jharness-models

OpenAI Chat (Chat Completions API), OpenAI Responses, and Anthropic Messages adapters; DeepSeek profiles; and provider-neutral model composition for the JHarness kernel.

uv add jharness-models

from jharness.models.openai import OpenAIResponsesModel

DeepSeek's native Responses endpoint uses OpenAIResponsesModel with deepseek_responses_profile. That profile is text-only, accepts only deepseek-v4-flash, exposes provider-hosted web search plus the exact freeform apply_patch runtime tool, and forces stateless requests with complete history. The DeepSeek Messages profile independently exposes its verified server-side web search.

Model modalities describe what the model itself understands or produces. Tool ownership is separate: RuntimeToolCall is executed by the JHarness runtime, while a ProviderToolCall records work already executed by the supplier. Both remain interleaved with ContentPart values in ordered output.

Each protocol profile contains the exact immutable ModelCapabilities returned by its model client. The default Responses and Messages profile classes remain provider-tool neutral. The official openai_responses_profile() and anthropic_messages_profile() factories install their hosted-tool identities and codecs, but do not add a tool to any request. The host must still pass an explicit ProviderToolSpec factory result to Runtime, and selecting an official profile is the host's confirmation that the chosen endpoint and model support its advertised capabilities. Tool selection is declared as a set of supported types rather than a coarse boolean. Supplier factories only compose protocol capabilities and wire policies; the shared codecs contain no supplier-name branches.

from jharness.kernel import Runtime
from jharness.models.openai import (
    OpenAIResponsesModel,
    openai_responses_profile,
    openai_responses_web_search,
)

model = OpenAIResponsesModel(..., profile=openai_responses_profile())
runtime = Runtime(
    model=model,
    provider_tools=(openai_responses_web_search(),),
)

OpenAI Responses sends store=false by default and requests encrypted reasoning history. Hosted image generation additionally requires a host-owned OpenAIResponsesArtifactStore; generated base64 is persisted externally and durable history contains only integrity-bearing ArtifactRef values. Stores must be durable, idempotent, safe for provider-controlled call ids, available during run recovery, and responsible for retention and garbage collection of uncommitted saves.

Retry and fallback compose directly around model values:

from jharness.models.decorators import FallbackModel, RetryingModel

model = FallbackModel(
    RetryingModel(primary_model, max_attempts=3),
    RetryingModel(backup_model, max_attempts=2),
)

Installing this distribution installs the exact matching jharness-kernel version. Provider configuration and composition details are in the model adapter guide.