Create app.py

app.py

@@ -0,0 +1,155 @@
+import os
+import streamlit as st
+from typing import Generator
+from groq import Groq
+from dotenv import load_dotenv
+import yaml
+
+# Load environment variables from .env file
+load_dotenv()
+
+def generate_chat_responses(chat_completion) -> Generator[str, None, None]:
+    """Yield chat response content from the Groq API response."""
+    for chunk in chat_completion:
+        if chunk.choices[0].delta.content:
+            yield chunk.choices[0].delta.content
+
+def load_config():
+    """Load and validate the configuration from config.yaml"""
+    try:
+        with open("config.yaml", "r") as f:
+            config = yaml.safe_load(f)
+        
+        if "models" not in config:
+            st.error("The 'models' section is missing from the config file.")
+            st.stop()
+        
+        if "default_max_tokens" not in config:
+            st.warning("'default_max_tokens' is not specified in the config. Using 1024 as default.")
+            config["default_max_tokens"] = 1024
+        
+        if "prompt_templates" not in config:
+            st.warning("No prompt templates found in the config.")
+            config["prompt_templates"] = {}
+        
+        return config
+    except FileNotFoundError:
+        st.error("config.yaml file not found. Please ensure it exists in the same directory as this script.")
+        st.stop()
+    except yaml.YAMLError as e:
+        st.error(f"Error reading config.yaml: {e}")
+        st.stop()
+
+# Set up the Streamlit page
+st.set_page_config(page_icon="💬", layout="wide", page_title="Llama 3.1 Chat App")
+
+# Load configuration
+config = load_config()
+
+# Load Groq API key from environment variable
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+if not GROQ_API_KEY:
+    st.error("GROQ_API_KEY environment variable not found. Please set it in the .env file.")
+    st.stop()
+
+client = Groq(api_key=GROQ_API_KEY)
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Define model details
+model_option = "llama-3.1-70b-versatile"
+if model_option not in config["models"]:
+    st.error(f"The model '{model_option}' is not defined in the config file.")
+    st.stop()
+
+model_info = config["models"][model_option]
+
+# Display model information
+st.sidebar.header("Model Information")
+st.sidebar.markdown(f"**Name:** {model_info.get('name', 'N/A')}")
+st.sidebar.markdown(f"**Developer:** {model_info.get('developer', 'N/A')}")
+st.sidebar.markdown(f"**Description:** {model_info.get('description', 'N/A')}")
+
+max_tokens_range = model_info.get("tokens", 1024)  # Default to 1024 if not specified
+
+# Adjust max_tokens slider
+max_tokens = st.sidebar.slider(
+    "Max Tokens:",
+    min_value=512,
+    max_value=max_tokens_range,
+    value=min(config["default_max_tokens"], max_tokens_range),
+    step=512,
+    help=f"Adjust the maximum number of tokens (words) for the model's response. Max for selected model: {max_tokens_range}"
+)
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    avatar = '🤖' if message["role"] == "assistant" else '👨‍💻'
+    with st.chat_message(message["role"], avatar=avatar):
+        st.markdown(message["content"])
+
+if prompt := st.chat_input("Enter your prompt here..."):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    with st.chat_message("user", avatar='👨‍💻'):
+        st.markdown(prompt)
+
+    # Fetch response from Groq API
+    try:
+        chat_completion = client.chat.completions.create(
+            model=model_option,
+            messages=[
+                {
+                    "role": m["role"],
+                    "content": m["content"]
+                }
+                for m in st.session_state.messages
+            ],
+            max_tokens=max_tokens,
+            stream=True
+        )
+
+        # Use the generator function with st.write_stream
+        with st.chat_message("assistant", avatar="🤖"):
+            chat_responses_generator = generate_chat_responses(chat_completion)
+            full_response = st.write_stream(chat_responses_generator)
+    except Exception as e:
+        st.error(f"Error: {e}", icon="🚨")
+    else:
+        # Append the full response to session_state.messages
+        if isinstance(full_response, str):
+            st.session_state.messages.append(
+                {"role": "assistant", "content": full_response})
+        else:
+            # Handle the case where full_response is not a string
+            combined_response = "\n".join(str(item) for item in full_response)
+            st.session_state.messages.append(
+                {"role": "assistant", "content": combined_response})
+
+# Add a clear chat button
+if st.sidebar.button("Clear Chat"):
+    st.session_state.messages = []
+
+# Add a download chat history button
+if st.sidebar.button("Download Chat History"):
+    chat_history = "\n".join([f"{m['role'].capitalize()}: {m['content']}" for m in st.session_state.messages])
+    st.download_button(
+        label="Download Chat History",
+        data=chat_history,
+        file_name="chat_history.txt",
+        mime="text/plain",
+    )
+
+# Add a prompt templates section
+st.sidebar.header("Prompt Templates")
+template_options = list(config["prompt_templates"].keys())
+if template_options:
+    selected_template = st.sidebar.selectbox("Choose a prompt template", options=template_options)
+    if st.sidebar.button("Load Template"):
+        prompt_template = config["prompt_templates"][selected_template]
+        st.session_state.messages.append({"role": "user", "content": prompt_template})
+        st.experimental_rerun()
+else:
+    st.sidebar.info("No prompt templates available.")