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fix: rag tool embeddings config
* fix: ensure config is not flattened, add tests * chore: refactor inits to model_validator * chore: refactor rag tool config parsing * chore: add initial docs * chore: add additional validation aliases for provider env vars * chore: add solid docs * chore: move imports to top * fix: revert circular import * fix: lazy import qdrant-client * fix: allow collection name config * chore: narrow model names for google * chore: update additional docs * chore: add backward compat on model name aliases * chore: add tests for config changes
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@@ -64,10 +64,10 @@ tool = JSONSearchTool(
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},
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},
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"embedding_model": {
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"provider": "google", # or openai, ollama, ...
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"provider": "google-generativeai", # or openai, ollama, ...
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"config": {
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"model": "models/embedding-001",
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"task_type": "retrieval_document",
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"model_name": "gemini-embedding-001",
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"task_type": "RETRIEVAL_DOCUMENT",
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# Further customization options can be added here.
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},
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},
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@@ -63,15 +63,15 @@ tool = PDFSearchTool(
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"config": {
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# Model identifier for the chosen provider. "model" will be auto-mapped to "model_name" internally.
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"model": "text-embedding-3-small",
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# Optional: API key. If omitted, the tool will use provider-specific env vars when available
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# (e.g., OPENAI_API_KEY for provider="openai").
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# Optional: API key. If omitted, the tool will use provider-specific env vars
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# (e.g., OPENAI_API_KEY or EMBEDDINGS_OPENAI_API_KEY for OpenAI).
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# "api_key": "sk-...",
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# Provider-specific examples:
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# --- Google Generative AI ---
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# (Set provider="google-generativeai" above)
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# "model": "models/embedding-001",
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# "task_type": "retrieval_document",
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# "model_name": "gemini-embedding-001",
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# "task_type": "RETRIEVAL_DOCUMENT",
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# "title": "Embeddings",
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# --- Cohere ---
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@@ -66,9 +66,9 @@ tool = TXTSearchTool(
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"provider": "openai", # or google-generativeai, cohere, ollama, ...
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"config": {
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"model": "text-embedding-3-small",
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# "api_key": "sk-...", # optional if env var is set
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# "api_key": "sk-...", # optional if env var is set (e.g., OPENAI_API_KEY or EMBEDDINGS_OPENAI_API_KEY)
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# Provider examples:
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# Google → model: "models/embedding-001", task_type: "retrieval_document"
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# Google → model_name: "gemini-embedding-001", task_type: "RETRIEVAL_DOCUMENT"
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# Cohere → model: "embed-english-v3.0"
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# Ollama → model: "nomic-embed-text"
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},
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