8848a310dfAdds a self-contained RAG stack to Studio: knowledge bases with chunked indexing, hybrid (dense + lexical) retrieval, and an automatic first-pass context inject into chat. Embeddings run through a local llama-server GGUF backend (default unsloth/bge-small-en-v1.5-GGUF) with a sentence-transformers fallback. The chat tool loop gains a search_knowledge_base tool, a per-turn re-search cap, and source citation, layered on top of the shared ToolLoopController.
39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""
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API Routes
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"""
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from routes.training import router as training_router
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from routes.models import router as models_router
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from routes.inference import router as inference_router
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from routes.inference import studio_router as inference_studio_router
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from routes.datasets import router as datasets_router
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from routes.auth import router as auth_router
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from routes.data_recipe import router as data_recipe_router
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from routes.export import router as export_router
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from routes.training_history import router as training_history_router
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from routes.chat_history import router as chat_history_router
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from routes.providers import router as providers_router
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from routes.mcp_servers import router as mcp_servers_router
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from routes.rag import router as rag_router
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__all__ = [
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"training_router",
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"models_router",
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"inference_router",
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"inference_studio_router",
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"datasets_router",
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"auth_router",
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"data_recipe_router",
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"export_router",
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"training_history_router",
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"chat_history_router",
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"providers_router",
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"mcp_servers_router",
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"rag_router",
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]
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# Bind the re-export so the import-hoist verifier counts it as used.
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_ = (rag_router,)
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