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07a91a1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | """End-to-end orchestration for generation and validation."""
from __future__ import annotations
import time
from src.config import settings
from src.generator import generate_response
from src.hallucination import hallucination_check
from src.model_loader import load_model_bundle
from src.prompts import SYSTEM_PROMPT, build_user_prompt
from src.rag import CodeRAG
from src.relevancy import RelevancyScorer
class CodingLLMPipeline:
"""Coordinates model, RAG, explainability, and quality checks."""
def __init__(self):
self.model_bundle = None
self.relevancy = RelevancyScorer()
self.rag = CodeRAG() if settings.use_rag else None
def _ensure_model_loaded(self):
if self.model_bundle is None:
self.model_bundle = load_model_bundle()
def run(self, instruction: str, user_input: str) -> dict:
started = time.perf_counter()
self._ensure_model_loaded()
query_text = f"{instruction}\n{user_input}".strip()
retrieved_context = self.rag.retrieve(query_text) if self.rag else ""
prompt = f"{SYSTEM_PROMPT}\n\n{build_user_prompt(instruction, user_input, retrieved_context)}"
generation = generate_response(self.model_bundle, prompt)
hallucination_result = hallucination_check(generation.code)
relevancy_score = self.relevancy.score(query_text, generation.code)
explanation = generation.explanation
if hallucination_result.hallucination:
explanation = f"{generation.explanation}\n\nHallucination check reason: {hallucination_result.reason}"
latency_ms = int((time.perf_counter() - started) * 1000)
return {
"code": generation.code,
"explanation": explanation,
"confidence": round(generation.confidence, 4),
"important_tokens": generation.important_tokens,
"relevancy_score": round(relevancy_score, 4),
"hallucination": hallucination_result.hallucination,
"latency_ms": latency_ms,
}
@property
def active_model_name(self) -> str:
"""Current model name, loading lazily if needed."""
self._ensure_model_loaded()
return self.model_bundle.active_model_name
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