from flask import current_app
from langchain.embeddings import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate

from common.models.document import EmbeddingSmallOpenAI


def select_model_variables(tenant):
    embedding_provider = tenant.embedding_model.rsplit('.', 1)[0]
    embedding_model = tenant.embedding_model.rsplit('.', 1)[1]

    llm_provider = tenant.llm_model.rsplit('.', 1)[0]
    llm_model = tenant.llm_model.rsplit('.', 1)[1]

    # Set model variables
    model_variables = {}
    if tenant.es_k:
        model_variables['k'] = tenant.es_k
    else:
        model_variables['k'] = 5

    if tenant.es_similarity_threshold:
        model_variables['similarity_threshold'] = tenant.es_similarity_threshold
    else:
        model_variables['similarity_threshold'] = 0.7

    if tenant.chat_RAG_temperature:
        model_variables['RAG_temperature'] = tenant.chat_RAG_temperature
    else:
        model_variables['RAG_temperature'] = 0.3

    if tenant.chat_no_RAG_temperature:
        model_variables['no_RAG_temperature'] = tenant.chat_no_RAG_temperature
    else:
        model_variables['no_RAG_temperature'] = 0.5

    # Set Embedding variables
    match embedding_provider:
        case 'openai':
            match embedding_model:
                case 'text-embedding-3-small':
                    api_key = current_app.config.get('OPENAI_API_KEY')
                    model_variables['embedding_model'] = OpenAIEmbeddings(api_key=api_key,
                                                                    model='text-embedding-3-small')
                    model_variables['embedding_db_model'] = EmbeddingSmallOpenAI
                    model_variables['min_chunk_size'] = current_app.config.get('OAI_TE3S_MIN_CHUNK_SIZE')
                    model_variables['max_chunk_size'] = current_app.config.get('OAI_TE3S_MAX_CHUNK_SIZE')
                case _:
                    raise Exception(f'Error setting model variables for tenant {tenant.id} '
                                    f'error: Invalid embedding model')
        case _:
            raise Exception(f'Error setting model variables for tenant {tenant.id} '
                            f'error: Invalid embedding provider')

    # Set Chat model variables
    match llm_provider:
        case 'openai':
            api_key = current_app.config.get('OPENAI_API_KEY')
            model_variables['llm'] = ChatOpenAI(api_key=api_key,
                                                model=llm_model,
                                                temperature=model_variables['RAG_temperature'])
            match llm_model:
                case 'gpt-4-turbo' | 'gpt-4o':
                    summary_template = current_app.config.get('GPT4_SUMMARY_TEMPLATE')
                    rag_template = current_app.config.get('GPT4_RAG_TEMPLATE')
                case 'gpt-3-5-turbo':
                    summary_template = current_app.config.get('GPT3_5_SUMMARY_TEMPLATE')
                    rag_template = current_app.config.get('GPT3_5_RAG_TEMPLATE')
                case _:
                    raise Exception(f'Error setting model variables for tenant {tenant.id} '
                                    f'error: Invalid chat model')
            model_variables['summary_prompt'] = ChatPromptTemplate.from_template(summary_template)
            model_variables['rag_prompt'] = ChatPromptTemplate.from_template(rag_template)
        case _:
            raise Exception(f'Error setting model variables for tenant {tenant.id} '
                            f'error: Invalid chat provider')

    return model_variables