from langchain.agents import create_react_agent, AgentExecutor
from langchain.memory import ConversationBufferMemory
from langchain_community.vectorstores import FAISS
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain.prompts import PromptTemplate
from langchain_openai import ChatOpenAI
from tools.web import web_search_tool
from tools.local_docs import local_knowledge_tool
import os

def create_agent():
    llm = ChatOpenAI(
        model="gpt-4o-mini",
        temperature=0.2
    )

    tools = [
        local_knowledge_tool,
        web_search_tool,
    ]

    prompt = PromptTemplate.from_template(
        """Tu es Kibali, un agent IA avancé.

CAPACITÉS :
- Base de connaissances locale
- Recherche web Tavily

RÈGLES :
1. Base locale TOUJOURS en premier
2. Web seulement si nécessaire
3. Cite les sources
4. Mentionne les contradictions

FORMAT ReAct STRICT :

Question: {input}
Thought: raisonnement
Action: outil
Action Input: entrée
Observation: résultat
...
Final Answer: réponse claire

Commence !

Question: {input}
Thought: {agent_scratchpad}
"""
    )

    agent = create_react_agent(
        llm=llm,
        tools=tools,
        prompt=prompt
    )

    memory = ConversationBufferMemory(
        memory_key="chat_history",
        return_messages=True
    )

    executor = AgentExecutor(
        agent=agent,
        tools=tools,
        memory=memory,
        verbose=True,
        max_iterations=5,
        handle_parsing_errors=True
    )

    return executor