import os import sys import tempfile import time import itertools import streamlit as st import pandas as pd from threading import Thread from io import StringIO # Add 'src' to Python path so we can import main.py sys.path.append(os.path.join(os.path.dirname(__file__), 'src')) from main import run_pipeline st.set_page_config(page_title="📰 AI News Analyzer", layout="wide") st.title("🧠 AI-Powered Investing News Analyzer") # === API Key Input === st.subheader("🔐 API Keys") openai_api_key = st.text_input("OpenAI API Key", type="password").strip() tavily_api_key = st.text_input("Tavily API Key", type="password").strip() # === Topic Input === st.subheader("📈 Topics of Interest") topics_data = [] with st.form("topics_form"): topic_count = st.number_input("How many topics?", min_value=1, max_value=10, value=1, step=1) for i in range(topic_count): col1, col2 = st.columns(2) with col1: topic = st.text_input(f"Topic {i+1}", key=f"topic_{i}") with col2: days = st.number_input(f"Timespan (days)", min_value=1, max_value=30, value=7, key=f"days_{i}") topics_data.append({"topic": topic, "timespan_days": days}) submitted = st.form_submit_button("Run Analysis") # === Submission logic === if submitted: if not openai_api_key or not tavily_api_key or not all([td['topic'] for td in topics_data]): st.warning("Please fill in all fields.") else: os.environ["OPENAI_API_KEY"] = openai_api_key os.environ["TAVILY_API_KEY"] = tavily_api_key df = pd.DataFrame(topics_data) with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp_csv: df.to_csv(tmp_csv.name, index=False) csv_path = tmp_csv.name # === UI Elements === spinner_box = st.empty() # For rotating messages log_box = st.empty() # For logs logs = [] rotating = True def log(msg): logs.append(msg) log_box.code("\n".join(logs)) # === Rotating UI Messages === def rotating_messages(): messages = itertools.cycle([ "🔍 Searching financial news...", "🧠 Running language models...", "📊 Analyzing investor sentiment...", "📝 Summarizing key takeaways...", "💹 Building markdown reports..." ]) while rotating: spinner_box.markdown(f"⏳ {next(messages)}") time.sleep(1.5) rotator_thread = Thread(target=rotating_messages) rotator_thread.start() try: # Check API Keys import openai openai.OpenAI(api_key=openai_api_key).models.list() log("✅ OpenAI API key is valid.") import requests tavily_test = requests.post( "https://api.tavily.com/search", headers={"Authorization": f"Bearer {tavily_api_key}"}, json={"query": "test", "days": 1, "max_results": 1} ) if tavily_test.status_code == 200: log("✅ Tavily API key is valid.") else: raise ValueError(f"Tavily error: {tavily_test.status_code} - {tavily_test.text}") # Run the full pipeline log("🚀 Running analysis pipeline...") output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=log) rotating = False rotator_thread.join() spinner_box.success("✅ Analysis complete!") if output_path and isinstance(output_path, list): for path in output_path: if os.path.exists(path): with open(path, 'r', encoding='utf-8') as file: html_content = file.read() filename = os.path.basename(path) st.download_button( label=f"📥 Download {filename}", data=html_content, file_name=filename, mime="text/html" ) st.components.v1.html(html_content, height=600, scrolling=True) else: st.error("❌ No reports were generated.") except Exception as e: rotating = False rotator_thread.join() spinner_box.error("❌ Failed.") log_box.error(f"❌ Error: {e}") ################################################################################################## ################################################################################################## # import os # import sys # import tempfile # import streamlit as st # import pandas as pd # from io import StringIO # # Add 'src' to Python path so we can import main.py # sys.path.append(os.path.join(os.path.dirname(__file__), 'src')) # from main import run_pipeline # st.set_page_config(page_title="📰 AI News Analyzer", layout="wide") # st.title("🧠 AI-Powered Investing News Analyzer") # # === API Key Input === # st.subheader("🔐 API Keys") # openai_api_key = st.text_input("OpenAI API Key", type="password").strip() # tavily_api_key = st.text_input("Tavily API Key", type="password").strip() # # === Topic Input === # st.subheader("📈 Topics of Interest") # topics_data = [] # with st.form("topics_form"): # topic_count = st.number_input("How many topics?", min_value=1, max_value=10, value=1, step=1) # for i in range(topic_count): # col1, col2 = st.columns(2) # with col1: # topic = st.text_input(f"Topic {i+1}", key=f"topic_{i}") # with col2: # days = st.number_input(f"Timespan (days)", min_value=1, max_value=30, value=7, key=f"days_{i}") # topics_data.append({"topic": topic, "timespan_days": days}) # submitted = st.form_submit_button("Run Analysis") # # === Submission logic === # if submitted: # if not openai_api_key or not tavily_api_key or not all([td['topic'] for td in topics_data]): # st.warning("Please fill in all fields.") # else: # os.environ["OPENAI_API_KEY"] = openai_api_key # os.environ["TAVILY_API_KEY"] = tavily_api_key # df = pd.DataFrame(topics_data) # with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp_csv: # df.to_csv(tmp_csv.name, index=False) # csv_path = tmp_csv.name # progress_box = st.empty() # def show_progress(msg): # progress_box.markdown(f"⏳ {msg}") # try: # output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=show_progress) # progress_box.success("✅ Analysis complete!") # if output_path and isinstance(output_path, list): # for path in output_path: # if os.path.exists(path): # with open(path, 'r', encoding='utf-8') as file: # html_content = file.read() # filename = os.path.basename(path) # st.download_button( # label=f"📥 Download {filename}", # data=html_content, # file_name=filename, # mime="text/html" # ) # st.components.v1.html(html_content, height=600, scrolling=True) # else: # st.error("❌ No reports were generated.") # except Exception as e: # progress_box.error(f"❌ Error: {e}")