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.NET: Adds Valkey to chat message history - issue 5445 (#5542)
* Adds Valkey to chat message history * Address review: switch to Valkey.Glide, add options class, remove context provider - Switch from StackExchange.Redis to Valkey.Glide 1.1.0 (official Valkey .NET client) - Extract optional params into ValkeyChatHistoryProviderOptions - Add JsonSerializerOptions support, remove [RequiresUnreferencedCode] - Make MaxMessages/MaxMessagesToRetrieve readonly via options - Remove ValkeyContextProvider (overlaps with ChatHistoryMemoryProvider + MEVD) - Remove ValkeyProviderScope (only used by context provider) - Remove connection string constructors (caller manages IConnectionMultiplexer) - Update samples to use new API and gpt-5.4-mini * Use type-safe JsonSerializer overloads, remove suppress attributes Use JsonSerializerOptions.GetTypeInfo() for Serialize/Deserialize calls to enable NativeAOT/trimming compatibility without suppress attributes. Default to AgentAbstractionsJsonUtilities.DefaultOptions when no options provided. Signed-off-by: Matthias Howell <matthias.howell@improving.com> * Update READMEs: remove context provider references Remove ValkeyContextProvider and long-term memory references from sample READMEs since the context provider was removed from this PR. Simplify Valkey server requirements (no search module needed for chat history). Signed-off-by: Matthias Howell <matthias.howell@improving.com> * Apply suggestion from @westey-m * Fix formatting (dotnet format) Signed-off-by: Matthias Howell <matthias.howell@improving.com> * Update dotnet/src/Microsoft.Agents.AI.Valkey/Microsoft.Agents.AI.Valkey.csproj Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com> --------- Signed-off-by: Matthias Howell <matthias.howell@improving.com> Co-authored-by: Matthias Howell <matthias.howell@yoppworks.com> Co-authored-by: westey <164392973+westey-m@users.noreply.github.com> Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>
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Matthias Howell
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFrameworks>net10.0</TargetFrameworks>
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<Nullable>enable</Nullable>
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<ImplicitUsings>enable</ImplicitUsings>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Azure.AI.OpenAI" />
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<PackageReference Include="Azure.Identity" />
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<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
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<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Valkey\Microsoft.Agents.AI.Valkey.csproj" />
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</ItemGroup>
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</Project>
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// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates using Valkey for persistent chat history with the Agent Framework.
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// ValkeyChatHistoryProvider persists conversation history across sessions using Valkey lists.
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//
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// Prerequisites:
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// - A running Valkey server (any version):
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// docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
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// - Azure OpenAI endpoint and deployment configured via environment variables
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using Azure.AI.OpenAI;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.Valkey;
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using Microsoft.Extensions.AI;
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using OpenAI.Chat;
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using Valkey.Glide;
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var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
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var valkeyConnection = Environment.GetEnvironmentVariable("VALKEY_CONNECTION") ?? "localhost:6379";
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var connection = await ConnectionMultiplexer.ConnectAsync(valkeyConnection);
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Console.WriteLine("=== ValkeyChatHistoryProvider — Persistent Chat History ===\n");
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var historyProvider = new ValkeyChatHistoryProvider(
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connection,
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_ => new ValkeyChatHistoryProvider.State($"sample-{Guid.NewGuid():N}"),
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new ValkeyChatHistoryProviderOptions
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{
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KeyPrefix = "sample_chat",
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MaxMessages = 20
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});
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AIAgent historyAgent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
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.GetChatClient(deploymentName)
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.AsAIAgent(new ChatClientAgentOptions()
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{
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ChatOptions = new() { Instructions = "You are a helpful assistant that remembers our conversation." },
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ChatHistoryProvider = historyProvider
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});
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AgentSession session1 = await historyAgent.CreateSessionAsync();
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Console.WriteLine(await historyAgent.RunAsync("Hello! My name is Alex and I'm a software engineer.", session1));
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Console.WriteLine(await historyAgent.RunAsync("I'm working on a project using Valkey for caching.", session1));
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Console.WriteLine(await historyAgent.RunAsync("What do you remember about me?", session1));
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var messageCount = await historyProvider.GetMessageCountAsync(session1);
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Console.WriteLine($"\n Stored {messageCount} messages in Valkey.\n");
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// Clean up
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connection.Dispose();
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Console.WriteLine("Done!");
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# Agent with Memory Using Valkey
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This sample demonstrates using Valkey for persistent chat history with the Agent Framework.
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## Components
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- **ValkeyChatHistoryProvider** — Persists conversation history across sessions using Valkey lists. Works with any Valkey or Redis OSS server (no search module required).
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## Prerequisites
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- Azure OpenAI endpoint and deployment
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- A running Valkey server (any version):
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```bash
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docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
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```
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## Environment Variables
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| Variable | Description | Default |
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|---|---|---|
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| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI endpoint URL | (required) |
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| `AZURE_OPENAI_DEPLOYMENT_NAME` | Model deployment name | `gpt-5.4-mini` |
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| `VALKEY_CONNECTION` | Valkey connection string | `localhost:6379` |
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## Running
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```bash
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dotnet run
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```
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+20
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFrameworks>net10.0</TargetFrameworks>
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<Nullable>enable</Nullable>
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<ImplicitUsings>enable</ImplicitUsings>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="AWSSDK.Extensions.Bedrock.MEAI" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
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<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Valkey\Microsoft.Agents.AI.Valkey.csproj" />
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</ItemGroup>
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</Project>
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// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates using Valkey for persistent chat history with the Agent Framework,
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// powered by Amazon Bedrock.
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//
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// Prerequisites:
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// - A running Valkey server (any version):
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// docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
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// - AWS credentials configured (environment variables, AWS profile, or IAM role)
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// - Access to an Amazon Bedrock model (e.g., Anthropic Claude)
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using Amazon;
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using Amazon.BedrockRuntime;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.Valkey;
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using Microsoft.Extensions.AI;
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using Valkey.Glide;
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var awsRegion = Environment.GetEnvironmentVariable("AWS_REGION") ?? "us-east-1";
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var modelId = Environment.GetEnvironmentVariable("BEDROCK_MODEL_ID") ?? "anthropic.claude-3-5-sonnet-20241022-v2:0";
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var valkeyConnection = Environment.GetEnvironmentVariable("VALKEY_CONNECTION") ?? "localhost:6379";
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// Create the Bedrock runtime client.
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var bedrockRuntime = new AmazonBedrockRuntimeClient(RegionEndpoint.GetBySystemName(awsRegion));
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IChatClient chatClient = bedrockRuntime.AsIChatClient(modelId);
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var connection = await ConnectionMultiplexer.ConnectAsync(valkeyConnection);
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Console.WriteLine("=== ValkeyChatHistoryProvider — Persistent Chat History (Bedrock) ===\n");
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var historyProvider = new ValkeyChatHistoryProvider(
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connection,
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_ => new ValkeyChatHistoryProvider.State($"bedrock-sample-{Guid.NewGuid():N}"),
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new ValkeyChatHistoryProviderOptions
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{
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KeyPrefix = "bedrock_chat",
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MaxMessages = 20
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});
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AIAgent historyAgent = chatClient.AsAIAgent(new ChatClientAgentOptions()
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{
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ChatOptions = new() { Instructions = "You are a helpful assistant that remembers our conversation." },
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ChatHistoryProvider = historyProvider
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});
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AgentSession session1 = await historyAgent.CreateSessionAsync();
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Console.WriteLine(await historyAgent.RunAsync("Hello! My name is Alex and I'm a software engineer.", session1));
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Console.WriteLine(await historyAgent.RunAsync("I'm working on a project using Valkey for caching.", session1));
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Console.WriteLine(await historyAgent.RunAsync("What do you remember about me?", session1));
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var messageCount = await historyProvider.GetMessageCountAsync(session1);
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Console.WriteLine($"\n Stored {messageCount} messages in Valkey.\n");
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// Clean up
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connection.Dispose();
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Console.WriteLine("Done!");
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# Agent with Memory Using Valkey + Amazon Bedrock
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This sample demonstrates using Valkey for persistent chat history with the Agent Framework, powered by Amazon Bedrock via the `AWSSDK.Extensions.Bedrock.MEAI` adapter.
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## Components
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- **ValkeyChatHistoryProvider** — Persists conversation history across sessions using Valkey lists. Works with any Valkey or Redis OSS server (no search module required).
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- **Amazon Bedrock** — Provides the LLM via `AWSSDK.Extensions.Bedrock.MEAI`, which implements `IChatClient` from `Microsoft.Extensions.AI`.
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## Prerequisites
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- AWS credentials configured (environment variables, AWS CLI profile, or IAM role)
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- Access to an Amazon Bedrock model (e.g., Anthropic Claude 3.5 Sonnet)
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- A running Valkey server (any version):
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```bash
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docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
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```
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## Environment Variables
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| Variable | Description | Default |
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|---|---|---|
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| `AWS_REGION` | AWS region for Bedrock | `us-east-1` |
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| `BEDROCK_MODEL_ID` | Bedrock model identifier | `anthropic.claude-3-5-sonnet-20241022-v2:0` |
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| `VALKEY_CONNECTION` | Valkey connection string | `localhost:6379` |
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| `AWS_ACCESS_KEY_ID` | AWS access key (if not using profile/role) | — |
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| `AWS_SECRET_ACCESS_KEY` | AWS secret key (if not using profile/role) | — |
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## Running
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```bash
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# Using default AWS credential chain (profile, env vars, or IAM role)
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dotnet run
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# Or with explicit credentials
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export AWS_ACCESS_KEY_ID="your-access-key"
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export AWS_SECRET_ACCESS_KEY="your-secret-key"
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export AWS_REGION="us-east-1"
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dotnet run
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```
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