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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.

Release files for 3tears-models 0.53.0

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