Create components/canvas_chat.py

components/canvas_chat.py

@@ -1,33 +1,56 @@
 import streamlit as st
+from langchain_core.messages import AIMessage
 from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.runnables import RunnableLambda, RunnablePassthrough
-from langchain_core.output_parsers import StrOutputParser
-from langchain_groq import ChatGroq
-from utils.prompts import STRATEGY_PROMPT
-import time
+from langchain_community.chat_models import ChatGroq
+from utils.prompts import canvas_prompt
+from utils.session import update_state, get_state_value
 
 def run_canvas_chat():
     st.title("🧠 Canvas Assistant")
+    st.markdown("Let AI guide you step-by-step through your Business Model Canvas.")
 
-    if "canvas_data" not in st.session_state:
-        st.session_state.canvas_data = {}
+    questions = [
+        "What’s your business idea?",
+        "Who are your target customers?",
+        "What problem are you solving?",
+        "What’s your unique value proposition?",
+        "What are your main revenue streams?",
+        "What are your key cost drivers?",
+        "What channels will you use to reach your customers?",
+        "What key partnerships will you need?",
+        "What resources are essential to deliver your solution?",
+        "What are your core activities for success?"
+    ]
 
-    with st.form("canvas_form"):
-        st.header("Complete the Business Model Canvas")
+    responses = get_state_value("canvas_responses", {})
+    current_index = get_state_value("canvas_current_index", 0)
 
-        st.session_state.canvas_data["customer_segments"] = st.text_area("Customer Segments")
-        st.session_state.canvas_data["value_propositions"] = st.text_area("Value Propositions")
-        st.session_state.canvas_data["channels"] = st.text_area("Channels")
-        st.session_state.canvas_data["customer_relationships"] = st.text_area("Customer Relationships")
-        st.session_state.canvas_data["revenue_streams"] = st.text_area("Revenue Streams")
-        st.session_state.canvas_data["key_resources"] = st.text_area("Key Resources")
-        st.session_state.canvas_data["key_activities"] = st.text_area("Key Activities")
-        st.session_state.canvas_data["key_partnerships"] = st.text_area("Key Partnerships")
-        st.session_state.canvas_data["cost_structure"] = st.text_area("Cost Structure")
+    if current_index < len(questions):
+        question = questions[current_index]
+        st.subheader(f"Step {current_index + 1}: {question}")
 
-        submitted = st.form_submit_button("Submit Canvas")
+        user_input = st.text_input("Your Answer", key="user_input")
+        if st.button("Submit"):
+            if user_input.strip() != "":
+                responses[str(current_index)] = user_input.strip()
+                update_state("canvas_responses", responses)
+                update_state("canvas_current_index", current_index + 1)
+                st.rerun()
+            else:
+                st.warning("Please provide a valid answer before proceeding.")
 
-    if submitted:
-        st.success("✅ Canvas information saved!")
-        time.sleep(1)
-        st.rerun()
+    else:
+        st.success("✅ All Canvas steps completed!")
+        st.markdown("### Here's a summary of your Business Model Canvas:")
+
+        summary = ""
+        for idx, q in enumerate(questions):
+            answer = responses.get(str(idx), "Not answered")
+            summary += f"**{q}**\n\n{answer}\n\n"
+
+        st.markdown(summary)
+
+        if st.button("Reset Canvas"):
+            update_state("canvas_responses", {})
+            update_state("canvas_current_index", 0)
+            st.rerun()