Add MoodDetectorPlugin to examples/mood_detector_plugin.py and update requirements.txt

examples/mood_detector_plugin.py

@@ -0,0 +1,71 @@
+import nltk
+from nltk.sentiment import SentimentIntensityAnalyzer
+from rich.console import Console
+from rich import print as rprint
+from _context import simplemind as sm
+
+nltk.download("vader_lexicon")
+
+console = Console()
+
+
+class MoodDetectorPlugin(sm.BasePlugin):
+    model_config = {"arbitrary_types_allowed": True}
+    analyzer: SentimentIntensityAnalyzer = None
+
+    def __init__(self):
+        super().__init__()
+        # Initialize sentiment analyzer from nltk
+        self.analyzer = SentimentIntensityAnalyzer()
+
+    def detect_mood(self, text):
+        # Analyze the sentiment of the given text
+        scores = self.analyzer.polarity_scores(text)
+
+        # Print sentiment analysis details with colors
+        console.print("\n[bold]Sentiment Analysis:[/bold]")
+        console.print(f"Text: [italic]{text}[/italic]")
+        console.print("\nScores:")
+        console.print(f"🟢 Positive: [green]{scores['pos']:.3f}[/green]")
+        console.print(f"🔴 Negative: [red]{scores['neg']:.3f}[/red]")
+        console.print(f"⚪ Neutral: [blue]{scores['neu']:.3f}[/blue]")
+        console.print(f"📊 Compound: [yellow]{scores['compound']:.3f}[/yellow]\n")
+
+        if scores["compound"] >= 0.5:
+            console.print("Overall Mood: [green]positive[/green] 😊")
+            return "positive"
+        elif scores["compound"] <= -0.5:
+            console.print("Overall Mood: [red]negative[/red] 😢")
+            return "negative"
+        else:
+            console.print("Overall Mood: [blue]neutral[/blue] 😐")
+            return "neutral"
+
+    def pre_send_hook(self, conversation: sm.Conversation):
+        # Get the last user message to analyze its mood
+        last_message = conversation.get_last_message(role="user")
+        if last_message:
+            mood = self.detect_mood(last_message.text)
+            # Adjust AI response style based on the detected mood
+            if mood == "positive":
+                tone_message = (
+                    "The user seems cheerful. Respond with enthusiasm and positivity."
+                )
+            elif mood == "negative":
+                tone_message = "The user seems to be in a low mood. Respond with empathy and warmth."
+            else:
+                tone_message = "The user seems neutral. Respond with a balanced tone."
+
+            # Inject the tone adjustment message as a system prompt
+            conversation.add_message(role="system", text=tone_message)
+
+
+# Create a conversation and add the plugin
+conversation = sm.create_conversation(llm_model="gpt-4o-mini", llm_provider="openai")
+conversation.add_plugin(MoodDetectorPlugin())
+
+# Add a user message and send the conversation
+conversation.add_message(role="user", text="I'm having a really rough day.")
+response = conversation.send()
+
+console.print(f"*{ response.text }*")

examples/requirements.txt

@@ -3,3 +3,4 @@ openai
 pydantic
 faiss-cpu
 rich
+nltk

simplemind/models.py

@@ -30,6 +30,7 @@ class BasePlugin(SMBaseModel):
 
     class Config:
         extra = "allow"
+        # allow_arbitrary_types = True
 
     def initialize_hook(self, conversation: "Conversation") -> Any:
         """Initialize a hook for the plugin."""