stage academic conversation

crazy_functions/review_fns/handlers/qa_handler.py

@@ -0,0 +1,147 @@
+from typing import List, Dict, Any
+from .base_handler import BaseHandler
+from crazy_functions.review_fns.query_analyzer import SearchCriteria
+from textwrap import dedent
+from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency as request_gpt
+
+class 学术问答功能(BaseHandler):
+    """学术问答处理器"""
+
+    def __init__(self, arxiv, semantic, llm_kwargs=None):
+        super().__init__(arxiv, semantic, llm_kwargs)
+
+    async def handle(
+        self,
+        criteria: SearchCriteria,
+        chatbot: List[List[str]],
+        history: List[List[str]],
+        system_prompt: str,
+        llm_kwargs: Dict[str, Any],
+        plugin_kwargs: Dict[str, Any],
+    ) -> str:
+        """处理学术问答请求，返回最终的prompt"""
+
+        # 1. 获取搜索参数
+        search_params = self._get_search_params(plugin_kwargs)
+
+        # 2. 搜索相关论文
+        papers = await self._search_relevant_papers(criteria, search_params)
+        if not papers:
+            return self._generate_apology_prompt(criteria)
+
+        # 构建最终的prompt
+        current_time = self._get_current_time()
+        final_prompt = dedent(f"""Current time: {current_time}
+
+            Based on the following paper abstracts, please answer this academic question: {criteria.original_query}
+
+            Available papers for reference:
+            {self._format_papers(self.ranked_papers)}
+
+            Please structure your response in the following format:
+
+            1. Core Answer (2-3 paragraphs)
+            - Provide a clear, direct answer synthesizing key findings
+            - Support main points with citations [1,2,etc.]
+            - Focus on consensus and differences across papers
+
+            2. Key Evidence (2-3 paragraphs)
+            - Present supporting evidence from abstracts
+            - Compare methodologies and results
+            - Highlight significant findings with citations
+
+            3. Research Context (1-2 paragraphs)
+            - Discuss current trends and developments
+            - Identify research gaps or limitations
+            - Suggest potential future directions
+
+            Guidelines:
+            - Base your answer ONLY on the provided abstracts
+            - Use numbered citations [1], [2,3], etc. for every claim
+            - Maintain academic tone and objectivity
+            - Synthesize findings across multiple papers
+            - Focus on the most relevant information to the question
+
+            Constraints:
+            - Do not include information beyond the provided abstracts
+            - Avoid speculation or personal opinions
+            - Do not elaborate on technical details unless directly relevant
+            - Keep citations concise and focused
+            - Use [N] citations for every major claim or finding
+            - Cite multiple papers [1,2,3] when showing consensus
+            - Place citations immediately after the relevant statements
+
+            Note: Provide citations for every major claim to ensure traceability to source papers.
+            Language requirement:
+            - If the query explicitly specifies a language, use that language. Use Chinese to answer if no language is specified.
+            - Otherwise, match the language of the original user query
+            """
+        )
+
+        return final_prompt
+
+    async def _search_relevant_papers(self, criteria: SearchCriteria, search_params: Dict) -> List:
+        """搜索相关论文"""
+        # 使用_search_all_sources替代原来的并行搜索
+        all_papers = await self._search_all_sources(criteria, search_params)
+
+        if not all_papers:
+            return []
+
+        # 使用BGE重排序
+        self.ranked_papers = self.paper_ranker.rank_papers(
+            query=criteria.main_topic,
+            papers=all_papers,
+            search_criteria=criteria
+        )
+
+        return self.ranked_papers or []
+
+    async def _generate_answer(
+        self,
+        criteria: SearchCriteria,
+        papers: List,
+        chatbot: List[List[str]],
+        history: List[List[str]],
+        system_prompt: str,
+        llm_kwargs: Dict[str, Any]
+    ) -> List[List[str]]:
+        """生成答案"""
+
+        # 构建提示
+        qa_prompt = dedent(f"""Please answer the following academic question based on recent research papers.
+
+            Question: {criteria.main_topic}
+
+            Relevant papers:
+            {self._format_papers(papers)}
+
+            Please provide:
+            1. A direct answer to the question
+            2. Supporting evidence from the papers
+            3. Different perspectives or approaches if applicable
+            4. Current limitations and open questions
+            5. References to specific papers
+
+            Format your response in markdown with clear sections."""
+        )
+        # 调用LLM生成答案
+        for response_chunk in request_gpt(
+            inputs_array=[qa_prompt],
+            inputs_show_user_array=["Generating answer..."],
+            llm_kwargs=llm_kwargs,
+            chatbot=chatbot,
+            history_array=[history],
+            sys_prompt_array=[system_prompt]
+        ):
+            pass  # 等待生成完成
+
+        # 获取最后的回答
+        if chatbot and len(chatbot[-1]) >= 2:
+            answer = chatbot[-1][1]
+            chatbot.append(["Here is the answer:", answer])
+        else:
+            chatbot.append(["Here is the answer:", "Failed to generate answer."])
+
+        return chatbot
+