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main.py

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+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from TextToSpeech import text_to_speech
+import torch
+import base64
+
+# =========================================
+# ENUM MAPPINGS (Match Backend Enums)
+# =========================================
+
+SESSION_TYPES = {
+    1: "technical",
+    2: "softskills"
+}
+
+TRACKS = {
+    19: "generalprogramming"
+}
+
+# =========================================
+# LOAD MODEL ONCE (Global)
+# =========================================
+
+MODEL_PATH = "Fayza38/Question_and_Answer"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
+
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_PATH,
+    torch_dtype=torch.float32,
+    device_map="cpu"
+)
+
+app = FastAPI()
+
+
+# =========================================
+# REQUEST MODEL
+# =========================================
+
+class QuestionRequest(BaseModel):
+    sessionType: int
+    difficultyLevel: int | None = None
+    trackName: int
+
+
+# =========================================
+# HELPER: GENERATE TEXT USING QWEN TEMPLATE
+# =========================================
+
+def generate_from_model(prompt: str):
+
+    messages = [
+        {"role": "system", "content": "You are a professional interview question generator."},
+        {"role": "user", "content": prompt}
+    ]
+
+    formatted_prompt = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+
+    inputs = tokenizer(formatted_prompt, return_tensors="pt")
+
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=1200,
+            temperature=0.7
+        )
+
+    decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    return decoded
+
+
+# =========================================
+# PARSE Q/A FORMAT
+# =========================================
+
+def parse_qa_blocks(text: str):
+
+    blocks = text.split("\n\n")
+    results = []
+
+    for block in blocks:
+        if "Q:" in block and "A:" in block:
+            parts = block.split("A:")
+            question = parts[0].replace("Q:", "").strip()
+            answer = parts[1].strip()
+            results.append((question, answer))
+
+    return results
+
+
+
+
+# =========================================
+# MAIN ENDPOINT
+# =========================================
+
+@app.post("/generate-questions")
+def generate_questions(request: QuestionRequest):
+
+    if request.sessionType not in SESSION_TYPES:
+        raise HTTPException(status_code=400, detail="Invalid session type")
+
+    session_type = SESSION_TYPES[request.sessionType]
+
+    # ---------------- SOFT SKILLS ----------------
+
+    if session_type == "softskills":
+
+        prompt = """
+Generate 10 behavioral interview questions.
+Format exactly as:
+Q: ...
+A: ...
+"""
+
+    # ---------------- TECHNICAL ----------------
+
+    elif session_type == "technical":
+
+        if request.trackName not in TRACKS:
+            raise HTTPException(status_code=400, detail="Track not supported")
+
+        difficulty = request.difficultyLevel or 1
+
+        prompt = f"""
+Generate 10 General Programming interview questions.
+Difficulty level: {difficulty}
+Format exactly as:
+Q: ...
+A: ...
+"""
+
+    else:
+        raise HTTPException(status_code=400, detail="Invalid session type")
+
+    # -------- Generate once --------
+    raw_output = generate_from_model(prompt)
+
+    qa_pairs = parse_qa_blocks(raw_output)
+
+    if len(qa_pairs) == 0:
+        raise HTTPException(status_code=500, detail="Model failed to generate valid Q/A format")
+
+    response = []
+
+    for idx, (question, answer) in enumerate(qa_pairs[:10], 1):
+
+        response.append({
+            "questionText": question,
+            "questionId": idx,
+            "questionIdealAnswer": answer
+        })
+
+    return response

requirements.txt

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+fastapi==0.110.0
+uvicorn==0.29.0
+torch==2.2.2
+transformers==4.40.1
+accelerate==0.29.3
+peft==0.10.0
+pydantic==2.6.4
+soundfile
+