Update app.py

app.py

@@ -2,44 +2,55 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 import requests
 
+# Main + Fallback Models
 MODELS = [
     "meta-llama/Meta-Llama-3-8B-Instruct",
     "mistralai/Mistral-7B-Instruct-v0.3",
     "google/gemma-7b-it",
+    "HuggingFaceH4/zephyr-7b-beta"  # reliable fallback
 ]
 
-# ---------- Chat Function ----------
+# ---------- Chat ----------
 def chat_with_ai(message, history):
     if history is None:
         history = []
     for model in MODELS:
         try:
             client = InferenceClient(model)
-            conversation = ""
-            for h in history:
-                conversation += f"User: {h[0]}\nStudyMate: {h[1]}\n"
-            full_prompt = (
-                "You are StudyMate AI — a multilingual personal tutor and career assistant.\n"
-                "Answer questions in the same language as the user (Urdu or English).\n\n"
-                + conversation
-                + f"User: {message}\nStudyMate:"
+            conversation = "".join(
+                [f"User: {h[0]}\nStudyMate: {h[1]}\n" for h in history]
+            )
+            prompt = (
+                "You are StudyMate AI — a friendly, multilingual personal tutor and assistant. "
+                "You answer *every* question completely in the user’s language (English or Urdu). "
+                "If unsure, provide a helpful general explanation or example.\n\n"
+                f"{conversation}User: {message}\nStudyMate:"
             )
-
             reply = ""
             for chunk in client.text_generation(
-                full_prompt,
-                max_new_tokens=512,
-                stream=True,
-                temperature=0.7,
+                prompt, max_new_tokens=512, stream=True, temperature=0.7
             ):
                 reply += chunk.token
-            history.append([message, reply])
-            return history, ""
+            if reply.strip():
+                history.append([message, reply])
+                return history, ""
         except Exception:
             continue
-    history.append([message, "Sorry, I couldn’t generate a full answer right now. Please try again."])
+    # Ultimate fallback response
+    history.append([message, "I'm having a little trouble fetching a detailed response, but here's a quick idea:\n"
+                             f"{generate_smart_fallback(message)}"])
     return history, ""
 
+def generate_smart_fallback(question):
+    # Simple built-in emergency logic
+    if "job" in question.lower():
+        return "Try searching for this in the Job Finder tab — it's updated daily with remote and local roles."
+    if "career" in question.lower():
+        return "Focus on upskilling and building a small portfolio — it opens many doors faster than degrees alone."
+    if "love" in question.lower():
+        return "Love and respect go hand in hand — nurture both and life feels lighter."
+    return "I’ll keep learning from your feedback — please rephrase or ask again."
+
 # ---------- Job Finder ----------
 def find_jobs(skill):
     if not skill:
@@ -86,20 +97,22 @@ def career_guidance(skills, goal, education):
         try:
             client = InferenceClient(model)
             prompt = (
-                "You are StudyMate AI — a professional career coach.\n"
-                "Analyze the user's skills, goals, and education level.\n"
-                "Suggest realistic career paths, high-demand roles, and recommended learning platforms.\n"
-                "Output in clear, structured bullet points.\n\n"
-                f"Skills: {skills}\nGoal: {goal}\nEducation: {education}\n\n"
-                "Career Recommendations:"
+                "You are StudyMate AI — a professional career coach. "
+                "Give career path suggestions, high-demand roles, and study resources. "
+                "Write in clear, bullet-point form. If Urdu is detected, reply in Urdu.\n\n"
+                f"Skills: {skills}\nGoal: {goal}\nEducation: {education}\n\nCareer Advice:"
             )
             reply = ""
-            for chunk in client.text_generation(prompt, max_new_tokens=600, stream=True, temperature=0.7):
+            for chunk in client.text_generation(
+                prompt, max_new_tokens=600, stream=True, temperature=0.7
+            ):
                 reply += chunk.token
-            return reply
+            if reply.strip():
+                return reply
         except Exception:
             continue
-    return "Sorry, I couldn’t generate a full career plan right now."
+    return "Sorry, I couldn’t load a detailed career plan, but here’s a quick tip:\n" \
+           "Pick one skill you enjoy most and start offering it online — consistent practice beats overthinking."
 
 # ---------- UI Theme ----------
 css_code = """
@@ -155,10 +168,9 @@ with gr.Blocks(css=css_code, theme=gr.themes.Soft(primary_hue="blue")) as demo:
         refresh.click(show_job_posts, None, posts_display)
 
     with gr.Tab("🧭 Career Compass"):
-        gr.Markdown("### 🎯 Personalized Career Guidance")
-        skills = gr.Textbox(label="Your Skills (e.g. Video Editing, Marketing, Python)")
-        goal = gr.Textbox(label="Career Goal (e.g. Freelance Developer, Doctor, Designer)")
-        education = gr.Textbox(label="Education Level (e.g. Intermediate, Graduate, PhD)")
+        skills = gr.Textbox(label="Your Skills (e.g. Video Editing, Marketing)")
+        goal = gr.Textbox(label="Career Goal (e.g. Doctor, Developer, Designer)")
+        education = gr.Textbox(label="Education Level (e.g. Intermediate, Graduate)")
         generate = gr.Button("Get Career Plan")
         output = gr.Markdown()
         generate.click(career_guidance, [skills, goal, education], output)