EntwineAgents.Intake 0.1.0

EntwineAgents

A lean, composable agent runtime for .NET — the shared substrate for building LLM agents that behave like software components: typed inputs and outputs, prompts managed as data, privacy by construction, and graceful degradation everywhere.

Extracted from a production system where the same agent loop had been hand-rolled fifteen times across three products. The loop lives here once; what varies stays yours.

The idea

An agent = a prompt (loaded by key, host-overridable) + input shaping + typed parsing + graceful degrade, riding a shell that owns the loop.

sealed class TaglineAgent(IAgentChat chat, IPromptSource? prompts = null) : Agent<string, string>(chat, prompts)
{
    protected override string Key => "quickstart.tagline.system";   // hosts can override by key
    protected override string FallbackPrompt =>
        "You write one short, punchy product tagline. Reply with the tagline only.";
    protected override bool Json => false;
    protected override string BuildUser(string product) => $"Product: {product}";
    protected override string Parse(string raw) => raw.Trim();
    protected override string OnFailure => "(the model was unavailable — try again)";
}

Four overrides carry everything that is domain-specific. The shell owns the loop: fetch the prompt by key (falling back to the built-in), run one turn, degrade to a typed failure value if the model or network fails, parse to a typed result. There is also a batched sibling, BatchAgent<TItem, TResult>, for classify-many-items work: chunking, per-batch retry, position-aligned parsing, and per-item degrade.

Run it:

set OPENAI_API_KEY=sk-...        # any OpenAI-compatible endpoint; OPENAI_BASE_URL / OPENAI_MODEL to override
dotnet run --project samples/QuickStart -- "a keyboard for cats"

Packages

Each package stands alone; take what you need. Runtime depends on Ai; Prompts depends on Runtime; everything else is independent.

Design principles

• Two seams, bridged once. IChatProvider is the SPI providers implement; IAgentChat is the API agents consume; ChatProviderAgentChat connects them. Your agents never know which model or vendor is behind them.
• Agents propose; algorithms compute; humans decide. The shells make agent output typed and validated so deterministic code — and people — can act on it. Nothing here auto-persists a model's opinion.
• Prompts are data. Loaded by key with a compiled fallback, so prompts can be versioned, per-client overridden, and served remotely — and a prompt-service outage can never take an agent down.
• Fail open, degrade typed. A failed call returns your OnFailure value, not an exception across your pipeline; a batch the model mangles degrades per-item, never by discarding the batch.
• Privacy by construction. Session-local pseudonyms for what reaches a model; separated-key tokenisation for what reaches a database.

Building

dotnet build entwine-agents.slnx
dotnet test  entwine-agents.slnx

Requires the .NET 10 SDK.

License

Apache-2.0