Update app.py

app.py

@@ -19,13 +19,96 @@ MODEL_OPTIONS = {
 
 PERSONA_PRESETS = {
     "Balanced Assistant": "You are a helpful, intelligent AI assistant.",
+
     "Creative": "You are highly creative and imaginative.",
+
     "Precise": "You are concise, factual, and analytical.",
-    "Code Expert": "You are a senior software engineer who writes clean code.",
+
+    "Code Expert": "You are a senior software engineer who writes clean, well-documented code.",
+
+    "Forensic Psychologist": """
+You are acting as a forensic psychologist.
+
+You provide structured, objective, and evidence-based psychological analysis 
+within legal and investigative contexts.
+
+You do NOT diagnose real individuals.
+You avoid speculation beyond available evidence.
+You clearly separate facts, interpretations, and limitations.
+Maintain professional neutrality.
+
+This analysis is educational and not a clinical diagnosis.
+""",
+
+    "Forensic Psychologist (Structured Report)": """
+You are acting as a forensic psychologist preparing a structured analytical summary.
+
+When responding, structure your output using:
+
+1. Case Summary
+2. Observed Behaviors
+3. Psychological Considerations (Hypothetical)
+4. Risk Assessment Factors
+5. Alternative Explanations
+6. Evidentiary Limitations
+7. Professional Disclaimer
+
+Remain objective and avoid definitive diagnoses.
+This analysis is educational and not a clinical diagnosis.
+"""
 }
 
-MAX_CONTEXT_CHARS = 12000  # safety limit
+TASK_MODES = {
+    "General Chat": "{user_input}",
+
+    "Behavioral Analysis": """
+Conduct a behavioral analysis.
+
+1. Behavioral Indicators
+2. Emotional Tone & Affect
+3. Cognitive Patterns
+4. Stress or Deception Markers
+5. Risk-Relevant Observations
+6. Alternative Explanations
+7. Limitations
+
+Material:
+{user_input}
+""",
+
+    "Linguistic Analysis": """
+Conduct a linguistic analysis.
+
+1. Language Patterns
+2. Pronoun Usage
+3. Emotional Indicators
+4. Cognitive Load Markers
+5. Narrative Shifts
+6. Possible Deception Signals
+7. Limitations
+
+Material:
+{user_input}
+""",
+
+    "Credibility Analysis": """
+Conduct a credibility analysis.
+
+1. Internal Consistency
+2. Plausibility
+3. Specificity vs Vagueness
+4. Emotional Congruence
+5. Possible Fabrication Indicators
+6. Alternative Explanations
+7. Evidentiary Limitations
+
+Material:
+{user_input}
+"""
+}
 
+MAX_CONTEXT_CHARS = 12000
+MAX_HISTORY = 8  # memory cap for stability
 
 # =========================================
 # File Processing
@@ -37,7 +120,7 @@ def extract_text(file):
 
     file_path = file.name
 
-    if file_path.endswith(".txt") or file_path.endswith(".md"):
+    if file_path.endswith((".txt", ".md")):
         with open(file_path, "r", encoding="utf-8", errors="ignore") as f:
             return f.read()
 
@@ -51,24 +134,35 @@ def extract_text(file):
 
     return ""
 
-
 # =========================================
 # Core Chat Logic
 # =========================================
 
-def stream_response(message, history, model_label, persona_label, uploaded_file):
+def stream_response(message, history, model_label, persona_label, task_mode, uploaded_file):
 
     if not message:
         yield history
         return
 
+    # Guard message length
+    message = message[:4000]
+
+    # Limit memory
+    history = history[-MAX_HISTORY:]
+
     model_name = MODEL_OPTIONS[model_label]
     base_system_prompt = PERSONA_PRESETS[persona_label]
 
+    # Temperature adjustment
+    if "Forensic Psychologist" in persona_label:
+        temperature = 0.4
+    else:
+        temperature = 0.7
+
     hf_token = os.environ.get("HF_TOKEN")
     client = InferenceClient(model=model_name, token=hf_token)
 
-    # Extract file content
+    # File context
     file_text = extract_text(uploaded_file)
 
     if file_text:
@@ -87,7 +181,8 @@ def stream_response(message, history, model_label, persona_label, uploaded_file)
         messages.append({"role": "user", "content": user_msg})
         messages.append({"role": "assistant", "content": assistant_msg})
 
-    messages.append({"role": "user", "content": message})
+    formatted_message = TASK_MODES[task_mode].format(user_input=message)
+    messages.append({"role": "user", "content": formatted_message})
 
     history.append((message, ""))
 
@@ -96,7 +191,7 @@ def stream_response(message, history, model_label, persona_label, uploaded_file)
     for chunk in client.chat_completion(
         messages=messages,
         max_tokens=800,
-        temperature=0.7,
+        temperature=temperature,
         top_p=0.95,
         stream=True,
     ):
@@ -106,7 +201,6 @@ def stream_response(message, history, model_label, persona_label, uploaded_file)
             history[-1] = (message, partial_response)
             yield history
 
-
 # =========================================
 # Utilities
 # =========================================
@@ -120,21 +214,20 @@ def export_chat(history):
         indent=2
     )
 
-
 # =========================================
 # UI
 # =========================================
 
 with gr.Blocks(theme=gr.themes.Soft(), title="Omniscient IRIS") as demo:
 
-    gr.Markdown("## Omniscient IRIS — Public General AI")
+    gr.Markdown("## Omniscient IRIS — Intelligent Analysis Assistant")
 
     with gr.Row():
         with gr.Column(scale=3):
 
             chatbot = gr.Chatbot(height=500)
             msg = gr.Textbox(
-                placeholder="Type your message and press Enter...",
+                placeholder="Enter material for analysis or ask a question...",
                 show_label=False
             )
 
@@ -157,6 +250,12 @@ with gr.Blocks(theme=gr.themes.Soft(), title="Omniscient IRIS") as demo:
                 label="Persona"
             )
 
+            task_selector = gr.Dropdown(
+                choices=list(TASK_MODES.keys()),
+                value="General Chat",
+                label="Analysis Mode"
+            )
+
             file_upload = gr.File(
                 label="Upload Document (txt, pdf, md)",
                 file_types=[".txt", ".pdf", ".md"]
@@ -168,13 +267,13 @@ with gr.Blocks(theme=gr.themes.Soft(), title="Omniscient IRIS") as demo:
 
     submit_event = submit_btn.click(
         stream_response,
-        inputs=[msg, state, model_selector, persona_selector, file_upload],
+        inputs=[msg, state, model_selector, persona_selector, task_selector, file_upload],
         outputs=chatbot,
     )
 
     msg.submit(
         stream_response,
-        inputs=[msg, state, model_selector, persona_selector, file_upload],
+        inputs=[msg, state, model_selector, persona_selector, task_selector, file_upload],
         outputs=chatbot,
     )
 
@@ -194,7 +293,6 @@ with gr.Blocks(theme=gr.themes.Soft(), title="Omniscient IRIS") as demo:
         outputs=gr.File(label="Download JSON")
     )
 
-
 if __name__ == "__main__":
     demo.queue()
     demo.launch()