First commit - WIP

app.py

@@ -0,0 +1,61 @@
+import os
+import requests
+from markitdown import MarkItDown
+import datetime
+
+
+"""
+Retrieve the file at https://pulse.zerodha.com
+Then convert it to markdown format using markitdown library.
+
+"""
+
+# Initialize the client
+def initialize_client(api_key_env_var):
+    load_dotenv(find_dotenv())
+    api_key = os.getenv(api_key_env_var)
+    if not api_key:
+        raise ValueError(f"API key not found in environment variable {api_key_env_var}")
+    return genai.Client(api_key=api_key)
+
+my_model = 'gemini-2.0-flash' #'gemini-2.0-flash-exp'
+client = initialize_client('GOOGLE_API_KEY')
+
+# Main function
+if __name__ == '__main__':
+
+    # Current time is, dd-mm-YYYY HH:MM:SS
+    timenow = datetime.datetime.now().strftime("%d-%m-%Y %H:%M:%S")
+
+    # get the pulse file
+    print(f"Start getting the pulse file at {timenow}...")
+    response = requests.get('https://pulse.zerodha.com')
+    html_content = response.text
+    # Save it to a file
+    with open('output.html', 'w') as file:
+        file.write(html_content)
+
+    print(f"Start converting the pulse file to markdown format at {timenow}...")
+    md = MarkItDown()
+    result = md.convert("output.html")
+    #print(result.text_content)
+    # Save the markdown content to a file
+    with open('output.md', 'w') as file:
+        file.write(result.text_content)
+
+    print(f"Start arranging the pulse file at {timenow}...")
+    analyzer = client.chats.create(model=my_model)
+    response = analyzer.send_message(f"Arrange and group the news feed provided based on the order of importance for an investor in the markets. Include whatever data related to the news is available in the input, such as short summaries, hyperlinks etc. If available include time of report of the news. The time now is: {timenow}. The input is in markdown. Input: {result.text_content}")
+    output = ""
+    parts = response.candidates[0].content.parts
+    if parts is None:
+            print(f'finish_reason={response.candidates[0].finish_reason}')
+    for part in parts:
+        if part.text:
+            #print(part.text)
+            # join the text parts
+            output += part.text
+
+    # Save the output to a file
+    with open('output_arranged.md', 'w') as file:
+        file.write(output)