Update app.py

add review sentiment analysis for product

app.py

@@ -89,6 +89,54 @@ def sig_expander(sig: str) -> str:
     }
 
     return sig_map.get(sig.lower(), "❌ No direct match found. Please clarify.")
+
+    def scrape_amazon_reviews(product_url):
+    """Scrapes reviews from an Amazon product page (basic version)."""
+    headers = {"User-Agent": "Mozilla/5.0"}
+    response = requests.get(product_url, headers=headers)
+    if response.status_code != 200:
+        return f"❌ Error fetching Amazon reviews: {response.status_code}"
+
+    soup = BeautifulSoup(response.text, 'html.parser')
+    reviews = [r.text.strip() for r in soup.find_all("span", {"data-hook": "review-body"})]
+    return reviews[:10]  # Return the first 10 reviews
+
+def analyze_sentiment(reviews):
+    """Analyzes the sentiment of a list of reviews."""
+    results = {"Positive": 0, "Neutral": 0, "Negative": 0}
+    for review in reviews:
+        sentiment_score = TextBlob(review).sentiment.polarity
+        if sentiment_score > 0.2:
+            results["Positive"] += 1
+        elif sentiment_score < -0.2:
+            results["Negative"] += 1
+        else:
+            results["Neutral"] += 1
+    return results
+
+def generate_summary(results):
+    """Generates a summary report of sentiment analysis."""
+    total = sum(results.values())
+    if total == 0:
+        return "No reviews available for analysis."
+    return (
+        f"🔍 **Sentiment Analysis Report:**\n"
+        f"✅ Positive: {results['Positive']} ({(results['Positive']/total)*100:.1f}%)\n"
+        f"⚖️ Neutral: {results['Neutral']} ({(results['Neutral']/total)*100:.1f}%)\n"
+        f"❌ Negative: {results['Negative']} ({(results['Negative']/total)*100:.1f}%)"
+    )
+@tool
+def review_sentiment_tool(product_url: str) -> str:
+    """Agent tool: Scrapes reviews and performs sentiment analysis.
+    Args:
+        product_url: the amazon url for product to be evaluated
+    """
+    reviews = scrape_amazon_reviews(product_url)
+    if isinstance(reviews, str):  # Error message
+        return reviews
+    sentiment_results = analyze_sentiment(reviews)
+    return generate_summary(sentiment_results)
+    
 @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
@@ -133,7 +181,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, sig_expander,drug_interaction_checker], ## add your tools here (don't remove final answer)
+    tools=[final_answer, review_sentiment_tool], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,