from flask import Flask, request, jsonify
from huggingface_hub import InferenceClient

app = Flask(__name__)
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")

def generate_response(message, history, system_message, max_tokens, temperature, top_p):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})
    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content
        response += token

    return response

def generate_journal_suggestion(current_page):
    suggestion_prompt = (
        f"Pe baza înregistrării din jurnal: '{current_page}', sugerează ce ar putea scrie utilizatorul în continuare în jurnalul său. "
        "Concentrează-te pe încurajarea reflecției mai profunde, stabilirea obiectivelor sau explorarea ideilor conexe."
    )
    suggestion_response = ""

    for message in client.chat_completion(
        [{"role": "user", "content": suggestion_prompt}],
        max_tokens=150,
        stream=True,
        temperature=0.7,
        top_p=0.9,
    ):
        token = message.choices[0].delta.content
        suggestion_response += token

    return suggestion_response

@app.route("/", methods=["POST","GET"])
def home():
    return "Hi!"

@app.route("/chat", methods=["POST"])
def chat():
    try:
        data = request.json
        message = data.get("message", "")
        history = data.get("history", [])
        system_message = data.get("system_message", "You are a friendly chatbot.")
        max_tokens = data.get("max_tokens", 512)
        temperature = data.get("temperature", 0.7)
        top_p = data.get("top_p", 0.95)
        journal_page = data.get("journal_page", "")

        if not isinstance(history, list) or not all(isinstance(pair, list) for pair in history):
            return jsonify({"error": "Invalid history format. It should be a list of [message, response] pairs."}), 400

        response = generate_response(message, history, system_message, max_tokens, temperature, top_p)

        suggestion = ""
        if journal_page:
            suggestion = generate_journal_suggestion(journal_page)

        return jsonify({"response": response, "journal_suggestion": suggestion})
    except Exception as e:
        return jsonify({"error": str(e)}), 500

if __name__ == "__main__":
    app.run(debug=True)