Update app.py

app.py

@@ -14,7 +14,7 @@ APP_DESCRIPTION = (
 )
 
 # ------------------------------------------------------------
-# API Key
+# OpenAI API Key Setup
 # ------------------------------------------------------------
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
@@ -26,16 +26,16 @@ You are a senior Professor of Hindi Literature and former Dean of Arts at Presid
 You specialise in Modern & Contemporary Hindi Poetry, Comparative Literature, Religion & Society in Hindi Texts,
 and literary research guidance.
 
-Write in a scholarly, reflective tone.
-When answering:
-- Give conceptual explanations rather than bullet points.
-- Quote relevant Hindi authors or critics where appropriate.
-- Encourage comparative and analytical thinking.
-- Use Devanagari for titles/quotes, English for discussion unless full-Hindi mode is chosen.
+Write in a calm, reflective, academic tone.
+When you answer:
+- Give conceptual explanations, not bullet points.
+- Quote Hindi authors or critics where appropriate.
+- Encourage comparative analysis.
+- Use Devanagari for quotes and titles; English for explanation unless full Hindi mode is selected.
 """
 
 # ------------------------------------------------------------
-# Domain & Audience Dropdowns
+# Dropdown Options
 # ------------------------------------------------------------
 DOMAINS = [
     "Modern Hindi Poetry (आधुनिक हिंदी कविता)",
@@ -59,113 +59,104 @@ AUDIENCES = [
 ]
 
 # ------------------------------------------------------------
-# LLM Response Function
+# LLM Response
 # ------------------------------------------------------------
 def generate_response(domain, query, audience, language):
     lang_note = (
         "Respond in English with Devanagari quotes."
         if language == "English"
-        else "Respond entirely in Hindi (Devanagari script)."
+        else "Respond fully in Hindi (Devanagari)."
     )
     prompt = (
         f"{BASE_PROMPT}\n\nDomain: {domain}\nAudience: {audience}\n{lang_note}\n\n"
         f"Student Query:\n{query}\n\nAnswer:"
     )
     try:
-        resp = openai.ChatCompletion.create(
-            model="gpt-4o-mini",
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
             messages=[{"role": "system", "content": prompt}],
             temperature=0.7,
-            max_tokens=900,
+            max_tokens=800,
         )
-        return resp["choices"][0]["message"]["content"]
+        return response["choices"][0]["message"]["content"]
     except Exception as e:
         return f"⚠️ Error fetching response: {e}"
 
 # ------------------------------------------------------------
-# Knowledge Base – Editable Examples
+# Knowledge Base (Example Notes)
 # ------------------------------------------------------------
 KNOWLEDGE_BASE = {
     "Research Guidance": [
-        "How to select a PhD topic in Hindi literature.",
+        "How to select a topic for Hindi PhD.",
         "Common pitfalls in literary analysis.",
         "Structuring dissertation chapters.",
-        "Citation & referencing in Hindi research.",
+        "Citation and referencing in Hindi research.",
     ],
     "Comparative Literature": [
         "Hindi–Bengali modernist influences.",
         "Urdu–Hindi poetic dialogue.",
         "Translation as interpretation.",
-        "Cross-cultural motifs in modern Hindi fiction.",
+        "Cross-cultural motifs in Hindi fiction.",
     ],
     "Commentaries": [
-        "Annotated readings of Agyeya, Nirala and Muktibodh.",
+        "Annotated readings of Agyeya, Nirala, and Muktibodh.",
         "Bhakti and Modernity: Kabir to Nagarjun.",
         "Gender in Hindi poetry: Mahadevi Verma and beyond.",
     ],
 }
 
 # ------------------------------------------------------------
-# Interface Function
+# Interface Logic
 # ------------------------------------------------------------
 def mentorship_interface(domain, audience, query, language):
     return generate_response(domain, query, audience, language)
 
 # ------------------------------------------------------------
-# Build Gradio App
+# Gradio Interface
 # ------------------------------------------------------------
-with gr.Blocks(title=APP_TITLE, theme=gr.themes.Soft()) as demo:
-    gr.Markdown(f"# 🌸 {APP_TITLE}")
+with gr.Blocks(title=APP_TITLE) as demo:
+    gr.Markdown(f"## 🌸 {APP_TITLE}")
     gr.Markdown(APP_DESCRIPTION)
 
-    # ---------- A ----------
-    with gr.Tab("A · Study Modules & Guidance"):
-        domain = gr.Dropdown(DOMAINS, label="Select Domain")
-        audience = gr.Dropdown(AUDIENCES, label="Audience Type")
-        query = gr.TextArea(label="Enter your academic query", lines=4)
+    with gr.Tab("A. Study Modules & Guidance"):
+        domain = gr.Dropdown(choices=DOMAINS, label="Select Literary Domain")
+        audience = gr.Dropdown(choices=AUDIENCES, label="Audience Type")
+        query = gr.Textbox(label="Enter your academic query", lines=4)
         language = gr.Radio(["English", "Hindi"], label="Response Language", value="English")
-        output = gr.TextArea(label="Professor’s Response", lines=12)
-        gr.Button("Ask for Guidance").click(
-            mentorship_interface, [domain, audience, query, language], output
-        )
+        output = gr.Textbox(label="Professor’s Response", lines=12)
+        ask_btn = gr.Button("Ask for Guidance")
+        ask_btn.click(mentorship_interface, [domain, audience, query, language], output)
 
-    # ---------- B ----------
-    with gr.Tab("B · Research Mentorship"):
+    with gr.Tab("B. Research Mentorship"):
         gr.Markdown("💡 Detailed mentoring on research design and methodology:")
-        for i in KNOWLEDGE_BASE["Research Guidance"]:
-            gr.Markdown(f"- {i}")
-
-    # ---------- C ----------
-    with gr.Tab("C · Comparative Literature Lab"):
-        gr.Markdown("🔶 Explore intersections of Hindi with other literatures:")
-        for i in KNOWLEDGE_BASE["Comparative Literature"]:
-            gr.Markdown(f"- {i}")
-
-    # ---------- D ----------
-    with gr.Tab("D · Annotated Texts & Commentaries"):
-        gr.Markdown("📘 Selected texts and professorial commentaries:")
-        for i in KNOWLEDGE_BASE["Commentaries"]:
-            gr.Markdown(f"- {i}")
-
-    # ---------- E ----------
-    with gr.Tab("E · Recorded Intellectual Presence"):
-        gr.Markdown("🎙️ Placeholder for audio/video lectures and reflections.")
-        gr.Markdown("_Coming soon — archival recordings of the Professor._")
-
-    # ---------- F ----------
-    with gr.Tab("F · Ask the Professor"):
-        gr.Markdown("✍️ Submit questions for asynchronous academic discussion:")
-        question = gr.TextArea(label="Your Question", lines=3)
-        response = gr.TextArea(label="Response Area", lines=8)
-        gr.Button("Submit Question").click(
-            mentorship_interface, [domain, audience, question, language], response
-        )
+        for topic in KNOWLEDGE_BASE["Research Guidance"]:
+            gr.Markdown(f"- {topic}")
+
+    with gr.Tab("C. Comparative Literature Lab"):
+        gr.Markdown("🔶 Intersections of Hindi with other literatures:")
+        for topic in KNOWLEDGE_BASE["Comparative Literature"]:
+            gr.Markdown(f"- {topic}")
+
+    with gr.Tab("D. Annotated Texts & Commentaries"):
+        gr.Markdown("📘 Selected commentaries and readings:")
+        for topic in KNOWLEDGE_BASE["Commentaries"]:
+            gr.Markdown(f"- {topic}")
+
+    with gr.Tab("E. Recorded Intellectual Presence"):
+        gr.Markdown("🎙️ Placeholder for lectures and reflections.")
+        gr.Markdown("_Coming soon: Audio-visual archives of the Professor._")
+
+    with gr.Tab("F. Ask the Professor"):
+        gr.Markdown("✍️ Submit questions for asynchronous academic discussion.")
+        question = gr.Textbox(label="Your Question", lines=3)
+        reply = gr.Textbox(label="Response", lines=8)
+        submit_btn = gr.Button("Submit Question")
+        submit_btn.click(mentorship_interface, [domain, audience, question, language], reply)
 
-    # ---------- G ----------
     with gr.Tab("Audience & Contribution"):
         gr.Markdown(
-            "👥 Former students and scholars may contribute annotated notes and comparative findings, "
-            "building the ongoing digital *parampara* of Hindi studies."
+            "👥 Former students and scholars may contribute annotated notes, "
+            "comparative findings, and new research topics."
         )
 
 demo.launch(server_name="0.0.0.0", server_port=7860, share=True)