3tears-models 0.18.0

LangChain-native AI model factories with capability metadata, circuit breakers, and usage tracking for the 3tears platform

3tears-models

LangChain-native AI model factories for the 3tears framework. Build chat and embedding models from a single call, with capability metadata, circuit breakers, error translation, and usage tracking wired in.

pip install 3tears-models

What you get

• Factories -- create_chat_model() and create_embedding_model() return standard LangChain BaseChatModel / Embeddings instances. No custom runtime protocols to learn.
• Providers -- Anthropic, OpenAI, OpenRouter, VoyageAI, Whisper, and image backends (OpenAI Images, HuggingFace, A1111, ModelsLab, ComfyUI).
• Capability registry -- get_capabilities(), register_capabilities(), and per-model overrides describe context windows, vision support, tool support, and tier.
• Circuit breakers -- CircuitBreaker and CircuitBreakerRegistry trip on repeated provider failures and recover on a timer.
• Usage tracking -- UsageTracker.record() emits an OpenTelemetry span plus Prometheus instruments, with optional per-application audit and counter sinks.
• Message hygiene -- preprocess_messages(), enforce_alternating_roles(), filter_invalid_tool_calls(), and streaming chunk helpers (parse_chunk, merge_chunks).

Quickstart

from threetears.models import create_chat_model, create_embedding_model

chat = create_chat_model("claude-sonnet-4-6")
reply = await chat.ainvoke("Summarize three-tier caching in one sentence.")

embedder = create_embedding_model("voyage-3")
vectors = await embedder.aembed_documents(["first doc", "second doc"])

Capabilities, circuit breakers, and usage tracking attach automatically. Reach for the registry and tracker APIs directly when you need to inspect or override them.

License

MIT. See LICENSE.