fixed by chatgpt

app.py

@@ -7,27 +7,27 @@ from langchain.tools import Tool
 from langchain_huggingface import HuggingFacePipeline
 import os
 from dotenv import load_dotenv
-from transformers import AutoModelForCausalLM, AutoTokenizer,pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 import torch
 
-
+# Load environment variables from .env
 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)
+# Initialize the model and tokenizer for the HuggingFace pipeline
+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
+    token=access_token
 )
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=2048)
 
+# Define functions for fetching stock data, news, and moving averages
 def validate_ticker(ticker):
-    # Ensure ticker is uppercase and length is reasonable (1-5 characters)
     return ticker.strip().upper()
 
-
 def fetch_stock_data(ticker):
     try:
         ticker = ticker.strip().upper()
@@ -39,7 +39,6 @@ def fetch_stock_data(ticker):
     except Exception as e:
         return {"error": str(e)}
 
-
 def fetch_stock_news(ticker, NEWSAPI_KEY):
     api_url = f"https://newsapi.org/v2/everything?q={ticker}&apiKey={NEWSAPI_KEY}"
     response = requests.get(api_url)
@@ -55,15 +54,16 @@ def calculate_moving_average(ticker, window=5):
     hist[f"{window}-day MA"] = hist["Close"].rolling(window=window).mean()
     return hist[["Close", f"{window}-day MA"]].tail(5)
 
+# Initialize HuggingFace pipeline
 llm = HuggingFacePipeline(pipeline=pipe)
 
+# Define LangChain tools
 stock_data_tool = Tool(
     name="Stock Data Fetcher",
     func=fetch_stock_data,
     description="Fetch recent stock data for a valid stock ticker symbol (e.g., AAPL for Apple)."
 )
 
-
 stock_news_tool = Tool(
     name="Stock News Fetcher",
     func=lambda ticker: fetch_stock_news(ticker, NEWSAPI_KEY),
@@ -78,6 +78,7 @@ moving_average_tool = Tool(
 
 tools = [stock_data_tool, stock_news_tool, moving_average_tool]
 
+# Initialize the LangChain agent
 agent = initialize_agent(
     tools=tools,
     llm=llm,
@@ -86,12 +87,7 @@ agent = initialize_agent(
     handle_parsing_errors=True
 )
 
-
-print(fetch_stock_data("AAPL"))
-print(fetch_stock_news("AAPL", NEWSAPI_KEY))
-print(calculate_moving_average("AAPL"))
-
-
+# Streamlit app
 st.title("Trading Helper Agent")
 
 query = st.text_input("Enter your query:")
@@ -101,8 +97,8 @@ if st.button("Submit"):
         st.write("Debug: User Query ->", query)
         with st.spinner("Processing..."):
             try:
-                response = agent.invoke(query)
-                print(f'Response: {response}')
+                # Run the agent and get the response
+                response = agent.run(query)  # Correct method is `run()`
                 st.success("Response:")
                 st.write(response)
             except Exception as e: