🔧 Optimize Tool Definition: RAG Search vs Language Model

- ✨ Updated tool_001 from 'GPT-4o Language Model' to 'Oxford Economics Knowledge Search'
- 🔍 Enhanced RAG-powered knowledge retrieval capabilities in sample data
- 📚 Updated descriptions to reflect proper tool vs agent distinction
- ⚡ Modified interaction prompts to show knowledge base querying workflow
- 🎯 Updated optimization recommendations for RAG tool enhancement
- 📋 Refined documentation to highlight RAG search capabilities

Key improvements:
- Tools now represent external knowledge systems (RAG search)
- Language models are implicit agent capabilities, not separate tools
- Better alignment with real-world AI assistant architectures
- More accurate representation of retrieval-augmented generation flows

backend/database/README_sample_data.md

@@ -19,7 +19,7 @@ The system includes 2 carefully selected examples showcasing AgentGraph's advanc
 1. **Oxford Economics AI Assistant** (Enhanced)
 
    - Type: `aif_inference`
-   - Example: AI assistant processing economic inquiry with failure detection
+   - Example: RAG-powered assistant processing economic inquiry with knowledge search and failure detection
    - 6 entities, 5 relations, 1 failure, 2 optimizations
    - Features: Content references, quality scoring, system summary
 
@@ -37,6 +37,7 @@ Each trace comes with a pre-generated knowledge graph showcasing AgentGraph's co
 - **Agent interactions and roles** with detailed prompts and content references
 - **Task decomposition** with clear importance levels
 - **Information flow** with specific interaction prompts
+- **RAG-powered knowledge search** retrieving relevant documents and context
 - **Failure detection** identifying real issues (spelling errors, system gaps)
 - **Optimization recommendations** providing actionable improvements
 - **Quality assessment** with confidence scores and metadata
@@ -122,7 +123,7 @@ To disable automatic sample data insertion, modify `init_db.py`:
 ## Benefits for Users
 
 1. **Immediate Value**: New users see AgentGraph's complete capabilities immediately
-2. **Learning**: Examples demonstrate failure detection, optimization suggestions, and advanced features
+2. **Learning**: Examples demonstrate RAG search, failure detection, optimization suggestions, and advanced features
 3. **Testing**: Users can test all AgentGraph features including quality assessment and content referencing
 4. **Reference**: Examples serve as high-quality templates showcasing best practices
 5. **Feature Discovery**: Users understand the full potential of knowledge graph enhancement
@@ -133,6 +134,7 @@ To disable automatic sample data insertion, modify `init_db.py`:
 - All sample traces are realistic and demonstrate real-world scenarios
 - Knowledge graphs are hand-crafted to showcase AgentGraph's complete feature set
 - Examples include actual failure detection (spelling errors, system gaps)
+- RAG search capabilities demonstrate knowledge retrieval workflows
 - Optimization recommendations are practical and actionable
 - Content references are accurate and support proper traceability
 - Quality scores reflect realistic assessment metrics

backend/database/sample_data.py

@@ -15,10 +15,10 @@ SAMPLE_TRACES = [
     {
         "filename": "oxford_economics_inquiry.json",
         "title": "Oxford Economics AI Assistant Demo",
-        "description": "Enhanced example showing AI assistant processing economic inquiry with failure detection and optimization suggestions",
+        "description": "Enhanced example showing RAG-powered AI assistant processing economic inquiry with knowledge search, failure detection and optimization suggestions",
         "trace_type": "aif_inference",
         "trace_source": "sample_data",
-        "tags": ["economics", "ai_assistant", "enhanced", "failure_detection", "optimization"],
+        "tags": ["economics", "rag_assistant", "knowledge_search", "failure_detection", "optimization"],
         "content": """{
   "id": "aif_trace_demo_001",
   "timestamp": "2025-01-27T00:00:00",
@@ -29,14 +29,14 @@ SAMPLE_TRACES = [
   },
   "data": {
     "total_observations": 1,
-    "summary": "Oxford Economics inquiry with AI assistant response"
+    "summary": "Oxford Economics inquiry with RAG-powered assistant response"
   },
   "observations": [
     {
       "id": "demo_obs_001",
       "type": "inference",
       "timestamp": "2025-01-27T00:00:00",
-      "input": "You are a knowledgeable assistant on Oxford Economics designed to answer questions accurately based on the provided context. Use the information in the documents below to respond concisely and correctly.\\n\\n### Context:\\n['Oxford Economics contact: Mateusz Urban - murban@oxfordeconomics.com', 'Oxford Economics research and analysis services', 'Economic forecasting and consultancy expertise']\\n\\n### Question:\\nwhat does oxford economics present?\\n\\n### Answer:",
+      "input": "You are a knowledgeable assistant on Oxford Economics designed to answer questions accurately based on the provided context. Use the information retrieved from the knowledge base below to respond concisely and correctly.\\n\\n### Retrieved Documents:\\n['Oxford Economics contact: Mateusz Urban - murban@oxfordeconomics.com', 'Oxford Economics research and analysis services', 'Economic forecasting and consultancy expertise']\\n\\n### Question:\\nwhat does oxford economics present?\\n\\n### Answer:",
       "output": "Oxford Economics provides economic analysis, forecasting, and consultancy services.",
       "metadata": {
         "request_date": "2025-01-27T00:00:00",
@@ -100,14 +100,14 @@ SAMPLE_KNOWLEDGE_GRAPHS = [
         "trace_index": 0,  # Links to first trace
         "graph_data": {
             "system_name": "Oxford Economics AI Assistant",
-            "system_summary": "This intelligent assistant processes user inquiries about Oxford Economics through a streamlined workflow. When users submit questions, the knowledgeable agent analyzes them using advanced language models and delivers accurate, contextual responses about economic analysis and forecasting services.",
+            "system_summary": "This intelligent assistant processes user inquiries about Oxford Economics through a streamlined workflow. When users submit questions, the knowledgeable agent analyzes them using RAG-powered knowledge search and delivers accurate, contextual responses about economic analysis and forecasting services.",
             "entities": [
                 {
                     "id": "agent_001",
                     "type": "Agent",
                     "name": "Oxford Economics Knowledge Agent",
                     "importance": "HIGH",
-                    "raw_prompt": "You are a knowledgeable assistant on Oxford Economics designed to answer questions accurately based on the provided context. Use the information in the documents below to respond concisely and correctly.",
+                    "raw_prompt": "You are a knowledgeable assistant on Oxford Economics designed to answer questions accurately based on retrieved knowledge base context. Use the search results to provide precise responses.",
                     "raw_prompt_ref": [
                         {
                             "line_start": 31,
@@ -170,9 +170,9 @@ SAMPLE_KNOWLEDGE_GRAPHS = [
                 {
                     "id": "tool_001",
                     "type": "Tool",
-                    "name": "GPT-4o Language Model",
+                    "name": "Oxford Economics Knowledge Search",
                     "importance": "HIGH",
-                    "raw_prompt": "Advanced AI language model with economic domain knowledge and structured response capabilities.",
+                    "raw_prompt": "Retrieval-Augmented Generation (RAG) system that searches Oxford Economics knowledge base for relevant documents, contact information, and service details to provide contextual information.",
                     "raw_prompt_ref": [
                         {
                             "line_start": 49,
@@ -244,7 +244,7 @@ SAMPLE_KNOWLEDGE_GRAPHS = [
                     "target": "tool_001",
                     "type": "USES",
                     "importance": "HIGH",
-                    "interaction_prompt": "Agent leverages language model for natural language understanding and generation",
+                    "interaction_prompt": "Agent queries knowledge search system to retrieve relevant Oxford Economics documents and contextual information",
                     "interaction_prompt_ref": [
                         {
                             "line_start": 49,
@@ -284,7 +284,7 @@ SAMPLE_KNOWLEDGE_GRAPHS = [
                 {
                     "id": "opt_002",
                     "recommendation_type": "TOOL_ENHANCEMENT",
-                    "description": "Integrate Oxford Economics knowledge base with the language model to provide more specific and detailed responses about services and capabilities.",
+                    "description": "Expand knowledge search capabilities to include real-time market data, recent publications, and dynamic economic indicators alongside static company information.",
                     "affected_ids": ["tool_001"],
                     "raw_text_ref": [
                         {
@@ -334,7 +334,7 @@ SAMPLE_KNOWLEDGE_GRAPHS = [
                     "type": "Agent",
                     "name": "Q&A Assistant",
                     "importance": "HIGH",
-                    "raw_prompt": "Helpful assistant specialized in providing information about Oxford Economics services and capabilities.",
+                    "raw_prompt": "RAG-powered assistant specialized in searching knowledge base and providing accurate information about Oxford Economics services and capabilities.",
                     "raw_prompt_ref": [
                         {
                             "line_start": 3,
@@ -559,6 +559,6 @@ def get_sample_data_info():
         "knowledge_graphs_count": len(SAMPLE_KNOWLEDGE_GRAPHS),
         "trace_types": list(set(t["trace_type"] for t in SAMPLE_TRACES)),
         "complexity_levels": ["enhanced", "simple"],
-        "features": ["failure_detection", "optimization_recommendations", "content_references", "quality_scoring"],
-        "description": "Enhanced AgentGraph examples showcasing Oxford Economics AI assistant with complete failure detection, optimization suggestions, and advanced knowledge graph features"
+        "features": ["rag_search", "failure_detection", "optimization_recommendations", "content_references", "quality_scoring"],
+        "description": "Enhanced AgentGraph examples showcasing Oxford Economics RAG-powered assistant with knowledge search, failure detection, optimization suggestions, and advanced knowledge graph features"
     }