Initial commit: jaspersoft-agent-learn teaching project

2026-05-29 23:22:18 +08:00
commit 05bb511aab
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+"""
+Step 05-07: RAG / Self-Correction / Multi-Agent
+
+进阶内容代码示例
+"""
+
+# ═══════════════════════════════════════════════════════════════════════════════════════
+# RAG 实现
+# ═══════════════════════════════════════════════════════════════════════════════════════
+
+class SimpleRAG:
+    """
+    简化版 RAG 系统
+
+    实际应用中请使用：
+    - ChromaDB / Pinecone / Weaviate（向量数据库）
+    - sentence-transformers / OpenAI Embeddings（向量模型）
+    """
+
+    def __init__(self):
+        self.documents = []
+
+    def add_document(self, text: str, metadata: dict = None):
+        """添加文档"""
+        self.documents.append({
+            "text": text,
+            "metadata": metadata or {},
+            "id": len(self.documents)
+        })
+
+    def retrieve(self, query: str, top_k: int = 3) -> list:
+        """检索相关文档（简化版：基于关键词）"""
+        results = []
+        query_words = set(query.lower().split())
+
+        for doc in self.documents:
+            doc_words = set(doc["text"].lower().split())
+            # 简单的 Jaccard 相似度
+            intersection = query_words & doc_words
+            union = query_words | doc_words
+            if union:
+                score = len(intersection) / len(union)
+                results.append((score, doc))
+
+        results.sort(key=lambda x: x[0], reverse=True)
+        return [doc for _, doc in results[:top_k]]
+
+    def generate(self, query: str, context_only: bool = False):
+        """
+        生成答案
+
+        如果 context_only=True，只返回检索到的上下文
+        否则进行 RAG 生成（需要接入 LLM）
+        """
+        docs = self.retrieve(query)
+        context = "\n\n".join([
+            f"[来源: {d['metadata'].get('source', '未知')}]\n{d['text']}"
+            for d in docs
+        ])
+        return context
+
+
+# ═══════════════════════════════════════════════════════════════════════════════════════
+# Self-Correction 实现
+# ═══════════════════════════════════════════════════════════════════════════════════════
+
+@dataclass
+class ValidationResult:
+    """验证结果"""
+    passed: bool
+    score: float
+    issues: List[str]
+    suggestion: str = ""
+
+
+class SelfCorrectingAgent:
+    """
+    自我修正 Agent
+
+    工作流程：
+    1. 生成初始结果
+    2. 验证结果
+    3. 如果有问题，分析错误并修复
+    4. 循环直到通过或达到最大重试次数
+    """
+
+    def __init__(self, generator, validator):
+        self.generator = generator
+        self.validator = validator
+        self.max_retries = 3
+
+    def generate_with_correction(self, requirement: str) -> dict:
+        """带自我修正的生成"""
+        history = []
+        current_requirement = requirement
+
+        for attempt in range(self.max_retries):
+            # 1. 生成
+            result = self.generator.generate(current_requirement)
+            history.append({
+                "attempt": attempt + 1,
+                "requirement": current_requirement,
+                "result": result
+            })
+
+            # 2. 验证
+            validation = self.validator.validate(result)
+            history[-1]["validation"] = validation
+
+            if validation.passed:
+                return {
+                    "success": True,
+                    "result": result,
+                    "attempts": attempt + 1,
+                    "history": history
+                }
+
+            # 3. 分析错误，准备修复
+            print(f"尝试 {attempt + 1} 失败: {validation.issues}")
+            current_requirement = self._prepare_fix(
+                requirement,
+                validation,
+                result
+            )
+
+        return {
+            "success": False,
+            "error": "达到最大重试次数",
+            "history": history
+        }
+
+    def _prepare_fix(self, original: str, validation: ValidationResult, result) -> str:
+        """准备修复提示"""
+        issues_text = "\n".join(f"- {issue}" for issue in validation.issues)
+
+        return f"""
+原始需求：{original}
+
+上次生成结果：
+{result}
+
+验证发现的问题：
+{issues_text}
+
+验证建议：{validation.suggestion}
+
+请根据以上信息，修正生成结果。
+"""
+
+
+# ═══════════════════════════════════════════════════════════════════════════════════════
+# Multi-Agent 实现
+# ═══════════════════════════════════════════════════════════════════════════════════════
+
+from dataclasses import dataclass, field
+from typing import Dict, List, Callable
+
+
+@dataclass
+class AgentMessage:
+    """Agent 之间的消息"""
+    from_agent: str
+    to_agent: str
+    content: Any
+    message_type: str  # "request" / "response" / "broadcast"
+
+
+class Agent:
+    """基础 Agent 类"""
+    name: str
+
+    def process(self, input_data: Any) -> Any:
+        """处理输入，返回结果"""
+        raise NotImplementedError
+
+
+class MultiAgentSystem:
+    """
+    多 Agent 协作系统
+
+    组件：
+    - agents: 注册的 Agent 字典
+    - orchestrator: 协调器，决定消息路由
+    - message_queue: 消息队列
+    """
+
+    def __init__(self):
+        self.agents: Dict[str, Agent] = {}
+        self.message_queue: List[AgentMessage] = []
+        self.history: List[AgentMessage] = []
+
+    def register(self, agent: Agent):
+        """注册 Agent"""
+        self.agents[agent.name] = agent
+
+    def send_message(self, from_agent: str, to_agent: str, content: Any,
+                    msg_type: str = "request"):
+        """发送消息"""
+        msg = AgentMessage(
+            from_agent=from_agent,
+            to_agent=to_agent,
+            content=content,
+            message_type=msg_type
+        )
+        self.message_queue.append(msg)
+
+    def broadcast(self, from_agent: str, content: Any):
+        """广播消息给所有 Agent"""
+        for agent_name in self.agents:
+            if agent_name != from_agent:
+                self.send_message(from_agent, agent_name, content, "broadcast")
+
+    def process(self, requirement: str) -> Any:
+        """
+        处理请求
+
+        简化实现：顺序执行各个 Agent
+        """
+        # 1. 搜索
+        searcher = self.agents.get("searcher")
+        context = searcher.process(requirement) if searcher else ""
+
+        # 2. 生成
+        generator = self.agents.get("generator")
+        result = generator.process({"requirement": requirement, "context": context}) if generator else requirement
+
+        # 3. 验证
+        validator = self.agents.get("validator")
+        validation = validator.process(result) if validator else {"passed": True}
+
+        if not validation.get("passed", True):
+            return {"error": "验证失败", "validation": validation}
+
+        return result
+
+
+def demo():
+    """演示"""
+    print("=" * 60)
+    print("Step 05-07: 进阶功能演示")
+    print("=" * 60)
+
+    # RAG 演示
+    print("\n📚 RAG 演示")
+    rag = SimpleRAG()
+    rag.add_document("JasperReports 是一个 Java 报表库", {"source": "文档1"})
+    rag.add_document("JRXML 是 JasperReports 的报表模板格式", {"source": "文档2"})
+    rag.add_document("可以使用 LLM 生成 JRXML 代码", {"source": "文档3"})
+
+    result = rag.retrieve("JasperReports 是什么")
+    print(f"  查询 'JasperReports 是什么'")
+    for doc in result:
+        print(f"    - {doc['text']} (来源: {doc['metadata']['source']})")
+
+    # Multi-Agent 演示
+    print("\n\n🤖 Multi-Agent 演示")
+
+    class DemoSearcher(Agent):
+        name = "searcher"
+        def process(self, input_data):
+            print(f"    [{self.name}] 搜索相关资料...")
+            return "找到相关模板和文档"
+
+    class DemoGenerator(Agent):
+        name = "generator"
+        def process(self, input_data):
+            print(f"    [{self.name}] 生成报表...")
+            return "<jasperReport>生成的报表</jasperReport>"
+
+    class DemoValidator(Agent):
+        name = "validator"
+        def process(self, input_data):
+            print(f"    [{self.name}] 验证结果...")
+            return {"passed": True}
+
+    system = MultiAgentSystem()
+    system.register(DemoSearcher())
+    system.register(DemoGenerator())
+    system.register(DemoValidator())
+
+    result = system.process("生成销售报表")
+    print(f"\n  最终结果: {result[:50]}...")
+
+
+if __name__ == "__main__":
+    demo()