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import gradio as gr |
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from urllib.request import urlopen |
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import certifi |
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import json |
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import pandas as pd |
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import os |
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import warnings |
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import re |
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warnings.filterwarnings("ignore") |
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from langchain_community.document_loaders import CSVLoader |
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from langchain_community.vectorstores import Chroma |
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from langchain.text_splitter import RecursiveCharacterTextSplitter |
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from langchain_community.embeddings import HuggingFaceEmbeddings |
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from langchain.chains import RetrievalQA |
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from langchain.prompts import PromptTemplate |
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from langchain_community.llms import HuggingFacePipeline |
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline |
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os.environ["HUGGINGFACEHUB_API_TOKEN"] = os.environ.get("HUGGINGFACEHUB_API_TOKEN") |
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model_id = "tiiuae/Falcon3-3B-Instruct" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained(model_id) |
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pipe = pipeline( |
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"text-generation", |
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model=model, |
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tokenizer=tokenizer, |
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max_new_tokens=512, |
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do_sample=True, |
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temperature=0.1, |
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top_k=50, |
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top_p=0.95, |
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eos_token_id=tokenizer.eos_token_id, |
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) |
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llm = HuggingFacePipeline(pipeline=pipe) |
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template = """ |
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You are a Financial Market Expert. Analyze the provided market data and create a comprehensive financial report. |
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Market Data: {context} |
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Company: {question} |
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Please provide a detailed analysis including: |
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1. Current stock performance metrics |
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2. Price movements and trends |
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3. Market capitalization details |
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4. Trading volume analysis |
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5. Key financial indicators |
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Format the response as a clear, professional financial report with proper sections and bullet points. |
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""" |
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PROMPT = PromptTemplate(input_variables=["context", "question"], template=template) |
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def format_currency(value): |
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"""Format currency values""" |
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try: |
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if isinstance(value, (int, float)): |
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return f"${value:,.2f}" |
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return str(value) |
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except: |
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return str(value) |
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def format_percentage(value): |
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"""Format percentage values""" |
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try: |
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if isinstance(value, (int, float)): |
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return f"{value:.2f}%" |
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return str(value) |
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except: |
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return str(value) |
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def create_html_report(data, llm_analysis): |
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"""Create a formatted HTML report""" |
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if not data or len(data) == 0: |
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return "<div class='error'>No data available for this ticker.</div>" |
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stock_data = data[0] if isinstance(data, list) else data |
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symbol = stock_data.get('symbol', 'N/A') |
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name = stock_data.get('name', 'N/A') |
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price = stock_data.get('price', 0) |
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change = stock_data.get('change', 0) |
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change_percent = stock_data.get('changesPercentage', 0) |
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market_cap = stock_data.get('marketCap', 0) |
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volume = stock_data.get('volume', 0) |
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avg_volume = stock_data.get('avgVolume', 0) |
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pe_ratio = stock_data.get('pe', 'N/A') |
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eps = stock_data.get('eps', 'N/A') |
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trend_color = "#22c55e" if change >= 0 else "#ef4444" |
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trend_icon = "📈" if change >= 0 else "📉" |
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html = f""" |
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<div style="font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; max-width: 800px; margin: 0 auto;"> |
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<!-- Header Section --> |
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<div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 25px; border-radius: 12px; margin-bottom: 20px; box-shadow: 0 4px 15px rgba(0,0,0,0.1);"> |
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<h1 style="margin: 0 0 10px 0; font-size: 28px; font-weight: 600;">{symbol} - Financial Report</h1> |
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<h2 style="margin: 0; font-size: 18px; font-weight: 400; opacity: 0.9;">{name}</h2> |
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<div style="margin-top: 15px; font-size: 14px; opacity: 0.8;"> |
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📅 Generated on {pd.Timestamp.now().strftime('%Y-%m-%d %H:%M:%S')} |
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</div> |
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</div> |
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<!-- Key Metrics Grid --> |
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<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 15px; margin-bottom: 25px;"> |
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<!-- Current Price Card --> |
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<div style="background: white; border-radius: 10px; padding: 20px; box-shadow: 0 2px 10px rgba(0,0,0,0.1); border-left: 4px solid #3b82f6;"> |
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<div style="color: #6b7280; font-size: 14px; margin-bottom: 5px;">Current Price</div> |
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<div style="font-size: 24px; font-weight: 700; color: #1f2937;">{format_currency(price)}</div> |
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</div> |
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<!-- Price Change Card --> |
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<div style="background: white; border-radius: 10px; padding: 20px; box-shadow: 0 2px 10px rgba(0,0,0,0.1); border-left: 4px solid {trend_color};"> |
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<div style="color: #6b7280; font-size: 14px; margin-bottom: 5px;">Price Change {trend_icon}</div> |
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<div style="font-size: 18px; font-weight: 600; color: {trend_color};"> |
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{format_currency(change)} ({format_percentage(change_percent)}) |
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</div> |
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</div> |
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<!-- Market Cap Card --> |
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<div style="background: white; border-radius: 10px; padding: 20px; box-shadow: 0 2px 10px rgba(0,0,0,0.1); border-left: 4px solid #10b981;"> |
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<div style="color: #6b7280; font-size: 14px; margin-bottom: 5px;">Market Cap</div> |
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<div style="font-size: 18px; font-weight: 600; color: #1f2937;"> |
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{format_currency(market_cap) if market_cap else 'N/A'} |
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</div> |
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</div> |
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<!-- Volume Card --> |
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<div style="background: white; border-radius: 10px; padding: 20px; box-shadow: 0 2px 10px rgba(0,0,0,0.1); border-left: 4px solid #f59e0b;"> |
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<div style="color: #6b7280; font-size: 14px; margin-bottom: 5px;">Volume</div> |
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<div style="font-size: 18px; font-weight: 600; color: #1f2937;"> |
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{f"{volume:,}" if volume else 'N/A'} |
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</div> |
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</div> |
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</div> |
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<!-- Additional Metrics Table --> |
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<div style="background: white; border-radius: 10px; padding: 25px; box-shadow: 0 2px 10px rgba(0,0,0,0.1); margin-bottom: 25px;"> |
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<h3 style="margin: 0 0 20px 0; color: #1f2937; font-size: 20px; font-weight: 600; border-bottom: 2px solid #e5e7eb; padding-bottom: 10px;"> |
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📊 Detailed Metrics |
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</h3> |
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<table style="width: 100%; border-collapse: collapse;"> |
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<tr style="border-bottom: 1px solid #e5e7eb;"> |
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<td style="padding: 12px 0; font-weight: 600; color: #374151; width: 40%;">P/E Ratio</td> |
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<td style="padding: 12px 0; color: #6b7280;">{pe_ratio}</td> |
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</tr> |
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<tr style="border-bottom: 1px solid #e5e7eb;"> |
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<td style="padding: 12px 0; font-weight: 600; color: #374151;">Earnings Per Share (EPS)</td> |
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<td style="padding: 12px 0; color: #6b7280;">{format_currency(eps) if eps != 'N/A' else 'N/A'}</td> |
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</tr> |
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<tr style="border-bottom: 1px solid #e5e7eb;"> |
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<td style="padding: 12px 0; font-weight: 600; color: #374151;">Average Volume</td> |
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<td style="padding: 12px 0; color: #6b7280;">{f"{avg_volume:,}" if avg_volume else 'N/A'}</td> |
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</tr> |
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<tr> |
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<td style="padding: 12px 0; font-weight: 600; color: #374151;">Exchange</td> |
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<td style="padding: 12px 0; color: #6b7280;">{stock_data.get('exchange', 'N/A')}</td> |
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</tr> |
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</table> |
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</div> |
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<!-- AI Analysis Section --> |
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<div style="background: white; border-radius: 10px; padding: 25px; box-shadow: 0 2px 10px rgba(0,0,0,0.1);"> |
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<h3 style="margin: 0 0 20px 0; color: #1f2937; font-size: 20px; font-weight: 600; border-bottom: 2px solid #e5e7eb; padding-bottom: 10px;"> |
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🤖 AI Analysis |
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</h3> |
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<div style="background: #f8fafc; border-radius: 8px; padding: 20px; border-left: 4px solid #6366f1;"> |
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<pre style="white-space: pre-wrap; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; margin: 0; line-height: 1.6; color: #374151;">{llm_analysis}</pre> |
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</div> |
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</div> |
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<!-- Footer --> |
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<div style="text-align: center; margin-top: 25px; padding: 20px; color: #6b7280; font-size: 14px; border-top: 1px solid #e5e7eb;"> |
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<p style="margin: 0;">⚠️ This report is for informational purposes only and should not be considered as investment advice.</p> |
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</div> |
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</div> |
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""" |
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return html |
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def generate_report(ticker: str, exchange: str): |
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"""Generate enhanced financial report""" |
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api_key = "C1HRSweTniWdBuLmTTse9w8KpkoiouM5" |
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if not ticker.strip(): |
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return "<div style='color: red; padding: 20px; text-align: center;'>❌ Please enter a valid ticker symbol.</div>" |
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try: |
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loading_html = """ |
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<div style="text-align: center; padding: 40px; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;"> |
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<div style="display: inline-block; padding: 20px; background: #f0f9ff; border-radius: 10px; border: 1px solid #0ea5e9;"> |
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<div style="font-size: 18px; color: #0369a1; margin-bottom: 10px;">🔄 Generating Report...</div> |
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<div style="color: #64748b;">Fetching data and running AI analysis</div> |
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</div> |
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</div> |
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""" |
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ticker = ticker.upper().strip() |
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if exchange == "NSE": |
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url = f"https://financialmodelingprep.com/api/v3/search?query={ticker}&exchange=NSE&apikey={api_key}" |
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else: |
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url = f"https://financialmodelingprep.com/api/v3/quote/{ticker}?apikey={api_key}" |
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response = urlopen(url, cafile=certifi.where()) |
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data = json.loads(response.read().decode("utf-8")) |
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if not data: |
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return "<div style='color: red; padding: 20px; text-align: center;'>❌ No data found for ticker: " + ticker + "</div>" |
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df = pd.DataFrame(data) |
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if 'timestamp' in df.columns: |
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df['timestamp'] = pd.to_datetime(df['timestamp'], errors='coerce') |
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if 'earningsAnnouncement' in df.columns: |
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df['earningsAnnouncement'] = pd.to_datetime(df['earningsAnnouncement'], errors='coerce') |
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df.to_csv("eco_ind.csv", index=False) |
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loader = CSVLoader("eco_ind.csv") |
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documents = loader.load() |
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splitter = RecursiveCharacterTextSplitter(chunk_size=200, chunk_overlap=20) |
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texts = splitter.split_documents(documents) |
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embeddings = HuggingFaceEmbeddings() |
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chroma = Chroma.from_documents( |
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documents=texts, |
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collection_name="economic_data", |
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embedding=embeddings, |
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persist_directory="docs/chroma_rag" |
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) |
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retriever = chroma.as_retriever(search_kwargs={"k": 3}) |
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qa = RetrievalQA.from_chain_type( |
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llm=llm, |
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chain_type="stuff", |
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chain_type_kwargs={"prompt": PROMPT}, |
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retriever=retriever, |
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return_source_documents=False |
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) |
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query = f"Provide a comprehensive financial analysis for {ticker}" |
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result = qa({"query": query}) |
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llm_analysis = result["result"] |
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return create_html_report(data, llm_analysis) |
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except Exception as e: |
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error_html = f""" |
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<div style="font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; max-width: 600px; margin: 20px auto; padding: 25px; background: #fef2f2; border-radius: 10px; border: 1px solid #fecaca;"> |
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<h3 style="color: #dc2626; margin: 0 0 15px 0; display: flex; align-items: center;"> |
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❌ Error Occurred |
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</h3> |
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<div style="background: white; padding: 15px; border-radius: 6px; border: 1px solid #f3f4f6;"> |
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<strong>Details:</strong> {str(e)} |
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</div> |
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<div style="margin-top: 15px; color: #6b7280; font-size: 14px;"> |
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Please check your ticker symbol and try again. Make sure you have a stable internet connection. |
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</div> |
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</div> |
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""" |
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return error_html |
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custom_css = """ |
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#component-0 { |
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max-width: 1200px !important; |
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margin: 0 auto !important; |
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} |
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.gradio-container { |
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background-color: black !important; |
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min-height: 100vh !important; |
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} |
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#title { |
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text-align: center !important; |
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color: white !important; |
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font-size: 2.5rem !important; |
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font-weight: 700 !important; |
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margin-bottom: 1rem !important; |
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text-shadow: 0 2px 4px rgba(0,0,0,0.1) !important; |
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} |
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#description { |
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text-align: center !important; |
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color: white !important; |
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font-size: 1.1rem !important; |
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margin-bottom: 2rem !important; |
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} |
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.input-container { |
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background: white !important; |
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border-radius: 5px !important; |
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padding: 3px !important; |
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box-shadow: 0 10px 30px rgba(0,0,0,0.1) !important; |
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margin-bottom: 20px !important; |
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} |
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.output-container { |
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background: transparent !important; |
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border-radius: 15px !important; |
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padding: 10px; |
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border: 2px white solid ; |
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overflow: hidden !important; |
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box-shadow: 0 10px 30px rgba(0,0,0,0.2) !important; |
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} |
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""" |
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with gr.Blocks(css=custom_css, title="📊 Financial Report Generator") as iface: |
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gr.HTML('<div id="title">📊 AI-Powered Financial Report Generator</div>') |
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gr.HTML('<div id="description">Enter a stock ticker and exchange to get a comprehensive AI-generated financial analysis</div>') |
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with gr.Sidebar(): |
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gr.Markdown("## 📥 Input Parameters") |
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ticker_input = gr.Textbox( |
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label="🎯 Stock Ticker Symbol", |
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placeholder="e.g., MSFT, AAPL, GOOGL", |
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info="Enter the stock symbol you want to analyze" |
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) |
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exchange_input = gr.Radio( |
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choices=["US", "NSE"], |
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label="🏢 Exchange", |
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value="US", |
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info="Select the stock exchange" |
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) |
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generate_btn = gr.Button( |
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"🚀 Generate Report", |
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variant="primary" |
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) |
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clear_btn = gr.Button( |
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"🔄 Clear", |
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variant="secondary" |
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) |
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with gr.Row(elem_classes=["output-container"]): |
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output = gr.HTML(label="📊 Financial Report") |
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generate_btn.click( |
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fn=generate_report, |
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inputs=[ticker_input, exchange_input], |
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outputs=output |
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) |
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clear_btn.click( |
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lambda: ["", "US", ""], |
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outputs=[ticker_input, exchange_input, output] |
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) |
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ticker_input.submit( |
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fn=generate_report, |
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inputs=[ticker_input, exchange_input], |
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outputs=output |
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) |
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if __name__ == "__main__": |
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iface.launch( |
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share=True, |
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show_error=True |
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) |
