🔧 Remove Remaining Oxford Economics References

- ✅ Fixed request_raw metadata to use Python programming assistant context
- ✅ Updated response_raw metadata with Python list comprehensions response
- 🔢 Adjusted token counts to match new response length (13→22 completion, 162→168 prompt, 175→190 total)
- 📁 Updated knowledge graph filename: kg_oxford_economics_enhanced.json → kg_python_documentation_enhanced.json
- ✨ Complete removal of all Oxford Economics references from sample data

All traces now fully consistent with Python Documentation Assistant use case.

backend/database/sample_data.py

@@ -44,27 +44,27 @@ SAMPLE_TRACES = [
         "request_time": "2025-01-27T12:00:00.000",
         "status_code": 200,
         "sampling_fraction": 1,
-        "request_raw": "{\"messages\":[{\"role\":\"system\",\"content\":\"You are a knowledgeable assistant on Oxford Economics\"},{\"role\":\"user\",\"content\":\"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:\"}]}",
-        "response_raw": "{\"choices\":[{\"content_filter_results\":{\"hate\":{\"filtered\":false,\"severity\":\"safe\"},\"self_harm\":{\"filtered\":false,\"severity\":\"safe\"},\"sexual\":{\"filtered\":false,\"severity\":\"safe\"},\"violence\":{\"filtered\":false,\"severity\":\"safe\"}},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"Oxford Economics provides economic analysis, forecasting, and consultancy services.\",\"refusal\":null,\"role\":\"assistant\"}}],\"created\":1737979200,\"id\":\"chatcmpl-DEMO001\",\"model\":\"gpt-4o-2024-11-20\",\"object\":\"chat.completion\",\"system_fingerprint\":\"fp_demo_001\",\"usage\":{\"completion_tokens\":13,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens\":162,\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0},\"total_tokens\":175}}",
+        "request_raw": "{\"messages\":[{\"role\":\"system\",\"content\":\"You are a helpful Python programming assistant\"},{\"role\":\"user\",\"content\":\"You are a helpful Python programming assistant designed to answer questions accurately based on the provided documentation. Use the information retrieved from the knowledge base below to respond concisely and correctly.\\\\n\\\\n### Retrieved Documents:\\\\n['Python list comprehensions - efficient way to create lists', 'Python built-in functions - len(), range(), enumerate()', 'Python data structures - lists, dictionaries, sets, tuples']\\\\n\\\\n### Question:\\\\nwhat are python list comprehensions used for?\\\\n\\\\n### Answer:\"}]}",
+        "response_raw": "{\"choices\":[{\"content_filter_results\":{\"hate\":{\"filtered\":false,\"severity\":\"safe\"},\"self_harm\":{\"filtered\":false,\"severity\":\"safe\"},\"sexual\":{\"filtered\":false,\"severity\":\"safe\"},\"violence\":{\"filtered\":false,\"severity\":\"safe\"}},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"Python list comprehensions provide an efficient and readable way to create lists by applying expressions to elements in iterables.\",\"refusal\":null,\"role\":\"assistant\"}}],\"created\":1737979200,\"id\":\"chatcmpl-DEMO001\",\"model\":\"gpt-4o-2024-11-20\",\"object\":\"chat.completion\",\"system_fingerprint\":\"fp_demo_001\",\"usage\":{\"completion_tokens\":22,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens\":168,\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0},\"total_tokens\":190}}",
         "served_entity_id": "demo-entity-001",
         "logging_error_codes": "[]",
         "requester": "demo-user-001"
       },
       "latency": 0.531,
       "usage": {
-        "completion_tokens": 13,
+        "completion_tokens": 22,
         "completion_tokens_details": {
           "accepted_prediction_tokens": 0,
           "audio_tokens": 0,
           "reasoning_tokens": 0,
           "rejected_prediction_tokens": 0
         },
-        "prompt_tokens": 162,
+        "prompt_tokens": 168,
         "prompt_tokens_details": {
           "audio_tokens": 0,
           "cached_tokens": 0
         },
-        "total_tokens": 175
+        "total_tokens": 190
       },
       "model": "gpt-4o-2024-11-20"
     }
@@ -96,7 +96,7 @@ Would you like to see more specific examples or learn about related Python featu
 # Enhanced knowledge graphs demonstrating AgentGraph's complete feature set
 SAMPLE_KNOWLEDGE_GRAPHS = [
     {
-        "filename": "kg_oxford_economics_enhanced.json",
+        "filename": "kg_python_documentation_enhanced.json",
         "trace_index": 0,  # Links to first trace
         "graph_data": {
             "system_name": "Python Documentation Assistant",