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import streamlit as st
import yfinance as yf
import requests
import pandas as pd
from langchain.agents import initialize_agent, AgentType
from langchain.tools import Tool
from langchain_huggingface import HuggingFacePipeline
import os
from dotenv import load_dotenv
from transformers import AutoModelForCausalLM, AutoTokenizer,pipeline
import torch
load_dotenv()
NEWSAPI_KEY = os.getenv("NEWSAPI_KEY")
access_token = os.getenv("API_KEY")
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b-it", token = access_token)
model = AutoModelForCausalLM.from_pretrained(
"google/gemma-2b-it",
torch_dtype=torch.bfloat16,
token = access_token
)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=100, top_k=50, temperature=0.1)
def fetch_stock_data(ticker):
print("fetching stock data")
stock = yf.Ticker(ticker)
hist = stock.history(period="1mo")
return hist.tail(5)
def fetch_stock_news(ticker, NEWSAPI_KEY):
print("fetching stock news")
api_url = f"https://newsapi.org/v2/everything?q={ticker}&apiKey={NEWSAPI_KEY}"
response = requests.get(api_url)
if response.status_code == 200:
articles = response.json().get('articles', [])
return [{"title": article['title'], "description": article['description']} for article in articles[:5]]
else:
return [{"error": "Unable to fetch news."}]
def calculate_moving_average(ticker, window=5):
print("calculating moving average")
stock = yf.Ticker(ticker)
hist = stock.history(period="1mo")
hist[f"{window}-day MA"] = hist["Close"].rolling(window=window).mean()
return hist[["Close", f"{window}-day MA"]].tail(5)
llm = HuggingFacePipeline(pipeline=pipe)
stock_data_tool = Tool(
name="Stock Data Fetcher",
func=fetch_stock_data,
description="Fetch recent stock data for a given ticker."
)
stock_news_tool = Tool(
name="Stock News Fetcher",
func=lambda ticker: fetch_stock_news(ticker, NEWSAPI_KEY),
description="Fetch recent news articles about a stock ticker."
)
moving_average_tool = Tool(
name="Moving Average Calculator",
func=calculate_moving_average,
description="Calculate the moving average of a stock over a 5-day window."
)
tools = [stock_data_tool, stock_news_tool, moving_average_tool]
agent = initialize_agent(
tools=tools,
llm=llm,
agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
verbose=True
)
st.title("Trading Helper Agent")
query = st.text_input("Enter your query:")
if st.button("Submit"):
if query:
with st.spinner("Processing..."):
try:
response = agent.run(query)
print(f"Response: {response}")
st.success("Response:")
st.write(response)
except Exception as e:
st.error(f"An error occurred: {e}")
else:
st.warning("Please enter a query.")
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