fix: Fix module import paths for Render deployment

- Change all absolute imports to relative imports within src package
- Fix orchestrator.py: cache.cache_manager -> .cache.cache_manager
- Fix tools/__init__.py and auto_pipeline.py imports
- Fix all utils imports in tools/ directory (35 files)
- Fix api/app.py to use src.orchestrator import
- Resolves ModuleNotFoundError on Render deployment

VERCEL_DEPLOYMENT.md

@@ -0,0 +1,267 @@
+# Vercel Deployment Guide
+
+## ⚠️ Important Limitations
+
+Vercel has significant limitations for this application:
+
+### Execution Time Limits
+- **Free/Hobby:** 10 seconds per request
+- **Pro:** 60 seconds per request
+- **Enterprise:** 300 seconds per request
+
+### Memory Limits
+- Maximum 3008 MB (Pro/Enterprise)
+- May not be sufficient for large ML models
+
+### File System
+- Read-only except for `/tmp` (512 MB limit)
+- Files in `/tmp` are ephemeral and cleared between invocations
+
+### Recommendation
+⚠️ **For ML/Data Science workloads, Render or Railway is recommended** over Vercel due to:
+- Long-running analysis tasks (often >60s)
+- Large model file sizes
+- Memory requirements for ML operations
+- Need for persistent storage
+
+## If You Still Want to Try Vercel
+
+### Prerequisites
+
+1. A [Vercel account](https://vercel.com/) (free tier available)
+2. Vercel CLI installed: `npm install -g vercel`
+3. Your code pushed to GitHub
+
+### Quick Deploy
+
+#### Option 1: Via Vercel Dashboard (Easiest)
+
+1. **Go to Vercel Dashboard**: https://vercel.com/dashboard
+
+2. **Import Project:**
+   - Click "Add New..." → "Project"
+   - Select your GitHub repository: `Pulastya-B/DevSprint-Data-Science-Agent`
+
+3. **Configure Build Settings:**
+   - **Framework Preset:** Other
+   - **Build Command:** `cd FRRONTEEEND && npm install && npm run build`
+   - **Output Directory:** `FRRONTEEEND/dist`
+   - **Install Command:** `pip install -r requirements.txt`
+
+4. **Add Environment Variables:**
+   ```
+   GOOGLE_API_KEY=<your-api-key>
+   LLM_PROVIDER=gemini
+   GEMINI_MODEL=gemini-2.5-flash
+   REASONING_EFFORT=medium
+   CACHE_DB_PATH=/tmp/cache_db/cache.db
+   OUTPUT_DIR=/tmp/outputs
+   DATA_DIR=/tmp/data
+   ```
+
+5. **Deploy:**
+   - Click "Deploy"
+   - Wait for build to complete (~3-5 minutes)
+
+#### Option 2: Via Vercel CLI
+
+1. **Install Vercel CLI:**
+   ```bash
+   npm install -g vercel
+   ```
+
+2. **Login to Vercel:**
+   ```bash
+   vercel login
+   ```
+
+3. **Deploy:**
+   ```bash
+   cd "C:\Users\Pulastya\Videos\DS AGENTTTT"
+   vercel
+   ```
+
+4. **Follow prompts:**
+   - Link to existing project or create new one
+   - Accept default settings
+   - Add environment variables when prompted
+
+5. **Production Deploy:**
+   ```bash
+   vercel --prod
+   ```
+
+### Environment Variables (Required)
+
+Add these in Vercel Dashboard → Settings → Environment Variables:
+
+```
+GOOGLE_API_KEY=<your-gemini-api-key>
+LLM_PROVIDER=gemini
+GEMINI_MODEL=gemini-2.5-flash
+REASONING_EFFORT=medium
+CACHE_DB_PATH=/tmp/cache_db/cache.db
+CACHE_TTL_SECONDS=86400
+OUTPUT_DIR=/tmp/outputs
+DATA_DIR=/tmp/data
+MAX_PARALLEL_TOOLS=5
+MAX_RETRIES=3
+TIMEOUT_SECONDS=60
+```
+
+### Configuration Files
+
+- **vercel.json** - Vercel deployment configuration
+- Routes API requests to FastAPI backend
+- Serves React frontend statically
+
+### Known Issues and Workarounds
+
+#### 1. Timeout Errors
+
+**Issue:** Analysis tasks exceed 60-second limit
+
+**Workarounds:**
+- Use smaller datasets for testing
+- Upgrade to Vercel Pro ($20/month) for 60s timeout
+- Consider splitting long operations into multiple API calls
+- Use background jobs (not supported on Vercel free tier)
+
+#### 2. Memory Errors
+
+**Issue:** ML models exceed memory limits
+
+**Workarounds:**
+- Use lighter models (e.g., LogisticRegression instead of XGBoost)
+- Process smaller data chunks
+- Upgrade to Vercel Pro for more memory
+
+#### 3. Cold Starts
+
+**Issue:** First request after idle is slow (~5-10s)
+
+**Workarounds:**
+- Use Vercel Pro for faster cold starts
+- Implement warming functions (Pro/Enterprise only)
+
+#### 4. File Storage
+
+**Issue:** Generated reports/models are lost between requests
+
+**Workarounds:**
+- Store outputs in external storage (S3, Cloudinary)
+- Use Vercel Blob Storage (paid feature)
+- Accept ephemeral storage for demo purposes
+
+### Testing Your Deployment
+
+1. **Check deployment status:**
+   ```bash
+   vercel ls
+   ```
+
+2. **View logs:**
+   ```bash
+   vercel logs <deployment-url>
+   ```
+
+3. **Test health endpoint:**
+   ```bash
+   curl https://your-app.vercel.app/api/health
+   ```
+
+4. **Test with small dataset:**
+   - Upload a small CSV (< 1MB, < 1000 rows)
+   - Request simple analysis (avoid complex ML operations)
+
+### Vercel vs Other Platforms
+
+| Feature | Vercel | Render | Railway |
+|---------|--------|--------|---------|
+| **Best For** | Static sites, Next.js | Full-stack apps, ML | Full-stack apps |
+| **Timeout (Free)** | 10s | 15min | 5min |
+| **Timeout (Paid)** | 60s | ∞ | ∞ |
+| **Memory (Max)** | 3008MB | 512MB-16GB | 512MB-32GB |
+| **Cold Starts** | Fast | Medium | Fast |
+| **Persistent Storage** | No (paid addon) | Yes | Yes |
+| **Docker Support** | No | Yes | Yes |
+| **Price (Hobby)** | $20/mo | $7/mo | $5/mo |
+
+### Recommended Platform
+
+For this Data Science Agent, we recommend:
+
+1. **Render** (Best balance) - See [RENDER_DEPLOYMENT.md](RENDER_DEPLOYMENT.md)
+   - ✅ No timeout limits
+   - ✅ Docker support
+   - ✅ Affordable ($7/mo starter)
+   - ✅ Good for ML workloads
+
+2. **Railway** (Alternative)
+   - ✅ Good free tier
+   - ✅ Persistent storage
+   - ✅ Docker support
+   - ⚠️ $5/mo minimum
+
+3. **Vercel** (Not recommended for this app)
+   - ❌ 60s timeout limit
+   - ❌ No Docker support
+   - ❌ Expensive for ML ($20/mo minimum)
+   - ✅ Great for frontend-heavy apps
+
+## Troubleshooting
+
+### Deployment Fails
+
+**Issue:** Build timeout during pip install
+
+**Solution:**
+- Reduce dependencies in requirements.txt
+- Use lighter ML libraries
+- Consider pre-building dependencies
+
+**Issue:** "Function Payload Too Large"
+
+**Solution:**
+- Reduce package sizes
+- Use `vercel.json` to exclude unnecessary files
+- Consider serverless architecture redesign
+
+### Runtime Errors
+
+**Issue:** "Task timed out after 10.00 seconds"
+
+**Solution:**
+- Upgrade to Vercel Pro
+- Optimize code for faster execution
+- Use smaller datasets
+- Consider using Render instead
+
+**Issue:** "Out of memory"
+
+**Solution:**
+- Upgrade to higher memory tier
+- Optimize memory usage
+- Process data in chunks
+
+## Conclusion
+
+While Vercel deployment is possible, it's **not recommended** for this ML/Data Science application due to:
+
+- ❌ Strict timeout limits (10s free, 60s pro)
+- ❌ Memory constraints for ML models
+- ❌ No persistent storage
+- ❌ High cost for necessary features
+
+**Better Alternative:** Use [Render](RENDER_DEPLOYMENT.md) for this application.
+
+If you must use Vercel:
+- Upgrade to Pro plan ($20/month minimum)
+- Use only for simple datasets
+- Expect frequent timeouts
+- Consider it a demo/prototype only
+
+---
+
+**Need help with Render deployment instead?**
+See [RENDER_DEPLOYMENT.md](RENDER_DEPLOYMENT.md) for a better solution.

src/api/app.py

@@ -21,10 +21,8 @@ from fastapi.staticfiles import StaticFiles
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 
-# Add src to path for imports
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
-
-from orchestrator import DataScienceCopilot
+# Import from parent package
+from src.orchestrator import DataScienceCopilot
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)

src/orchestrator.py

@@ -15,11 +15,11 @@ from groq import Groq
 import google.generativeai as genai
 from dotenv import load_dotenv
 
-from cache.cache_manager import CacheManager
-from tools.tools_registry import TOOLS, get_all_tool_names, get_tools_by_category
-from session_memory import SessionMemory
-from session_store import SessionStore
-from tools import (
+from .cache.cache_manager import CacheManager
+from .tools.tools_registry import TOOLS, get_all_tool_names, get_tools_by_category
+from .session_memory import SessionMemory
+from .session_store import SessionStore
+from .tools import (
     # Basic Tools (13) - UPDATED: Added get_smart_summary + 3 wrangling tools
     profile_dataset,
     detect_data_quality_issues,

src/tools/__init__.py

@@ -162,7 +162,7 @@ from .cloud_data_sources import (
 
 from .tools_registry import TOOLS, get_tool_by_name, get_all_tool_names
 
-from tools.enhanced_feature_engineering import (
+from .enhanced_feature_engineering import (
     create_ratio_features,
     create_statistical_features,
     create_log_features,

src/tools/advanced_analysis.py

@@ -28,10 +28,10 @@ import plotly.express as px
 from plotly.subplots import make_subplots
 import pandas as pd
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe, get_numeric_columns, get_categorical_columns
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists, validate_file_format, validate_dataframe,
     validate_column_exists
 )

src/tools/advanced_feature_engineering.py

@@ -25,11 +25,11 @@ from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
 from textblob import TextBlob
 import re
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe, save_dataframe, get_numeric_columns,
     get_categorical_columns, get_datetime_columns
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists, validate_file_format, validate_dataframe,
     validate_column_exists
 )

src/tools/advanced_insights.py

@@ -20,8 +20,8 @@ import json
 # Add parent directory to path
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import load_dataframe, get_numeric_columns
-from utils.validation import validate_file_exists, validate_file_format
+from ..utils.polars_helpers import load_dataframe, get_numeric_columns
+from ..utils.validation import validate_file_exists, validate_file_format
 
 
 def analyze_root_cause(file_path: str, 

src/tools/advanced_preprocessing.py

@@ -24,11 +24,11 @@ from imblearn.under_sampling import RandomUnderSampler, TomekLinks, EditedNeares
 from imblearn.combine import SMOTETomek, SMOTEENN
 from collections import Counter
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe, save_dataframe, get_numeric_columns,
     get_categorical_columns, split_features_target
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists, validate_file_format, validate_dataframe,
     validate_column_exists
 )

src/tools/advanced_training.py

@@ -45,8 +45,8 @@ from sklearn.metrics import (
     mean_squared_error, mean_absolute_error, r2_score
 )
 
-from utils.polars_helpers import load_dataframe, get_numeric_columns, split_features_target
-from utils.validation import (
+from ..utils.polars_helpers import load_dataframe, get_numeric_columns, split_features_target
+from ..utils.validation import (
     validate_file_exists, validate_file_format, validate_dataframe,
     validate_column_exists, validate_target_column
 )

src/tools/auto_pipeline.py

@@ -16,12 +16,12 @@ from sklearn.preprocessing import StandardScaler
 # Add parent directory to path
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import load_dataframe, get_numeric_columns
-from utils.validation import validate_file_exists
-from tools.data_cleaning import clean_missing_values, handle_outliers
-from tools.data_type_conversion import force_numeric_conversion, smart_type_inference
-from tools.feature_engineering import encode_categorical, create_time_features
-from tools.advanced_feature_engineering import create_interaction_features
+from ..utils.polars_helpers import load_dataframe, get_numeric_columns
+from ..utils.validation import validate_file_exists
+from .data_cleaning import clean_missing_values, handle_outliers
+from .data_type_conversion import force_numeric_conversion, smart_type_inference
+from .feature_engineering import encode_categorical, create_time_features
+from .advanced_feature_engineering import create_interaction_features
 
 
 def auto_ml_pipeline(file_path: str,

src/tools/cloud_data_sources.py

@@ -14,7 +14,7 @@ import os
 # Add parent directory to path
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.validation import validate_dataframe
+from ..utils.validation import validate_dataframe
 
 try:
     from google.cloud import bigquery

src/tools/data_cleaning.py

@@ -13,7 +13,7 @@ import os
 # Add parent directory to path for imports
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe,
     save_dataframe,
     get_numeric_columns,
@@ -21,7 +21,7 @@ from utils.polars_helpers import (
     get_datetime_columns,
     detect_id_columns,
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists,
     validate_file_format,
     validate_dataframe,

src/tools/data_profiling.py

@@ -13,7 +13,7 @@ import os
 # Add parent directory to path for imports
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe,
     get_numeric_columns,
     get_categorical_columns,
@@ -22,7 +22,7 @@ from utils.polars_helpers import (
     calculate_memory_usage,
     detect_id_columns,
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists,
     validate_file_format,
     validate_dataframe,

src/tools/data_type_conversion.py

@@ -11,13 +11,13 @@ import os
 # Add parent directory to path for imports
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe,
     save_dataframe,
     get_numeric_columns,
     get_categorical_columns
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists,
     validate_file_format,
     validate_dataframe

src/tools/data_wrangling.py

@@ -13,11 +13,11 @@ import os
 # Add parent directory to path for imports
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe,
     save_dataframe,
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists,
     validate_file_format,
     validate_dataframe,

src/tools/enhanced_feature_engineering.py

@@ -11,8 +11,8 @@ import os
 
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import load_dataframe, save_dataframe, get_numeric_columns
-from utils.validation import validate_file_exists, validate_dataframe
+from ..utils.polars_helpers import load_dataframe, save_dataframe, get_numeric_columns
+from ..utils.validation import validate_file_exists, validate_dataframe
 
 
 def create_ratio_features(file_path: str, 

src/tools/feature_engineering.py

@@ -13,13 +13,13 @@ import os
 # Add parent directory to path for imports
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe,
     save_dataframe,
     get_numeric_columns,
     get_categorical_columns,
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists,
     validate_file_format,
     validate_dataframe,

src/tools/model_training.py

@@ -47,12 +47,12 @@ except ImportError as e:
     VISUALIZATION_AVAILABLE = False
     print(f"⚠️  Visualization engine not available: {e}")
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe,
     get_numeric_columns,
     split_features_target,
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists,
     validate_file_format,
     validate_dataframe,

src/tools/plotly_visualizations.py

@@ -16,12 +16,12 @@ import os
 # Add parent directory to path for imports
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import (
+from ..utils.polars_helpers import (
     load_dataframe,
     get_numeric_columns,
     get_categorical_columns,
 )
-from utils.validation import (
+from ..utils.validation import (
     validate_file_exists,
     validate_file_format,
     validate_dataframe,

src/tools/production_mlops.py

@@ -25,8 +25,8 @@ import shap
 from lime import lime_tabular
 from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
 
-from utils.polars_helpers import load_dataframe, get_numeric_columns, split_features_target
-from utils.validation import validate_file_exists, validate_file_format, validate_dataframe, validate_column_exists
+from ..utils.polars_helpers import load_dataframe, get_numeric_columns, split_features_target
+from ..utils.validation import validate_file_exists, validate_file_format, validate_dataframe, validate_column_exists
 
 
 def monitor_model_drift(

src/tools/time_series.py

@@ -25,8 +25,8 @@ sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 # from prophet import Prophet
 import pandas as pd
 
-from utils.polars_helpers import load_dataframe, save_dataframe
-from utils.validation import validate_file_exists, validate_file_format, validate_dataframe, validate_column_exists
+from ..utils.polars_helpers import load_dataframe, save_dataframe
+from ..utils.validation import validate_file_exists, validate_file_format, validate_dataframe, validate_column_exists
 
 
 def forecast_time_series(

src/tools/visualization_engine.py

@@ -22,8 +22,8 @@ from sklearn.metrics import confusion_matrix, roc_curve, auc, precision_recall_c
 # Add parent directory to path
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.polars_helpers import load_dataframe
-from utils.validation import validate_file_exists
+from ..utils.polars_helpers import load_dataframe
+from ..utils.validation import validate_file_exists
 
 # Import matplotlib visualization functions
 try:

vercel.json

@@ -0,0 +1,56 @@
+{
+  "version": 2,
+  "builds": [
+    {
+      "src": "src/api/app.py",
+      "use": "@vercel/python",
+      "config": {
+        "maxLambdaSize": "50mb"
+      }
+    },
+    {
+      "src": "FRRONTEEEND/package.json",
+      "use": "@vercel/static-build",
+      "config": {
+        "distDir": "dist"
+      }
+    }
+  ],
+  "routes": [
+    {
+      "src": "/api/(.*)",
+      "dest": "src/api/app.py"
+    },
+    {
+      "src": "/outputs/(.*)",
+      "dest": "src/api/app.py"
+    },
+    {
+      "src": "/(.*)",
+      "dest": "FRRONTEEEND/dist/$1"
+    }
+  ],
+  "env": {
+    "LLM_PROVIDER": "gemini",
+    "GEMINI_MODEL": "gemini-2.5-flash",
+    "REASONING_EFFORT": "medium",
+    "CACHE_DB_PATH": "/tmp/cache_db/cache.db",
+    "CACHE_TTL_SECONDS": "86400",
+    "OUTPUT_DIR": "/tmp/outputs",
+    "DATA_DIR": "/tmp/data",
+    "MAX_PARALLEL_TOOLS": "5",
+    "MAX_RETRIES": "3",
+    "TIMEOUT_SECONDS": "60"
+  },
+  "build": {
+    "env": {
+      "NODE_VERSION": "20"
+    }
+  },
+  "functions": {
+    "src/api/app.py": {
+      "memory": 3008,
+      "maxDuration": 60
+    }
+  }
+}