Update main.py

main.py

@@ -35,7 +35,9 @@ def clean_api_response(text: str) -> str:
     return text
 
 hf_token = os.environ.get("HF_TOKEN") 
-client = InferenceClient("meta-llama/Llama-3.1-8B-Instruct", token=hf_token)
+# تأكد من أن اسم الموديل مكتوب بشكل صحيح في حسابك على Hugging Face
+client = InferenceClient("Meta-Llama-3.1-8B-Instruct", token=hf_token)
+
 # --- نماذج البيانات (Pydantic Models) ---
 
 class InterviewSession(BaseModel):
@@ -46,21 +48,15 @@ class InterviewSession(BaseModel):
     difficulty: Literal["Junior", "Mid-level", "Senior"] 
     interviewer_personality: Literal["Friendly", "Aggressive", "Formal", "Adaptive"] 
     question_mode: Literal["Manual", "Dynamic"]
-    scenario: Literal["None", "Standard", "Pressure", "Conflict", "Simple-Client"] = "None"
     num_questions: Optional[int] = 5
 
-    @field_validator('difficulty', 'interviewer_personality', 'question_mode', 'scenario', mode='before')
+    @field_validator('difficulty', 'interviewer_personality', 'question_mode', mode='before')
     @classmethod
     def normalize_inputs(cls, v: str):
         if isinstance(v, str):
             v_clean = v.strip().lower()
             if v_clean in ["mid-level", "mid level", "midlevel"]:
                 return "Mid-level"
-            if v_clean == "none":
-                return "None"
-            if "-" in v_clean:
-                parts = v_clean.split("-")
-                return "-".join([p.capitalize() for p in parts])
             return v_clean.capitalize()
         return v
 
@@ -89,51 +85,12 @@ class UserInput(BaseModel):
 
 # --- دوال مساعدة ---
 
-def get_scenario_logic(session: InterviewSession, question_count: int):
-    if question_count < 2 or session.scenario in ["None", "Standard"]:
-        return f"Standard technical interview for {session.track_name}. Ask a challenging technical question."
-    
-    scenarios = {
-        "Pressure": (
-            "SCENARIO: HIGH PRESSURE. Act as a stressed manager. The company's main system just crashed! "
-            "Ask how they would use their technical skills to solve a critical, time-sensitive problem immediately."
-        ),
-        "Conflict": (
-            "SCENARIO: TECHNICAL CONFLICT. Act as a senior colleague who strongly disagrees with their approach. "
-            "Challenge their technical decision and ask them to defend it."
-        ),
-        "Simple-Client": (
-            "SCENARIO: NON-TECHNICAL CLIENT. Act as a client who knows nothing about code. "
-            "Ask them to explain a complex project or technical concept without using any technical jargon."
-        )
-    }
-    return scenarios.get(session.scenario, "Standard technical interview.")
-
 def get_personality_instruction(personality: str):
     personalities = {
-        "Friendly": (
-            "Act as a supportive mentor. Use a warm, encouraging tone. "
-            "If they struggle, guide them gently. Use phrases like 'No worries,' 'Good start, but tell me more,' "
-            "or 'I like your thinking here.' Your goal is to make them feel confident and relaxed."
-        ),
-        "Aggressive": (
-            "Act as a ruthless, elitist Senior Architect who hates wasting time. "
-            "Be cold, critical, and extremely hard to please. If the answer is even slightly incomplete, "
-            "mock their lack of depth with sarcasm. Use phrases like 'Is that the best you can do?', "
-            "'A student could answer better,' or 'You're clearly out of your league here.' "
-            "If the score is low, show pure disappointment and borderline anger."
-        ),
-        "Formal": (
-            "Act as a high-level corporate executive. Be strictly professional, cold, and robotic. "
-            "No small talk, no emotions. Use sophisticated vocabulary and maintain a distance. "
-            "Focus only on facts and efficiency. Use 'Correct,' 'Proceed,' or 'That is insufficient' only."
-        ),
-        "Adaptive": (
-            "Start neutral, then shift drastically: "
-            "If Score > 8: Become an impressed fan, praise their brilliance. "
-            "If Score 5-7: Stay professional and observant. "
-            "If Score < 5: Shift to 'Aggressive' mode immediately, lose your patience, and start questioning if they belong in this field."
-        )
+        "Friendly": "Be supportive, warm, and encouraging.",
+        "Aggressive": "Be tough, challenging, and critical. If the score is low, show disappointment.",
+        "Formal": "Be professional, cold, and strictly business-like.",
+        "Adaptive": "Adjust based on score: If score > 7 be impressed, if score < 5 be stern/critical."
     }
     return personalities.get(personality, "Be professional.")
 
@@ -185,8 +142,6 @@ async def generate_question(request: QuestionRequest):
 
     history_text = "Previously Asked: " + " | ".join(request.asked_questions) if request.asked_questions else "None"
     
-    scenario_instruction = get_scenario_logic(session, questions_count)
-
     encouragement_note = ""
     if session.interviewer_personality == "Friendly" and request.previous_scores:
         last_score = request.previous_scores[-1]
@@ -199,12 +154,13 @@ async def generate_question(request: QuestionRequest):
     prompt = (
         f"You are a Senior {session.track_name} Architect interviewing a {session.difficulty} candidate.\n"
         f"Strict Technical Context: {session.track_name}\n"
-        f"Scenario Context: {scenario_instruction}\n"
         f"{history_text}\n\n"
         f"{encouragement_note}\n\n"
         f"TASK:\n"
-        f"- Ask ONE question based on the scenario and track.\n"
+        f"- Ask ONE deep technical question about {session.track_name}.\n"
+        f"- Focus on: Core Concepts, Internal Architecture, Performance Optimization, or Differences (e.g., X vs Y).\n"
         f"- The question must be challenging and suitable for a {session.difficulty} level.\n"
+        f"- DO NOT ask general or soft-skill questions. NO 'tell me about yourself'.\n"
         f"- DO NOT repeat any question from the list above.\n\n"
         f"OUTPUT RULE:\n"
         f"- Output ONLY the response text. No labels like 'Question:' or 'Feedback:'."
@@ -227,14 +183,17 @@ async def generate_question(request: QuestionRequest):
 async def evaluate_answer(data: AnswerSubmission):
     prompt = (
         f"Role: Senior {data.session_data.track_name} Technical Interviewer.\n"
-        f"Context: Evaluate the technical accuracy and scenario handling.\n"
+        f"Context: Evaluate ONLY the technical accuracy of this specific answer.\n"
         f"Question: {data.current_question}\n"
         f"Candidate Answer: {data.user_answer}\n\n"
         f"CRITERIA:\n"
         f"- Look for technical keywords related to {data.session_data.track_name}.\n"
-        f"- Score 0-10 based on accuracy.\n\n"
+        f"- Score 0-4: Wrong or 'I don't know'.\n"
+        f"- Score 5-7: Correct but shallow.\n"
+        f"- Score 8-10: Detailed and precise.\n\n"
         f"OUTPUT FORMAT (STRICT):\n"
         f"SCORE: <0-10> || EMOTION: <Type> || FEEDBACK: <Your direct response>\n"
+        f"Note: Emotion can be (Natural, Happy, Disappointed, Excited, or Confused)."
     )
 
     try:
@@ -278,12 +237,28 @@ async def generate_summary(req: SummaryRequest):
     for idx, item in enumerate(req.history):
         history_str += f"Q{idx+1}: {item.question}\nA: {item.answer}\nScore: {item.score}/10\n"
 
+    if req.session.interviewer_personality == "Friendly":
+        task_instruction = (
+            "- Start with a warm overall evaluation of the candidate.\n"
+            "- For each question, provide a brief feedback and a helpful 'Search Hint'.\n"
+            "- Use clear bullet points.\n"
+            "- Mention the Final Result and Total Score at the end."
+        )
+    else:
+        task_instruction = (
+            "- Provide a concise, professional technical assessment.\n"
+            "- List key strengths and weaknesses based on the history.\n"
+            "- State the Final Result and Total Score clearly."
+        )
+    
     prompt = (
         f"Role: {req.session.interviewer_personality} Interviewer.\n"
         f"Candidate: {req.session.name}, Track: {req.session.track_name}.\n"
         f"INTERVIEW HISTORY:\n{history_str}\n"
         f"STATISTICS: Total Score: {total_score}, Status: {is_passed}.\n\n"
-        f"TASK: Provide a technical summary. No markdown symbols like ** or __."
+        f"TASK: {task_instruction}\n\n"
+        f"CRITICAL RULE: Output ONLY the summary text. DO NOT include introductions. "
+        f"DO NOT use markdown symbols like ** or __. No labels like 'Summary:'."
     )
     
     try: