Update app.py

app.py

@@ -17,6 +17,7 @@ from langchain.chains import StuffDocumentsChain
 
 GOOGLE_API_KEY=os.environ['GOOGLE_API_KEY']
 
+st.title('Stock Market Insights')
 
 ticker_user = st.text_input("Enter Ticker","ADANIENT")
 
@@ -30,13 +31,30 @@ gemini_embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
 
 llm = ChatGoogleGenerativeAI(model="gemini-pro",google_api_key = GOOGLE_API_KEY)
 
+st.divider()
+# llm_prompt_template = """You are an expert Stock Market Trader for stock market insights based on fundamental, analytical, profit based and company financials.
+# Based on the context below
+# {context}, Summarize the stock based on Historical data based on fundamental, price, news, sentiment , any red flags and suggest rating of the Stock in a 1 to 10 Scale"""
 
+llm_prompt_template = """You are an expert Stock Market Trader specializing in stock market insights derived from fundamental analysis, analytical trends, profit-based evaluations, and detailed company financials. Using your expertise, please analyze the stock based on the provided context below.
 
-llm_prompt_template = """You are an expert Stock Market Trader for stock market insights based on fundamental, analytical, profit based and company financials.
-Based on the context below
-{context}, Summarize the stock based on Historical data based on fundamental, price, news, sentiment , any red flags and suggest rating of the Stock in a 1 to 10 Scale"""
+Context:
+{context}
 
-user_prompt = st.text_area("Enter Prompt",llm_prompt_template)
+Task:
+Summarize the stock based on its historical and current data.
+Evaluate the stock on the following parameters:
+1. Company Fundamentals: Assess the stock's intrinsic value, growth potential, and financial health.
+2. Current & Future Price Trends: Analyze historical price movements and current price trends.
+3. News and Sentiment: Review recent news articles, press releases, and social media sentiment.
+4. Red Flags: Identify any potential risks or warning signs.
+5. Provide a rating for the stock on a scale of 1 to 10.
+6. Advise if the stock is a good buy for the next 2 weeks.
+7. Suggest at what price we need to buy and hold or sell
+"""
+
+st.sidebar.subheader('Prompt')
+user_prompt = st.sidebar.text_area("Enter Prompt",llm_prompt_template)
 
 llm_prompt = PromptTemplate.from_template(user_prompt)
 
@@ -45,6 +63,8 @@ stuff_chain = StuffDocumentsChain(llm_chain=llm_chain,document_variable_name="co
 
 
 res = stuff_chain.invoke(docs)
+
+
 st.write(res["output_text"])
 
 # If there is no environment variable set for the API key, you can pass the API