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https://github.com/httprunner/httprunner.git
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7c45acd061
- Add new AI Querier module for structured information extraction from screenshots - Support custom output schema for structured data response - Implement automatic type conversion and data validation - Add comprehensive test suite with various data structure examples - Refactor callModelWithLogging to utils.go as shared function for planner, asserter, and querier - Eliminate code duplication across AI modules (30+ lines of repeated code) - Improve maintainability with unified logging and timing logic - Add environment variable checks in test setup to handle missing API keys gracefully Key features: - Custom output schema support with JSON Schema generation - Automatic data type conversion with reflection - Fallback mechanisms for robust parsing - Comprehensive documentation and usage examples - Backward compatibility with existing functionality
21 lines
958 B
Go
21 lines
958 B
Go
package ai
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// Default query system prompt
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const defaultQueryPrompt = `You are an AI assistant specialized in analyzing images and extracting information. User will provide a screenshot and a query asking for specific information to be extracted from the image. Please analyze the image carefully and provide the requested information.`
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// UI-TARS query response format
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const uiTarsQueryResponseFormat = `
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## Output Json String Format
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` + "```" + `
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"{
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"content": "<<is a string containing the extracted information or analysis result>>",
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"thought": "<<is a string explaining your analysis process and reasoning. Use Chinese.>>"
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}"
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` + "```" + `
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## Rules **MUST** follow
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- Make sure to return **only** the JSON, with **no additional** text or explanations.
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- Use Chinese in ` + "`Thought`" + ` part.
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- You **MUST** strictly follow up the **Output Json String Format**.
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- Provide detailed and accurate information extraction based on the image content.`
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