Update app.py

app.py

@@ -3,11 +3,12 @@ from dotenv import find_dotenv, load_dotenv
 import streamlit as st
 from typing import Generator
 from groq import Groq
+import requests
+from bs4 import BeautifulSoup
 
 _ = load_dotenv(find_dotenv())
 st.set_page_config(page_icon="💬", layout="wide", page_title="Groq Chat Bot...")
 
-
 def icon(emoji: str):
     """Shows an emoji as a Notion-style page icon."""
     st.write(
@@ -15,34 +16,26 @@ def icon(emoji: str):
         unsafe_allow_html=True,
     )
 
-
 icon("⚡")
 
 st.subheader("GroqChatbot", divider="rainbow", anchor=False)
 
-client = Groq(
-    api_key=os.environ['GROQ_API_KEY'],
-)
+client = Groq(api_key=os.environ['GROQ_API_KEY'])
 
-# Initialize chat history and selected model
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
 if "selected_model" not in st.session_state:
     st.session_state.selected_model = None
 
-# Define model details
 models = {
-    "mixtral-8x7b-32768": {
-        "name": "Mixtral-8x7b-Instruct-v0.1",
-        "tokens": 32768,
-        "developer": "Mistral",
-    },
-    "llama2-70b-4096": {"name": "LLaMA2-70b-chat", "tokens": 4096, "developer": "Meta"},
+    "mixtral-8x7b-32768": {"name": "Mixtral-8x7b-Instruct-v0.1", "tokens": 32768, "developer": "Mistral"},
     "gemma-7b-it": {"name": "Gemma-7b-it", "tokens": 8192, "developer": "Google"},
+    "llama2-70b-4096": {"name": "LLaMA2-70b-chat", "tokens": 4096, "developer": "Meta"},
+    "llama3-70b-8192": {"name": "LLaMA3-70b-8192", "tokens": 8192, "developer": "Meta"},
+    "llama3-8b-8192": {"name": "LLaMA3-8b-8192", "tokens": 8192, "developer": "Meta"},
 }
 
-# Layout for model selection and max_tokens slider
 col1, col2 = st.columns(2)
 
 with col1:
@@ -50,10 +43,9 @@ with col1:
         "Choose a model:",
         options=list(models.keys()),
         format_func=lambda x: models[x]["name"],
-        index=0,  # Default to the first model in the list
+        index=0, 
     )
 
-# Detect model change and clear chat history if model has changed
 if st.session_state.selected_model != model_option:
     st.session_state.messages = []
     st.session_state.selected_model = model_option
@@ -61,30 +53,44 @@ if st.session_state.selected_model != model_option:
 max_tokens_range = models[model_option]["tokens"]
 
 with col2:
-    # Adjust max_tokens slider dynamically based on the selected model
     max_tokens = st.slider(
         "Max Tokens:",
-        min_value=512,  # Minimum value to allow some flexibility
+        min_value=512,  
         max_value=max_tokens_range,
-        # Default value or max allowed if less
         value=min(32768, 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"])
 
-
 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 search_web(query):
+    try:
+        search_url = f"https://www.google.com/search?q={query}"
+        response = requests.get(search_url)
+        if response.status_code == 200:
+            soup = BeautifulSoup(response.text, 'html.parser')
+            search_results = soup.find_all('div', class_='tF2Cxc')
+            results = []
+            for result in search_results:
+                title = result.find('h3').text
+                url = result.find('a')['href']
+                snippet = result.find('span', class_='aCOpRe').text
+                results.append({"title": title, "url": url, "snippet": snippet})
+            return results
+        else:
+            return "Failed to retrieve search results"
+    except Exception as e:
+        return f"An error occurred: {e}"
 
 if prompt := st.chat_input("Enter your prompt here..."):
     st.session_state.messages.append({"role": "user", "content": prompt})
@@ -92,33 +98,35 @@ if prompt := st.chat_input("Enter your prompt here..."):
     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)
+        if "search for" in prompt.lower():
+            query = prompt.lower().replace("search for", "").strip()
+            search_results = search_web(query)
+            formatted_results = "\n\n".join([f"Title: {result['title']}\nURL: {result['url']}\nSnippet: {result['snippet']}" for result in search_results])
+            st.session_state.messages.append({"role": "assistant", "content": formatted_results})
+        else:
+            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,
+            )
+
+            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(e, icon="🚨")
 
-    # 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}
-        )
+        )