===== Application Startup at 2026-02-19 18:09:03 ===== INFO:src.api.app:πŸ‘₯ Multi-user session isolation initialized (fast mode) INFO:src.api.app:πŸ”’ Workflow lock initialized for request queuing INFO:src.api.app:βœ… Frontend assets mounted from /home/user/app/FRRONTEEEND/dist INFO: Started server process [1] INFO: Waiting for application startup. INFO:src.api.app:Initializing legacy global agent for health checks... πŸ€– Initialized with Mistral provider - Model: mistral-large-latest βœ… Cache database initialized at /home/user/app/cache_db/cache.db 🧠 Loading SBERT model: all-MiniLM-L6-v2... INFO:sentence_transformers.SentenceTransformer:Use pytorch device_name: cpu INFO:sentence_transformers.SentenceTransformer:Load pretrained SentenceTransformer: all-MiniLM-L6-v2 βœ… SBERT loaded on CPU πŸ“Š Token Budget: 120,000 tokens available (128,000 - 8,000 reserve) βœ… Sessions database initialized at ./cache_db/sessions.db βœ… Created new session: 5081830f-32ee-4f0a-81c5-cf0fc6906e43 πŸ“ Output directory: /tmp/data_science_agent/outputs INFO:src.api.app:βœ… Health check agent initialized with provider: mistral INFO:src.api.app:πŸ‘₯ Per-session agents enabled - each user gets isolated instance INFO:src.api.app:πŸ€– Multi-agent architecture enabled with 5 specialists INFO: Application startup complete. INFO: Uvicorn running on http://0.0.0.0:7860 (Press CTRL+C to quit) INFO: 10.16.34.155:32798 - "GET / HTTP/1.1" 200 OK INFO: 10.16.4.123:43387 - "GET /index.css HTTP/1.1" 200 OK INFO: 10.16.34.155:32798 - "GET /assets/index-C_AP0pY-.js HTTP/1.1" 200 OK INFO: 10.16.4.123:54623 - "GET / HTTP/1.1" 200 OK INFO: 10.16.4.123:54623 - "GET /index.css HTTP/1.1" 200 OK INFO: 10.16.34.155:7477 - "GET /assets/index-C_AP0pY-.js HTTP/1.1" 200 OK INFO: 10.16.34.155:53091 - "GET /favicon.ico HTTP/1.1" 200 OK [SSE] ENDPOINT: Client connected for session_id=d41f7d5d-57f2-4b66-8137-b91496eda810 [SSE] Queue registered, total subscribers: 1 INFO: 10.16.4.123:30718 - "GET /api/progress/stream/d41f7d5d-57f2-4b66-8137-b91496eda810 HTTP/1.1" 200 OK [SSE] SENDING connection event to client [SSE] No history to replay (fresh session) [SSE] Starting event stream loop for session d41f7d5d-57f2-4b66-8137-b91496eda810 INFO:src.api.app:SSE stream cancelled for session d41f7d5d-57f2-4b66-8137-b91496eda810 INFO:src.api.app:SSE stream closed for session d41f7d5d-57f2-4b66-8137-b91496eda810 INFO:src.api.app:[ASYNC] Created new session: 2df5d6d1... INFO:src.api.app:[ASYNC] File saved: uber_trips_dataset_50k.csv INFO: 10.16.4.123:29159 - "POST /run-async HTTP/1.1" 200 OK INFO:src.api.app:[BACKGROUND] Starting analysis for session 2df5d6d1... [🧹] Clearing SSE history for 2df5d6d1... INFO:src.api.app:[πŸ†•] Creating lightweight session for 2df5d6d1... INFO:src.api.app:βœ… Session created for 2df5d6d1 (cache: 1/50) - <1s init [DEBUG] Session fallback triggered - has_ambiguous_ref=True, resolved={} [DEBUG] resolve_ambiguity returning: {} [DEBUG] Orchestrator received resolved_params: {} [DEBUG] Current file_path: '/tmp/data_science_agent/uber_trips_dataset_50k.csv', target_col: 'None' πŸ“ User provided new file: /tmp/data_science_agent/uber_trips_dataset_50k.csv (ignoring session file: none) πŸ” Extracting dataset schema locally (no LLM)... [SSE] ENDPOINT: Client connected for session_id=2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Queue registered, total subscribers: 1 INFO: 10.16.34.155:32511 - "GET /api/progress/stream/2df5d6d1-f23c-48fb-b353-373e7693b75e HTTP/1.1" 200 OK [SSE] SENDING connection event to client [SSE] No history to replay (fresh session) [SSE] Starting event stream loop for session 2df5d6d1-f23c-48fb-b353-373e7693b75e 🧠 Semantic layer: Embedded 14 columns Found 10 similar column pairs (potential duplicates) 🧠 Semantic layer enriched 14 columns βœ… Schema extracted: 50000 rows Γ— 14 cols File size: 8.46 MB 🎯 Intent Classification: Mode: EXPLORATORY Confidence: 40% Reasoning: No strong pattern match, defaulting to exploratory analysis Sub-intent: default [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=intent_classified, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 1 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 🧠 Routing to REASONING LOOP (exploratory mode) [SSE] GOT event from queue: intent_classified [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=reasoning_mode, msg=🧠 Reasoning Loop activated (exploratory mode) [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 2 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ============================================================ 🧠 REASONING LOOP (EXPLORATORY mode) Question: Explain the important features in this dataset Max iterations: 8 ============================================================ πŸ”¬ Generating hypotheses from data profile... πŸ“‹ Final parameters: ['file_path'] [SSE] GOT event from queue: reasoning_mode INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Generated 5 hypotheses: 1. [0.9] The 'fare_amount' distribution exhibits unexpected spikes at round numbers (e.g., $10, $20, $50), suggesting potential fare manipulation, rounding errors, or psychological pricing effects by drivers. This could indicate data quality issues or behavioral patterns worth investigating. 2. [0.9] 'distance_km' and 'fare_amount' show a non-linear relationship, with fares increasing disproportionately for very short or very long trips. This may reveal surge pricing effects, city-specific pricing models, or data entry errors in distance calculations. 3. [0.8] Certain 'driver_id' or 'rider_id' values appear in an implausibly high number of trips (e.g., >100 trips/day), suggesting potential data duplication, bot activity, or fraudulent ride patterns that could skew demand/supply metrics. 4. [0.8] The 'status' column contains a small percentage of 'cancelled' or 'failed' trips, but these are disproportionately concentrated in specific cities or time windows, indicating potential regional service issues or rider/driver behavior differences. 5. [0.8] Geospatial anomalies exist where 'pickup_lat'/'pickup_lng' or 'drop_lat'/'drop_lng' fall outside expected city boundaries, suggesting GPS errors, incorrect city assignments, or fraudulent trip reporting. [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=hypotheses_generated, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 3 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ── Iteration 1/8 ── πŸ€” REASON: Deciding next action... [SSE] GOT event from queue: hypotheses_generated INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Status: investigating Reasoning: To explain the important features in the dataset, we first need a comprehensive understanding of the data, including distributions, correlations, and potential relationships between features. This will help identify which features are most relevant or influential. Tool: generate_ydata_profiling_report Hypothesis: The profiling report will reveal key statistics, distributions, correlations, and potential data quality issues, which will help identify the most important features in the dataset. [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=reasoning_step, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 4 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ⚑ ACT: Executing generate_ydata_profiling_report... [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_executing, msg=πŸ”§ Executing: generate_ydata_profiling_report [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 5 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“‹ Final parameters: ['file_path', 'output_path', 'minimal', 'title'] [SSE] GOT event from queue: reasoning_step [SSE] GOT event from queue: tool_executing INFO:visions.backends:Pandas backend loaded 2.3.3 INFO:visions.backends:Numpy backend loaded 2.1.3 INFO:visions.backends:Pyspark backend NOT loaded INFO:visions.backends:Python backend loaded Upgrade to ydata-sdk Improve your data and profiling with ydata-sdk, featuring data quality scoring, redundancy detection, outlier identification, text validation, and synthetic data generation. Register at https://ydata.ai/register Summarize dataset: 0%| | 0/5 [00:00 failed (attempt 1/2): Unsupported file format: /tmp/data_science_agent/outputs/plots/interactive/correlation_heatmap.html Retrying in 1.0s... [SSE] GOT event from queue: reasoning_step [SSE] GOT event from queue: tool_executing πŸ“‹ Final parameters: ['file_path', 'target_col', 'task_type', 'method'] ❌ failed after 2 attempts πŸ’‘ Suggested fallback tools: [] ❌ Tool failed: Unsupported file format: /tmp/data_science_agent/outputs/plots/interactive/correlation_heatmap.html [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_failed, msg=❌ FAILED: auto_feature_selection [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 18 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“Š EVALUATE: Interpreting results... [SSE] GOT event from queue: tool_failed INFO: 10.16.34.155:21041 - "GET / HTTP/1.1" 200 OK INFO: 10.16.4.123:60395 - "GET /index.css HTTP/1.1" 200 OK INFO: 10.16.34.155:21041 - "GET /assets/index-C_AP0pY-.js HTTP/1.1" 304 Not Modified INFO: 10.16.34.155:21041 - "GET /favicon.ico HTTP/1.1" 200 OK INFO: 10.16.34.155:21041 - "GET /favicon.ico HTTP/1.1" 200 OK INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Interpretation: The feature importance analysis failed due to an unsupported file format (HTML heatmap instead of raw data), meaning we cannot yet directly quantify which features most influence 'fare_amount'. However, prior steps (correlation analysis and profiling) provide indirect evidence about potential important features, though manual interpretation is still required. Answered: False (confidence: 30%) Should stop: False Next questions: ["What are the exact correlation values between 'fare_amount' and other features (e.g., 'distance_km', 'pickup_time') from the raw correlation analysis?", 'Can we extract the numerical correlation matrix from the interactive heatmap to perform feature importance ranking?', 'Are there non-linear relationships or interaction effects (e.g., distance Γ— city) that simple correlation misses?'] [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=finding_discovered, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 19 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ── Iteration 5/8 ── πŸ€” REASON: Deciding next action... [SSE] GOT event from queue: finding_discovered INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Status: investigating Reasoning: The `auto_feature_selection` tool failed due to an unsupported file format, and prior steps (correlation heatmap and profiling) provide indirect evidence but no direct quantification of feature importance. Running `train_with_autogluon` will train a model and explicitly rank features by their importance to 'fare_amount', addressing the user's question directly. Tool: train_with_autogluon Hypothesis: We expect to identify the top features (e.g., 'distance_km', 'city', temporal features) that strongly influence 'fare_amount', providing a ranked list of important features with quantifiable importance scores. [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=reasoning_step, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 20 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ⚑ ACT: Executing train_with_autogluon... [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_executing, msg=πŸ”§ Executing: train_with_autogluon [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 21 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“‹ Final parameters: ['file_path', 'target_col', 'task_type', 'time_limit', 'presets'] [SSE] GOT event from queue: reasoning_step [SSE] GOT event from queue: tool_executing [SSE] ENDPOINT: Client connected for session_id=1963e777-4930-4200-9ada-ad742e5de6bc [SSE] Queue registered, total subscribers: 1 INFO: 10.16.4.123:23205 - "GET /api/progress/stream/1963e777-4930-4200-9ada-ad742e5de6bc HTTP/1.1" 200 OK [SSE] SENDING connection event to client [SSE] No history to replay (fresh session) [SSE] Starting event stream loop for session 1963e777-4930-4200-9ada-ad742e5de6bc πŸš€ AutoGluon Training Starting... πŸ“ Dataset: /tmp/data_science_agent/outputs/plots/interactive/correlation_heatmap.html 🎯 Target: fare_amount ⏱️ Time limit: 1800s πŸ“Š Presets: medium_quality ⚠️ failed (attempt 1/2): Failed to load data: Error tokenizing data. C error: Expected 1 fields in line 7, saw 3 Retrying in 1.0s... πŸ“‹ Final parameters: ['file_path', 'target_col', 'task_type', 'time_limit', 'presets'] πŸš€ AutoGluon Training Starting... πŸ“ Dataset: /tmp/data_science_agent/outputs/plots/interactive/correlation_heatmap.html 🎯 Target: fare_amount ⏱️ Time limit: 1800s πŸ“Š Presets: medium_quality ❌ failed after 2 attempts πŸ’‘ Suggested fallback tools: [] ❌ Tool failed: Failed to load data: Error tokenizing data. C error: Expected 1 fields in line 7, saw 3 [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_failed, msg=❌ FAILED: train_with_autogluon [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 22 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“Š EVALUATE: Interpreting results... [SSE] GOT event from queue: tool_failed INFO:src.api.app:SSE stream cancelled for session 1963e777-4930-4200-9ada-ad742e5de6bc INFO:src.api.app:SSE stream closed for session 1963e777-4930-4200-9ada-ad742e5de6bc INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Interpretation: The AutoGluon training failed due to a data tokenization error, likely caused by malformed input data (e.g., inconsistent delimiters or corrupted rows). This means we cannot yet directly quantify feature importance for 'fare_amount' using automated methods, and prior indirect evidence (e.g., correlations) remains unvalidated. Answered: False (confidence: 20%) Should stop: False Next questions: ['What is the root cause of the tokenization error (e.g., delimiter mismatch, corrupted rows), and how can the data be cleaned to resolve it?', 'Can we manually inspect the raw data (e.g., line 7) to identify and fix formatting issues before retrying automated feature importance analysis?', 'Are there alternative methods (e.g., manual feature engineering, simpler models) to estimate feature importance given the current data limitations?'] [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=finding_discovered, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 23 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ── Iteration 6/8 ── πŸ€” REASON: Deciding next action... [SSE] GOT event from queue: finding_discovered INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Status: investigating Reasoning: The previous `auto_feature_selection` and `train_with_autogluon` steps failed due to incorrect input formats, but we have an interactive correlation heatmap that visually suggests relationships. To quantify feature importance, we need to extract the raw correlation data or re-run feature selection on the original dataset (not the HTML file). Tool: auto_feature_selection Hypothesis: We expect to identify the top features (e.g., 'distance_km', 'city', temporal features) that strongly influence 'fare_amount', providing a ranked list of important features with quantifiable importance scores. [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=reasoning_step, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 24 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ⚑ ACT: Executing auto_feature_selection... [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_executing, msg=πŸ”§ Executing: auto_feature_selection [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 25 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“‹ Final parameters: ['file_path', 'target_col', 'task_type', 'method'] ❌ Tool failed: File not found: /tmp/data_science_agent/data/processed_data.parquet [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_failed, msg=❌ FAILED: auto_feature_selection [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 26 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“Š EVALUATE: Interpreting results... [SSE] GOT event from queue: reasoning_step [SSE] GOT event from queue: tool_executing [SSE] GOT event from queue: tool_failed INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Interpretation: The failure of the `auto_feature_selection` tool due to a missing file means we cannot directly quantify feature importance for 'fare_amount' at this stage. This blocks our ability to answer the original question about important features, though prior indirect evidence (e.g., correlations) suggests potential candidates like 'distance_km' and 'city'. The root cause appears to be a file path or data pipeline issue, not a methodological limitation. Answered: False (confidence: 20%) Should stop: False Next questions: ['What is the correct file path or format for the processed data to enable feature importance analysis?', 'Can we rerun prior correlation analyses on the raw data to extract quantifiable feature importance metrics (e.g., correlation coefficients) as a temporary workaround?', 'Are there data quality issues (e.g., missing values, incorrect formats) in the raw data that caused the AutoGluon tokenization error and need to be addressed first?'] [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=finding_discovered, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 27 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ── Iteration 7/8 ── πŸ€” REASON: Deciding next action... [SSE] GOT event from queue: finding_discovered INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Status: investigating Reasoning: The previous attempts to quantify feature importance failed due to file format issues or data errors. The most direct next step is to re-run `auto_feature_selection` on the raw dataset (not the HTML heatmap) to obtain a ranked list of important features for 'fare_amount'. Tool: auto_feature_selection Hypothesis: We expect to identify the top features (e.g., 'distance_km', 'city', temporal features) that strongly influence 'fare_amount', providing a ranked list of important features with quantifiable importance scores. [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=reasoning_step, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 28 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ⚑ ACT: Executing auto_feature_selection... [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_executing, msg=πŸ”§ Executing: auto_feature_selection [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 29 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“‹ Final parameters: ['file_path', 'target_col', 'task_type', 'method'] ❌ Tool failed: File not found: /tmp/data_science_agent/data/raw_dataset.parquet [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_failed, msg=❌ FAILED: auto_feature_selection [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 30 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“Š EVALUATE: Interpreting results... [SSE] GOT event from queue: reasoning_step [SSE] GOT event from queue: tool_executing [SSE] GOT event from queue: tool_failed INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Interpretation: The failure due to a missing file means we cannot directly quantify feature importance for 'fare_amount' at this stage, blocking the original question. This is likely a data pipeline or file path issue, not a methodological limitation, and requires immediate resolution before proceeding with feature analysis. Answered: False (confidence: 10%) Should stop: False Next questions: ['What is the correct file path for the raw dataset, and does the file exist in the expected location?', 'Are there alternative data sources or formats (e.g., CSV, JSON) available for the same dataset to bypass the file path issue?', 'Can we validate the integrity of the data pipeline to ensure no corruption or misalignment occurred during prior steps?'] [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=finding_discovered, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 31 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ── Iteration 8/8 ── πŸ€” REASON: Deciding next action... [SSE] GOT event from queue: finding_discovered INFO:src.api.app:[ASYNC] Created new session: f0b5e746... INFO:src.api.app:[ASYNC] File saved: intraday_tips.csv INFO: 10.16.4.123:13810 - "POST /run-async HTTP/1.1" 200 OK [SSE] ENDPOINT: Client connected for session_id=f0b5e746-66ec-40ba-b4dc-dbff0ff5ac77 [SSE] Queue registered, total subscribers: 1 INFO: 10.16.34.155:48122 - "GET /api/progress/stream/f0b5e746-66ec-40ba-b4dc-dbff0ff5ac77 HTTP/1.1" 200 OK [SSE] SENDING connection event to client [SSE] No history to replay (fresh session) [SSE] Starting event stream loop for session f0b5e746-66ec-40ba-b4dc-dbff0ff5ac77 INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Status: investigating Reasoning: The previous attempts to quantify feature importance failed due to file format issues (HTML instead of raw data). We need to ensure the raw data is used for feature selection to directly answer the user's question about important features. Tool: auto_feature_selection Hypothesis: We expect to identify the top features (e.g., 'distance_km', 'city', temporal features) that strongly influence 'fare_amount', providing a ranked list of important features with quantifiable importance scores. [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=reasoning_step, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 32 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ⚑ ACT: Executing auto_feature_selection... [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_executing, msg=πŸ”§ Executing: auto_feature_selection [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 33 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“‹ Final parameters: ['file_path', 'target_col', 'task_type', 'method'] ❌ Tool failed: File not found: /tmp/data_science_agent/data/raw_data.parquet [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=tool_failed, msg=❌ FAILED: auto_feature_selection [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 34 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 πŸ“Š EVALUATE: Interpreting results... [SSE] GOT event from queue: reasoning_step [SSE] GOT event from queue: tool_executing [SSE] GOT event from queue: tool_failed INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" Interpretation: The result indicates a critical data pipeline failureβ€”specifically, the input file cannot be locatedβ€”blocking any direct analysis of feature importance for 'fare_amount'. This means the original question remains unanswered, and no new insights about feature importance can be derived until the file path or data access issue is resolved. Answered: False (confidence: 10%) Should stop: False Next questions: ['What is the correct file path for the dataset, and does the file exist in the expected location?', 'Are there alternative datasets or backups available to proceed with feature importance analysis?', 'Can we validate the data pipeline to ensure no other files are missing or corrupted before retrying?', 'Should we prioritize debugging the file access issue or switch to indirect methods (e.g., correlation analysis) to infer feature importance temporarily?'] [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=finding_discovered, msg= [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 35 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 ============================================================ πŸ“ SYNTHESIZE: Building final answer from 8 findings... ============================================================ [SSE] GOT event from queue: finding_discovered INFO:httpx:HTTP Request: POST https://api.mistral.ai/v1/chat/completions "HTTP/1.1 200 OK" [DEBUG] Report tool detected: generate_ydata_profiling_report [DEBUG] nested_result keys: ['success', 'report_path', 'message', 'statistics'] [DEBUG] Report path found: /tmp/data_science_agent/uber_trips_profiling_report.html [DEBUG] Added to artifacts[reports], total reports: 1 [DEBUG] Extracting plot from tool: generate_interactive_correlation_heatmap [DEBUG] result keys: ['success', 'tool', 'arguments', 'result'] [DEBUG] nested_result keys: ['status', 'plot_type', 'output_path', 'num_features'] [DEBUG] output_path in nested_result: True [DEBUG] output_path value: /tmp/data_science_agent/outputs/plots/interactive/correlation_heatmap.html [DEBUG] Added plot to array: [DEBUG] title: Correlation Heatmap [DEBUG] url: /outputs/plots/interactive/correlation_heatmap.html [DEBUG] type: html [DEBUG] Merging 1 reports into plots array [DEBUG] Added report to plots array: title='Generate Ydata Profiling Report', url='/outputs//tmp/data_science_agent/uber_trips_profiling_report.html' [DEBUG] Final plots array length: 2 βœ… Reasoning loop completed in 233.75s Iterations: 8 Tools used: generate_ydata_profiling_report, analyze_correlations, generate_interactive_correlation_heatmap, auto_feature_selection, train_with_autogluon API calls: 18 INFO:src.api.app:[BACKGROUND] Analysis completed for session 2df5d6d1... [SSE] PROGRESS_MANAGER EMIT: session=2df5d6d1-f23c-48fb-b353-373e7693b75e, event_type=analysis_complete, msg=βœ… Analysis completed successfully! [SSE] History stored, total events for 2df5d6d1-f23c-48fb-b353-373e7693b75e: 36 [SSE] Found 1 subscribers for 2df5d6d1-f23c-48fb-b353-373e7693b75e [SSE] Successfully queued event to subscriber 1 [SSE] GOT event from queue: analysis_complete INFO:src.api.app:SSE stream closed for session 2df5d6d1-f23c-48fb-b353-373e7693b75e INFO:src.api.app:Found file at: /tmp/data_science_agent/uber_trips_profiling_report.html INFO: 10.16.4.123:27264 - "GET /outputs//tmp/data_science_agent/uber_trips_profiling_report.html HTTP/1.1" 200 OK INFO:src.api.app:Found file at: /tmp/data_science_agent/outputs/plots/interactive/correlation_heatmap.html INFO: 10.16.4.123:46507 - "GET /outputs/plots/interactive/correlation_heatmap.html HTTP/1.1" 200 OK