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| # src/goal_based_extractor.py | |
| """ | |
| Goal-based content extraction prompt inspired by Alibaba Tongyi DeepResearch. | |
| """ | |
| EXTRACTOR_PROMPT = """Please process the following webpage content and user goal to extract relevant information: | |
| ## **Webpage Content** | |
| {webpage_content} | |
| ## **User Goal** | |
| {goal} | |
| ## **Task Guidelines** | |
| 1. **Content Scanning for Rational**: Locate the **specific sections/data** directly related to the user's goal within the webpage content | |
| 2. **Key Extraction for Evidence**: Identify and extract the **most relevant information** from the content, you never miss any important information, output the **full original context** of the content as far as possible, it can be more than three paragraphs. | |
| 3. **Summary Output for Summary**: Organize into a concise paragraph with logical flow, prioritizing clarity and judge the contribution of the information to the goal. | |
| **Final Output Format using JSON format has "rational", "evidence", "summary" fields** | |
| Example output: | |
| {{ | |
| "rational": "This section discusses X which directly relates to the goal of understanding Y", | |
| "evidence": "Full quotes and context from the page...", | |
| "summary": "Concise summary of how this information answers the goal" | |
| }} | |
| """ | |