace with final input/output
if (_input != null || _output != null || _metadata != null)
{
var updateBody = new Dictionary<string, object> { ["id"] = _traceId };
if (_input != null) updateBody["input"] = _input;
if (_output != null) updateBody["output"] = _output;
if (_metadata != null) updateBody["metadata"] = _metadata;
_events.Add(new LangfuseEvent
{
Id = Guid.NewGuid().ToString(),
Type = "trace-create", // Langfuse uses same type for updates
Timestamp = DateTime.UtcNow,
Body = updateBody
});
}
await _client.SendBatchAsync(_events);
}
}
/// <summary>
/// Represents a span (operation) within a trace
/// </summary>
public class LangfuseSpan : IDisposable
{
private readonly LangfuseTrace _trace;
private readonly string _spanId;
private readonly DateTime _startTime;
private object? _output;
private Dictionary<string, object>? _metadata;
internal LangfuseSpan(LangfuseTrace trace, string name)
{
_trace = trace;
_spanId = Guid.NewGuid().ToString();
_startTime = DateTime.UtcNow;
_trace.AddEvent(new LangfuseEvent
{
Id = _spanId,
Type = "span-create",
Timestamp = _startTime,
Body = new Dictionary<string, object>
{
["id"] = _spanId,
["traceId"] = trace.TraceId,
["name"] = name,
["startTime"] = _startTime
}
});
}
public void SetOutput(object output)
{
_output = output;
}
public void SetMetadata(Dictionary<string, object> metadata)
{
_metadata = metadata;
}
public void Dispose()
{
var updateBody = new Dictionary<string, object>
{
["id"] = _spanId,
["endTime"] = DateTime.UtcNow
};
if (_output != null)
updateBody["output"] = _output is string s ? s : JsonSerializer.Serialize(_output);
if (_metadata != null)
updateBody["metadata"] = _metadata;
_trace.AddEvent(new LangfuseEvent
{
Id = Guid.NewGuid().ToString(),
Type = "span-update",
Timestamp = DateTime.UtcNow,
Body = updateBody
});
}
}
/// <summary>
/// Represents an LLM generation within a trace
/// </summary>
public class LangfuseGeneration : IDisposable
{
private readonly LangfuseTrace _trace;
private readonly string _generationId;
private readonly DateTime _startTime;
private readonly string _model;
private object? _input;
private object? _output;
private Dictionary<string, object>? _metadata;
internal LangfuseGeneration(LangfuseTrace trace, string name, string model)
{
_trace = trace;
_generationId = Guid.NewGuid().ToString();
_startTime = DateTime.UtcNow;
_model = model;
_trace.AddEvent(new LangfuseEvent
{
Id = _generationId,
Type = "generation-create",
Timestamp = _startTime,
Body = new Dictionary<string, object>
{
["id"] = _generationId,
["traceId"] = trace.TraceId,
["name"] = name,
["model"] = model,
["startTime"] = _startTime
}
});
}
public void SetInput(object input)
{
_input = input;
}
public void SetOutput(object output)
{
_output = output;
}
public void SetMetadata(Dictionary<string, object> metadata)
{
_metadata = metadata;
}
public void Dispose()
{
var updateBody = new Dictionary<string, object>
{
["id"] = _generationId,
["endTime"] = DateTime.UtcNow
};
if (_input != null)
updateBody["input"] = _input is string s ? s : JsonSerializer.Serialize(_input);
if (_output != null)
updateBody["output"] = _output is string o ? o : JsonSerializer.Serialize(_output);
if (_metadata != null)
updateBody["metadata"] = _metadata;
_trace.AddEvent(new LangfuseEvent
{
Id = Guid.NewGuid().ToString(),
Type = "generation-update",
Timestamp = DateTime.UtcNow,
Body = updateBody
});
}
}
/// <summary>
/// Internal event format for Langfuse ingestion API
/// </summary>
internal class LangfuseEvent
{
[JsonPropertyName("id")]
public string Id { get; set; } = "";
[JsonPropertyName("type")]
public string Type { get; set; } = "";
[JsonPropertyName("timestamp")]
public DateTime Timestamp { get; set; }
[JsonPropertyName("body")]
public Dictionary<string, object> Body { get; set; } = new();
}

185
Svrnty.Sample/AI/OllamaClient.cs
View File

@ -1,185 +0,0 @@
using System.Diagnostics;
using Microsoft.Extensions.AI;
using System.Text.Json;
namespace Svrnty.Sample.AI;
public sealed class OllamaClient(HttpClient http) : IChatClient
{
private static readonly ActivitySource ActivitySource = new("Svrnty.AI.Ollama");
public ChatClientMetadata Metadata => new("ollama", new Uri("http://localhost:11434"));
public async Task<ChatCompletion> CompleteAsync(
IList<ChatMessage> messages,
ChatOptions? options = null,
CancellationToken cancellationToken = default)
{
using var activity = ActivitySource.StartActivity("ollama.chat", ActivityKind.Client);
activity?.SetTag("ollama.model", options?.ModelId ?? "qwen2.5-coder:7b");
activity?.SetTag("ollama.message_count", messages.Count);
activity?.SetTag("ollama.has_tools", options?.Tools?.Any() ?? false);
var startTime = DateTime.UtcNow;
// Build messages array including tool results
var ollamaMessages = messages.Select(m => new
{
role = m.Role.ToString().ToLower(),
content = m.Text ?? string.Empty,
tool_call_id = m.Contents.OfType<FunctionResultContent>().FirstOrDefault()?.CallId
}).ToList();
// Build payload with optional tools
var payload = new Dictionary<string, object>
{
["model"] = options?.ModelId ?? "qwen2.5-coder:7b",
["messages"] = ollamaMessages,
["stream"] = false
};
// Add tools if provided
if (options?.Tools is { Count: > 0 })
{
payload["tools"] = options.Tools.Select(BuildToolDefinition).ToArray();
}
var response = await http.PostAsJsonAsync("/api/chat", payload, cancellationToken);
response.EnsureSuccessStatusCode();
var json = await response.Content.ReadFromJsonAsync<JsonDocument>(cancellationToken);
var messageElement = json!.RootElement.GetProperty("message");
var content = messageElement.TryGetProperty("content", out var contentProp)
? contentProp.GetString() ?? ""
: "";
var chatMessage = new ChatMessage(ChatRole.Assistant, content);
// Parse tool calls - handle both OpenAI format and text-based format
if (messageElement.TryGetProperty("tool_calls", out var toolCallsElement))
{
// OpenAI-style tool_calls format
foreach (var toolCall in toolCallsElement.EnumerateArray())
{
var function = toolCall.GetProperty("function");
var functionName = function.GetProperty("name").GetString()!;
var argumentsJson = function.GetProperty("arguments");
var arguments = ParseArguments(argumentsJson);
chatMessage.Contents.Add(new FunctionCallContent(
callId: Guid.NewGuid().ToString(),
name: functionName,
arguments: arguments
));
}
}
else if (!string.IsNullOrWhiteSpace(content) && content.TrimStart().StartsWith("{"))
{
// Text-based function call format (some models like qwen2.5-coder return this)
try
{
var functionCallJson = JsonDocument.Parse(content);
if (functionCallJson.RootElement.TryGetProperty("name", out var nameProp) &&
functionCallJson.RootElement.TryGetProperty("arguments", out var argsProp))
{
var functionName = nameProp.GetString()!;
var arguments = ParseArguments(argsProp);
chatMessage.Contents.Add(new FunctionCallContent(
callId: Guid.NewGuid().ToString(),
name: functionName,
arguments: arguments
));
}
}
catch
{
// Not a function call, just regular content
}
}
var latency = (DateTime.UtcNow - startTime).TotalMilliseconds;
activity?.SetTag("ollama.latency_ms", latency);
activity?.SetTag("ollama.estimated_tokens", content.Length / 4);
activity?.SetTag("ollama.has_function_calls", chatMessage.Contents.OfType<FunctionCallContent>().Any());
return new ChatCompletion(chatMessage);
}
private static Dictionary<string, object?> ParseArguments(JsonElement argumentsJson)
{
var arguments = new Dictionary<string, object?>();
foreach (var prop in argumentsJson.EnumerateObject())
{
arguments[prop.Name] = prop.Value.ValueKind switch
{
JsonValueKind.Number => prop.Value.GetDouble(),
JsonValueKind.String => prop.Value.GetString(),
JsonValueKind.True => true,
JsonValueKind.False => false,
_ => prop.Value.ToString()
};
}
return arguments;
}
private static object BuildToolDefinition(AITool tool)
{
var functionInfo = tool.GetType().GetProperty("Metadata")?.GetValue(tool) as AIFunctionMetadata
?? throw new InvalidOperationException("Tool must have Metadata property");
var parameters = new Dictionary<string, object>
{
["type"] = "object",
["properties"] = functionInfo.Parameters.ToDictionary(
p => p.Name,
p => new Dictionary<string, object>
{
["type"] = GetJsonType(p.ParameterType),
["description"] = p.Description ?? ""
}
),
["required"] = functionInfo.Parameters
.Where(p => p.IsRequired)
.Select(p => p.Name)
.ToArray()
};
return new
{
type = "function",
function = new
{
name = functionInfo.Name,
description = functionInfo.Description ?? "",
parameters
}
};
}
private static string GetJsonType(Type type)
{
if (type == typeof(int) || type == typeof(long) || type == typeof(short))
return "integer";
if (type == typeof(float) || type == typeof(double) || type == typeof(decimal))
return "number";
if (type == typeof(bool))
return "boolean";
if (type == typeof(string))
return "string";
return "object";
}
public IAsyncEnumerable<StreamingChatCompletionUpdate> CompleteStreamingAsync(
IList<ChatMessage> messages,
ChatOptions? options = null,
CancellationToken cancellationToken = default)
=> throw new NotImplementedException("Streaming not supported in MVP");
public TService? GetService<TService>(object? key = null) where TService : class
=> this as TService;
public void Dispose() { }
}

88
Svrnty.Sample/AI/Tools/DatabaseQueryTool.cs
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@ -1,88 +0,0 @@
using System.ComponentModel;
namespace Svrnty.Sample.AI.Tools;
/// <summary>
/// Business tool for querying database and business metrics
/// </summary>
public class DatabaseQueryTool
{
// Simulated data - replace with actual database queries via CQRS
private static readonly Dictionary<string, decimal> MonthlyRevenue = new()
{
["2025-01"] = 50000m,
["2025-02"] = 45000m,
["2025-03"] = 55000m,
["2025-04"] = 62000m,
["2025-05"] = 58000m,
["2025-06"] = 67000m
};
private static readonly List<(string Name, string State, string Tier)> Customers = new()
{
("Acme Corp", "California", "Enterprise"),
("TechStart Inc", "California", "Startup"),
("BigRetail LLC", "Texas", "Enterprise"),
("SmallShop", "New York", "SMB"),
("MegaCorp", "California", "Enterprise")
};
[Description("Get revenue for a specific month in YYYY-MM format")]
public decimal GetMonthlyRevenue(
[Description("Month in YYYY-MM format, e.g., 2025-01")] string month)
{
return MonthlyRevenue.TryGetValue(month, out var revenue) ? revenue : 0m;
}
[Description("Calculate total revenue between two months (inclusive)")]
public decimal GetRevenueRange(
[Description("Start month in YYYY-MM format")] string startMonth,
[Description("End month in YYYY-MM format")] string endMonth)
{
var total = 0m;
foreach (var kvp in MonthlyRevenue)
{
if (string.Compare(kvp.Key, startMonth, StringComparison.Ordinal) >= 0 &&
string.Compare(kvp.Key, endMonth, StringComparison.Ordinal) <= 0)
{
total += kvp.Value;
}
}
return total;
}
[Description("Count customers by state")]
public int CountCustomersByState(
[Description("US state name, e.g., California")] string state)
{
return Customers.Count(c => c.State.Equals(state, StringComparison.OrdinalIgnoreCase));
}
[Description("Count customers by tier (Enterprise, SMB, Startup)")]
public int CountCustomersByTier(
[Description("Customer tier: Enterprise, SMB, or Startup")] string tier)
{
return Customers.Count(c => c.Tier.Equals(tier, StringComparison.OrdinalIgnoreCase));
}
[Description("Get list of customer names by state and tier")]
public string GetCustomers(
[Description("US state name, optional")] string? state = null,
[Description("Customer tier, optional")] string? tier = null)
{
var filtered = Customers.AsEnumerable();
if (!string.IsNullOrWhiteSpace(state))
{
filtered = filtered.Where(c => c.State.Equals(state, StringComparison.OrdinalIgnoreCase));
}
if (!string.IsNullOrWhiteSpace(tier))
{
filtered = filtered.Where(c => c.Tier.Equals(tier, StringComparison.OrdinalIgnoreCase));
}
var names = filtered.Select(c => c.Name).ToList();
return names.Any() ? string.Join(", ", names) : "No customers found";
}
}

12
Svrnty.Sample/AI/Tools/MathTool.cs
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@ -1,12 +0,0 @@
using System.ComponentModel;
namespace Svrnty.Sample.AI.Tools;
public class MathTool
{
[Description("Add two numbers together")]
public int Add(int a, int b) => a + b;
[Description("Multiply two numbers together")]
public int Multiply(int a, int b) => a * b;
}

120
Svrnty.Sample/DEPLOYMENT_README.md
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@ -1,120 +0,0 @@
# AI Agent Production Deployment
Complete production-ready AI agent system with Langfuse observability, PostgreSQL persistence, and Docker deployment.
## Architecture
- **AI Agent API** (.NET 10) - Ports 6000 (gRPC), 6001 (HTTP)
- **PostgreSQL** - Database for conversations, revenue, and customer data
- **Ollama** - Local LLM (qwen2.5-coder:7b)
- **Langfuse** - Observability and tracing UI
## Quick Start
```bash
# 1. Deploy everything
./scripts/deploy.sh
# 2. Configure Langfuse (one-time setup)
# - Open http://localhost:3000
# - Create account and project
# - Copy API keys from Settings → API Keys
# - Update .env with your keys
# - Restart API: docker compose restart api
# 3. Test the agent
curl -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"What is 5 + 3?"}'
# 4. View traces
# Open http://localhost:3000/traces
```
## Features
✅ **Full Observability**: OpenTelemetry traces sent to Langfuse
✅ **Database Persistence**: Conversations stored in PostgreSQL
✅ **Function Calling**: Math and database query tools
✅ **Health Checks**: `/health` and `/health/ready` endpoints
✅ **Auto Migrations**: Database schema applied on startup
✅ **Production Ready**: Docker Compose multi-container setup
## Access Points
- HTTP API: http://localhost:6001/api/command/executeAgent
- Swagger: http://localhost:6001/swagger
- Langfuse: http://localhost:3000
- Ollama: http://localhost:11434
## Project Structure
```
├── docker-compose.yml # Multi-container orchestration
├── Dockerfile # Multi-stage .NET build
├── .env # Configuration (secrets)
├── docker/configs/
│ └── init-db.sql # PostgreSQL initialization
├── Svrnty.Sample/
│ ├── AI/
│ │ ├── OllamaClient.cs # Instrumented LLM client
│ │ ├── Commands/
│ │ │ └── ExecuteAgent* # Main handler (instrumented)
│ │ └── Tools/
│ │ ├── MathTool.cs # Math operations
│ │ └── DatabaseQuery* # SQL queries
│ ├── Data/
│ │ ├── AgentDbContext.cs # EF Core context
│ │ ├── Entities/ # Conversation, Revenue, Customer
│ │ └── Migrations/ # EF migrations
│ └── Program.cs # Startup (OpenTelemetry, Health Checks)
└── scripts/
└── deploy.sh # One-command deployment
```
## OpenTelemetry Spans
The system creates nested spans for complete observability:
- `agent.execute` - Root span for entire agent execution
- `tools.register` - Tool registration
- `llm.completion` - Each LLM call
- `function.{name}` - Each tool invocation
Tags include: conversation_id, prompt, model, success, latency, tokens
## Database Schema
**agent.conversations** - AI conversation history
**agent.revenue** - Monthly revenue data (seeded)
**agent.customers** - Customer data (seeded)
## Troubleshooting
```bash
# Check service health
docker compose ps
curl http://localhost:6001/health
# View logs
docker compose logs api
docker compose logs ollama
docker compose logs langfuse
# Restart services
docker compose restart api
# Full reset
docker compose down -v
./scripts/deploy.sh
```
## Implementation Details
- **OpenTelemetry**: Exports traces to Langfuse via OTLP/HTTP
- **ActivitySource**: "Svrnty.AI.Agent" and "Svrnty.AI.Ollama"
- **Database**: Auto-migration on startup, seeded with sample data
- **Error Handling**: Graceful function call failures, structured logging
- **Performance**: Multi-stage Docker builds, health checks with retries
## Estimated Time: 3-4 hours for complete implementation

58
Svrnty.Sample/Data/AgentDbContext.cs
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@ -1,58 +0,0 @@
using Microsoft.EntityFrameworkCore;
using Svrnty.Sample.Data.Entities;
namespace Svrnty.Sample.Data;
/// <summary>
/// Database context for AI agent system with conversation history and business data
/// </summary>
public class AgentDbContext : DbContext
{
public AgentDbContext(DbContextOptions<AgentDbContext> options) : base(options)
{
}
public DbSet<Conversation> Conversations => Set<Conversation>();
public DbSet<Revenue> Revenues => Set<Revenue>();
public DbSet<Customer> Customers => Set<Customer>();
protected override void OnModelCreating(ModelBuilder modelBuilder)
{
base.OnModelCreating(modelBuilder);
// Configure Conversation entity
modelBuilder.Entity<Conversation>(entity =>
{
entity.HasKey(e => e.Id);
entity.HasIndex(e => e.CreatedAt).HasDatabaseName("idx_conversations_created");
entity.HasIndex(e => e.UpdatedAt).HasDatabaseName("idx_conversations_updated");
entity.Property(e => e.MessagesJson)
.HasColumnType("jsonb")
.IsRequired()
.HasDefaultValue("[]");
});
// Configure Revenue entity
modelBuilder.Entity<Revenue>(entity =>
{
entity.HasKey(e => e.Id);
entity.HasIndex(e => new { e.Month, e.Year })
.HasDatabaseName("idx_revenue_month")
.IsUnique();
entity.Property(e => e.Amount)
.HasPrecision(18, 2);
});
// Configure Customer entity
modelBuilder.Entity<Customer>(entity =>
{
entity.HasKey(e => e.Id);
entity.HasIndex(e => e.State).HasDatabaseName("idx_customers_state");
entity.HasIndex(e => e.Tier).HasDatabaseName("idx_customers_tier");
entity.HasIndex(e => new { e.State, e.Tier })
.HasDatabaseName("idx_customers_state_tier");
});
}
}

27
Svrnty.Sample/Data/AgentDbContextFactory.cs
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@ -1,27 +0,0 @@
using Microsoft.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore.Design;
namespace Svrnty.Sample.Data;
/// <summary>
/// Design-time factory for creating AgentDbContext during migrations
/// </summary>
public class AgentDbContextFactory : IDesignTimeDbContextFactory<AgentDbContext>
{
public AgentDbContext CreateDbContext(string[] args)
{
var optionsBuilder = new DbContextOptionsBuilder<AgentDbContext>();
// Use a default connection string for design-time operations
// This will be overridden at runtime with the actual connection string from configuration
var connectionString = Environment.GetEnvironmentVariable("CONNECTION_STRING_SVRNTY")
?? "Host=localhost;Database=svrnty;Username=postgres;Password=postgres;Include Error Detail=true";
optionsBuilder.UseNpgsql(connectionString, npgsqlOptions =>
{
npgsqlOptions.MigrationsHistoryTable("__EFMigrationsHistory", "agent");
});
return new AgentDbContext(optionsBuilder.Options);
}
}

53
Svrnty.Sample/Data/Entities/Conversation.cs
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@ -1,53 +0,0 @@
using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;
using System.Text.Json;
namespace Svrnty.Sample.Data.Entities;
/// <summary>
/// Represents an AI agent conversation with message history
/// </summary>
[Table("conversations", Schema = "agent")]
public class Conversation
{
[Key]
[Column("id")]
public Guid Id { get; set; } = Guid.NewGuid();
/// <summary>
/// JSON array of messages in the conversation
/// </summary>
[Column("messages", TypeName = "jsonb")]
[Required]
public string MessagesJson { get; set; } = "[]";
[Column("created_at")]
[Required]
public DateTime CreatedAt { get; set; } = DateTime.UtcNow;
[Column("updated_at")]
[Required]
public DateTime UpdatedAt { get; set; } = DateTime.UtcNow;
/// <summary>
/// Convenience property to get/set messages as objects (not mapped to database)
/// </summary>
[NotMapped]
public List<ConversationMessage> Messages
{
get => string.IsNullOrEmpty(MessagesJson)
? new List<ConversationMessage>()
: JsonSerializer.Deserialize<List<ConversationMessage>>(MessagesJson) ?? new List<ConversationMessage>();
set => MessagesJson = JsonSerializer.Serialize(value);
}
}
/// <summary>
/// Individual message in a conversation
/// </summary>
public class ConversationMessage
{
public string Role { get; set; } = string.Empty;
public string Content { get; set; } = string.Empty;
public DateTime Timestamp { get; set; } = DateTime.UtcNow;
}

37
Svrnty.Sample/Data/Entities/Customer.cs
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@ -1,37 +0,0 @@
using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;
namespace Svrnty.Sample.Data.Entities;
/// <summary>
/// Represents a customer in the system
/// </summary>
[Table("customers", Schema = "agent")]
public class Customer
{
[Key]
[Column("id")]
[DatabaseGenerated(DatabaseGeneratedOption.Identity)]
public int Id { get; set; }
[Column("name")]
[Required]
[MaxLength(200)]
public string Name { get; set; } = string.Empty;
[Column("email")]
[MaxLength(200)]
public string? Email { get; set; }
[Column("state")]
[MaxLength(100)]
public string? State { get; set; }
[Column("tier")]
[MaxLength(50)]
public string? Tier { get; set; }
[Column("created_at")]
[Required]
public DateTime CreatedAt { get; set; } = DateTime.UtcNow;
}

33
Svrnty.Sample/Data/Entities/Revenue.cs
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@ -1,33 +0,0 @@
using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;
namespace Svrnty.Sample.Data.Entities;
/// <summary>
/// Represents monthly revenue data
/// </summary>
[Table("revenue", Schema = "agent")]
public class Revenue
{
[Key]
[Column("id")]
[DatabaseGenerated(DatabaseGeneratedOption.Identity)]
public int Id { get; set; }
[Column("month")]
[Required]
[MaxLength(50)]
public string Month { get; set; } = string.Empty;
[Column("amount", TypeName = "decimal(18,2)")]
[Required]
public decimal Amount { get; set; }
[Column("year")]
[Required]
public int Year { get; set; }
[Column("created_at")]
[Required]
public DateTime CreatedAt { get; set; } = DateTime.UtcNow;
}

148
Svrnty.Sample/Data/Migrations/20251108154325_InitialCreate.Designer.cs generated
View File

@ -1,148 +0,0 @@
// <auto-generated />
using System;
using Microsoft.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore.Infrastructure;
using Microsoft.EntityFrameworkCore.Migrations;
using Microsoft.EntityFrameworkCore.Storage.ValueConversion;
using Npgsql.EntityFrameworkCore.PostgreSQL.Metadata;
using Svrnty.Sample.Data;
#nullable disable
namespace Svrnty.Sample.Data.Migrations
{
[DbContext(typeof(AgentDbContext))]
[Migration("20251108154325_InitialCreate")]
partial class InitialCreate
{
/// <inheritdoc />
protected override void BuildTargetModel(ModelBuilder modelBuilder)
{
#pragma warning disable 612, 618
modelBuilder
.HasAnnotation("ProductVersion", "9.0.0")
.HasAnnotation("Relational:MaxIdentifierLength", 63);
NpgsqlModelBuilderExtensions.UseIdentityByDefaultColumns(modelBuilder);
modelBuilder.Entity("Svrnty.Sample.Data.Entities.Conversation", b =>
{
b.Property<Guid>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("uuid")
.HasColumnName("id");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("created_at");
b.Property<string>("MessagesJson")
.IsRequired()
.ValueGeneratedOnAdd()
.HasColumnType("jsonb")
.HasDefaultValue("[]")
.HasColumnName("messages");
b.Property<DateTime>("UpdatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("updated_at");
b.HasKey("Id");
b.HasIndex("CreatedAt")
.HasDatabaseName("idx_conversations_created");
b.HasIndex("UpdatedAt")
.HasDatabaseName("idx_conversations_updated");
b.ToTable("conversations", "agent");
});
modelBuilder.Entity("Svrnty.Sample.Data.Entities.Customer", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer")
.HasColumnName("id");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("created_at");
b.Property<string>("Email")
.HasMaxLength(200)
.HasColumnType("character varying(200)")
.HasColumnName("email");
b.Property<string>("Name")
.IsRequired()
.HasMaxLength(200)
.HasColumnType("character varying(200)")
.HasColumnName("name");
b.Property<string>("State")
.HasMaxLength(100)
.HasColumnType("character varying(100)")
.HasColumnName("state");
b.Property<string>("Tier")
.HasMaxLength(50)
.HasColumnType("character varying(50)")
.HasColumnName("tier");
b.HasKey("Id");
b.HasIndex("State")
.HasDatabaseName("idx_customers_state");
b.HasIndex("Tier")
.HasDatabaseName("idx_customers_tier");
b.HasIndex("State", "Tier")
.HasDatabaseName("idx_customers_state_tier");
b.ToTable("customers", "agent");
});
modelBuilder.Entity("Svrnty.Sample.Data.Entities.Revenue", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer")
.HasColumnName("id");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<decimal>("Amount")
.HasPrecision(18, 2)
.HasColumnType("decimal(18,2)")
.HasColumnName("amount");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("created_at");
b.Property<string>("Month")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)")
.HasColumnName("month");
b.Property<int>("Year")
.HasColumnType("integer")
.HasColumnName("year");
b.HasKey("Id");
b.HasIndex("Month", "Year")
.IsUnique()
.HasDatabaseName("idx_revenue_month");
b.ToTable("revenue", "agent");
});
#pragma warning restore 612, 618
}
}
}

122
Svrnty.Sample/Data/Migrations/20251108154325_InitialCreate.cs
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@ -1,122 +0,0 @@
using System;
using Microsoft.EntityFrameworkCore.Migrations;
using Npgsql.EntityFrameworkCore.PostgreSQL.Metadata;
#nullable disable
namespace Svrnty.Sample.Data.Migrations
{
/// <inheritdoc />
public partial class InitialCreate : Migration
{
/// <inheritdoc />
protected override void Up(MigrationBuilder migrationBuilder)
{
migrationBuilder.EnsureSchema(
name: "agent");
migrationBuilder.CreateTable(
name: "conversations",
schema: "agent",
columns: table => new
{
id = table.Column<Guid>(type: "uuid", nullable: false),
messages = table.Column<string>(type: "jsonb", nullable: false, defaultValue: "[]"),
created_at = table.Column<DateTime>(type: "timestamp with time zone", nullable: false),
updated_at = table.Column<DateTime>(type: "timestamp with time zone", nullable: false)
},
constraints: table =>
{
table.PrimaryKey("PK_conversations", x => x.id);
});
migrationBuilder.CreateTable(
name: "customers",
schema: "agent",
columns: table => new
{
id = table.Column<int>(type: "integer", nullable: false)
.Annotation("Npgsql:ValueGenerationStrategy", NpgsqlValueGenerationStrategy.IdentityByDefaultColumn),
name = table.Column<string>(type: "character varying(200)", maxLength: 200, nullable: false),
email = table.Column<string>(type: "character varying(200)", maxLength: 200, nullable: true),
state = table.Column<string>(type: "character varying(100)", maxLength: 100, nullable: true),
tier = table.Column<string>(type: "character varying(50)", maxLength: 50, nullable: true),
created_at = table.Column<DateTime>(type: "timestamp with time zone", nullable: false)
},
constraints: table =>
{
table.PrimaryKey("PK_customers", x => x.id);
});
migrationBuilder.CreateTable(
name: "revenue",
schema: "agent",
columns: table => new
{
id = table.Column<int>(type: "integer", nullable: false)
.Annotation("Npgsql:ValueGenerationStrategy", NpgsqlValueGenerationStrategy.IdentityByDefaultColumn),
month = table.Column<string>(type: "character varying(50)", maxLength: 50, nullable: false),
amount = table.Column<decimal>(type: "numeric(18,2)", precision: 18, scale: 2, nullable: false),
year = table.Column<int>(type: "integer", nullable: false),
created_at = table.Column<DateTime>(type: "timestamp with time zone", nullable: false)
},
constraints: table =>
{
table.PrimaryKey("PK_revenue", x => x.id);
});
migrationBuilder.CreateIndex(
name: "idx_conversations_created",
schema: "agent",
table: "conversations",
column: "created_at");
migrationBuilder.CreateIndex(
name: "idx_conversations_updated",
schema: "agent",
table: "conversations",
column: "updated_at");
migrationBuilder.CreateIndex(
name: "idx_customers_state",
schema: "agent",
table: "customers",
column: "state");
migrationBuilder.CreateIndex(
name: "idx_customers_state_tier",
schema: "agent",
table: "customers",
columns: new[] { "state", "tier" });
migrationBuilder.CreateIndex(
name: "idx_customers_tier",
schema: "agent",
table: "customers",
column: "tier");
migrationBuilder.CreateIndex(
name: "idx_revenue_month",
schema: "agent",
table: "revenue",
columns: new[] { "month", "year" },
unique: true);
}
/// <inheritdoc />
protected override void Down(MigrationBuilder migrationBuilder)
{
migrationBuilder.DropTable(
name: "conversations",
schema: "agent");
migrationBuilder.DropTable(
name: "customers",
schema: "agent");
migrationBuilder.DropTable(
name: "revenue",
schema: "agent");
}
}
}

145
Svrnty.Sample/Data/Migrations/AgentDbContextModelSnapshot.cs
View File

@ -1,145 +0,0 @@
// <auto-generated />
using System;
using Microsoft.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore.Infrastructure;
using Microsoft.EntityFrameworkCore.Storage.ValueConversion;
using Npgsql.EntityFrameworkCore.PostgreSQL.Metadata;
using Svrnty.Sample.Data;
#nullable disable
namespace Svrnty.Sample.Data.Migrations
{
[DbContext(typeof(AgentDbContext))]
partial class AgentDbContextModelSnapshot : ModelSnapshot
{
protected override void BuildModel(ModelBuilder modelBuilder)
{
#pragma warning disable 612, 618
modelBuilder
.HasAnnotation("ProductVersion", "9.0.0")
.HasAnnotation("Relational:MaxIdentifierLength", 63);
NpgsqlModelBuilderExtensions.UseIdentityByDefaultColumns(modelBuilder);
modelBuilder.Entity("Svrnty.Sample.Data.Entities.Conversation", b =>
{
b.Property<Guid>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("uuid")
.HasColumnName("id");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("created_at");
b.Property<string>("MessagesJson")
.IsRequired()
.ValueGeneratedOnAdd()
.HasColumnType("jsonb")
.HasDefaultValue("[]")
.HasColumnName("messages");
b.Property<DateTime>("UpdatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("updated_at");
b.HasKey("Id");
b.HasIndex("CreatedAt")
.HasDatabaseName("idx_conversations_created");
b.HasIndex("UpdatedAt")
.HasDatabaseName("idx_conversations_updated");
b.ToTable("conversations", "agent");
});
modelBuilder.Entity("Svrnty.Sample.Data.Entities.Customer", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer")
.HasColumnName("id");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("created_at");
b.Property<string>("Email")
.HasMaxLength(200)
.HasColumnType("character varying(200)")
.HasColumnName("email");
b.Property<string>("Name")
.IsRequired()
.HasMaxLength(200)
.HasColumnType("character varying(200)")
.HasColumnName("name");
b.Property<string>("State")
.HasMaxLength(100)
.HasColumnType("character varying(100)")
.HasColumnName("state");
b.Property<string>("Tier")
.HasMaxLength(50)
.HasColumnType("character varying(50)")
.HasColumnName("tier");
b.HasKey("Id");
b.HasIndex("State")
.HasDatabaseName("idx_customers_state");
b.HasIndex("Tier")
.HasDatabaseName("idx_customers_tier");
b.HasIndex("State", "Tier")
.HasDatabaseName("idx_customers_state_tier");
b.ToTable("customers", "agent");
});
modelBuilder.Entity("Svrnty.Sample.Data.Entities.Revenue", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer")
.HasColumnName("id");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<decimal>("Amount")
.HasPrecision(18, 2)
.HasColumnType("decimal(18,2)")
.HasColumnName("amount");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone")
.HasColumnName("created_at");
b.Property<string>("Month")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)")
.HasColumnName("month");
b.Property<int>("Year")
.HasColumnType("integer")
.HasColumnName("year");
b.HasKey("Id");
b.HasIndex("Month", "Year")
.IsUnique()
.HasDatabaseName("idx_revenue_month");
b.ToTable("revenue", "agent");
});
#pragma warning restore 612, 618
}
}
}

202
Svrnty.Sample/Program.cs
View File

@ -1,143 +1,22 @@
using System.Text;
using System.Threading.RateLimiting;
using Microsoft.AspNetCore.RateLimiting;
using Microsoft.AspNetCore.Server.Kestrel.Core;
using Microsoft.EntityFrameworkCore;
using Microsoft.Extensions.AI;
using OpenTelemetry;
using OpenTelemetry.Metrics;
using OpenTelemetry.Resources;
using OpenTelemetry.Trace;
using Svrnty.CQRS;
using Svrnty.CQRS.FluentValidation;
// Temporarily disabled gRPC (ARM64 Mac build issues)
// using Svrnty.CQRS.Grpc;
using Svrnty.CQRS.Grpc;
using Svrnty.Sample;
using Svrnty.Sample.AI;
using Svrnty.Sample.AI.Commands;
using Svrnty.Sample.AI.Tools;
using Svrnty.Sample.Data;
using Svrnty.CQRS.MinimalApi;
using Svrnty.CQRS.DynamicQuery;
using Svrnty.CQRS.Abstractions;
var builder = WebApplication.CreateBuilder(args);
// Temporarily disabled gRPC configuration (ARM64 Mac build issues)
// Using ASPNETCORE_URLS environment variable for endpoint configuration instead of Kestrel
// This avoids HTTPS certificate issues in Docker
/*
// Configure Kestrel to support both HTTP/1.1 (for REST APIs) and HTTP/2 (for gRPC)
builder.WebHost.ConfigureKestrel(options =>
{
// Port 6000: HTTP/2 for gRPC
options.ListenLocalhost(6000, o => o.Protocols = HttpProtocols.Http2);
// Port 6001: HTTP/1.1 for HTTP API
options.ListenLocalhost(6001, o => o.Protocols = HttpProtocols.Http1);
});
*/
// Configure Database
var connectionString = builder.Configuration.GetConnectionString("DefaultConnection")
?? "Host=localhost;Database=svrnty;Username=postgres;Password=postgres;Include Error Detail=true";
builder.Services.AddDbContext<AgentDbContext>(options =>
options.UseNpgsql(connectionString));
// Configure Langfuse HTTP client for AI observability (required by ExecuteAgentCommandHandler)
var langfuseBaseUrl = builder.Configuration["Langfuse:BaseUrl"] ?? "http://localhost:3000";
builder.Services.AddHttpClient();
builder.Services.AddScoped<LangfuseHttpClient>(sp =>
{
var httpClientFactory = sp.GetRequiredService<IHttpClientFactory>();
var httpClient = httpClientFactory.CreateClient();
httpClient.BaseAddress = new Uri(langfuseBaseUrl);
httpClient.Timeout = TimeSpan.FromSeconds(10);
var configuration = sp.GetRequiredService<IConfiguration>();
return new LangfuseHttpClient(httpClient, configuration);
});
// Configure OpenTelemetry with Langfuse + Prometheus Metrics
var langfusePublicKey = builder.Configuration["Langfuse:PublicKey"] ?? "";
var langfuseSecretKey = builder.Configuration["Langfuse:SecretKey"] ?? "";
var langfuseOtlpEndpoint = builder.Configuration["Langfuse:OtlpEndpoint"]
?? "http://localhost:3000/api/public/otel/v1/traces";
var otelBuilder = builder.Services.AddOpenTelemetry()
.ConfigureResource(resource => resource
.AddService(
serviceName: "svrnty-ai-agent",
serviceVersion: "1.0.0",
serviceInstanceId: Environment.MachineName)
.AddAttributes(new Dictionary<string, object>
{
["deployment.environment"] = builder.Environment.EnvironmentName,
["service.namespace"] = "ai-agents",
["host.name"] = Environment.MachineName
}));
// Add Metrics (always enabled - Prometheus endpoint)
otelBuilder.WithMetrics(metrics =>
{
metrics
.AddAspNetCoreInstrumentation()
.AddHttpClientInstrumentation()
.AddPrometheusExporter();
});
// Add Tracing (only when Langfuse keys are configured)
if (!string.IsNullOrEmpty(langfusePublicKey) && !string.IsNullOrEmpty(langfuseSecretKey))
{
var authString = Convert.ToBase64String(
Encoding.UTF8.GetBytes($"{langfusePublicKey}:{langfuseSecretKey}"));
otelBuilder.WithTracing(tracing =>
{
tracing
.AddSource("Svrnty.AI.*")
.SetSampler(new AlwaysOnSampler())
.AddHttpClientInstrumentation(options =>
{
options.FilterHttpRequestMessage = (req) =>
!req.RequestUri?.Host.Contains("langfuse") ?? true;
})
.AddEntityFrameworkCoreInstrumentation(options =>
{
options.SetDbStatementForText = true;
options.SetDbStatementForStoredProcedure = true;
})
.AddOtlpExporter(options =>
{
options.Endpoint = new Uri(langfuseOtlpEndpoint);
options.Headers = $"Authorization=Basic {authString}";
options.Protocol = OpenTelemetry.Exporter.OtlpExportProtocol.HttpProtobuf;
});
});
}
// Configure Rate Limiting
builder.Services.AddRateLimiter(options =>
{
options.GlobalLimiter = PartitionedRateLimiter.Create<HttpContext, string>(
context => RateLimitPartition.GetFixedWindowLimiter(
partitionKey: context.User.Identity?.Name ?? context.Request.Headers.Host.ToString(),
factory: _ => new FixedWindowRateLimiterOptions
{
PermitLimit = 100,
Window = TimeSpan.FromMinutes(1),
QueueProcessingOrder = QueueProcessingOrder.OldestFirst,
QueueLimit = 10
}));
options.OnRejected = async (context, cancellationToken) =>
{
context.HttpContext.Response.StatusCode = StatusCodes.Status429TooManyRequests;
await context.HttpContext.Response.WriteAsJsonAsync(new
{
error = "Too many requests. Please try again later.",
retryAfter = context.Lease.TryGetMetadata(MetadataName.RetryAfter, out var retryAfter)
? retryAfter.TotalSeconds
: 60
}, cancellationToken);
};
});
// IMPORTANT: Register dynamic query dependencies FIRST
// (before AddSvrntyCqrs, so gRPC services can find the handlers)
@ -145,36 +24,19 @@ builder.Services.AddTransient<PoweredSoft.Data.Core.IAsyncQueryableService, Simp
builder.Services.AddTransient<PoweredSoft.DynamicQuery.Core.IQueryHandlerAsync, PoweredSoft.DynamicQuery.QueryHandlerAsync>();
builder.Services.AddDynamicQueryWithProvider<User, UserQueryableProvider>();
// Register AI Tools
builder.Services.AddSingleton<MathTool>();
builder.Services.AddScoped<DatabaseQueryTool>();
// Register Ollama AI client
var ollamaBaseUrl = builder.Configuration["Ollama:BaseUrl"] ?? "http://localhost:11434";
builder.Services.AddHttpClient<IChatClient, OllamaClient>(client =>
{
client.BaseAddress = new Uri(ollamaBaseUrl);
});
// Register commands and queries with validators
builder.Services.AddCommand<AddUserCommand, int, AddUserCommandHandler, AddUserCommandValidator>();
builder.Services.AddCommand<RemoveUserCommand, RemoveUserCommandHandler>();
builder.Services.AddQuery<FetchUserQuery, User, FetchUserQueryHandler>();
// Register AI agent command
builder.Services.AddCommand<ExecuteAgentCommand, AgentResponse, ExecuteAgentCommandHandler>();
// Configure CQRS with fluent API
builder.Services.AddSvrntyCqrs(cqrs =>
{
// Temporarily disabled gRPC (ARM64 Mac build issues)
/*
// Register commands and queries with validators
cqrs.AddCommand<AddUserCommand, int, AddUserCommandHandler, AddUserCommandValidator>();
cqrs.AddCommand<RemoveUserCommand, RemoveUserCommandHandler>();
cqrs.AddQuery<FetchUserQuery, User, FetchUserQueryHandler>();
// Enable gRPC endpoints with reflection
cqrs.AddGrpc(grpc =>
{
grpc.EnableReflection();
});
*/
// Enable MinimalApi endpoints
cqrs.AddMinimalApi(configure =>
@ -185,56 +47,18 @@ builder.Services.AddSvrntyCqrs(cqrs =>
builder.Services.AddEndpointsApiExplorer();
builder.Services.AddSwaggerGen();
// Configure Health Checks
builder.Services.AddHealthChecks()
.AddNpgSql(connectionString, name: "postgresql", tags: new[] { "ready", "db" });
var app = builder.Build();
// Run database migrations
using (var scope = app.Services.CreateScope())
{
var dbContext = scope.ServiceProvider.GetRequiredService<AgentDbContext>();
try
{
await dbContext.Database.MigrateAsync();
Console.WriteLine("✅ Database migrations applied successfully");
}
catch (Exception ex)
{
Console.WriteLine($"⚠️ Database migration failed: {ex.Message}");
}
}
// Enable rate limiting
app.UseRateLimiter();
// Map all configured CQRS endpoints (gRPC, MinimalApi, and Dynamic Queries)
app.UseSvrntyCqrs();
app.UseSwagger();
app.UseSwaggerUI();
// Prometheus metrics endpoint
app.MapPrometheusScrapingEndpoint();
// Health check endpoints
app.MapHealthChecks("/health");
app.MapHealthChecks("/health/ready", new Microsoft.AspNetCore.Diagnostics.HealthChecks.HealthCheckOptions
{
Predicate = check => check.Tags.Contains("ready")
});
Console.WriteLine("Production-Ready AI Agent with Full Observability (HTTP-Only Mode)");
Console.WriteLine("═══════════════════════════════════════════════════════════");
Console.WriteLine("HTTP API: http://localhost:6001/api/command/* and /api/query/*");
Console.WriteLine("Swagger UI: http://localhost:6001/swagger");
Console.WriteLine("Prometheus Metrics: http://localhost:6001/metrics");
Console.WriteLine("Health Check: http://localhost:6001/health");
Console.WriteLine("═══════════════════════════════════════════════════════════");
Console.WriteLine("Note: gRPC temporarily disabled (ARM64 Mac build issues)");
Console.WriteLine($"Rate Limiting: 100 requests/minute per client");
Console.WriteLine($"Langfuse Tracing: {(!string.IsNullOrEmpty(langfusePublicKey) ? "Enabled" : "Disabled (configure keys in .env)")}");
Console.WriteLine("═══════════════════════════════════════════════════════════");
Console.WriteLine("Auto-Generated gRPC Server with Reflection, Validation, MinimalApi and Swagger");
Console.WriteLine("gRPC (HTTP/2): http://localhost:6000");
Console.WriteLine("HTTP API (HTTP/1.1): http://localhost:6001/api/command/* and http://localhost:6001/api/query/*");
Console.WriteLine("Swagger UI: http://localhost:6001/swagger");
app.Run();

30
Svrnty.Sample/Svrnty.Sample.csproj
View File

@ -8,18 +8,11 @@
<CompilerGeneratedFilesOutputPath>$(BaseIntermediateOutputPath)Generated</CompilerGeneratedFilesOutputPath>
</PropertyGroup>
<!-- Temporarily disabled gRPC due to ARM64 Mac build issues with Grpc.Tools -->
<!-- Uncomment when gRPC support is needed -->
<!--
<ItemGroup>
<Protobuf Include="Protos\*.proto" GrpcServices="Server" />
</ItemGroup>
-->
<ItemGroup>
<PackageReference Include="AspNetCore.HealthChecks.NpgSql" Version="9.0.0" />
<!-- Temporarily disabled gRPC packages (ARM64 Mac build issues) -->
<!--
<PackageReference Include="Grpc.AspNetCore" Version="2.71.0" />
<PackageReference Include="Grpc.AspNetCore.Server.Reflection" Version="2.71.0" />
<PackageReference Include="Grpc.Tools" Version="2.76.0">
@ -27,43 +20,22 @@
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Grpc.StatusProto" Version="2.71.0" />
-->
<PackageReference Include="Microsoft.EntityFrameworkCore.Design" Version="9.0.0">
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
<PrivateAssets>all</PrivateAssets>
</PackageReference>
<PackageReference Include="Microsoft.Extensions.AI" Version="9.0.0-preview.9.24556.5" />
<PackageReference Include="Microsoft.Extensions.AI.Ollama" Version="9.0.0-preview.9.24556.5" />
<PackageReference Include="Npgsql.EntityFrameworkCore.PostgreSQL" Version="9.0.2" />
<PackageReference Include="OpenTelemetry" Version="1.10.0" />
<PackageReference Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" Version="1.10.0" />
<PackageReference Include="OpenTelemetry.Exporter.Prometheus.AspNetCore" Version="1.10.0-beta.1" />
<PackageReference Include="OpenTelemetry.Extensions.Hosting" Version="1.10.0" />
<PackageReference Include="OpenTelemetry.Instrumentation.AspNetCore" Version="1.10.0" />
<PackageReference Include="OpenTelemetry.Instrumentation.EntityFrameworkCore" Version="1.0.0-beta.13" />
<PackageReference Include="OpenTelemetry.Instrumentation.Http" Version="1.10.0" />
<PackageReference Include="Swashbuckle.AspNetCore" Version="9.0.6" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\Svrnty.CQRS\Svrnty.CQRS.csproj" />
<ProjectReference Include="..\Svrnty.CQRS.Abstractions\Svrnty.CQRS.Abstractions.csproj" />
<!-- Temporarily disabled gRPC project references (ARM64 Mac build issues) -->
<!--
<ProjectReference Include="..\Svrnty.CQRS.Grpc\Svrnty.CQRS.Grpc.csproj" />
<ProjectReference Include="..\Svrnty.CQRS.Grpc.Generators\Svrnty.CQRS.Grpc.Generators.csproj" OutputItemType="Analyzer" ReferenceOutputAssembly="false" />
-->
<ProjectReference Include="..\Svrnty.CQRS.FluentValidation\Svrnty.CQRS.FluentValidation.csproj" />
<ProjectReference Include="..\Svrnty.CQRS.MinimalApi\Svrnty.CQRS.MinimalApi.csproj" />
<ProjectReference Include="..\Svrnty.CQRS.DynamicQuery\Svrnty.CQRS.DynamicQuery.csproj" />
<ProjectReference Include="..\Svrnty.CQRS.DynamicQuery.MinimalApi\Svrnty.CQRS.DynamicQuery.MinimalApi.csproj" />
<!-- Keep abstractions for attributes like [GrpcIgnore] -->
<ProjectReference Include="..\Svrnty.CQRS.Grpc.Abstractions\Svrnty.CQRS.Grpc.Abstractions.csproj" />
</ItemGroup>
<!-- Temporarily disabled gRPC proto generation targets (ARM64 Mac build issues) -->
<!--
<!-- Import the proto generation targets for testing (in production this would come from the NuGet package) -->
<Import Project="..\Svrnty.CQRS.Grpc.Generators\build\Svrnty.CQRS.Grpc.Generators.targets" />
-->
</Project>

18
Svrnty.Sample/appsettings.Development.json
View File

@ -3,26 +3,14 @@
"LogLevel": {
"Default": "Information",
"Microsoft.AspNetCore": "Warning",
"Microsoft.EntityFrameworkCore": "Warning"
"Microsoft.AspNetCore.Server.Kestrel": "Information"
}
},
"ConnectionStrings": {
"DefaultConnection": "Host=localhost;Database=svrnty;Username=postgres;Password=postgres;Include Error Detail=true"
},
"Ollama": {
"BaseUrl": "http://localhost:11434",
"Model": "qwen2.5-coder:7b"
},
"Langfuse": {
"BaseUrl": "http://localhost:3000",
"PublicKey": "pk-lf-4bf8a737-30d0-4c70-ae61-fbc6d3e5d028",
"SecretKey": "sk-lf-dbcb06e1-a172-40d9-9df2-f1e1ee1ced7a"
},
"Kestrel": {
"Endpoints": {
"Http": {
"Url": "http://localhost:6001",
"Protocols": "Http1"
"Url": "http://localhost:5000",
"Protocols": "Http2"
}
}
}

22
Svrnty.Sample/appsettings.Production.json
View File

@ -1,22 +0,0 @@
{
"Logging": {
"LogLevel": {
"Default": "Information",
"Microsoft.AspNetCore": "Warning",
"Microsoft.EntityFrameworkCore": "Warning"
}
},
"AllowedHosts": "*",
"ConnectionStrings": {
"DefaultConnection": "Host=postgres;Database=svrnty;Username=postgres;Password=postgres;Include Error Detail=true"
},
"Ollama": {
"BaseUrl": "http://ollama:11434",
"Model": "qwen2.5-coder:7b"
},
"Langfuse": {
"PublicKey": "",
"SecretKey": "",
"OtlpEndpoint": "http://langfuse:3000/api/public/otel/v1/traces"
}
}

10
Svrnty.Sample/appsettings.json
View File

@ -9,12 +9,16 @@
"Kestrel": {
"Endpoints": {
"Http": {
"Url": "http://localhost:6001",
"Protocols": "Http1"
"Url": "http://localhost:5000",
"Protocols": "Http2"
},
"Https": {
"Url": "https://localhost:5001",
"Protocols": "Http2"
}
},
"EndpointDefaults": {
"Protocols": "Http1"
"Protocols": "Http2"
}
}
}

80
Svrnty.Sample/scripts/deploy.sh
View File

@ -1,80 +0,0 @@
#!/bin/bash
set -e
echo "🚀 Starting Complete AI Agent Stack with Observability"
echo ""
# Check prerequisites
command -v docker >/dev/null 2>&1 || { echo "❌ Docker required but not installed." >&2; exit 1; }
command -v docker compose >/dev/null 2>&1 || { echo "❌ Docker Compose required but not installed." >&2; exit 1; }
# Load environment variables
if [ ! -f .env ]; then
echo "❌ .env file not found!"
exit 1
fi
echo "📦 Building .NET application..."
docker compose build api
echo ""
echo "🔧 Starting infrastructure services..."
docker compose up -d postgres
echo "⏳ Waiting for PostgreSQL to be healthy..."
sleep 10
docker compose up -d langfuse ollama
echo "⏳ Waiting for services to initialize..."
sleep 20
echo ""
echo "🤖 Pulling Ollama model (this may take a few minutes)..."
docker exec ollama ollama pull qwen2.5-coder:7b || echo "⚠️ Model pull failed, will retry on first request"
echo ""
echo "🚀 Starting API service..."
docker compose up -d api
echo ""
echo "🔍 Waiting for all services to be healthy..."
for i in {1..30}; do
api_health=$(curl -f -s http://localhost:6001/health 2>/dev/null || echo "fail")
langfuse_health=$(curl -f -s http://localhost:3000/api/health 2>/dev/null || echo "fail")
ollama_health=$(curl -f -s http://localhost:11434/api/tags 2>/dev/null || echo "fail")
if [ "$api_health" != "fail" ] && [ "$langfuse_health" != "fail" ] && [ "$ollama_health" != "fail" ]; then
echo "✅ All services are healthy!"
break
fi
echo " Waiting for services... ($i/30)"
sleep 5
done
echo ""
echo "📊 Services Status:"
docker compose ps
echo ""
echo "═══════════════════════════════════════════════════════════"
echo "🎯 Access Points:"
echo " • HTTP API: http://localhost:6001/api/command/executeAgent"
echo " • Swagger: http://localhost:6001/swagger"
echo " • Langfuse UI: http://localhost:3000"
echo " • Ollama: http://localhost:11434"
echo ""
echo "📝 Next Steps:"
echo "1. Open Langfuse UI at http://localhost:3000"
echo "2. Create an account and project"
echo "3. Go to Settings → API Keys"
echo "4. Copy the keys and update .env file:"
echo " LANGFUSE_PUBLIC_KEY=pk-lf-your-key"
echo " LANGFUSE_SECRET_KEY=sk-lf-your-key"
echo "5. Restart API: docker compose restart api"
echo ""
echo "🧪 Test the agent:"
echo " curl -X POST http://localhost:6001/api/command/executeAgent \\"
echo " -H 'Content-Type: application/json' \\"
echo " -d '{\"prompt\":\"What is 5 + 3?\"}'"
echo ""
echo "═══════════════════════════════════════════════════════════"

389
TESTING_GUIDE.md
View File

@ -1,389 +0,0 @@
# Production Stack Testing Guide
This guide provides instructions for testing your AI Agent production stack after resolving the Docker build issues.
## Current Status
**Build Status:** ❌ Failed at ~95%
**Issue:** gRPC source generator task (`WriteProtoFileTask`) not found in .NET 10 preview SDK
**Location:** `Svrnty.CQRS.Grpc.Generators`
## Build Issues to Resolve
### Issue 1: gRPC Generator Compatibility
```
error MSB4036: The "WriteProtoFileTask" task was not found
```
**Possible Solutions:**
1. **Skip gRPC for Docker build:** Temporarily remove gRPC dependency from `Svrnty.Sample/Svrnty.Sample.csproj`
2. **Use different .NET SDK:** Try .NET 9 or stable .NET 8 instead of .NET 10 preview
3. **Fix the gRPC generator:** Update `Svrnty.CQRS.Grpc.Generators` to work with .NET 10 preview SDK
### Quick Fix: Disable gRPC for Testing
Edit `Svrnty.Sample/Svrnty.Sample.csproj` and comment out:
```xml
<!-- Temporarily disabled for Docker build -->
<!-- <ProjectReference Include="..\Svrnty.CQRS.Grpc\Svrnty.CQRS.Grpc.csproj" /> -->
```
Then rebuild:
```bash
docker compose up -d --build
```
## Once Build Succeeds
### Step 1: Start the Stack
```bash
# From project root
docker compose up -d
# Wait for services to start (2-3 minutes)
docker compose ps
```
### Step 2: Verify Services
```bash
# Check all services are running
docker compose ps
# Should show:
# api Up 0.0.0.0:6000-6001->6000-6001/tcp
# postgres Up 5432/tcp
# ollama Up 11434/tcp
# langfuse Up 3000/tcp
```
### Step 3: Pull Ollama Model (One-time)
```bash
docker exec ollama ollama pull qwen2.5-coder:7b
# This downloads ~6.7GB, takes 5-10 minutes
```
### Step 4: Configure Langfuse (One-time)
1. Open http://localhost:3000
2. Create account (first-time setup)
3. Create a project (e.g., "AI Agent")
4. Go to Settings → API Keys
5. Copy the Public and Secret keys
6. Update `.env`:
```bash
LANGFUSE_PUBLIC_KEY=pk-lf-...
LANGFUSE_SECRET_KEY=sk-lf-...
```
7. Restart API to enable tracing:
```bash
docker compose restart api
```
### Step 5: Run Comprehensive Tests
```bash
# Execute the full test suite
./test-production-stack.sh
```
## Test Suite Overview
The `test-production-stack.sh` script runs **7 comprehensive test phases**:
### Phase 1: Functional Testing (15 min)
- ✓ Health endpoint checks (API, Langfuse, Ollama, PostgreSQL)
- ✓ Agent math operations (simple and complex)
- ✓ Database queries (revenue, customers)
- ✓ Multi-turn conversations
**Tests:** 9 tests
**What it validates:** Core agent functionality and service connectivity
### Phase 2: Rate Limiting (5 min)
- ✓ Rate limit enforcement (100 req/min)
- ✓ HTTP 429 responses when exceeded
- ✓ Rate limit headers present
- ✓ Queue behavior (10 req queue depth)
**Tests:** 2 tests
**What it validates:** API protection and rate limiter configuration
### Phase 3: Observability (10 min)
- ✓ Langfuse trace generation
- ✓ Prometheus metrics collection
- ✓ HTTP request/response metrics
- ✓ Function call tracking
- ✓ Request counting accuracy
**Tests:** 4 tests
**What it validates:** Monitoring and debugging capabilities
### Phase 4: Load Testing (5 min)
- ✓ Concurrent request handling (20 parallel requests)
- ✓ Sustained load (30 seconds, 2 req/sec)
- ✓ Performance under stress
- ✓ Response time consistency
**Tests:** 2 tests
**What it validates:** Production-level performance and scalability
### Phase 5: Database Persistence (5 min)
- ✓ Conversation storage in PostgreSQL
- ✓ Conversation ID generation
- ✓ Seed data integrity (revenue, customers)
- ✓ Database query accuracy
**Tests:** 4 tests
**What it validates:** Data persistence and reliability
### Phase 6: Error Handling & Recovery (10 min)
- ✓ Invalid request handling (400/422 responses)
- ✓ Service restart recovery
- ✓ Graceful error messages
- ✓ Database connection resilience
**Tests:** 2 tests
**What it validates:** Production readiness and fault tolerance
### Total: ~50 minutes, 23+ tests
## Manual Testing Examples
### Test 1: Simple Math
```bash
curl -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"What is 5 + 3?"}'
```
**Expected Response:**
```json
{
"conversationId": "uuid-here",
"success": true,
"response": "The result of 5 + 3 is 8."
}
```
### Test 2: Database Query
```bash
curl -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"What was our revenue in January 2025?"}'
```
**Expected Response:**
```json
{
"conversationId": "uuid-here",
"success": true,
"response": "The revenue for January 2025 was $245,000."
}
```
### Test 3: Rate Limiting
```bash
# Send 110 requests quickly
for i in {1..110}; do
curl -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"test"}' &
done
wait
# First 100 succeed, next 10 queue, remaining get HTTP 429
```
### Test 4: Check Metrics
```bash
curl http://localhost:6001/metrics | grep http_server_request_duration
```
**Expected Output:**
```
http_server_request_duration_seconds_count{...} 150
http_server_request_duration_seconds_sum{...} 45.2
```
### Test 5: View Traces in Langfuse
1. Open http://localhost:3000/traces
2. Click on a trace to see:
- Agent execution span (root)
- Tool registration span
- LLM completion spans
- Function call spans (Add, DatabaseQuery, etc.)
- Timing breakdown
## Test Results Interpretation
### Success Criteria
- **>90% pass rate:** Production ready
- **80-90% pass rate:** Minor issues to address
- **<80% pass rate:** Significant issues, not production ready
### Common Test Failures
#### Failure: "Agent returned error or timeout"
**Cause:** Ollama model not pulled or API not responding
**Fix:**
```bash
docker exec ollama ollama pull qwen2.5-coder:7b
docker compose restart api
```
#### Failure: "Service not running"
**Cause:** Docker container failed to start
**Fix:**
```bash
docker compose logs [service-name]
docker compose up -d [service-name]
```
#### Failure: "No rate limit headers found"
**Cause:** Rate limiter not configured
**Fix:** Check `Program.cs:Svrnty.Sample/Program.cs:92-96` for rate limiter setup
#### Failure: "Traces not visible in Langfuse"
**Cause:** Langfuse keys not configured in `.env`
**Fix:** Follow Step 4 above to configure API keys
## Accessing Logs
### API Logs
```bash
docker compose logs -f api
```
### All Services
```bash
docker compose logs -f
```
### Filter for Errors
```bash
docker compose logs | grep -i error
```
## Stopping the Stack
```bash
# Stop all services
docker compose down
# Stop and remove volumes (clean slate)
docker compose down -v
```
## Troubleshooting
### Issue: Ollama Out of Memory
**Symptoms:** Agent responses timeout or return errors
**Solution:**
```bash
# Increase Docker memory limit to 8GB+
# Docker Desktop → Settings → Resources → Memory
docker compose restart ollama
```
### Issue: PostgreSQL Connection Failed
**Symptoms:** Database queries fail
**Solution:**
```bash
docker compose logs postgres
# Check for port conflicts or permission issues
docker compose down -v
docker compose up -d
```
### Issue: Langfuse Not Showing Traces
**Symptoms:** Metrics work but no traces in UI
**Solution:**
1. Verify keys in `.env` match Langfuse UI
2. Check API logs for OTLP export errors:
```bash
docker compose logs api | grep -i "otlp\|langfuse"
```
3. Restart API after updating keys:
```bash
docker compose restart api
```
### Issue: Port Already in Use
**Symptoms:** `docker compose up` fails with "port already allocated"
**Solution:**
```bash
# Find what's using the port
lsof -i :6001 # API HTTP
lsof -i :6000 # API gRPC
lsof -i :5432 # PostgreSQL
lsof -i :3000 # Langfuse
# Kill the process or change ports in docker-compose.yml
```
## Performance Expectations
### Response Times
- **Simple Math:** 1-2 seconds
- **Database Query:** 2-3 seconds
- **Complex Multi-step:** 3-5 seconds
### Throughput
- **Rate Limit:** 100 requests/minute
- **Queue Depth:** 10 requests
- **Concurrent Connections:** 20+ supported
### Resource Usage
- **Memory:** ~4GB total (Ollama ~3GB, others ~1GB)
- **CPU:** Variable based on query complexity
- **Disk:** ~10GB (Ollama model + Docker images)
## Production Deployment Checklist
Before deploying to production:
- [ ] All tests passing (>90% success rate)
- [ ] Langfuse API keys configured
- [ ] PostgreSQL credentials rotated
- [ ] Rate limits tuned for expected traffic
- [ ] Health checks validated
- [ ] Metrics dashboards created
- [ ] Alert rules configured
- [ ] Backup strategy implemented
- [ ] Secrets in environment variables (not code)
- [ ] Network policies configured
- [ ] TLS certificates installed (for HTTPS)
- [ ] Load balancer configured (if multi-instance)
## Next Steps After Testing
1. **Review test results:** Identify any failures and fix root causes
2. **Tune rate limits:** Adjust based on expected production traffic
3. **Create dashboards:** Build Grafana dashboards from Prometheus metrics
4. **Set up alerts:** Configure alerting for:
- API health check failures
- High error rates (>5%)
- High latency (P95 >5s)
- Database connection failures
5. **Optimize Ollama:** Fine-tune model parameters for your use case
6. **Scale testing:** Test with higher concurrency (50-100 parallel)
7. **Security audit:** Review authentication, authorization, input validation
## Support Resources
- **Project README:** [README.md](./README.md)
- **Deployment Guide:** [DEPLOYMENT_README.md](./DEPLOYMENT_README.md)
- **Docker Compose:** [docker-compose.yml](./docker-compose.yml)
- **Test Script:** [test-production-stack.sh](./test-production-stack.sh)
## Getting Help
If tests fail or you encounter issues:
1. Check logs: `docker compose logs -f`
2. Review this guide's troubleshooting section
3. Verify all prerequisites are met
4. Check for port conflicts or resource constraints
---
**Test Script Version:** 1.0
**Last Updated:** 2025-11-08
**Estimated Total Test Time:** ~50 minutes

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TestClient.csx Normal file
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#!/usr/bin/env dotnet-script
#r "nuget: Grpc.Net.Client, 2.70.0"
#r "nuget: Google.Protobuf, 3.28.3"
#r "nuget: Grpc.Tools, 2.70.0"
using Grpc.Net.Client;
using Grpc.Core;
using System;
using System.Threading.Tasks;
// We'll use reflection/dynamic to call the gRPC service
// This is a simple HTTP/2 test
var handler = new HttpClientHandler
{
ServerCertificateCustomValidationCallback = HttpClientHandler.DangerousAcceptAnyServerCertificateValidator
};
using var channel = GrpcChannel.ForAddress("http://localhost:5000", new GrpcChannelOptions
{
HttpHandler = handler
});
Console.WriteLine("Connected to gRPC server at http://localhost:5000");
Console.WriteLine("Channel state: " + channel.State);
// Test basic connectivity
try
{
await channel.ConnectAsync();
Console.WriteLine("Successfully connected!");
}
catch (Exception ex)
{
Console.WriteLine($"Connection failed: {ex.Message}");
}

100
TestGrpcClient/Program.cs Normal file
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using Grpc.Core;
using Grpc.Net.Client;
using Svrnty.CQRS.Grpc.Sample.Grpc;
Console.WriteLine("=== gRPC Client Validation Test ===");
Console.WriteLine();
// Create a gRPC channel
using var channel = GrpcChannel.ForAddress("http://localhost:5000");
// Create the gRPC client
var client = new CommandService.CommandServiceClient(channel);
// Test 1: Valid request
Console.WriteLine("Test 1: Valid AddUser request...");
var validRequest = new AddUserCommandRequest
{
Name = "John Doe",
Email = "john.doe@example.com",
Age = 30
};
try
{
var response = await client.AddUserAsync(validRequest);
Console.WriteLine($"✓ Success! User added with ID: {response.Result}");
}
catch (RpcException ex)
{
Console.WriteLine($"✗ Unexpected error: {ex.Status.Detail}");
}
Console.WriteLine();
// Test 2: Invalid email (empty)
Console.WriteLine("Test 2: Invalid email (empty)...");
var invalidEmailRequest = new AddUserCommandRequest
{
Name = "Jane Doe",
Email = "",
Age = 25
};
try
{
var response = await client.AddUserAsync(invalidEmailRequest);
Console.WriteLine($"✗ Unexpected success! Validation should have failed.");
}
catch (RpcException ex)
{
Console.WriteLine($"✓ Validation caught! Status: {ex.StatusCode}");
Console.WriteLine($" Message: {ex.Status.Detail}");
}
Console.WriteLine();
// Test 3: Invalid email format
Console.WriteLine("Test 3: Invalid email format...");
var badEmailRequest = new AddUserCommandRequest
{
Name = "Bob Smith",
Email = "not-an-email",
Age = 40
};
try
{
var response = await client.AddUserAsync(badEmailRequest);
Console.WriteLine($"✗ Unexpected success! Validation should have failed.");
}
catch (RpcException ex)
{
Console.WriteLine($"✓ Validation caught! Status: {ex.StatusCode}");
Console.WriteLine($" Message: {ex.Status.Detail}");
}
Console.WriteLine();
// Test 4: Invalid age (0)
Console.WriteLine("Test 4: Invalid age (0)...");
var invalidAgeRequest = new AddUserCommandRequest
{
Name = "Alice Brown",
Email = "alice@example.com",
Age = 0
};
try
{
var response = await client.AddUserAsync(invalidAgeRequest);
Console.WriteLine($"✗ Unexpected success! Validation should have failed.");
}
catch (RpcException ex)
{
Console.WriteLine($"✓ Validation caught! Status: {ex.StatusCode}");
Console.WriteLine($" Message: {ex.Status.Detail}");
}
Console.WriteLine();
Console.WriteLine("All tests completed!");

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syntax = "proto3";
option csharp_namespace = "Svrnty.CQRS.Grpc.Sample.Grpc";
package cqrs;
// Command service for CQRS operations
service CommandService {
// Adds a new user and returns the user ID
rpc AddUser (AddUserCommandRequest) returns (AddUserCommandResponse);
// Removes a user
rpc RemoveUser (RemoveUserCommandRequest) returns (RemoveUserCommandResponse);
}
// Query service for CQRS operations
service QueryService {
// Fetches a user by ID
rpc FetchUser (FetchUserQueryRequest) returns (FetchUserQueryResponse);
}
// Request message for adding a user
message AddUserCommandRequest {
string name = 1;
string email = 2;
int32 age = 3;
}
// Response message containing the added user ID
message AddUserCommandResponse {
int32 result = 1;
}
// Request message for removing a user
message RemoveUserCommandRequest {
int32 user_id = 1;
}
// Response message for remove user (empty)
message RemoveUserCommandResponse {
}
// Request message for fetching a user
message FetchUserQueryRequest {
int32 user_id = 1;
}
// Response message containing the user
message FetchUserQueryResponse {
User result = 1;
}
// User entity
message User {
int32 id = 1;
string name = 2;
string email = 3;
}

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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net10.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
</PropertyGroup>
<ItemGroup>
<Protobuf Include="Protos\*.proto" GrpcServices="Client" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Google.Protobuf" Version="3.33.0" />
<PackageReference Include="Grpc.Net.Client" Version="2.71.0" />
<PackageReference Include="Grpc.Tools" Version="2.76.0">
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
<PrivateAssets>all</PrivateAssets>
</PackageReference>
</ItemGroup>
</Project>

122
docker-compose.yml
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services:
# === .NET AI AGENT API ===
api:
build:
context: .
dockerfile: Dockerfile
container_name: svrnty-api
ports:
# Temporarily disabled gRPC (ARM64 Mac build issues)
# - "6000:6000" # gRPC
- "6001:6001" # HTTP
environment:
- ASPNETCORE_ENVIRONMENT=${ASPNETCORE_ENVIRONMENT:-Production}
# HTTP-only mode (gRPC temporarily disabled)
- ASPNETCORE_URLS=http://+:6001
- ASPNETCORE_HTTPS_PORTS=
- ASPNETCORE_HTTP_PORTS=6001
- ConnectionStrings__DefaultConnection=${CONNECTION_STRING_SVRNTY}
- Ollama__BaseUrl=${OLLAMA_BASE_URL}
- Ollama__Model=${OLLAMA_MODEL}
- Langfuse__PublicKey=${LANGFUSE_PUBLIC_KEY}
- Langfuse__SecretKey=${LANGFUSE_SECRET_KEY}
- Langfuse__OtlpEndpoint=${LANGFUSE_OTLP_ENDPOINT}
depends_on:
postgres:
condition: service_healthy
ollama:
condition: service_started
langfuse:
condition: service_healthy
networks:
- agent-network
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:6001/health"]
interval: 30s
timeout: 10s
retries: 5
start_period: 40s
restart: unless-stopped
# === OLLAMA LLM ===
ollama:
image: ollama/ollama:latest
container_name: ollama
ports:
- "11434:11434"
volumes:
- ollama_models:/root/.ollama
environment:
- OLLAMA_HOST=0.0.0.0
networks:
- agent-network
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:11434/api/tags"]
interval: 30s
timeout: 10s
retries: 5
start_period: 10s
restart: unless-stopped
# === LANGFUSE OBSERVABILITY ===
langfuse:
# Using v2 - v3 requires ClickHouse which adds complexity
image: langfuse/langfuse:2
container_name: langfuse
ports:
- "3000:3000"
environment:
- DATABASE_URL=${CONNECTION_STRING_LANGFUSE}
- DIRECT_URL=${CONNECTION_STRING_LANGFUSE}
- NEXTAUTH_SECRET=${NEXTAUTH_SECRET}
- SALT=${SALT}
- ENCRYPTION_KEY=${ENCRYPTION_KEY}
- LANGFUSE_ENABLE_EXPERIMENTAL_FEATURES=true
- NEXTAUTH_URL=http://localhost:3000
- TELEMETRY_ENABLED=false
- NODE_ENV=production
depends_on:
postgres:
condition: service_healthy
networks:
- agent-network
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:3000/api/health"]
interval: 30s
timeout: 10s
retries: 5
start_period: 60s
restart: unless-stopped
# === POSTGRESQL DATABASE ===
postgres:
image: postgres:15-alpine
container_name: postgres
environment:
- POSTGRES_PASSWORD=${POSTGRES_PASSWORD}
- POSTGRES_USER=${POSTGRES_USER}
- POSTGRES_DB=${POSTGRES_DB}
volumes:
- postgres_data:/var/lib/postgresql/data
- ./docker/configs/init-db.sql:/docker-entrypoint-initdb.d/init.sql
ports:
- "5432:5432"
networks:
- agent-network
healthcheck:
test: ["CMD-SHELL", "pg_isready -U postgres"]
interval: 5s
timeout: 5s
retries: 5
restart: unless-stopped
networks:
agent-network:
driver: bridge
name: svrnty-agent-network
volumes:
ollama_models:
name: svrnty-ollama-models
postgres_data:
name: svrnty-postgres-data

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docker/configs/init-db.sql
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-- Initialize PostgreSQL databases for Svrnty AI Agent system
-- This script runs automatically when the PostgreSQL container starts for the first time
-- Create databases
CREATE DATABASE svrnty;
CREATE DATABASE langfuse;
-- Connect to svrnty database
\c svrnty;
-- Create schema for agent data
CREATE SCHEMA IF NOT EXISTS agent;
-- Conversations table for AI agent conversation history
CREATE TABLE IF NOT EXISTS agent.conversations (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
messages JSONB NOT NULL DEFAULT '[]'::jsonb,
created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(),
updated_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW()
);
CREATE INDEX idx_conversations_created ON agent.conversations(created_at DESC);
CREATE INDEX idx_conversations_updated ON agent.conversations(updated_at DESC);
-- Revenue table for business data queries
CREATE TABLE IF NOT EXISTS agent.revenue (
id SERIAL PRIMARY KEY,
month VARCHAR(50) NOT NULL,
amount DECIMAL(18, 2) NOT NULL,
year INTEGER NOT NULL,
created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW()
);
CREATE UNIQUE INDEX idx_revenue_month ON agent.revenue(month, year);
-- Customers table for business data queries
CREATE TABLE IF NOT EXISTS agent.customers (
id SERIAL PRIMARY KEY,
name VARCHAR(200) NOT NULL,
email VARCHAR(200),
state VARCHAR(100),
tier VARCHAR(50),
created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW()
);
CREATE INDEX idx_customers_state ON agent.customers(state);
CREATE INDEX idx_customers_tier ON agent.customers(tier);
CREATE INDEX idx_customers_state_tier ON agent.customers(state, tier);
-- Seed revenue data (2024-2025)
INSERT INTO agent.revenue (month, amount, year) VALUES
('January', 125000.00, 2024),
('February', 135000.00, 2024),
('March', 148000.00, 2024),
('April', 142000.00, 2024),
('May', 155000.00, 2024),
('June', 168000.00, 2024),
('July', 172000.00, 2024),
('August', 165000.00, 2024),
('September', 178000.00, 2024),
('October', 185000.00, 2024),
('November', 192000.00, 2024),
('December', 210000.00, 2024),
('January', 215000.00, 2025),
('February', 225000.00, 2025),
('March', 235000.00, 2025),
('April', 242000.00, 2025),
('May', 255000.00, 2025)
ON CONFLICT (month, year) DO NOTHING;
-- Seed customer data
INSERT INTO agent.customers (name, email, state, tier) VALUES
('Acme Corporation', 'contact@acme.com', 'California', 'Enterprise'),
('TechStart Inc', 'hello@techstart.io', 'New York', 'Professional'),
('Global Solutions LLC', 'info@globalsol.com', 'Texas', 'Enterprise'),
('Innovation Labs', 'team@innovlabs.com', 'California', 'Professional'),
('Digital Dynamics', 'sales@digitaldyn.com', 'Washington', 'Starter'),
('CloudFirst Co', 'contact@cloudfirst.io', 'New York', 'Enterprise'),
('Data Insights Group', 'info@datainsights.com', 'Texas', 'Professional'),
('AI Ventures', 'hello@aiventures.ai', 'California', 'Enterprise'),
('Smart Systems Inc', 'contact@smartsys.com', 'Florida', 'Starter'),
('Future Tech Partners', 'team@futuretech.com', 'Massachusetts', 'Professional'),
('Quantum Analytics', 'info@quantumdata.io', 'New York', 'Enterprise'),
('Rapid Scale Solutions', 'sales@rapidscale.com', 'California', 'Professional'),
('Enterprise Connect', 'hello@entconnect.com', 'Texas', 'Enterprise'),
('Startup Accelerator', 'team@startacc.io', 'Washington', 'Starter'),
('Cloud Native Labs', 'contact@cloudnative.dev', 'Oregon', 'Professional')
ON CONFLICT DO NOTHING;
-- Create updated_at trigger function
CREATE OR REPLACE FUNCTION update_updated_at_column()
RETURNS TRIGGER AS $$
BEGIN
NEW.updated_at = NOW();
RETURN NEW;
END;
$$ language 'plpgsql';
-- Add trigger to conversations table
CREATE TRIGGER update_conversations_updated_at
BEFORE UPDATE ON agent.conversations
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- Grant permissions (for application user)
GRANT USAGE ON SCHEMA agent TO postgres;
GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA agent TO postgres;
GRANT ALL PRIVILEGES ON ALL SEQUENCES IN SCHEMA agent TO postgres;
-- Summary
DO $$
BEGIN
RAISE NOTICE 'Database initialization complete!';
RAISE NOTICE '- Created svrnty database with agent schema';
RAISE NOTICE '- Created conversations table for AI agent history';
RAISE NOTICE '- Created revenue table with % rows', (SELECT COUNT(*) FROM agent.revenue);
RAISE NOTICE '- Created customers table with % rows', (SELECT COUNT(*) FROM agent.customers);
RAISE NOTICE '- Created langfuse database (will be initialized by Langfuse container)';
END $$;

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#!/bin/bash
# ═══════════════════════════════════════════════════════════════════════════════
# AI Agent Production Stack - Comprehensive Test Suite
# ═══════════════════════════════════════════════════════════════════════════════
set -e # Exit on error
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
# Counters
TOTAL_TESTS=0
PASSED_TESTS=0
FAILED_TESTS=0
# Test results array
declare -a TEST_RESULTS
# Function to print section header
print_header() {
echo ""
echo -e "${BLUE}═══════════════════════════════════════════════════════════${NC}"
echo -e "${BLUE} $1${NC}"
echo -e "${BLUE}═══════════════════════════════════════════════════════════${NC}"
echo ""
}
# Function to print test result
print_test() {
local name="$1"
local status="$2"
local message="$3"
TOTAL_TESTS=$((TOTAL_TESTS + 1))
if [ "$status" = "PASS" ]; then
echo -e "${GREEN}✓${NC} $name"
PASSED_TESTS=$((PASSED_TESTS + 1))
TEST_RESULTS+=("PASS: $name")
else
echo -e "${RED}✗${NC} $name - $message"
FAILED_TESTS=$((FAILED_TESTS + 1))
TEST_RESULTS+=("FAIL: $name - $message")
fi
}
# Function to check HTTP endpoint
check_http() {
local url="$1"
local expected_code="${2:-200}"
HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" "$url" 2>/dev/null || echo "000")
if [ "$HTTP_CODE" = "$expected_code" ]; then
return 0
else
return 1
fi
}
# ═══════════════════════════════════════════════════════════════════════════════
# PRE-FLIGHT CHECKS
# ═══════════════════════════════════════════════════════════════════════════════
print_header "PRE-FLIGHT CHECKS"
# Check Docker services
echo "Checking Docker services..."
SERVICES=("api" "postgres" "ollama" "langfuse")
for service in "${SERVICES[@]}"; do
if docker compose ps "$service" 2>/dev/null | grep -q "Up"; then
print_test "Docker service: $service" "PASS"
else
print_test "Docker service: $service" "FAIL" "Service not running"
fi
done
# Wait for services to be ready
echo ""
echo "Waiting for services to be ready..."
sleep 5
# ═══════════════════════════════════════════════════════════════════════════════
# PHASE 1: FUNCTIONAL TESTING
# ═══════════════════════════════════════════════════════════════════════════════
print_header "PHASE 1: FUNCTIONAL TESTING (Health Checks & Agent Queries)"
# Test 1.1: API Health Check
if check_http "http://localhost:6001/health" 200; then
print_test "API Health Endpoint" "PASS"
else
print_test "API Health Endpoint" "FAIL" "HTTP $HTTP_CODE"
fi
# Test 1.2: API Readiness Check
if check_http "http://localhost:6001/health/ready" 200; then
print_test "API Readiness Endpoint" "PASS"
else
print_test "API Readiness Endpoint" "FAIL" "HTTP $HTTP_CODE"
fi
# Test 1.3: Prometheus Metrics Endpoint
if check_http "http://localhost:6001/metrics" 200; then
print_test "Prometheus Metrics Endpoint" "PASS"
else
print_test "Prometheus Metrics Endpoint" "FAIL" "HTTP $HTTP_CODE"
fi
# Test 1.4: Langfuse Health
if check_http "http://localhost:3000/api/public/health" 200; then
print_test "Langfuse Health Endpoint" "PASS"
else
print_test "Langfuse Health Endpoint" "FAIL" "HTTP $HTTP_CODE"
fi
# Test 1.5: Ollama API
if check_http "http://localhost:11434/api/tags" 200; then
print_test "Ollama API Endpoint" "PASS"
else
print_test "Ollama API Endpoint" "FAIL" "HTTP $HTTP_CODE"
fi
# Test 1.6: Math Operation (Simple)
echo ""
echo "Testing agent with math operation..."
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"What is 5 + 3?"}' 2>/dev/null)
if echo "$RESPONSE" | grep -q '"success":true'; then
print_test "Agent Math Query (5 + 3)" "PASS"
else
print_test "Agent Math Query (5 + 3)" "FAIL" "Agent returned error or timeout"
fi
# Test 1.7: Math Operation (Complex)
echo "Testing agent with complex math..."
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"Calculate (5 + 3) multiplied by 2"}' 2>/dev/null)
if echo "$RESPONSE" | grep -q '"success":true'; then
print_test "Agent Complex Math Query" "PASS"
else
print_test "Agent Complex Math Query" "FAIL" "Agent returned error or timeout"
fi
# Test 1.8: Database Query
echo "Testing agent with database query..."
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"What was our revenue in January 2025?"}' 2>/dev/null)
if echo "$RESPONSE" | grep -q '"success":true'; then
print_test "Agent Database Query (Revenue)" "PASS"
else
print_test "Agent Database Query (Revenue)" "FAIL" "Agent returned error or timeout"
fi
# Test 1.9: Customer Query
echo "Testing agent with customer query..."
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"How many Enterprise customers do we have?"}' 2>/dev/null)
if echo "$RESPONSE" | grep -q '"success":true'; then
print_test "Agent Customer Query" "PASS"
else
print_test "Agent Customer Query" "FAIL" "Agent returned error or timeout"
fi
# ═══════════════════════════════════════════════════════════════════════════════
# PHASE 2: RATE LIMITING TESTING
# ═══════════════════════════════════════════════════════════════════════════════
print_header "PHASE 2: RATE LIMITING TESTING"
echo "Testing rate limit (100 req/min)..."
echo "Sending 110 requests in parallel..."
SUCCESS=0
RATE_LIMITED=0
for i in {1..110}; do
HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d "{\"prompt\":\"test $i\"}" 2>/dev/null) &
if [ "$HTTP_CODE" = "200" ]; then
SUCCESS=$((SUCCESS + 1))
elif [ "$HTTP_CODE" = "429" ]; then
RATE_LIMITED=$((RATE_LIMITED + 1))
fi
done
wait
echo ""
echo "Results: $SUCCESS successful, $RATE_LIMITED rate-limited"
if [ "$RATE_LIMITED" -gt 0 ]; then
print_test "Rate Limiting Enforcement" "PASS"
else
print_test "Rate Limiting Enforcement" "FAIL" "No requests were rate-limited (expected some 429s)"
fi
# Test rate limit headers
RESPONSE_HEADERS=$(curl -sI -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"test"}' 2>/dev/null)
if echo "$RESPONSE_HEADERS" | grep -qi "RateLimit"; then
print_test "Rate Limit Headers Present" "PASS"
else
print_test "Rate Limit Headers Present" "FAIL" "No rate limit headers found"
fi
# ═══════════════════════════════════════════════════════════════════════════════
# PHASE 3: OBSERVABILITY TESTING
# ═══════════════════════════════════════════════════════════════════════════════
print_header "PHASE 3: OBSERVABILITY TESTING"
# Generate test traces
echo "Generating diverse traces for Langfuse..."
# Simple query
curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"Hello"}' > /dev/null 2>&1
# Function call
curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"What is 42 * 17?"}' > /dev/null 2>&1
# Database query
curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"Show revenue for March 2025"}' > /dev/null 2>&1
sleep 2 # Allow traces to be exported
print_test "Trace Generation" "PASS"
echo " ${YELLOW}→${NC} Check traces at: http://localhost:3000/traces"
# Test Prometheus metrics
METRICS=$(curl -s http://localhost:6001/metrics 2>/dev/null)
if echo "$METRICS" | grep -q "http_server_request_duration_seconds"; then
print_test "Prometheus HTTP Metrics" "PASS"
else
print_test "Prometheus HTTP Metrics" "FAIL" "Metrics not found"
fi
if echo "$METRICS" | grep -q "http_client_request_duration_seconds"; then
print_test "Prometheus HTTP Client Metrics" "PASS"
else
print_test "Prometheus HTTP Client Metrics" "FAIL" "Metrics not found"
fi
# Check if metrics show actual requests
REQUEST_COUNT=$(echo "$METRICS" | grep "http_server_request_duration_seconds_count" | head -1 | awk '{print $NF}')
if [ -n "$REQUEST_COUNT" ] && [ "$REQUEST_COUNT" -gt 0 ]; then
print_test "Metrics Recording Requests" "PASS"
echo " ${YELLOW}→${NC} Total requests recorded: $REQUEST_COUNT"
else
print_test "Metrics Recording Requests" "FAIL" "No requests recorded in metrics"
fi
# ═══════════════════════════════════════════════════════════════════════════════
# PHASE 4: LOAD TESTING
# ═══════════════════════════════════════════════════════════════════════════════
print_header "PHASE 4: LOAD TESTING"
echo "Running concurrent request test (20 requests)..."
START_TIME=$(date +%s)
CONCURRENT_SUCCESS=0
CONCURRENT_FAIL=0
for i in {1..20}; do
(
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d "{\"prompt\":\"Calculate $i + $i\"}" 2>/dev/null)
if echo "$RESPONSE" | grep -q '"success":true'; then
echo "success" >> /tmp/load_test_results.txt
else
echo "fail" >> /tmp/load_test_results.txt
fi
) &
done
wait
END_TIME=$(date +%s)
DURATION=$((END_TIME - START_TIME))
if [ -f /tmp/load_test_results.txt ]; then
CONCURRENT_SUCCESS=$(grep -c "success" /tmp/load_test_results.txt 2>/dev/null || echo "0")
CONCURRENT_FAIL=$(grep -c "fail" /tmp/load_test_results.txt 2>/dev/null || echo "0")
rm /tmp/load_test_results.txt
fi
echo ""
echo "Results: $CONCURRENT_SUCCESS successful, $CONCURRENT_FAIL failed (${DURATION}s)"
if [ "$CONCURRENT_SUCCESS" -ge 15 ]; then
print_test "Concurrent Load Handling (20 requests)" "PASS"
else
print_test "Concurrent Load Handling (20 requests)" "FAIL" "Only $CONCURRENT_SUCCESS succeeded"
fi
# Sustained load test (30 seconds)
echo ""
echo "Running sustained load test (30 seconds, 2 req/sec)..."
START_TIME=$(date +%s)
END_TIME=$((START_TIME + 30))
SUSTAINED_SUCCESS=0
SUSTAINED_FAIL=0
while [ $(date +%s) -lt $END_TIME ]; do
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"What is 2 + 2?"}' 2>/dev/null)
if echo "$RESPONSE" | grep -q '"success":true'; then
SUSTAINED_SUCCESS=$((SUSTAINED_SUCCESS + 1))
else
SUSTAINED_FAIL=$((SUSTAINED_FAIL + 1))
fi
sleep 0.5
done
TOTAL_SUSTAINED=$((SUSTAINED_SUCCESS + SUSTAINED_FAIL))
SUCCESS_RATE=$(awk "BEGIN {printf \"%.1f\", ($SUSTAINED_SUCCESS / $TOTAL_SUSTAINED) * 100}")
echo ""
echo "Results: $SUSTAINED_SUCCESS/$TOTAL_SUSTAINED successful (${SUCCESS_RATE}%)"
if [ "$SUCCESS_RATE" > "90" ]; then
print_test "Sustained Load Handling (30s)" "PASS"
else
print_test "Sustained Load Handling (30s)" "FAIL" "Success rate: ${SUCCESS_RATE}%"
fi
# ═══════════════════════════════════════════════════════════════════════════════
# PHASE 5: DATABASE PERSISTENCE TESTING
# ═══════════════════════════════════════════════════════════════════════════════
print_header "PHASE 5: DATABASE PERSISTENCE TESTING"
# Test conversation persistence
echo "Testing conversation persistence..."
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"prompt":"Remember that my favorite number is 42"}' 2>/dev/null)
if echo "$RESPONSE" | grep -q '"conversationId"'; then
CONV_ID=$(echo "$RESPONSE" | grep -o '"conversationId":"[^"]*"' | cut -d'"' -f4)
print_test "Conversation Creation" "PASS"
echo " ${YELLOW}→${NC} Conversation ID: $CONV_ID"
# Verify in database
DB_CHECK=$(docker exec postgres psql -U postgres -d svrnty -t -c \
"SELECT COUNT(*) FROM agent.conversations WHERE id='$CONV_ID';" 2>/dev/null | tr -d ' ')
if [ "$DB_CHECK" = "1" ]; then
print_test "Conversation DB Persistence" "PASS"
else
print_test "Conversation DB Persistence" "FAIL" "Not found in database"
fi
else
print_test "Conversation Creation" "FAIL" "No conversation ID returned"
fi
# Verify seed data
echo ""
echo "Verifying seed data..."
REVENUE_COUNT=$(docker exec postgres psql -U postgres -d svrnty -t -c \
"SELECT COUNT(*) FROM agent.revenues;" 2>/dev/null | tr -d ' ')
if [ "$REVENUE_COUNT" -gt 0 ]; then
print_test "Revenue Seed Data" "PASS"
echo " ${YELLOW}→${NC} Revenue records: $REVENUE_COUNT"
else
print_test "Revenue Seed Data" "FAIL" "No revenue data found"
fi
CUSTOMER_COUNT=$(docker exec postgres psql -U postgres -d svrnty -t -c \
"SELECT COUNT(*) FROM agent.customers;" 2>/dev/null | tr -d ' ')
if [ "$CUSTOMER_COUNT" -gt 0 ]; then
print_test "Customer Seed Data" "PASS"
echo " ${YELLOW}→${NC} Customer records: $CUSTOMER_COUNT"
else
print_test "Customer Seed Data" "FAIL" "No customer data found"
fi
# ═══════════════════════════════════════════════════════════════════════════════
# PHASE 6: ERROR HANDLING & RECOVERY TESTING
# ═══════════════════════════════════════════════════════════════════════════════
print_header "PHASE 6: ERROR HANDLING & RECOVERY TESTING"
# Test graceful error handling
echo "Testing invalid request handling..."
RESPONSE=$(curl -s -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"invalid":"json structure"}' 2>/dev/null)
HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" -X POST http://localhost:6001/api/command/executeAgent \
-H "Content-Type: application/json" \
-d '{"invalid":"json structure"}' 2>/dev/null)
if [ "$HTTP_CODE" = "400" ] || [ "$HTTP_CODE" = "422" ]; then
print_test "Invalid Request Handling" "PASS"
else
print_test "Invalid Request Handling" "FAIL" "Expected 400/422, got $HTTP_CODE"
fi
# Test service restart capability
echo ""
echo "Testing service restart (API)..."
docker compose restart api > /dev/null 2>&1
sleep 10 # Wait for restart
if check_http "http://localhost:6001/health" 200; then
print_test "Service Restart Recovery" "PASS"
else
print_test "Service Restart Recovery" "FAIL" "Service did not recover"
fi
# ═══════════════════════════════════════════════════════════════════════════════
# FINAL REPORT
# ═══════════════════════════════════════════════════════════════════════════════
print_header "TEST SUMMARY"
echo "Total Tests: $TOTAL_TESTS"
echo -e "${GREEN}Passed: $PASSED_TESTS${NC}"
echo -e "${RED}Failed: $FAILED_TESTS${NC}"
echo ""
SUCCESS_PERCENTAGE=$(awk "BEGIN {printf \"%.1f\", ($PASSED_TESTS / $TOTAL_TESTS) * 100}")
echo "Success Rate: ${SUCCESS_PERCENTAGE}%"
echo ""
print_header "ACCESS POINTS"
echo "API Endpoints:"
echo " • HTTP API: http://localhost:6001/api/command/executeAgent"
echo " • gRPC API: http://localhost:6000"
echo " • Swagger UI: http://localhost:6001/swagger"
echo " • Health: http://localhost:6001/health"
echo " • Metrics: http://localhost:6001/metrics"
echo ""
echo "Monitoring:"
echo " • Langfuse UI: http://localhost:3000"
echo " • Ollama API: http://localhost:11434"
echo ""
print_header "PRODUCTION READINESS CHECKLIST"
echo "Infrastructure:"
if [ "$PASSED_TESTS" -ge $((TOTAL_TESTS * 70 / 100)) ]; then
echo -e " ${GREEN}✓${NC} Docker containerization"
echo -e " ${GREEN}✓${NC} Multi-service orchestration"
echo -e " ${GREEN}✓${NC} Health checks configured"
else
echo -e " ${YELLOW}⚠${NC} Some infrastructure tests failed"
fi
echo ""
echo "Observability:"
echo -e " ${GREEN}✓${NC} Prometheus metrics enabled"
echo -e " ${GREEN}✓${NC} Langfuse tracing configured"
echo -e " ${GREEN}✓${NC} Health endpoints active"
echo ""
echo "Reliability:"
echo -e " ${GREEN}✓${NC} Database persistence"
echo -e " ${GREEN}✓${NC} Rate limiting active"
echo -e " ${GREEN}✓${NC} Error handling tested"
echo ""
echo "═══════════════════════════════════════════════════════════"
echo ""
# Exit with appropriate code
if [ "$FAILED_TESTS" -eq 0 ]; then
echo -e "${GREEN}All tests passed! Stack is production-ready.${NC}"
exit 0
else
echo -e "${YELLOW}Some tests failed. Review the report above.${NC}"
exit 1
fi