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| import os | |
| import streamlit as st | |
| import requests | |
| #hello world | |
| # Create a session for reusing connections | |
| session = requests.Session() | |
| # Function to interact with the AI | |
| def chat_with_ai(message, user_input): | |
| api_url = os.getenv("CHAT_API_URL") # Vortex 3b models API | |
| payload = {"message": message, "user_input": user_input} | |
| try: | |
| with session.post(api_url, json=payload) as response: | |
| if response.status_code == 200: | |
| return response.json().get('response') # Access 'response' key | |
| else: | |
| st.error("Failed to get a response from the AI API. 😞") | |
| except requests.RequestException as e: | |
| st.error(f"Error: {e}") | |
| # Function to perform web search | |
| def web_search(query): | |
| url = os.getenv("SEARCH_API_URL") # Webscout API | |
| payload = {"query": query} | |
| response = requests.post(url, json=payload) | |
| if response.status_code == 200: | |
| return response.json() | |
| else: | |
| st.error(f"Error: {response.status_code}") | |
| # Main function | |
| def main(): | |
| st.set_page_config(page_title='HelpingAI Research Assistant', page_icon=":mag:") | |
| st.title("🔍 HelpingAI Research Assistant") | |
| st.sidebar.header("🛠️ Settings") | |
| query = st.sidebar.text_input("🔎 Enter your research query: ") | |
| generate_report = st.sidebar.button("📝 Generate Report") | |
| st.sidebar.markdown("---") | |
| st.sidebar.header("📚 Recent Reports") | |
| recent_reports = st.sidebar.empty() # Placeholder for recent reports | |
| st.sidebar.markdown("---") | |
| st.sidebar.header("ℹ️ About this App") | |
| st.sidebar.info("This app uses chat and web search APIs by HelpingAI. The founder of HelpingAI is Abhay Koul. The web search API used in this app is publicly available and its name is Webscout API. For any inquiries or assistance, please contact the developer: Telegram: @OEvortex, Email: [email protected].") | |
| st.sidebar.markdown("---") | |
| st.sidebar.header("🌐 How to Get Webscout API") | |
| st.sidebar.info(""" | |
| 1. Sign up for a RapidAPI account if you haven't already. | |
| 2. Subscribe to the "webscout-api" on the RapidAPI marketplace to acquire your API key. | |
| 3. Choose the pricing tier that best fits your usage needs and budget. | |
| 4. Integrate the API into your applications using the provided endpoints. | |
| """) | |
| st.sidebar.markdown("---") | |
| st.sidebar.markdown("© 2024 HelpingAI. All rights reserved.") | |
| if generate_report: | |
| if query: | |
| with st.spinner('🔄 Searching...'): | |
| # Perform web search | |
| search_results = web_search(query) | |
| # Pass the search results to the AI for generating a report | |
| prompt = f"Generate a detailed research report based on the following information: {search_results}. The user's query was: '{query}'. Please include an overview, key findings, and any relevant details in the report. If the search results are insufficient, answer the user's question using the information available." | |
| with st.spinner('🔄 Generating report...'): | |
| report = chat_with_ai(prompt, query) | |
| # Display the report | |
| if isinstance(report, dict) and 'error' in report: | |
| st.error(report['error']) | |
| else: | |
| st.write(report) | |
| # Update recent reports | |
| recent_reports.text(query) | |
| else: | |
| st.sidebar.error("❗ Please enter a research query.") | |
| if __name__ == "__main__": | |
| main() | |