hf

.gitignore

@@ -0,0 +1 @@
+.env

app.py

@@ -0,0 +1,78 @@
+import streamlit as st
+import time
+import requests
+import json
+import os
+from PIL import Image
+from dotenv import load_dotenv
+load_dotenv()
+
+st.set_page_config(layout="centered")  
+
+col1, col2 = st.columns([2,3])
+
+with col1:
+    image = Image.open('danigpt.png')
+    st.image(image, width=200)
+
+with col2:
+    st.title("DaniGPT 🤖")
+st.write("Preguntame cualquier cosa sobre python, Judini o Langchain")
+st.write("OJO 👀 No estoy conectado a internet, así que puedo alucinar 😵‍💫, es tu trabajo corroborar que la respuesta que te entregue sea correcta.")
+st.markdown('---')
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Accept user input
+if prompt := st.chat_input("En que te puedo ayudar?"):
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+        message_placeholder = st.empty()
+        full_response = ""
+        #Judini
+        api_key= os.getenv("JUDINI_API_KEY")
+        agent_id= os.getenv("JUDINI_AGENT_ID")
+        url = 'https://playground.judini.ai/api/v1/agent/'+agent_id
+        headers = {"Content-Type": "application/json; charset=utf-8", "Authorization": "Bearer "+api_key}
+        data = {
+            "messages": [
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ]
+        }
+        response = requests.post(url, headers=headers, json=data, stream=True)
+        raw_data = ''
+        tokens = ''
+        for chunk in response.iter_content(chunk_size=1024):
+            if chunk:
+                raw_data = chunk.decode('utf-8').replace("data: ", '')
+                if raw_data != "":
+                    lines = raw_data.strip().splitlines()
+                    for line in lines:
+                        line = line.strip()
+                        if line and line != "[DONE]":
+                            try:
+                                json_object = json.loads(line) 
+                                result = json_object['data']
+                                full_response += result
+                                time.sleep(0.05)
+                                # Add a blinking cursor to simulate typing
+                                message_placeholder.markdown(full_response + "▌")
+                            except json.JSONDecodeError:
+                                print(f'Error al decodificar el objeto JSON en la línea: {line}')
+        message_placeholder.markdown(full_response)
+    st.session_state.messages.append({"role": "assistant", "content": full_response})

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+requests
+python-dotenv
+Pillow