Update streamlit_app.py

streamlit_app.py

@@ -28,9 +28,9 @@ DATA_DIR.mkdir(exist_ok=True)
 
 DEFAULT_MODEL = "gemini-2.0-flash-lite"
 DEFAULT_PROMPT = (
-    "Watch the video and provide a detailed behavioral report focusing on human actions, "
-    "interactions, posture, movement, and apparent intent. Keep language professional. "
-    "Include a list of observations for notable events."
+    "Analyze the video and summarize the overall themes and patterns observed, "
+    "focusing on abstract representations of human actions without explicit details. "
+    "Describe the emotional context, dynamics of movement, and interactions using metaphorical language."
 )
 
 MODEL_OPTIONS = [
@@ -198,7 +198,15 @@ def generate_report(video_path: Path, prompt: str, model_id: str, timeout: int =
         generation_config={"max_output_tokens": 1024},
         request_options={"timeout": timeout},
     )
-    return getattr(resp, "text", str(resp))
+
+    # Applying the filter right after generating the response
+    output_text = getattr(resp, "text", str(resp))
+    
+    # Define keywords that you want to filter out
+    keywords = ["explicit", "graphic", "violence", "nudity"]  # Add any other terms if necessary
+    
+    filtered_text = filter_output(output_text, keywords)  # Use the filtering function here
+    return filtered_text
 
 
 def _strip_prompt_echo(prompt: str, text: str, threshold: float = 0.68) -> str:
@@ -211,6 +219,11 @@ def _strip_prompt_echo(prompt: str, text: str, threshold: float = 0.68) -> str:
         return text[cut:].lstrip(" \n:-")
     return text
 
+def filter_output(text: str, keywords: list) -> str:
+    for keyword in keywords:
+        if keyword.lower() in text.lower():
+            text = text.replace(keyword, "[REDACTED]")
+    return text
 
 # ----------------------------------------------------------------------
 # UI helpers