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feat(tests): make inference_recorder into api_recorder (include tool_invoke) (#3403)
Renames `inference_recorder.py` to `api_recorder.py` and extends it to support recording/replaying tool invocations in addition to inference calls. This allows us to record web-search, etc. tool calls and thereafter apply recordings for `tests/integration/responses` ## Test Plan ``` export OPENAI_API_KEY=... export TAVILY_SEARCH_API_KEY=... ./scripts/integration-tests.sh --stack-config ci-tests \ --suite responses --inference-mode record-if-missing ```
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284 changed files with 296191 additions and 631 deletions
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@ -40,6 +40,7 @@ from llama_stack.apis.vector_io import (
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VectorStoreSearchResponse,
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VectorStoreSearchResponsePage,
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)
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from llama_stack.core.id_generation import generate_object_id
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from llama_stack.log import get_logger
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from llama_stack.providers.utils.kvstore.api import KVStore
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from llama_stack.providers.utils.memory.vector_store import (
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@ -352,7 +353,7 @@ class OpenAIVectorStoreMixin(ABC):
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"""Creates a vector store."""
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created_at = int(time.time())
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# Derive the canonical vector_db_id (allow override, else generate)
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vector_db_id = provider_vector_db_id or f"vs_{uuid.uuid4()}"
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vector_db_id = provider_vector_db_id or generate_object_id("vector_store", lambda: f"vs_{uuid.uuid4()}")
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if provider_id is None:
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raise ValueError("Provider ID is required")
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@ -986,7 +987,7 @@ class OpenAIVectorStoreMixin(ABC):
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chunking_strategy = chunking_strategy or VectorStoreChunkingStrategyAuto()
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created_at = int(time.time())
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batch_id = f"batch_{uuid.uuid4()}"
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batch_id = generate_object_id("vector_store_file_batch", lambda: f"batch_{uuid.uuid4()}")
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# File batches expire after 7 days
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expires_at = created_at + (7 * 24 * 60 * 60)
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