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Equires a solution that can generate interactive graph charts from uploaded CSV or Excel files based on natural language queries in both English and Hindi. The solution should be implemented within the Strealit application framework. Here's a comprehensive approach to achieve this: 1. Data Ingestion and Preprocessing: File Upload: Allow users to upload CSV or Excel files to the Strealit application. Data Validation: Ensure the uploaded file is in a valid format and contains the necessary data. Data Cleaning: Handle missing values, inconsistent data, and outliers to improve data quality. Data Transformation: Convert data types as needed (e.g., strings to numbers) and normalize data if necessary. 2. Natural Language Processing (NLP): Query Parsing: Use an NLP library (e.g., NLTK, spaCy) to parse natural language queries in English and Hindi. Keyword Extraction: Identify relevant keywords and phrases from the queries. Intent Classification: Determine the user's intent (e.g., "show me the sales trend," "compare product A and B"). Entity Extraction: Extract entities from the queries (e.g., "sales," "product A"). 3. Query to Chart Mapping: Chart Type Selection: Based on the identified intent and entities, determine the appropriate chart type (e.g., line chart for trends, bar chart for comparisons). Data Aggregation: Aggregate data from the CSV or Excel file as required for the chart (e.g., group by product, calculate averages). Chart Configuration: Set chart parameters (e.g., title, labels, colors) based on the query and user preferences. 4. Chart Generation and Visualization: Chart Library: Use a charting library (e.g., Plotly, Matplotlib) to create the desired chart based on the aggregated data and configuration. Interactive Features: Enable interactive elements like zooming, panning, and tooltips for exploration. Language Localization: Provide localized labels, tooltips, and other UI elements for Hindi queries. 5. Integration with Strealit: Component Development: Create Strealit components that handle file upload, query processing, chart generation, and visualization. User Interface: Design an intuitive user interface that allows users to upload files, enter queries, and interact with the generated charts. Deployment: Deploy the Strealit application to a suitable environment (e.g., cloud platform, local server). Additional Considerations: Performance Optimization: Optimize data processing and chart generation for large datasets. Error Handling: Implement robust error handling to gracefully handle unexpected situations. Accessibility: Ensure the application is accessible to users with disabilities. Security: Protect user data and prevent unauthorized access. Scalability: Design the application to handle increasing user demand and data volumes.