Initial commit

README.md

@@ -1,6 +1,6 @@
 ---
 title: YFinanceAgents
-emoji: 🐠
+emoji: 📈
 colorFrom: blue
 colorTo: gray
 sdk: gradio

app.py

@@ -0,0 +1,69 @@
+import gradio as gr
+import google.generativeai as genai
+import os
+
+genai.configure(api_key=os.environ['GEMINI_API_KEY'])
+
+from tools import analyze_financials, analyze_stock, analyze_analysts_estimatations, analyze_news
+
+functions = {
+    "analyze_financials": analyze_financials,
+    "analyze_stock": analyze_stock,
+    "analyze_analysts_estimatations": analyze_analysts_estimatations,
+    "analyze_news": analyze_news,
+}
+
+model = genai.GenerativeModel(
+    model_name="gemini-1.5-pro",
+    tools=functions.values(),
+    system_instruction="You are an expert in financial analysis. Given a set of financial statements of a company, I ask you to analyze the company. If analyze_stock function is called determine the period from one of the items in the list depending on the request ['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']."
+)
+
+chat_session = model.start_chat(history=[])
+
+def call_function(function_call, functions):
+    function_name = function_call.name
+    function_args = function_call.args
+    return functions[function_name](**function_args)
+
+def chat_with_bot(user_input, history=[]):
+    # Send user message to model
+    response = chat_session.send_message(user_input)
+    part = response.candidates[0].content.parts[0]
+
+    function_result = ""
+    if part.function_call:
+        function_result = call_function(part.function_call, functions)
+        function_name = part.function_call.name
+        bot_response = f"Function `{function_name}` was called. Result:\n\n{function_result}"
+    else:
+        bot_response = part.text
+
+    history.append((user_input, bot_response))
+    return history, history
+
+examples = [
+    "Summarize analysts views on GOOG.",
+    "Analyze last month's stock data of NVDA.",
+    "Provide a brief overview of MSFT news.",
+    "Analyze financials of META in detail."
+]
+
+with gr.Blocks() as demo:
+    gr.Markdown("### Financial Analysis Chatbot")
+    
+    chatbot = gr.Chatbot()
+    state = gr.State([])
+
+    with gr.Row():
+        with gr.Column(scale=4):
+            msg_input = gr.Textbox(label="Your message", placeholder="Ask something...", lines=1)
+        with gr.Column(scale=1):
+            send_button = gr.Button("Send")
+
+    gr.Examples(examples=examples, inputs=msg_input, fn=chat_with_bot, outputs=[chatbot, state], cache_examples=False)
+
+    send_button.click(chat_with_bot, inputs=[msg_input, state], outputs=[chatbot, state])
+    msg_input.submit(chat_with_bot, inputs=[msg_input, state], outputs=[chatbot, state])
+
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+google-generativeai==0.8.3
+yfinance==0.2.49
+gradio==5.5.0

tools.py

@@ -0,0 +1,127 @@
+import google.generativeai as genai
+import yfinance as yf
+
+def analyze_financials(company: str, user_input: str):
+  ticker = yf.Ticker(company)
+  info = ticker.info
+  calendar = ticker.calendar
+  sec_filings = ticker.sec_filings
+  income_stmt = ticker.income_stmt
+  quarterly_income_stmt = ticker.quarterly_income_stmt
+  balance_sheet = ticker.balance_sheet
+  quarterly_balance_sheet = ticker.quarterly_balance_sheet
+  cashflow = ticker.cashflow
+  quarterly_cashflow = ticker.quarterly_cashflow
+
+  analyst_generation_config = {
+  "temperature": 0.1,
+  "top_p": 0.95,
+  "top_k": 40,
+  "max_output_tokens": 8192,
+  "response_mime_type": "text/plain",
+  }
+
+  analyst_model = genai.GenerativeModel(
+  model_name="gemini-1.5-pro",
+  generation_config=analyst_generation_config,
+  system_instruction="You are an expert financial analyst. Given a set of financial statements of a company, I ask you to analyze the company. You will have access to ticker name, calendar, sec filings, income statement, quarterly income statement, balance sheet, quarterly balance sheet, cashflow, quarterly cashflow."
+  )
+
+  analyst_chat_session = analyst_model.start_chat(
+  history=[
+  ]
+  )
+
+  analyst_response = analyst_chat_session.send_message(f"Given the following data answer the question {user_input}\n, {ticker}, {info}, {calendar}, {sec_filings}, {income_stmt}, {quarterly_income_stmt}, {balance_sheet}, {quarterly_balance_sheet}, {cashflow}, {quarterly_cashflow}")
+
+  return analyst_response.text
+
+def analyze_stock(company: str, period: str, user_input: str):
+  ticker = yf.Ticker(company)
+  info = ticker.info
+  hist = ticker.history(period=period)
+  hist_metadata = ticker.history_metadata
+
+  stock_generation_config = {
+  "temperature": 0.1,
+  "top_p": 0.95,
+  "top_k": 40,
+  "max_output_tokens": 8192,
+  "response_mime_type": "text/plain",
+  }
+
+  stock_model = genai.GenerativeModel(
+  model_name="gemini-1.5-pro",
+  generation_config=stock_generation_config,
+  system_instruction="You are an expert financial analyst. Given a set of financial statements of a company, I ask you to analyze the company. You will have access to ticker name, company info, historical data."
+  )
+
+  stock_chat_session = stock_model.start_chat(
+  history=[
+  ]
+  )
+
+  stock_response = stock_chat_session.send_message(f"Given the following data answer the question {user_input}\n, {info}, {hist}, {hist_metadata}")
+
+  return stock_response.text
+
+def analyze_analysts_estimatations(company: str, user_input: str):
+  ticker = yf.Ticker(company)
+  info = ticker.info
+  analyst_price_targets = ticker.analyst_price_targets
+  earnings_estimate = ticker.earnings_estimate
+  revenue_estimate = ticker.revenue_estimate
+  earnings_history = ticker.earnings_history
+  eps_trend = ticker.eps_trend
+  eps_revisions = ticker.eps_revisions
+  growth_estimates = ticker.growth_estimates
+
+  analysts_generation_config = {
+  "temperature": 0.1,
+  "top_p": 0.95,
+  "top_k": 40,
+  "max_output_tokens": 8192,
+  "response_mime_type": "text/plain",
+  }
+
+  analysts_model = genai.GenerativeModel(
+  model_name="gemini-1.5-pro",
+  generation_config=analysts_generation_config,
+  system_instruction="You are an expert financial analyst. Given a set of financial statements of a company, I ask you to analyze the company. You will have access to ticker name, company info, analyst price targets, earnings estimate, revenue estimate, earnings history, eps trend, eps revisions, growth estimates."
+  )
+
+  analysts_chat_session = analysts_model.start_chat(
+  history=[
+  ]
+  )
+
+  analysts_response = analysts_chat_session.send_message(f"Given the following data answer the question {user_input}\n, {info}, {analyst_price_targets}, {earnings_estimate}, {revenue_estimate}, {earnings_history}, {eps_trend}, {eps_revisions}, {growth_estimates}")
+
+  return analysts_response.text
+
+def analyze_news(company: str, user_input: str):
+  ticker = yf.Ticker(company)
+  news = ticker.news
+
+  news_generation_config = {
+  "temperature": 0.1,
+  "top_p": 0.95,
+  "top_k": 40,
+  "max_output_tokens": 8192,
+  "response_mime_type": "text/plain",
+  }
+
+  news_model = genai.GenerativeModel(
+  model_name="gemini-1.5-pro",
+  generation_config=news_generation_config,
+  system_instruction="You are an expert financial analyst. Given a set of financial news on company, I ask you to analyze the company. You will have access to ticker name, news on yahoo finance."
+  )
+
+  news_chat_session = news_model.start_chat(
+  history=[
+  ]
+  )
+
+  news_response = news_chat_session.send_message(f"Given the following data answer the question {user_input}\n, {news}")
+
+  return news_response.text