Update app.py

app.py

@@ -6,139 +6,101 @@ from ibm_watson_machine_learning.foundation_models import Model
 from ibm_watson_machine_learning.metanames import GenTextParamsMetaNames as GenParams
 from ibm_watson_machine_learning.foundation_models.utils.enums import DecodingMethods
 
-# Configuration: API Keys and URLs
+# Configuration
 DISCOVERY_API_KEY = '5sSmoI6y0ZHP7D3a6Iu80neypsbK3tsUZR_VdRAb7ed2'
 WATSONX_API_KEY = 'zf-5qgRvW-_RMBGb0bQw5JPPGGj5wdYpLVypdjQxBGJz'
 WATSONX_PROJECT_ID = '32a4b026-a46a-48df-aae3-31e16caabc3b'
 DISCOVERY_SERVICE_URL = 'https://api.us-south.discovery.watson.cloud.ibm.com/instances/62dc0387-6c6f-4128-b479-00cf5dea09ef'
-
-# Watsonx Model Setup
 url = "https://us-south.ml.cloud.ibm.com"
-DEFAULT_MODEL = "meta-llama/llama-3-1-70b-instruct"
-max_tokens = 100
-min_tokens = 20
-decoding = DecodingMethods.GREEDY
-temperature = 0.7
 
-# IBM Watson Discovery Setup
-discovery_authenticator = IAMAuthenticator(DISCOVERY_API_KEY)
+# Streamlit Config
+st.set_page_config(page_title="Watsonx Advanced UI", layout="wide")
+
+# Sidebar - Model Selection
+st.sidebar.title("Settings")
+model_type = st.sidebar.selectbox(
+    "Select Model", 
+    ["meta-llama/llama-3-1-70b-instruct", "gpt-j-6b-instruct", "gpt-neo-2-7b"]
+)
+max_tokens = st.sidebar.slider("Max Tokens", 50, 4000, 1000)
+temperature = st.sidebar.slider("Temperature", 0.0, 1.0, 0.7)
+
+# Watson Discovery Setup
+authenticator = IAMAuthenticator(DISCOVERY_API_KEY)
 discovery = DiscoveryV2(
     version='2020-08-30',
-    authenticator=discovery_authenticator
+    authenticator=authenticator
 )
 discovery.set_service_url(DISCOVERY_SERVICE_URL)
 
-# Define the model generator function
+# Watsonx Model Setup
 def get_model():
     generate_params = {
         GenParams.MAX_NEW_TOKENS: max_tokens,
-        GenParams.MIN_NEW_TOKENS: min_tokens,
-        GenParams.DECODING_METHOD: decoding,
+        GenParams.MIN_NEW_TOKENS: 20,
+        GenParams.DECODING_METHOD: DecodingMethods.GREEDY,
         GenParams.TEMPERATURE: temperature,
     }
     model = Model(
-        model_id=DEFAULT_MODEL,
+        model_id=model_type,
         params=generate_params,
         credentials={"apikey": WATSONX_API_KEY, "url": url},
         project_id=WATSONX_PROJECT_ID
     )
     return model
 
-# Function to query Watson Discovery and Watsonx Model
+# Chat UI Container
+st.markdown("""
+    <style>
+        .main-chat-container { max-width: 800px; margin: 0 auto; }
+        .chat-bubble { padding: 12px; border-radius: 12px; margin-bottom: 10px; font-size: 16px; }
+        .user-message { background-color: #0078D7; color: white; text-align: right; }
+        .ai-message { background-color: #444; color: white; }
+        .prompt-buttons { display: flex; gap: 10px; }
+        .prompt-button { padding: 10px; border-radius: 10px; background-color: #0078D7; color: white; cursor: pointer; }
+    </style>
+""", unsafe_allow_html=True)
+
+# Suggested Prompts
+st.markdown("<h1 style='text-align: center;'>Watsonx Advanced UI</h1>", unsafe_allow_html=True)
+st.markdown("<div class='main-chat-container'>", unsafe_allow_html=True)
+suggested_prompts = ["Help me study", "Tell me a fun fact", "Overcome procrastination", "Give me ideas"]
+st.markdown("<div class='prompt-buttons'>", unsafe_allow_html=True)
+for prompt in suggested_prompts:
+    if st.button(prompt):
+        question = prompt
+st.markdown("</div>", unsafe_allow_html=True)
+
+# Text Input
+question = st.text_input("Ask your question here...")
+
+# Get Answer Function
 def get_answer(question):
     try:
+        # Watson Discovery Query
         response = discovery.query(
             project_id='016da9fc-26f5-464a-a0b8-c9b0b9da83c7',
             collection_ids=['1d91d603-cd71-5cf5-0000-019325bcd328'],
-            passages={'enabled': True, 'max_per_document': 5, 'find_answers': True},
+            passages={'enabled': True},
             natural_language_query=question
         ).get_result()
-
+        
+        # Extract Context
         passages = response['results'][0].get('document_passages', [])
         context = '\n'.join([p['passage_text'] for p in passages]) or "No relevant information found."
-
-        prompt = (
-            "<s>[INST] <<SYS>> "
-            "Answer the question briefly. If you can't, say 'unanswerable'. "
-            "Question: " + question + '<</SYS>>' + context + '[/INST]'
-        )
-
+        
+        # Watsonx Prompt
+        prompt = f"<s>[INST] <<SYS>> Please answer the question in a concise manner: {question} <<SYS>> {context} [/INST]"
         model = get_model()
         generated_response = model.generate(prompt)
         return generated_response['results'][0]['generated_text']
     except Exception as e:
         return f"Error: {str(e)}"
 
-# Streamlit UI setup
-st.set_page_config(page_title="Advanced AI Chat", layout="wide")
-st.markdown("""
-    <style>
-    .chat-container {
-        max-width: 800px;
-        margin: 0 auto;
-        padding: 20px;
-    }
-    .chat-bubble {
-        padding: 10px 15px;
-        border-radius: 10px;
-        margin-bottom: 10px;
-        font-size: 16px;
-        line-height: 1.5;
-    }
-    .user-question {
-        background-color: #007bff;
-        color: white;
-        align-self: flex-end;
-    }
-    .ai-response {
-        background-color: #f1f1f1;
-        color: black;
-    }
-    .input-container {
-        display: flex;
-        justify-content: center;
-        position: fixed;
-        bottom: 10px;
-        width: 100%;
-    }
-    .input-box {
-        width: 70%;
-        padding: 10px;
-        border-radius: 20px;
-        border: 1px solid #ddd;
-        outline: none;
-        font-size: 16px;
-    }
-    .send-button {
-        padding: 10px 20px;
-        background-color: #007bff;
-        color: white;
-        border: none;
-        border-radius: 20px;
-        cursor: pointer;
-        font-size: 16px;
-        margin-left: 10px;
-    }
-    .send-button:hover {
-        background-color: #0056b3;
-    }
-    </style>
-""", unsafe_allow_html=True)
-
-st.markdown('<div class="chat-container">', unsafe_allow_html=True)
-
-if 'history' not in st.session_state:
-    st.session_state['history'] = []
-
-question = st.text_input("", placeholder="Type your question here...", key="input")
-
-if st.button("Send"):
-    if question.strip():
-        response = get_answer(question.strip())
-        st.session_state['history'].append({"question": question, "answer": response})
-
-for entry in st.session_state['history']:
-    st.markdown(f'<div class="chat-bubble user-question">{entry["question"]}</div>', unsafe_allow_html=True)
-    st.markdown(f'<div class="chat-bubble ai-response">{entry["answer"]}</div>', unsafe_allow_html=True)
+# Display Chat
+if question:
+    answer = get_answer(question)
+    st.markdown(f"<div class='chat-bubble user-message'>{question}</div>", unsafe_allow_html=True)
+    st.markdown(f"<div class='chat-bubble ai-message'>{answer}</div>", unsafe_allow_html=True)
 
-st.markdown('</div>', unsafe_allow_html=True)
+st.markdown("</div>", unsafe_allow_html=True)