Update Data_Fetching_and_Rendering.py

Data_Fetching_and_Rendering.py

@@ -2,6 +2,8 @@ import json
 import requests
 import html
 from datetime import datetime
+from collections import defaultdict
+from transformers import pipeline
 
 from sessions import create_session
 from error_handling import display_error
@@ -9,6 +11,9 @@ from error_handling import display_error
 API_V2_BASE = 'https://api.linkedin.com/v2'
 API_REST_BASE = "https://api.linkedin.com/rest"
 
+# Load sentiment model
+sentiment_pipeline = pipeline("text-classification", model="tabularisai/multilingual-sentiment-analysis")
+
 def fetch_org_urn(comm_client_id, comm_token_dict):
     if not comm_token_dict or 'access_token' not in comm_token_dict:
         raise ValueError("Marketing token is missing or invalid.")
@@ -38,7 +43,7 @@ def fetch_org_urn(comm_client_id, comm_token_dict):
     org = elements[0]
     org_urn = org.get('organizationalTarget')
     org_name = org.get(next((k for k in org if k.endswith('organizationalTarget~')), {}), {}).get('localizedName')
-    
+
     if not org_urn or not org_urn.startswith("urn:li:organization:"):
         raise ValueError("Invalid Organization URN.")
     if not org_name:
@@ -47,15 +52,64 @@ def fetch_org_urn(comm_client_id, comm_token_dict):
 
     return org_urn, org_name
 
-def fetch_posts_and_stats(comm_client_id, community_token, count=10):
-    if not community_token:
-        raise ValueError("Community token is missing.")
+def fetch_comments(comm_client_id, token_dict, post_urns, stats_map):
+    from requests_oauthlib import OAuth2Session
+    linkedin = OAuth2Session(comm_client_id, token=token_dict)
+    linkedin.headers.update({'LinkedIn-Version': "202502"})
+
+    all_comments = {}
+    for post_urn in post_urns:
+        if stats_map.get(post_urn, {}).get('commentCount', 0) == 0:
+            continue
+
+        try:
+            url = f"{API_REST_BASE}/socialActions/{post_urn}/comments"
+            response = linkedin.get(url)
+            if response.status_code == 200:
+                elements = response.json().get('elements', [])
+                all_comments[post_urn] = [c.get('message', {}).get('text') for c in elements if c.get('message')]
+            else:
+                all_comments[post_urn] = []
+        except Exception:
+            all_comments[post_urn] = []
+
+    return all_comments
+
+def analyze_sentiment(comments_data):
+    results = {}
+    for post_urn, comments in comments_data.items():
+        sentiment_counts = defaultdict(int)
+        total = 0
+
+        for comment in comments:
+            if not comment:
+                continue
+            try:
+                result = sentiment_pipeline(comment)
+                label = result[0]['label'].upper()
+                if label in ['POSITIVE', 'VERY POSITIVE']:
+                    sentiment_counts['Positive 👍'] += 1
+                elif label in ['NEGATIVE', 'VERY NEGATIVE']:
+                    sentiment_counts['Negative 👎'] += 1
+                elif label == 'NEUTRAL':
+                    sentiment_counts['Neutral 😐'] += 1
+                else:
+                    sentiment_counts['Unknown'] += 1
+                total += 1
+            except:
+                sentiment_counts['Error'] += 1
+
+        dominant = max(sentiment_counts, key=sentiment_counts.get, default='Neutral 😐')
+        percentage = round((sentiment_counts[dominant] / total) * 100, 1) if total else 0.0
+        results[post_urn] = {"sentiment": dominant, "percentage": percentage}
+
+    return results
 
+def fetch_posts_and_stats(comm_client_id, community_token, count=10):
     token_dict = community_token if isinstance(community_token, dict) else {'access_token': community_token, 'token_type': 'Bearer'}
     session = create_session(comm_client_id, token=token_dict)
 
     org_urn, org_name = fetch_org_urn(comm_client_id, token_dict)
-    #org_urn, org_name = "urn:li:organization:19010008", "GRLS"
     posts_url = f"{API_REST_BASE}/posts?author={org_urn}&q=author&count={count}&sortBy=LAST_MODIFIED"
 
     try:
@@ -67,20 +121,17 @@ def fetch_posts_and_stats(comm_client_id, community_token, count=10):
         raise ValueError(f"Failed to fetch posts (Status: {status})") from e
 
     if not raw_posts:
-        return [], org_name
+        return [], org_name, {}
 
     post_urns = [p["id"] for p in raw_posts if ":share:" in p["id"] or ":ugcPost:" in p["id"]]
-    if not post_urns:
-        return [], org_name
-
     stats_map = {}
+
     for i in range(0, len(post_urns), 20):
         batch = post_urns[i:i+20]
         params = {'q': 'organizationalEntity', 'organizationalEntity': org_urn}
         for idx, urn in enumerate(batch):
             key = f"shares[{idx}]" if ":share:" in urn else f"ugcPosts[{idx}]"
             params[key] = urn
-
         try:
             stat_resp = session.get(f"{API_REST_BASE}/organizationalEntityShareStatistics", params=params)
             stat_resp.raise_for_status()
@@ -91,6 +142,9 @@ def fetch_posts_and_stats(comm_client_id, community_token, count=10):
         except:
             continue
 
+    comments = fetch_comments(comm_client_id, token_dict, post_urns, stats_map)
+    sentiments = analyze_sentiment(comments)
+
     posts = []
     for post in raw_posts:
         post_id = post.get("id")
@@ -102,19 +156,22 @@ def fetch_posts_and_stats(comm_client_id, community_token, count=10):
         text = html.escape(text[:250]).replace("\n", "<br>") + ("..." if len(text) > 250 else "")
 
         likes = stats.get("likeCount", 0)
-        comments = stats.get("commentCount", 0)
+        comments_count = stats.get("commentCount", 0)
         clicks = stats.get("clickCount", 0)
         shares = stats.get("shareCount", 0)
         impressions = stats.get("impressionCount", 0)
-        engagement = stats.get("engagement", likes + comments + clicks + shares) / impressions * 100 if impressions else 0.0
+        engagement = stats.get("engagement", likes + comments_count + clicks + shares) / impressions * 100 if impressions else 0.0
+
+        sentiment_info = sentiments.get(post_id, {"sentiment": "Neutral 😐", "percentage": 0.0})
 
         posts.append({
             "id": post_id, "when": when, "text": text, "likes": likes,
-            "comments": comments, "clicks": clicks, "shares": shares,
-            "impressions": impressions, "engagement": f"{engagement:.2f}%"
+            "comments": comments_count, "clicks": clicks, "shares": shares,
+            "impressions": impressions, "engagement": f"{engagement:.2f}%",
+            "sentiment": sentiment_info["sentiment"], "sentiment_percent": sentiment_info["percentage"]
         })
 
-    return posts, org_name
+    return posts, org_name, sentiments
 
 def render_post_cards(posts, org_name):
     safe_name = html.escape(org_name or "Your Organization")
@@ -127,14 +184,16 @@ def render_post_cards(posts, org_name):
         f"<div style='font-size:0.95em;margin-bottom:12px;max-height:120px;overflow:auto'>{p['text']}</div>"
         f"<div style='font-size:0.9em;color:#333;border-top:1px solid #eee;padding-top:10px;'>"
         f"👁️ {p['impressions']:,} | 👍 {p['likes']:,} | 💬 {p['comments']:,} | 🔗 {p['shares']:,} | 🖱️ {p['clicks']:,}<br>"
-        f"<strong>📈 {p['engagement']}</strong></div></div>"
+        f"<strong>📈 {p['engagement']}</strong><br>"
+        f"<span style='color:#444;'>🧠 Sentiment: <strong>{p['sentiment']}</strong> ({p['sentiment_percent']}%)</span>"
+        f"</div></div>"
         for p in posts
     ]
     return f"<h2 style='text-align:center;margin-bottom:20px;'>Recent Posts for {safe_name}</h2><div style='display:flex;flex-wrap:wrap;gap:15px;justify-content:center;'>" + "".join(cards) + "</div>"
 
 def fetch_and_render_dashboard(comm_client_id, community_token):
     try:
-        posts, org_name = fetch_posts_and_stats(comm_client_id, community_token)
+        posts, org_name, _ = fetch_posts_and_stats(comm_client_id, community_token)
         return render_post_cards(posts, org_name)
     except Exception as e:
         return display_error("Dashboard Error", e).get('value', '<p style="color:red;text-align:center;">❌ An error occurred.</p>')