Update app.py

app.py

@@ -1,225 +1,129 @@
 import streamlit as st
-
 from ibm_watsonx_ai import APIClient
-
 from ibm_watsonx_ai import Credentials
-
 from ibm_watsonx_ai.foundation_models import ModelInference
-
 from ibm_watsonx_ai.foundation_models.utils.enums import ModelTypes, DecodingMethods
-
 from ibm_watsonx_ai.metanames import GenTextParamsMetaNames as GenParams
-
 import os
 
-
-
 # Set up page configuration
-
 st.set_page_config(page_title="AI Product Design & Development", layout="wide")
 
-
-
-# Initialize session state to keep track of queries
-
+# Initialize session state to track queries and responses
 if 'query_count' not in st.session_state:
-
     st.session_state.query_count = 0
-
 if 'generated_response' not in st.session_state:
-
     st.session_state.generated_response = None
 
-
-
 # Limit the number of queries per session
-
 MAX_QUERIES = 5
 
-
-
 # Sidebar - User inputs for Product Specifications
-
 st.sidebar.title("Product Specifications")
-
 product_name = st.sidebar.text_input("Product Name", "Example Product")
-
 material = st.sidebar.selectbox("Material", ["Plastic", "Metal", "Wood", "Composite"])
-
 dimensions = st.sidebar.text_input("Dimensions (L x W x H in cm)", "10 x 5 x 3")
-
 constraints = st.sidebar.text_area("Design Constraints", "E.g., Must be lightweight, eco-friendly")
-
 budget = st.sidebar.number_input("Budget ($)", min_value=0, value=1000)
 
-
-
 st.sidebar.subheader("Project Info")
-
 st.sidebar.text("AI-Powered Product Design")
 
-
-
 # Main app title and description
-
 st.title("AI Product Design & Development Tool")
-
 st.markdown("""
-
 Welcome to the AI-powered product design and development tool. This app leverages generative AI to accelerate the design process, optimize products for manufacturing, and simulate product performance.
-
 """)
 
-
-
-# Tabs for different sections of the app
-
-tabs = st.tabs(["Design Generation", "Simulation", "Optimization"])
-
-
+# Model Selection
+model_choice = st.sidebar.selectbox(
+    "Choose AI Model",
+    options=[
+        "Granite-13B-Chat-V2 (Text Generation)",
+        "Granite-13B-Instruct-V2 (Detailed Instructions)",
+        "Granite-20B-Multilingual (Multilingual Support)"
+    ]
+)
 
 # IBM WatsonX API Setup
-
 project_id = os.getenv('WATSONX_PROJECT_ID')
-
 api_key = os.getenv('WATSONX_API_KEY')
 
-
-
 if api_key and project_id:
-
     credentials = Credentials(url="https://us-south.ml.cloud.ibm.com", api_key=api_key)
-
     client = APIClient(credentials)
-
     client.set.default_project(project_id)
 
+    # Model Mapping
+    model_mapping = {
+        "Granite-13B-Chat-V2 (Text Generation)": ModelTypes.GRANITE_13B_CHAT_V2,
+        "Granite-13B-Instruct-V2 (Detailed Instructions)": ModelTypes.GRANITE_13B_INSTRUCT_V2,
+        "Granite-20B-Multilingual (Multilingual Support)": ModelTypes.GRANITE_20B_MULTILINGUAL
+    }
 
-
+    selected_model = model_mapping[model_choice]
     parameters = {
-
         GenParams.DECODING_METHOD: DecodingMethods.GREEDY,
-
         GenParams.MIN_NEW_TOKENS: 50,
-
         GenParams.MAX_NEW_TOKENS: 200,
-
         GenParams.STOP_SEQUENCES: ["\n"]
-
     }
 
+    model = ModelInference(model_id=selected_model, params=parameters, credentials=credentials, project_id=project_id)
 
+    # Chat Interaction Box
+    st.subheader("Chat with AI for Product Design")
+    user_input = st.text_input("Ask AI a question related to product design", "")
 
-    model_id = ModelTypes.GRANITE_13B_CHAT_V2  # Initial model, to be evaluated further
-
-    model = ModelInference(model_id=model_id, params=parameters, credentials=credentials, project_id=project_id)
-
-
-
-    # Design Generation Tab
-
-    with tabs[0]:
-
-        st.header("Generate Product Designs")
-
-        st.write("Input your product specifications in the sidebar and click below to generate design concepts.")
-
-
-
+    if user_input and st.button("Submit Query"):
         if st.session_state.query_count < MAX_QUERIES:
+            # Build the prompt based on user input and specifications
+            prompt = f"""You are an AI specialized in product design. Based on the following details:\n
+            Product Name: {product_name}\n
+            Material: {material}\n
+            Dimensions: {dimensions}\n
+            Constraints: {constraints}\n
+            Budget: {budget} USD\n
+            User Query: {user_input}\n
+            Please provide a detailed response."""
+
+            try:
+                with st.spinner("Generating response..."):
+                    response = model.generate_text(prompt=prompt, params=parameters)
+                    st.session_state.generated_response = response
+                    st.session_state.query_count += 1
+                    st.success("AI Response:")
+                    st.write(response)
+            except Exception as e:
+                st.error(f"An error occurred: {e}")
+        else:
+            st.warning(f"You have reached the query limit of {MAX_QUERIES}. Please restart the session to continue.")
 
-            if st.button("Generate Design Concepts"):
-
-                prompt = f"""You are an AI specialized in product design. Generate creative product design concepts based on the following details:\n
-
-                Product Name: {product_name}\n
-
-                Material: {material}\n
-
-                Dimensions: {dimensions}\n
-
-                Constraints: {constraints}\n
-
-                Budget: {budget} USD\n
-
-                Provide detailed design concepts, explaining how they meet the constraints and budget. Also, suggest alternatives if the current design exceeds the budget or constraints."""
-
-
-
+    # Follow-up queries
+    if st.session_state.generated_response:
+        st.subheader("Refine Your Design")
+        
+        if st.session_state.query_count < MAX_QUERIES:
+            if st.button("Ask for a cheaper variant"):
+                follow_up_prompt = prompt + "\nPlease suggest a cheaper variant."
                 try:
-
-                    with st.spinner("Generating design concepts..."):
-
-                        response = model.generate_text(prompt=prompt, params=parameters)
-
-                        st.session_state.generated_response = response
-
-                        st.session_state.query_count += 1
-
-                        st.success("Generated Design Concepts:")
-
-                        st.write(response)
-
+                    follow_up_response = model.generate_text(prompt=follow_up_prompt, params=parameters)
+                    st.session_state.query_count += 1
+                    st.info("Cheaper Variant:")
+                    st.write(follow_up_response)
                 except Exception as e:
-
                     st.error(f"An error occurred: {e}")
 
+            if st.button("Explore alternative materials"):
+                follow_up_prompt = prompt + "\nPlease explore alternative materials that might better fit the design constraints."
+                try:
+                    follow_up_response = model.generate_text(prompt=follow_up_prompt, params=parameters)
+                    st.session_state.query_count += 1
+                    st.info("Alternative Materials:")
+                    st.write(follow_up_response)
+                except Exception as e:
+                    st.error(f"An error occurred: {e}")
         else:
-
-            st.warning(f"You have reached the query limit of {MAX_QUERIES}. Please restart the session to continue.")
-
-
-
-        # Display the previous generated response and allow for follow-up queries
-
-        if st.session_state.generated_response:
-
-            st.subheader("Refine Your Design")
-
-            if st.session_state.query_count < MAX_QUERIES:
-
-                if st.button("Ask for a cheaper variant"):
-
-                    follow_up_prompt = prompt + "\nPlease suggest a cheaper variant."
-
-                    try:
-
-                        follow_up_response = model.generate_text(prompt=follow_up_prompt, params=parameters)
-
-                        st.session_state.query_count += 1
-
-                        st.info("Cheaper Variant:")
-
-                        st.write(follow_up_response)
-
-                    except Exception as e:
-
-                        st.error(f"An error occurred: {e}")
-
-
-
-                if st.button("Explore alternative materials"):
-
-                    follow_up_prompt = prompt + "\nPlease explore alternative materials that might better fit the design constraints."
-
-                    try:
-
-                        follow_up_response = model.generate_text(prompt=follow_up_prompt, params=parameters)
-
-                        st.session_state.query_count += 1
-
-                        st.info("Alternative Materials:")
-
-                        st.write(follow_up_response)
-
-                    except Exception as e:
-
-                        st.error(f"An error occurred: {e}")
-
-            else:
-
-                st.warning("You have reached the query limit.")
-
-
-
-# Simulation and Optimization tabs will be expanded in future steps.
+            st.warning("You have reached the query limit.")
+else:
+    st.error("IBM WatsonX API credentials are not set. Please check your environment variables.")