Update app.py

app.py

@@ -1,34 +1,128 @@
 import os
+from groq import Groq
 import gradio as gr
-from langchain.chat_models import ChatOpenAI
-from langchain import LLMChain, PromptTemplate
-from langchain.memory import ConversationBufferMemory
+import logging
 
-OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
+# Set up logging configuration
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger(__name__)
 
-template = """You are a helpful assistant to answer all user queries.
-{chat_history}
-User: {user_message}
-Chatbot:"""
+# Initialize the Groq client with API key from environment variables
+api_key = os.environ.get("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")
+if not api_key:
+    logger.error("GROQ_API_KEY environment variable is not set.")
+    raise ValueError("GROQ_API_KEY environment variable is required.")
+client = Groq(api_key=api_key)
 
-prompt = PromptTemplate(
-    input_variables=["chat_history", "user_message"], template=template
-)
+# Default model name, can be overridden by environment variable
+MODEL_NAME = os.environ.get("MODEL_NAME", "llama3-8b-8192")
 
-memory = ConversationBufferMemory(memory_key="chat_history")
+def get_completion(user_input):
+    """
+    Generate a chat completion response using the Groq client.
 
-llm_chain = LLMChain(
-    llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),
-    prompt=prompt,
-    verbose=True,
-    memory=memory,
-)
+    Args:
+        user_input (str): The user's input query.
 
-def get_text_response(user_message,history):
-    response = llm_chain.predict(user_message = user_message)
-    return response
+    Returns:
+        str: The generated response or an error message.
+    """
+    try:
+        completion = client.chat.completions.create(
+            model=MODEL_NAME,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": user_input}
+            ],
+            temperature=1,
+            max_tokens=1024,
+            top_p=1,
+            stream=False,  # Gradio does not support stream=True
+        )
 
-demo = gr.ChatInterface(get_text_response)
+        # Extract the response
+        response = completion.choices[0].message.content.strip()
+        return response
+    except Exception as e:
+        logger.error(f"Error during completion: {e}")
+        return "Sorry, I encountered an error while processing your request."
+
+def launch_interface():
+    """
+    Launch the Gradio interface for the chatbot.
+    """
+    demo = gr.Interface(
+        fn=get_completion,
+        inputs=gr.Textbox(
+            label="Enter your query:",
+            placeholder="Ask me anything...",
+            lines=2,
+            max_lines=5
+        ),
+        outputs=gr.Textbox(
+            label="Response:",
+            lines=6,
+            max_lines=10
+        ),
+        title="Mr AI",
+        description="""
+        <style>
+        .gr-box {
+            border-radius: 10px;
+            border: 2px solid #007BFF;
+            padding: 15px;
+            background-color: #F8F9FA;
+        }
+        .gr-input {
+            font-size: 1.2em;
+            padding: 10px;
+            border-radius: 5px;
+            border: 2px solid #007BFF;
+            margin-bottom: 10px;
+        }
+        .gr-output {
+            font-size: 1.2em;
+            padding: 10px;
+            border-radius: 5px;
+            border: 2px solid #28A745;
+            background-color: #E9F7EF;
+        }
+        .gr-interface-title {
+            font-size: 2em;
+            font-weight: bold;
+            color: #007BFF;
+            text-align: center;
+            margin-bottom: 20px;
+        }
+        .gr-interface-description {
+            font-size: 1.2em;
+            color: #6C757D;
+            text-align: center;
+            margin-bottom: 20px;
+        }
+        .gr-button {
+            background-color: #007BFF;
+            color: white;
+            border-radius: 5px;
+            padding: 10px 20px;
+            font-size: 1em;
+            border: none;
+            cursor: pointer;
+            margin-top: 10px;
+        }
+        .gr-button:hover {
+            background-color: #0056b3;
+        }
+        </style>
+        <div class="gr-interface-title">Welcome to Mr AI</div>
+        <div class="gr-interface-description">Ask anything and get a helpful response.</div>
+        """,
+        allow_flagging="never",
+        live=True
+    )
+
+    logger.info("Starting Gradio interface")
+    demo.launch(share=True)
 
 if __name__ == "__main__":
-    demo.launch() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.
+    launch_interface()