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	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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			106 KiB
		
	
	
	
		
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			3587 lines
		
	
	
	
		
			106 KiB
		
	
	
	
		
			JSON
		
	
	
	
	
		
			Generated
		
	
	
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|           "content": "Show me marketing and sales documents"
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|                 "name": "knowledge_search",
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|                 "arguments": "{\"query\": \"marketing documents examples\"}"
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|               "type": "function",
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|                 "name": "knowledge_search",
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|                 "arguments": "{\"query\": \"sales documents examples\"}"
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|               "type": "text",
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|               "text": "knowledge_search tool found 3 chunks:\nBEGIN of knowledge_search tool results.\n"
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|               "text": "[1] document_id: file-862946202236, score: 0.7656461893973538, attributes: {'region': 'eu', 'category': 'marketing', 'date': 1672531200.0, 'filename': 'eu_marketing_q1.txt', 'document_id': 'file-862946202236', 'token_count': 17.0, 'metadata_token_count': 32.0} (cite as <|file-862946202236|>)\nEuropean advertising campaign results for Q1 2023. Strong growth in EU markets.\n"
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|               "text": "[3] document_id: file-862946202237, score: 0.5528548752393603, attributes: {'region': 'asia', 'category': 'sales', 'date': 1688169600.0, 'filename': 'asia_sales_q3.txt', 'document_id': 'file-862946202237', 'token_count': 17.0, 'metadata_token_count': 31.0} (cite as <|file-862946202237|>)\nAsia Pacific revenue figures for Q3 2023. Record breaking quarter in Asia.\n"
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|               "type": "text",
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|               "text": "END of knowledge_search tool results.\n"
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|             },
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|             {
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|               "type": "text",
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|               "type": "text",
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|               "text": "knowledge_search tool found 3 chunks:\nBEGIN of knowledge_search tool results.\n"
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