test

chat-8-api.py

@@ -10,8 +10,8 @@ load_dotenv()
 
 OPENAI_API_KEY = os.environ['GROQ_API_KEY']
 
-# llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')
-llm = openai(temperature=1.0, model='gpt-4-turbo')
+llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')
+# llm = ChatOpenAI(temperature=1.0, model='gpt-4-turbo')
 # llm = openai(temperature=1.0, model='gpt-4o')
 
 def predict(message, history):

chat-9-api.py

@@ -1,8 +1,15 @@
 from openai import OpenAI
 import gradio as gr
+import os
+import dotenv
 
-api_key = "sk-..."  # Replace with your key
-client = OpenAI(api_key=api_key)
+dotenv.load_dotenv()
+
+OPENAI_API_KEY = os.environ['OPENAI_API_KEY']
+
+print(OPENAI_API_KEY)
+
+client = OpenAI(api_key=OPENAI_API_KEY)
 
 def predict(message, history):
     history_openai_format = []
@@ -11,10 +18,14 @@ def predict(message, history):
         history_openai_format.append({"role": "assistant", "content":assistant})
     history_openai_format.append({"role": "user", "content": message})
   
-    response = client.chat.completions.create(model='gpt-3.5-turbo',
-    messages= history_openai_format,
-    temperature=1.0,
-    stream=True)
+    response = client.chat.completions.create(
+        #  model='gpt-3.5-turbo',
+        # model="gpt-4-turbo",
+        model="gpt-4o",
+        messages= history_openai_format,
+        temperature=1.0,
+        stream=True
+    )
 
     partial_message = ""
     for chunk in response:

chat-groq.py

@@ -0,0 +1,59 @@
+import streamlit as st
+import os
+from groq import Groq
+import random
+
+from langchain.chains import ConversationChain
+from langchain.chains.conversation.memory import ConversationBufferWindowMemory
+from langchain_groq import ChatGroq
+from langchain.prompts import PromptTemplate
+from dotenv import load_dotenv
+import os 
+
+load_dotenv()
+
+groq_api_key = os.environ['GROQ_API_KEY']
+
+def main():
+
+    st.title("Groq Chat App")
+
+    # Add customization options to the sidebar
+    st.sidebar.title('Select an LLM')
+    model = st.sidebar.selectbox(
+        'Choose a model',
+        ['mixtral-8x7b-32768', 'llama2-70b-4096']
+    )
+    conversational_memory_length = st.sidebar.slider('Conversational memory length:', 1, 10, value = 5)
+
+    memory=ConversationBufferWindowMemory(k=conversational_memory_length)
+
+    user_question = st.text_area("Ask a question:")
+
+    # session state variable
+    if 'chat_history' not in st.session_state:
+        st.session_state.chat_history=[]
+    else:
+        for message in st.session_state.chat_history:
+            memory.save_context({'input':message['human']},{'output':message['AI']})
+
+
+    # Initialize Groq Langchain chat object and conversation
+    groq_chat = ChatGroq(
+            groq_api_key=groq_api_key, 
+            model_name=model
+    )
+
+    conversation = ConversationChain(
+            llm=groq_chat,
+            memory=memory
+    )
+
+    if user_question:
+        response = conversation(user_question)
+        message = {'human':user_question,'AI':response['response']}
+        st.session_state.chat_history.append(message)
+        st.write("Chatbot:", response['response'])
+
+if __name__ == "__main__":
+    main()

chat.py

@@ -8,8 +8,9 @@ OPENAI_API_KEY = os.environ['OPENAI_API_KEY']
 client = OpenAI()
 
 response = client.chat.completions.create(
+  model="gpt-3.5-turbo",
 #   model="gpt-4-turbo",
-  model="gpt-4o",
+#   model="gpt-4o",
   messages=[
     {"role": "system", "content": "You are a helpful assistant."},
     {"role": "user", "content": "Who won the world series in 2020?"},