Create app.py

app.py

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+import os
+import time
+import re
+import requests
+import yfinance as yf
+import warnings
+warnings.filterwarnings("ignore")
+
+from bs4 import BeautifulSoup
+from langchain_community.tools import WikipediaQueryRun
+from langchain_community.utilities import WikipediaAPIWrapper
+from langchain_community.utilities.alpha_vantage import AlphaVantageAPIWrapper
+from langchain.agents import AgentType, initialize_agent, load_tools
+from langchain_community.tools import ShellTool
+from langchain_community.llms import HuggingFaceEndpoint
+from langchain.tools import BaseTool, StructuredTool, Tool, tool,DuckDuckGoSearchRun
+from langchain import LLMMathChain
+from pydantic import BaseModel, Field
+from langchain.tools import DuckDuckGoSearchRun
+
+search=DuckDuckGoSearchRun()
+llm = HuggingFaceEndpoint(repo_id="mistralai/Mistral-7B-Instruct-v0.2")
+
+# Fetch stock data from Yahoo Finance
+def get_stock_price(ticker,history=5):
+    # time.sleep(4) #To avoid rate limit error
+    if "." in ticker:
+        ticker=ticker.split(".")[0]
+    ticker=ticker+".NS"
+    stock = yf.Ticker(ticker)
+    df = stock.history(period="1y")
+    df=df[["Close","Volume"]]
+    df.index=[str(x).split()[0] for x in list(df.index)]
+    df.index.rename("Date",inplace=True)
+    df=df[-history:]
+    # print(df.columns)
+    
+    return df.to_string()
+
+# Script to scrap top5 googgle news for given company name
+def google_query(search_term):
+    if "news" not in search_term:
+        search_term=search_term+" stock news"
+    url=f"https://www.google.com/search?q={search_term}&cr=countryIN"
+    url=re.sub(r"\s","+",url)
+    return url
+
+def get_recent_stock_news(company_name):
+    # time.sleep(4) #To avoid rate limit error
+    headers={'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.0.0 Safari/537.36'}
+
+    g_query=google_query(company_name)
+    res=requests.get(g_query,headers=headers).text
+    soup=BeautifulSoup(res,"html.parser")
+    news=[]
+    for n in soup.find_all("div","n0jPhd ynAwRc tNxQIb nDgy9d"):
+        news.append(n.text)
+    for n in soup.find_all("div","IJl0Z"):
+        news.append(n.text)
+
+    if len(news)>6:
+        news=news[:4]
+    else:
+        news=news
+    news_string=""
+    for i,n in enumerate(news):
+        news_string+=f"{i}. {n}\n"
+    top5_news="Recent News:\n\n"+news_string
+    
+    return top5_news
+
+
+# Fetch financial statements from Yahoo Finance
+def get_financial_statements(ticker):
+    # time.sleep(4) #To avoid rate limit error
+    if "." in ticker:
+        ticker=ticker.split(".")[0]
+    else:
+        ticker=ticker
+    ticker=ticker+".NS"    
+    company = yf.Ticker(ticker)
+    balance_sheet = company.balance_sheet
+    if balance_sheet.shape[1]>=3:
+        balance_sheet=balance_sheet.iloc[:,:3]    # Remove 4th years data
+    balance_sheet=balance_sheet.dropna(how="any")
+    balance_sheet = balance_sheet.to_string()
+    return balance_sheet
+
+
+#Openai function calling
+function=[
+        {
+        "name": "get_company_Stock_ticker",
+        "description": "This will get the indian NSE/BSE stock ticker of the company",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "ticker_symbol": {
+                    "type": "string",
+                    "description": "This is the stock symbol of the company.",
+                },
+
+                "company_name": {
+                    "type": "string",
+                    "description": "This is the name of the company given in query",
+                }
+            },
+            "required": ["company_name","ticker_symbol"],
+        },
+    }
+]
+
+
+def get_stock_ticker(query):
+    response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            temperature=0,
+            messages=[{
+                "role":"user",
+                "content":f"Given the user request, what is the comapany name and the company stock ticker ?: {query}?"
+            }],
+            functions=function,
+            function_call={"name": "get_company_Stock_ticker"},
+    )
+    message = response["choices"][0]["message"]
+    arguments = json.loads(message["function_call"]["arguments"])
+    company_name = arguments["company_name"]
+    company_ticker = arguments["ticker_symbol"]
+    return company_name,company_ticker
+
+def Anazlyze_stock(query):
+    #agent.run(query) Outputs Company name, Ticker
+    Company_name,ticker=get_stock_ticker(query)
+    print({"Query":query,"Company_name":Company_name,"Ticker":ticker})
+    stock_data=get_stock_price(ticker,history=10)
+    stock_financials=get_financial_statements(ticker)
+    stock_news=get_recent_stock_news(Company_name)
+
+    available_information=f"Stock Price: {stock_data}\n\nStock Financials: {stock_financials}\n\nStock News: {stock_news}"
+    #available_information=f"Stock Financials: {stock_financials}\n\nStock News: {stock_news}"
+
+    # print("\n\nAnalyzing.....\n")
+    analysis=llm(f"Give detail stock analysis, Use the available data and provide investment recommendation. \
+             The user is fully aware about the investment risk, dont include any kind of warning like 'It is recommended to conduct further research and analysis or consult with a financial advisor before making an investment decision' in the answer \
+             User question: {query} \
+             You have the following information available about {Company_name}. Write (5-8) pointwise investment analysis to answer user query, At the end conclude with proper explaination.Try to Give positives and negatives  : \
+              {available_information} "
+             )
+    # print(analysis)
+
+    return analysis
+
+
+
+# Making tool list
+tools=[
+    Tool(
+        name="get stock data",
+        func=get_stock_price,
+        description="Use when you are asked to evaluate or analyze a stock. This will output historic share price data. You should input the the stock ticker to it "
+    ),
+    Tool(
+        name="DuckDuckGo Search",
+        func=search.run,
+        description="Use only when you need to get NSE/BSE stock ticker from internet, you can also get recent stock related news. Dont use it for any other analysis or task"
+    ),
+    Tool(
+        name="get recent news",
+        func=get_recent_stock_news,
+        description="Use this to fetch recent news about stocks"
+    ),
+
+    Tool(
+        name="get financial statements",
+        func=get_financial_statements,
+        description="Use this to get financial statement of the company. With the help of this data companys historic performance can be evaluaated. You should input stock ticker to it"
+    ) 
+
+
+]
+
+
+
+agent = initialize_agent(
+    tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True, max_iterations=4,
+    handle_parsing_errors=True
+)
+#Adding predefine evaluation steps in the agent Prompt
+
+new_prompt="""You are a financial advisor. Give stock recommendations for given query.
+Everytime first you should identify the company name and get the stock ticker symbole for indian stock.
+Answer the following questions as best you can. You have access to the following tools:
+
+get stock data: Use when you are asked to evaluate or analyze a stock. This will output historic share price data. You should input the the stock ticker to it 
+DuckDuckGo Search: Use only when you need to get NSE/BSE stock ticker from internet, you can also get recent stock related news. Dont use it for any other analysis or task
+get recent news: Use this to fetch recent news about stocks
+get financial statements: Use this to get financial statement of the company. With the help of this data companys historic performance can be evaluaated. You should input stock ticker to it
+
+steps- 
+Note- if you fail in satisfying any of the step below, Just move to next one
+1) Get the company name and search for the "company name + NSE/BSE stock ticker" on internet. Dont hallucinate extract stock ticker as it is from the text. Output- stock ticker
+2) Use "get stock data" tool to gather stock info. Output- Stock data
+3) Get company's historic financial data using "get financial statements". Output- Financial statement
+4) Use this "get recent news" tool to search for latest stock realted news. Output- Stock news
+5) Analyze the stock based on gathered data and give detail analysis for investment choice. provide numbers and reasons to justify your answer. Output- Detailed stock Analysis
+
+Use the following format:
+
+Question: the input question you must answer
+Thought: you should always think about what to do, Also try to follow steps mentioned above
+Action: the action to take, should be one of [get stock data, DuckDuckGo Search, get recent news, get financial statements]
+Action Input: the input to the action
+Observation: the result of the action
+... (this Thought/Action/Action Input/Observation can repeat N times)
+Thought: I now know the final answer
+Final Answer: the final answer to the original input question
+Begin!
+
+Question: {input}
+Thought:{agent_scratchpad}"""
+
+
+
+#Setting up new prompt
+agent.agent.llm_chain.prompt.template=new_prompt
+
+
+#App UI starts here
+st.set_page_config(page_title="STOCK Analyzer", page_icon=":robot:")
+st.header("STOCK Analyzer")
+
+#Gets the user input
+def get_text():
+    input_text = st.text_input("You:", "Is ITC stock a good investment choice right now? OR Shall I invest in Asian paints?.......")
+    if input_text.isalpha():
+        st.write(text, 'string', )
+    else:
+        st.write('Please type in a string Only')
+    return input_text
+
+user_input=get_text()
+response = agent(user_input)
+
+submit = st.button('Generate')  
+
+#If generate button is clicked
+if submit:
+
+    st.subheader("Answer:")
+
+    st.write(response)
+
+