diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/LICENSE.txt b/ai/gen-ai-agents/sql_graph_generator_dashboard/LICENSE.txt deleted file mode 100644 index 46c0c79d9..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/LICENSE.txt +++ /dev/null @@ -1,35 +0,0 @@ -Copyright (c) 2025 Oracle and/or its affiliates. - -The Universal Permissive License (UPL), Version 1.0 - -Subject to the condition set forth below, permission is hereby granted to any -person obtaining a copy of this software, associated documentation and/or data -(collectively the "Software"), free of charge and under any and all copyright -rights in the Software, and any and all patent rights owned or freely -licensable by each licensor hereunder covering either (i) the unmodified -Software as contributed to or provided by such licensor, or (ii) the Larger -Works (as defined below), to deal in both - -(a) the Software, and -(b) any piece of software and/or hardware listed in the lrgrwrks.txt file if -one is included with the Software (each a "Larger Work" to which the Software -is contributed by such licensors), - -without restriction, including without limitation the rights to copy, create -derivative works of, display, perform, and distribute the Software and make, -use, sell, offer for sale, import, export, have made, and have sold the -Software and the Larger Work(s), and to sublicense the foregoing rights on -either these or other terms. - -This license is subject to the following condition: -The above copyright notice and either this complete permission notice or at -a minimum a reference to the UPL must be included in all copies or -substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/README.md b/ai/gen-ai-agents/sql_graph_generator_dashboard/README.md deleted file mode 100644 index 20185e3c6..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/README.md +++ /dev/null @@ -1,231 +0,0 @@ -# SQL Graph Generator Dashboard - -SQL Graph Generator Dashboard is an AI-powered assistant that enables natural language database queries and intelligent chart generation. -It extracts data from your database using conversational queries, automatically generates appropriate visualizations, and provides multi-turn conversational context for data exploration. -It runs as an interactive Next.js web app backed by a FastAPI server, LangChain orchestration, and Oracle Cloud Infrastructure GenAI models. - -Reviewed: October 13, 2025 - -# When to use this asset? - -Use this asset when you want to: - -- Query databases using natural language instead of SQL -- Automatically generate charts and visualizations from query results -- Build conversational data exploration interfaces -- Integrate OCI GenAI models with database operations -- Demonstrate intelligent routing between data queries, visualizations, and insights - -Ideal for: - -- AI engineers building conversational data analytics tools -- Data teams needing natural language database interfaces -- OCI customers integrating GenAI into business intelligence workflows -- Anyone showcasing LangChain + OCI GenAI + dynamic visualization generation - -# How to use this asset? - -This assistant can be launched via: - -- Next.js Web UI - -It supports: - -- Natural language to SQL conversion -- Automatic chart generation from query results -- Multi-turn conversations with context preservation -- Multiple chart types: bar, line, pie, scatter, heatmap -- Real-time data visualization using matplotlib/seaborn -- Intelligent routing between data queries, visualizations, and insights - -## Setup Instructions - -### OCI Generative AI Model Configuration - -1. Go to: OCI Console → Generative AI -2. Select your model (this demo uses OpenAI GPT OSS 120B): - `ocid1.generativeaimodel.oc1.eu-frankfurt-1.amaaaaaask7dceyav...` -3. Set up an OCI Agent Runtime endpoint for SQL queries -4. Copy the following values: - - MODEL_ID - - AGENT_ENDPOINT_ID - - COMPARTMENT_ID - - SERVICE_ENDPOINT (e.g., `https://inference.generativeai.eu-frankfurt-1.oci.oraclecloud.com`) -5. Configure them in `backend/utils/config.py` - -Documentation: -[OCI Generative AI Documentation](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm) - -No API key is required — authentication is handled via OCI identity. - -Ensure your OCI CLI credentials are configured. -Edit or create the following config file at `~/.oci/config`: - -``` -[DEFAULT] -user=ocid1.user.oc1..exampleuniqueID -fingerprint=c6:4f:66:e7:xx:xx:xx:xx -tenancy=ocid1.tenancy.oc1..exampleuniqueID -region=eu-frankfurt-1 -key_file=~/.oci/oci_api_key.pem -``` - -### Install Dependencies - -Backend: - -```bash -cd backend -pip install -r requirements.txt -``` - -Frontend: - -```bash -cd .. -npm install -``` - -### Configure Database - -1. Set up your database connection in OCI Agent Runtime -2. The demo uses a sample e-commerce database with tables: - - orders - - customers - - products - - order_items - -### Start the Application - -Backend (FastAPI): - -```bash -cd backend -python -m uvicorn api.main:app --reload --host 0.0.0.0 --port 8000 -``` - -Frontend (Next.js): - -```bash -npm run dev -``` - -Access the application at: http://localhost:3000 - -## Key Features - -| Feature | Description | -| ------------------------ | ---------------------------------------------------------------- | -| Natural Language Queries | Ask questions like "show me the top 5 orders" | -| Intelligent Routing | GenAI-powered routing between data queries, charts, and insights | -| Auto Chart Generation | Automatically creates appropriate visualizations from data | -| Multi-Turn Conversations | Maintains context across multiple queries | -| Real-Time Visualization | Generates matplotlib/seaborn charts as base64 images | -| Multiple Chart Types | Supports bar, line, pie, scatter, and heatmap charts | -| OCI GenAI Integration | Uses OCI Agent Runtime and Chat API | -| LangChain Runnables | Clean integration pattern wrapping OCI SDK calls | -| Conversation Management | Tracks query history and data state | -| Error Handling | Clear error messages and fallback behavior | - -## Architecture - -### Backend Components - -1. **Router Agent** (OCI Chat API) - - - Intelligent query routing using GenAI - - Routes: DATA_QUERY, CHART_EDIT, INSIGHT_QA - - Returns structured JSON decisions - -2. **SQL Agent** (OCI Agent Runtime) - - - Natural language to SQL conversion - - Database query execution - - Structured data extraction - -3. **Chart Generator** (OCI Chat API + Python Execution) - - - GenAI generates matplotlib/seaborn code - - Safe code execution in sandboxed environment - - Returns base64-encoded chart images - -4. **Orchestrator** - - Coordinates agents based on routing decisions - - Manages conversation state - - Handles multi-turn context - -### Frontend Components - -1. **Chat Interface** - - - Real-time message display - - Support for text, tables, and images - - Speech recognition integration - -2. **Service Layer** - - - API communication with backend - - Response transformation - - Error handling - -3. **Context Management** - - User session handling - - Message history - - State management - -## Example Queries - -``` -"Show me the top 5 orders" -→ Returns table with order data - -"Make a bar chart of those orders by total amount" -→ Generates bar chart visualization - -"Show me orders grouped by region" -→ Returns data aggregated by region - -"Create a pie chart of the order distribution" -→ Generates pie chart from current data - -"What insights can you provide about these sales?" -→ Provides AI-generated analysis -``` - -## Configuration Files - -Key configuration in `backend/utils/config.py`: - -- MODEL_ID: Your OCI GenAI model OCID -- AGENT_ENDPOINT_ID: Your OCI Agent Runtime endpoint -- COMPARTMENT_ID: Your OCI compartment -- SERVICE_ENDPOINT: GenAI service endpoint URL -- DATABASE_SCHEMA: Database table definitions - -## Notes - -- Prompts can be customized in `backend/orchestration/oci_direct_runnables.py` -- Chart generation code is dynamically created by GenAI -- Designed specifically for Oracle Cloud Infrastructure + Generative AI -- Sample database schema included for e-commerce use case -- Frontend uses Material-UI for consistent design - -# Useful Links - -- [OCI Generative AI](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm) - Official documentation for Oracle Generative AI - -- [OCI Agent Runtime](https://docs.oracle.com/en-us/iaas/Content/generative-ai/agent-runtime.htm) - Documentation for OCI Agent Runtime - -- [LangChain Documentation](https://python.langchain.com/docs/get_started/introduction) - LangChain framework documentation - -- [Next.js Documentation](https://nextjs.org/docs) - Next.js framework documentation - -# License - -Copyright (c) 2025 Oracle and/or its affiliates. - -Licensed under the Universal Permissive License (UPL), Version 1.0. diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/DATABASE_SETUP.md b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/DATABASE_SETUP.md deleted file mode 100644 index 8b07ba82a..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/DATABASE_SETUP.md +++ /dev/null @@ -1,130 +0,0 @@ -# Database Setup - -## Overview - -This application uses OCI Agent Runtime to query your database. The sample schema is for an e-commerce database. - -## Database Schema - -### CUSTOMERS Table -```sql -CREATE TABLE CUSTOMERS ( - CUSTOMER_ID NUMBER PRIMARY KEY, - CUSTOMER_NAME VARCHAR2(100), - EMAIL VARCHAR2(100), - SIGNUP_DATE DATE, - SEGMENT VARCHAR2(50), - COUNTRY VARCHAR2(50), - LIFETIME_VALUE NUMBER(10,2), - CREATION_DATE DATE, - CREATED_BY VARCHAR2(50), - LAST_UPDATED_DATE DATE, - LAST_UPDATED_BY VARCHAR2(50) -); -``` - -### PRODUCTS Table -```sql -CREATE TABLE PRODUCTS ( - PRODUCT_ID NUMBER PRIMARY KEY, - PRODUCT_NAME VARCHAR2(200), - CATEGORY VARCHAR2(100), - PRICE NUMBER(10,2), - COST NUMBER(10,2), - STOCK_QUANTITY NUMBER, - LAUNCH_DATE DATE, - CREATION_DATE DATE, - CREATED_BY VARCHAR2(50), - LAST_UPDATED_DATE DATE, - LAST_UPDATED_BY VARCHAR2(50) -); -``` - -### ORDERS Table -```sql -CREATE TABLE ORDERS ( - ORDER_ID NUMBER PRIMARY KEY, - CUSTOMER_ID NUMBER, - ORDER_DATE DATE, - TOTAL_AMOUNT NUMBER(10,2), - STATUS VARCHAR2(50), - REGION VARCHAR2(100), - SALES_REP VARCHAR2(100), - CREATION_DATE DATE, - CREATED_BY VARCHAR2(50), - LAST_UPDATED_DATE DATE, - LAST_UPDATED_BY VARCHAR2(50), - FOREIGN KEY (CUSTOMER_ID) REFERENCES CUSTOMERS(CUSTOMER_ID) -); -``` - -### ORDER_ITEMS Table -```sql -CREATE TABLE ORDER_ITEMS ( - ORDER_ITEM_ID NUMBER PRIMARY KEY, - ORDER_ID NUMBER, - PRODUCT_ID NUMBER, - QUANTITY NUMBER, - UNIT_PRICE NUMBER(10,2), - DISCOUNT_PERCENT NUMBER(5,2), - CREATION_DATE DATE, - CREATED_BY VARCHAR2(50), - LAST_UPDATED_DATE DATE, - LAST_UPDATED_BY VARCHAR2(50), - FOREIGN KEY (ORDER_ID) REFERENCES ORDERS(ORDER_ID), - FOREIGN KEY (PRODUCT_ID) REFERENCES PRODUCTS(PRODUCT_ID) -); -``` - -## Sample Data - -### Sample Customers -```sql -INSERT INTO CUSTOMERS VALUES (1, 'Acme Corp', 'contact@acme.com', DATE '2023-01-15', 'Enterprise', 'USA', 150000, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO CUSTOMERS VALUES (2, 'TechStart Inc', 'info@techstart.com', DATE '2023-03-20', 'SMB', 'UK', 45000, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO CUSTOMERS VALUES (3, 'Global Solutions', 'sales@global.com', DATE '2023-02-10', 'Enterprise', 'Germany', 200000, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -``` - -### Sample Products -```sql -INSERT INTO PRODUCTS VALUES (1, 'Enterprise Security Suite', 'Software', 3499.99, 1200, 100, DATE '2023-01-01', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO PRODUCTS VALUES (2, 'AI Analytics Platform', 'Software', 2999.99, 1000, 150, DATE '2023-02-01', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO PRODUCTS VALUES (3, 'Cloud Storage Pro', 'Cloud', 999.99, 300, 500, DATE '2023-03-01', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO PRODUCTS VALUES (4, 'Premium Consulting', 'Services', 5000, 2000, 50, DATE '2023-01-15', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO PRODUCTS VALUES (5, 'Training Program', 'Services', 2500, 800, 100, DATE '2023-02-20', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -``` - -### Sample Orders -```sql -INSERT INTO ORDERS VALUES (1, 1, DATE '2024-01-15', 8999.98, 'Completed', 'North America', 'John Smith', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDERS VALUES (2, 2, DATE '2024-01-20', 2999.99, 'Completed', 'Europe', 'Sarah Johnson', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDERS VALUES (3, 3, DATE '2024-02-01', 12499.97, 'Completed', 'Europe', 'Mike Davis', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDERS VALUES (4, 1, DATE '2024-02-15', 7500, 'Processing', 'North America', 'John Smith', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDERS VALUES (5, 2, DATE '2024-03-01', 999.99, 'Completed', 'Europe', 'Sarah Johnson', SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -``` - -### Sample Order Items -```sql -INSERT INTO ORDER_ITEMS VALUES (1, 1, 1, 2, 3499.99, 0, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (2, 1, 3, 2, 999.99, 10, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (3, 2, 2, 1, 2999.99, 0, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (4, 3, 1, 1, 3499.99, 0, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (5, 3, 2, 2, 2999.99, 10, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (6, 3, 5, 1, 2500, 0, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (7, 4, 4, 1, 5000, 0, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (8, 4, 5, 1, 2500, 0, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -INSERT INTO ORDER_ITEMS VALUES (9, 5, 3, 1, 999.99, 0, SYSDATE, 'SYSTEM', SYSDATE, 'SYSTEM'); -``` - -## OCI Agent Runtime Configuration - -1. Create database connection in OCI Agent Runtime -2. Configure database tool/function with: - - Connection string - - User credentials - - Query permissions -3. Test connection with simple query -4. Update AGENT_ENDPOINT_ID in config.py - - - diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/README_FILES.md b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/README_FILES.md deleted file mode 100644 index 3278b89a6..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/README_FILES.md +++ /dev/null @@ -1,180 +0,0 @@ -# Files Directory - Quick Start Guide - -This directory contains all necessary files to run the SQL Graph Generator Dashboard. - -## Directory Structure - -``` -files/ -├── backend/ -│ ├── api/ -│ │ └── main.py # FastAPI server entry point -│ ├── orchestration/ -│ │ ├── langchain_orchestrator_v2.py # Main orchestrator with routing logic -│ │ ├── oci_direct_runnables.py # OCI GenAI Chat API wrappers -│ │ ├── oci_runnables.py # OCI Agent Runtime wrappers -│ │ └── conversation_manager.py # Conversation state management -│ ├── tools/ -│ │ └── genai_chart_generator.py # Chart generation with GenAI -│ ├── utils/ -│ │ └── config.py # OCI configuration (UPDATE THIS) -│ └── requirements.txt # Python dependencies -├── frontend/ -│ ├── services/ -│ │ └── genaiAgentService.js # Backend API communication -│ ├── contexts/ -│ │ └── ChatContext.js # Chat state management -│ └── package.json # Node.js dependencies -├── database/ -│ ├── customers.csv # Sample customer data -│ ├── products.csv # Sample product data -│ ├── orders.csv # Sample order data -│ └── order_items.csv # Sample order items data -├── SETUP_GUIDE.md # Detailed setup instructions -├── DATABASE_SETUP.md # Database schema and setup -└── README_FILES.md # This file -``` - -## Quick Start (5 Steps) - -### 1. Update OCI Configuration - -Edit `backend/utils/config.py`: -```python -MODEL_ID = "ocid1.generativeaimodel.oc1.YOUR_REGION.YOUR_MODEL_ID" -AGENT_ENDPOINT_ID = "ocid1.genaiagentendpoint.oc1.YOUR_REGION.YOUR_ENDPOINT_ID" -COMPARTMENT_ID = "ocid1.compartment.oc1..YOUR_COMPARTMENT_ID" -SERVICE_ENDPOINT = "https://inference.generativeai.YOUR_REGION.oci.oraclecloud.com" -``` - -### 2. Setup OCI CLI - -Create `~/.oci/config`: -``` -[DEFAULT] -user=ocid1.user.oc1..YOUR_USER_OCID -fingerprint=YOUR_FINGERPRINT -tenancy=ocid1.tenancy.oc1..YOUR_TENANCY_OCID -region=YOUR_REGION -key_file=~/.oci/oci_api_key.pem -``` - -### 3. Install Dependencies - -Backend: -```bash -cd backend -pip install -r requirements.txt -``` - -Frontend (in project root): -```bash -npm install -``` - -### 4. Setup Database - -The database CSV files are included in `database/` directory. -Configure your OCI Agent Runtime to access these files or load them into your database. - -See `DATABASE_SETUP.md` for SQL schema. - -### 5. Run the Application - -Terminal 1 - Backend: -```bash -cd backend -python -m uvicorn api.main:app --reload --host 0.0.0.0 --port 8000 -``` - -Terminal 2 - Frontend (from project root): -```bash -npm run dev -``` - -Open: http://localhost:3000 - -## Key Files Explained - -### Backend - -**main.py** - FastAPI server with `/query` endpoint -- Receives natural language questions -- Returns data, charts, or text responses - -**langchain_orchestrator_v2.py** - Main orchestration logic -- Routes queries to appropriate agents -- Manages conversation state -- Coordinates data retrieval and chart generation - -**oci_direct_runnables.py** - OCI GenAI Chat API integration -- Router for intelligent query routing -- Uses GenAI for decision making - -**oci_runnables.py** - OCI Agent Runtime integration -- SQL Agent for database queries -- Extracts structured data from tool outputs - -**genai_chart_generator.py** - Chart generation -- Uses GenAI to create matplotlib code -- Executes code safely -- Returns base64-encoded images - -**conversation_manager.py** - State management -- Tracks conversation history -- Maintains data context - -### Frontend - -**genaiAgentService.js** - API client -- Communicates with backend -- Maps response fields (chart_base64 → diagram_base64) - -**ChatContext.js** - React context -- Manages chat state -- Processes responses for display -- Handles different message types - -## Configuration Tips - -1. **Region Consistency**: Ensure all OCIDs and endpoints use the same region -2. **Model Selection**: OpenAI GPT OSS 120B recommended for routing and generation -3. **Agent Tools**: Configure database tools in OCI Agent Runtime console -4. **Permissions**: Ensure OCI user has GenAI and Agent Runtime permissions - -## Common Issues - -**Authentication Error:** -- Check `~/.oci/config` file -- Verify API key is uploaded to OCI Console -- Test with: `oci iam region list` - -**Module Import Error:** -- Ensure you're in the correct directory -- Check all `__init__.py` files exist -- Verify Python path includes backend directory - -**Chart Not Displaying:** -- Check browser console for errors -- Verify chart_base64 field in API response -- Ensure frontend compiled successfully - -**SQL Agent Timeout:** -- Check AGENT_ENDPOINT_ID is correct -- Verify agent is deployed and active -- Test agent in OCI Console first - -## Next Steps - -1. Customize DATABASE_SCHEMA in config.py for your database -2. Adjust prompts in oci_direct_runnables.py for your use case -3. Add custom chart types in genai_chart_generator.py -4. Extend routing logic for additional query types - -## Support - -For OCI GenAI documentation: -https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm - -For OCI Agent Runtime: -https://docs.oracle.com/en-us/iaas/Content/generative-ai/agent-runtime.htm diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/SETUP_GUIDE.md b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/SETUP_GUIDE.md deleted file mode 100644 index 72ae21fc4..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/SETUP_GUIDE.md +++ /dev/null @@ -1,118 +0,0 @@ -# Setup Guide - -## Prerequisites - -1. Oracle Cloud Infrastructure (OCI) account -2. Python 3.8+ -3. Node.js 18+ -4. OCI CLI configured - -## Step 1: OCI Configuration - -Create `~/.oci/config`: - -``` -[DEFAULT] -user=ocid1.user.oc1..YOUR_USER_OCID -fingerprint=YOUR_FINGERPRINT -tenancy=ocid1.tenancy.oc1..YOUR_TENANCY_OCID -region=eu-frankfurt-1 -key_file=~/.oci/oci_api_key.pem -``` - -Generate API key: -```bash -openssl genrsa -out ~/.oci/oci_api_key.pem 2048 -openssl rsa -pubout -in ~/.oci/oci_api_key.pem -out ~/.oci/oci_api_key_public.pem -``` - -Upload public key to OCI Console → User Settings → API Keys - -## Step 2: OCI GenAI Setup - -1. Go to OCI Console → Generative AI -2. Create or select a model (e.g., OpenAI GPT OSS 120B) -3. Note the MODEL_ID -4. Create an Agent Runtime endpoint for SQL queries -5. Note the AGENT_ENDPOINT_ID -6. Get your COMPARTMENT_ID - -## Step 3: Update Configuration - -Edit `backend/utils/config.py`: -- Replace MODEL_ID with your model OCID -- Replace AGENT_ENDPOINT_ID with your agent endpoint OCID -- Replace COMPARTMENT_ID with your compartment OCID -- Update region if different from eu-frankfurt-1 - -## Step 4: Install Dependencies - -Backend: -```bash -cd backend -pip install -r requirements.txt -``` - -Frontend: -```bash -cd .. -npm install -``` - -## Step 5: Database Setup - -This demo uses OCI Agent Runtime with database tools. -Configure your database connection in the OCI Agent Runtime console: -1. Go to OCI Console → Generative AI → Agents -2. Create or configure your agent -3. Add database tool/function -4. Configure connection to your database - -Sample schema is provided in `config.py` for reference. - -## Step 6: Run the Application - -Terminal 1 (Backend): -```bash -cd backend -python -m uvicorn api.main:app --reload --host 0.0.0.0 --port 8000 -``` - -Terminal 2 (Frontend): -```bash -npm run dev -``` - -Access: http://localhost:3000 - -## Troubleshooting - -**OCI Authentication Error:** -- Verify ~/.oci/config is correct -- Check API key permissions in OCI Console -- Ensure key_file path is absolute - -**Model Not Found:** -- Verify MODEL_ID matches your OCI model OCID -- Check model is in same region as config -- Ensure compartment access permissions - -**Agent Endpoint Error:** -- Verify AGENT_ENDPOINT_ID is correct -- Check agent is deployed and active -- Ensure database tools are configured - -**Chart Generation Fails:** -- Check matplotlib/seaborn are installed -- Verify python code execution permissions -- Check logs for specific errors - -## Environment Variables (Optional) - -Instead of editing config.py, you can use environment variables: - -```bash -export MODEL_ID="ocid1.generativeaimodel..." -export AGENT_ENDPOINT_ID="ocid1.genaiagentendpoint..." -export COMPARTMENT_ID="ocid1.compartment..." -``` diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/api/main.py b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/api/main.py deleted file mode 100644 index e706a936a..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/api/main.py +++ /dev/null @@ -1,119 +0,0 @@ -""" -FastAPI server for SQL Graph Generator Dashboard -""" - -from fastapi import FastAPI, HTTPException -from fastapi.middleware.cors import CORSMiddleware -from pydantic import BaseModel -from typing import Dict, Any, List, Optional -import json -import logging - -from orchestration.langchain_orchestrator_v2 import LangChainOrchestratorV2 - -# Setup logging -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger(__name__) - -app = FastAPI(title="SQL Graph Generator Dashboard", version="1.0.0") - -# CORS configuration -app.add_middleware( - CORSMiddleware, - allow_origins=["http://localhost:3000", "http://localhost:3001"], - allow_credentials=True, - allow_methods=["*"], - allow_headers=["*"], -) - -# Initialize LangChain orchestrator -orchestrator = LangChainOrchestratorV2() - -# Request/Response models -class QueryRequest(BaseModel): - question: str - context: Optional[str] = "" - -class QueryResponse(BaseModel): - success: bool - response_type: str # "visualization", "data", "error" - query: Optional[str] = None - agent_response: Optional[str] = None - dashboard: Optional[Dict] = None - data: Optional[List[Dict]] = None - insights: Optional[List[str]] = None - text_response: Optional[str] = None - error: Optional[str] = None - chart_base64: Optional[str] = None - chart_config: Optional[Dict] = None - method: Optional[str] = None - generated_sql: Optional[str] = None - additional_info: Optional[str] = None - -@app.get("/") -async def root(): - return { - "message": "SQL Graph Generator Dashboard API", - "version": "1.0.0", - "status": "active" - } - -@app.get("/health") -async def health_check(): - return {"status": "healthy", "service": "sql-graph-generator"} - -@app.post("/query", response_model=QueryResponse) -async def process_query(request: QueryRequest): - """ - Process a user query and return data, visualization, or text response - """ - try: - logger.info(f"Processing query: {request.question}") - - result = orchestrator.process_natural_language_query(request.question) - - return QueryResponse(**result) - - except Exception as e: - logger.error(f"Error processing query: {str(e)}") - raise HTTPException(status_code=500, detail=str(e)) - -@app.get("/sample-questions") -async def get_sample_questions(): - """ - Get sample questions that users can ask - """ - return { - "questions": orchestrator.get_sample_questions(), - "description": "Sample questions you can ask the SQL Graph Generator" - } - -@app.get("/database-schema") -async def get_database_schema(): - """ - Get the database schema information - """ - from utils.config import DATABASE_SCHEMA - return { - "schema": DATABASE_SCHEMA, - "description": "E-commerce database schema with orders, customers, products, and order_items" - } - -@app.get("/chart-types") -async def get_supported_chart_types(): - """ - Get supported chart types - """ - return { - "chart_types": [ - {"type": "bar", "description": "Bar charts for category comparisons"}, - {"type": "line", "description": "Line charts for trends over time"}, - {"type": "pie", "description": "Pie charts for distributions"}, - {"type": "scatter", "description": "Scatter plots for correlations"}, - {"type": "heatmap", "description": "Heatmaps for correlation analysis"} - ] - } - -if __name__ == "__main__": - import uvicorn - uvicorn.run(app, host="0.0.0.0", port=8000) \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/conversation_manager.py b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/conversation_manager.py deleted file mode 100644 index fba047a15..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/conversation_manager.py +++ /dev/null @@ -1,211 +0,0 @@ -""" -Conversation History Manager for Multi-Turn Conversational Flow -Tracks context across multiple GenAI calls for intelligent responses -""" - -from typing import Dict, Any, List, Optional -from dataclasses import dataclass, asdict -from datetime import datetime -import json - - -@dataclass -class ConversationTurn: - """Single conversation turn with full context""" - user_query: str - route: str - data: Optional[List[Dict]] - chart_config: Optional[Dict] - response_type: str - agent_response: str - generated_sql: Optional[str] - chart_base64: Optional[str] - timestamp: datetime - success: bool - method: str - - def to_dict(self) -> Dict[str, Any]: - """Convert to dictionary for JSON serialization""" - return { - **asdict(self), - 'timestamp': self.timestamp.isoformat(), - 'data_summary': { - 'count': len(self.data) if self.data else 0, - 'columns': list(self.data[0].keys()) if self.data else [], - 'sample': self.data[:2] if self.data else [] - } if self.data else None - } - - def to_context_string(self) -> str: - """Convert to concise context string for prompts""" - context_parts = [ - f"Q: {self.user_query}", - f"Route: {self.route}", - f"Response: {self.agent_response[:100]}..." if len(self.agent_response) > 100 else f"Response: {self.agent_response}" - ] - - if self.data: - context_parts.append(f"Data: {len(self.data)} rows with columns {list(self.data[0].keys())}") - - if self.chart_config: - chart_type = self.chart_config.get('chart_type', 'unknown') - context_parts.append(f"Chart: {chart_type} chart created") - - return " | ".join(context_parts) - - -class ConversationManager: - """ - Manages conversation history and context for multi-turn interactions - """ - - def __init__(self, max_history: int = 10): - self.conversation_history: List[ConversationTurn] = [] - self.max_history = max_history - self.session_id = datetime.now().strftime("%Y%m%d_%H%M%S") - - def add_turn(self, - user_query: str, - route: str, - result: Dict[str, Any]) -> None: - """Add a new conversation turn""" - - turn = ConversationTurn( - user_query=user_query, - route=route, - data=result.get('data'), - chart_config=result.get('chart_config'), - response_type=result.get('response_type', 'unknown'), - agent_response=result.get('agent_response', ''), - generated_sql=result.get('generated_sql'), - chart_base64=result.get('chart_base64'), - timestamp=datetime.now(), - success=result.get('success', False), - method=result.get('method', 'unknown') - ) - - self.conversation_history.append(turn) - - # Keep only recent history - if len(self.conversation_history) > self.max_history: - self.conversation_history = self.conversation_history[-self.max_history:] - - print(f" Added conversation turn: {user_query} → {route}") - - def get_context_for_prompt(self, context_window: int = 3) -> str: - """ - Get formatted conversation context for GenAI prompts - """ - if not self.conversation_history: - return "No previous conversation history." - - recent_turns = self.conversation_history[-context_window:] if context_window else self.conversation_history - - context_lines = ["Previous conversation context:"] - for i, turn in enumerate(recent_turns, 1): - context_lines.append(f"{i}. {turn.to_context_string()}") - - return "\n".join(context_lines) - - def get_current_data(self) -> Optional[List[Dict]]: - """Get data from the most recent turn that has data""" - for turn in reversed(self.conversation_history): - if turn.data and turn.success: - return turn.data - return None - - def get_current_chart_config(self) -> Optional[Dict]: - """Get chart config from the most recent turn that has a chart""" - for turn in reversed(self.conversation_history): - if turn.chart_config and turn.success: - return turn.chart_config - return None - - def get_current_chart_base64(self) -> Optional[str]: - """Get the most recent chart image""" - for turn in reversed(self.conversation_history): - if turn.chart_base64 and turn.success: - return turn.chart_base64 - return None - - def has_data_context(self) -> bool: - """Check if we have data in recent context""" - return self.get_current_data() is not None - - def has_chart_context(self) -> bool: - """Check if we have a chart in recent context""" - return self.get_current_chart_config() is not None - - def get_data_summary(self) -> Dict[str, Any]: - """Get summary of current data context""" - data = self.get_current_data() - if not data: - return {"has_data": False} - - return { - "has_data": True, - "row_count": len(data), - "columns": list(data[0].keys()) if data else [], - "sample_row": data[0] if data else None - } - - def get_chart_summary(self) -> Dict[str, Any]: - """Get summary of current chart context""" - chart_config = self.get_current_chart_config() - if not chart_config: - return {"has_chart": False} - - return { - "has_chart": True, - "chart_type": chart_config.get("chart_type", "unknown"), - "x_axis": chart_config.get("x_axis", "unknown"), - "y_axis": chart_config.get("y_axis", "unknown"), - "title": chart_config.get("title", "") - } - - def clear_history(self) -> None: - """Clear conversation history""" - self.conversation_history = [] - print(" Conversation history cleared") - - def export_history(self) -> List[Dict]: - """Export conversation history as JSON-serializable format""" - return [turn.to_dict() for turn in self.conversation_history] - - def get_recent_queries(self, count: int = 5) -> List[str]: - """Get recent user queries for context""" - recent_turns = self.conversation_history[-count:] if count else self.conversation_history - return [turn.user_query for turn in recent_turns] - - def get_last_successful_sql(self) -> Optional[str]: - """Get the most recent successful SQL query""" - for turn in reversed(self.conversation_history): - if turn.generated_sql and turn.success and turn.route == "DATA_QUERY": - return turn.generated_sql - return None - - def should_use_existing_data(self, user_query: str) -> bool: - """ - Determine if the query can use existing data or needs new data - """ - query_lower = user_query.lower() - - # Keywords that suggest working with existing data - chart_keywords = ["chart", "graph", "plot", "visualize", "show", "display"] - edit_keywords = ["change", "modify", "edit", "update", "make it", "convert to"] - analysis_keywords = ["analyze", "explain", "what does", "tell me about", "insights", "trends"] - - has_data = self.has_data_context() - - # If we have data and query suggests chart/analysis work - if has_data and any(keyword in query_lower for keyword in chart_keywords + edit_keywords + analysis_keywords): - return True - - # If query explicitly asks for new data - new_data_keywords = ["get", "find", "show me", "list", "select", "data"] - specific_requests = ["orders", "customers", "products", "sales"] - - if any(keyword in query_lower for keyword in new_data_keywords + specific_requests): - return False - - return has_data # Default to using existing data if available \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/langchain_orchestrator_v2.py b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/langchain_orchestrator_v2.py deleted file mode 100644 index 771c2b510..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/langchain_orchestrator_v2.py +++ /dev/null @@ -1,443 +0,0 @@ -""" -LangChain orchestrator using RunnableSequence for SQL Graph Dashboard -Router → branch(DATA_QUERY→OCI, CHART_EDIT→viz_edit, INSIGHT_QA→insight) -""" - -from langchain_core.runnables import Runnable, RunnableLambda, RunnableBranch -from langchain_core.runnables.utils import Input, Output -from typing import Dict, Any, List, Optional -import base64 -import json - -from .oci_runnables import OciSqlAgentRunnable -from .oci_direct_runnables import RouterRunnable, VizGeneratorRunnable, InsightQARunnable -from .conversation_manager import ConversationManager -from tools.genai_chart_generator import GenAIChartGenerator - - -class ChartEditRunnable(Runnable): - """ - Runnable for editing existing chart configurations - """ - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Modify existing chart based on user request - """ - current_config = input_data.get("current_chart_config", {}) - question = input_data.get("question", "") - data = input_data.get("data", []) - - # Simple chart type modifications - if "pie" in question.lower(): - current_config["chart_type"] = "pie" - elif "bar" in question.lower(): - current_config["chart_type"] = "bar" - elif "line" in question.lower(): - current_config["chart_type"] = "line" - elif "scatter" in question.lower(): - current_config["chart_type"] = "scatter" - - # Sorting modifications - if "sort" in question.lower(): - if "desc" in question.lower() or "highest" in question.lower(): - current_config["sort_direction"] = "desc" - else: - current_config["sort_direction"] = "asc" - - return { - "success": True, - "config": current_config, - "data": data, - "method": "chart_edit", - "response_type": "visualization" - } - - -class InsightQARunnable(Runnable): - """ - Runnable for generating insights about current data - """ - - def __init__(self): - try: - from langchain_community.chat_models.oci_generative_ai import ChatOCIGenAI - from langchain_core.messages import HumanMessage - from utils import config - - self.genai_client = ChatOCIGenAI( - model_id=config.MODEL_ID, - service_endpoint=config.SERVICE_ENDPOINT, - compartment_id=config.COMPARTMENT_ID, - model_kwargs={ - "temperature": 0.7, - "top_p": 0.9, - "max_tokens": 500 - } - ) - self.oci_available = True - print(" Insight QA Runnable initialized") - except Exception as e: - print(f"⚠️ Insight QA fallback mode: {e}") - self.genai_client = None - self.oci_available = False - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Generate insights about the current data - """ - data = input_data.get("data", []) - question = input_data.get("question", "") - - if not data: - return { - "success": False, - "error": "No data available for analysis", - "response_type": "text_response" - } - - # Create analysis prompt - data_summary = { - "total_rows": len(data), - "columns": list(data[0].keys()) if data else [], - "sample_data": data[:3] - } - - prompt = f"""Analyze this data and answer the user's question with insights. - -User Question: "{question}" - -Data Summary: -- Total rows: {data_summary['total_rows']} -- Columns: {data_summary['columns']} -- Sample data: {data_summary['sample_data']} - -Provide a concise analysis with specific insights, trends, or patterns you observe in the data. -""" - - if self.oci_available: - try: - from langchain_core.messages import HumanMessage - messages = [HumanMessage(content=prompt)] - response = self.genai_client.invoke(messages) - - # Extract content - if hasattr(response, 'content'): - insight_text = response.content - else: - insight_text = str(response) - - return { - "success": True, - "text_response": insight_text, - "data": data, - "response_type": "text_response", - "method": "genai_analysis" - } - - except Exception as e: - print(f" Insight generation error: {e}") - return self._fallback_insight(data, question) - else: - return self._fallback_insight(data, question) - - def _fallback_insight(self, data: List[Dict], question: str) -> Dict[str, Any]: - """Generate simple fallback insights""" - if not data: - return { - "success": True, - "text_response": "No data available for analysis.", - "response_type": "text_response" - } - - insights = [ - f"Dataset contains {len(data)} records", - f"Available fields: {', '.join(data[0].keys()) if data else 'None'}" - ] - - # Simple numeric analysis - numeric_fields = [] - for field in data[0].keys() if data else []: - try: - values = [float(row.get(field, 0)) for row in data[:10]] - if values: - avg_val = sum(values) / len(values) - insights.append(f"{field} average: {avg_val:.2f}") - numeric_fields.append(field) - except (ValueError, TypeError): - pass - - if not numeric_fields: - insights.append("No numeric fields found for statistical analysis.") - - return { - "success": True, - "text_response": "\n".join(insights), - "data": data, - "response_type": "text_response", - "method": "fallback_analysis" - } - - -class LangChainOrchestratorV2: - """ - Clean LangChain orchestrator using RunnableSequence architecture - """ - - def __init__(self): - print("🚀 Initializing LangChain Orchestrator V2...") - - # Initialize all runnables - self.router = RouterRunnable() - self.sql_agent = OciSqlAgentRunnable() - self.viz_generator = VizGeneratorRunnable() - self.chart_editor = ChartEditRunnable() - self.insight_qa = InsightQARunnable() # Now using direct OCI calls - self.chart_generator = GenAIChartGenerator() - - # Conversation history manager - self.conversation = ConversationManager() - - # Track current state (for backward compatibility) - self.current_data = None - self.current_chart_config = None - - print(" LangChain Orchestrator V2 initialized") - - def process_natural_language_query(self, user_question: str) -> Dict[str, Any]: - """ - Main entry point - processes user query through the complete pipeline - """ - try: - print(f" Processing query: {user_question}") - - # Step 1: Route the query with conversation context - route_input = { - "question": user_question, - "context": { - "has_data": self.conversation.has_data_context(), - "has_chart": self.conversation.has_chart_context(), - "conversation_history": self.conversation.get_context_for_prompt(3), - "data_summary": self.conversation.get_data_summary(), - "chart_summary": self.conversation.get_chart_summary() - } - } - - routing_result = self.router.invoke(route_input) - route = routing_result.get("route", "DATA_QUERY") - print(f" Router decision: {route} (confidence: {routing_result.get('confidence', 0.5)})") - print(f" Reasoning: {routing_result.get('reasoning', 'No reasoning')}") - - # Step 2: Branch based on route - if route == "DATA_QUERY": - result = self._handle_data_query(user_question) - elif route == "CHART_EDIT": - result = self._handle_chart_edit(user_question) - elif route == "INSIGHT_QA": - result = self._handle_insight_qa(user_question) - else: - # Fallback to data query - result = self._handle_data_query(user_question) - - # Step 3: Record this conversation turn - self.conversation.add_turn(user_question, route, result) - - # Update backward compatibility state - if result.get('data'): - self.current_data = result['data'] - if result.get('chart_config'): - self.current_chart_config = result['chart_config'] - - return result - - except Exception as e: - print(f" Orchestrator error: {e}") - import traceback - traceback.print_exc() - return { - "success": False, - "error": str(e), - "response_type": "error" - } - - def _handle_data_query(self, user_question: str) -> Dict[str, Any]: - """ - Handle DATA_QUERY route: SQL Agent → Viz Generator → Chart Generator - """ - try: - # Step 1: Get data from OCI SQL Agent - sql_input = {"question": user_question} - sql_result = self.sql_agent.invoke(sql_input) - - if not sql_result.get("success", False): - return { - "success": False, - "error": sql_result.get("error", "SQL query failed"), - "response_type": "error" - } - - data = sql_result.get("data", []) - if not data: - return { - "success": True, - "query": user_question, - "agent_response": sql_result.get("agent_response", "No data found"), - "response_type": "text_response", - "text_response": sql_result.get("agent_response", "No data found"), - "data": [] - } - - # Update current state (conversation manager handles this) - - # DATA_QUERY only returns data - no automatic chart generation - # Charts should only be created when explicitly requested via CHART_EDIT - - # Store data for conversation context - self.current_data = data - - # Add to conversation history - self.conversation.add_turn(user_question, "DATA_QUERY", {"data": data}) - - # Return data without chart - return { - "success": True, - "query": user_question, - "agent_response": sql_result.get("agent_response", ""), - "response_type": "data", - "data": data, - "generated_sql": sql_result.get("generated_sql"), - "additional_info": sql_result.get("additional_info"), - "method": "data_only" - } - - except Exception as e: - print(f" Data query handling error: {e}") - return { - "success": False, - "error": str(e), - "response_type": "error" - } - - def _handle_chart_edit(self, user_question: str) -> Dict[str, Any]: - """ - Handle CHART_EDIT route: modify existing chart - """ - # Always get fresh data for chart requests to ensure we're using the right dataset - print(" Getting fresh data for chart...") - sql_input = {"question": user_question} - sql_result = self.sql_agent.invoke(sql_input) - - if not sql_result.get("success", False): - return { - "success": False, - "error": f"Failed to get data for chart: {sql_result.get('error', 'Unknown error')}", - "response_type": "error" - } - - current_data = sql_result.get("data", []) - if not current_data: - return { - "success": False, - "error": "No data available for chart creation", - "response_type": "error" - } - - # Store the new data - self.current_data = current_data - print(f" Retrieved {len(current_data)} rows for chart generation") - - # Get current chart config for potential reuse - current_chart_config = self.conversation.get_current_chart_config() - - # If we have data but no chart config, create a new chart (don't redirect to data query) - - try: - # Generate chart directly using GenAI Chart Generator - chart_result = self.chart_generator.generate_chart( - user_request=user_question, - data=current_data, - chart_params=current_chart_config or {} - ) - - if chart_result.get("success", False): - # Store the chart config for future use - self.current_chart_config = chart_result.get("chart_config", {}) - - # Add to conversation history - self.conversation.add_turn(user_question, "CHART_EDIT", { - "chart_config": chart_result.get("chart_config", {}), - "chart_base64": chart_result.get("chart_base64") - }) - - return { - "success": True, - "query": user_question, - "agent_response": f"Chart created: {user_question}", - "response_type": "visualization", - "data": current_data, - "chart_base64": chart_result.get("chart_base64"), - "chart_config": chart_result.get("chart_config", {}), - "method": f"chart_generated_+_{chart_result.get('method', 'unknown')}" - } - else: - return { - "success": False, - "error": f"Failed to update chart: {chart_result.get('error', 'Unknown error')}", - "response_type": "error" - } - - except Exception as e: - print(f" Chart edit handling error: {e}") - return { - "success": False, - "error": str(e), - "response_type": "error" - } - - def _handle_insight_qa(self, user_question: str) -> Dict[str, Any]: - """ - Handle INSIGHT_QA route: analyze current data - """ - if not self.current_data: - # No data to analyze, redirect to data query - return self._handle_data_query(user_question) - - try: - insight_input = { - "question": user_question, - "data": self.current_data - } - - insight_result = self.insight_qa.invoke(insight_input) - - return { - "success": insight_result.get("success", True), - "query": user_question, - "agent_response": insight_result.get("text_response", "No insights generated"), - "response_type": "text_response", - "text_response": insight_result.get("text_response", "No insights generated"), - "data": self.current_data, - "method": insight_result.get("method", "insight_analysis") - } - - except Exception as e: - print(f" Insight QA handling error: {e}") - return { - "success": False, - "error": str(e), - "response_type": "error" - } - - def get_current_data(self) -> Optional[List[Dict]]: - """Get current data for transparency""" - return self.current_data - - def get_current_chart_config(self) -> Optional[Dict]: - """Get current chart config for transparency""" - return self.current_chart_config - - def clear_context(self): - """Clear current context""" - self.current_data = None - self.current_chart_config = None - print(" Context cleared") \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/oci_direct_runnables.py b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/oci_direct_runnables.py deleted file mode 100644 index aefda1ecf..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/oci_direct_runnables.py +++ /dev/null @@ -1,412 +0,0 @@ -""" -LangChain Runnables using direct OCI SDK calls for GenAI models -Pure OCI SDK wrapped as LangChain Runnables - no langchain-community dependencies -""" - -from langchain_core.runnables import Runnable -from typing import Dict, Any, List -import oci -import json -from utils import config - - -class OciGenAIRunnable(Runnable): - """ - Direct OCI GenAI model calls wrapped as LangChain Runnable - """ - - def __init__(self, purpose: str = "general"): - self.purpose = purpose - try: - # Initialize OCI GenAI client with correct endpoint - oci_config = oci.config.from_file() - # Override endpoint to match the model's region - oci_config['region'] = 'eu-frankfurt-1' - self.genai_client = oci.generative_ai_inference.GenerativeAiInferenceClient(oci_config) - - # Set correct service endpoint - self.genai_client.base_client.endpoint = config.SERVICE_ENDPOINT - - self.model_id = config.MODEL_ID - self.service_endpoint = config.SERVICE_ENDPOINT - self.compartment_id = config.COMPARTMENT_ID - self.oci_available = True - print(f"OCI GenAI Direct Runnable ({purpose}) initialized with endpoint: {config.SERVICE_ENDPOINT}") - except Exception as e: - print(f"OCI GenAI Direct Runnable ({purpose}) failed: {e}") - self.genai_client = None - self.oci_available = False - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Call OCI GenAI model directly - """ - prompt = input_data.get("prompt", "") - max_tokens = input_data.get("max_tokens", 500) - temperature = input_data.get("temperature", 0.7) - - if not self.oci_available: - return { - "success": False, - "error": "OCI GenAI not available", - "response": "", - "method": "error" - } - - try: - # Create chat request using Oracle demo format for OpenAI GPT OSS 120B - content = oci.generative_ai_inference.models.TextContent() - content.text = prompt - - message = oci.generative_ai_inference.models.Message() - message.role = "USER" - message.content = [content] - - chat_request = oci.generative_ai_inference.models.GenericChatRequest() - chat_request.api_format = oci.generative_ai_inference.models.BaseChatRequest.API_FORMAT_GENERIC - chat_request.messages = [message] - chat_request.max_tokens = max_tokens - chat_request.temperature = temperature - chat_request.frequency_penalty = 0 - chat_request.presence_penalty = 0 - chat_request.top_p = 1 - chat_request.top_k = 0 - - chat_detail = oci.generative_ai_inference.models.ChatDetails() - chat_detail.serving_mode = oci.generative_ai_inference.models.OnDemandServingMode(model_id=self.model_id) - chat_detail.chat_request = chat_request - chat_detail.compartment_id = self.compartment_id - - # Call OCI GenAI - response = self.genai_client.chat(chat_detail) - - # Extract response text - response_text = "" - if hasattr(response.data, 'chat_response') and response.data.chat_response: - if hasattr(response.data.chat_response, 'choices') and response.data.chat_response.choices: - choice = response.data.chat_response.choices[0] - if hasattr(choice, 'message') and choice.message: - if hasattr(choice.message, 'content') and choice.message.content: - for content in choice.message.content: - if hasattr(content, 'text'): - response_text += content.text - - return { - "success": True, - "response": response_text.strip(), - "method": "oci_direct", - "model_id": self.model_id - } - - except Exception as e: - error_msg = str(e) - print(f"OCI GenAI Direct call failed ({self.purpose}): {error_msg}") - - # Check for specific error types - if "does not support" in error_msg: - return { - "success": False, - "error": f"Model {self.model_id} API format incompatible", - "response": "", - "method": "model_error" - } - - return { - "success": False, - "error": error_msg, - "response": "", - "method": "call_error" - } - - -class RouterRunnable(Runnable): - """ - Intelligent routing using direct OCI GenAI calls - """ - - def __init__(self): - self.genai_runnable = OciGenAIRunnable("router") - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Route user query and return routing decision - """ - user_question = input_data.get("question", "") - context = input_data.get("context", {}) - - # Create routing prompt - prompt = f"""You are an intelligent router for a data dashboard. Analyze the user query and decide which tool to use. - -Tools Available: -1. DATA_QUERY: For getting NEW data from database (show orders, get customers, list products, etc.) -2. CHART_EDIT: For creating ANY charts or visualizations (make chart, graph, pie chart, bar chart, etc.) - Will automatically get data if needed -3. INSIGHT_QA: For analyzing current data (trends, patterns, outliers) - -IMPORTANT: If user asks for ANY chart/graph/visualization, always choose CHART_EDIT regardless of whether data exists or not. - -Context: -- Has existing data: {context.get('has_data', False)} -- Has existing chart: {context.get('has_chart', False)} - -User Query: "{user_question}" - -Respond with ONLY a JSON object: -{{"route": "DATA_QUERY|CHART_EDIT|INSIGHT_QA", "reasoning": "Brief explanation", "confidence": 0.0-1.0}}""" - - if not self.genai_runnable.oci_available: - return self._fallback_route(user_question) - - # Call OCI GenAI - genai_input = { - "prompt": prompt, - "max_tokens": 200, - "temperature": 0.3 - } - - result = self.genai_runnable.invoke(genai_input) - - if result.get("success"): - try: - # Parse JSON response - route_data = json.loads(result["response"]) - return { - "route": route_data.get("route", "DATA_QUERY"), - "reasoning": route_data.get("reasoning", "GenAI routing"), - "confidence": route_data.get("confidence", 0.9), - "method": "oci_genai" - } - except json.JSONDecodeError: - print(f"Failed to parse GenAI response: {result['response']}") - return self._fallback_route(user_question) - else: - print(f"GenAI routing failed: {result.get('error')}") - return self._fallback_route(user_question) - - def _fallback_route(self, user_question: str) -> Dict[str, Any]: - """Simple rule-based fallback routing""" - user_lower = user_question.lower() - - if any(word in user_lower for word in ["show", "get", "find", "list", "data"]): - return { - "route": "DATA_QUERY", - "reasoning": "Fallback: Detected data request", - "confidence": 0.5, - "method": "fallback" - } - elif any(word in user_lower for word in ["chart", "pie", "bar", "line", "graph"]): - return { - "route": "CHART_EDIT", - "reasoning": "Fallback: Detected chart modification", - "confidence": 0.5, - "method": "fallback" - } - else: - return { - "route": "INSIGHT_QA", - "reasoning": "Fallback: Default to analysis", - "confidence": 0.3, - "method": "fallback" - } - - -class VizGeneratorRunnable(Runnable): - """ - Generate visualization configs using direct OCI GenAI calls - """ - - def __init__(self): - self.genai_runnable = OciGenAIRunnable("viz_generator") - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Generate chart config from data and user question - """ - data = input_data.get("data", []) - question = input_data.get("question", "") - - if not data: - return { - "success": False, - "error": "No data provided for visualization" - } - - # Analyze data structure - sample_row = data[0] if data else {} - columns = list(sample_row.keys()) if sample_row else [] - - # Generate chart config prompt - prompt = f"""Generate a chart configuration for this data visualization request. - -User Question: "{question}" -Data Columns: {columns} -Data Sample (first 2 rows): {data[:2]} -Total Rows: {len(data)} - -Respond with ONLY a JSON object: -{{"chart_type": "bar|line|pie|scatter", "x_axis": "column_name", "y_axis": "column_name", "title": "Chart Title", "caption": "Brief insight"}}""" - - if not self.genai_runnable.oci_available: - return self._fallback_config(data, question) - - # Call OCI GenAI - genai_input = { - "prompt": prompt, - "max_tokens": 300, - "temperature": 0.3 - } - - result = self.genai_runnable.invoke(genai_input) - - if result.get("success"): - try: - # Parse JSON response - config_data = json.loads(result["response"]) - return { - "success": True, - "config": config_data, - "method": "oci_genai" - } - except json.JSONDecodeError: - print(f"Failed to parse viz config: {result['response']}") - return self._fallback_config(data, question) - else: - print(f"Viz generation failed: {result.get('error')}") - return self._fallback_config(data, question) - - def _fallback_config(self, data: List[Dict], question: str) -> Dict[str, Any]: - """Generate simple fallback chart config""" - if not data: - return {"success": False, "error": "No data"} - - sample_row = data[0] - columns = list(sample_row.keys()) - - # Find numeric columns - numeric_cols = [] - for col in columns: - try: - float(str(sample_row[col])) - numeric_cols.append(col) - except (ValueError, TypeError): - pass - - # Simple config generation - if len(columns) >= 2: - x_axis = columns[0] - y_axis = numeric_cols[0] if numeric_cols else columns[1] - chart_type = "bar" - else: - x_axis = columns[0] - y_axis = columns[0] - chart_type = "bar" - - return { - "success": True, - "config": { - "chart_type": chart_type, - "x_axis": x_axis, - "y_axis": y_axis, - "title": f"Chart for: {question}", - "caption": "Fallback visualization configuration" - }, - "method": "fallback" - } - - -class InsightQARunnable(Runnable): - """ - Generate insights using direct OCI GenAI calls - """ - - def __init__(self): - self.genai_runnable = OciGenAIRunnable("insight_qa") - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Generate insights about the current data - """ - data = input_data.get("data", []) - question = input_data.get("question", "") - - if not data: - return { - "success": False, - "error": "No data available for analysis", - "response_type": "text_response" - } - - # Create analysis prompt - data_summary = { - "total_rows": len(data), - "columns": list(data[0].keys()) if data else [], - "sample_data": data[:3] - } - - prompt = f"""Analyze this data and answer the user's question with insights. - -User Question: "{question}" - -Data Summary: -- Total rows: {data_summary['total_rows']} -- Columns: {data_summary['columns']} -- Sample data: {data_summary['sample_data']} - -Provide a concise analysis with specific insights, trends, or patterns you observe in the data. -""" - - if not self.genai_runnable.oci_available: - return self._fallback_insight(data, question) - - # Call OCI GenAI - genai_input = { - "prompt": prompt, - "max_tokens": 400, - "temperature": 0.7 - } - - result = self.genai_runnable.invoke(genai_input) - - if result.get("success"): - return { - "success": True, - "text_response": result["response"], - "data": data, - "response_type": "text_response", - "method": "oci_genai" - } - else: - print(f"⚠️ Insight generation failed: {result.get('error')}") - return self._fallback_insight(data, question) - - def _fallback_insight(self, data: List[Dict], question: str) -> Dict[str, Any]: - """Generate simple fallback insights""" - if not data: - return { - "success": True, - "text_response": "No data available for analysis.", - "response_type": "text_response", - "method": "fallback" - } - - insights = [ - f"Dataset contains {len(data)} records", - f"Available fields: {', '.join(data[0].keys()) if data else 'None'}" - ] - - # Simple numeric analysis - for field in data[0].keys() if data else []: - try: - values = [float(row.get(field, 0)) for row in data[:10]] - if values: - avg_val = sum(values) / len(values) - insights.append(f"{field} average: {avg_val:.2f}") - except (ValueError, TypeError): - pass - - return { - "success": True, - "text_response": "\n".join(insights), - "data": data, - "response_type": "text_response", - "method": "fallback" - } \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/oci_runnables.py b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/oci_runnables.py deleted file mode 100644 index 212854ad1..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/orchestration/oci_runnables.py +++ /dev/null @@ -1,374 +0,0 @@ -""" -LangChain Runnables that wrap OCI SDK calls for clean integration -""" - -from langchain_core.runnables import Runnable -try: - from langchain_oci.chat_models import ChatOCIGenAI -except ImportError: - try: - from langchain_community.chat_models.oci_generative_ai import ChatOCIGenAI - except ImportError: - print("⚠️ Neither langchain-oci nor langchain-community ChatOCIGenAI available") - ChatOCIGenAI = None -from langchain_core.messages import HumanMessage -from typing import Dict, Any, List -import oci -from utils import config -import json - -class OciSqlAgentRunnable(Runnable): - """ - LangChain Runnable that wraps OCI Agent Runtime SDK to extract tool_outputs reliably - """ - - def __init__(self): - # Initialize OCI Agent Runtime client - try: - oci_config = oci.config.from_file() - # Override region to match the agent endpoint - oci_config['region'] = 'eu-frankfurt-1' - self.client = oci.generative_ai_agent_runtime.GenerativeAiAgentRuntimeClient(oci_config) - self.agent_endpoint_id = config.AGENT_ENDPOINT_ID - print("OCI SQL Agent Runnable initialized with eu-frankfurt-1") - except Exception as e: - print(f"Failed to initialize OCI Agent Runtime: {e}") - self.client = None - self.agent_endpoint_id = None - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Call OCI Agent and extract tool_outputs[0].result for reliable data - """ - user_question = input_data.get("question", "") if isinstance(input_data, dict) else str(input_data) - - if not self.client or not self.agent_endpoint_id: - return { - "success": False, - "error": "OCI Agent Runtime not available", - "data": [], - "agent_response": "Agent not initialized" - } - - try: - print(f"OCI SQL Agent: Executing query: {user_question}") - - # Step 1: Create a session first (required for sessionId) - create_session_response = self.client.create_session( - create_session_details=oci.generative_ai_agent_runtime.models.CreateSessionDetails( - display_name="SQL Query Session", - description="Session for SQL query execution" - ), - agent_endpoint_id=self.agent_endpoint_id - ) - session_id = create_session_response.data.id - print(f"Created session: {session_id}") - - # Step 2: Create chat request with required sessionId - chat_request = oci.generative_ai_agent_runtime.models.ChatDetails( - user_message=user_question, - session_id=session_id, - should_stream=False - ) - - # Step 3: Call OCI Agent - response = self.client.chat( - agent_endpoint_id=self.agent_endpoint_id, - chat_details=chat_request - ) - - # Extract message content - message_content = "" - if hasattr(response.data, 'message') and response.data.message: - if hasattr(response.data.message, 'content') and response.data.message.content: - if hasattr(response.data.message.content, 'text'): - message_content = response.data.message.content.text or "" - - # Extract tool outputs (where SQL data lives) - tool_outputs = getattr(response.data, 'tool_outputs', []) or [] - data = [] - generated_sql = None - additional_info = None - - if tool_outputs and len(tool_outputs) > 0: - result = tool_outputs[0].result if hasattr(tool_outputs[0], 'result') else None - if result: - try: - # Parse JSON data from tool output - if isinstance(result, str): - parsed_result = json.loads(result) - else: - parsed_result = result - - if isinstance(parsed_result, list): - data = parsed_result - elif isinstance(parsed_result, dict): - data = parsed_result.get('data', []) - generated_sql = parsed_result.get('generated_sql') - additional_info = parsed_result.get('additional_info') - except json.JSONDecodeError: - # If not JSON, treat as raw data - data = [{"result": result}] - - return { - "success": True, - "agent_response": message_content.strip(), - "data": data, - "generated_sql": generated_sql, - "additional_info": additional_info, - "tool_outputs": tool_outputs # Pass through for transparency - } - - except Exception as e: - print(f"OCI SQL Agent error: {e}") - return { - "success": False, - "error": str(e), - "data": [], - "agent_response": f"Error calling SQL Agent: {str(e)}" - } - - -class RouterRunnable(Runnable): - """ - LangChain Runnable for intelligent routing using ChatOCIGenAI - """ - - def __init__(self): - self.genai_client = None - self.oci_available = False - - if ChatOCIGenAI is None: - print("ChatOCIGenAI not available - Router using fallback") - return - - try: - self.genai_client = ChatOCIGenAI( - model_id=config.MODEL_ID, - service_endpoint=config.SERVICE_ENDPOINT, - compartment_id=config.COMPARTMENT_ID, - model_kwargs={ - "temperature": config.TEMPERATURE, - "top_p": config.TOP_P, - "max_tokens": config.MAX_TOKENS - } - ) - self.oci_available = True - print("Router Runnable with ChatOCIGenAI initialized") - except Exception as e: - print(f"Router Runnable fallback mode: {e}") - self.genai_client = None - self.oci_available = False - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Route user query and return routing decision - """ - user_question = input_data.get("question", "") if isinstance(input_data, dict) else str(input_data) - context = input_data.get("context", {}) if isinstance(input_data, dict) else {} - - # Routing prompt - prompt = f"""You are an intelligent router for a data dashboard. Analyze the user query and decide which tool to use. - -Tools Available: -1. DATA_QUERY: For getting new data from database (show orders, get customers, etc.) -2. CHART_EDIT: For modifying existing charts (make it pie chart, sort by amount, etc.) -3. INSIGHT_QA: For analyzing current data (trends, patterns, outliers) - -User Query: "{user_question}" - -Respond with ONLY a JSON object: -{{ - "route": "DATA_QUERY|CHART_EDIT|INSIGHT_QA", - "reasoning": "Brief explanation", - "confidence": 0.0-1.0, - "params": {{}} -}}""" - - if self.oci_available: - try: - messages = [HumanMessage(content=prompt)] - response = self.genai_client.invoke(messages) - - # Extract content from response - if hasattr(response, 'content'): - content = response.content - else: - content = str(response) - - # Parse JSON response - try: - import json - route_data = json.loads(content) - return { - "route": route_data.get("route", "DATA_QUERY"), - "reasoning": route_data.get("reasoning", "GenAI routing"), - "confidence": route_data.get("confidence", 0.9), - "params": route_data.get("params", {}) - } - except json.JSONDecodeError: - print(f"Failed to parse GenAI response: {content}") - return self._fallback_route(user_question) - - except Exception as e: - print(f"GenAI routing error: {e}") - return self._fallback_route(user_question) - else: - return self._fallback_route(user_question) - - def _fallback_route(self, user_question: str) -> Dict[str, Any]: - """Simple rule-based fallback routing""" - user_lower = user_question.lower() - - if any(word in user_lower for word in ["show", "get", "find", "list", "data"]): - return { - "route": "DATA_QUERY", - "reasoning": "Fallback: Detected data request", - "confidence": 0.5, - "params": {} - } - elif any(word in user_lower for word in ["chart", "pie", "bar", "line", "graph"]): - return { - "route": "CHART_EDIT", - "reasoning": "Fallback: Detected chart modification", - "confidence": 0.5, - "params": {} - } - else: - return { - "route": "INSIGHT_QA", - "reasoning": "Fallback: Default to analysis", - "confidence": 0.3, - "params": {} - } - - -class VizGeneratorRunnable(Runnable): - """ - LangChain Runnable for generating visualization configs from data - """ - - def __init__(self): - try: - self.genai_client = ChatOCIGenAI( - model_id=config.MODEL_ID, - service_endpoint=config.SERVICE_ENDPOINT, - compartment_id=config.COMPARTMENT_ID, - model_kwargs={ - "temperature": 0.3, - "top_p": 0.9, - "max_tokens": 1000 - } - ) - self.oci_available = True - print("Viz Generator Runnable initialized") - except Exception as e: - print(f"Viz Generator fallback mode: {e}") - self.genai_client = None - self.oci_available = False - - def invoke(self, input_data: Dict[str, Any]) -> Dict[str, Any]: - """ - Generate chart config from data and user question - """ - data = input_data.get("data", []) - question = input_data.get("question", "") - suggested_type = input_data.get("chart_type", "auto") - - if not data: - return { - "success": False, - "error": "No data provided for visualization" - } - - # Analyze data structure - sample_row = data[0] if data else {} - columns = list(sample_row.keys()) if sample_row else [] - - # Generate chart config prompt - prompt = f"""Generate a chart configuration for this data visualization request. - -User Question: "{question}" -Suggested Chart Type: {suggested_type} -Data Columns: {columns} -Data Sample (first 3 rows): {data[:3]} -Total Rows: {len(data)} - -Respond with ONLY a JSON object: -{{ - "chart_type": "bar|line|pie|scatter", - "x_axis": "column_name", - "y_axis": "column_name", - "title": "Chart Title", - "caption": "Brief insight about the data", - "color_field": "optional_column_for_colors" -}}""" - - if self.oci_available: - try: - messages = [HumanMessage(content=prompt)] - response = self.genai_client.invoke(messages) - - # Extract content - if hasattr(response, 'content'): - content = response.content - else: - content = str(response) - - # Parse JSON response - try: - import json - config_data = json.loads(content) - return { - "success": True, - "config": config_data, - "method": "genai_generated" - } - except json.JSONDecodeError: - print(f"Failed to parse viz config: {content}") - return self._fallback_config(data, question) - - except Exception as e: - print(f"Viz generation error: {e}") - return self._fallback_config(data, question) - else: - return self._fallback_config(data, question) - - def _fallback_config(self, data: List[Dict], question: str) -> Dict[str, Any]: - """Generate simple fallback chart config""" - if not data: - return {"success": False, "error": "No data"} - - sample_row = data[0] - columns = list(sample_row.keys()) - - # Find numeric columns - numeric_cols = [] - for col in columns: - try: - float(str(sample_row[col])) - numeric_cols.append(col) - except (ValueError, TypeError): - pass - - # Simple config generation - if len(columns) >= 2: - x_axis = columns[0] - y_axis = numeric_cols[0] if numeric_cols else columns[1] - chart_type = "bar" - else: - x_axis = columns[0] - y_axis = columns[0] - chart_type = "bar" - - return { - "success": True, - "config": { - "chart_type": chart_type, - "x_axis": x_axis, - "y_axis": y_axis, - "title": f"Chart for: {question}", - "caption": "Fallback visualization configuration" - }, - "method": "fallback" - } \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/requirements.txt b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/requirements.txt deleted file mode 100644 index d9e66384a..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/requirements.txt +++ /dev/null @@ -1,22 +0,0 @@ -# Core dependencies -fastapi==0.104.1 -uvicorn==0.24.0 -pydantic==2.5.0 -python-multipart==0.0.6 - -# OCI SDK -oci==2.119.1 - -# LangChain -langchain==0.1.0 -langchain-core==0.1.10 -langchain-community==0.0.13 - -# Data visualization -matplotlib==3.8.2 -seaborn==0.13.0 -pandas==2.1.4 -numpy==1.26.2 - -# Utilities -python-dotenv==1.0.0 diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/tools/genai_chart_generator.py b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/tools/genai_chart_generator.py deleted file mode 100644 index 1b42fe021..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/tools/genai_chart_generator.py +++ /dev/null @@ -1,341 +0,0 @@ -""" -GenAI-Powered Chart Generator -Uses OCI GenAI to generate custom visualization code based on data and user requirements -""" - -import json -import oci -import matplotlib.pyplot as plt -import seaborn as sns -import pandas as pd -import numpy as np -import io -import base64 -from typing import Dict, Any, List, Optional -from utils import config -import signal - - -class GenAIChartGenerator: - """ - Generate custom charts using OCI GenAI to create Python visualization code - """ - - CHART_GENERATION_PROMPT = """You are an expert data visualization developer. Generate Python code to create beautiful, insightful charts. - -User Request: "{user_request}" - -Available Data (first 3 rows shown): -{data_preview} - -Data Summary: -- Total rows: {total_rows} -- Columns: {columns} -- Numeric columns: {numeric_columns} - -Requirements: -1. Create a matplotlib/seaborn visualization -2. Use the provided data variable called 'df' (pandas DataFrame) -3. Make the chart beautiful with proper titles, labels, colors -4. Return the chart as base64 image -5. Handle any data preprocessing needed -6. Choose the most appropriate chart type for the data and request - -Generate ONLY Python code in this format: -```python -import matplotlib.pyplot as plt -import seaborn as sns -import pandas as pd -import numpy as np -import io -import base64 - -# Set style for beautiful charts -plt.style.use('seaborn-v0_8') -sns.set_palette("husl") - -# Your visualization code here -# Use df as the DataFrame variable -# Example: -fig, ax = plt.subplots(figsize=(12, 8)) - -# Create your chart (customize based on user request and data) -# ... your chart code ... - -# Finalize chart -plt.title("Your Chart Title", fontsize=16, fontweight='bold') -plt.tight_layout() - -# Convert to base64 -img_buffer = io.BytesIO() -plt.savefig(img_buffer, format='png', dpi=150, bbox_inches='tight', - facecolor='white', edgecolor='none') -img_buffer.seek(0) -img_base64 = base64.b64encode(img_buffer.getvalue()).decode('utf-8') -plt.close() - -# Return the base64 string -chart_base64 = img_base64 -``` - -Generate the complete Python code that will create an appropriate visualization.""" - - def __init__(self): - # Initialize direct OCI GenAI client using chat API - try: - oci_config = oci.config.from_file() - oci_config['region'] = 'eu-frankfurt-1' - self.genai_client = oci.generative_ai_inference.GenerativeAiInferenceClient(oci_config) - self.genai_client.base_client.endpoint = config.SERVICE_ENDPOINT - - self.model_id = config.MODEL_ID - self.compartment_id = config.COMPARTMENT_ID - self.oci_available = True - print("LangChain OCI GenAI Chart Generator initialized successfully") - except Exception as e: - print(f"LangChain OCI GenAI Chart Generator not available: {e}") - self.genai_client = None - self.oci_available = False - - def generate_chart(self, user_request: str, data: List[Dict], chart_params: Dict[str, Any] = None) -> Dict[str, Any]: - """ - Generate custom chart using GenAI-generated code - """ - try: - print(f"GenAI Chart Generator: Creating chart for: {user_request}") - - if not data: - return { - "success": False, - "error": "No data provided for chart generation" - } - - # Prepare data summary for GenAI - df = pd.DataFrame(data) - data_preview = df.head(3).to_dict('records') - columns = list(df.columns) - numeric_columns = list(df.select_dtypes(include=[np.number]).columns) - - # Create GenAI prompt - prompt = self.CHART_GENERATION_PROMPT.format( - user_request=user_request, - data_preview=json.dumps(data_preview, indent=2, default=str), - total_rows=len(df), - columns=columns, - numeric_columns=numeric_columns - ) - - # Call GenAI to generate code - genai_response = self._call_genai(prompt) - print(f"GenAI Response length: {len(genai_response)} chars") - print(f"GenAI Response preview: {genai_response[:200]}...") - - # Extract Python code from response - python_code = self._extract_code(genai_response) - print(f" Extracted code length: {len(python_code) if python_code else 0} chars") - - if not python_code: - print(" No Python code extracted, using fallback") - return self._fallback_chart(df, user_request) - - print(f" Code preview: {python_code[:100]}...") - - # Execute the generated code - print(" Executing generated Python code...") - chart_result = self._execute_chart_code(python_code, df) - print(f" Chart execution result: {chart_result.get('success', False)}") - - if chart_result["success"]: - return { - "success": True, - "chart_base64": chart_result["chart_base64"], - "generated_code": python_code, - "method": "genai_generated", - "chart_config": { - "title": f"GenAI Chart: {user_request}", - "type": "custom", - "description": "Custom chart generated using GenAI" - } - } - else: - print(f" Generated code failed, using fallback: {chart_result['error']}") - return self._fallback_chart(df, user_request) - - except Exception as e: - print(f" GenAI Chart Generation error: {e}") - return self._fallback_chart(pd.DataFrame(data) if data else pd.DataFrame(), user_request) - - def _call_genai(self, prompt: str) -> str: - """ - Call OCI GenAI model to generate chart code using direct Chat API - """ - try: - print(" Creating chat request...") - # Create chat request using Oracle demo format for OpenAI GPT OSS 120B - content = oci.generative_ai_inference.models.TextContent() - content.text = prompt - - message = oci.generative_ai_inference.models.Message() - message.role = "USER" - message.content = [content] - - chat_request = oci.generative_ai_inference.models.GenericChatRequest() - chat_request.api_format = oci.generative_ai_inference.models.BaseChatRequest.API_FORMAT_GENERIC - chat_request.messages = [message] - chat_request.max_tokens = 2000 - chat_request.temperature = 0.3 - chat_request.frequency_penalty = 0 - chat_request.presence_penalty = 0 - chat_request.top_p = 1 - chat_request.top_k = 0 - - chat_detail = oci.generative_ai_inference.models.ChatDetails() - chat_detail.serving_mode = oci.generative_ai_inference.models.OnDemandServingMode(model_id=self.model_id) - chat_detail.chat_request = chat_request - chat_detail.compartment_id = self.compartment_id - - # Call OCI GenAI - print(" Calling OCI GenAI Chat API...") - response = self.genai_client.chat(chat_detail) - print(" Got response from OCI GenAI") - - # Extract response text - response_text = "" - if hasattr(response.data, 'chat_response') and response.data.chat_response: - if hasattr(response.data.chat_response, 'choices') and response.data.chat_response.choices: - choice = response.data.chat_response.choices[0] - if hasattr(choice, 'message') and choice.message: - if hasattr(choice.message, 'content') and choice.message.content: - for content in choice.message.content: - if hasattr(content, 'text'): - response_text += content.text - - return response_text.strip() - - except Exception as e: - print(f" LangChain GenAI API call failed: {e}") - return f"Error: {str(e)}" - - def _extract_code(self, genai_response: str) -> Optional[str]: - """ - Extract Python code from GenAI response - """ - try: - # Look for code blocks - if "```python" in genai_response: - start = genai_response.find("```python") + 9 - end = genai_response.find("```", start) - if end != -1: - return genai_response[start:end].strip() - elif "```" in genai_response: - start = genai_response.find("```") + 3 - end = genai_response.find("```", start) - if end != -1: - return genai_response[start:end].strip() - - # If no code blocks, try to find code patterns - lines = genai_response.split('\n') - code_lines = [] - in_code = False - - for line in lines: - if any(keyword in line for keyword in ['import ', 'plt.', 'sns.', 'fig,', 'ax =']): - in_code = True - if in_code: - code_lines.append(line) - - return '\n'.join(code_lines) if code_lines else None - - except Exception as e: - print(f" Code extraction error: {e}") - return None - - def _execute_chart_code(self, python_code: str, df: pd.DataFrame) -> Dict[str, Any]: - """ - Safely execute the generated Python code - """ - try: - # Create a safe execution environment - safe_globals = { - 'plt': plt, - 'sns': sns, - 'pd': pd, - 'np': np, - 'io': io, - 'base64': base64, - 'df': df, - 'chart_base64': None - } - - # Execute the code - exec(python_code, safe_globals) - - # Get the result - chart_base64 = safe_globals.get('chart_base64') - - if chart_base64: - return { - "success": True, - "chart_base64": chart_base64 - } - else: - return { - "success": False, - "error": "No chart_base64 variable found in generated code" - } - - except Exception as e: - return { - "success": False, - "error": f"Code execution error: {str(e)}" - } - - def _fallback_chart(self, df: pd.DataFrame, user_request: str) -> Dict[str, Any]: - """ - Generate a simple fallback chart when GenAI fails - """ - try: - fig, ax = plt.subplots(figsize=(10, 6)) - - # Choose chart based on data - if len(df.columns) >= 2: - numeric_cols = df.select_dtypes(include=[np.number]).columns - if len(numeric_cols) >= 2: - # Scatter plot for numeric data - ax.scatter(df[numeric_cols[0]], df[numeric_cols[1]], alpha=0.7) - ax.set_xlabel(numeric_cols[0]) - ax.set_ylabel(numeric_cols[1]) - elif len(numeric_cols) == 1: - # Bar chart - if len(df) <= 20: - df[numeric_cols[0]].plot(kind='bar', ax=ax) - else: - df[numeric_cols[0]].plot(kind='line', ax=ax) - ax.set_ylabel(numeric_cols[0]) - - plt.title(f"Chart for: {user_request}", fontsize=14) - plt.tight_layout() - - # Convert to base64 - img_buffer = io.BytesIO() - plt.savefig(img_buffer, format='png', dpi=150, bbox_inches='tight') - img_buffer.seek(0) - chart_base64 = base64.b64encode(img_buffer.getvalue()).decode('utf-8') - plt.close() - - return { - "success": True, - "chart_base64": chart_base64, - "method": "fallback", - "chart_config": { - "title": f"Fallback Chart: {user_request}", - "type": "auto", - "description": "Simple fallback visualization" - } - } - - except Exception as e: - return { - "success": False, - "error": f"Fallback chart error: {str(e)}" - } \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/utils/config.py b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/utils/config.py deleted file mode 100644 index 35278f713..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/backend/utils/config.py +++ /dev/null @@ -1,45 +0,0 @@ -MODEL_ID = "ocid1.generativeaimodel.oc1.eu-frankfurt-1.YOUR_MODEL_ID" -SERVICE_ENDPOINT = "https://inference.generativeai.eu-frankfurt-1.oci.oraclecloud.com" -COMPARTMENT_ID = "ocid1.compartment.oc1..YOUR_COMPARTMENT_ID" -AGENT_ENDPOINT_ID = "ocid1.genaiagentendpoint.oc1.eu-frankfurt-1.YOUR_AGENT_ENDPOINT_ID" -SQL_AGENT_ID = "ocid1.genaiagentendpoint.oc1.eu-frankfurt-1.YOUR_AGENT_ENDPOINT_ID" -SQL_AGENT_ENDPOINT = "https://agent-runtime.generativeai.eu-frankfurt-1.oci.oraclecloud.com" - -TEMPERATURE = 0.1 -MAX_TOKENS = 1024 -TOP_P = 0.9 -MAX_ROWS_IN_CHART = 50 -CHART_EXPORT_FORMAT = "json" -DEBUG = False -AUTH = "API_KEY" - -# Database Schema - Customize for your database -DATABASE_SCHEMA = { - "CUSTOMERS": [ - "CUSTOMER_ID", "CUSTOMER_NAME", "EMAIL", "SIGNUP_DATE", "SEGMENT", - "COUNTRY", "LIFETIME_VALUE", "CREATION_DATE", "CREATED_BY", - "LAST_UPDATED_DATE", "LAST_UPDATED_BY" - ], - "PRODUCTS": [ - "PRODUCT_ID", "PRODUCT_NAME", "CATEGORY", "PRICE", "COST", - "STOCK_QUANTITY", "LAUNCH_DATE", "CREATION_DATE", "CREATED_BY", - "LAST_UPDATED_DATE", "LAST_UPDATED_BY" - ], - "ORDERS": [ - "ORDER_ID", "CUSTOMER_ID", "ORDER_DATE", "TOTAL_AMOUNT", "STATUS", - "REGION", "SALES_REP", "CREATION_DATE", "CREATED_BY", - "LAST_UPDATED_DATE", "LAST_UPDATED_BY" - ], - "ORDER_ITEMS": [ - "ORDER_ITEM_ID", "ORDER_ID", "PRODUCT_ID", "QUANTITY", "UNIT_PRICE", - "DISCOUNT_PERCENT", "CREATION_DATE", "CREATED_BY", - "LAST_UPDATED_DATE", "LAST_UPDATED_BY" - ] -} - -ECOMMERCE_CORE_FIELDS = { - "CUSTOMERS": ["CUSTOMER_ID", "CUSTOMER_NAME", "SEGMENT", "COUNTRY", "LIFETIME_VALUE"], - "PRODUCTS": ["PRODUCT_ID", "PRODUCT_NAME", "CATEGORY", "PRICE"], - "ORDERS": ["ORDER_ID", "CUSTOMER_ID", "ORDER_DATE", "TOTAL_AMOUNT", "STATUS", "REGION"], - "ORDER_ITEMS": ["ORDER_ITEM_ID", "ORDER_ID", "PRODUCT_ID", "QUANTITY", "UNIT_PRICE"] -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/customers.csv b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/customers.csv deleted file mode 100644 index c01f396a4..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/customers.csv +++ /dev/null @@ -1,16 +0,0 @@ -CUSTOMER_ID,CUSTOMER_NAME,EMAIL,SIGNUP_DATE,SEGMENT,COUNTRY,LIFETIME_VALUE -1001,Tech Innovators Inc,contact@techinnovators.com,2023-01-15,Enterprise,USA,25000 -1002,Global Retail Corp,orders@globalretail.com,2023-02-20,Enterprise,Canada,18500 -1003,Startup Solutions,hello@startupsol.com,2023-01-30,SMB,UK,8500 -1004,Digital Commerce Co,sales@digitalcom.com,2023-03-10,Enterprise,Australia,22000 -1005,Local Business Hub,info@localbiz.com,2023-02-05,SMB,USA,6200 -1006,European Distributors,contact@eudist.com,2023-04-12,SMB,Germany,7800 -1007,Premium Brands Ltd,premium@brands.com,2023-03-25,Enterprise,Spain,28500 -1008,Creative Studios,studio@creative.com,2023-01-08,SMB,France,9200 -1009,Asia Pacific Trade,trade@apac.com,2023-02-18,Enterprise,Japan,31000 -1010,Market Leaders Inc,leaders@market.com,2023-04-05,Enterprise,Mexico,24800 -1011,Regional Partners,partners@regional.com,2023-05-12,SMB,Brazil,5900 -1012,Innovation Labs,labs@innovation.com,2023-06-08,Enterprise,Singapore,19500 -1013,Growth Ventures,growth@ventures.com,2023-07-15,SMB,India,7100 -1014,Excellence Corp,corp@excellence.com,2023-08-22,Enterprise,South Korea,26800 -1015,Future Tech,future@tech.com,2023-09-10,SMB,Netherlands,8900 \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/order_items.csv b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/order_items.csv deleted file mode 100644 index 933cab359..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/order_items.csv +++ /dev/null @@ -1,36 +0,0 @@ -order_item_id,order_id,product_id,quantity,unit_price,discount_percent -4001,3001,2001,2,2999.99,10 -4002,3001,2009,1,5000.00,0 -4003,3002,2002,2,1899.99,0 -4004,3003,2012,1,1799.99,0 -4005,3004,2004,1,3499.99,5 -4006,3004,2010,1,2500.00,0 -4007,3005,2005,1,1299.99,0 -4008,3005,2006,1,599.99,0 -4009,3006,2007,1,1599.99,0 -4010,3007,2001,3,2999.99,15 -4011,3007,2009,1,5000.00,0 -4012,3008,2003,2,899.99,10 -4013,3008,2010,1,2500.00,0 -4014,3009,2008,2,899.99,0 -4015,3009,2011,2,1200.00,5 -4016,3010,2004,2,3499.99,10 -4017,3010,2015,1,7500.00,0 -4018,3011,2002,2,1899.99,5 -4019,3011,2005,1,1299.99,0 -4020,3012,2013,1,999.99,0 -4021,3012,2006,2,599.99,10 -4022,3013,2005,1,1299.99,0 -4023,3014,2001,1,2999.99,0 -4024,3014,2009,1,5000.00,0 -4025,3015,2012,1,1799.99,0 -4026,3015,2011,1,1200.00,0 -4027,3016,2015,1,7500.00,5 -4028,3016,2001,1,2999.99,0 -4029,3016,2010,1,2500.00,0 -4030,3017,2004,2,3499.99,8 -4031,3017,2014,1,2299.99,0 -4032,3018,2001,1,2999.99,0 -4033,3019,2012,1,1799.99,0 -4034,3020,2002,2,1899.99,5 -4035,3020,2011,1,1200.00,0 \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/orders.csv b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/orders.csv deleted file mode 100644 index ff180257f..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/orders.csv +++ /dev/null @@ -1,21 +0,0 @@ -norder_id,customer_id,order_date,total_amount,status,region,sales_rep -3001,1001,2024-01-15,8999.97,DELIVERED,North America,Sarah Chen -3002,1002,2024-01-20,3799.98,DELIVERED,North America,Mike Johnson -3003,1003,2024-01-25,1799.98,SHIPPED,Europe,Emma Rodriguez -3004,1004,2024-02-01,6299.97,DELIVERED,Asia Pacific,David Kim -3005,1005,2024-02-10,2199.98,PROCESSING,North America,Sarah Chen -3006,1006,2024-02-15,1599.99,DELIVERED,Europe,Emma Rodriguez -3007,1007,2024-02-20,11999.96,SHIPPED,Europe,Emma Rodriguez -3008,1008,2024-03-01,3699.98,DELIVERED,Europe,Emma Rodriguez -3009,1009,2024-03-05,4499.98,DELIVERED,Asia Pacific,David Kim -3010,1010,2024-03-10,9799.97,PROCESSING,North America,Sarah Chen -3011,1001,2024-03-15,5999.98,SHIPPED,North America,Sarah Chen -3012,1003,2024-03-20,2699.98,DELIVERED,Europe,Emma Rodriguez -3013,1005,2024-04-01,1299.99,PENDING,North America,Sarah Chen -3014,1007,2024-04-05,7999.98,PROCESSING,Europe,Emma Rodriguez -3015,1009,2024-04-10,3199.98,SHIPPED,Asia Pacific,David Kim -3016,1012,2024-05-01,12499.97,DELIVERED,Asia Pacific,David Kim -3017,1014,2024-05-15,8799.98,DELIVERED,Asia Pacific,David Kim -3018,1011,2024-06-01,2999.98,SHIPPED,South America,Carlos Lopez -3019,1013,2024-06-10,1799.99,DELIVERED,Asia Pacific,David Kim -3020,1015,2024-07-01,4299.98,PROCESSING,Europe,Emma Rodriguez \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/products.csv b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/products.csv deleted file mode 100644 index 4139547bf..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/database/products.csv +++ /dev/null @@ -1,16 +0,0 @@ -product_id,product_name,category,price,cost,stock_quantity,launch_date -2001,AI Analytics Platform,Software,2999.99,1200.00,100,2023-01-15 -2002,Cloud Infrastructure,Software,1899.99,800.00,150,2023-02-01 -2003,Data Visualization Tool,Software,899.99,350.00,200,2023-01-20 -2004,Enterprise Security Suite,Software,3499.99,1500.00,75,2023-03-01 -2005,Mobile App Framework,Software,1299.99,550.00,120,2023-02-15 -2006,IoT Sensor Kit,Hardware,599.99,250.00,300,2023-04-01 -2007,Smart Dashboard Display,Hardware,1599.99,700.00,80,2023-03-15 -2008,Network Monitoring Device,Hardware,899.99,400.00,150,2023-05-01 -2009,Premium Consulting,Services,5000.00,2000.00,999,2023-01-01 -2010,Training Program,Services,2500.00,800.00,999,2023-02-01 -2011,Support Package,Services,1200.00,400.00,999,2023-01-15 -2012,API Gateway,Software,1799.99,750.00,90,2023-06-01 -2013,Backup Solution,Software,999.99,420.00,180,2023-04-15 -2014,Load Balancer,Hardware,2299.99,1000.00,60,2023-07-01 -2015,Custom Integration,Services,7500.00,3000.00,999,2023-03-01 \ No newline at end of file diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/Chat.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/Chat.js deleted file mode 100644 index 2bfa28082..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/Chat.js +++ /dev/null @@ -1,352 +0,0 @@ -"use client"; - -import { APP_CONFIG } from "../../config/app"; -import DynamicThemeProvider from "../../contexts/DynamicThemeProvider"; -import { - Alert, - alpha, - Box, - Container, - lighten, - Paper, - Snackbar, - Typography, -} from "@mui/material"; -import { AnimatePresence, motion } from "framer-motion"; -import { useState } from "react"; -import { useChat } from "../../contexts/ChatContext"; -import { useProject } from "../../contexts/ProjectsContext"; -import ChatHeader from "./ChatHeader"; -import ChatInputBar from "./ChatInputBar"; -import MessageList from "./MessageList"; - -const containerVariants = { - initial: { - scale: 0.8, - opacity: 0, - }, - animate: { - scale: 1, - opacity: 1, - transition: { - type: "spring", - stiffness: 260, - damping: 20, - }, - }, -}; - -const dynamicIslandVariants = { - initial: { - y: 100, - opacity: 0, - }, - animate: { - y: 0, - opacity: 1, - transition: { - type: "spring", - stiffness: 350, - damping: 25, - delay: 0.3, - }, - }, -}; - -const logoVariants = { - initial: { - opacity: 0, - }, - animate: { - opacity: 1, - transition: { - duration: 0.3, - }, - }, - exit: { - opacity: 0, - transition: { - duration: 0.2, - }, - }, -}; - -export default function Chat({ onAddProject, onEditProject, onDeleteProject }) { - const { - messages, - connected, - loading, - error, - isListening, - isWaitingForResponse, - sendMessage, - sendAttachment, - clearChat, - toggleSpeechRecognition, - setError, - currentSpeechProvider, - } = useChat(); - - const { getCurrentProject } = useProject(); - const currentProject = getCurrentProject(); - - const [isDragOver, setIsDragOver] = useState(false); - - const isOracleRecording = currentSpeechProvider === "oracle" && isListening; - - const handleDragOver = (e) => { - e.preventDefault(); - e.stopPropagation(); - }; - - const handleDragEnter = (e) => { - e.preventDefault(); - e.stopPropagation(); - setIsDragOver(true); - }; - - const handleDragLeave = (e) => { - e.preventDefault(); - e.stopPropagation(); - if (!e.currentTarget.contains(e.relatedTarget)) { - setIsDragOver(false); - } - }; - - const handleDrop = (e) => { - e.preventDefault(); - e.stopPropagation(); - setIsDragOver(false); - - const files = e.dataTransfer.files; - if (files.length > 0) { - const file = files[0]; - const isValidType = - file.type.startsWith("image/") || file.type === "application/pdf"; - - if (isValidType) { - window.dispatchEvent(new CustomEvent("fileDropped", { detail: file })); - } - } - }; - - const getBackgroundStyle = () => { - if (currentProject.backgroundImage) { - return { - backgroundImage: `url(${currentProject.backgroundImage})`, - backgroundSize: "cover", - backgroundPosition: "center", - backgroundRepeat: "no-repeat", - }; - } - return { - backgroundColor: lighten( - currentProject.backgroundColor || APP_CONFIG.defaults.backgroundColor, - 0.5 - ), - }; - }; - - const hasMessages = messages.length > 0 || isWaitingForResponse; - - return ( - - - {isDragOver && ( - - - 📎 Drop images or PDFs here - - - )} - - - {/* - - */} - - - - - - - - - - {hasMessages && ( - - - - - - )} - - - setError("")} - anchorOrigin={{ vertical: "bottom", horizontal: "center" }} - > - setError("")} severity="error"> - {error} - - - - - - - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatHeader.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatHeader.js deleted file mode 100644 index 2917619ca..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatHeader.js +++ /dev/null @@ -1,91 +0,0 @@ -"use client"; - -import { LoupeOutlined } from "@mui/icons-material"; -import { Box, IconButton, Stack, Tooltip, Typography } from "@mui/material"; -import { AnimatePresence, motion } from "framer-motion"; -import { useRouter } from "next/navigation"; - -export default function ChatHeader({ - messagesCount, - onNewChat, - isConnected = false, - projectName, -}) { - const router = useRouter(); - - const titleVariants = { - initial: { - opacity: 0, - y: -10, - scale: 0.95, - }, - animate: { - opacity: 1, - y: 0, - scale: 1, - transition: { - type: "spring", - stiffness: 400, - damping: 25, - duration: 0.4, - }, - }, - exit: { - opacity: 0, - y: -10, - scale: 0.95, - transition: { - duration: 0.2, - }, - }, - }; - - return ( - - - - - {messagesCount > 0 && ( - - - {projectName} - - - )} - - - - - - - - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatInputBar.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatInputBar.js deleted file mode 100644 index 7726d7ce8..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatInputBar.js +++ /dev/null @@ -1,440 +0,0 @@ -"use client"; - -import { - alpha, - Box, - IconButton, - Stack, - TextField, - Typography, -} from "@mui/material"; -import { useTheme } from "@mui/material/styles"; -import { motion } from "framer-motion"; -import { FileText, Forward, Mic, X, Paperclip } from "lucide-react"; -import { useEffect, useRef, useState } from "react"; - -export default function ChatInputBar({ - onSendMessage, - onToggleSpeechRecognition, - onSendAttachment, - isConnected, - isListening, - isPreview, - currentSpeechProvider, -}) { - const [input, setInput] = useState(""); - const [audioLevels, setAudioLevels] = useState([0, 0, 0, 0, 0]); - const inputRef = useRef(null); - const audioContextRef = useRef(null); - const analyserRef = useRef(null); - const animationFrameRef = useRef(null); - - const [selectedFile, setSelectedFile] = useState(null); - const [filePreview, setFilePreview] = useState(null); - const fileInputRef = useRef(null); - - const theme = useTheme(); - const isOracleListening = currentSpeechProvider === "oracle" && isListening; - - const handleSendMessage = async () => { - if (!isConnected) return; - - const hasText = input.trim(); - const hasFile = selectedFile; - - if (!hasText && !hasFile) return; - - if (hasFile && onSendAttachment) { - const success = await onSendAttachment(selectedFile); - if (!success) return; - } - - if (hasText && onSendMessage) { - onSendMessage(input.trim()); - } - - setInput(""); - setSelectedFile(null); - setFilePreview(null); - }; - - const handleKeyPress = (e) => { - if (e.key === "Enter" && !e.shiftKey) { - e.preventDefault(); - handleSendMessage(); - } - }; - - const handleFileSelect = (event) => { - const file = event.target.files[0]; - if (file) { - setSelectedFile(file); - - if (file.type.startsWith("image/")) { - const reader = new FileReader(); - reader.onload = (e) => setFilePreview(e.target.result); - reader.readAsDataURL(file); - } else { - setFilePreview(null); - } - - event.target.value = ""; - } - }; - - const handleRemoveFile = () => { - setSelectedFile(null); - setFilePreview(null); - }; - - useEffect(() => { - if (isOracleListening) { - const startAudioAnalysis = async () => { - try { - const stream = await navigator.mediaDevices.getUserMedia({ - audio: { sampleRate: 16000, channelCount: 1 }, - }); - - audioContextRef.current = new AudioContext(); - analyserRef.current = audioContextRef.current.createAnalyser(); - - const source = - audioContextRef.current.createMediaStreamSource(stream); - source.connect(analyserRef.current); - - analyserRef.current.fftSize = 256; - const bufferLength = analyserRef.current.frequencyBinCount; - const dataArray = new Uint8Array(bufferLength); - - const updateLevels = () => { - analyserRef.current.getByteFrequencyData(dataArray); - - const newLevels = []; - const segmentSize = Math.floor(bufferLength / 5); - - for (let i = 0; i < 5; i++) { - const start = i * segmentSize; - const end = start + segmentSize; - let sum = 0; - - for (let j = start; j < end; j++) { - sum += dataArray[j]; - } - - const average = sum / segmentSize; - const normalized = Math.min(average / 80, 3); - newLevels.push(normalized); - } - - setAudioLevels(newLevels); - animationFrameRef.current = requestAnimationFrame(updateLevels); - }; - - updateLevels(); - } catch (error) { - console.error("Error accessing microphone:", error); - } - }; - - startAudioAnalysis(); - } else { - if (animationFrameRef.current) { - cancelAnimationFrame(animationFrameRef.current); - } - if ( - audioContextRef.current && - audioContextRef.current.state !== "closed" - ) { - audioContextRef.current.close(); - audioContextRef.current = null; - } - setAudioLevels([0, 0, 0, 0, 0]); - } - - return () => { - if (animationFrameRef.current) { - cancelAnimationFrame(animationFrameRef.current); - } - if ( - audioContextRef.current && - audioContextRef.current.state !== "closed" - ) { - audioContextRef.current.close(); - } - }; - }, [isOracleListening]); - - useEffect(() => { - if (isConnected && inputRef.current) { - inputRef.current.focus(); - } - }, [isConnected]); - - useEffect(() => { - const handleFileDropped = (event) => { - const file = event.detail; - setSelectedFile(file); - - if (file.type.startsWith("image/")) { - const reader = new FileReader(); - reader.onload = (e) => setFilePreview(e.target.result); - reader.readAsDataURL(file); - } else { - setFilePreview(null); - } - }; - - window.addEventListener("fileDropped", handleFileDropped); - return () => window.removeEventListener("fileDropped", handleFileDropped); - }, []); - - return ( - - {selectedFile && ( - - - - - - {filePreview ? ( - - ) : ( - - - - )} - - - {selectedFile.name} - - - )} - - - fileInputRef.current?.click()} - disabled={!isConnected} - title="Upload file" - sx={{ - color: theme.palette.text.secondary, - "&:hover": { - backgroundColor: theme.palette.primary.main + "14", - }, - "&:disabled": { - color: theme.palette.text.disabled, - }, - mr: 1, - }} - > - - - - {!isOracleListening && ( - setInput(e.target.value)} - onKeyPress={handleKeyPress} - disabled={!isConnected || isListening} - multiline - maxRows={4} - inputRef={inputRef} - slotProps={{ - input: { - disableUnderline: true, - sx: { - color: theme.palette.text.primary, - "::placeholder": { - color: theme.palette.text.secondary, - }, - }, - }, - }} - sx={{ pl: 2, pr: 2, py: 0.5 }} - /> - )} - - - {isOracleListening ? ( - - {[2, 1, 0, 1, 2].map((position, index) => ( - - ))} - - ) : ( - - )} - - {!isOracleListening && ( - - - - )} - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatPreview.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatPreview.js deleted file mode 100644 index b05f71582..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/ChatPreview.js +++ /dev/null @@ -1,186 +0,0 @@ -"use client"; - -import DynamicThemeProvider from "../../contexts/DynamicThemeProvider"; -import { Alert, Box, lighten, Paper, Snackbar } from "@mui/material"; -import { motion } from "framer-motion"; -import { useState } from "react"; -import ChatHeader from "../Chat/ChatHeader"; -import ChatInputBar from "../Chat/ChatInputBar"; -import MessageList from "../Chat/MessageList"; - -const containerVariants = { - initial: { - scale: 0.8, - opacity: 0, - }, - animate: { - scale: 1, - opacity: 1, - transition: { - type: "spring", - stiffness: 260, - damping: 20, - }, - }, -}; - -const dynamicIslandVariants = { - initial: { - y: 100, - opacity: 0, - }, - animate: { - y: 0, - opacity: 1, - transition: { - type: "spring", - stiffness: 350, - damping: 25, - delay: 0.3, - }, - }, -}; - -export default function ChatPreview({ projectData }) { - const [error, setError] = useState(""); - - const messages = []; - const connected = true; - const loading = false; - const isListening = false; - - const sendMessage = () => {}; - const clearChat = () => {}; - const toggleSpeechRecognition = () => {}; - - const getBackgroundStyle = () => { - if (projectData.backgroundImage) { - return { - backgroundImage: `url(${projectData.backgroundImage})`, - backgroundSize: "cover", - backgroundPosition: "center", - backgroundRepeat: "no-repeat", - }; - } - return { - backgroundColor: lighten(projectData.backgroundColor || "#F5F5F5", 0.5), - }; - }; - - return ( - - - - - - - - - - - setError("")} - > - setError("")} severity="error"> - {error} - - - - - - - - - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageContent.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageContent.js deleted file mode 100644 index ce5f0874c..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageContent.js +++ /dev/null @@ -1,444 +0,0 @@ -"use client"; - -import { - Box, - Button, - Card, - CardContent, - Dialog, - DialogActions, - DialogContent, - DialogTitle, - IconButton, - Paper, - Table, - TableBody, - TableCell, - TableContainer, - TableHead, - TableRow, - Tooltip, - Typography, -} from "@mui/material"; -import { ExternalLink, Eye, FileText } from "lucide-react"; -import Markdown from "markdown-to-jsx"; -import { useState } from "react"; - -export default function MessageContent({ message, isFromBot }) { - const payload = message.messagePayload; - const [citationDialogOpen, setCitationDialogOpen] = useState(false); - const [selectedCitationContent, setSelectedCitationContent] = useState(""); - - const isLongText = (value) => { - const stringValue = - value !== null && value !== undefined ? String(value) : ""; - return stringValue.length > 100; - }; - - switch (payload.type) { - case "text": - return ( - - - {payload.text} - - - {payload.citations && payload.citations.length > 0 && ( - - - Sources: - - {payload.citations.map((citation, index) => ( - - - - - - {citation.document_name} - - - - {citation.page_numbers && - citation.page_numbers.length > 0 && ( - - pages {citation.page_numbers.join(", ")} - - )} - - - - { - setSelectedCitationContent(citation.content); - setCitationDialogOpen(true); - }} - > - - - - - - - window.open(citation.source_url, "_blank") - } - > - - - - - - ))} - - setCitationDialogOpen(false)} - maxWidth="md" - fullWidth - > - Citation Content - - - {selectedCitationContent} - - - - - - - - )} - - ); - - case "diagram": - return ( - - {payload.text && payload.text.trim() && ( - - {payload.text} - - )} - - - ); - - case "sql_result": - return ( - - {payload.generatedQuery && ( - - - Generated Query: - - - {payload.generatedQuery} - - - )} - - {payload.executionResult && - payload.executionResult.length > 0 && - (() => { - const data = payload.executionResult; - const columns = Object.keys(data[0]); - - const getColumnWidth = (columnName, columnIndex) => { - const columnValues = data.map( - (row) => Object.values(row)[columnIndex] - ); - const allValues = [columnName, ...columnValues]; - - const lengths = allValues.map( - (val) => String(val || "").length - ); - const avgLength = - lengths.reduce((sum, len) => sum + len, 0) / lengths.length; - const maxLength = Math.max(...lengths); - const headerLength = columnName.length; - - const headerMinWidth = Math.max(headerLength * 8, 100); - - let calculatedWidth; - if (maxLength > 200) { - calculatedWidth = { minWidth: "280px", maxWidth: "350px" }; - } else if (maxLength > 100) { - calculatedWidth = { minWidth: "200px", maxWidth: "280px" }; - } else if (avgLength > 30) { - calculatedWidth = { minWidth: "150px", maxWidth: "200px" }; - } else if (avgLength > 15) { - calculatedWidth = { minWidth: "120px", maxWidth: "150px" }; - } else { - calculatedWidth = { minWidth: "100px", maxWidth: "120px" }; - } - - const finalMinWidth = Math.max( - parseInt(calculatedWidth.minWidth), - headerMinWidth - ); - - return { - minWidth: `${finalMinWidth}px`, - maxWidth: calculatedWidth.maxWidth, - }; - }; - - return ( - - - Results: - - - - - - {columns.map((key, index) => { - const widths = getColumnWidth(key, index); - return ( - - {key} - - ); - })} - - - - {data.map((row, rowIndex) => ( - - {Object.values(row).map((value, cellIndex) => { - const stringValue = - value !== null && value !== undefined - ? String(value) - : ""; - const isLong = isLongText(value); - const widths = getColumnWidth( - columns[cellIndex], - cellIndex - ); - - return ( - - {isLong ? ( - - {stringValue} - - ) : ( - 50 && { - whiteSpace: "pre-wrap", - overflow: "visible", - textOverflow: "clip", - }), - }} - title={stringValue} - > - {stringValue} - - )} - - ); - })} - - ))} - -
- - - ); - })()} - - ); - - case "card": - return ( - - - {payload.cards && - payload.cards.map((card, idx) => ( - - {card.title && ( - {card.title} - )} - {card.description && ( - {card.description} - )} - {card.url && ( - - - {card.url} - - - )} - - ))} - - - ); - - case "attachment": - const attachment = payload.attachment; - - if (attachment.type.startsWith("image/")) { - return ( - - ); - } - - return ( - - Attachment: {attachment.type} -{" "} - - {attachment.title || "View"} - - - ); - - default: - return ( - - Unsupported message type: {payload.type} - - ); - } -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageItem.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageItem.js deleted file mode 100644 index ff8259e6f..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageItem.js +++ /dev/null @@ -1,183 +0,0 @@ -"use client"; - -import { Box, useTheme } from "@mui/material"; -import { motion } from "framer-motion"; -import { useChat } from "../../contexts/ChatContext"; -import MessageContent from "./MessageContent"; - -export default function MessageItem({ message }) { - const theme = useTheme(); - const { speakMessage, cancelAudio, playingMessageId, setPlayingMessageId } = - useChat(); - - const isFromBot = message.from; - - const primaryColor = theme.palette.primary.main; - const primaryLight = theme.palette.primary.light; - const primaryDark = theme.palette.primary.dark; - - const messageId = `${message.userId}-${message.date}`; - const isPlaying = playingMessageId === messageId; - - const handlePlayAudio = (message) => { - if (isPlaying) { - cancelAudio(); - } else { - if (playingMessageId) { - cancelAudio(); - } - if (speakMessage(message)) { - setPlayingMessageId(messageId); - } - } - }; - - const botMessageVariants = { - initial: { - opacity: 0, - x: -30, - scale: 0.96, - }, - animate: { - opacity: 1, - x: 0, - scale: 1, - transition: { - type: "spring", - stiffness: 300, - damping: 30, - duration: 0.5, - }, - }, - }; - - const userMessageVariants = { - initial: { - opacity: 0, - x: 30, - scale: 0.96, - }, - animate: { - opacity: 1, - x: 0, - scale: 1, - transition: { - type: "spring", - stiffness: 320, - damping: 25, - duration: 0.4, - }, - }, - }; - - return ( - - {isFromBot ? ( - - - - - {/* - handlePlayAudio(message)} - sx={{ - width: 24, - height: 24, - backgroundColor: "rgba(0, 0, 0, 0.1)", - "&:hover": { - backgroundColor: "rgba(0, 0, 0, 0.2)", - }, - }} - > - {isPlaying ? ( - - ) : ( - - )} - - */} - - ) : ( - - - - - - )} - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageList.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageList.js deleted file mode 100644 index a75c314fb..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/MessageList.js +++ /dev/null @@ -1,94 +0,0 @@ -"use client"; - -import { Box, CircularProgress, List } from "@mui/material"; -import { AnimatePresence, motion } from "framer-motion"; -import { useEffect, useRef } from "react"; -import MessageItem from "./MessageItem"; -import TypingIndicator from "./TypingIndicator"; -import WelcomeScreen from "./WelcomeScreen"; - -export default function MessageList({ - messages, - loading, - projectName, - logoUrl, - onSendMessage, - isWaitingForResponse = false, -}) { - const messagesEndRef = useRef(null); - - useEffect(() => { - scrollToBottom(); - }, [messages, isWaitingForResponse]); - - const scrollToBottom = () => { - messagesEndRef.current?.scrollIntoView({ behavior: "smooth" }); - }; - - const welcomeVariants = { - initial: { - opacity: 1, - scale: 1, - }, - exit: { - opacity: 0, - scale: 0.95, - transition: { - duration: 0.3, - ease: "easeInOut", - }, - }, - }; - - if (loading && messages.length === 0) { - return ( - - - - ); - } - - const hasMessages = messages.length > 0 || isWaitingForResponse; - - return ( - - - {!hasMessages && ( - - - - )} - - - - {messages.map((msg, idx) => ( - - ))} - {isWaitingForResponse && } -
- - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/TypingIndicator.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/TypingIndicator.js deleted file mode 100644 index 17029f596..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/TypingIndicator.js +++ /dev/null @@ -1,79 +0,0 @@ -"use client"; - -import { Box } from "@mui/material"; -import { motion } from "framer-motion"; - -export default function TypingIndicator() { - const dotVariants = { - animate: { - scale: [1, 1.2, 1], - opacity: [0.4, 1, 0.4], - transition: { - duration: 1.4, - repeat: Infinity, - ease: "easeInOut", - }, - }, - }; - - const containerVariants = { - animate: { - transition: { - staggerChildren: 0.2, - repeat: Infinity, - }, - }, - }; - - return ( - - - - {[0, 1, 2].map((index) => ( - - ))} - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/WelcomeScreen.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/WelcomeScreen.js deleted file mode 100644 index f14621a89..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Chat/WelcomeScreen.js +++ /dev/null @@ -1,102 +0,0 @@ -"use client"; - -import { Box, Button, Typography, alpha, darken, lighten } from "@mui/material"; -import { useTheme } from "@mui/material/styles"; - -const SUGGESTIONS = [ - "show the top 5 orders", - "show the number of order per region?", -]; - -export default function WelcomeScreen({ projectName, logoUrl, onSendMessage }) { - const theme = useTheme(); - - const handleSuggestionClick = (suggestion) => { - if (onSendMessage) { - onSendMessage(suggestion); - } - }; - - return ( - - - - - {projectName} - - - How can I help you today? - - - - {SUGGESTIONS.map((suggestion, index) => ( - - ))} - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/ClientThemeProvider.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/ClientThemeProvider.js deleted file mode 100644 index df9556b00..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/ClientThemeProvider.js +++ /dev/null @@ -1,13 +0,0 @@ -"use client"; -import { CssBaseline, ThemeProvider } from "@mui/material"; -import { ProjectProvider } from "../contexts/ProjectsContext"; -import theme from "../theme/theme"; - -export default function ClientThemeProvider({ children }) { - return ( - - - {children} - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/NavMenu.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/NavMenu.js deleted file mode 100644 index 55a242865..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/NavMenu.js +++ /dev/null @@ -1,236 +0,0 @@ -"use client"; - -import { Add, Delete, Edit } from "@mui/icons-material"; -import { Avatar, Box, IconButton, Paper, Stack, Tooltip } from "@mui/material"; -import { motion } from "framer-motion"; -import { useRouter } from "next/navigation"; -import { useProject } from "../contexts/ProjectsContext"; - -const menuVariants = { - initial: { - x: -100, - opacity: 0, - }, - animate: { - x: 0, - opacity: 1, - transition: { - type: "spring", - stiffness: 350, - damping: 25, - delay: 0.2, - }, - }, -}; - -export default function NavMenu({ - onAddProject, - onEditProject, - onDeleteProject, -}) { - const router = useRouter(); - const { projects, switchProject, getCurrentProject } = useProject(); - const currentProject = getCurrentProject(); - - const handleProjectSwitch = (projectId) => { - switchProject(projectId); - router.push(`/?projectId=${projectId}`); - }; - - return ( - - - {projects.map((project) => ( - - - - {project.name} - - - { - e.stopPropagation(); - handleProjectSwitch(project.id); - onEditProject(project); - }} - sx={{ - width: 24, - height: 24, - backgroundColor: "white", - color: "black", - boxShadow: "0 2px 6px rgba(0, 0, 0, 0.12)", - "&:hover": { - backgroundColor: "rgba(255,255,255,0.8)", - }, - }} - > - - - {project.id !== "default" && ( - { - e.stopPropagation(); - onDeleteProject(project.id); - }} - sx={{ - width: 24, - height: 24, - backgroundColor: "white", - color: "red", - boxShadow: "0 2px 6px rgba(0, 0, 0, 0.12)", - "&:hover": { - backgroundColor: "rgba(255,255,255,0.8)", - }, - }} - > - - - )} - - - } - placement="right" - leaveDelay={100} - componentsProps={{ - tooltip: { - sx: { - backgroundColor: "transparent", - padding: 0, - margin: 0, - "& .MuiTooltip-arrow": { - display: "none", - }, - }, - }, - }} - > - handleProjectSwitch(project.id)} - sx={{ - backgroundColor: - currentProject.id === project.id - ? project.mainColor - : "transparent", - padding: 0, - display: "flex", - alignItems: "center", - justifyContent: "center", - "&:hover": { - backgroundColor: - currentProject.id === project.id - ? project.mainColor - : "rgba(0, 0, 0, 0.04)", - }, - }} - > - - {project.name.charAt(0).toUpperCase()} - - - - - ))} - - - - - - = 8 ? "Maximum 8 projects allowed" : "Add Project" - } - placement="right" - > - - - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Settings/ProjectCard.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Settings/ProjectCard.js deleted file mode 100644 index fe52a7d84..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Settings/ProjectCard.js +++ /dev/null @@ -1,184 +0,0 @@ -"use client"; - -import { useProject } from "../../contexts/ProjectsContext"; -import { Box, Card, Typography, alpha, useTheme } from "@mui/material"; -import { motion } from "framer-motion"; -import { MessageSquare, Settings } from "lucide-react"; -import { useRouter } from "next/navigation"; - -export default function ProjectCard({ project, onEdit }) { - const router = useRouter(); - const { switchProject } = useProject(); - const theme = useTheme(); - - const handleEditClick = (e) => { - e.stopPropagation(); - onEdit(project); - }; - - const handleGoToChat = (e) => { - e.stopPropagation(); - switchProject(project.id); - router.push(`/?projectId=${project.id}`); - }; - - return ( - theme.spacing(4, 4, 4, 1), - }} - > - {} - - - - - - - - {project.logoUrl ? ( - - ) : ( - - {project.name.charAt(0).toUpperCase()} - - )} - - - {project.name} - - - {} - - - - Go to chat - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Settings/ProjectModal.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Settings/ProjectModal.js deleted file mode 100644 index 9b9f542fb..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/Settings/ProjectModal.js +++ /dev/null @@ -1,411 +0,0 @@ -"use client"; - -import { APP_CONFIG } from "../../config/app"; -import CloseIcon from "@mui/icons-material/Close"; -import DeleteIcon from "@mui/icons-material/Delete"; -import SaveIcon from "@mui/icons-material/Save"; -import { - Box, - Button, - Dialog, - DialogActions, - DialogContent, - DialogContentText, - DialogTitle, - FormControl, - FormControlLabel, - FormLabel, - IconButton, - Radio, - RadioGroup, - Stack, - TextField, - Typography, -} from "@mui/material"; -import { useEffect, useState } from "react"; -import ChatPreview from "../Chat/ChatPreview"; - -export default function ProjectModal({ - open, - onClose, - project = null, - onSave, - onDelete, -}) { - const isNewProject = !project; - const [formData, setFormData] = useState({ - name: "", - logoUrl: APP_CONFIG.defaults.logoUrl, - mainColor: APP_CONFIG.defaults.color, - backgroundColor: APP_CONFIG.defaults.backgroundColor, - backgroundImage: APP_CONFIG.defaults.image, - backgroundType: "image", - speechProvider: APP_CONFIG.defaults.speechProvider, - }); - const [errors, setErrors] = useState({}); - const [deleteDialogOpen, setDeleteDialogOpen] = useState(false); - - useEffect(() => { - if (project) { - setFormData({ - name: project.name, - logoUrl: project.logoUrl || APP_CONFIG.defaults.logoUrl, - mainColor: project.mainColor || APP_CONFIG.defaults.color, - backgroundColor: - project.backgroundColor || APP_CONFIG.defaults.backgroundColor, - backgroundImage: project.backgroundImage || APP_CONFIG.defaults.image, - backgroundType: "image", - speechProvider: - project.speechProvider || APP_CONFIG.defaults.speechProvider, - }); - - if ( - !APP_CONFIG.availableColors.includes( - project.mainColor || APP_CONFIG.defaults.color - ) - ) { - setFormData((prev) => ({ - ...prev, - mainColor: APP_CONFIG.defaults.color, - })); - } - } else { - setFormData({ - name: "", - logoUrl: APP_CONFIG.defaults.logoUrl, - mainColor: APP_CONFIG.defaults.color, - backgroundColor: APP_CONFIG.defaults.backgroundColor, - backgroundImage: APP_CONFIG.defaults.image, - backgroundType: "image", - speechProvider: APP_CONFIG.defaults.speechProvider, - }); - } - setErrors({}); - }, [project, open]); - - const handleInputChange = (e) => { - const { name, value } = e.target; - setFormData((prev) => ({ ...prev, [name]: value })); - - if (errors[name]) { - setErrors((prev) => ({ ...prev, [name]: undefined })); - } - }; - - const handleMainColorSelect = (colorValue) => { - setFormData((prev) => ({ - ...prev, - mainColor: colorValue, - })); - }; - - const handleImageSelect = (imageUrl) => { - setFormData((prev) => ({ - ...prev, - backgroundImage: imageUrl, - backgroundType: "image", - })); - }; - - const validateForm = () => { - const newErrors = {}; - - if (!formData.name.trim()) { - newErrors.name = "Name is required"; - } - - if (formData.logoUrl && !isValidUrl(formData.logoUrl)) { - newErrors.logoUrl = "Please enter a valid URL"; - } - - setErrors(newErrors); - return Object.keys(newErrors).length === 0; - }; - - const isValidUrl = (string) => { - try { - new URL(string); - return true; - } catch (_) { - return false; - } - }; - - const handleSave = () => { - if (!validateForm()) return; - onSave(formData); - onClose(); - }; - - const handleDelete = () => { - onDelete(project.id); - setDeleteDialogOpen(false); - onClose(); - }; - - const handleClose = () => { - onClose(); - setDeleteDialogOpen(false); - }; - - return ( - <> - - e.stopPropagation()} - > - - - - {isNewProject ? "Create New Project" : "Edit Project"} - - - - - - - - - - - - - - - Main Color - - - - {APP_CONFIG.availableColors.map((color) => ( - handleMainColorSelect(color)} - sx={{ - width: 40, - height: 40, - bgcolor: color, - borderRadius: 1, - cursor: "pointer", - border: "1px solid rgba(0, 0, 0, 0.1)", - transform: - formData.mainColor === color - ? "scale(1.2)" - : "scale(1)", - transition: "transform 0.15s ease-out", - "&:hover": { - transform: - formData.mainColor === color - ? "scale(1.2)" - : "scale(1.05)", - }, - }} - /> - ))} - - - - - - Background - - - - {APP_CONFIG.availableImages.map((image, index) => ( - handleImageSelect(image)} - sx={{ - width: 50, - height: 50, - borderRadius: 1, - cursor: "pointer", - backgroundImage: `url(${image})`, - backgroundSize: "cover", - backgroundPosition: "center", - transform: - formData.backgroundType === "image" && - formData.backgroundImage === image - ? "scale(1.2)" - : "scale(1)", - transition: "transform 0.15s ease-out", - "&:hover": { - transform: - formData.backgroundType === "image" && - formData.backgroundImage === image - ? "scale(1.2)" - : "scale(1.05)", - }, - }} - /> - ))} - - - - - - Speech Service - - - } - label="Browser" - /> - } - label="Oracle" - /> - - - - - - - {!isNewProject && project?.id !== "default" && ( - - )} - - - - - - - - - - - - - - - setDeleteDialogOpen(false)} - > - Delete Project? - - - Are you sure you want to delete this project? This action cannot be - undone. - - - - - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/TestOracleSpeech.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/TestOracleSpeech.js deleted file mode 100644 index 12c38a819..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/components/TestOracleSpeech.js +++ /dev/null @@ -1,208 +0,0 @@ -"use client"; - -import { Box, Button, Chip, Paper, Typography } from "@mui/material"; -import { Mic, MicOff } from "lucide-react"; -import { useEffect, useState } from "react"; -import createOracleSpeechService from "../services/oracleSpeechService"; - -export default function TestOracleSpeech() { - const [speechService, setSpeechService] = useState(null); - const [isRecording, setIsRecording] = useState(false); - const [transcript, setTranscript] = useState(""); - const [logs, setLogs] = useState([]); - const [error, setError] = useState(""); - const [serviceState, setServiceState] = useState({}); - - useEffect(() => { - const service = createOracleSpeechService(); - setSpeechService(service); - - if (!service.isSupported()) { - setError("Tu navegador no soporta las APIs necesarias"); - } - - const interval = setInterval(() => { - if (service.getState) { - setServiceState(service.getState()); - } - }, 1000); - - return () => { - clearInterval(interval); - if (service) { - service.disconnect(); - } - }; - }, []); - - const addLog = (message, type = "info") => { - const timestamp = new Date().toLocaleTimeString(); - setLogs((prev) => [...prev, { timestamp, message, type }]); - }; - - const handleStartRecording = async () => { - if (!speechService) return; - - setError(""); - setTranscript(""); - addLog("Iniciando grabación...", "info"); - - try { - const success = await speechService.startRecording( - (result) => { - addLog( - `Transcripción: "${result.transcript}" (Final: ${result.isFinal})`, - "success" - ); - if (result.isFinal) { - setTranscript((prev) => prev + " " + result.transcript); - } - }, - (error) => { - addLog(`Error: ${error}`, "error"); - setError(error); - setIsRecording(false); - } - ); - - if (success) { - setIsRecording(true); - addLog("Grabación iniciada exitosamente", "success"); - } else { - addLog("Fallo al iniciar grabación", "error"); - } - } catch (err) { - addLog(`Error no capturado: ${err.message}`, "error"); - setError(err.message); - } - - if (speechService.getState) { - setServiceState(speechService.getState()); - } - }; - - const handleStopRecording = async () => { - if (!speechService) return; - - addLog("Deteniendo grabación...", "info"); - await speechService.stopRecording(); - setIsRecording(false); - addLog("Grabación detenida", "info"); - - if (speechService.getState) { - setServiceState(speechService.getState()); - } - }; - - const clearLogs = () => { - setLogs([]); - setTranscript(""); - setError(""); - }; - - return ( - - - Prueba Oracle Speech Service - - - {} - - - Estado del Servicio: - - - - - - - - - - {} - - - - - - {} - {error && ( - - {error} - - )} - - {} - {transcript && ( - - - Transcripción: - - {transcript} - - )} - - {} - - - Logs: - - {logs.map((log, index) => ( - - - [{log.timestamp}] {log.message} - - - ))} - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/config/app.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/config/app.js deleted file mode 100644 index e885755d4..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/config/app.js +++ /dev/null @@ -1,32 +0,0 @@ -export const APP_CONFIG = { - availableColors: [ - "#2E2E2E", - "#2979FF", - "#34C759", - "#FF9500", - "#FF375F", - "#AF52DE", - "#8E8E93", - "#FFD60A", - ], - availableImages: [ - "/background.png", - "/backgrounds/radial-sky-blue.jpg", - "/backgrounds/sonoma.jpg", - "/backgrounds/imac-blue.jpg", - "/backgrounds/imac-green.jpg", - "/backgrounds/imac-orange.jpg", - "/backgrounds/imac-pink.jpg", - "/backgrounds/imac-purple.jpg", - "/backgrounds/imac-silver.jpg", - "/backgrounds/imac-yellow.jpg", - ], - defaults: { - color: "#3a3632", - image: "/backgrounds/imac-blue.jpg", - backgroundColor: "#F5F5F5", - name: "OCI Generative AI Agents", - logoUrl: "", - speechProvider: "browser", - }, -}; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/ChatContext.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/ChatContext.js deleted file mode 100644 index 9c1e13fd9..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/ChatContext.js +++ /dev/null @@ -1,294 +0,0 @@ -"use client"; - -import { - createContext, - useCallback, - useContext, - useEffect, - useState, -} from "react"; -import createGenaiAgentService from "../services/genaiAgentService"; -import createOracleSpeechService from "../services/oracleSpeechService"; -import createSpeechService from "../services/speechService"; -import { createUserMessage } from "../utils/messageUtils"; -import { useProject } from "./ProjectsContext"; - -const ChatContext = createContext(null); - -export const useChat = () => { - const context = useContext(ChatContext); - if (!context) { - throw new Error("useChat must be used within a ChatProvider"); - } - return context; -}; - -const createSpeechServiceFactory = (speechProvider) => { - switch (speechProvider) { - case "oracle": - return createOracleSpeechService(); - case "browser": - default: - return createSpeechService(); - } -}; - -export const ChatProvider = ({ children }) => { - const { getCurrentProject } = useProject(); - const [messages, setMessages] = useState([]); - const [connected, setConnected] = useState(true); - const [loading, setLoading] = useState(false); - const [error, setError] = useState(""); - const [userId, setUserId] = useState(""); - const [isListening, setIsListening] = useState(false); - const [isWaitingForResponse, setIsWaitingForResponse] = useState(false); - const [genaiService, setGenaiService] = useState(null); - const [speechService, setSpeechService] = useState(null); - const [currentSpeechProvider, setCurrentSpeechProvider] = useState("browser"); - const [playingMessageId, setPlayingMessageId] = useState(null); - - useEffect(() => { - const storedUserId = - typeof window !== "undefined" - ? window.localStorage.getItem("chatUserId") - : null; - - const newUserId = - storedUserId || `user${Math.random().toString(36).substring(2, 10)}`; - - setUserId(newUserId); - - if (typeof window !== "undefined") { - window.localStorage.setItem("chatUserId", newUserId); - } - }, []); - - useEffect(() => { - const currentProject = getCurrentProject(); - const provider = currentProject.speechProvider || "browser"; - - if (currentSpeechProvider !== provider) { - setSpeechService(createSpeechServiceFactory(provider)); - setCurrentSpeechProvider(provider); - setMessages([]); - setIsWaitingForResponse(false); - } - }, [getCurrentProject, currentSpeechProvider]); - - useEffect(() => { - if (!userId) return; - setGenaiService(createGenaiAgentService()); - }, [userId]); - - const sendMessage = useCallback( - async (text) => { - if (!text.trim() || !genaiService) return false; - - const message = createUserMessage(text, userId); - setMessages((prev) => [...prev, message]); - setIsWaitingForResponse(true); - setError(""); - - try { - const response = await genaiService.sendMessage(text); - - const botMessage = { - userId: "bot", - messagePayload: processResponse(response), - date: new Date().toISOString(), - from: { type: "bot" }, - }; - - setMessages((prev) => [...prev, botMessage]); - setIsWaitingForResponse(false); - return true; - } catch (error) { - setError(`Error: ${error.message}`); - setIsWaitingForResponse(false); - return false; - } - }, - [genaiService, userId] - ); - - const processResponse = (apiResponse) => { - const { answer, diagram_base64, citations } = apiResponse; - - if (diagram_base64) { - return { - type: "diagram", - text: answer, - diagram_base64: diagram_base64, - }; - } - - try { - const parsed = JSON.parse(answer); - if (parsed.executionResult) { - return { - type: "sql_result", - generatedQuery: parsed.generatedQuery || "", - executionResult: parsed.executionResult || [], - text: `Query executed: ${parsed.generatedQuery || "SQL query"}`, - }; - } - } catch {} - - return { - type: "text", - text: answer, - citations: citations || [], - }; - }; - - const sendAttachment = useCallback( - async (file) => { - if (!file || !genaiService) return false; - - setIsWaitingForResponse(true); - setError(""); - - // Step 1: Show file preview in UI - const attachmentMessage = { - userId: userId, - messagePayload: { - type: "attachment", - attachment: { - type: file.type, - title: file.name, - url: URL.createObjectURL(file), - }, - }, - date: new Date().toISOString(), - from: { type: "user" }, - }; - setMessages((prev) => [...prev, attachmentMessage]); - - // Step 2: Upload file to FastAPI backend - try { - const formData = new FormData(); - formData.append("message", "Extract text from uploaded file"); - formData.append("file", file); - - const response = await fetch( - `${process.env.NEXT_PUBLIC_GENAI_API_URL}/chat`, - { - method: "POST", - body: formData, - } - ); - - const data = await response.json(); - - const botMessage = { - userId: "bot", - messagePayload: { - type: "text", - text: data.text || "No response from server.", - }, - date: new Date().toISOString(), - from: { type: "bot" }, - }; - - setMessages((prev) => [...prev, botMessage]); - setIsWaitingForResponse(false); - return true; - } catch (error) { - console.error("Attachment upload error:", error); - setError("Error uploading file."); - setIsWaitingForResponse(false); - return false; - } - }, - [genaiService, userId] - ); - - - const clearChat = useCallback(() => { - setMessages([]); - setIsWaitingForResponse(false); - }, []); - - const toggleSpeechRecognition = useCallback(() => { - if (!speechService || !speechService.isSupported()) { - setError("Speech recognition is not supported"); - return; - } - - if (isListening) { - if (speechService.stopListening) { - speechService.stopListening(); - } else if (speechService.stopRecording) { - speechService.stopRecording(); - } - setIsListening(false); - return; - } - - let started = false; - - if (currentSpeechProvider === "oracle") { - started = speechService.startRecording( - (result) => { - if (result.isFinal && result.transcript) { - sendMessage(result.transcript); - } - }, - (error) => { - setIsListening(false); - setError(`Speech recognition error: ${error}`); - } - ); - } else { - started = speechService.startListening( - (result) => { - if (result.stopped) { - setIsListening(false); - return; - } - - if (result.isFinal || result.stopped) { - setIsListening(false); - if (result.transcript) { - sendMessage(result.transcript); - } - } - }, - (error) => { - setIsListening(false); - setError(`Speech recognition error: ${error}`); - } - ); - } - - setIsListening(started); - }, [isListening, sendMessage, speechService, currentSpeechProvider]); - - useEffect(() => { - if (!speechService) { - setSpeechService(createSpeechServiceFactory("browser")); - } - }, [speechService]); - - const value = { - messages, - connected, - loading, - error, - isListening, - isWaitingForResponse, - userId, - sendMessage, - sendAttachment, - clearChat, - toggleSpeechRecognition, - setError, - currentSpeechProvider, - speakMessage: () => false, - cancelAudio: () => setPlayingMessageId(null), - playingMessageId, - setPlayingMessageId, - }; - - return {children}; -}; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/DynamicThemeProvider.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/DynamicThemeProvider.js deleted file mode 100644 index 5ea9b6a40..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/DynamicThemeProvider.js +++ /dev/null @@ -1,41 +0,0 @@ -"use client"; - -import { createTheme, ThemeProvider } from "@mui/material/styles"; -import { useMemo } from "react"; -import { APP_CONFIG } from "../config/app"; - -export default function DynamicThemeProvider({ - children, - projectConfig = null, -}) { - const theme = useMemo(() => { - const baseTheme = createTheme({ - palette: { - mode: "light", - primary: { - main: projectConfig?.mainColor || APP_CONFIG.defaults.color, - light: projectConfig?.mainColor || APP_CONFIG.defaults.color, - dark: projectConfig?.mainColor || APP_CONFIG.defaults.color, - contrastText: "#FFFFFF", - }, - secondary: { - main: "#3FB37F", - light: "#52C08D", - dark: "#36A071", - contrastText: "#EDEBE6", - }, - background: { - default: "#F5F5F5", - paper: "#FFFFFF", - }, - }, - shape: { - borderRadius: 14, - }, - }); - - return baseTheme; - }, [projectConfig]); - - return {children}; -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/ProjectsContext.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/ProjectsContext.js deleted file mode 100644 index 3717469fc..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/contexts/ProjectsContext.js +++ /dev/null @@ -1,162 +0,0 @@ -"use client"; - -import { createContext, useContext, useEffect, useState } from "react"; -import { APP_CONFIG } from "../config/app"; - -const ProjectContext = createContext(null); - -export const useProject = () => { - const context = useContext(ProjectContext); - if (!context) { - throw new Error("useProject must be used within a ProjectProvider"); - } - return context; -}; - -export const ProjectProvider = ({ children }) => { - const [projects, setProjects] = useState([]); - const [currentProjectId, setCurrentProjectId] = useState(""); - - useEffect(() => { - if (typeof window !== "undefined") { - const storedProjects = localStorage.getItem("chatProjects"); - const storedCurrentProjectId = localStorage.getItem("currentProjectId"); - - if (!storedProjects) { - const defaultProject = { - id: "default", - name: APP_CONFIG.defaults.name, - logoUrl: APP_CONFIG.defaults.logoUrl, - mainColor: APP_CONFIG.defaults.color, - backgroundColor: APP_CONFIG.defaults.backgroundColor, - backgroundImage: APP_CONFIG.defaults.image, - speechProvider: APP_CONFIG.defaults.speechProvider, - }; - - setProjects([defaultProject]); - setCurrentProjectId("default"); - - localStorage.setItem("chatProjects", JSON.stringify([defaultProject])); - localStorage.setItem("currentProjectId", "default"); - } else { - const parsedProjects = JSON.parse(storedProjects); - const migratedProjects = parsedProjects.map((project) => ({ - ...project, - mainColor: - project.mainColor || - project.backgroundColor || - APP_CONFIG.defaults.color, - backgroundColor: - project.backgroundColor || APP_CONFIG.defaults.backgroundColor, - speechProvider: - project.speechProvider || APP_CONFIG.defaults.speechProvider, - })); - - setProjects(migratedProjects); - setCurrentProjectId(storedCurrentProjectId || "default"); - } - } - }, []); - - useEffect(() => { - if (typeof window !== "undefined" && projects.length > 0) { - localStorage.setItem("chatProjects", JSON.stringify(projects)); - } - }, [projects]); - - useEffect(() => { - if (typeof window !== "undefined" && currentProjectId) { - localStorage.setItem("currentProjectId", currentProjectId); - } - }, [currentProjectId]); - - const createProject = (projectData) => { - if (projects.length >= 8) { - console.warn("Maximum number of projects (8) reached"); - return null; - } - - const newProject = { - id: Date.now().toString(), - name: APP_CONFIG.defaults.name, - logoUrl: APP_CONFIG.defaults.logoUrl, - mainColor: APP_CONFIG.defaults.color, - backgroundColor: APP_CONFIG.defaults.backgroundColor, - speechProvider: APP_CONFIG.defaults.speechProvider, - ...projectData, - }; - - setProjects((prev) => [...prev, newProject]); - return newProject.id; - }; - - const updateProject = (id, projectData) => { - setProjects((prev) => - prev.map((project) => - project.id === id ? { ...project, ...projectData } : project - ) - ); - }; - - const deleteProject = (id) => { - if (id === "default") return false; - - setProjects((prev) => prev.filter((project) => project.id !== id)); - - if (currentProjectId === id) { - setCurrentProjectId("default"); - } - - return true; - }; - - const getCurrentProject = () => { - const project = - projects.find((p) => p.id === currentProjectId) || projects[0]; - - if (project?.id === "default") { - return { - ...project, - name: APP_CONFIG.defaults.name, - logoUrl: APP_CONFIG.defaults.logoUrl, - mainColor: APP_CONFIG.defaults.color, - backgroundColor: APP_CONFIG.defaults.backgroundColor, - backgroundImage: APP_CONFIG.defaults.image, - speechProvider: APP_CONFIG.defaults.speechProvider, - }; - } - - return ( - project || { - id: "default", - name: APP_CONFIG.defaults.name, - logoUrl: APP_CONFIG.defaults.logoUrl, - mainColor: APP_CONFIG.defaults.color, - backgroundColor: APP_CONFIG.defaults.backgroundColor, - speechProvider: APP_CONFIG.defaults.speechProvider, - } - ); - }; - - const switchProject = (id) => { - if (currentProjectId !== id) { - setCurrentProjectId(id); - } - }; - - return ( - - {children} - - ); -}; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/favicon.ico b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/favicon.ico deleted file mode 100644 index b0090fb52..000000000 Binary files a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/favicon.ico and /dev/null differ diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/globals.css b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/globals.css deleted file mode 100644 index 00cf4305a..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/globals.css +++ /dev/null @@ -1,40 +0,0 @@ -html, -body { - margin: 0; - padding: 0; -} - -body, -h1, -h2, -h3, -h4, -h5, -h6 { - margin: 0; -} - -* { - box-sizing: border-box; -} - -.markdown-content > * + * { - margin-top: 1rem; -} - -.markdown-content ol, -.markdown-content ul { - margin: 1rem 0; - padding-left: 1.5rem; -} - -.markdown-content { - font-family: var(--font-roboto); -} - -* span { - font-family: var(--font-exo2), sans-serif !important; - font-size: 0.88rem !important; - line-height: 1.5 !important; - letter-spacing: 0.01px !important; -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/layout.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/layout.js deleted file mode 100644 index 070af89e9..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/layout.js +++ /dev/null @@ -1,38 +0,0 @@ -import { AppRouterCacheProvider } from "@mui/material-nextjs/v15-appRouter"; -import { Exo_2, Roboto } from "next/font/google"; -import { ProjectProvider } from "./contexts/ProjectsContext"; -import DynamicThemeProvider from "./contexts/DynamicThemeProvider"; -import "./globals.css"; - -const roboto = Roboto({ - weight: ["300", "400", "500", "700"], - subsets: ["latin"], - display: "swap", - variable: "--font-roboto", -}); - -const exo2 = Exo_2({ - weight: ["300", "400", "500", "600", "700"], - subsets: ["latin"], - display: "swap", - variable: "--font-exo2", -}); - -export const metadata = { - title: "OCI Generative AI Agents", - description: "Chat with our AI assistant", -}; - -export default function RootLayout({ children }) { - return ( - - - - - {children} - - - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/page.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/page.js deleted file mode 100644 index 98b7c8af5..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/page.js +++ /dev/null @@ -1,108 +0,0 @@ -"use client"; - -import { Box, CircularProgress } from "@mui/material"; -import { useRouter, useSearchParams } from "next/navigation"; -import { Suspense, useEffect, useState } from "react"; -import Chat from "./components/Chat/Chat"; -import ProjectModal from "./components/Settings/ProjectModal"; -import { ChatProvider } from "./contexts/ChatContext"; -import { useProject } from "./contexts/ProjectsContext"; - -function HomeContent() { - const searchParams = useSearchParams(); - const projectId = searchParams.get("projectId"); - const router = useRouter(); - const { switchProject, createProject, updateProject, deleteProject } = - useProject(); - - const [modalOpen, setModalOpen] = useState(false); - const [selectedProject, setSelectedProject] = useState(null); - - useEffect(() => { - if (projectId) { - switchProject(projectId); - } - }, [projectId, switchProject]); - - const handleAddProject = () => { - setSelectedProject(null); - setModalOpen(true); - }; - - const handleEditProject = (project) => { - setSelectedProject(project); - setModalOpen(true); - }; - - const handleSaveProject = (formData) => { - if (selectedProject) { - updateProject(selectedProject.id, formData); - setModalOpen(false); - setSelectedProject(null); - } else { - const newProjectId = createProject(formData); - if (newProjectId) { - switchProject(newProjectId); - router.push(`/?projectId=${newProjectId}`); - setModalOpen(false); - setSelectedProject(null); - } else { - alert("Maximum number of projects (8) reached"); - } - } - }; - - const handleDeleteProject = (projectId) => { - deleteProject(projectId); - setModalOpen(false); - setSelectedProject(null); - }; - - const handleCloseModal = () => { - setModalOpen(false); - setSelectedProject(null); - }; - - return ( - <> - - - - - - - ); -} - -function LoadingFallback() { - return ( - - - - ); -} - -export default function Home() { - return ( - }> - - - ); -} diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/page.module.css b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/page.module.css deleted file mode 100644 index e69de29bb..000000000 diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/apiClient.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/apiClient.js deleted file mode 100644 index a06e0b2ed..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/apiClient.js +++ /dev/null @@ -1,25 +0,0 @@ -"use client"; - -const API_BASE_URL = process.env.NEXT_PUBLIC_API_URL; -console.log("API_BASE_URL:", API_BASE_URL); - -async function request(endpoint, options = {}) { - const url = `${API_BASE_URL}${endpoint}`; - - try { - const response = await fetch(url, options); - - if (!response.ok) { - throw new Error(`API error: ${response.status}`); - } - - return await response.json(); - } catch (error) { - console.error(`Request failed: ${url}`, error); - throw error; - } -} - -export default { - request, -}; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/genaiAgentService.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/genaiAgentService.js deleted file mode 100644 index 10a86c091..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/genaiAgentService.js +++ /dev/null @@ -1,47 +0,0 @@ -"use client"; - -const createGenaiAgentService = () => { - const API_BASE_URL = - process.env.NEXT_PUBLIC_GENAI_API_URL || "http://localhost:8000"; - let sessionId = null; - - const sendMessage = async (text) => { - const payload = { - question: text, - context: "", - }; - - const response = await fetch(`${API_BASE_URL}/query`, { - method: "POST", - headers: { - "Content-Type": "application/json", - }, - body: JSON.stringify(payload), - }); - - if (!response.ok) { - throw new Error(`API Error: ${response.status}`); - } - - const data = await response.json(); - - // Transform backend response to match frontend expectations - return { - answer: data.agent_response || data.text_response || "No response", - response_type: data.response_type, - query: data.query, - dashboard: data.dashboard, - data: data.data, - insights: data.insights, - diagram_base64: data.chart_base64, // Map chart_base64 to diagram_base64 for frontend display - chart_config: data.chart_config, - method: data.method, - }; - }; - - return { - sendMessage, - }; -}; - -export default createGenaiAgentService; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/oracleSpeechService.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/oracleSpeechService.js deleted file mode 100644 index 610d5492c..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/oracleSpeechService.js +++ /dev/null @@ -1,81 +0,0 @@ -"use client"; - -const createOracleSpeechService = () => { - let ws = null; - let mediaRecorder = null; - let mediaStream = null; - let isRecording = false; - - const startRecording = async (onResult, onError) => { - try { - ws = new WebSocket("ws://localhost:3001/ws/speech"); - - ws.onopen = () => {}; - ws.onmessage = (event) => { - const data = JSON.parse(event.data); - if (data.type === "ready") { - } - if (data.type === "transcription") { - onResult({ transcript: data.text, isFinal: data.isFinal }); - } else if (data.type === "error") { - console.error("[Cliente] Oracle WS error:", data.message); - onError(data.message); - } - }; - ws.onerror = (err) => { - console.error("[Cliente][oracleSpeechService] 🔴 WS error:", err); - onError("WebSocket error"); - }; - ws.onclose = (ev) => {}; - - await new Promise((resolve) => { - ws.onopen = resolve; - }); - - mediaStream = await navigator.mediaDevices.getUserMedia({ - audio: { sampleRate: 16000, channelCount: 1 }, - }); - - mediaRecorder = new MediaRecorder(mediaStream); - mediaRecorder.ondataavailable = (event) => { - if (event.data.size > 0 && ws.readyState === WebSocket.OPEN) { - event.data.arrayBuffer().then((buffer) => { - ws.send(buffer); - }); - } - }; - mediaRecorder.onstart = () => - (mediaRecorder.onstop = () => - (mediaRecorder.onerror = (e) => - console.error("[Cliente] Recorder error:", e))); - - mediaRecorder.start(500); - isRecording = true; - return true; - } catch (error) { - console.error("[Cliente] startRecording error:", error); - onError(error.message); - return false; - } - }; - - const stopRecording = () => { - if (mediaRecorder) mediaRecorder.stop(); - if (mediaStream) mediaStream.getTracks().forEach((t) => t.stop()); - if (ws) ws.close(); - isRecording = false; - return true; - }; - - const isSupported = () => - !!(navigator.mediaDevices && window.MediaRecorder && window.WebSocket); - - return { - isSupported, - startRecording, - stopRecording, - isRecording: () => isRecording, - }; -}; - -export default createOracleSpeechService; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/speechService.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/speechService.js deleted file mode 100644 index c48a74319..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/services/speechService.js +++ /dev/null @@ -1,69 +0,0 @@ -const createSpeechService = () => { - let recognition = null; - - const isSupported = () => { - return "SpeechRecognition" in window || "webkitSpeechRecognition" in window; - }; - - const startListening = (onResult, onError) => { - if (!isSupported()) { - onError("Speech recognition is not supported in your browser"); - return false; - } - - try { - const SpeechRecognition = - window.SpeechRecognition || window.webkitSpeechRecognition; - recognition = new SpeechRecognition(); - - recognition.lang = "en-US"; - recognition.interimResults = true; - recognition.continuous = false; - - recognition.onresult = (event) => { - const transcript = Array.from(event.results) - .map((result) => result[0]) - .map((result) => result.transcript) - .join(""); - - onResult({ - transcript, - isFinal: event.results[event.results.length - 1].isFinal, - }); - }; - - recognition.onend = () => { - onResult({ stopped: true }); - }; - - recognition.onerror = (event) => { - console.error("Speech recognition error", event); - onError(event.error); - }; - - recognition.start(); - return true; - } catch (err) { - console.error("Error starting speech recognition:", err); - onError(err.message); - return false; - } - }; - - const stopListening = () => { - if (recognition) { - recognition.stop(); - recognition = null; - return true; - } - return false; - }; - - return { - isSupported, - startListening, - stopListening, - }; -}; - -export default createSpeechService; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/overrides.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/overrides.js deleted file mode 100644 index 59343cb7d..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/overrides.js +++ /dev/null @@ -1,56 +0,0 @@ -export const getComponentOverrides = (theme) => ({ - MuiButton: { - styleOverrides: { - root: { - textTransform: "none", - borderRadius: theme.shape.borderRadius * 2, - boxShadow: "none", - "&:hover": { - boxShadow: "none", - }, - }, - }, - }, - MuiAvatar: { - styleOverrides: { - root: { - fontSize: "0.875rem", - fontWeight: 600, - }, - }, - }, - MuiListItemButton: { - styleOverrides: { - root: { - borderRadius: "4px", - margin: "2px 0", - "&:hover": { - backgroundColor: "rgba(255,255,255,0.1)", - }, - }, - }, - }, - MuiListItemIcon: { - styleOverrides: { - root: { - minWidth: "36px", - }, - }, - }, - MuiDivider: { - styleOverrides: { - root: { - borderColor: "rgba(255,255,255,0.1)", - }, - }, - }, - MuiCard: { - styleOverrides: { - root: { - backgroundColor: theme.palette.background.paper, - boxShadow: "none", - border: "1px solid rgba(255,255,255,0.1)", - }, - }, - }, -}); diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/palette.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/palette.js deleted file mode 100644 index f9481c420..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/palette.js +++ /dev/null @@ -1,19 +0,0 @@ -export const palette = { - mode: "light", - primary: { - main: "#525252", - light: "#737373", - dark: "#404040", - contrastText: "#FFFFFF", - }, - secondary: { - main: "#3FB37F", - light: "#52C08D", - dark: "#36A071", - contrastText: "#EDEBE6", - }, - background: { - default: "#F5F5F5", - paper: "#FFFFFF", - }, -}; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/theme.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/theme.js deleted file mode 100644 index 04038c60e..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/theme/theme.js +++ /dev/null @@ -1,20 +0,0 @@ -"use client"; - -import { createTheme } from "@mui/material/styles"; -import { getComponentOverrides } from "./overrides"; -import { palette } from "./palette"; - -const theme = createTheme({ - palette, - typography: { - fontFamily: "var(--font-roboto)", - }, - shape: { - borderRadius: 14, - }, - spacing: 8, -}); - -theme.components = getComponentOverrides(theme); - -export default theme; diff --git a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/utils/messageUtils.js b/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/utils/messageUtils.js deleted file mode 100644 index 75a04111a..000000000 --- a/ai/gen-ai-agents/sql_graph_generator_dashboard/files/frontend/app/utils/messageUtils.js +++ /dev/null @@ -1,200 +0,0 @@ -export const createUserMessage = (text, userId) => { - return { - userId, - messagePayload: { - type: "text", - text: text.trim(), - }, - date: new Date().toISOString(), - from: null, - }; -}; - -export const createSuggestionRequest = (query, userId) => { - return { - userId, - messagePayload: { - type: "suggest", - query: query, - threshold: 5, - }, - }; -}; - -export const isFromBot = (message) => { - return message.from && message.from.type === "bot"; -}; - -export const isFromUser = (message) => { - return message.from === null; -}; - -export const getMessageType = (message) => { - return message.messagePayload?.type || "unknown"; -}; - -export const getMessageText = (message) => { - const payload = message.messagePayload; - if (!payload) return ""; - - switch (payload.type) { - case "text": - return payload.text; - case "card": - if (payload.cards && payload.cards.length > 0) { - const card = payload.cards[0]; - return card.title || card.description || "Card message"; - } - return "Card message"; - case "attachment": - return `Attachment: ${payload.attachment.type}`; - default: - return `Message of type: ${payload.type}`; - } -}; - -export const formatMessageTime = (dateString) => { - try { - const date = new Date(dateString); - return date.toLocaleTimeString([], { hour: "2-digit", minute: "2-digit" }); - } catch (e) { - return ""; - } -}; - -export const extractCodeBlocks = (text) => { - const codeBlockRegex = /```(\w+)?\n([\s\S]*?)\n```/g; - const matches = []; - let match; - - while ((match = codeBlockRegex.exec(text)) !== null) { - matches.push({ - language: match[1] || "", - code: match[2], - }); - } - - return matches; -}; - -export const convertMarkdownLinks = (text) => { - const linkRegex = /\[([^\]]+)\]\(([^)]+)\)/g; - return text.replace( - linkRegex, - '$1' - ); -}; - -export const processMessageContent = (text) => { - if (!text) return ""; - - const codeBlocks = extractCodeBlocks(text); - let processedText = text; - - codeBlocks.forEach((block, index) => { - const placeholder = `__CODE_BLOCK_${index}__`; - processedText = processedText.replace( - /```(\w+)?\n([\s\S]*?)\n```/, - placeholder - ); - }); - - processedText = convertMarkdownLinks(processedText); - - codeBlocks.forEach((block, index) => { - const placeholder = `__CODE_BLOCK_${index}__`; - const formattedCode = `
${block.code}
`; - processedText = processedText.replace(placeholder, formattedCode); - }); - - return processedText; -}; - -export const formatConversationTime = (dateString) => { - try { - const date = new Date(dateString); - const now = new Date(); - const diffInHours = Math.floor((now - date) / (1000 * 60 * 60)); - - if (diffInHours < 24) { - return date.toLocaleTimeString([], { - hour: "2-digit", - minute: "2-digit", - }); - } else if (diffInHours < 48) { - return "Yesterday"; - } else { - return date.toLocaleDateString([], { month: "short", day: "numeric" }); - } - } catch (e) { - return ""; - } -}; - -export const truncateText = (text, maxLength = 60) => { - if (!text) return ""; - if (text.length <= maxLength) return text; - - return text.substring(0, maxLength).trim() + "..."; -}; - -export const sanitizeHtml = (html) => { - if (!html) return ""; - - return html - .replace(/)<[^<]*)*<\/script>/gi, "") - .replace(/on\w+="[^"]*"/g, "") - .replace(/javascript:/g, ""); -}; - -export const hasImage = (message) => { - const payload = message.messagePayload; - if (!payload) return false; - - if ( - payload.type === "attachment" && - payload.attachment && - payload.attachment.type.startsWith("image/") - ) { - return true; - } - - if (payload.type === "card" && payload.cards) { - return payload.cards.some((card) => card.imageUrl); - } - - return false; -}; - -export const messageToShareableFormat = (message) => { - if (!message || !message.messagePayload) return ""; - - const isBot = isFromBot(message); - const sender = isBot ? "ChatBPI" : "You"; - const content = getMessageText(message); - const time = formatMessageTime(message.date); - - return `${sender} (${time}): ${content}`; -}; - -export const adaptSdkMessage = (sdkMessage, userId) => { - if (!sdkMessage || !sdkMessage.messagePayload) { - console.warn("Invalid message format received from SDK"); - return { - userId: userId, - messagePayload: { - type: "text", - text: "Sorry, I received an invalid message.", - }, - date: new Date().toISOString(), - from: { type: "bot" }, - }; - } - - return { - userId: userId, - messagePayload: sdkMessage.messagePayload, - date: new Date().toISOString(), - from: { type: "bot" }, - }; -};