Fix: Adjustments

main.py

@@ -7,9 +7,7 @@ from datetime import datetime, timedelta
 import time
 import jwt
 import openai
-from openai import util as openai_util
 from openai import error as openai_error
-from html import escape
 from hashlib import sha256
 import tiktoken
 from supported import supp_langs
@@ -70,112 +68,16 @@ async def root(request: Request, credentials: HTTPBasicCredentials = Depends(sec
             return HTMLResponse(f.read().replace("{% token %}", token).replace("{% version %}", "3"))
 
     
-@app.post("/chat")
-async def chat(data = Depends(validate_token)):
-    openai.api_key = str(os.getenv("OPENAI_API_KEY"))
-    model_engine = "gpt-3.5-turbo"
-    messages = data["messages"]
-    config = {
-        "temperature": 1.0,
-        "frequency_penalty": 0.0,
-        "presence_penalty": 0.0,
-    }
-    if "config" in data:
-        config["temperature"] = float(data["config"].get("temperature", 1))
-        config["frequency_penalty"] = float(data["config"].get("frequency_penalty", 0))
-        config["presence_penalty"] = float(data["config"].get("presence_penalty", 0))
-    try:
-        response = openai.ChatCompletion.create(
-            model=model_engine,
-            messages=messages,
-            max_tokens=3000,
-            temperature=config["temperature"],
-            frequency_penalty=config["frequency_penalty"],
-            presence_penalty=config["presence_penalty"],
-            request_timeout = 25
-            )
-    except requests.exceptions.RequestException as e:
-        print("Timeout (requests)")
-        print(e)
-        raise HTTPException(
-            status_code=status.HTTP_408_REQUEST_TIMEOUT,
-            detail="Los servidores tardaron mucho en responder, puede haber sobrecarga en OpenAI, reintenta luego (error 1)"
-        )
-    except openai_error.APIConnectionError as e:
-        print("APIConnectionError")
-        print(e)
-        raise HTTPException(
-            status_code=status.HTTP_408_REQUEST_TIMEOUT,
-            detail="El servidor no respondió, puede haber sobrecarga en OpenAI, reintenta luego (error 2)"
-        )
-    except openai_error.Timeout as e:
-        print("Timeout (openai)")
-        print(e)
-        raise HTTPException(
-            status_code=status.HTTP_408_REQUEST_TIMEOUT,
-            detail="El servidor no respondió, puede haber sobrecarga en OpenAI, reintenta luego (error 3)"
-        )
-    
-    message = response.choices[0].message.content
-    contexto = openai_util.convert_to_dict(response)
-    
-    codigos = []
-    while "```" in message:
-        start = message.find("```")
-        end = message.find("```", start+3)+3
-        temp_text = message[start:end]
-        end_lang = temp_text.find("\n")
-
-        message = message.replace(temp_text, "{#$&---&$#}")
-
-        t_language = temp_text[3:end_lang].strip()
-
-
-        language = t_language.replace(" ", "-")
-
-        if language in supp_langs:
-            temp_text = f'<pre><code class="language-{language}">' + escape(temp_text[end_lang:-3].strip()) + "</code></pre>"
-        else:
-            temp_text = '<pre><code class="language-none">' + escape(temp_text[3:-3].strip()) + "</code></pre>"
-        codigos.append(temp_text)
-    
-    message = message.replace("\n", "<br>")
-
-    for codigo in codigos:
-        message = message.replace("{#$&---&$#}", codigo, 1)
-    message = re.sub(r'`([^`]+)`', r'<b>\1</b>', message)
-
-
-    messages.append({"role": "assistant", "content": message})
-    token = create_jwt_token(data.pop("token_data"))
-    return {"messages": messages, "token": token, "config": config, "contexto":contexto}
- 
-def procesar_codigo(data):
-    temp_text = data[3:-3]
-    end_lang = temp_text.find("\n")
-    language = temp_text[:end_lang].strip().replace(" ", "-")
-
-    if language in supp_langs:
-        temp_text = f'<pre><code class="language-{language}">' + escape(temp_text[end_lang:].strip()) + "</code></pre>"
-    else:
-        temp_text = '<pre><code class="language-none">' + escape(temp_text.strip()) + "</code></pre>"
-    
-    return temp_text
-
-
 @app.post("/chat_stream")
 async def chat_stream(data = Depends(validate_token)):
     messages = data["messages"]
     token_length = len(tokenizer.encode(messages[-1]["content"]))
     config = {
-        "temperature": 1.0,
-        "frequency_penalty": 0.0,
-        "presence_penalty": 0.0
+        "temperature": float(data.get("config", []).get("temperature", 1)),
+        "frequency_penalty": float(data.get("config", []).get("frequency_penalty", 1)),
+        "presence_penalty": float(data.get("config", []).get("presence_penalty", 1))
     }
-    if "config" in data:
-        config["temperature"] = float(data["config"].get("temperature", 1))
-        config["frequency_penalty"] = float(data["config"].get("frequency_penalty", 0))
-        config["presence_penalty"] = float(data["config"].get("presence_penalty", 0))
+ 
     try:
         response = openai.ChatCompletion.create(
             model="gpt-3.5-turbo",

static/js/windowHandler.js

@@ -2,10 +2,8 @@ class WindowHandler{
     constructor(token){
         this.chatbox = $("#chat");
         this.template = $('<div class="message"><div><p></p></div></div>');
-        
-        this.evCtx = document;
-
 
+        this.evCtx = document;
 
         $(this.evCtx).on("enviar:exito", (event, params) => this.procesarTexto(params));
         $(this.evCtx).on("chat:cargar", (event, params) => this.cargarChat(params));
@@ -14,11 +12,13 @@ class WindowHandler{
     }
 
     manejadorEnviar(){
-        let message = $("#input-text").val();
-        if(message==""){
+        let mensaje = $("#input-text").val();
+        if(mensaje==""){
             return false;
         }
         $("#input-text").val("");
+        mostarMensaje(mensaje, "user");
+        precargaMensaje("", "")
         $(this.evCtx).trigger("chat:enviar", message);
     }
     
@@ -56,12 +56,25 @@ class WindowHandler{
         if(role=="user"){
             clone.addClass("me");
         }
+        
+        if($(".precarga").length){
+            clone = $(".precarga")
+            clone.removeClass("precarga")
+        }
+        
         clone.find("div p").html(mensaje.content);
         Prism.highlightElement(clone[0], true, () => {
             this.chatbox.append(clone);
             this.chatbox.scrollTop(this.chatbox[0].scrollHeight);
         } );
-        
+    }
+
+    precargaMensaje(mensaje, role){
+        let clone = this.template.clone();
+        clone.addClass("precarga");
+        clone.find("div p").html("Cargando...");
+        this.chatbox.append(clone);
+        this.chatbox.scrollTop(this.chatbox[0].scrollHeight);
     }