added more tools

README.md

@@ -1,14 +1,11 @@
 ---
 title: Power Agent
-emoji: 💬
-colorFrom: yellow
+emoji: 🚀
+colorFrom: pink
 colorTo: purple
 sdk: gradio
 sdk_version: 5.0.1
 app_file: app.py
 pinned: false
 license: mit
-short_description: Multimodal agent with a wide range of tools
----
-
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+short_description: Multimodal agent with a wide range of tools.

agent.py

@@ -0,0 +1,56 @@
+import os
+import gradio as gr
+import requests
+import inspect
+import pandas as pd
+from dataclasses import asdict
+from smolagents import CodeAgent, OpenAIServerModel, DuckDuckGoSearchTool, WikipediaSearchTool, GoogleSearchTool, LiteLLMModel
+from dotenv import find_dotenv, load_dotenv
+from  tools import  SafeDuckDuckGoSearchTool, ImageUnderstanding, WikipediaSearch, ExcelReader, CsvReader,ChessSolver, download_files, get_images, FileReader, AudioTransciber, YouTubeTranscipt, YouTubeVideoUnderstanding, WeatherTool, OCR
+from pathlib import Path
+from PIL import Image
+import time
+from smolagents import stream_to_gradio
+
+class PowerAgent(CodeAgent):
+    def __init__(self, model):
+        #web_search = DuckDuckGoSearchTool()
+        tools = [
+            SafeDuckDuckGoSearchTool(),
+            ImageUnderstanding(),
+            WikipediaSearchTool(),
+            FileReader(),
+            ExcelReader(),
+            CsvReader(),
+            AudioTransciber(),
+            YouTubeTranscipt(),
+            YouTubeVideoUnderstanding(),
+            WeatherTool(),
+            OCR()
+        ]
+        super().__init__(
+            tools=tools,
+            model=model,
+            verbosity_level=3,
+            additional_authorized_imports=['pandas', 'numpy', 'io']
+        )
+        # Add your custom system prompt
+        SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question. Report your thoughts, and
+        finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER].
+        YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated
+        list of numbers and/or strings.
+        If you are asked for a number, don't use comma to write your number neither use units such as $ or
+        percent sign unless specified otherwise.
+        If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the
+        digits in plain text unless specified otherwise. Never include currency symbols in the response. 
+        If you are asked for a comma separated list, apply the above rules depending of whether the element
+        to be put in the list is a number or a string. For question that contain phrases like `what is the number` or 
+        `what is the highest number` return just the number, e.g., 2. For questions around currency, 
+        include just the number, not the currency sign.
+        """
+        self.prompt_templates["system_prompt"] = self.prompt_templates["system_prompt"] + SYSTEM_PROMPT
+
+    # def __call__(self, message: str) -> str:
+    #     final_answer = self.agent.run(message)
+    #     print(f"Agent returning answer: {final_answer}")
+    #     return final_answer

app.py

@@ -1,64 +1,96 @@
+import os
 import gradio as gr
-from huggingface_hub import InferenceClient
-
+import requests
+import inspect
+import pandas as pd
+from dataclasses import asdict
+from smolagents import CodeAgent, OpenAIServerModel, DuckDuckGoSearchTool, WikipediaSearchTool, HfApiModel, GoogleSearchTool, LiteLLMModel
+from dotenv import find_dotenv, load_dotenv
+from  tools import  ImageUnderstanding, WikipediaSearch, ExcelReader, CsvReader,ChessSolver, download_files, get_images, FileReader, AudioTransciber, YouTubeTranscipt, YouTubeVideoUnderstanding, VegetableFruitClassification
+from pathlib import Path
+from PIL import Image
+import time
+from smolagents import stream_to_gradio
+from agent import PowerAgent
 """
 For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
 """
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
+    
+def interact_with_agent(message, history):
+    load_dotenv(find_dotenv())
+    gemini_model = LiteLLMModel(model_id= "gemini/gemini-2.0-flash",
+                                    api_key=os.getenv("GEMINI_API_KEY"))
+    # os.environ["SERPER_API_KEY"] = os.getenv('SERPER_API_KEY')
+    prompt = message['text']
+    web_search = DuckDuckGoSearchTool()
+    # agent = CodeAgent(
+    #                 tools=[
+    #                        web_search,
+    #                        ImageUnderstanding(),
+    #                        FileReader(),
+    #                        ExcelReader(),
+    #                        CsvReader(),
+    #                        AudioTransciber()
+    #                        ],
+    #                 model=gemini_model,
+    #                 verbosity_level=3,
+    #                 additional_authorized_imports=['pandas','numpy', 'io']
+    #     )
+    agent = PowerAgent(model=gemini_model)
+    messages = []
+    formatted_history = ""
+    if len(message.get('files')) > 0:
+        file_prompt = "The following files are uploaded: " + str(message.get('files'))
+    else:
+        file_prompt = ""
+    for entry in history:
+        user_msg = ''
+        agent_msg = ''
+        role = entry.get('role')
+        if role == 'user':
+            user_msg += entry.get('content')
+        if role == 'assistant':
+            agent_msg += entry.get('content')
+        formatted_history += f"User: {user_msg}\nAgent: {agent_msg}\n"
+     # Add current message
+    prompt = formatted_history + f"User: {message['text']}{file_prompt}\nAgent:"
+    #yield messages
+    for msg in stream_to_gradio(agent, prompt):
+         messages.append(asdict(msg))
+         yield messages
+    history.append([{'user':prompt, 'agent':msg.content}])
+    #print(history)
+    yield messages
 
 
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
 demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
+    interact_with_agent,
+    theme=gr.themes.Monochrome(),
+    chatbot= gr.Chatbot(
+        label="Power Agent",
+        type="messages",
+        avatar_images=(
+            "https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png",
+            "https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png",
         ),
+    ),
+    fill_height=True,
+    #textbox=gr.Textbox(placeholder="Ask me a question", container=False, scale=7),
+    multimodal=True,
+    textbox=gr.MultimodalTextbox(placeholder="Ask me a question", 
+    file_count="multiple", 
+    file_types=['image', '.json', '.mp4', '.pdf', '.txt', '.csv', '.xlsx', '.xls', 'audio'], 
+    sources=["upload", "microphone"], 
+    container=False, scale=7),
+    examples=[
+        ["Solve a math problem"],
     ],
-)
+    type="messages",
+    )
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(debug=False, share=True)

requirements.txt

@@ -1 +1,16 @@
+gradio
+requests==2.32.3
+smolagents==1.14.0
+smolagents[openai]
+smolagents[litellm]
+openpyxl==3.1.5
+wikipedia==1.4.0
+llama-index-readers-youtube-transcript==0.3.0
+google-genai==1.13.0
+tabulate==0.9.0
+beautifulsoup4==4.13.3
+pandas==2.2.3
+openai==1.75.0
+google==3.0.0
+pillow==11.1.0
 huggingface_hub==0.25.2

tools.py

@@ -0,0 +1,356 @@
+import time
+import io 
+from smolagents import Tool
+import wikipedia
+from bs4 import BeautifulSoup
+import pandas as pd
+import requests 
+from tabulate import tabulate
+import os
+import tempfile
+from pathlib import Path
+from PIL import Image
+from PIL import ImageDraw
+from io import BytesIO
+from dotenv import find_dotenv, load_dotenv
+from openai import OpenAI
+from llama_index.readers.youtube_transcript import YoutubeTranscriptReader
+from google import genai
+from google.genai import types
+import chess
+from PIL import ImageDraw
+from smolagents import DuckDuckGoSearchTool
+from duckduckgo_search.exceptions import DuckDuckGoSearchException
+import torch
+import easyocr
+import fitz
+import numpy as np
+
+class SafeDuckDuckGoSearchTool(DuckDuckGoSearchTool):
+    def forward(self, query: str) -> str:
+        try:
+            return super().forward(query)
+        except DuckDuckGoSearchException as e:
+            error_message = f"❌ DuckDuckGoSearchException: {str(e)}. Retrying in 3 seconds due to possible rate limit..."
+            print(error_message)
+            time.sleep(3)
+            try:
+                return super().forward(query)
+            except DuckDuckGoSearchException as e2:
+                return f"❌ DuckDuckGoSearchException after retry: {str(e2)}. The search engine may be rate-limited. Please try again later."
+            except Exception as e2:
+                return f"❌ An unexpected error occurred during web search after retry: {str(e2)}"
+        except Exception as e:
+            return f"❌ An unexpected error occurred during web search: {str(e)}"
+
+class WikipediaSearch(Tool):
+    name = "wikipedia_search"
+    description = "Fetches wikipedia pages."
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "Query to be searched on wikipedia"
+        }
+        }
+    output_type = "string"
+
+    def forward(self, query:str)->str:
+        res = wikipedia.page(query)
+        bs = BeautifulSoup(res.html(), 'html.parser')
+        text_only = bs.get_text()
+        return text_only
+
+class ExcelReader(Tool):
+    name = 'excel_processor'
+    description = "excel reading tool, processed files of .xlsx and .xls format."
+    inputs = {
+
+        "file_path": {
+            "type": "string",
+            "description": "path to the excel file"
+        }
+        }
+    output_type = "string"
+    
+    def forward(self, file_path:str)->str:
+        df = pd.read_excel(file_path)
+        txt_excel = tabulate(df, headers="keys", tablefmt="github", showindex=False)
+        return txt_excel
+
+class CsvReader(Tool):
+    name = 'csv_processor'
+    description = "csv reading tool, processed files of .csv format."
+    inputs = {
+
+        "file_path": {
+            "type": "string",
+            "description": "path to the excel file"
+        }
+        }
+    output_type = "string"
+    
+    def forward(self, file_path:str)->str:
+        df = pd.read_csv(file_path)
+        txt = tabulate(df, headers="keys", tablefmt="github", showindex=False)
+        return txt
+    
+class FileReader(Tool):
+    name = 'file_reader'
+    description = "reads saved files"
+    inputs = {
+
+        "file_path": {
+            "type": "string",
+            "description": "path to the file"
+        }
+        }
+    output_type = "string"
+    
+    def forward(self, file_path:str)->str:
+        with open(file_path, "r") as file:
+            content = file.read()
+        return content
+    
+def download_files(task_id, file_name):
+    url = f'https://agents-course-unit4-scoring.hf.space/files/{task_id}'
+    response = requests.get(url, timeout=15)
+    tmp_dir = Path(tempfile.gettempdir()) / "project_files"
+    tmp_dir.mkdir(exist_ok=True)
+    filepath = os.path.join(tmp_dir, file_name)
+    with open(filepath, "wb") as f:
+        f.write(response.content)
+
+    return filepath
+
+def get_images(file_format, file_path):
+    if file_format in ['png', 'jpeg', 'jpg']:
+        images  = [Image.open(file_path).convert("RGB")]
+    else:
+        images = []
+
+    return images
+
+class AudioTransciber(Tool):
+    name = 'audio_transcriber'
+    description = "transcribes audio files"
+    inputs = {
+
+        "file_path": {
+            "type": "string",
+            "description": "path to the file"
+        }
+        }
+    output_type = "string"
+    
+    def forward(self, file_path:str)->str:
+        audio = open(file_path, 'rb')
+        client = OpenAI(api_key=os.getenv("OPEN_AI_KEY"))
+        transcript = client.audio.transcriptions.create(model='whisper-1',
+                                         file=audio)
+        return transcript
+    
+class YouTubeTranscipt(Tool):
+    name = 'youtube_transcript'
+    description = "a tool that returns a transcript for a youtube video. Youtube videos come from urls containing www.youtube.com"
+    inputs = {
+
+        "url": {
+            "type": "string",
+            "description": "url to the youtube video, has 'www.youtube.com' in it."
+        }
+        }
+    output_type = "string"
+    
+    def forward(self, url:str)->str:
+        loader = YoutubeTranscriptReader()
+        documents = loader.load_data(ytlinks=[url])
+        transcript = documents[0].text
+        return transcript
+    
+class YouTubeVideoUnderstanding(Tool):
+    name = 'youtube_video_understanding'
+    description = "a tool that processes summarizes what is happenening in a youtube video. Youtube videos come from urls containing www.youtube.com"
+    inputs = {
+        "url": {
+            "type": "string",
+            "description": "url to the youtube video, has 'www.youtube.com' in it."
+        },
+        "prompt": {
+            "type": "string",
+            "description": "user prompt about the video content"
+
+        }
+        }
+    output_type = "string"
+  
+    def forward(self, url:str, prompt:str)->str:
+        load_dotenv(find_dotenv())
+        client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))
+        response = client.models.generate_content(
+         model='models/gemini-2.5-flash',
+            contents=types.Content(
+                parts=[
+                    types.Part(
+                        file_data=types.FileData(file_uri=url)
+                    ),
+                    types.Part(text=prompt)
+                ]
+            )
+        )
+        return response.text
+
+class ImageUnderstanding(Tool):
+    name = 'image_understanding'
+    description = "a tool that answers questions about images. Images are files in the .jpeg, .png and jpg fomatats."
+    inputs = {
+        "file_path": {
+            "type": "string",
+            "description": "path to the image file. These are files in the .jpeg, .png and jpg fomatats."
+        },
+        "prompt": {
+            "type": "string",
+            "description": "user prompt about the image content"
+
+        }
+        }
+    output_type = "string"
+  
+    def forward(self, file_path:str, prompt:str)->str:
+        load_dotenv(find_dotenv())
+        with open(file_path, 'rb') as f:
+            image_bytes = f.read()
+        file_format = file_path.split('.')[-1]
+        client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))
+        response = client.models.generate_content(
+         model='models/gemini-2.0-flash',
+            contents=types.Content(
+                parts=[
+                    types.Part.from_bytes(data=image_bytes,
+                        mime_type=f'image/{file_format}'
+                    ),
+                    types.Part(text=prompt)
+                ]
+            )
+        )
+        return response.text
+    
+class ChessSolver(Tool):
+    name = "chess_analysis_tool"
+    description = "analyzes the chess board to determine the best next move."
+    inputs = {
+        "image_path": {
+            "type": "string",
+            "description": "path to the image showing a chess board."
+        },
+        "current_player":{
+            "type": "string",
+            "description": "player whose turn it is. Acceptable inputs are 'black' or 'white'"
+        },
+        }
+    output_type = "string"
+        
+    def forward(self, image_path:str, current_player:str)->str:
+        fen = chess.fen_notation(image_path, current_player)
+        best_move = chess.chess_analysis(fen)
+        return best_move
+
+class WeatherTool(Tool):
+    name = 'weather_tool'
+    description = "Gets current weather for the specified city. Units: 'metric' (Celsius) or 'imperial' (Fahrenheit, default)."
+    inputs = {
+        "location": {
+            "type": "string",
+            "description": "City name"
+        },
+        "units": {
+            "type": "string",
+            "description": "Units: 'metric' or 'imperial' (default: 'imperial')",
+            "default": "imperial",
+            "nullable": True
+        }
+    }
+    output_type = "string"
+    GEO_URL = "http://api.openweathermap.org/geo/1.0/direct"
+    WEATHER_URL = "https://api.openweathermap.org/data/2.5/weather"
+    DEFAULT_UNITS = "imperial"
+    VALID_UNITS = {"metric", "imperial"}
+
+    def get_lat_lon(self, city, api_key):
+        params = {"q": city, "appid": api_key, "limit": 1}
+        response = requests.get(self.GEO_URL, params=params)
+        response.raise_for_status()
+        data = response.json()
+        if not data:
+            raise ValueError(f"City '{city}' not found.")
+        return data[0]['lat'], data[0]['lon']
+
+    def get_weather(self, lat, lon, api_key, units):
+        params = {"lat": lat, "lon": lon, "appid": api_key, "units": units}
+        response = requests.get(self.WEATHER_URL, params=params)
+        response.raise_for_status()
+        return response.json()
+
+    def forward(self, location: str, units: str = "imperial") -> str:
+        """
+        Get current weather for a city.
+        """
+        try:
+            api_key = os.getenv("WEATHER_API_KEY")
+            units = units if units in self.VALID_UNITS else self.DEFAULT_UNITS
+            lat, lon = self.get_lat_lon(location, api_key)
+            weather = self.get_weather(lat, lon, api_key, units)
+            result = {
+                "description": weather['weather'][0]['description'],
+                "temperature": weather['main']['temp'],
+                "humidity": weather['main']['humidity'],
+                "pressure": weather['main']['pressure'],
+                "units": units,
+                "city": location
+            }
+            return str(result)
+        except Exception as e:
+            return f"❌ An error occurred while retrieving weather data: {str(e)}"
+
+class OCR(Tool):
+    name = "ocr_tool"
+    description = "recognizes text from images."
+    inputs = {
+        "pdf_path": {
+            "type": "string",
+            "description": "path to the pdf with text."
+        },
+        "language": {   
+            "type": "string",
+            "description": "language of the text in the image. Acceptable inputs are 'en' for English, 'es' for Spanish, 'fr' for French, 'de' for German, 'it' for Italian, 'pt' for Portuguese, 'ru' for Russian, 'zh' for Chinese, 'ja' for Japanese, 'ko' for Korean, 'ar' for Arabic, 'hi' for Hindi, 'bn' for Bengali, 'mr' for Marathi, 'ta' for Tamil, 'te' for Telugu, 'ur' for Urdu, 'fa' for Persian, 'tr' for Turkish, 'nl' for Dutch, 'sv' for Swedish, 'no' for Norwegian, 'da' for Danish, 'fi' for Finnish, 'el' for Greek, 'he' for Hebrew, 'id' for Indonesian, 'ms' for Malay, 'pl' for Polish, 'ro' for Romanian, 'sk' for Slovak, 'sl' for Slovenian, 'uk' for Ukrainian, 'vi' for Vietnamese, 'th' for Thai, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay, 'ms' for Malay etc."
+        }
+    }
+    output_type = "string"
+    
+    def draw_boxes(self, image, bounds, color='yellow', width=2):
+        draw = ImageDraw.Draw(image)
+        for bound in bounds:
+            p0, p1, p2, p3 = bound[0]
+            draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
+        return image    
+    
+    def forward(self, pdf_path: str, language: str) -> str:
+        reader = easyocr.Reader([language])
+        results = []
+        all_text = ''
+        pdf_document = fitz.open(pdf_path)
+        for page_num in range(len(pdf_document)):
+            page = pdf_document[page_num]
+            pix = page.get_pixmap(matrix=fitz.Matrix(300/72, 300/72))
+            img = Image.frombytes('RGB', [pix.width, pix.height], pix.samples)
+            im_small = img.resize((img.width // 10, img.height // 10), Image.LANCZOS)
+            image_path = f'saved_image_{page_num}.jpeg'
+            im_small.save(image_path, 'JPEG')
+            bounds = reader.readtext(image_path)
+            im = Image.open(image_path)
+            self.draw_boxes(im, bounds)
+            im.save('result.jpg')
+            summary_df  = pd.DataFrame(bounds).iloc[: , 1:]
+            text_result = ' '.join(summary_df[summary_df[2] >= 0.7][1].astype(str).tolist())
+            
+        all_text += text_result
+        return all_text

utils.py

@@ -0,0 +1,239 @@
+def format_history(history):
+    formatted_history = ""
+    for entry in history:
+        user_msg = ''
+        agent_msg = ''
+        print('Entry', entry)
+        role = entry.get('role')
+        print(entry.get('content'))
+        if role == 'user':
+            user_msg += str(entry.get('content'))
+        if role == 'assistant':
+            agent_msg += str(entry.get('content'))
+        formatted_history += f"User: {user_msg}\nAgent: {agent_msg}\n"
+    return formatted_history
+
+css = """
+:root {
+  --background-fill-primary: var(--neutral-950);
+  --background-fill-secondary: var(--neutral-900);
+  --block-background-fill: var(--neutral-800);
+  --block-border-color: var(--border-color-primary);
+  --block-border-width: 1px;
+  --block-info-text-color: var(--body-text-color-subdued);
+  --block-label-background-fill: var(--background-fill-secondary);
+  --block-label-border-color: var(--border-color-primary);
+  --block-label-border-width: 1px;
+  --block-label-text-color: var(--neutral-200);
+  --block-shadow: none;
+  --block-title-background-fill: none;
+  --block-title-border-color: none;
+  --block-title-border-width: 0px;
+  --block-title-text-color: var(--neutral-200);
+  --body-background-fill: var(--background-fill-primary);
+  --body-text-color: var(--neutral-100);
+  --body-text-color-subdued: var(--neutral-400);
+  --border-color-accent: var(--neutral-600);
+  --border-color-primary: var(--neutral-700);
+  --button-border-width: var(--input-border-width);
+  --button-cancel-background-fill: var(--button-secondary-background-fill);
+  --button-cancel-background-fill-hover: var(--button-cancel-background-fill);
+  --button-cancel-border-color: var(--button-secondary-border-color);
+  --button-cancel-border-color-hover: var(--button-cancel-border-color);
+  --button-cancel-text-color: var(--button-secondary-text-color);
+  --button-cancel-text-color-hover: var(--button-cancel-text-color);
+  --button-primary-background-fill: var(--primary-700);
+  --button-primary-background-fill-hover: var(--button-primary-background-fill);
+  --button-primary-border-color: var(--primary-600);
+  --button-primary-border-color-hover: var(--button-primary-border-color);
+  --button-primary-text-color: white;
+  --button-primary-text-color-hover: var(--button-primary-text-color);
+  --button-secondary-background-fill: var(--neutral-600);
+  --button-secondary-background-fill-hover: var(--button-secondary-background-fill);
+  --button-secondary-border-color: var(--neutral-600);
+  --button-secondary-border-color-hover: var(--button-secondary-border-color);
+  --button-secondary-text-color: white;
+  --button-secondary-text-color-hover: var(--button-secondary-text-color);
+  --chatbot-code-background-color: var(--neutral-800);
+  --checkbox-background-color: var(--neutral-800);
+  --checkbox-background-color-focus: var(--checkbox-background-color);
+  --checkbox-background-color-hover: var(--checkbox-background-color);
+  --checkbox-background-color-selected: var(--secondary-600);
+  --checkbox-border-color: var(--neutral-700);
+  --checkbox-border-color-focus: var(--secondary-500);
+  --checkbox-border-color-hover: var(--neutral-600);
+  --checkbox-border-color-selected: var(--secondary-600);
+  --checkbox-border-width: var(--input-border-width);
+  --checkbox-label-background-fill: var(--button-secondary-background-fill);
+  --checkbox-label-background-fill-hover: var(--button-secondary-background-fill-hover);
+  --checkbox-label-background-fill-selected: var(--checkbox-label-background-fill);
+  --checkbox-label-border-color: var(--border-color-primary);
+  --checkbox-label-border-color-hover: var(--checkbox-label-border-color);
+  --checkbox-label-border-width: var(--input-border-width);
+  --checkbox-label-text-color: var(--body-text-color);
+  --checkbox-label-text-color-selected: var(--checkbox-label-text-color);
+  --color-accent-soft: var(--neutral-700);
+  --error-background-fill: var(--background-fill-primary);
+  --error-border-color: var(--border-color-primary);
+  --error-border-width: 1px;
+  --error-text-color: #ef4444;
+  --input-background-fill: var(--neutral-700);
+  --input-background-fill-focus: var(--secondary-600);
+  --input-background-fill-hover: var(--input-background-fill);
+  --input-border-color: var(--border-color-primary);
+  --input-border-color-focus: var(--neutral-700);
+  --input-border-color-hover: var(--input-border-color);
+  --input-border-width: 0px;
+  --input-placeholder-color: var(--neutral-500);
+  --input-shadow: none;
+  --input-shadow-focus: var(--input-shadow);
+  --link-text-color-active: var(--secondary-500);
+  --link-text-color: var(--secondary-500);
+  --link-text-color-hover: var(--secondary-400);
+  --link-text-color-visited: var(--secondary-600);
+  --loader-color: var(--color-accent);
+  --panel-background-fill: var(--background-fill-secondary);
+  --panel-border-color: var(--border-color-primary);
+  --panel-border-width: 0;
+  --shadow-spread: 1px;
+  --slider-color: auto;
+  --stat-background-fill: var(--primary-500);
+  --table-border-color: var(--neutral-700);
+  --table-even-background-fill: var(--neutral-950);
+  --table-odd-background-fill: var(--neutral-900);
+  --table-row-focus: var(--color-accent-soft);
+  --accordion-text-color: var(--body-text-color);
+  --table-text-color: var(--body-text-color);
+  --border-color-accent-subdued: var(--border-color-accent);
+  --code-background-fill: var(--neutral-800);
+  --checkbox-label-border-color-selected: var(--checkbox-label-border-color);
+  --error-icon-color: #ef4444;
+  --button_primary_shadow: None;
+  --button-primary-shadow-hover: var(--button-primary-shadow);
+  --button-primary-shadow-active: var(--button-primary-shadow);
+  --button_secondary_shadow: None;
+  --button-secondary-shadow-hover: var(--button-secondary-shadow);
+  --button-secondary-shadow-active: var(--button-secondary-shadow);
+  --name: Franklisi/darkmode;
+  --block-info-text-size: var(--text-sm);
+  --block-info-text-weight: 400;
+  --block-label-margin: 0;
+  --block-label-padding: var(--spacing-sm) var(--spacing-lg);
+  --block-label-radius: calc(var(--radius-lg) - 1px) 0 calc(var(--radius-lg) - 1px) 0;
+  --block-label-right-radius: 0 calc(var(--radius-lg) - 1px) 0 calc(var(--radius-lg) - 1px);
+  --block-label-shadow: var(--block-shadow);
+  --block-label-text-size: var(--text-sm);
+  --block-label-text-weight: 400;
+  --block-padding: var(--spacing-xl) calc(var(--spacing-xl) + 2px);
+  --block-radius: var(--radius-lg);
+  --block-title-padding: 0;
+  --block-title-radius: none;
+  --block-title-text-size: var(--text-md);
+  --block-title-text-weight: 400;
+  --body-text-size: var(--text-md);
+  --body-text-weight: 400;
+  --button-large-padding: var(--spacing-lg) calc(2 * var(--spacing-lg));
+  --button-large-radius: var(--radius-lg);
+  --button-large-text-size: var(--text-lg);
+  --button-large-text-weight: 600;
+  --button-shadow: none;
+  --button-shadow-active: none;
+  --button-shadow-hover: none;
+  --button-small-padding: var(--spacing-sm) calc(2 * var(--spacing-sm));
+  --button-small-radius: var(--radius-lg);
+  --button-small-text-size: var(--text-md);
+  --button-small-text-weight: 400;
+  --button-transition: background-color 0.2s ease;
+  --checkbox-border-radius: var(--radius-sm);
+  --checkbox-check: url("data:image/svg+xml,%3csvg viewBox='0 0 16 16' fill='white' xmlns='http://www.w3.org/2000/svg'%3e%3cpath d='M12.207 4.793a1 1 0 010 1.414l-5 5a1 1 0 01-1.414 0l-2-2a1 1 0 011.414-1.414L6.5 9.086l4.293-4.293a1 1 0 011.414 0z'/%3e%3c/svg%3e");
+  --checkbox-label-gap: var(--spacing-lg);
+  --checkbox-label-padding: var(--spacing-md) calc(2 * var(--spacing-md));
+  --checkbox-label-shadow: none;
+  --checkbox-label-text-size: var(--text-md);
+  --checkbox-label-text-weight: 400;
+  --checkbox-shadow: var(--input-shadow);
+  --color-accent: var(--primary-500);
+  --container-radius: var(--radius-lg);
+  --embed-radius: var(--radius-lg);
+  --font: 'Source Sans Pro', 'ui-sans-serif', 'system-ui', sans-serif;
+  --font-mono: 'IBM Plex Mono', 'ui-monospace', 'Consolas', monospace;
+  --form-gap-width: 0px;
+  --input-padding: var(--spacing-xl);
+  --input-radius: var(--radius-lg);
+  --input-text-size: var(--text-md);
+  --input-text-weight: 400;
+  --layout-gap: var(--spacing-xxl);
+  --neutral-100: #f3f4f6;
+  --neutral-200: #e5e7eb;
+  --neutral-300: #d1d5db;
+  --neutral-400: #9ca3af;
+  --neutral-50: #f9fafb;
+  --neutral-500: #6b7280;
+  --neutral-600: #4b5563;
+  --neutral-700: #374151;
+  --neutral-800: #1f2937;
+  --neutral-900: #111827;
+  --neutral-950: #0b0f19;
+  --primary-100: #dbeafe;
+  --primary-200: #bfdbfe;
+  --primary-300: #93c5fd;
+  --primary-400: #60a5fa;
+  --primary-50: #eff6ff;
+  --primary-500: #3b82f6;
+  --primary-600: #2563eb;
+  --primary-700: #1d4ed8;
+  --primary-800: #1e40af;
+  --primary-900: #1e3a8a;
+  --primary-950: #1d3660;
+  --prose-header-text-weight: 600;
+  --prose-text-size: var(--text-md);
+  --prose-text-weight: 400;
+  --radio-circle: url("data:image/svg+xml,%3csvg viewBox='0 0 16 16' fill='white' xmlns='http://www.w3.org/2000/svg'%3e%3ccircle cx='8' cy='8' r='3'/%3e%3c/svg%3e");
+  --radius-lg: 8px;
+  --radius-md: 6px;
+  --radius-sm: 4px;
+  --radius-xl: 12px;
+  --radius-xs: 2px;
+  --radius-xxl: 22px;
+  --radius-xxs: 1px;
+  --secondary-100: #dbeafe;
+  --secondary-200: #bfdbfe;
+  --secondary-300: #93c5fd;
+  --secondary-400: #60a5fa;
+  --secondary-50: #eff6ff;
+  --secondary-500: #3b82f6;
+  --secondary-600: #2563eb;
+  --secondary-700: #1d4ed8;
+  --secondary-800: #1e40af;
+  --secondary-900: #1e3a8a;
+  --secondary-950: #1d3660;
+  --section-header-text-size: var(--text-md);
+  --section-header-text-weight: 400;
+  --shadow-drop: rgba(0,0,0,0.05) 0px 1px 2px 0px;
+  --shadow-drop-lg: 0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1);
+  --shadow-inset: rgba(0,0,0,0.05) 0px 2px 4px 0px inset;
+  --spacing-lg: 8px;
+  --spacing-md: 6px;
+  --spacing-sm: 4px;
+  --spacing-xl: 10px;
+  --spacing-xs: 2px;
+  --spacing-xxl: 16px;
+  --spacing-xxs: 1px;
+  --table-radius: var(--radius-lg);
+  --text-lg: 16px;
+  --text-md: 14px;
+  --text-sm: 12px;
+  --text-xl: 22px;
+  --text-xs: 10px;
+  --text-xxl: 26px;
+  --text-xxs: 9px;
+  --chatbot-text-size: var(--text-lg);
+  --button-transform-hover: none;
+  --button-transform-active: none;
+  --button-primary-shadow: none;
+  --button-secondary-shadow: var(--button-primary-shadow);
+  --button-medium-padding: var(--spacing-md) calc(2 * var(--spacing-md));
+  --button-medium-radius: var(--radius-md);
+  --button-medium-text-size: var(--text-md);
+  --button-medium-text-weight: 600;
+}"""