| import os |
| import time |
| from datetime import datetime |
|
|
| import schedule |
| import telebot |
| from dotenv import load_dotenv |
| from langchain_chroma import Chroma |
| from langchain_community.tools import DuckDuckGoSearchRun |
| from langchain_core.messages import HumanMessage, SystemMessage |
| from langchain_huggingface import HuggingFaceEmbeddings |
| from langchain_openai import ChatOpenAI |
|
|
| from news_price_correlation import build_correlation_analysis |
| from nvidia_agent_core import forecast_markdown, predict_nvidia_stock_payload, route_query |
|
|
|
|
| load_dotenv() |
|
|
| BOT_TOKEN = os.getenv("TELEGRAM_BOT_TOKEN") |
| CHAT_ID = os.getenv("TELEGRAM_CHAT_ID") |
| USE_WEBHOOK = os.getenv("USE_WEBHOOK", "False").lower() == "true" |
| WEBHOOK_URL = os.getenv("RENDER_WEBHOOK_URL") |
|
|
| if not BOT_TOKEN or not CHAT_ID: |
| raise ValueError("TELEGRAM_BOT_TOKEN or TELEGRAM_CHAT_ID not found in .env") |
|
|
| bot = telebot.TeleBot(BOT_TOKEN, parse_mode="Markdown") |
| llm = ChatOpenAI(model="gpt-5.4", temperature=0.3, max_tokens=1024) |
| ddg_search = DuckDuckGoSearchRun() |
|
|
| vectorstore = None |
| try: |
| import chromadb |
| from chromadb.config import Settings |
|
|
| embeddings = HuggingFaceEmbeddings(model_name="all-mpnet-base-v2") |
| client = chromadb.PersistentClient(path="./chroma_db_v2", settings=Settings(allow_reset=True)) |
| vectorstore = Chroma( |
| client=client, |
| collection_name="nvidia_annual_reports_2014_2025", |
| embedding_function=embeddings, |
| ) |
| print("RAG loaded successfully") |
| except Exception as exc: |
| print(f"RAG load failed; continuing without it: {exc}") |
|
|
|
|
| def truncate_telegram(text: str, limit: int = 3800) -> str: |
| return text[:limit] + "\n\n... (truncated)" if len(text) > limit else text |
|
|
|
|
| def trader_forecast() -> str: |
| try: |
| payload = predict_nvidia_stock_payload(periods=7) |
| return truncate_telegram(forecast_markdown(payload)) |
| except Exception as exc: |
| return f"Forecast error: {exc}" |
|
|
|
|
| def correlation_answer(query: str) -> str: |
| try: |
| answer = build_correlation_analysis( |
| query=query, |
| search=ddg_search.run, |
| llm=llm, |
| csv_path="nvda_2014_to_2026.csv", |
| ) |
| return truncate_telegram(answer) |
| except Exception as exc: |
| return f"Correlation analysis error: {exc}" |
|
|
|
|
| def researcher_answer(query: str) -> str: |
| context = "" |
| if vectorstore: |
| docs = vectorstore.similarity_search(query, k=4) |
| context = "\n\n".join(doc.page_content[:600] for doc in docs) |
|
|
| news = ddg_search.run(f"NVIDIA {query} latest news OR Blackwell OR Huawei")[:900] |
| response = llm.invoke( |
| [ |
| SystemMessage(content="You are a senior NVIDIA strategy analyst. Give concise, evidence-aware answers."), |
| HumanMessage(content=f"Question: {query}\n\nAnnual-report context:\n{context}\n\nNews:\n{news}"), |
| ] |
| ).content |
| return truncate_telegram(response) |
|
|
|
|
| def answer_query(query: str) -> str: |
| route = route_query(query) |
| if route == "correlation_agent": |
| return correlation_answer(query) |
| if route == "ML_agent": |
| return trader_forecast() |
| return researcher_answer(query) |
|
|
|
|
| @bot.message_handler(commands=["start", "help"]) |
| def send_welcome(message): |
| bot.reply_to( |
| message, |
| "NVIDIA Bot is online.\n\n" |
| "/forecast - 7-business-day Prophet v3 residual ensemble forecast\n" |
| "/news - latest NVIDIA news\n" |
| "/correlate <event> - news/event to price-impact analysis or geopolitical shock stress test", |
| ) |
|
|
|
|
| @bot.message_handler(commands=["forecast"]) |
| def send_forecast(message): |
| bot.reply_to(message, trader_forecast()) |
|
|
|
|
| @bot.message_handler(commands=["news"]) |
| def send_news(message): |
| bot.reply_to(message, truncate_telegram(ddg_search.run("NVIDIA latest news"))) |
|
|
|
|
| @bot.message_handler(commands=["correlate"]) |
| def send_correlation(message): |
| query = message.text.replace("/correlate", "", 1).strip() |
| if not query: |
| query = "Nvidia China Huawei export controls selloff May 2026" |
| bot.reply_to(message, correlation_answer(query)) |
|
|
|
|
| @bot.message_handler(func=lambda message: True) |
| def handle_message(message): |
| bot.send_chat_action(message.chat.id, "typing") |
| bot.reply_to(message, answer_query(message.text.strip())) |
|
|
|
|
| def send_daily_alert(): |
| forecast = trader_forecast() |
| news = truncate_telegram(ddg_search.run("NVIDIA latest news OR Blackwell OR earnings"), limit=800) |
| alert = f"NVIDIA DAILY ALERT {datetime.now().strftime('%Y-%m-%d %H:%M')}\n\n{forecast}\n\nNews:\n{news}" |
| try: |
| bot.send_message(CHAT_ID, truncate_telegram(alert)) |
| print(f"Daily alert sent at {datetime.now()}") |
| except Exception as exc: |
| print(f"Alert error: {exc}") |
|
|
|
|
| if __name__ == "__main__": |
| print("Nvidia_bot starting...") |
| send_daily_alert() |
| schedule.every(60).minutes.do(send_daily_alert) |
|
|
| if USE_WEBHOOK and WEBHOOK_URL: |
| bot.remove_webhook() |
| time.sleep(1) |
| bot.set_webhook(url=WEBHOOK_URL) |
| print(f"Webhook set to: {WEBHOOK_URL}") |
| while True: |
| schedule.run_pending() |
| time.sleep(60) |
| else: |
| print("Using polling mode...") |
| while True: |
| try: |
| schedule.run_pending() |
| bot.polling(none_stop=True, interval=1, timeout=30) |
| except Exception as exc: |
| print(f"Polling error: {exc}") |
| time.sleep(10) |
|
|
