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c8fb072 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | import streamlit as st
from src.sdlc.graph.graph_builder import GraphBuilder
from src.sdlc.LLMS.groqllm import GroqLLM
from src.sdlc.LLMS.openaillm import OpenAILLM
from src.sdlc.ui.uiconfigfile import Config
import base64
def get_cached_graph():
"""Cache the model so it persists across reruns."""
user_input=st.session_state.get('user_input','')
if user_input['selected_llm'] == 'Groq':
obj_llm_config = GroqLLM(user_controls_input=user_input)
elif user_input['selected_llm'] == 'OpenAI':
obj_llm_config = OpenAILLM(user_controls_input=user_input)
else:
st.error("Invalid LLM selection.")
return
model = obj_llm_config.get_llm_model()
graph_builder = GraphBuilder(model)
return graph_builder.setup_graph()
@st.cache_data
def get_cached_sdlc_nodes():
sdlc_nodes = Config().get_sdlc_nodes()
sdlc_nodes = sdlc_nodes.split(",")
return sdlc_nodes
def clear_cache_data():
st.session_state.clear()
st.cache_data.clear() # Clear all cached data
st.cache_resource.clear() # Clear all cached resources
st.session_state.page = "home"
def display_states(curr_state,response):
state=curr_state.replace('_', ' ')
b64_docs = base64.b64encode(response.encode()).decode()
href = f'''
<a href="data:text/markdown;base64,{b64_docs}"
download="{curr_state}.md"
style="text-decoration: none; color: inherit; font-weight: bold;">
⬇️ Download {state}
</a>
'''
st.markdown(href, unsafe_allow_html=True)
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