Update app.py

app.py

@@ -1,61 +1,123 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
-import datetime
+from smolagents import CodeAgent, DuckDuckGoSearchTool, tool, load_tool, HfApiModel
 import requests
-import pytz
+from bs4 import BeautifulSoup
+import pandas as pd
 import yaml
-from tools.final_answer import FinalAnswerTool
-
-from Gradio_UI import GradioUI
+import datetime
+import pytz
+from textblob import TextBlob  # Simple sentiment analysis
+from Gradio_UI import GradioUI  # For building Gradio UI
 
-# Below is an example of a tool that does nothing. Amaze us with your creativity !
+#### TOOL 1: Scrape GSMArena Reviews & Specs ####
 @tool
-def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
-    #Keep this format for the description / args / args description but feel free to modify the tool
-    """A tool that does nothing yet 
+def scrape_gsmarena_reviews(phone_name: str) -> dict:
+    """Scrapes GSMArena for reviews and specs of a given smartphone.
     Args:
-        arg1: the first argument
-        arg2: the second argument
+        phone_name: The model name (exact/substantial match).
+    Returns:
+        Dictionary with keys: 'reviews', 'price', 'specs'
     """
-    return "What magic will you build ?"
+    # You’ll need accurate GSMArena URL fetching logic per phone_name.
+    search_url = f"https://www.gsmarena.com/res.php3?sSearch={phone_name.replace(' ', '+')}"
+    res = requests.get(search_url)
+    soup = BeautifulSoup(res.text, "html.parser")
+    # Find first matching phone page link
+    link = soup.find("div", class_="makers").find("a")["href"]
+    phone_url = f"https://www.gsmarena.com/{link}"
+    phone_page = requests.get(phone_url)
+    phone_soup = BeautifulSoup(phone_page.text, "html.parser")
+    # Parse reviews and price
+    reviews = []
+    for rev in phone_soup.find_all("div", class_="user-review"):
+        reviews.append(rev.text)
+    # Fallback if structure changes
+    price = "Unknown"
+    for spec in phone_soup.find_all("td", string="Price"):
+        price = spec.find_next_sibling("td").text
+    specs = {li.find('span').text: li.text for li in phone_soup.find_all("li")}
+    return {"reviews": reviews, "price": price, "specs": specs}
 
+#### TOOL 2: Churn/Sentiment Scoring ####
 @tool
-def get_current_time_in_timezone(timezone: str) -> str:
-    """A tool that fetches the current local time in a specified timezone.
+def score_churn(reviews: list) -> float:
+    """Calculates aggregate churn score from reviews using sentiment analysis.
     Args:
-        timezone: A string representing a valid timezone (e.g., 'America/New_York').
+        reviews: List of review texts.
+    Returns:
+        float churn score (avg polarity; lower = less churn)
     """
-    try:
-        # Create timezone object
-        tz = pytz.timezone(timezone)
-        # Get current time in that timezone
-        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
-        return f"The current local time in {timezone} is: {local_time}"
-    except Exception as e:
-        return f"Error fetching time for timezone '{timezone}': {str(e)}"
+    scores = [TextBlob(r).sentiment.polarity for r in reviews]
+    churn_score = 1 - (sum(scores) / len(scores)) if scores else 1  # Lower is better
+    return churn_score
 
+#### TOOL 3: Find Competing Phones ####
+@tool
+def find_competitors(price: str) -> list:
+    """Scrapes or queries GSM Arena for phones in the same price bracket.
+    Args:
+        price: The reference price.
+    Returns:
+        List of phone names.
+    """
+    price_value = ''.join(filter(str.isdigit, price))
+    # For demo: just pick other search results in same price bracket
+    # Expand with real price logic as needed
+    return ["Phone1", "Phone2", "Phone3"]
 
-final_answer = FinalAnswerTool()
-
-# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
-# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
+#### FINAL TOOL: Recommend Phone ####
+@tool
+def recommend_smartphone(user_phone: str):
+    """Main logic for recommendation."""
+    user_data = scrape_gsmarena_reviews(user_phone)
+    user_reviews = user_data['reviews']
+    user_score = score_churn(user_reviews)
+    user_price = user_data['price']
+    competitors = find_competitors(user_price)
+    best_score = user_score
+    best_phone = user_phone
 
-model = HfApiModel(
-max_tokens=2096,
-temperature=0.5,
-model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
-custom_role_conversions=None,
-)
+    for c in competitors:
+        c_data = scrape_gsmarena_reviews(c)
+        c_reviews = c_data['reviews']
+        c_score = score_churn(c_reviews)
+        if c_score < best_score:
+            best_score = c_score
+            best_phone = c
 
+    # If best_phone is not user's, recommend; else try next bracket
+    result = {
+        "Your phone": user_phone,
+        "Your phone score": user_score,
+        "Best competitor": best_phone,
+        "Best score": best_score,
+        "Recommended": "Yes" if best_phone != user_phone else "No better phone in range",
+    }
+    return result
 
-# Import tool from Hub
-image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
+#### Gradio UI ####
+def agent_ui(user_phone_name):
+    """Gradio UI interface handler."""
+    result = recommend_smartphone(user_phone_name)
+    return f"""
+    **Your phone:** {result['Your phone']}
+    **Churn score:** {result['Your phone score']}
+    **Best alternative:** {result['Best competitor']} (score: {result['Best score']})
+    **Recommended:** {result['Recommended']}
+    """
 
+# Connect everything for Hugging Face Space
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
-    
+
+model = HfApiModel(
+    max_tokens=2096,
+    temperature=0.5,
+    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+)
+
 agent = CodeAgent(
     model=model,
-    tools=[final_answer], ## add your tools here (don't remove final answer)
+    tools=[recommend_smartphone],  # add your main tool, you can add others as desired
     max_steps=6,
     verbosity_level=1,
     grammar=None,
@@ -65,5 +127,4 @@ agent = CodeAgent(
     prompt_templates=prompt_templates
 )
 
-
-GradioUI(agent).launch()
+GradioUI(agent_ui).launch()