Update app.py

app.py

@@ -3,24 +3,17 @@ from bs4 import BeautifulSoup
 import pandas as pd
 from io import StringIO
 from datetime import datetime, timedelta
-
+import gradio as gr
 from langchain.tools import tool
-from langchain.agents import initialize_agent, Tool
+from langchain.agents import initialize_agent, Tool, AgentExecutor
 from langchain_openai import ChatOpenAI
+from langchain.callbacks.base import BaseCallbackHandler
 
 # === Configuration ===
-OPENROUTER_API_KEY = "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"
-
+OPENROUTER_API_KEY = "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"
 HEADERS = {
-    'User-Agent': (
-        'Mozilla/5.0 (Windows NT 10.0; Win64; x64) '
-        'AppleWebKit/537.36 (KHTML, like Gecko) '
-        'Chrome/124.0.0.0 Safari/537.36'
-    ),
-    'Accept': (
-        'text/html,application/xhtml+xml,application/xml;'
-        'q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8'
-    ),
+    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36',
+    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8',
     'Accept-Language': 'en-US,en;q=0.9',
     'Referer': 'https://www.google.com/',
     'Connection': 'keep-alive',
@@ -28,9 +21,10 @@ HEADERS = {
     'Upgrade-Insecure-Requests': '1'
 }
 
+# === Tools ===
 @tool("GetCurrentPrice")
 def get_current_price(symbol: str) -> str:
-    """Get the current price for a stock symbol (e.g., 'AAPL')."""
+    """here is the doc string"""
     url = f'https://www.marketwatch.com/investing/stock/{symbol}'
     response = requests.get(url, headers=HEADERS)
     if response.status_code == 200:
@@ -38,7 +32,7 @@ def get_current_price(symbol: str) -> str:
         price_tag = soup.find('bg-quote', class_='value')
         if price_tag:
             price = price_tag.get_text(strip=True)
-            return f"{symbol.upper()} current price: ${price} (from MarketWatch)"
+            return f"{symbol.upper()} current price: ${price}"
         else:
             return "Stock price not found."
     else:
@@ -46,7 +40,7 @@ def get_current_price(symbol: str) -> str:
 
 @tool("GetHistoricalData")
 def get_historical_data(symbol: str, days: int = 5000) -> str:
-    """Get the last N days of historical OHLCV data for a stock symbol as CSV."""
+    """here is it"""
     end_date = datetime.now()
     start_date = end_date - timedelta(days=days)
     start_date_str = start_date.strftime('%m/%d/%Y 00:00:00')
@@ -61,7 +55,7 @@ def get_historical_data(symbol: str, days: int = 5000) -> str:
     if response.status_code == 200:
         try:
             df = pd.read_csv(StringIO(response.text))
-            return f"Historical data for {symbol.upper()} (from MarketWatch):\n" + df.head(10).to_csv(index=False)
+            return df.head(10).to_csv(index=False)
         except Exception as e:
             return f"Failed to parse CSV data: {e}"
     else:
@@ -79,6 +73,7 @@ Technical Analysis: Core Concepts & Formulas
 
 Key Technical Indicators and Their Formulas:
 -------------------------------------------
+
 1. Simple Moving Average (SMA): SMA(time_period) = Sum(Price_t ... Price_{t-n}) / n
 2. Exponential Moving Average (EMA): EMA_t = (Price_t * α) + EMA_{t-1} * (1 - α), where α = 2/(n+1)
 3. Relative Strength Index (RSI): RSI = 100 - [100 / (1 + Avg Gain / Avg Loss)]
@@ -144,45 +139,69 @@ Key Technical Indicators and Their Formulas:
    - Hammer, Shooting Star, Engulfing, Doji, Morning/Evening Star, etc.
 """
 
+# === Register Tools ===
 tools = [
-    Tool.from_function(
-        get_current_price,
-        name="GetCurrentPrice",
-        description="Get the current price for a stock symbol (e.g., AAPL)"
-    ),
-    Tool.from_function(
-        get_historical_data,
-        name="GetHistoricalData",
-        description="Get the last N days of historical OHLCV data for a stock symbol as CSV"
-    ),
-    Tool.from_function(
-        get_technical_analysis_docs,
-        name="GetTechnicalAnalysisDocs",
-        description="Provide documentation for technical analysis indicators"
-    )
+    Tool.from_function(get_current_price, name="GetCurrentPrice", description="Get current stock price."),
+    Tool.from_function(get_historical_data, name="GetHistoricalData", description="Get stock historical data as CSV."),
+    Tool.from_function(get_technical_analysis_docs, name="GetTechnicalAnalysisDocs", description="Technical indicator docs.")
 ]
 
+# === Callback handler to stream reasoning to chat ===
+class ReasoningCallbackHandler(BaseCallbackHandler):
+    def __init__(self, chat_callback):
+        self.chat_callback = chat_callback
+
+    def on_tool_start(self, serialized, input_str, **kwargs):
+        self.chat_callback(f"🛠️ Using Tool: {serialized['name']} with input: {input_str}")
+
+    def on_tool_end(self, output, **kwargs):
+        self.chat_callback(f"✅ Tool output: {output}")
+
+    def on_llm_new_token(self, token, **kwargs):
+        if token.strip():
+            self.chat_callback(token)
+
+# === OpenAI-compatible LLM via OpenRouter ===
 llm = ChatOpenAI(
     openai_api_key=OPENROUTER_API_KEY,
     openai_api_base="https://openrouter.ai/api/v1",
     model_name="google/gemma-3n-e4b-it:free"
 )
 
-agent = initialize_agent(
-    tools,
-    llm,
-    agent="zero-shot-react-description",
-    verbose=True  # This will show all reasoning and tool usage!
-)
+# === Agent Execution with live reasoning ===
+def run_agent(question, chat_callback):
+    callback_handler = ReasoningCallbackHandler(chat_callback)
+    agent_executor = initialize_agent(
+        tools, llm,
+        agent="zero-shot-react-description",
+        verbose=True,
+        callbacks=[callback_handler]
+    )
+    try:
+        result = agent_executor.run(question)
+    except Exception as e:
+        result = f"❌ Error: {str(e)}"
+
+    chat_callback(f"✅ Final Answer: {result}")
+
+# === Gradio UI ===
+with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
+    gr.Markdown("## 📈 Stock Market Analysis Agent")
+    chatbot = gr.Chatbot(label="Stock Agent Chat")
+    with gr.Row():
+        user_input = gr.Textbox(label="Type your question here...", scale=4)
+        submit_btn = gr.Button("Submit", scale=1)
+
+    def respond(msg, chat_history):
+        chat_history.append((msg, ""))
+        def chat_callback(new_msg):
+            chat_history.append(("", new_msg))
+            chatbot.value = chat_history
+        run_agent(msg, chat_callback)
+        return chat_history
+
+
+
+    submit_btn.click(respond, [user_input, chatbot], [chatbot])
 
-if __name__ == "__main__":
-    print("Welcome to the Stock Analysis Agent!")
-    print("Ask anything about stocks, technical analysis, or predictions.")
-    print("Type 'exit' to quit.")
-    while True:
-        user_input = input("\nYour question: ")
-        if user_input.lower() in ["exit", "quit"]:
-            print("Goodbye!")
-            break
-        result = agent.run(user_input)
-        print("\nAgent's answer:\n", result)
+demo.launch()