Delete src/interview_simulator

src/interview_simulator/entretient_version_prod.py

@@ -1,74 +0,0 @@
-import os
-import sys
-import json
-from typing import Dict, List, Any, Annotated
-from typing_extensions import TypedDict
-
-from langchain_core.messages import AIMessage, SystemMessage, HumanMessage
-from langgraph.graph import StateGraph, START, END
-from langgraph.graph.message import add_messages
-from langchain_openai import ChatOpenAI
-
-from src.config import read_system_prompt, format_cv
-
-class State(TypedDict):
-    messages: Annotated[list, add_messages]
-
-class InterviewProcessor:
-    def __init__(self, cv_document: Dict[str, Any], job_offer: Dict[str, Any], conversation_history: List[Dict[str, Any]]):
-        if not cv_document or 'candidat' not in cv_document:
-            raise ValueError("Document CV invalide fourni.")
-        if not job_offer:
-            raise ValueError("Données de l'offre d'emploi non fournies.")
-
-        self.job_offer = job_offer
-        self.cv_data = cv_document['candidat']
-        self.conversation_history = conversation_history
-        self.llm = self._get_llm()
-
-        self.system_prompt_template = self._load_prompt_template()
-        self.graph = self._build_graph()
-
-    def _get_llm(self) -> ChatOpenAI:
-        openai_api_key = os.getenv("OPENAI_API_KEY")
-        return ChatOpenAI(
-            temperature=0.6, 
-            model_name="gpt-4o-mini", 
-            api_key=openai_api_key
-        )
-
-    def _load_prompt_template(self) -> str:
-        return read_system_prompt('prompts/rag_prompt_old.txt') 
-
-    def _chatbot_node(self, state: State) -> dict:
-        messages = state["messages"]
-        formatted_cv_str = format_cv(self.cv_data)
-
-        # Formatage du prompt système
-        system_prompt = self.system_prompt_template.format(
-            entreprise=self.job_offer.get('entreprise', 'notre entreprise'),
-            poste=self.job_offer.get('poste', 'ce poste'),
-            mission=self.job_offer.get('mission', 'Non spécifiée'),
-            profil_recherche=self.job_offer.get('profil_recherche', 'Non spécifié'),
-            competences=self.job_offer.get('competences', 'Non spécifiées'),
-            pole=self.job_offer.get('pole', 'Non spécifié'),
-            cv=formatted_cv_str
-        )
-        
-        llm_messages = [SystemMessage(content=system_prompt)] + messages
-        response = self.llm.invoke(llm_messages)
-        return {"messages": [response]}
-
-    def _build_graph(self) -> any:
-        graph_builder = StateGraph(State)
-        
-        graph_builder.add_node("chatbot", self._chatbot_node)
-        graph_builder.add_edge(START, "chatbot")
-        # Le graph se termine toujours après la réponse du chatbot
-        graph_builder.add_edge("chatbot", END)
-        
-        return graph_builder.compile()
-
-    def run(self, messages: List[Dict[str, Any]]) -> Dict[str, Any]:
-        initial_state = self.conversation_history + messages
-        return self.graph.invoke({"messages": initial_state})