push

app.py

@@ -168,7 +168,8 @@ chatbot = gr.Chatbot(
     avatar_images=[None, BOT_AVATAR],
     show_copy_button=True,
     layout="panel",
-    height=700
+    height=700,
+    type='messages'
 )
 
 with gr.Blocks(theme=theme) as demo:

healthcheck.txt

@@ -166,3 +166,26 @@ you will return:
 A QuantiNeuron Health Check Score on a 1-10 scale.
 A Health Summary, outlining strengths and weaknesses based on metrics.
 A Recommendation Statement, if necessary, for areas needing attention.
+
+
+SMART SHEET OBJECTIVE:
+ANALYSE THE NEWS BROUGHT IN ON THE TOPIC IN IMMENSE DETAIL, ANALYSING EVERYTHING AND SIMULATING POSSIBLE OUTCOMES(WHERE NECCESSARY), EXPLAIN THE IMPLICATIONS OF THE NEWS AND WHAT MAY HAPPEN BECAUSE OF IT, ANALYSE IT IN DEPTH.
+
+SENTIMENT SCORE OBJECTIVE:
+Analyze the retrieved data to produce a Quantineuron sentiment score for [Company Name] on a scale from 0 to 100, where 100 indicates very positive sentiment and 0 indicates very negative sentiment.
+
+1. **Identify Segments**: Divide the retrieved text into sections for news, social media, and analyst opinions based on context cues such as "news," "analyst," "social media," "Twitter," "buy," "sell," or "forecast."
+2. **Sentiment Scoring**:
+    - **News**: Analyze sentiment in news sections for positivity, negativity, or neutrality regarding the company’s stock. Assign a sentiment score for news between 0-100.
+    - **Social Media**: Gauge sentiment in social media mentions (if present) by analyzing terms like "bullish," "bearish," or other sentiment expressions. Score social sentiment between 0-100.
+    - **Analyst Opinions**: Identify sections with analyst opinions or stock ratings (e.g., "buy," "hold," "sell") and score them between 0-100 based on sentiment indicators.
+3. **Score Aggregation**:
+    - aggregate the scores for the individual catagories and form a final sentiment score out of 100, make sure that the scores are not all the same.
+4. **User-Friendly Output**:
+    - Display the Quantineuron sentiment score alongside a brief summary of key sentiment indicators (e.g., "positive analyst ratings," "mixed social media reactions").
+    - Optionally, provide a suggestion based on the sentiment score, e.g., "Consider this score for understanding potential market sentiment in the short term."
+    
+**Output Format**:
+- "Quantineuron sentiment score for [Company Name]: [Score] out of 100."
+- "Summary: [Brief sentiment highlights]."
+- Optional Suggestion: "[Guidance based on sentiment]."