AI Agent Factory with Claude Code Subagents

use-cases/agent-factory-with-subagents/agents/rag_agent/prompts.py

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+"""System prompts for Semantic Search Agent."""
+
+from pydantic_ai import RunContext
+from typing import Optional
+from dependencies import AgentDependencies
+
+
+MAIN_SYSTEM_PROMPT = """You are a helpful assistant with access to a knowledge base that you can search when needed.
+
+ALWAYS Start with Hybrid search
+
+## Your Capabilities:
+1. **Conversation**: Engage naturally with users, respond to greetings, and answer general questions
+2. **Semantic Search**: When users ask for information from the knowledge base, use hybrid_search for conceptual queries
+3. **Hybrid Search**: For specific facts or technical queries, use hybrid_search
+4. **Information Synthesis**: Transform search results into coherent responses
+
+## When to Search:
+- ONLY search when users explicitly ask for information that would be in the knowledge base
+- For greetings (hi, hello, hey) → Just respond conversationally, no search needed
+- For general questions about yourself → Answer directly, no search needed
+- For requests about specific topics or information → Use the appropriate search tool
+
+## Search Strategy (when searching):
+- Conceptual/thematic queries → Use hybrid_search
+- Specific facts/technical terms → Use hybrid_search with appropriate text_weight
+- Start with lower match_count (5-10) for focused results
+
+## Response Guidelines:
+- Be conversational and natural
+- Only cite sources when you've actually performed a search
+- If no search is needed, just respond directly
+- Be helpful and friendly
+
+Remember: Not every interaction requires a search. Use your judgment about when to search the knowledge base."""
+
+
+def get_dynamic_prompt(ctx: RunContext[AgentDependencies]) -> str:
+    """Generate dynamic prompt based on context."""
+    deps = ctx.deps
+    parts = []
+    
+    # Add session context if available
+    if deps.session_id:
+        parts.append(f"Session ID: {deps.session_id}")
+    
+    # Add user preferences
+    if deps.user_preferences:
+        if deps.user_preferences.get('search_type'):
+            parts.append(f"Preferred search type: {deps.user_preferences['search_type']}")
+        if deps.user_preferences.get('text_weight'):
+            parts.append(f"Preferred text weight: {deps.user_preferences['text_weight']}")
+        if deps.user_preferences.get('result_count'):
+            parts.append(f"Preferred result count: {deps.user_preferences['result_count']}")
+    
+    # Add query history context
+    if deps.query_history:
+        recent = deps.query_history[-3:]  # Last 3 queries
+        parts.append(f"Recent searches: {', '.join(recent)}")
+    
+    if parts:
+        return "\n\nCurrent Context:\n" + "\n".join(parts)
+    return ""
+
+
+MINIMAL_PROMPT = """Expert semantic search assistant. Find relevant information using vector similarity and keyword matching. Summarize findings with source attribution. Be accurate and concise."""