first commit

.gitignore

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+.env
+env

app.py

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+import os
+import openai
+from transformers import pipeline, Conversation
+import gradio as gr
+import json
+from dotenv import load_dotenv
+
+# Load environment variables from the .env file de forma local
+load_dotenv()
+import base64
+
+with open("Iso_Logotipo_Ceibal.png", "rb") as image_file:
+    encoded_image = base64.b64encode(image_file.read()).decode()
+
+
+openai.api_key = os.environ['OPENAI_API_KEY']
+
+def clear_chat(message, chat_history):
+     return "", []
+
+def add_new_message(message,chat_history):
+     new_chat = []
+     new_chat.append({"role": "system", "content": "Sos Albert Einstein y tendrás que responder preguntas que te harán niños de escuela, las respuestas tienen que ser cómo si hablaras con albert Einstein y con la información de su vida. Las respuestas tienen que estar orientadas a niños entre 9 y 10 años."})
+     for turn in chat_history:
+          user, bot = turn
+          new_chat.append({"role": "user", "content": user})
+          new_chat.append({"role": "assistant","content":bot})
+     new_chat.append({"role": "user","content":message})
+     return new_chat
+    
+          
+
+def respond(message, chat_history):
+    prompt = add_new_message(message, chat_history)
+    # stream = client.generate_stream(prompt,
+    #                                   max_new_tokens=1024,
+    #                                   stop_sequences=["\nUser:", "<|endoftext|>"],
+    #                                   temperature=temperature)
+    #                                   #stop_sequences to not generate the user answer
+    # acc_text = ""
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages= prompt,
+        temperature=0.5,
+        max_tokens=1000,
+        stream=True,
+        )#.choices[0].message.content
+    #chat_history.append((message, response))
+
+    token_counter = 0 
+    partial_words = "" 
+
+    counter=0
+    for chunk in response:
+        chunk_message = chunk['choices'][0]['delta']
+        if(len(chat_history))<1:
+            # print("entró acaá")
+            partial_words += chunk_message.content
+            chat_history.append([message,chunk_message.content])
+        else:
+            # print("antes", chat_history)
+            if(len(chunk_message)!=0):
+                if(len(chunk_message)==2):
+                    partial_words += chunk_message.content
+                    chat_history.append([message,chunk_message.content])
+                else:
+                    partial_words += chunk_message.content
+                    chat_history[-1] =([message,partial_words])
+        yield "",chat_history
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("""
+    <center>
+    <h1>
+    Uso de AI para un chatbot.
+    </h1>
+    <img src='data:image/jpg;base64,{}' width=200px>
+    <h3>
+    Con este espacio podrás hablar en formato conversación con Alber Einstein!
+    </h3>
+    </center>
+    """.format(encoded_image))
+    with gr.Row():
+        chatbot = gr.Chatbot( height=700) #just to fit the notebook
+    with gr.Row():
+        with gr.Row():
+            with gr.Column(scale=4):
+                msg = gr.Textbox(label="Texto de entrada")
+            with gr.Column(scale=1):
+                btn = gr.Button("Enviar")
+                clear = gr.ClearButton(components=[msg, chatbot], value="Borrar chat")
+
+   
+
+
+    btn.click(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])
+    msg.submit(respond, inputs=[msg, chatbot], outputs=[msg, chatbot]) #Press enter to submit
+    clear.click(clear_chat,inputs=[msg, chatbot], outputs=[msg, chatbot])
+demo.queue()
+demo.launch()

requirements.txt

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+einops
+openai
+gradio
+transformers
+python-dotenv