from llama_index.embeddings.huggingface import HuggingFaceEmbedding
from flask import Flask, request,abort,jsonify
from g4f.client import Client
from os import getenv
from requests import get as reqget
from re import search
app  = Flask(__name__)
emb = HuggingFaceEmbedding(getenv("embmodel").strip())
embcache:dict[str,list[float]] = {}
chatcache:dict[str,str] = {}
transcache: dict[tuple[str, str], str] = {}
@app.get("/")
def index():
    return "Hello World!"
@app.post("/api")
def api():
    text = request.data.decode().strip()
    typeofapi = request.headers.get("type")
    if not text or not typeofapi:
        abort(400,"text and type is required")
    if typeofapi == "embedding":
        if text in embcache:
            return embcache.get(text)
        result = emb.get_query_embedding(text)
        embcache[text] = result
        return jsonify(result)
    elif typeofapi == "chat":
        if text in chatcache:
            return chatcache.get(text)
        response:str = Client().chat.completions.create(max_tokens=2024,model="gpt-4o-mini",messages=[{"role": "user", "content": text}]).choices[0].message.content
        chatcache[text] = response
        return response
    elif typeofapi == "translate_to_en":
        srclang: str = request.headers.get("srclang")
        if not srclang:
            abort(400,"srclang is required")
        if (srclang,text) in transcache:
            return transcache.get((srclang,text))
        if search(r"[A-Za-z]", text): # transliration
            origtxt = text
            text = reqget(f"https://inputtools.google.com/request?itc={srclang}-t-i0-und&num=1&text={text}").json()[1][0][1][0]
        response:str = "".join([i[0] for i in reqget(f'https://translate.googleapis.com/translate_a/single?client=gtx&sl={srclang}&tl=en&dt=t&q={text}').json()[0]])
        if origtxt:
            transcache[(srclang,origtxt)] = response
        transcache[(srclang,text)] = response
        return response
    else:
        abort(400,"type is invalid")
@app.get("/data")
def data():
    return jsonify({"embcache": embcache, "chatcache": chatcache, "transcache": transcache})

app.run(host="0.0.0.0", port=7860)