From 89924c1580cfa6d4902a96c3e76ff11ec292a07a Mon Sep 17 00:00:00 2001 From: Aditya Pulipaka Date: Sun, 19 Oct 2025 05:29:30 -0500 Subject: [PATCH] Remove all previously tracked files that are now ignored --- .gitignore | 1 + ai_intelligence_layer/.env | 25 --------- .../__pycache__/config.cpython-313.pyc | Bin 1819 -> 0 bytes .../__pycache__/main.cpython-312.pyc | Bin 9390 -> 0 bytes .../__pycache__/main.cpython-313.pyc | Bin 27121 -> 0 bytes .../test_api.cpython-312-pytest-8.3.3.pyc | Bin 8539 -> 0 bytes ..._buffer_usage.cpython-312-pytest-8.3.3.pyc | Bin 5072 -> 0 bytes ...st_components.cpython-312-pytest-8.3.3.pyc | Bin 5384 -> 0 bytes ..._webhook_push.cpython-312-pytest-8.3.3.pyc | Bin 5610 -> 0 bytes ...hment_service.cpython-312-pytest-8.3.3.pyc | Bin 8363 -> 0 bytes ai_intelligence_layer/main.py | 36 +++++++++++-- .../__pycache__/input_models.cpython-312.pyc | Bin 6654 -> 0 bytes .../__pycache__/input_models.cpython-313.pyc | Bin 7208 -> 0 bytes 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...t_integration.cpython-312-pytest-8.3.3.pyc | Bin 6602 -> 0 bytes 45 files changed, 117 insertions(+), 43 deletions(-) delete mode 100644 ai_intelligence_layer/.env delete mode 100644 ai_intelligence_layer/__pycache__/config.cpython-313.pyc delete mode 100644 ai_intelligence_layer/__pycache__/main.cpython-312.pyc delete mode 100644 ai_intelligence_layer/__pycache__/main.cpython-313.pyc delete mode 100644 ai_intelligence_layer/__pycache__/test_api.cpython-312-pytest-8.3.3.pyc delete mode 100644 ai_intelligence_layer/__pycache__/test_buffer_usage.cpython-312-pytest-8.3.3.pyc delete mode 100644 ai_intelligence_layer/__pycache__/test_components.cpython-312-pytest-8.3.3.pyc delete mode 100644 ai_intelligence_layer/__pycache__/test_webhook_push.cpython-312-pytest-8.3.3.pyc delete mode 100644 ai_intelligence_layer/__pycache__/test_with_enrichment_service.cpython-312-pytest-8.3.3.pyc delete mode 100644 ai_intelligence_layer/models/__pycache__/input_models.cpython-312.pyc delete mode 100644 ai_intelligence_layer/models/__pycache__/input_models.cpython-313.pyc delete mode 100644 ai_intelligence_layer/models/__pycache__/output_models.cpython-312.pyc delete mode 100644 ai_intelligence_layer/models/__pycache__/output_models.cpython-313.pyc delete mode 100644 ai_intelligence_layer/prompts/__pycache__/analyze_prompt.cpython-313.pyc delete mode 100644 ai_intelligence_layer/prompts/__pycache__/brainstorm_prompt.cpython-313.pyc delete mode 100644 ai_intelligence_layer/services/__pycache__/gemini_client.cpython-313.pyc delete mode 100644 ai_intelligence_layer/services/__pycache__/strategy_analyzer.cpython-313.pyc delete mode 100644 ai_intelligence_layer/services/__pycache__/strategy_generator.cpython-313.pyc delete mode 100644 ai_intelligence_layer/services/__pycache__/telemetry_client.cpython-313.pyc delete mode 100644 ai_intelligence_layer/utils/__pycache__/telemetry_buffer.cpython-313.pyc delete mode 100644 ai_intelligence_layer/utils/__pycache__/validators.cpython-312.pyc delete mode 100644 ai_intelligence_layer/utils/__pycache__/validators.cpython-313.pyc delete mode 100644 hpcsim/__pycache__/__init__.cpython-312.pyc delete mode 100644 hpcsim/__pycache__/__init__.cpython-313.pyc delete mode 100644 hpcsim/__pycache__/adapter.cpython-312.pyc delete mode 100644 hpcsim/__pycache__/adapter.cpython-313.pyc delete mode 100644 hpcsim/__pycache__/api.cpython-312.pyc delete mode 100644 hpcsim/__pycache__/api.cpython-313.pyc delete mode 100644 hpcsim/__pycache__/enrichment.cpython-312.pyc delete mode 100644 hpcsim/__pycache__/enrichment.cpython-313.pyc delete mode 100644 scripts/__pycache__/enrich_telemetry.cpython-312.pyc delete mode 100644 scripts/__pycache__/simulate_pi_stream.cpython-312.pyc delete mode 100644 tests/__pycache__/test_adapter.cpython-312-pytest-8.3.3.pyc delete mode 100644 tests/__pycache__/test_adapter.cpython-312.pyc delete mode 100644 tests/__pycache__/test_api.cpython-312-pytest-8.3.3.pyc delete mode 100644 tests/__pycache__/test_api.cpython-312.pyc delete mode 100644 tests/__pycache__/test_enrichment.cpython-312-pytest-8.3.3.pyc delete mode 100644 tests/__pycache__/test_enrichment.cpython-312.pyc delete mode 100644 tests/__pycache__/test_integration.cpython-312-pytest-8.3.3.pyc diff --git a/.gitignore b/.gitignore index ee79715..9204635 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,3 @@ .env +__pycache__/ *.pyc \ No newline at end of file diff --git a/ai_intelligence_layer/.env b/ai_intelligence_layer/.env deleted file mode 100644 index 4603b93..0000000 --- a/ai_intelligence_layer/.env +++ /dev/null @@ -1,25 +0,0 @@ -# Gemini API Configuration -GEMINI_API_KEY=AIzaSyDK_jxVlJUpzyxuiGcopSFkiqMAUD3-w0I -GEMINI_MODEL=gemini-2.5-flash - -# Service Configuration -AI_SERVICE_PORT=9000 -AI_SERVICE_HOST=0.0.0.0 - -# Enrichment Service Integration -ENRICHMENT_SERVICE_URL=http://localhost:8000 -ENRICHMENT_FETCH_LIMIT=10 - -# Demo Mode (enables caching and consistent responses for demos) 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AI layer processes telemetry and generates strategies 3. AI layer pushes control commands back to Pi (brake_bias, differential_slip) """ - global current_race_context, last_control_command + global current_race_context, last_control_command, strategy_history vehicle_id = await websocket_manager.connect(websocket) @@ -389,7 +390,11 @@ async def websocket_pi_endpoint(websocket: WebSocket): # Reset last control command to neutral for new session last_control_command = {"brake_bias": 5, "differential_slip": 5} + # Clear strategy history for new race + strategy_history = [] + logger.info("[WebSocket] Telemetry buffer cleared for new connection") + logger.info("[WebSocket] Strategy history cleared for new race") # Notify dashboards of new vehicle connection await dashboard_manager.broadcast({ @@ -454,12 +459,26 @@ async def websocket_pi_endpoint(websocket: WebSocket): try: response = await strategy_generator.generate( enriched_telemetry=buffer_data, - race_context=current_race_context + race_context=current_race_context, + strategy_history=strategy_history ) # Extract top strategy (first one) top_strategy = response.strategies[0] if response.strategies else None + # Add to strategy history + if top_strategy: + strategy_history.append({ + "lap": lap_number, + "strategy_name": top_strategy.strategy_name, + "risk_level": top_strategy.risk_level, + "brief_description": top_strategy.brief_description, + "reasoning": top_strategy.reasoning + }) + # Keep only last 10 strategies + if len(strategy_history) > 10: + strategy_history.pop(0) + # Generate control commands based on strategy control_command = generate_control_command( lap_number=lap_number, @@ -490,6 +509,11 @@ async def websocket_pi_endpoint(websocket: WebSocket): "type": "lap_data", "vehicle_id": vehicle_id, "lap_data": enriched, + "race_context": { + "position": current_race_context.driver_state.current_position, + "gap_to_leader": current_race_context.driver_state.gap_to_leader, + "gap_to_ahead": current_race_context.driver_state.gap_to_ahead + }, "control_output": { "brake_bias": control_command["brake_bias"], "differential_slip": control_command["differential_slip"] @@ -497,7 +521,8 @@ async def websocket_pi_endpoint(websocket: WebSocket): "strategy": { "strategy_name": top_strategy.strategy_name, "risk_level": top_strategy.risk_level, - "brief_description": top_strategy.brief_description + "brief_description": top_strategy.brief_description, + "reasoning": top_strategy.reasoning } if top_strategy else None, "timestamp": datetime.now().isoformat() }) @@ -527,6 +552,11 @@ async def websocket_pi_endpoint(websocket: WebSocket): "type": "lap_data", "vehicle_id": vehicle_id, "lap_data": enriched, + "race_context": { + "position": current_race_context.driver_state.current_position, + "gap_to_leader": current_race_context.driver_state.gap_to_leader, + "gap_to_ahead": current_race_context.driver_state.gap_to_ahead + }, "control_output": { "brake_bias": 5, "differential_slip": 5 diff --git 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a/ai_intelligence_layer/prompts/brainstorm_prompt.py +++ b/ai_intelligence_layer/prompts/brainstorm_prompt.py @@ -9,7 +9,8 @@ from config import get_settings def build_brainstorm_prompt_fast( enriched_telemetry: List[EnrichedTelemetryWebhook], - race_context: RaceContext + race_context: RaceContext, + strategy_history: List[dict] = None ) -> str: """Build a faster, more concise prompt for quicker responses (lap-level data).""" settings = get_settings() @@ -27,17 +28,29 @@ def build_brainstorm_prompt_fast( if gap_to_leader > 0 and position > 1: comp_info += f", {gap_to_leader:.1f}s from leader" + # Format strategy history (last 3 strategies) + history_text = "" + if strategy_history and len(strategy_history) > 0: + recent_history = strategy_history[-3:] # Last 3 strategies + history_lines = [] + for h in recent_history: + history_lines.append(f"Lap {h['lap']}: {h['strategy_name']} (Risk: {h['risk_level']})") + history_text = f"\n\nPAST STRATEGIES:\n" + "\n".join(history_lines) + history_text += f"\n\nREQUIREMENT: If changing from previous strategy '{recent_history[-1]['strategy_name']}', explain WHY the switch is necessary. If staying with same approach, explain continuity." + else: + history_text = "\n\nNOTE: This is the first strategy generation - no previous strategy to compare." + if count == 1: # Ultra-fast mode: just generate 1 strategy return f"""Generate 1 F1 race strategy for {race_context.driver_state.driver_name} at {race_context.race_info.track_name}. CURRENT: Lap {race_context.race_info.current_lap}/{race_context.race_info.total_laps}, {comp_info}, {race_context.driver_state.current_tire_compound} tires ({race_context.driver_state.tire_age_laps} laps old) -TELEMETRY: Tire deg {latest.tire_degradation_rate:.2f}, Cliff risk {latest.tire_cliff_risk:.2f}, Pace {latest.pace_trend}, Position trend {latest.position_trend}, Competitive pressure {latest.competitive_pressure:.2f} +TELEMETRY: Tire deg {latest.tire_degradation_rate:.2f}, Cliff risk {latest.tire_cliff_risk:.2f}, Pace {latest.pace_trend}, Position trend {latest.position_trend}, Competitive pressure {latest.competitive_pressure:.2f}{history_text} Generate 1 optimal strategy considering competitive position. Min 2 tire compounds required. -JSON: {{"strategies": [{{"strategy_id": 1, "strategy_name": "name", "stop_count": 1, "pit_laps": [32], "tire_sequence": ["medium", "hard"], "brief_description": "one sentence", "risk_level": "medium", "key_assumption": "main assumption"}}]}}""" +JSON: {{"strategies": [{{"strategy_id": 1, "strategy_name": "name", "stop_count": 1, "pit_laps": [32], "tire_sequence": ["medium", "hard"], "brief_description": "one sentence", "reasoning": "detailed explanation including strategy change rationale if applicable", "risk_level": "medium", "key_assumption": "main assumption"}}]}}""" elif count <= 5: # Fast mode: 2-5 strategies with different approaches @@ -47,11 +60,13 @@ CURRENT: Lap {race_context.race_info.current_lap}/{race_context.race_info.total_ TELEMETRY: Tire deg {latest.tire_degradation_rate:.2f}, Cliff risk {latest.tire_cliff_risk:.2f}, Pace {latest.pace_trend}, Delta {latest.performance_delta:+.2f}s, Position trend {latest.position_trend}, Competitive pressure {latest.competitive_pressure:.2f} -COMPETITIVE SITUATION: Gap to ahead {gap_to_ahead:.1f}s ({"DRS RANGE - attack opportunity!" if gap_to_ahead < 1.0 else "close battle" if gap_to_ahead < 3.0 else "need to push"}) +COMPETITIVE SITUATION: Gap to ahead {gap_to_ahead:.1f}s ({"DRS RANGE - attack opportunity!" if gap_to_ahead < 1.0 else "close battle" if gap_to_ahead < 3.0 else "need to push"}){history_text} Generate {count} strategies balancing tire management with competitive pressure. Consider if aggressive undercut makes sense given gaps. Min 2 tire compounds each. -JSON: {{"strategies": [{{"strategy_id": 1, "strategy_name": "Conservative Stay Out", "stop_count": 1, "pit_laps": [35], "tire_sequence": ["medium", "hard"], "brief_description": "extend current stint then hard tires to end", "risk_level": "low", "key_assumption": "tire cliff risk stays below 0.7"}}]}}""" +CRITICAL: Each strategy MUST include 'reasoning' field explaining the approach and, if applicable, why it differs from or continues the previous strategy. + +JSON: {{"strategies": [{{"strategy_id": 1, "strategy_name": "Conservative Stay Out", "stop_count": 1, "pit_laps": [35], "tire_sequence": ["medium", "hard"], "brief_description": "extend current stint then hard tires to end", "reasoning": "Detailed explanation of this strategy including why we're switching from/continuing previous approach based on current telemetry and competitive situation", "risk_level": "low", "key_assumption": "tire cliff risk stays below 0.7"}}]}}""" return f"""Generate {count} F1 race strategies for {race_context.driver_state.driver_name} at {race_context.race_info.track_name}. @@ -59,16 +74,19 @@ CURRENT: Lap {race_context.race_info.current_lap}/{race_context.race_info.total_ TELEMETRY: Tire deg {latest.tire_degradation_rate:.2f}, Cliff risk {latest.tire_cliff_risk:.2f}, Pace {latest.pace_trend}, Delta {latest.performance_delta:+.2f}s, Position trend {latest.position_trend}, Competitive pressure {latest.competitive_pressure:.2f} -COMPETITIVE: Gap ahead {gap_to_ahead:.1f}s, Position trending {latest.position_trend} +COMPETITIVE: Gap ahead {gap_to_ahead:.1f}s, Position trending {latest.position_trend}{history_text} Generate {count} diverse strategies considering both tire management AND competitive positioning. Min 2 compounds. -JSON: {{"strategies": [{{"strategy_id": 1, "strategy_name": "name", "stop_count": 1, "pit_laps": [32], "tire_sequence": ["medium", "hard"], "brief_description": "one sentence", "risk_level": "low|medium|high|critical", "key_assumption": "main assumption"}}]}}""" +CRITICAL: Each strategy MUST include 'reasoning' field with detailed rationale and strategy continuity/change explanation. + +JSON: {{"strategies": [{{"strategy_id": 1, "strategy_name": "name", "stop_count": 1, "pit_laps": [32], "tire_sequence": ["medium", "hard"], "brief_description": "one sentence", "reasoning": "Comprehensive explanation including strategy evolution context", "risk_level": "low|medium|high|critical", "key_assumption": "main assumption"}}]}}""" def build_brainstorm_prompt( enriched_telemetry: List[EnrichedTelemetryWebhook], - race_context: RaceContext + race_context: RaceContext, + strategy_history: List[dict] = None ) -> str: """ Build the brainstorm prompt for Gemini. @@ -76,6 +94,7 @@ def build_brainstorm_prompt( Args: enriched_telemetry: Recent enriched telemetry data race_context: Current race context + strategy_history: List of previous strategies for context Returns: Formatted prompt string @@ -108,6 +127,14 @@ def build_brainstorm_prompt( "gap_seconds": round(c.gap_seconds, 1) }) + # Format strategy history + history_section = "" + if strategy_history and len(strategy_history) > 0: + history_section = "\n\nSTRATEGY HISTORY (Recent decisions):\n" + for h in strategy_history[-5:]: # Last 5 strategies + history_section += f"- Lap {h['lap']}: {h['strategy_name']} (Risk: {h['risk_level']}) - {h.get('brief_description', 'N/A')}\n" + history_section += f"\nCONTEXT: Previous strategy was '{strategy_history[-1]['strategy_name']}'. If recommending a change, clearly explain WHY. If continuing same approach, explain the continuity.\n" + prompt = f"""You are an expert F1 strategist. Generate 20 diverse race strategies based on lap-level telemetry AND competitive positioning. LAP-LEVEL TELEMETRY METRICS: @@ -135,7 +162,7 @@ COMPETITORS: {competitors_data} ENRICHED TELEMETRY (Last {len(telemetry_data)} laps, newest first): -{telemetry_data} +{telemetry_data}{history_section} KEY INSIGHTS: - Latest tire degradation rate: {latest.tire_degradation_rate:.3f} @@ -160,9 +187,12 @@ For each strategy provide: - pit_laps: [array of lap numbers] - tire_sequence: [array of compounds: "soft", "medium", "hard"] - brief_description: One sentence rationale +- reasoning: DETAILED explanation (3-5 sentences) including: (1) Why this strategy fits current conditions, (2) How it addresses telemetry trends, (3) Strategy evolution - why changing from or continuing previous approach - risk_level: "low", "medium", "high", or "critical" - key_assumption: Main assumption this strategy relies on +CRITICAL: The 'reasoning' field must include strategy continuity/change rationale relative to past decisions. + OUTPUT FORMAT (JSON only, no markdown): {{ "strategies": [ @@ -173,6 +203,7 @@ OUTPUT FORMAT (JSON only, no markdown): "pit_laps": [32], "tire_sequence": ["medium", "hard"], "brief_description": "Extend mediums to lap 32, safe finish on hards", + "reasoning": "Current tire degradation at 0.45 suggests we can safely extend to lap 32 before hitting the cliff. This maintains our conservative approach from lap 3 as conditions haven't changed significantly - tire deg is stable and we're not under immediate competitive pressure. The hard tire finish provides low-risk race completion.", "risk_level": "low", "key_assumption": "Tire degradation stays below 0.85 until lap 32" }} diff --git a/ai_intelligence_layer/services/__pycache__/gemini_client.cpython-313.pyc b/ai_intelligence_layer/services/__pycache__/gemini_client.cpython-313.pyc deleted file mode 100644 index 13195d89a2a4a25041e6ac2f5ed47cf83511e86b..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 6706 zcmcgwU2GdycD}>^e=-tfO0pzg*_3U{GG#}Sf3&t^)sBB;OLjPB)?TTYjLDHS2{n}O zjAEPUL(morIW1~svq7{A6suqtSS{KI6`KbG?SuQ!g@L?~k+)=LUDQB>0(vOGth~Dg z+9Eyo&J0N@+NMvvz|8$S_vf5@?m6E*Tfv|YLDHp{bMNm#=wE5YN)EHI^`}ty2=Ry@ zp5tv-xp5n@W25XK4%X%*PL{if3v&Ba_qd06#=XQl?jt@%>$vJ450C&x)6R6KwL~M| zho(a#oKYv?cC-)i&Q8R;Mr>wVWY(5+7ti@FN%OKI4^E?>i zR2%H@Z4E=~M`)_vH^RCRQn)GetPo0Dx?}dyY#+*SX;)K&S>(A>97auJJzu9`W0|II z@3S-}gYxy6VHL{$jsz6-d4Zy3M>kY~!fUl2rM3EcQ*bkklm$Yfn0g!&ekplf}GTte=FX!&G;vPQN2Pz%!&Uk1ZWcfl|7~1zCWe;sNvg%u#R= 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ztc`XtD_uC+&ado`xS(_Mx%%iHezlqbdbQ32OsfKphWXVNmeNmQ(6hQ5Q@R~fo;@6G z!^TJ#Kj5&h_Tp%tXZ4T==vypZ=9ZmG-EtVTyY6^1bE`Sx9o)AJBf9-q%_5$>P0b}9uB7S=u^ag|kD6D{x z*m6{$*kZQFVX+vt5DB29?Gj9k87<;5*k$1nxxOLzRBR$k|H@FvHt7NiIRdz2H~gFh z?7>d|FW7@EVviyUgc`XEY9u>ObC&Tu4#A0hjNM+Ho53oDjj&U8^PR%mYNaD9xuVlj z@^wMB>e04@Evt~T6Uphs*)&{4x0kUoGAB{70@xRTcUnrMwdwh1gky=cDhU~FS|V>j z>U3r8VRNofbLw6oL9k-v-e=He>xT?E0q(=F6I#@y$v)v&$YEw^3W10~n-G z{{s&Bdw}(>ulw_0=L5#Wi>(%|4rVYov!|F=4P$GzmvJy!O`(f zj*fIQK!{%v8qXDVeBRT2>?_ z1Jm|+d@_@a#|i!S3!!%@oq<~>fg2Ap>MiM_W9->XCQW)MSsynlvz&}4G>yn-=K%PD zJcXEqqITol3H_RlhTi5?dY$ BrainstormResponse: """ Generate 20 diverse race strategies. @@ -33,6 +34,7 @@ class StrategyGenerator: Args: enriched_telemetry: Recent enriched telemetry data race_context: Current race context + strategy_history: List of previous strategies for continuity Returns: BrainstormResponse with 20 strategies @@ -41,13 +43,15 @@ class StrategyGenerator: Exception: If generation fails """ logger.info(f"Generating strategies using {len(enriched_telemetry)} laps of telemetry") + if strategy_history: + logger.info(f"Including {len(strategy_history)} previous strategies in context") # Build prompt (use fast mode if enabled) if self.settings.fast_mode: from prompts.brainstorm_prompt import build_brainstorm_prompt_fast - prompt = build_brainstorm_prompt_fast(enriched_telemetry, race_context) + prompt = build_brainstorm_prompt_fast(enriched_telemetry, race_context, strategy_history or []) else: - prompt = build_brainstorm_prompt(enriched_telemetry, race_context) + prompt = build_brainstorm_prompt(enriched_telemetry, race_context, strategy_history or []) # Generate with Gemini (high temperature for creativity) response_data = await self.gemini_client.generate_json( diff --git a/ai_intelligence_layer/static/dashboard.html b/ai_intelligence_layer/static/dashboard.html index cb6a5d5..498aeb2 100644 --- a/ai_intelligence_layer/static/dashboard.html +++ b/ai_intelligence_layer/static/dashboard.html @@ -715,14 +715,14 @@ } function handleMessage(data) { - const { type, vehicle_id, lap_data, control_output, strategy, timestamp } = data; + const { type, vehicle_id, lap_data, race_context, control_output, strategy, timestamp } = data; if (type === 'vehicle_connected') { addVehicle(vehicle_id, timestamp); } else if (type === 'vehicle_disconnected') { removeVehicle(vehicle_id); } else if (type === 'lap_data') { - addLapData(vehicle_id, lap_data, control_output, strategy, timestamp); + addLapData(vehicle_id, lap_data, race_context, control_output, strategy, timestamp); } } @@ -750,7 +750,7 @@ } } - function addLapData(vehicleId, lapData, controlOutput, strategy, timestamp) { + function addLapData(vehicleId, lapData, raceContext, controlOutput, strategy, timestamp) { if (!vehicles.has(vehicleId)) { addVehicle(vehicleId, timestamp); } @@ -758,6 +758,7 @@ const vehicle = vehicles.get(vehicleId); vehicle.laps.push({ ...lapData, + race_context: raceContext, // Add race context with position and gaps control_output: controlOutput, strategy: strategy, timestamp: timestamp @@ -907,6 +908,37 @@ let bodyHtml = ''; + // Race Position section (lap_time, position, gaps) + if (lap.race_context || lap.lap_time) { + bodyHtml += ` +

+

Race Position

+
+ ${lap.lap_time ? ` +
+ Lap Time + ${lap.lap_time} +
+ ` : ''} + ${lap.race_context ? ` +
+ Position + P${lap.race_context.position} +
+
+ Gap from Leader + ${lap.race_context.gap_to_leader > 0 ? '+' + lap.race_context.gap_to_leader.toFixed(3) + 's' : (lap.race_context.position === 1 ? 'Leading' : 'N/A')} +
+
+ Gap from Car Ahead + ${lap.race_context.gap_to_ahead > 0 ? '+' + lap.race_context.gap_to_ahead.toFixed(3) + 's' : (lap.race_context.position === 1 ? 'Leading' : 'N/A')} +
+ ` : ''} +
+
+ `; + } + // Telemetry data section bodyHtml += `
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