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()andcreate_embedding_model()return standard LangChainBaseChatModel/Embeddingsinstances. 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 --
CircuitBreakerandCircuitBreakerRegistrytrip 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.
1 maintainer
Release files for 3tears-models 0.51.0
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