F

app.py

@@ -6,6 +6,7 @@ import gradio as gr
 from transformers import pipeline
 import csv
 import tempfile
+import time
 from datetime import datetime, timedelta
 from urllib.parse import quote
 
@@ -43,16 +44,23 @@ def analyze_single_company(company_name: str, api_key: str, is_forced_analysis:
         url = f'https://newsapi.org/v2/everything?q="{encoded_company_name}"&from={thirty_days_ago}&sortBy=relevancy&language=en&apiKey={api_key}'
 
     try:
-        response = requests.get(url, timeout=15)
-        response.raise_for_status()
+        response = requests.get(url, timeout=20)
+        response.raise_for_status() # This will raise an HTTPError for 4xx/5xx responses
         articles = response.json().get("articles", [])
     except requests.exceptions.RequestException as e:
+        error_message = "API Request Failed."
+        if hasattr(e, 'response') and e.response is not None:
+            if e.response.status_code == 401:
+                error_message = "API Key is invalid or expired."
+            elif e.response.status_code == 429:
+                error_message = "API Rate Limit Exceeded."
+        
         print(f"API request failed for {company_name}: {e}")
         return {
             "Company": f"{company_name} {'(Forensic)' if is_forced_analysis else ''}",
             "Distress Score": -1,
-            "Summary": "API Request Failed",
-            "Key Evidence": "Possible rate limit or timeout."
+            "Summary": error_message,
+            "Key Evidence": "Please check your API key and try again with a smaller list."
         }
 
     if not articles:
@@ -61,7 +69,7 @@ def analyze_single_company(company_name: str, api_key: str, is_forced_analysis:
             summary = "Forensic search found no articles matching distress keywords."
         return {"Company": f"{company_name} {'(Forensic)' if is_forced_analysis else ''}", "Distress Score": 0, "Summary": summary, "Key Evidence": "N/A"}
 
-    # --- Initialize Metrics ---
+    # ... [rest of the analysis logic is the same] ...
     total_sentiment_score, sentiment_articles_count = 0, 0
     shutdown_mentions, layoff_mentions, exec_departure_mentions, negative_funding_mentions = 0, 0, 0, 0
     key_evidence = []
@@ -126,14 +134,13 @@ def batch_analyze_companies(company_list_str: str, high_suspicion_list_str: str,
     all_results = []
     progress(0, desc="Starting Analysis...")
     
-    # --- Sequential Processing for Reliability ---
-    # This loop processes one company at a time to avoid API rate limits.
     for i, name in enumerate(all_names):
         is_suspicious = name in suspicion_names
         progress((i) / len(all_names), desc=f"Analyzing {name}...")
         try:
             result = analyze_single_company(name, api_key, is_suspicious)
             if result: all_results.append(result)
+            time.sleep(0.5) # Add a small delay between requests to be gentle on the API
         except Exception as exc:
             print(f'{name} generated an exception: {exc}')
             all_results.append({
@@ -158,15 +165,15 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="blue")) a
     gr.Markdown("# PE Sourcing Intelligence Engine")
     gr.Markdown(
         """
-        **Step 1:** Add companies you are screening to the **Standard Watch List**.
-        **Step 2:** For companies you already suspect are distressed, add them to the **Forensic Analysis List** for a deeper, targeted search.
+        **Step 1:** Add companies to the **Standard Watch List**.
+        **Step 2:** For high-suspicion targets, add them to the **Forensic Analysis List** for a deeper search.
         **Pro Tip:** This tool runs sequentially to be reliable with free APIs. Long lists will take time. Please be patient.
         """
     )
     
     with gr.Row():
         with gr.Column(scale=1):
-            news_api_key_input = gr.Textbox(label="Enter Your NewsAPI Key", type="password", placeholder="Paste your key here")
+            news_api_key_input = gr.Textbox(label="Enter Your NewsAPI Key", type="password", placeholder="Paste your new, correct key here")
             company_list_input = gr.TextArea(label="Standard Watch List", lines=8, placeholder="Screening List:\nAcme Corp\nInnovate Inc...")
             high_suspicion_input = gr.TextArea(label="Forensic Analysis List", lines=7, placeholder="High-Suspicion Targets:\nConvoy\nWeWork...")
             submit_button = gr.Button("Generate Distress Briefing", variant="primary")