Renamed the right main app file

app.py

@@ -1,37 +1,93 @@
-# CREDITS
-# https://gist.github.com/truevis/f31706b8af60e8c73d62b281bddb988f
-
 import streamlit as st
 from groq import Groq
-
 import os
+import base64
+from io import BytesIO
+
+# Initialize Groq client
 client = Groq(
     api_key=os.environ.get("GROQ_API_KEY"),
 )
 
-def generate_response(user_input):
+# Initialize session state for chat history if it doesn't exist
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+
+def encode_image(uploaded_file):
+    bytes_data = uploaded_file.getvalue()
+    base64_image = base64.b64encode(bytes_data).decode('utf-8')
+    return f"data:image/{uploaded_file.type.split('/')[-1]};base64,{base64_image}"
+
+def generate_response(messages, current_image=None):
+    # Create a copy of messages for the API call
+    api_messages = messages.copy()
+    
+    # If there's a current image, add it to the last user message
+    if current_image:
+        api_messages[-1] = {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": api_messages[-1]["content"]},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": current_image}
+                }
+            ]
+        }
+    
+    model = "llama-3.2-11b-vision-preview" if current_image else "llama-3.2-3b-preview"
+    
     stream = client.chat.completions.create(
-        model="llama-3.2-3b-preview", #128K model
-        messages=[
-            {"role": "system", "content": "You are a helpful assistant"},
-            {"role": "user", "content": user_input},
-        ],
+        model=model,
+        messages=api_messages,
         temperature=0.1,
-        # max_tokens=128000,
         top_p=1,
         stream=True,
         stop=None,
     )
-
+    
     for chunk in stream:
         content = chunk.choices[0].delta.content
         if content:
-            yield content  # Yield content for streaming
+            yield content
+
+st.title("Groq Chat")
+
+# Display chat history
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
 
-st.title("Groq API Response Streaming")
+# File uploader for images
+uploaded_file = st.file_uploader("Upload an image (optional)", type=['png', 'jpg', 'jpeg'])
+
+# Get user input
 user_input = st.chat_input('Message to Assistant...', key='prompt_input')
-if user_input: # Get user input
-    with st.spinner("Generating response..."):
-        st.write_stream(generate_response(user_input))  # Use st.write_stream to display streamed content
-        st.markdown("Message: " + user_input) 
-        st.markdown("---")  # Add a newline after the 
+
+if user_input:
+    # Add user message to chat history (text only)
+    st.session_state.messages.append({"role": "user", "content": user_input})
+    
+    # Display user message with image if present
+    with st.chat_message("user"):
+        st.markdown(user_input)
+        if uploaded_file:
+            st.image(uploaded_file)
+    
+    # Generate and display assistant response
+    with st.chat_message("assistant"):
+        response_placeholder = st.empty()
+        full_response = ""
+        
+        # Prepare image for API call if present
+        current_image = encode_image(uploaded_file) if uploaded_file else None
+        
+        # Stream the response
+        with st.spinner("Generating response..."):
+            for content in generate_response(st.session_state.messages, current_image):
+                full_response += content
+                response_placeholder.markdown(full_response + "▌")
+            response_placeholder.markdown(full_response)
+    
+    # Add assistant response to chat history (text only)
+    st.session_state.messages.append({"role": "assistant", "content": full_response})

st_image_chat.py

@@ -1,93 +0,0 @@
-import streamlit as st
-from groq import Groq
-import os
-import base64
-from io import BytesIO
-
-# Initialize Groq client
-client = Groq(
-    api_key=os.environ.get("GROQ_API_KEY"),
-)
-
-# Initialize session state for chat history if it doesn't exist
-if 'messages' not in st.session_state:
-    st.session_state.messages = []
-
-def encode_image(uploaded_file):
-    bytes_data = uploaded_file.getvalue()
-    base64_image = base64.b64encode(bytes_data).decode('utf-8')
-    return f"data:image/{uploaded_file.type.split('/')[-1]};base64,{base64_image}"
-
-def generate_response(messages, current_image=None):
-    # Create a copy of messages for the API call
-    api_messages = messages.copy()
-    
-    # If there's a current image, add it to the last user message
-    if current_image:
-        api_messages[-1] = {
-            "role": "user",
-            "content": [
-                {"type": "text", "text": api_messages[-1]["content"]},
-                {
-                    "type": "image_url",
-                    "image_url": {"url": current_image}
-                }
-            ]
-        }
-    
-    model = "llama-3.2-11b-vision-preview" if current_image else "llama-3.2-3b-preview"
-    
-    stream = client.chat.completions.create(
-        model=model,
-        messages=api_messages,
-        temperature=0.1,
-        top_p=1,
-        stream=True,
-        stop=None,
-    )
-    
-    for chunk in stream:
-        content = chunk.choices[0].delta.content
-        if content:
-            yield content
-
-st.title("Groq Chat")
-
-# Display chat history
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
-
-# File uploader for images
-uploaded_file = st.file_uploader("Upload an image (optional)", type=['png', 'jpg', 'jpeg'])
-
-# Get user input
-user_input = st.chat_input('Message to Assistant...', key='prompt_input')
-
-if user_input:
-    # Add user message to chat history (text only)
-    st.session_state.messages.append({"role": "user", "content": user_input})
-    
-    # Display user message with image if present
-    with st.chat_message("user"):
-        st.markdown(user_input)
-        if uploaded_file:
-            st.image(uploaded_file)
-    
-    # Generate and display assistant response
-    with st.chat_message("assistant"):
-        response_placeholder = st.empty()
-        full_response = ""
-        
-        # Prepare image for API call if present
-        current_image = encode_image(uploaded_file) if uploaded_file else None
-        
-        # Stream the response
-        with st.spinner("Generating response..."):
-            for content in generate_response(st.session_state.messages, current_image):
-                full_response += content
-                response_placeholder.markdown(full_response + "▌")
-            response_placeholder.markdown(full_response)
-    
-    # Add assistant response to chat history (text only)
-    st.session_state.messages.append({"role": "assistant", "content": full_response})

st_long_context_basic.py

@@ -0,0 +1,37 @@
+# CREDITS
+# https://gist.github.com/truevis/f31706b8af60e8c73d62b281bddb988f
+
+import streamlit as st
+from groq import Groq
+
+import os
+client = Groq(
+    api_key=os.environ.get("GROQ_API_KEY"),
+)
+
+def generate_response(user_input):
+    stream = client.chat.completions.create(
+        model="llama-3.2-3b-preview", #128K model
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant"},
+            {"role": "user", "content": user_input},
+        ],
+        temperature=0.1,
+        # max_tokens=128000,
+        top_p=1,
+        stream=True,
+        stop=None,
+    )
+
+    for chunk in stream:
+        content = chunk.choices[0].delta.content
+        if content:
+            yield content  # Yield content for streaming
+
+st.title("Groq API Response Streaming")
+user_input = st.chat_input('Message to Assistant...', key='prompt_input')
+if user_input: # Get user input
+    with st.spinner("Generating response..."):
+        st.write_stream(generate_response(user_input))  # Use st.write_stream to display streamed content
+        st.markdown("Message: " + user_input) 
+        st.markdown("---")  # Add a newline after the