diff --git "a/app.py" "b/app.py"
--- "a/app.py"
+++ "b/app.py"
@@ -1,1971 +1,2006 @@
-# app.py
-"""
-Streamlit frontend application for orchestrating an AI-driven SDLC workflow.
-
-This application manages the user interface, state transitions, and calls
-backend logic functions defined in SDLC.py to generate project artifacts.
-Includes cycle-based chat history display.
-"""
-
-# --- Standard Library Imports ---
-import streamlit as st
-import os
-import shutil
-import logging
-from datetime import datetime
-import time
-import zipfile # Standard library zipfile
-
-# --- Third-party Imports ---
-import pydantic_core # For specific error checking
-
-# --- Import core logic from SDLC.py ---
-try:
- import SDLC
- from SDLC import (
- # State and Models
- MainState, GeneratedCode, PlantUMLCode, TestCase, CodeFile, TestCases,
- # Initialization function
- initialize_llm_clients,
- # Workflow Functions (Import all necessary functions)
- generate_questions, refine_prompt,
- generate_initial_user_stories, generate_user_story_feedback, refine_user_stories, save_final_user_story,
- generate_initial_product_review, generate_product_review_feedback, refine_product_review, save_final_product_review,
- generate_initial_design_doc, generate_design_doc_feedback, refine_design_doc, save_final_design_doc,
- select_uml_diagrams, generate_initial_uml_codes, generate_uml_feedback, refine_uml_codes, save_final_uml_diagrams,
- generate_initial_code, web_search_code, generate_code_feedback, refine_code,
- code_review, security_check, refine_code_with_reviews, save_review_security_outputs,
- generate_initial_test_cases, generate_test_cases_feedback, refine_test_cases_and_code, save_testing_outputs,
- generate_initial_quality_analysis, generate_quality_feedback, refine_quality_and_code, save_final_quality_analysis,
- generate_initial_deployment, generate_deployment_feedback, refine_deployment, save_final_deployment_plan,
- # Message Types
- HumanMessage, AIMessage
- )
- logging.info("Successfully imported components from SDLC.py.")
-except ImportError as e:
- st.error(f"Import Error: {e}. Critical file 'SDLC.py' not found or contains errors.")
- logging.critical(f"Failed to import SDLC.py: {e}", exc_info=True)
- st.stop()
-except Exception as e:
- st.error(f"An unexpected error occurred during import from SDLC: {e}")
- logging.critical(f"Unexpected error during import from SDLC: {e}", exc_info=True)
- st.stop()
-
-# --- Application Setup ---
-st.set_page_config(layout="wide", page_title="AI SDLC Workflow")
-logger = logging.getLogger(__name__)
-# Ensure logger is configured
-if not logger.handlers:
- logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
- logger.info("Streamlit app logger configured.")
-
-# --- Constants for Configuration ---
-# Define available providers and their models
-AVAILABLE_MODELS = {
- "Google": [
- "gemini-2.0-flash", "gemini-1.5-pro-latest", "gemini-1.5-flash-latest",
- "gemini-1.0-pro", "gemini-1.0-flash", "gemini-2.5-pro-exp-03-25",
- ],
- "OpenAI": [
- "gpt-4o-mini", "gpt-4o-mini-2024-07-18",
- "gpt-4o", "gpt-4o-2024-08-06",
- "o1-mini", "o1-mini-2024-09-12",
- "o3-mini", "o3-mini-2025-01-31",
- ],
- "Groq": [
- "llama3-8b-8192", "llama3-70b-8192", "llama-3.1-8b-instant",
- "llama-3.2-1b-preview", "llama-3.2-3b-preview", "llama-3.3-70b-specdec",
- "llama-3.3-70b-versatile", "mistral-saba-24b", "gemma2-9b-it",
- "deepseek-r1-distill-llama-70b", "deepseek-r1-distill-qwen-32b",
- "qwen-2.5-32b", "qwen-2.5-coder-32b", "qwen-qwq-32b",
- "mixtral-8x7b-32768",
- ],
-
- "Anthropic": [
- "claude-3-opus-20240229",
- "claude-3-sonnet-20240229",
- "claude-3-haiku-20240307",
- "claude-3-5-haiku-latest",
- "claude-3-5-sonnet-latest",
- "claude-3-7-sonnet-latest"
- ],
- "xAI": [
- "grok-1",
- "grok-2-latest",
- "grok-3",
- "grok-3-mini"
- ]
-}
-LLM_PROVIDERS = list(AVAILABLE_MODELS.keys())
-
-# --- Define Cycle Order and Stage-to-Cycle Mapping ---
-CYCLE_ORDER = [
- "Requirements", "User Story", "Product Review", "Design", "UML",
- "Code Generation", "Review & Security", "Testing", "Quality Analysis", "Deployment"
-]
-STAGE_TO_CYCLE = {
- "initial_setup": "Requirements",
- "run_generate_questions": "Requirements",
- "collect_answers": "Requirements",
- "run_refine_prompt": "Requirements",
- "run_generate_initial_user_stories": "User Story",
- "run_generate_user_story_feedback": "User Story",
- "collect_user_story_human_feedback": "User Story",
- "run_refine_user_stories": "User Story",
- "collect_user_story_decision": "User Story",
- "run_generate_initial_product_review": "Product Review",
- "run_generate_product_review_feedback": "Product Review",
- "collect_product_review_human_feedback": "Product Review",
- "run_refine_product_review": "Product Review",
- "collect_product_review_decision": "Product Review",
- "run_generate_initial_design_doc": "Design",
- "run_generate_design_doc_feedback": "Design",
- "collect_design_doc_human_feedback": "Design",
- "run_refine_design_doc": "Design",
- "collect_design_doc_decision": "Design",
- "run_select_uml_diagrams": "UML",
- "run_generate_initial_uml_codes": "UML",
- "run_generate_uml_feedback": "UML",
- "collect_uml_human_feedback": "UML",
- "run_refine_uml_codes": "UML",
- "collect_uml_decision": "UML",
- "run_generate_initial_code": "Code Generation",
- "collect_code_human_input": "Code Generation",
- "run_web_search_code": "Code Generation",
- "run_generate_code_feedback": "Code Generation",
- "collect_code_human_feedback": "Code Generation",
- "run_refine_code": "Code Generation",
- "collect_code_decision": "Code Generation",
- "run_code_review": "Review & Security",
- "run_security_check": "Review & Security",
- "merge_review_security_feedback": "Review & Security", # Stage name from prompt
- "collect_review_security_human_feedback": "Review & Security", # Hypothetical, check if needed
- "run_refine_code_with_reviews": "Review & Security",
- "collect_review_security_decision": "Review & Security",
- "run_generate_initial_test_cases": "Testing",
- "run_generate_test_cases_feedback": "Testing",
- "collect_test_cases_human_feedback": "Testing",
- "run_refine_test_cases_and_code": "Testing",
- "run_save_testing_outputs": "Testing",
- "run_generate_initial_quality_analysis": "Quality Analysis",
- "run_generate_quality_feedback": "Quality Analysis",
- "collect_quality_human_feedback": "Quality Analysis",
- "run_refine_quality_and_code": "Quality Analysis",
- "collect_quality_decision": "Quality Analysis",
- "generate_initial_deployment": "Deployment", # Stage for form display
- "run_generate_initial_deployment": "Deployment", # Stage for processing
- "run_generate_deployment_feedback": "Deployment",
- "collect_deployment_human_feedback": "Deployment",
- "run_refine_deployment": "Deployment",
- "collect_deployment_decision": "Deployment",
- "END": "END" # Final stage marker
-}
-
-# --- Helper Functions ---
-
-def initialize_state():
- """Initializes or resets the Streamlit session state."""
- timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
- default_project_folder = f"ai_sdlc_project_{timestamp}"
- st.session_state.clear() # Clear all session state keys
- st.session_state.stage = "initial_setup"
- st.session_state.workflow_state = {} # Master state dictionary
- st.session_state.user_input = "" # Temporary storage for text area
- st.session_state.display_content = "Welcome! Please configure API keys and project details to start." # Main display area content
- st.session_state.project_folder_base = default_project_folder
- st.session_state.current_prefs = "" # For deployment preferences
- # ZIP file paths for download buttons
- st.session_state.zip_path = None # Full project zip
- st.session_state.review_code_zip_path = None
- st.session_state.testing_code_zip_path = None
- st.session_state.final_code_zip_path = None
- # Configuration state
- st.session_state.config_applied = False
- st.session_state.selected_provider = LLM_PROVIDERS[0]
- st.session_state.selected_model = AVAILABLE_MODELS[LLM_PROVIDERS[0]][0]
- st.session_state.llm_api_key = ""
- st.session_state.tavily_api_key = ""
- st.session_state.llm_instance = None
- st.session_state.tavily_instance = None
- # Chat history state for current cycle display
- st.session_state.current_cycle_messages = [] # List to hold messages for display in the current cycle
- st.session_state.previous_major_cycle = None # Track the previous cycle to detect changes
- logger.info("Streamlit session state initialized/reset.")
-
- # --- ADDED Initialization for MD/PDF Paths ---
- st.session_state.refined_prompt_path = None
- st.session_state.refined_prompt_pdf_path = None
- st.session_state.final_user_story_path = None
- st.session_state.final_user_story_pdf_path = None
- st.session_state.final_product_review_path = None
- st.session_state.final_product_review_pdf_path = None
- st.session_state.final_design_document_path = None
- st.session_state.final_design_document_pdf_path = None
- st.session_state.final_quality_analysis_path = None
- st.session_state.final_quality_analysis_pdf_path = None
- st.session_state.final_deployment_path = None
- st.session_state.final_deployment_pdf_path = None
- # --- END ADDED ---
- # Snapshot paths
- st.session_state.snapshot_path_codegen_initial = None
- st.session_state.snapshot_path_codegen_refined = None
- st.session_state.snapshot_path_review_refined = None
- st.session_state.snapshot_path_testing_refined = None
- st.session_state.snapshot_path_qa_polished = None
- # Keep final folder paths (might point to last snapshot or dedicated folder)
- st.session_state.review_code_snapshot_folder = None # Points to post_review snapshot
- st.session_state.testing_passed_code_folder = None # Points to snapshot saved by save_testing_outputs
- st.session_state.final_code_folder = None # Points to post_qa snapshot
- # --- END ADDED/MODIFIED ---
-
- logger.info("Streamlit session state initialized/reset including PDF and Snapshot paths.")
-
- logger.info("Streamlit session state initialized/reset including PDF paths.")
-
-def update_display(new_content: str):
- """Updates the main display area content in the session state."""
- st.session_state.display_content = new_content
- logger.debug("Main display content updated.")
-
-def create_download_button(file_path: str, label: str, mime: str, key_suffix: str, help_text: str = ""):
- """Creates a download button for a given file path if it exists and is valid."""
- if not file_path or not isinstance(file_path, str):
- # logger.debug(f"Download button skipped for '{label}': Invalid path ({file_path}).")
- return # Skip if path is invalid
-
- abs_file_path = os.path.abspath(file_path)
- if os.path.exists(abs_file_path) and os.path.isfile(abs_file_path):
- try:
- with open(abs_file_path, "rb") as fp:
- # Sanitize label for key generation, keep it simple
- safe_label_part = "".join(c for c in label if c.isalnum() or c in ['_']).lower()[:15]
- button_key = f"dl_btn_{key_suffix}_{safe_label_part}" # Unique key per button
- st.download_button(
- label=f"Download {label}",
- data=fp,
- file_name=os.path.basename(abs_file_path),
- mime=mime,
- key=button_key,
- help=help_text or f"Download the {label} file."
- )
- except FileNotFoundError:
- # This shouldn't happen if os.path.exists passed, but handle defensively
- logger.warning(f"File disappeared before download button creation: {abs_file_path}")
- except Exception as e:
- logger.error(f"Error preparing download button for '{abs_file_path}': {e}", exc_info=True)
- # Show a less intrusive warning in the UI
- st.warning(f"Could not create download for {label}. Error: {e}", icon="⚠️")
- # else: logger.debug(f"Download button skipped for '{label}': File not found or not a file ({abs_file_path}).")
-
-
-def create_zip_and_download_button(folder_path_key: str, zip_path_key: str, zip_basename: str, button_label_prefix: str, sidebar_context):
- """
- Creates a button to generate a ZIP archive of a specified folder
- and provides a download button for the generated ZIP file.
-
- Args:
- folder_path_key: Key in workflow_state holding the path to the folder to zip.
- zip_path_key: Key in session_state where the path to the created zip file will be stored.
- zip_basename: The base name for the output zip file (without .zip).
- button_label_prefix: Prefix for the button labels (e.g., "Review Stage Code").
- sidebar_context: The Streamlit container (e.g., st.sidebar) where buttons are placed.
- """
- folder_path = st.session_state.workflow_state.get(folder_path_key)
- abs_folder_path = os.path.abspath(folder_path) if folder_path and isinstance(folder_path, str) else None
-
- if abs_folder_path and os.path.exists(abs_folder_path) and os.path.isdir(abs_folder_path):
- # --- Button to Generate ZIP ---
- zip_label = f"Generate & Download {button_label_prefix} ZIP"
- existing_zip = st.session_state.get(zip_path_key)
- if existing_zip and os.path.exists(existing_zip):
- zip_label = f"Download {button_label_prefix} ZIP" # Change label if ZIP exists
-
- # Use a descriptive and unique key for the generation button
- zip_gen_key = f"zip_gen_btn_{zip_path_key}"
- if sidebar_context.button(zip_label, key=zip_gen_key, help=f"Package the {button_label_prefix} folder into a downloadable ZIP file."):
- with st.spinner(f"Creating {button_label_prefix} archive..."):
- try:
- # Define output directory (same level as project folder) and base name
- out_dir = os.path.dirname(abs_folder_path) # Place zip next to the folder being zipped
- archive_base = os.path.join(out_dir, zip_basename) # e.g., ../ai_sdlc_project_xxx/code_snapshot_review
-
- # Define the root directory and the directory to archive relative to the root
- root_dir = os.path.dirname(abs_folder_path) # The parent directory of the folder to zip
- base_dir = os.path.basename(abs_folder_path) # The name of the folder to zip
-
- logger.info(f"Zipping: base_name='{archive_base}', format='zip', root_dir='{root_dir}', base_dir='{base_dir}'")
-
- # Construct the expected output zip file path
- zip_file_path = archive_base + ".zip"
-
- # Remove old zip file if it exists to avoid conflicts
- if os.path.exists(zip_file_path):
- try:
- os.remove(zip_file_path)
- logger.info(f"Removed existing ZIP: {zip_file_path}")
- except Exception as del_e:
- logger.warning(f"Could not remove existing ZIP {zip_file_path}: {del_e}")
-
- # Create the archive
- archive_path = shutil.make_archive(
- base_name=archive_base,
- format='zip',
- root_dir=root_dir,
- base_dir=base_dir
- )
-
- # Verify the archive was created
- if not os.path.exists(archive_path):
- raise OSError(f"ZIP archive creation failed: File not found at {archive_path}")
-
- # Store the path to the created zip file in session state
- st.session_state[zip_path_key] = archive_path
- st.success(f"{button_label_prefix} ZIP created successfully!")
- logger.info(f"Successfully created ZIP archive: {archive_path}")
- st.rerun() # Rerun to update the UI and show the download button
-
- except Exception as e:
- sidebar_context.error(f"ZIP Creation Error: {e}")
- logger.error(f"ZIP creation failed for folder '{abs_folder_path}': {e}", exc_info=True)
-
- # --- Download Button for Existing ZIP ---
- generated_zip = st.session_state.get(zip_path_key)
- if generated_zip and os.path.exists(generated_zip):
- try:
- with open(generated_zip, "rb") as fp:
- # Use a descriptive and unique key for the download button
- safe_prefix = "".join(c for c in button_label_prefix if c.isalnum()).lower()[:10]
- dl_key = f"dl_zip_btn_{zip_path_key}_{safe_prefix}"
- sidebar_context.download_button(
- label=f"Download {button_label_prefix} ZIP",
- data=fp,
- file_name=os.path.basename(generated_zip),
- mime="application/zip",
- key=dl_key,
- help=f"Download the generated {button_label_prefix} ZIP archive."
- )
- except Exception as e:
- sidebar_context.warning(f"Error reading ZIP file for download: {e}")
- logger.error(f"Error reading ZIP file {generated_zip} for download: {e}", exc_info=True)
- # else: logger.debug(f"ZIP button skipped for '{button_label_prefix}': Folder path invalid or not found ({folder_path}).")
-
-# --- Initialize State if First Run ---
-if 'stage' not in st.session_state:
- initialize_state()
-
-# --- Sidebar UI ---
-with st.sidebar:
- st.header("AI SDLC Orchestrator")
- st.caption("Automated workflow from requirements to deployment.")
- st.divider()
-
- # --- Configuration Expander ---
- with st.expander("Configuration", expanded=not st.session_state.get('config_applied', False)):
- st.subheader("LLM & API Keys")
-
- # LLM Provider Selection
- selected_provider = st.selectbox(
- "Select LLM Provider",
- options=LLM_PROVIDERS,
- key="selected_provider", # Keep existing key for state consistency
- index=LLM_PROVIDERS.index(st.session_state.selected_provider) if st.session_state.selected_provider in LLM_PROVIDERS else 0,
- help="Choose the primary Large Language Model provider."
- )
-
- # Dynamically update available models based on provider
- available_models = AVAILABLE_MODELS.get(selected_provider, ["N/A"])
- current_model_selection = st.session_state.selected_model
- model_index = available_models.index(current_model_selection) if current_model_selection in available_models else 0
-
- selected_model = st.selectbox(
- f"Select Model ({selected_provider})",
- options=available_models,
- key="selected_model", # Keep existing key
- index=model_index,
- help=f"Choose a specific model from {selected_provider}."
- )
-
- # API Key Inputs
- llm_api_key_input = st.text_input(
- f"{selected_provider} API Key",
- type="password",
- key="llm_api_key_input", # Keep existing key
- help=f"Enter your API key for the selected {selected_provider} provider.",
- value=st.session_state.get("llm_api_key", "") # Pre-fill if exists
- )
-
- tavily_api_key_input = st.text_input(
- "Tavily API Key (Optional)",
- type="password",
- key="tavily_api_key_input", # Keep existing key
- help="Enter your Tavily API key for enabling web search functionality.",
- value=st.session_state.get("tavily_api_key", "") # Pre-fill if exists
- )
-
- # Apply Configuration Button
- if st.button("Apply Configuration", key="apply_config_button"): # Changed key slightly to avoid potential conflicts if previous runs errored strangely
- with st.spinner("Initializing LLM and Tavily clients..."):
- # Store keys from inputs into session state
- st.session_state.llm_api_key = llm_api_key_input
- st.session_state.tavily_api_key = tavily_api_key_input
-
- # Attempt to initialize clients using the backend function
- llm_inst, tav_inst, error_msg = SDLC.initialize_llm_clients(
- provider=st.session_state.selected_provider,
- model_name=st.session_state.selected_model,
- llm_api_key=st.session_state.llm_api_key,
- tavily_api_key=st.session_state.tavily_api_key
- )
-
- # Update state based on initialization result
- if llm_inst:
- st.session_state.llm_instance = llm_inst
- st.session_state.tavily_instance = tav_inst
- st.session_state.config_applied = True
- st.success("Configuration applied successfully!")
- logger.info(f"LLM ({selected_provider}/{selected_model}) and Tavily clients configured via UI.")
- time.sleep(1) # Brief pause for user to see success message
- st.rerun() # Rerun to potentially collapse expander and enable main workflow
- else:
- st.session_state.config_applied = False
- st.session_state.llm_instance = None
- st.session_state.tavily_instance = None
- error_display = f"Configuration Failed: {error_msg or 'An unknown error occurred.'}"
- st.error(error_display)
- logger.error(error_display)
-
- st.divider()
-
- # --- Downloads Section ---
- st.header("Downloads")
- st.caption("Access generated artifacts and code snapshots.")
-
- # --- MODIFIED: Document Downloads (MD and PDF) ---
- st.markdown("---")
- st.subheader("Documents") # Combined header
-
- # Refined Prompt (Appears after Q&A cycle is complete)
- st.markdown("**Requirements Cycle:**") # Header for this artifact
- create_download_button(st.session_state.workflow_state.get("refined_prompt_path"), "Refined Prompt (MD)", "text/markdown", "refined_prompt_md", help_text="The final prompt generated after Q&A.")
- create_download_button(st.session_state.workflow_state.get("refined_prompt_pdf_path"), "Refined Prompt (PDF)", "application/pdf", "refined_prompt_pdf", help_text="PDF version of the refined prompt.")
- st.markdown("---") # Separator
-
- # User Story
- st.markdown("**User Story Cycle:**")
- create_download_button(st.session_state.workflow_state.get("final_user_story_path"), "User Story (MD)", "text/markdown", "final_us_md")
- create_download_button(st.session_state.workflow_state.get("final_user_story_pdf_path"), "User Story (PDF)", "application/pdf", "final_us_pdf")
- st.markdown("---")
-
- # Product Review
- st.markdown("**Product Review Cycle:**")
- create_download_button(st.session_state.workflow_state.get("final_product_review_path"), "Product Review (MD)", "text/markdown", "final_pr_md")
- create_download_button(st.session_state.workflow_state.get("final_product_review_pdf_path"), "Product Review (PDF)", "application/pdf", "final_pr_pdf")
- st.markdown("---")
-
- # Design Document
- st.markdown("**Design Cycle:**")
- create_download_button(st.session_state.workflow_state.get("final_design_document_path"), "Design Document (MD)", "text/markdown", "final_dd_md")
- create_download_button(st.session_state.workflow_state.get("final_design_document_pdf_path"), "Design Document (PDF)", "application/pdf", "final_dd_pdf")
- st.markdown("---")
-
- # QA Report
- st.markdown("**Quality Analysis Cycle:**")
- create_download_button(st.session_state.workflow_state.get("final_quality_analysis_path"), "QA Report (MD)", "text/markdown", "final_qa_md")
- create_download_button(st.session_state.workflow_state.get("final_quality_analysis_pdf_path"), "QA Report (PDF)", "application/pdf", "final_qa_pdf")
- st.markdown("---")
-
- # Deployment Plan
- st.markdown("**Deployment Cycle:**")
- create_download_button(st.session_state.workflow_state.get("final_deployment_path"), "Deployment Plan (MD)", "text/markdown", "final_deploy_md")
- create_download_button(st.session_state.workflow_state.get("final_deployment_pdf_path"), "Deployment Plan (PDF)", "application/pdf", "final_deploy_pdf")
- # --- END MODIFIED Document Downloads ---
-
- # UML Diagram Downloads
- st.markdown("---")
- st.subheader("UML Diagrams")
- uml_png_paths = st.session_state.workflow_state.get("final_uml_png_paths", [])
- uml_folder = st.session_state.workflow_state.get("final_uml_diagram_folder")
-
- if uml_png_paths:
- st.caption("Download generated PNG images:")
- # Create download buttons for each generated PNG
- for i, png_path in enumerate(uml_png_paths):
- # Attempt to create a meaningful label from the filename
- try:
- base_name = os.path.basename(png_path)
- # Assumes format like 'diagram_01_class_diagram.png'
- label_parts = base_name.split('_')[2:] # Get parts after 'diagram_xx_'
- label = ' '.join(label_parts).replace('.png', '').replace('_', ' ').title()
- if not label: label = f"Diagram {i+1}" # Fallback label
- except Exception:
- label = f"Diagram {i+1}" # Generic fallback
-
- create_download_button(png_path, f"UML: {label}", "image/png", f"uml_png_{i}")
- elif uml_folder and os.path.exists(uml_folder):
- # Indicates UML stage ran but PNGs weren't generated or found
- st.caption("*No PNG diagrams available for download (check PlantUML setup/server). Puml files might be available in the full project ZIP.*")
- else:
- # Indicates UML stage hasn't run or failed before saving
- st.caption("*UML diagrams have not been generated yet.*")
-
- # --- MODIFIED: Code Snapshot Downloads (ZIP) ---
- st.markdown("---")
- st.subheader("Code Snapshots (ZIP)")
- st.caption("Download code versions from various stages.")
-
- # Code Generation Cycle Snapshots
- st.markdown("**Code Generation Cycle:**")
- create_zip_and_download_button(
- folder_path_key="snapshot_path_codegen_initial", # Use the new state key
- zip_path_key="zip_path_cg_initial", # Unique key for session state zip path
- zip_basename="snapshot_codegen_initial",
- button_label_prefix="Initial Code",
- sidebar_context=st.sidebar
- )
- create_zip_and_download_button(
- folder_path_key="snapshot_path_codegen_refined", # Use the new state key
- zip_path_key="zip_path_cg_refined", # Unique key
- zip_basename="snapshot_codegen_refined",
- button_label_prefix="Refined Code (Latest)", # Label indicates latest
- sidebar_context=st.sidebar
- )
- st.markdown("---")
-
- # Review & Security Cycle Snapshot
- st.markdown("**Review & Security Cycle:**")
- create_zip_and_download_button(
- folder_path_key="snapshot_path_review_refined", # Use the new state key
- zip_path_key="zip_path_review_refined", # Unique key
- zip_basename="snapshot_review_refined",
- button_label_prefix="Post-Review Code",
- sidebar_context=st.sidebar
- )
- st.markdown("---")
-
- # Testing Cycle Snapshots
- st.markdown("**Testing Cycle:**")
- create_zip_and_download_button(
- folder_path_key="snapshot_path_testing_refined", # Use the new state key for failed refinement
- zip_path_key="zip_path_testing_refined", # Unique key
- zip_basename="snapshot_testing_refined",
- button_label_prefix="Post-Failure Refined Code (Latest)",
- sidebar_context=st.sidebar
- )
- create_zip_and_download_button(
- folder_path_key="testing_passed_code_folder", # Keep the one saved on PASS
- zip_path_key="zip_path_testing_passed", # Unique key
- zip_basename="snapshot_testing_passed",
- button_label_prefix="Passed Testing Code",
- sidebar_context=st.sidebar
- )
- st.markdown("---")
-
- # Quality Analysis Cycle Snapshot (Final Code)
- st.markdown("**Quality Analysis Cycle:**")
- create_zip_and_download_button(
- folder_path_key="snapshot_path_qa_polished", # Use the new state key (points to final code)
- zip_path_key="zip_path_qa_polished", # Unique key
- zip_basename="snapshot_qa_polished_final",
- button_label_prefix="Final Polished Code",
- sidebar_context=st.sidebar
- )
- # --- END MODIFIED Code Snapshots ---
-
- st.divider()
-
- # --- Full Project ZIP (only appears at the end) ---
- if st.session_state.stage == "END":
- st.markdown("**Full Project Archive**")
- st.caption("Download all generated artifacts and code snapshots in a single ZIP.")
- proj_folder = st.session_state.workflow_state.get("project_folder")
- abs_proj = os.path.abspath(proj_folder) if proj_folder and isinstance(proj_folder, str) else None
-
- if abs_proj and os.path.isdir(abs_proj):
- zip_label = "Generate & Download Full Project ZIP"
- if st.session_state.get("zip_path") and os.path.exists(st.session_state.zip_path):
- zip_label = "Download Full Project ZIP" # Change label if already generated
-
- if st.sidebar.button(zip_label, key="zip_gen_final_project_btn"): # Unique key
- with st.spinner("Creating full project archive..."):
- try:
- # Use the project_folder_base which is set at init and guaranteed unique
- zip_base = os.path.abspath(st.session_state.project_folder_base)
- out_dir = os.path.dirname(zip_base) # Place zip in parent dir
- os.makedirs(out_dir, exist_ok=True)
-
- root_dir = os.path.dirname(abs_proj) # Parent of the project folder
- base_dir = os.path.basename(abs_proj) # Name of the project folder
-
- logger.info(f"Zipping full project: base_name='{zip_base}', format='zip', root_dir='{root_dir}', base_dir='{base_dir}'")
- zip_file_path = zip_base + ".zip"
-
- # Remove old zip if exists
- if os.path.exists(zip_file_path):
- try:
- os.remove(zip_file_path)
- logger.info(f"Removed old final project ZIP: {zip_file_path}")
- except Exception as del_e:
- logger.warning(f"Could not remove old final project ZIP {zip_file_path}: {del_e}")
-
- # Create the archive
- archive_path = shutil.make_archive(
- base_name=zip_base,
- format='zip',
- root_dir=root_dir,
- base_dir=base_dir
- )
-
- # Verify creation
- if not os.path.exists(archive_path):
- raise OSError(f"Final project ZIP creation failed: File not found at {archive_path}")
-
- st.session_state.zip_path = archive_path # Store path
- st.success(f"Full project ZIP created: {os.path.basename(archive_path)}")
- st.rerun() # Update UI
-
- except Exception as e:
- st.sidebar.error(f"Final Project ZIP Error: {e}")
- logger.error(f"Final project ZIP creation failed: {e}", exc_info=True)
-
- # Provide download button if zip exists
- if st.session_state.get("zip_path") and os.path.exists(st.session_state.zip_path):
- try:
- with open(st.session_state.zip_path, "rb") as fp:
- st.sidebar.download_button(
- label="Download Full Project ZIP",
- data=fp,
- file_name=os.path.basename(st.session_state.zip_path),
- mime="application/zip",
- key="dl_zip_final_project_btn" # Unique key
- )
- except Exception as read_e:
- st.sidebar.warning(f"Error reading final project ZIP: {read_e}")
- logger.error(f"Error reading final project ZIP {st.session_state.zip_path}: {read_e}", exc_info=True)
- elif proj_folder:
- st.sidebar.warning(f"Project folder '{proj_folder}' not found for final ZIP.")
- else:
- st.sidebar.caption("*Project folder not yet defined.*")
-
- st.divider()
-
- # --- Restart Button ---
- if st.sidebar.button("Restart Workflow", key="restart_workflow_button", help="Clear all progress and configuration, then start over."):
- # Optional: Add confirmation dialog here if desired
- logger.info("Workflow restart requested by user.")
- # Clean up project directory if it exists
- proj_folder_to_delete = st.session_state.workflow_state.get("project_folder")
- if proj_folder_to_delete and os.path.isdir(proj_folder_to_delete):
- try:
- shutil.rmtree(proj_folder_to_delete)
- logger.info(f"Removed project folder on restart: {proj_folder_to_delete}")
- except Exception as e:
- logger.warning(f"Could not remove project folder '{proj_folder_to_delete}' on restart: {e}")
- initialize_state()
- st.rerun()
-
-# ==============================================================================
-# --- Main Layout Area ---
-# ==============================================================================
-
-main_col, indicator_col = st.columns([4, 1]) # Main content area, Cycle indicator sidebar
-
-# --- Cycle Change Detection and History Reset ---
-current_stage = st.session_state.stage
-current_major_cycle = STAGE_TO_CYCLE.get(current_stage, "Unknown")
-
-# Initialize previous cycle tracker if it doesn't exist
-if 'previous_major_cycle' not in st.session_state:
- st.session_state.previous_major_cycle = current_major_cycle
-
-# Check if the cycle has changed since the last run
-if st.session_state.previous_major_cycle != current_major_cycle and current_major_cycle != "Unknown":
- logger.info(f"Detected cycle change: '{st.session_state.previous_major_cycle}' -> '{current_major_cycle}'. Clearing current cycle message display.")
- st.session_state.current_cycle_messages = [] # Reset the list for the new cycle
- st.session_state.previous_major_cycle = current_major_cycle # Update the tracker
-
-# --- Main Column Content ---
-with main_col:
- # Display current stage and cycle title
- stage_display_name = current_stage.replace('_', ' ').title()
- if current_stage == "END":
- st.header("🏁 Workflow Complete")
- else:
- st.header(f"Cycle: {current_major_cycle} | Stage: {stage_display_name}")
-
- # --- Chat History Display Area (Current Cycle Only) ---
- st.markdown("### Current Cycle Interaction History")
- # Get the messages specifically for the current cycle display
- current_cycle_messages_list = st.session_state.get("current_cycle_messages", [])
-
- # Use a container with fixed height for scrollable chat
- chat_container = st.container(height=350, border=True)
- with chat_container:
- if not current_cycle_messages_list:
- st.caption("No interactions recorded for this cycle yet.")
- else:
- # Iterate through messages stored for the current cycle display
- for msg in current_cycle_messages_list:
- # Determine role based on message type
- if isinstance(msg, AIMessage):
- role = "assistant"
- avatar = "🤖"
- elif isinstance(msg, HumanMessage):
- role = "user"
- avatar = "🧑💻"
- else:
- role = "system" # Or handle other types if necessary
- avatar = "⚙️"
-
- with st.chat_message(role, avatar=avatar):
- # Display message content using markdown
- # Ensure content is string; handle potential non-string data safely
- content_display = str(msg.content) if msg.content is not None else "[No Content]"
- st.markdown(content_display, unsafe_allow_html=False) # Security best practice
-
- st.divider() # Visual separator
-
- # --- Current Task / Output Display ---
- st.markdown("### Current Task / Latest Output:")
- display_area = st.container(border=True) # Add border for visual separation
- with display_area:
- # Get content safely, default to a clear message
- display_content_md = st.session_state.get("display_content", "Awaiting next step...")
- # Ensure it's a string before displaying
- if not isinstance(display_content_md, str):
- display_content_md = str(display_content_md)
- st.markdown(display_content_md, unsafe_allow_html=False) # Disable HTML rendering
-
- st.divider() # Visual separator
-
- # --- Input / Decision Widgets ---
- # Only show workflow UI elements if configuration is applied
- if not st.session_state.get('config_applied', False):
- if st.session_state.stage != "initial_setup": # Don't show warning during initial setup itself
- st.warning("👈 Please apply LLM & API Key configuration in the sidebar to start the workflow.")
- else:
- # Determine which UI elements to show based on the current stage
- current_stage_ui = st.session_state.stage # Use a distinct variable for clarity
-
- input_needed_stages = {
- "collect_answers", "collect_user_story_human_feedback",
- "collect_product_review_human_feedback", "collect_design_doc_human_feedback",
- "collect_uml_human_feedback", "collect_code_human_input",
- "collect_code_human_feedback", "merge_review_security_feedback", # This stage now collects feedback
- "collect_quality_human_feedback", "collect_deployment_human_feedback"
- }
- decision_needed_stages = {
- "collect_user_story_decision", "collect_product_review_decision",
- "collect_design_doc_decision", "collect_uml_decision", "collect_code_decision",
- "collect_review_security_decision", "collect_quality_decision",
- "collect_deployment_decision"
- }
-
- show_initial_setup_form = (current_stage_ui == "initial_setup")
- show_deployment_prefs_form = (current_stage_ui == "generate_initial_deployment")
- show_input_box = current_stage_ui in input_needed_stages
- show_test_feedback_area = (current_stage_ui == "collect_test_cases_human_feedback")
- show_decision_buttons = current_stage_ui in decision_needed_stages
-
- # --- Initial Setup Form ---
- if show_initial_setup_form:
- with st.form("initial_project_setup_form"): # Descriptive key
- st.markdown("### Project Configuration")
- st.info("Define the initial parameters for your software project.")
-
- proj_folder = st.text_input(
- "Project Folder Name",
- value=st.session_state.project_folder_base,
- key="proj_folder_input",
- help="Directory name for saved outputs. Use valid filesystem characters (no spaces/special chars like /\\:*?\"<>| recommended)."
- )
- proj_name = st.text_input(
- "Project Description",
- value="Web Task Manager Example", # Example default
- key="proj_name_input",
- help="A brief, high-level description of the project's purpose."
- )
- proj_cat = st.text_input(
- "Category",
- value="Web Development", # Example default
- key="proj_cat_input",
- help="Broad category (e.g., Web Development, Data Science, Game Dev, Mobile App)."
- )
- proj_subcat = st.text_input(
- "Subcategory",
- value="Productivity Tool", # Example default
- key="proj_subcat_input",
- help="More specific classification (e.g., API, Library, CLI Tool, Backend Service)."
- )
- proj_lang = st.text_input(
- "Coding Language",
- value="Python", # Example default
- key="proj_lang_input",
- help="The primary programming language for the project (e.g., Python, JavaScript, Java, Go)."
- )
- min_iter = st.number_input(
- "Min Q&A Rounds",
- min_value=1, max_value=5, value=2,
- key="min_iter_input",
- help="Minimum required rounds of questions and answers for requirements gathering."
- )
-
- submitted = st.form_submit_button("Start Workflow")
-
- if submitted:
- # Validation checks
- error_messages = []
- if not all([proj_folder, proj_name, proj_cat, proj_subcat, proj_lang]):
- error_messages.append("Please fill all configuration fields.")
- # Basic check for invalid characters, can be expanded
- invalid_chars = ['/', '\\', ':', '*', '?', '"', '<', '>', '|']
- if any(c in proj_folder for c in invalid_chars) or ' ' in proj_folder:
- error_messages.append("Project Folder Name should not contain spaces or special characters like /\\:*?\"<>|.")
-
- if error_messages:
- for msg in error_messages: st.error(msg)
- else:
- try:
- # Prepare absolute path and check filesystem status
- abs_proj_folder = os.path.abspath(proj_folder)
- if os.path.exists(abs_proj_folder) and not os.path.isdir(abs_proj_folder):
- st.error(f"Error: A file (not a folder) already exists with the name '{proj_folder}'. Please choose a different name.")
- else:
- # Create folder if it doesn't exist, warn if it does
- if os.path.exists(abs_proj_folder):
- st.warning(f"Warning: Project folder '{abs_proj_folder}' already exists. Files within might be overwritten during the workflow.")
- else:
- os.makedirs(abs_proj_folder, exist_ok=True)
- st.success(f"Project folder created/confirmed: '{abs_proj_folder}'")
- logger.info(f"Project folder ready: {abs_proj_folder}")
-
- # --- Initialize workflow_state ---
- initial_human_message_content = f"Initial Setup:\n- Project: {proj_name}\n- Category: {proj_cat}/{proj_subcat}\n- Language: {proj_lang}\n- Min Q&A Rounds: {min_iter}"
- initial_human_message = SDLC.HumanMessage(content=initial_human_message_content)
-
- # Build the initial state dictionary carefully
- initial_workflow_state = {
- # Core instances (must be present if config applied)
- "llm_instance": st.session_state.llm_instance,
- "tavily_instance": st.session_state.tavily_instance,
- # Communication history starts with the setup message
- "messages": [initial_human_message],
- # Project Configuration
- "project_folder": proj_folder,
- "project": proj_name,
- "category": proj_cat,
- "subcategory": proj_subcat,
- "coding_language": proj_lang,
- # Requirements Gathering State
- "user_input_iteration": 0,
- "user_input_min_iterations": min_iter,
- "user_input_questions": [],
- "user_input_answers": [],
- "user_input_done": False,
- "user_query_with_qa": "", # Will be built later
- "refined_prompt": "",
- # Initialize cycle states (using defaults where appropriate)
- "user_story_current": "", "user_story_feedback": "", "user_story_human_feedback": "", "user_story_done": False,
- "product_review_current": "", "product_review_feedback": "", "product_review_human_feedback": "", "product_review_done": False,
- "design_doc_current": "", "design_doc_feedback": "", "design_doc_human_feedback": "", "design_doc_done": False,
- "uml_selected_diagrams": [], "uml_current_codes": [], "uml_feedback": {}, "uml_human_feedback": {}, "uml_done": False,
- # Use a valid default GeneratedCode object
- # Use a valid default GeneratedCode object with placeholder instructions meeting min_length
- "code_current": SDLC.GeneratedCode(files=[], instructions="[Placeholder - Code not generated yet.]"),
- "code_human_input": "", "code_web_search_results": "", "code_feedback": "", "code_human_feedback": "", "code_done": False,
- "code_review_current_feedback": "", "security_current_feedback": "", "review_security_human_feedback": "", "review_security_done": False,
- "test_cases_current": [], "test_cases_feedback": "", "test_cases_human_feedback": "", "test_cases_passed": False,
- "quality_current_analysis": "", "quality_feedback": "", "quality_human_feedback": "", "quality_done": False,
- "deployment_current_process": "", "deployment_feedback": "", "deployment_human_feedback": "", "deployment_done": False,
- # Final artifact storage (initialize as None or empty)
- "final_user_story": "", "final_product_review": "", "final_design_document": "",
- "final_uml_codes": [], "final_code_files": [], "final_code_review": "",
- "final_security_issues": "", "final_test_code_files": [], "final_quality_analysis": "",
- "final_deployment_process": "",
- # --- ADDED/MODIFIED: Initialize MD/PDF paths ---
- "refined_prompt_path": None,
- "refined_prompt_pdf_path": None,
- "final_user_story_path": None,
- "final_user_story_pdf_path": None,
- "final_product_review_path": None,
- "final_product_review_pdf_path": None,
- "final_design_document_path": None,
- "final_design_document_pdf_path": None,
- "final_uml_diagram_folder": None,
- "final_uml_png_paths": [],
- "final_review_security_folder": None,
- "review_code_snapshot_folder": None,
- "final_testing_folder": None,
- "testing_passed_code_folder": None,
- "final_quality_analysis_path": None, # MD path
- "final_quality_analysis_pdf_path": None, # PDF path
- "final_code_folder": None,
- "final_deployment_path": None, # MD path
- "final_deployment_pdf_path": None, # PDF path
- # --- END ADDED/MODIFIED ---
- # Intermediate Snapshot Paths
- "snapshot_path_codegen_initial": None,
- "snapshot_path_codegen_refined": None,
- "snapshot_path_review_refined": None,
- "snapshot_path_testing_refined": None,
- "snapshot_path_qa_polished": None,
- }
-
- # Update the main session state variables
- st.session_state.workflow_state = initial_workflow_state
- st.session_state.project_folder_base = proj_folder # Update base if user changed it
- st.session_state.stage = "run_generate_questions" # Move to the first processing stage
-
- # Add the initial setup message to the current cycle display list
- st.session_state.current_cycle_messages.append(initial_human_message)
- # Ensure previous_major_cycle is set for the first cycle
- if st.session_state.previous_major_cycle is None:
- st.session_state.previous_major_cycle = STAGE_TO_CYCLE.get("initial_setup", "Requirements")
-
- logger.info(f"Initial setup complete. Starting workflow for project '{proj_name}'.")
- st.rerun() # Rerun to start the workflow execution
-
- except OSError as oe:
- st.error(f"Filesystem Error creating folder '{proj_folder}': {oe}. Check permissions or choose a different name.")
- logger.error(f"OSError during initial setup folder creation: {oe}", exc_info=True)
- except Exception as e:
- st.error(f"An unexpected error occurred during setup: {e}")
- logger.error(f"Unexpected error during initial setup: {e}", exc_info=True)
-
- # --- Deployment Preferences Form ---
- elif show_deployment_prefs_form:
- with st.form("deployment_preferences_form"): # Descriptive key
- st.markdown("### Deployment Preferences")
- st.info("Specify your desired deployment target and any relevant details.")
-
- # Common deployment targets
- deploy_target = st.selectbox(
- "Target Environment",
- options=["Localhost (using Docker)", "Docker (generic)", "AWS EC2", "AWS ECS/Fargate", "AWS Lambda", "Google Cloud Run", "Google Kubernetes Engine (GKE)", "Azure App Service", "Azure Kubernetes Service (AKS)", "Other Cloud VM", "Other Serverless", "Other Container Orchestrator"],
- key="deploy_target_select",
- help="Choose the primary target environment for deployment."
- )
-
- deploy_details = st.text_area(
- "Additional Details / Constraints:",
- height=100,
- key="deploy_details_input",
- placeholder="e.g., Specific AWS region (us-east-1), use Nginx as reverse proxy, database connection string source, required OS, any existing infrastructure to leverage.",
- help="Provide any specific requirements, configurations, or constraints for the deployment."
- )
-
- submitted = st.form_submit_button("Generate Deployment Plan")
- if submitted:
- # Combine preferences into a string for the backend
- prefs = f"Target Environment: {deploy_target}\nAdditional Details: {deploy_details}"
- st.session_state.current_prefs = prefs # Store for potential use/display later
- st.session_state.stage = "run_generate_initial_deployment" # Move to the processing stage
- logger.info(f"Deployment preferences collected: Target='{deploy_target}'")
-
- # Add human message for context
- deploy_prefs_message = SDLC.HumanMessage(content=f"Deployment Preferences Set:\n{prefs}")
- st.session_state.workflow_state["messages"].append(deploy_prefs_message)
- st.session_state.current_cycle_messages.append(deploy_prefs_message)
-
- st.rerun()
-
- # --- General Input/Feedback Text Area ---
- elif show_input_box:
- input_label = "Your Input / Feedback:"
- input_help = "Provide your answers or feedback here. For Q&A, type '#DONE' on a new line when finished with the current round."
- # Customize label/help based on stage if needed
- if current_stage_ui == "collect_answers":
- input_label = "Your Answers:"
- elif current_stage_ui == "collect_code_human_input":
- input_label = "Describe Issues / Provide Input for Code:"
- input_help = "Describe any errors encountered, unexpected behavior, or specific inputs you want the AI to test/consider."
- elif current_stage_ui == "merge_review_security_feedback":
- input_label = "Your Feedback on Review/Security Reports:"
- input_help = "Provide any comments, clarifications, or priorities regarding the code review and security findings."
-
- input_key = f"text_input_{current_stage_ui}" # Stage-specific key
- user_val = st.text_area(
- input_label,
- height=150,
- key=input_key,
- value=st.session_state.get('user_input', ''), # Use temporary storage if needed for complex edits
- help=input_help
- )
-
- submit_key = f"submit_button_{current_stage_ui}" # Stage-specific key
- if st.button("Submit", key=submit_key):
- user_text = user_val.strip()
- # Basic validation: Ensure input is not empty
- if not user_text:
- st.warning("Please enter some input before submitting.")
- else:
- state = st.session_state.workflow_state
- # Validate state type
- if not isinstance(state, dict):
- st.error("Workflow state is invalid. Restarting.")
- logger.critical("Workflow state became invalid (not a dict). Forcing restart.")
- initialize_state()
- st.rerun()
- st.stop()
-
- try:
- next_stage = None # Initialize next stage
- # Ensure message list exists in state
- if 'messages' not in state or not isinstance(state['messages'], list):
- state['messages'] = []
-
- # Create the HumanMessage object
- human_message = SDLC.HumanMessage(content=user_text)
- # Add to master list
- state["messages"].append(human_message)
- # Add to current cycle display list
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.append(human_message)
-
- # --- Map current stage to state key, next run stage, and input type ---
- # Tuple format: (state_key_to_update, next_processing_stage, needs_list_append)
- map_logic = {
- "collect_answers": ("user_input_answers", "run_generate_questions", True),
- "collect_user_story_human_feedback": ("user_story_human_feedback", "run_refine_user_stories", False),
- "collect_product_review_human_feedback": ("product_review_human_feedback", "run_refine_product_review", False),
- "collect_design_doc_human_feedback": ("design_doc_human_feedback", "run_refine_design_doc", False),
- "collect_uml_human_feedback": ("uml_human_feedback", "run_refine_uml_codes", False), # Special dict handling below
- "collect_code_human_input": ("code_human_input", "run_web_search_code", False),
- "collect_code_human_feedback": ("code_human_feedback", "run_refine_code", False),
- "merge_review_security_feedback": ("review_security_human_feedback", "run_refine_code_with_reviews", False),
- "collect_quality_human_feedback": ("quality_human_feedback", "run_refine_quality_and_code", False),
- "collect_deployment_human_feedback": ("deployment_human_feedback", "run_refine_deployment", False),
- }
-
- if current_stage_ui in map_logic:
- key_to_update, next_process_stage, is_list_input = map_logic[current_stage_ui]
-
- # Store the input text in the workflow state dictionary
- if is_list_input:
- # Append input to the list for this key
- state[key_to_update] = state.get(key_to_update, []) + [user_text]
- elif key_to_update == "uml_human_feedback":
- # Store UML feedback in the expected dict format, using 'all' for simplicity
- state[key_to_update] = {"all": user_text}
- else:
- # Overwrite state key with the new text value
- state[key_to_update] = user_text
-
- next_stage = next_process_stage # Set the next stage for processing
-
- # --- Special Handling Logic ---
-
- # Q&A Completion Check
- if current_stage_ui == "collect_answers":
- state["user_input_iteration"] = state.get("user_input_iteration", 0) + 1
- min_iterations_required = state.get("user_input_min_iterations", 1)
- # Check if #DONE is present (case-insensitive) in the last non-empty line
- lines = [line.strip() for line in user_text.splitlines() if line.strip()]
- is_done_signal_present = "#DONE" in lines[-1].upper() if lines else False
-
- logger.debug(f"Q&A Iteration: {state['user_input_iteration']} / {min_iterations_required}. '#DONE' signal present: {is_done_signal_present}")
-
- # Check if minimum iterations met AND done signal given
- if state["user_input_iteration"] >= min_iterations_required and is_done_signal_present:
- state["user_input_done"] = True
- next_stage = "run_refine_prompt" # Override: Q&A phase is finished, move to refining the prompt
- logger.info("Minimum Q&A iterations met and #DONE signal received. Proceeding to prompt refinement.")
- else:
- state["user_input_done"] = False
- # next_stage remains 'run_generate_questions' (to ask more questions)
- logger.info("Continuing Q&A round.")
-
- # Skip Web Search if Tavily is not configured
- if current_stage_ui == "collect_code_human_input" and not state.get('tavily_instance'):
- state["code_web_search_results"] = "Skipped (Tavily client not configured)"
- next_stage = "run_generate_code_feedback" # Skip web search and go directly to code feedback
- logger.info("Tavily not configured. Skipping web search step.")
-
- else:
- # Fallback if stage logic is somehow missing
- st.error(f"Internal Error: Input handling logic is undefined for stage '{current_stage_ui}'. Please report this.")
- logger.error(f"Input handling logic missing for defined input stage: {current_stage_ui}")
-
- # --- Transition to Next Stage ---
- if next_stage:
- st.session_state.workflow_state = state # Commit state changes
- st.session_state.user_input = "" # Clear the temporary input box content on successful submission
- st.session_state.stage = next_stage # Update the application stage
- logger.info(f"User input submitted for stage '{current_stage_ui}'. Transitioning to stage '{next_stage}'.")
- st.rerun() # Rerun Streamlit to reflect the new stage
-
- except Exception as e:
- st.error(f"An error occurred while processing your input: {e}")
- logger.error(f"Error processing input for stage '{current_stage_ui}': {e}", exc_info=True)
- # Keep the input in the text box on error by not clearing st.session_state.user_input
-
- # --- Test Execution Feedback Area ---
- elif show_test_feedback_area:
- st.markdown("### Test Execution & Feedback")
- st.info("Please execute the generated tests against the code. Then, provide feedback on the results and indicate if the core functionality passed.")
-
- # Display AI feedback on the tests for context
- ai_test_feedback = st.session_state.workflow_state.get("test_cases_feedback", "*No AI feedback on tests was generated.*")
- with st.expander("View AI Feedback on Test Cases"):
- st.markdown(ai_test_feedback)
-
- # Input area for human feedback/results
- human_fb_text = st.text_area(
- "Your Feedback & Test Results:",
- height=150,
- key="test_case_human_feedback_input", # Unique key
- help="Describe which tests passed/failed, provide any error messages, stack traces, or observations from running the tests."
- )
-
- # Radio button for overall PASS/FAIL status
- pass_fail_status = st.radio(
- "Did the core functionality pass the tests?",
- options=("PASS", "FAIL"),
- index=1, # Default to FAIL
- key="test_case_pass_fail_radio", # Unique key
- horizontal=True,
- help="Select PASS only if the critical user stories are working as expected based on your testing."
- )
-
- # Action buttons
- col1, col2 = st.columns(2)
- with col1: # Submit Results button
- submit_key_test = "submit_test_results_button" # Unique key
- if st.button("Submit Test Results", key=submit_key_test):
- state = st.session_state.workflow_state
- # Ensure messages list exists
- if 'messages' not in state or not isinstance(state['messages'], list): state['messages'] = []
-
- # Format feedback and create HumanMessage
- feedback_content = f"Test Execution Summary:\n- Overall Status: {pass_fail_status}\n- Detailed Feedback/Results:\n{human_fb_text}"
- human_message = SDLC.HumanMessage(content=feedback_content)
-
- # Add message to master list and current cycle display
- state["messages"].append(human_message)
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.append(human_message)
-
- # Update state with feedback and pass/fail status
- state["test_cases_human_feedback"] = feedback_content
- state["test_cases_passed"] = (pass_fail_status == "PASS")
- logger.info(f"Test results submitted. Overall status: {pass_fail_status}.")
-
- # Determine next stage based on pass/fail
- next_stage_after_test = "run_save_testing_outputs" if state["test_cases_passed"] else "run_refine_test_cases_and_code"
- st.session_state.stage = next_stage_after_test
- st.session_state.workflow_state = state # Commit state changes
- logger.info(f"Transitioning to stage '{next_stage_after_test}' based on test results.")
- st.rerun()
-
- with col2: # Submit & Regenerate Code button (optional, allows skipping refinement)
- regen_key_test = "regenerate_code_from_testing_button" # Unique key
- if st.button("Regenerate Code (If Stuck)", key=regen_key_test, help="Use this if refinement isn't working and you want the AI to try generating code again from scratch, incorporating this test feedback."):
- state = st.session_state.workflow_state
- if 'messages' not in state or not isinstance(state['messages'], list): state['messages'] = []
-
- # Format feedback indicating regeneration request
- feedback_content_regen = f"Test Execution Summary:\n- Overall Status: {pass_fail_status}\n- Detailed Feedback/Results:\n{human_fb_text}\n\nDecision: Requesting full code regeneration based on this feedback."
- human_message_regen = SDLC.HumanMessage(content=feedback_content_regen)
-
- # Add message to history
- state["messages"].append(human_message_regen)
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.append(human_message_regen)
-
- # Store feedback, ensure test_cases_passed is False
- state["test_cases_human_feedback"] = feedback_content_regen # Store context
- state["test_cases_passed"] = False # Force refinement/regen path
- logger.info(f"Test feedback submitted ({pass_fail_status}), requesting code regeneration.")
-
- # --- Prepare Context for Code Regeneration ---
- # Package testing feedback to guide the *initial* code generation step again
- regen_context = f"Context from Failed Testing Cycle:\n- Overall Status: {pass_fail_status}\n- User Feedback/Errors:\n{human_fb_text}\n- AI Feedback on Failed Tests:\n{ai_test_feedback}\n\nInstruction: Regenerate the entire codebase attempting to address these issues from the start."
- state["code_human_input"] = regen_context # Use the input field of the code generation cycle
-
- # Add context message (optional, can be verbose but useful for tracing)
- context_message = SDLC.HumanMessage(content=f"Context Forwarded for Code Regeneration (from Testing): {regen_context[:300]}...")
- state["messages"].append(context_message) # Add to master list
- st.session_state.current_cycle_messages.append(context_message) # Add to cycle list
-
- # --- Transition Back to Code Generation ---
- # NOTE: This jumps back significantly. Consider if a less drastic jump is desired.
- # For now, jumping back to the *input* stage before initial code gen.
- st.session_state.stage = "run_generate_initial_code" # Go back to generate initial code
- st.session_state.workflow_state = state # Commit state
- logger.info("Transitioning back to 'run_generate_initial_code' for regeneration based on test feedback.")
- st.rerun()
-
- # --- Decision Buttons (Approve/Refine) ---
- elif show_decision_buttons:
- st.markdown("### Decision Point")
- st.info("Review the latest output for this cycle. Choose whether to refine it further based on feedback or approve it and proceed to the next cycle.")
-
- # Define mappings for Refine and Proceed actions based on the current stage
- # Refine Map: current_decision_stage -> next_feedback_or_input_stage
- refine_map = {
- "collect_user_story_decision": "run_generate_user_story_feedback",
- "collect_product_review_decision": "run_generate_product_review_feedback",
- "collect_design_doc_decision": "run_generate_design_doc_feedback",
- "collect_uml_decision": "run_generate_uml_feedback",
- "collect_code_decision": "collect_code_human_input", # Refining code usually needs new input/issues
- "collect_review_security_decision": "run_code_review", # Restart review cycle
- "collect_quality_decision": "run_generate_quality_feedback",
- "collect_deployment_decision": "run_generate_deployment_feedback",
- }
- # Proceed Map: current_decision_stage -> (done_flag_key, save_function or None, next_cycle_start_stage)
- proceed_map = {
- "collect_user_story_decision": ("user_story_done", SDLC.save_final_user_story, "run_generate_initial_product_review"),
- "collect_product_review_decision": ("product_review_done", SDLC.save_final_product_review, "run_generate_initial_design_doc"),
- "collect_design_doc_decision": ("design_doc_done", SDLC.save_final_design_doc, "run_select_uml_diagrams"),
- "collect_uml_decision": ("uml_done", SDLC.save_final_uml_diagrams, "run_generate_initial_code"),
- # Proceeding from Code Generation saves the current code to final_code_files
- "collect_code_decision": ("code_done", None, "run_code_review"), # No specific save func here, handled in logic below
- "collect_review_security_decision": ("review_security_done", SDLC.save_review_security_outputs, "run_generate_initial_test_cases"),
- "collect_quality_decision": ("quality_done", SDLC.save_final_quality_analysis, "generate_initial_deployment"), # Go to deployment prefs form
- "collect_deployment_decision": ("deployment_done", SDLC.save_final_deployment_plan, "END"), # End of workflow
- }
-
- # Determine button layout (add third button for QA code regen)
- num_cols = 3 if current_stage_ui == "collect_quality_decision" else 2
- cols = st.columns(num_cols)
-
- # --- Refine Button ---
- with cols[0]:
- refine_key = f"refine_button_{current_stage_ui}" # Unique key
- if st.button("Refine Further", key=refine_key, help="Go back and provide more feedback or request AI changes for the current artifact(s)."):
- if current_stage_ui in refine_map:
- state = st.session_state.workflow_state
- # Mark as not done (to allow refinement loop)
- done_key = current_stage_ui.replace("collect_", "").replace("_decision", "_done")
- state[done_key] = False
- next_refine_stage = refine_map[current_stage_ui]
-
- # Add human message indicating decision
- refine_message = SDLC.HumanMessage(content=f"Decision: Refine '{current_major_cycle}' cycle further.")
- state['messages'] = state.get('messages', []) + [refine_message]
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.append(refine_message)
-
- # Transition to the refinement starting stage
- st.session_state.stage = next_refine_stage
- st.session_state.workflow_state = state
- logger.info(f"Decision made to Refine cycle '{current_major_cycle}'. Transitioning to stage '{next_refine_stage}'.")
- st.rerun()
- else:
- st.warning(f"Refinement logic is not defined for stage '{current_stage_ui}'.")
- logger.warning(f"Attempted to refine from stage '{current_stage_ui}' but no refine path is defined.")
-
- # --- Proceed Button ---
- with cols[1]:
- proceed_key = f"proceed_button_{current_stage_ui}" # Unique key
- if st.button("Approve & Proceed", key=proceed_key, help="Finalize the current cycle's artifacts and move to the next stage of the workflow."):
- if current_stage_ui in proceed_map:
- state = st.session_state.workflow_state
- done_key, save_function, next_major_stage = proceed_map[current_stage_ui]
- error_occurred = False
-
- try:
- # Mark the cycle as done
- state[done_key] = True
- logger.info(f"Decision made to Proceed from cycle '{current_major_cycle}'. Marked '{done_key}'=True.")
-
- # Add human message indicating decision
- proceed_message = SDLC.HumanMessage(content=f"Decision: Approve and proceed from '{current_major_cycle}' cycle.")
- state['messages'] = state.get('messages', []) + [proceed_message]
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.append(proceed_message)
-
- # --- Special Handling for Code Promotion ---
- # When proceeding from Code Generation, store the current code as the baseline for Review/Security
- if current_stage_ui == "collect_code_decision":
- current_code_object = state.get("code_current")
- if current_code_object and isinstance(current_code_object, SDLC.GeneratedCode) and current_code_object.files:
- state["final_code_files"] = current_code_object.files # This becomes the input for the next stage
- logger.info(f"Promoted {len(current_code_object.files)} code files from 'code_current' to 'final_code_files' for Review cycle.")
- else:
- st.warning("Proceeding from Code Generation, but the 'code_current' state seems invalid or empty. Review cycle might lack code.")
- logger.warning("Proceeding from Code Generation, but 'code_current' is invalid or has no files. Setting 'final_code_files' to empty list.")
- state["final_code_files"] = []
-
- # --- Execute Save Function (if applicable) ---
- if save_function:
- save_func_name = getattr(save_function, '__name__', 'artifact_save_function')
- logger.info(f"Executing save function: {save_func_name}")
- with st.spinner(f"Saving {save_func_name.replace('save_final_', '').replace('_', ' ')}..."):
- state = save_function(state) # Update state with results of save function (e.g., file paths)
- st.session_state.workflow_state = state # Commit state update
-
- # --- Post-Save Validation (Check if expected output path exists) ---
- # Map save functions to the state keys where they store output paths
- save_path_keys = {
- SDLC.save_final_user_story: "final_user_story_path",
- SDLC.save_final_product_review: "final_product_review_path",
- SDLC.save_final_design_doc: "final_design_document_path",
- SDLC.save_final_uml_diagrams: "final_uml_diagram_folder", # Check folder for UML
- SDLC.save_review_security_outputs: "final_review_security_folder", # Check main folder
- SDLC.save_testing_outputs: "final_testing_folder", # Check main folder
- SDLC.save_final_quality_analysis: "final_quality_analysis_path", # Check report path
- SDLC.save_final_deployment_plan: "final_deployment_path",
- }
- expected_path_key = save_path_keys.get(save_function)
- saved_path_value = state.get(expected_path_key) if expected_path_key else True # Assume success if no path key expected
-
- # Check if the path exists (and is a file/dir as appropriate)
- save_successful = False
- if expected_path_key:
- if saved_path_value and isinstance(saved_path_value, str) and os.path.exists(saved_path_value):
- # Basic check: path exists. Could add isfile/isdir if needed.
- save_successful = True
- else:
- save_successful = True # No specific path to check
-
- # Additionally check for QA saving the final code folder
- if save_function == SDLC.save_final_quality_analysis:
- final_code_folder_path = state.get("final_code_folder")
- if not (final_code_folder_path and os.path.isdir(final_code_folder_path)):
- save_successful = False # Mark as failed if final code didn't save properly
-
- if not save_successful:
- st.warning(f"Proceeding, but the save operation for '{current_major_cycle}' might have failed (output path invalid or missing). Check logs.")
- logger.warning(f"Save check failed after running {save_func_name}. Expected path key: {expected_path_key}, Value: {saved_path_value}")
- else:
- logger.info(f"Save function {save_func_name} completed successfully and path validation passed (if applicable).")
-
- except Exception as e:
- st.error(f"An error occurred while finalizing cycle '{current_major_cycle}': {e}")
- logger.error(f"Error during 'Proceed' action for stage '{current_stage_ui}': {e}", exc_info=True)
- error_occurred = True
-
- # Transition only if no errors occurred
- if not error_occurred:
- st.session_state.stage = next_major_stage
- logger.info(f"Transitioning to the next cycle's start stage: '{next_major_stage}'")
- st.rerun()
- else:
- st.warning(f"Proceed logic is not defined for stage '{current_stage_ui}'.")
- logger.warning(f"Attempted to proceed from stage '{current_stage_ui}' but no proceed path is defined.")
-
- # --- Regenerate Code Button (Only for QA Decision) ---
- if current_stage_ui == "collect_quality_decision":
- with cols[2]:
- regen_key_qa = "regenerate_code_from_qa_button" # Unique key
- if st.button("Regenerate Code", key=regen_key_qa, help="If QA revealed significant issues needing a code rewrite, use this to jump back to code generation, providing QA feedback as context."):
- state = st.session_state.workflow_state
- if 'messages' not in state or not isinstance(state['messages'], list): state['messages'] = []
- logger.info("Decision: Requesting code regeneration based on QA findings.")
-
- # Add human message
- regen_message = SDLC.HumanMessage(content="Decision: Regenerate code based on Quality Analysis findings.")
- state["messages"].append(regen_message)
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.append(regen_message)
-
- # --- Prepare context for regeneration ---
- qa_report_summary = state.get('quality_current_analysis', 'No QA report available.')[:1500] # Limit summary length
- regen_context = f"Context from Quality Analysis Cycle:\n- Final QA Report Summary:\n{qa_report_summary}\n\nInstruction: Regenerate the codebase attempting to address the quality concerns raised in the report."
- state["code_human_input"] = regen_context # Feed context into the code gen input
-
- # Add context message to history
- context_message = SDLC.HumanMessage(content=f"Context Forwarded for Code Regeneration (from QA): {regen_context[:300]}...")
- state["messages"].append(context_message)
- st.session_state.current_cycle_messages.append(context_message)
-
- # --- Transition back to Code Generation ---
- st.session_state.stage = "run_generate_initial_code" # Jump back
- st.session_state.workflow_state = state
- logger.info("Transitioning back to 'run_generate_initial_code' for regeneration based on QA feedback.")
- st.rerun()
-
- # --- End Stage ---
- elif current_stage_ui == "END":
- st.balloons()
- final_message = "## 🎉 Workflow Completed Successfully! 🎉\n\nAll cycles have been processed.\n\nYou can download the final artifacts and code snapshots from the sidebar.\n\nUse the 'Restart Workflow' button in the sidebar to begin a new project."
- update_display(final_message) # Update the display area as well
- st.markdown(final_message)
- logger.info("Workflow reached END stage.")
-
- # --- Fallback for Unknown UI Stages ---
- # This handles cases where the stage is not 'initial_setup', not a 'run_' stage,
- # and not one of the known input/decision stages. Should ideally not happen.
- elif not current_stage_ui.startswith("run_"):
- st.error(f"Internal Error: Reached an unknown UI interaction stage: '{current_stage_ui}'. The workflow might be stuck. Consider restarting.")
- logger.error(f"Reached unknown UI stage: {current_stage_ui}. State might be inconsistent.")
-
-
-# ==============================================================================
-# --- Cycle Indicator Column ---
-# ==============================================================================
-with indicator_col:
- st.subheader("Workflow Cycles")
- st.caption("Current progress through the SDLC.")
-
- # Determine the current cycle index for highlighting
- current_major_indicator = STAGE_TO_CYCLE.get(st.session_state.stage, "Unknown")
- current_idx_indicator = -1 # Default if stage/cycle is unknown
- if current_major_indicator == "END":
- current_idx_indicator = len(CYCLE_ORDER) # Mark as completed
- elif current_major_indicator in CYCLE_ORDER:
- current_idx_indicator = CYCLE_ORDER.index(current_major_indicator)
-
- # Simple CSS for styling the cycle list
- st.markdown("""
-
- """, unsafe_allow_html=True)
-
- # Display the cycle list with indicators
- # Optionally implement windowing/scrolling if list gets very long
- # win_before, win_after = 2, 4 # Example windowing parameters
- # start = max(0, current_idx_indicator - win_before)
- # end = min(len(CYCLE_ORDER), start + win_before + win_after + 1)
- # start = max(0, end - (win_before + win_after + 1)) # Adjust start if end was clamped
-
- for i, cycle_name in enumerate(CYCLE_ORDER):
- # if start <= i < end : # Apply windowing if uncommented above
- css_class = "cycle-item"
- display_name = cycle_name
-
- if i < current_idx_indicator:
- css_class += " cycle-past"
- display_name = f"✓ {cycle_name}" # Indicate past cycles
- elif i == current_idx_indicator and current_major_indicator != "END":
- css_class += " cycle-current"
- display_name = f"➡️ {cycle_name}" # Indicate current cycle
- else: # Future cycles
- css_class += " cycle-future"
-
- # Render the cycle item using markdown with embedded HTML/CSS
- st.markdown(f'{display_name}
', unsafe_allow_html=True)
-
- # Display completion marker if workflow is finished
- if current_major_indicator == "END":
- st.markdown(f'✅ Workflow End
', unsafe_allow_html=True)
-
-
-# ==============================================================================
-# --- Invisible Stage Execution Logic ---
-# ==============================================================================
-
-def run_workflow_step(func, next_display_stage, *args):
- """
- Executes a backend workflow function (from SDLC.py), handles state updates,
- manages display content, adds messages to history, and transitions the UI stage.
-
- Args:
- func: The backend function to execute (e.g., SDLC.generate_questions).
- next_display_stage: The stage the UI should transition to after this step completes.
- *args: Additional arguments required by the backend function.
- """
- state_before = st.session_state.workflow_state
- messages_before_count = len(state_before.get('messages', []))
-
- # --- Define a VALID default GeneratedCode object for safety ---
- # This object includes the required 'instructions' field.
- valid_default_code = SDLC.GeneratedCode(files=[], instructions="[Default Instructions - Code Not Generated or Error]")
-
- # --- Pre-execution Checks ---
- if not isinstance(state_before, dict):
- st.error("Workflow state has become invalid. Please restart.")
- logger.critical("Workflow state is not a dictionary. Halting execution.")
- initialize_state() # Consider resetting state automatically or just stopping
- st.rerun()
- return # Stop execution
-
- # Get function name for logging/display
- func_name = getattr(func, '__name__', repr(func))
- # Handle lambda function name (specifically for deployment)
- if func_name == '': func_name = "generate_initial_deployment"
-
- logger.info(f"Executing workflow step: {func_name}")
- try:
- # Show spinner during execution
- with st.spinner(f"Running: {func_name.replace('_',' ').title()}..."):
-
- # --- Check for Required Resources (LLM, Tavily) ---
- needs_llm = func not in [
- SDLC.save_final_user_story, SDLC.save_final_product_review,
- SDLC.save_final_design_doc, SDLC.save_final_uml_diagrams,
- SDLC.save_review_security_outputs, SDLC.save_testing_outputs,
- SDLC.save_final_quality_analysis, SDLC.save_final_deployment_plan,
- SDLC.web_search_code # Web search uses Tavily, checked separately
- ]
- if needs_llm and not state_before.get('llm_instance'):
- raise ConnectionError("LLM client is not configured or initialized in the workflow state.")
-
- # --- Handle Skippable Steps (e.g., Web Search) ---
- if func == SDLC.web_search_code and not state_before.get('tavily_instance'):
- logger.warning("Web search step called, but Tavily client is not available in state. Skipping step.")
- state_before["code_web_search_results"] = "Skipped (Tavily client not configured or API key missing)"
- # Add a message indicating the skip
- skip_message = AIMessage(content="Web Search: Skipped (Tavily client unavailable)")
- state_before["messages"] = state_before.get("messages", []) + [skip_message]
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.append(skip_message)
-
- # Manually update state and transition
- st.session_state.workflow_state = state_before
- st.session_state.stage = "run_generate_code_feedback" # Define the stage *after* web search
- logger.info("Skipped web search. Transitioning directly to 'run_generate_code_feedback'.")
- st.rerun()
- return # Exit this function call
-
- # --- Special Handling for Sequential Review/Security Steps ---
- # If the function is code_review, run it, update state, and immediately trigger security_check
- if func == SDLC.code_review:
- logger.info("Executing code review step...")
- state_after_review = SDLC.code_review(state_before, *args)
- if not isinstance(state_after_review, dict):
- raise TypeError(f"Function 'code_review' did not return a dictionary state. Got: {type(state_after_review)}")
-
- # Add any new messages from code_review to the cycle display
- messages_after_review_count = len(state_after_review.get('messages', []))
- new_review_messages = state_after_review.get('messages', [])[messages_before_count:messages_after_review_count]
- if new_review_messages:
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.extend(new_review_messages)
-
- # Update the main state
- st.session_state.workflow_state = state_after_review
- # Transition directly to the security check stage
- st.session_state.stage = "run_security_check"
- logger.info("Code review completed. Transitioning directly to 'run_security_check'.")
- st.rerun()
- return # Exit this function call, security check will run on the next rerun
-
- # --- Normal Function Execution ---
- updated_state = func(state_before, *args)
-
- # --- Post-execution State Update and Validation ---
- if not isinstance(updated_state, dict):
- # This indicates a fundamental issue with the backend function
- logger.error(f"Workflow function '{func_name}' returned an invalid type: {type(updated_state)}. Expected a dictionary.")
- st.error(f"Internal Error: Step '{func_name}' failed due to an unexpected return type. Workflow halted.")
- st.stop() # Halt execution as state is likely corrupted
- return
-
- st.session_state.workflow_state = updated_state
- logger.debug(f"State successfully updated after executing {func_name}.")
-
- # --- Add New AI Messages to Cycle Display ---
- messages_after_count = len(updated_state.get('messages', []))
- new_messages = updated_state.get('messages', [])[messages_before_count:messages_after_count]
- if new_messages:
- # Filter to only add AI messages generated by this step
- new_ai_messages = [msg for msg in new_messages if isinstance(msg, AIMessage)]
- if new_ai_messages:
- if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
- st.session_state.current_cycle_messages.extend(new_ai_messages)
- logger.debug(f"Added {len(new_ai_messages)} new AI message(s) from {func_name} to cycle display.")
-
- # --- Determine Display Content for the Next UI Stage ---
- # (This complex block sets `display_text` and potentially overrides `next_display_stage`)
- display_text = f"Completed step: {func_name}. Preparing for {next_display_stage}..." # Default message
-
- if func == SDLC.generate_questions:
- # Display the newly generated questions
- questions = updated_state.get("user_input_questions", [])[-5:] # Get last 5 questions
- if questions:
- min_iter = updated_state.get('user_input_min_iterations', 1)
- current_iter = updated_state.get("user_input_iteration", 0) # Iteration *before* answering these
- is_min_met = (current_iter + 1 >= min_iter) # Check if *this round* meets the minimum
- min_iter_msg = f"(Minimum {min_iter} rounds required)" if not is_min_met else ""
- display_text = f"**Please answer the following questions {min_iter_msg}:**\n\n" + "\n".join(f"- {q}" for q in questions)
- if is_min_met:
- display_text += "\n\n*When finished answering, type **#DONE** on a new line to proceed.*"
- next_display_stage = "collect_answers" # Ensure UI goes to answer collection
- else:
- # If no questions were generated (e.g., AI decided it's enough)
- display_text = "The AI generated no further questions. Refining the project prompt based on the discussion..."
- logger.info("No new questions generated by AI. Moving to refine prompt.")
- next_display_stage = "run_refine_prompt" # Skip answer collection
-
- elif func == SDLC.refine_prompt:
- refined_prompt = updated_state.get('refined_prompt', '*Error: Refined prompt not found in state.*')
- display_text = f"**Refined Project Prompt:**\n```markdown\n{refined_prompt}\n```\n\n*Generating initial User Stories based on this prompt...*"
-
- elif func == SDLC.generate_initial_user_stories:
- stories = updated_state.get('user_story_current', '*Error: User stories not found.*')
- display_text = f"**Initial User Stories Generated:**\n\n{stories}\n\n*Generating AI feedback on these stories...*"
-
- elif func == SDLC.generate_user_story_feedback:
- current_stories = updated_state.get('user_story_current', '*N/A*')
- ai_feedback = updated_state.get('user_story_feedback', '*N/A*')
- display_text = f"**Current User Stories:**\n```\n{current_stories}\n```\n---\n**AI Feedback on Stories:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or desired changes below.*"
- next_display_stage = "collect_user_story_human_feedback" # Ready for human input
-
- elif func == SDLC.refine_user_stories:
- refined_stories = updated_state.get('user_story_current', '*N/A*')
- display_text = f"**Refined User Stories:**\n\n{refined_stories}\n\n*Please review the refined stories. Choose 'Refine Further' or 'Approve & Proceed' below.*"
- next_display_stage = "collect_user_story_decision" # Ready for decision
-
- elif func == SDLC.generate_initial_product_review:
- review = updated_state.get('product_review_current', '*N/A*')
- display_text = f"**Initial Product Owner Review Generated:**\n\n{review}\n\n*Generating AI feedback on this review...*"
-
- elif func == SDLC.generate_product_review_feedback:
- current_review = updated_state.get('product_review_current', '*N/A*')
- ai_feedback = updated_state.get('product_review_feedback', '*N/A*')
- display_text = f"**Current Product Review:**\n```\n{current_review}\n```\n---\n**AI Feedback on Review:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or desired changes below.*"
- next_display_stage = "collect_product_review_human_feedback"
-
- elif func == SDLC.refine_product_review:
- refined_review = updated_state.get('product_review_current', '*N/A*')
- display_text = f"**Refined Product Review:**\n\n{refined_review}\n\n*Please review the refined PO review. Choose 'Refine Further' or 'Approve & Proceed' below.*"
- next_display_stage = "collect_product_review_decision"
-
- elif func == SDLC.generate_initial_design_doc:
- doc = updated_state.get('design_doc_current', '*N/A*')
- display_text = f"**Initial Design Document Generated:**\n```markdown\n{doc}\n```\n\n*Generating AI feedback on this document...*"
-
- elif func == SDLC.generate_design_doc_feedback:
- current_doc = updated_state.get('design_doc_current', '*N/A*')
- ai_feedback = updated_state.get('design_doc_feedback', '*N/A*')
- display_text = f"**Current Design Document:**\n```markdown\n{current_doc}\n```\n---\n**AI Feedback on Design:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or desired changes below.*"
- next_display_stage = "collect_design_doc_human_feedback"
-
- elif func == SDLC.refine_design_doc:
- refined_doc = updated_state.get('design_doc_current', '*N/A*')
- display_text = f"**Refined Design Document:**\n```markdown\n{refined_doc}\n```\n\n*Please review the refined design. Choose 'Refine Further' or 'Approve & Proceed' below.*"
- next_display_stage = "collect_design_doc_decision"
-
- elif func == SDLC.select_uml_diagrams:
- messages = updated_state.get('messages', [])
- # Try to find the specific justification message from the AI
- justification_msg_content = "Relevant UML diagram types selected based on the design." # Default
- if messages and isinstance(messages[-1], AIMessage) and ("selected" in messages[-1].content.lower() or "recommend" in messages[-1].content.lower()):
- justification_msg_content = messages[-1].content # Use the actual AI message content
- display_text = f"**UML Diagram Selection:**\n\n{justification_msg_content}\n\n*Generating initial PlantUML code for selected diagrams...*"
-
- elif func == SDLC.generate_initial_uml_codes:
- codes = updated_state.get('uml_current_codes', [])
- if codes:
- codes_display = "\n\n".join([f"**{c.diagram_type}**:\n```plantuml\n{c.code}\n```" for c in codes])
- else:
- codes_display = "*No UML codes were generated.*"
- display_text = f"**Generated Initial PlantUML Codes:**\n\n{codes_display}\n\n*Generating AI feedback on these diagrams...*"
-
- elif func == SDLC.generate_uml_feedback:
- codes = updated_state.get('uml_current_codes', [])
- feedback_dict = updated_state.get('uml_feedback', {})
- codes_display = "\n\n".join([f"**{c.diagram_type}**:\n```plantuml\n{c.code}\n```" for c in codes]) if codes else "*N/A*"
- feedback_display = "\n\n".join([f"**Feedback for {dt}:**\n{fb}" for dt, fb in feedback_dict.items()]) if feedback_dict else "*N/A*"
- display_text = f"**Current UML Codes:**\n{codes_display}\n---\n**AI Feedback on Diagrams:**\n{feedback_display}\n\n---\n*Provide your overall feedback or specific changes needed below.*"
- next_display_stage = "collect_uml_human_feedback"
-
- elif func == SDLC.refine_uml_codes:
- codes = updated_state.get('uml_current_codes', [])
- codes_display = "\n\n".join([f"**{c.diagram_type} (Refined):**\n```plantuml\n{c.code}\n```" for c in codes]) if codes else "*N/A*"
- display_text = f"**Refined UML Codes:**\n\n{codes_display}\n\n*Please review the refined diagrams. Choose 'Refine Further' or 'Approve & Proceed' below.*"
- next_display_stage = "collect_uml_decision"
-
- elif func == SDLC.generate_initial_code:
- code_data = updated_state.get("code_current", valid_default_code) # Use valid default here!
- files_display = []
- total_len, max_len = 0, 4000 # Limit display length
- num_files = len(code_data.files) if code_data and code_data.files else 0
- instr = code_data.instructions if code_data else "[Instructions not available]"
-
- if num_files > 0:
- for f in code_data.files:
- header = f"**File: {f.filename}**:\n```\n"
- footer = "\n```\n"
- # Calculate max content preview length safely
- max_content = max(0, max_len - total_len - len(header) - len(footer) - 50) # 50 char buffer
- content_preview = f.content[:max_content] if f.content else ""
- is_truncated = len(f.content) > len(content_preview) if f.content else False
- preview_str = f"{header}{content_preview}{'... (content truncated)' if is_truncated else ''}{footer}"
- files_display.append(preview_str)
- total_len += len(preview_str)
- if total_len >= max_len:
- files_display.append("\n*...(Code file display truncated due to length)*")
- break
- code_files_str = "".join(files_display)
- display_text = f"**Initial Code Generated ({num_files} file{'s' if num_files != 1 else ''}):**\n{code_files_str}\n---\n**Setup & Run Instructions:**\n```\n{instr}\n```\n\n---\n*Try to set up and run the code. Describe any errors or issues below.*"
- else:
- display_text = "Initial code generation step completed, but no code files were generated. This might indicate an issue with the request or the LLM's response.\n\n*Please describe the expected outcome or provide feedback below.*"
- logger.warning("generate_initial_code resulted in a valid GeneratedCode structure but with an empty file list.")
- next_display_stage = "collect_code_human_input"
-
- elif func == SDLC.web_search_code:
- results = updated_state.get('code_web_search_results', '*No web search results available.*')
- display_text = f"**Web Search Results (if applicable):**\n\n{results}\n\n*Generating AI feedback on the code, considering your input and these search results...*"
-
- elif func == SDLC.generate_code_feedback:
- ai_feedback = updated_state.get('code_feedback', '*N/A*')
- user_input = updated_state.get('code_human_input', None) # Get the input that triggered this
- context_header = "**Context Provided (User Input/Issue):**\n" if user_input else ""
- user_input_display = f"```\n{user_input}\n```\n---\n" if user_input else ""
- display_text = f"{context_header}{user_input_display}**AI Code Feedback:**\n\n{ai_feedback}\n\n---\n*Please provide your comments on the AI's feedback below (e.g., 'Yes, suggestion 1 seems right', 'No, the issue is actually in file X').*"
- next_display_stage = "collect_code_human_feedback"
-
- elif func == SDLC.refine_code:
- code_data = updated_state.get("code_current", valid_default_code) # Use valid default
- files_display=[]; total_len, max_len=0, 4000
- num_files = len(code_data.files) if code_data else 0
- instr = code_data.instructions if code_data else "[Instructions not available]"
- if num_files > 0:
- for f in code_data.files:
- header = f"**File: {f.filename} (Refined):**\n```\n"; footer = "\n```\n"
- max_content = max(0, max_len - total_len - len(header) - len(footer) - 50)
- content_preview = f.content[:max_content] if f.content else ""; is_truncated = len(f.content) > len(content_preview) if f.content else False
- preview_str = f"{header}{content_preview}{'... (content truncated)' if is_truncated else ''}{footer}"
- files_display.append(preview_str); total_len += len(preview_str)
- if total_len >= max_len: files_display.append("\n*...(Code file display truncated)*"); break
- code_files_str = "".join(files_display)
- display_text = f"**Refined Code ({num_files} file{'s' if num_files != 1 else ''}):**\n{code_files_str}\n---\n**Setup/Run Instructions:**\n```\n{instr}\n```\n\n---\n*Please review the refined code. Choose 'Refine Further' or 'Approve & Proceed' below.*"
- else:
- display_text = "Code refinement step completed, but no files were found in the result. This might indicate an error.\n\n*Choose 'Refine Further' to provide input or 'Approve & Proceed' if this is expected.*"
- logger.warning("refine_code resulted in a valid GeneratedCode structure but with an empty file list.")
- next_display_stage = "collect_code_decision"
-
- elif func == SDLC.security_check: # Display after security check completes (code review ran just before)
- review_fb = updated_state.get('code_review_current_feedback', '*Code review feedback not available.*')
- security_fb = updated_state.get('security_current_feedback', '*Security check feedback not available.*')
- display_text = f"**Code Review Findings:**\n```\n{review_fb}\n```\n---\n**Security Check Findings:**\n```\n{security_fb}\n```\n---\n*Please provide your overall feedback on these reports below (e.g., prioritize fixes, accept risks).*";
- next_display_stage = "merge_review_security_feedback" # Stage to collect feedback on both reports
-
- elif func == SDLC.refine_code_with_reviews:
- code_data = updated_state.get("code_current", valid_default_code) # Use valid default
- files_display=[]; total_len, max_len=0, 4000
- num_files = len(code_data.files) if code_data else 0
- instr = code_data.instructions if code_data else "[Instructions not available]"
- if num_files > 0:
- for f in code_data.files:
- header = f"**File: {f.filename} (Post-Review/Security):**\n```\n"; footer = "\n```\n"
- max_content = max(0, max_len - total_len - len(header) - len(footer) - 50)
- content_preview = f.content[:max_content] if f.content else ""; is_truncated = len(f.content) > len(content_preview) if f.content else False
- preview_str = f"{header}{content_preview}{'... (content truncated)' if is_truncated else ''}{footer}"
- files_display.append(preview_str); total_len += len(preview_str)
- if total_len >= max_len: files_display.append("\n*...(Code file display truncated)*"); break
- code_files_str = "".join(files_display)
- display_text = f"**Code Refined Post-Review & Security ({num_files} file{'s' if num_files != 1 else ''}):**\n{code_files_str}\n---\n**Setup/Run Instructions:**\n```\n{instr}\n```\n\n---\n*This code incorporates feedback from the review cycle. Review the final code and decide below.*"
- else:
- display_text = "Code refinement post-review completed, but no files found. This likely indicates an error.\n\n*Choose 'Refine Further' (to restart review) or 'Approve & Proceed' if this was somehow expected.*"
- logger.error("refine_code_with_reviews resulted in an empty file list.")
- next_display_stage = "collect_review_security_decision"
-
- elif func == SDLC.generate_initial_test_cases:
- tests = updated_state.get('test_cases_current', [])
- tests_display = "\n\n".join([f"**Test: {tc.description}**\n - Input: `{tc.input_data}`\n - Expected Output: `{tc.expected_output}`" for tc in tests]) if tests else "*No test cases generated.*"
- display_text=f"**Generated Initial Test Cases ({len(tests)}):**\n\n{tests_display}\n\n*Generating AI feedback on these test cases...*"
-
- elif func == SDLC.generate_test_cases_feedback:
- tests = updated_state.get('test_cases_current', [])
- ai_feedback = updated_state.get('test_cases_feedback', '*N/A*')
- tests_display = "\n\n".join([f"**Test: {tc.description}**\n - Input: `{tc.input_data}`\n - Expected Output: `{tc.expected_output}`" for tc in tests]) if tests else "*N/A*"
- display_text=f"**Current Test Cases ({len(tests)}):**\n{tests_display}\n---\n**AI Feedback on Tests:**\n\n{ai_feedback}\n\n---\n*Please execute these tests against the code and report the results/feedback below.*";
- next_display_stage = "collect_test_cases_human_feedback"
-
- elif func == SDLC.refine_test_cases_and_code:
- tests = updated_state.get('test_cases_current', [])
- code_data_after_test_refine = updated_state.get('code_current', valid_default_code) # Use valid default
- files_count = len(code_data_after_test_refine.files) if code_data_after_test_refine else 0
- code_update_msg = f"Code ({files_count} files) and {len(tests)} test case(s) were refined based on test failures." if files_count > 0 else f"{len(tests)} Test case(s) refined (code may not have changed)."
- tests_display = "\n\n".join([f"**Test: {tc.description}**:\n - Input:`{tc.input_data}`\n - Expected:`{tc.expected_output}`" for tc in tests]) if tests else "*N/A*"
- display_text = f"**Refinement After Test Failure:**\n*{code_update_msg}*\n\n**Refined Tests ({len(tests)}):**\n{tests_display}\n\n*Please execute the tests again using the refined code and provide results/feedback below.*";
- next_display_stage = "collect_test_cases_human_feedback" # Loop back to collect results again
-
- elif func == SDLC.save_testing_outputs:
- display_text = f"Testing cycle completed (PASS). Final tests and passed code snapshot saved.\n\n*Generating overall Quality Analysis report...*"
-
- elif func == SDLC.generate_initial_quality_analysis:
- report = updated_state.get('quality_current_analysis', '*N/A*')
- display_text=f"**Initial Quality Analysis Report Generated:**\n\n{report}\n\n*Generating AI feedback on this QA report...*"
-
- elif func == SDLC.generate_quality_feedback:
- current_report = updated_state.get('quality_current_analysis', '*N/A*')
- ai_feedback = updated_state.get('quality_feedback', '*N/A*')
- display_text=f"**Current QA Report:**\n```\n{current_report}\n```\n---\n**AI Feedback on QA Report:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback on the QA report below.*";
- next_display_stage = "collect_quality_human_feedback"
-
- elif func == SDLC.refine_quality_and_code:
- report = updated_state.get('quality_current_analysis', '*N/A*')
- code_data_qa_refined = updated_state.get('code_current', valid_default_code) # Use valid default
- code_files_exist = bool(code_data_qa_refined and code_data_qa_refined.files)
- code_update_msg = "*Minor, non-functional code polish may have been applied based on QA feedback.*" if code_files_exist else "*QA report refined (code unchanged).*"
- display_text=f"**Refined Quality Analysis Report:**\n\n{report}\n\n{code_update_msg}\n\n*Please review the final QA report. Choose 'Refine Further', 'Approve & Proceed', or 'Regenerate Code' below.*";
- next_display_stage = "collect_quality_decision"
-
- elif func_name == "generate_initial_deployment": # Handle lambda name
- plan = updated_state.get('deployment_current_process', '*N/A*')
- # Retrieve prefs used from state if stored, otherwise use placeholder
- prefs_used = st.session_state.get('current_prefs', '[Preferences used previously, not displayed]')
- display_text = f"**Initial Deployment Plan Generated:**\n*Based on Preferences:*\n```\n{prefs_used}\n```\n*Generated Plan:*\n```markdown\n{plan}\n```\n\n*Generating AI feedback on this deployment plan...*";
-
- elif func == SDLC.generate_deployment_feedback:
- current_plan = updated_state.get('deployment_current_process', '*N/A*')
- ai_feedback = updated_state.get('deployment_feedback', '*N/A*')
- display_text=f"**Current Deployment Plan:**\n```markdown\n{current_plan}\n```\n---\n**AI Feedback on Plan:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or required changes for the deployment plan below.*";
- next_display_stage = "collect_deployment_human_feedback"
-
- elif func == SDLC.refine_deployment:
- plan = updated_state.get('deployment_current_process', '*N/A*')
- display_text = f"**Refined Deployment Plan:**\n```markdown\n{plan}\n```\n\n*Please review the refined deployment plan. Choose 'Refine Further' or 'Approve & Proceed' below.*";
- next_display_stage = "collect_deployment_decision"
-
- # Display logic for save functions
- elif func in [SDLC.save_final_user_story, SDLC.save_final_product_review, SDLC.save_final_design_doc, SDLC.save_final_uml_diagrams, SDLC.save_review_security_outputs, SDLC.save_testing_outputs, SDLC.save_final_quality_analysis, SDLC.save_final_deployment_plan]:
- # Determine artifact name from function name
- artifact_name = func.__name__.replace('save_final_','').replace('_',' ').title()
- # Determine next major action/cycle name
- next_action_stage = next_display_stage # The stage name provided to run_workflow_step
- next_action_cycle = STAGE_TO_CYCLE.get(next_action_stage, next_action_stage).replace('_',' ').title()
- # Special case names for clarity
- if next_action_stage == "generate_initial_deployment":
- next_action_name = "Deployment Preferences Input"
- elif next_action_stage == "END":
- next_action_name = "Workflow End"
- else:
- next_action_name = f"{next_action_cycle} Cycle"
-
- display_text = f"✅ **{artifact_name} saved successfully.**\n\n*Proceeding to: {next_action_name}...*"
- logger.info(f"Artifact saved: {artifact_name}. Next step starts stage: {next_action_stage}")
-
- # --- Update UI Display and Transition Stage ---
- update_display(display_text)
- st.session_state.stage = next_display_stage
- logger.info(f"Completed step '{func_name}'. UI transitioning to stage '{next_display_stage}'.")
- st.rerun() # Rerun Streamlit to reflect the changes
-
- # --- Error Handling ---
- except ConnectionError as ce:
- error_msg = f"Connection Error during step '{func_name}': {ce}. Please check your API keys, network connection, and service status."
- st.error(error_msg)
- logger.critical(error_msg, exc_info=False) # Log as critical, but maybe don't need full traceback always
- # Optionally add a retry button here specific to connection errors if desired
- except pydantic_core.ValidationError as pve:
- # Handle Pydantic errors (often from LLM structured output) gracefully
- error_details = str(pve)
- logger.error(f"Data Validation Error in step '{func_name}': {error_details}", exc_info=True)
- # Check if it's the specific error related to the default GeneratedCode
- if "GeneratedCode" in error_details and "instructions" in error_details and "Field required" in error_details:
- error_msg = f"Internal Application Error: Failed processing a code object during step '{func_name}', likely due to a missing default value in the application code. Please report this issue. Details: {error_details}"
- st.error(error_msg)
- # Halt here as it's an app logic issue needing a fix in app.py
- st.stop()
- else:
- # General Pydantic error
- error_msg = f"Data Validation Error during step '{func_name}': The AI's response did not match the expected format. Details: {error_details}"
- st.error(error_msg)
- # Offer retry for general validation errors
- retry_key_pve = f"retry_btn_pve_{func_name}_{int(time.time())}"
- if st.button("Retry Last Step", key=retry_key_pve):
- logger.info(f"User initiated retry after Pydantic error in {func_name}.")
- st.rerun()
- except TypeError as te:
- # TypeErrors often indicate programming errors (e.g., wrong argument types)
- error_msg = f"Type Error during step '{func_name}': {te}. This might indicate an internal application issue."
- st.error(error_msg)
- logger.error(f"TypeError executing step '{func_name}': {te}", exc_info=True)
- st.stop() # Halt on TypeErrors as they usually require code fixes
- except ValueError as ve:
- # ValueErrors can be raised by backend logic for specific input issues
- error_msg = f"Input Error during step '{func_name}': {ve}. Please check the inputs or previous steps."
- st.error(error_msg)
- logger.error(f"ValueError executing step '{func_name}': {ve}", exc_info=True)
- # Offer retry for ValueErrors as they might be transient or fixable by adjusting input
- retry_key_ve = f"retry_btn_ve_{func_name}_{int(time.time())}"
- if st.button("Retry Last Step", key=retry_key_ve):
- logger.info(f"User initiated retry after ValueError in {func_name}.")
- st.rerun()
- except Exception as e:
- # Catch-all for other unexpected errors
- error_msg = f"An unexpected error occurred during step '{func_name}': {e}"
- st.error(error_msg)
- logger.error(f"Unexpected error executing step '{func_name}': {e}", exc_info=True)
- # Offer retry for general exceptions
- retry_key_exc = f"retry_btn_exc_{func_name}_{int(time.time())}" # Ensure unique key
- if st.button("Retry Last Step", key=retry_key_exc):
- logger.info(f"User initiated retry after general exception in {func_name}.")
- st.rerun()
-
-
-# ==============================================================================
-# --- Workflow Map Definition ---
-# Maps "run_*" stages to their backend function and the next UI stage
-# ==============================================================================
-workflow_map = {
- # Requirements Cycle
- "run_generate_questions": (SDLC.generate_questions, "collect_answers"),
- "run_refine_prompt": (SDLC.refine_prompt, "run_generate_initial_user_stories"), # End of Requirements
- # User Story Cycle
- "run_generate_initial_user_stories": (SDLC.generate_initial_user_stories, "run_generate_user_story_feedback"),
- "run_generate_user_story_feedback": (SDLC.generate_user_story_feedback, "collect_user_story_human_feedback"),
- "run_refine_user_stories": (SDLC.refine_user_stories, "collect_user_story_decision"),
- # Product Review Cycle
- "run_generate_initial_product_review": (SDLC.generate_initial_product_review, "run_generate_product_review_feedback"),
- "run_generate_product_review_feedback": (SDLC.generate_product_review_feedback, "collect_product_review_human_feedback"),
- "run_refine_product_review": (SDLC.refine_product_review, "collect_product_review_decision"),
- # Design Cycle
- "run_generate_initial_design_doc": (SDLC.generate_initial_design_doc, "run_generate_design_doc_feedback"),
- "run_generate_design_doc_feedback": (SDLC.generate_design_doc_feedback, "collect_design_doc_human_feedback"),
- "run_refine_design_doc": (SDLC.refine_design_doc, "collect_design_doc_decision"),
- # UML Cycle
- "run_select_uml_diagrams": (SDLC.select_uml_diagrams, "run_generate_initial_uml_codes"),
- "run_generate_initial_uml_codes": (SDLC.generate_initial_uml_codes, "run_generate_uml_feedback"),
- "run_generate_uml_feedback": (SDLC.generate_uml_feedback, "collect_uml_human_feedback"),
- "run_refine_uml_codes": (SDLC.refine_uml_codes, "collect_uml_decision"),
- # Code Generation Cycle
- "run_generate_initial_code": (SDLC.generate_initial_code, "collect_code_human_input"),
- "run_web_search_code": (SDLC.web_search_code, "run_generate_code_feedback"), # Handled specially in run_workflow_step if skipped
- "run_generate_code_feedback": (SDLC.generate_code_feedback, "collect_code_human_feedback"),
- "run_refine_code": (SDLC.refine_code, "collect_code_decision"),
- # Review & Security Cycle
- "run_code_review": (SDLC.code_review, "run_security_check"), # Special handling: runs review then triggers security check
- "run_security_check": (SDLC.security_check, "merge_review_security_feedback"), # Displays both reports, waits for feedback
- "run_refine_code_with_reviews": (SDLC.refine_code_with_reviews, "collect_review_security_decision"),
- # Testing Cycle
- "run_generate_initial_test_cases": (SDLC.generate_initial_test_cases, "run_generate_test_cases_feedback"),
- "run_generate_test_cases_feedback": (SDLC.generate_test_cases_feedback, "collect_test_cases_human_feedback"),
- "run_refine_test_cases_and_code": (SDLC.refine_test_cases_and_code, "collect_test_cases_human_feedback"), # Loop back to test execution
- "run_save_testing_outputs": (SDLC.save_testing_outputs, "run_generate_initial_quality_analysis"), # End of Testing
- # Quality Analysis Cycle
- "run_generate_initial_quality_analysis": (SDLC.generate_initial_quality_analysis, "run_generate_quality_feedback"),
- "run_generate_quality_feedback": (SDLC.generate_quality_feedback, "collect_quality_human_feedback"),
- "run_refine_quality_and_code": (SDLC.refine_quality_and_code, "collect_quality_decision"),
- # Deployment Cycle
- "run_generate_initial_deployment": (
- lambda state: SDLC.generate_initial_deployment(state, st.session_state.get('current_prefs', '')), # Pass prefs via lambda
- "run_generate_deployment_feedback"
- ),
- "run_generate_deployment_feedback": (SDLC.generate_deployment_feedback, "collect_deployment_human_feedback"),
- "run_refine_deployment": (SDLC.refine_deployment, "collect_deployment_decision"),
- }
-
-# ==============================================================================
-# --- Main Execution Logic ---
-# Checks the current stage and runs the corresponding backend function if it's a "run_" stage.
-# ==============================================================================
-if st.session_state.get('config_applied', False):
- current_stage_to_run = st.session_state.stage # Get the current stage
-
- # Check if the stage indicates a background processing step
- if current_stage_to_run.startswith("run_"):
- if current_stage_to_run in workflow_map:
- # Retrieve the function and the next UI stage from the map
- func_to_execute, next_ui_stage = workflow_map[current_stage_to_run]
- # Call the central execution function
- run_workflow_step(func_to_execute, next_ui_stage)
- else:
- # This indicates a potential error in the workflow definition or state
- st.error(f"Internal Error: Unknown processing stage '{current_stage_to_run}' encountered. Workflow cannot proceed. Please restart.")
- logger.critical(f"Workflow halted at unknown 'run_' stage: {current_stage_to_run}. Check workflow_map definition.")
- # Optionally force a reset or stop execution
- # initialize_state()
- # st.rerun()
- st.stop()
- # elif current_stage_to_run == "END":
- # Handled within the main column display logic
- # pass # No processing needed for END stage
- # else:
- # Stage is likely an input/decision stage, handled by the UI widgets above
- # pass
-
-# Display warning if configuration hasn't been applied, unless at the very start
-elif st.session_state.stage != "initial_setup":
- logger.warning("Workflow cannot proceed because configuration has not been applied.")
+# app.py
+"""
+Streamlit frontend application for orchestrating an AI-driven SDLC workflow.
+
+This application manages the user interface, state transitions, and calls
+backend logic functions defined in SDLC.py to generate project artifacts.
+Includes cycle-based chat history display.
+"""
+
+# --- Standard Library Imports ---
+import streamlit as st
+import os
+import shutil
+import logging
+from datetime import datetime
+import time
+import zipfile # Standard library zipfile
+
+# --- Third-party Imports ---
+import pydantic_core # For specific error checking
+
+# --- Import core logic from SDLC.py ---
+try:
+ import SDLC
+ from SDLC import (
+ # State and Models
+ MainState, GeneratedCode, PlantUMLCode, TestCase, CodeFile, TestCases,
+ # Initialization function
+ initialize_llm_clients,
+ # Workflow Functions (Import all necessary functions)
+ generate_questions, refine_prompt,
+ generate_initial_user_stories, generate_user_story_feedback, refine_user_stories, save_final_user_story,
+ generate_initial_product_review, generate_product_review_feedback, refine_product_review, save_final_product_review,
+ generate_initial_design_doc, generate_design_doc_feedback, refine_design_doc, save_final_design_doc,
+ select_uml_diagrams, generate_initial_uml_codes, generate_uml_feedback, refine_uml_codes, save_final_uml_diagrams,
+ generate_initial_code, web_search_code, generate_code_feedback, refine_code,
+ code_review, security_check, refine_code_with_reviews, save_review_security_outputs,
+ generate_initial_test_cases, generate_test_cases_feedback, refine_test_cases_and_code, save_testing_outputs,
+ generate_initial_quality_analysis, generate_quality_feedback, refine_quality_and_code, save_final_quality_analysis,
+ generate_initial_deployment, generate_deployment_feedback, refine_deployment, save_final_deployment_plan,
+ # Message Types
+ HumanMessage, AIMessage
+ )
+ logging.info("Successfully imported components from SDLC.py.")
+except ImportError as e:
+ st.error(f"Import Error: {e}. Critical file 'SDLC.py' not found or contains errors.")
+ logging.critical(f"Failed to import SDLC.py: {e}", exc_info=True)
+ st.stop()
+except Exception as e:
+ st.error(f"An unexpected error occurred during import from SDLC: {e}")
+ logging.critical(f"Unexpected error during import from SDLC: {e}", exc_info=True)
+ st.stop()
+
+# --- Application Setup ---
+st.set_page_config(layout="wide", page_title="AI SDLC Workflow")
+logger = logging.getLogger(__name__)
+# Ensure logger is configured
+if not logger.handlers:
+ logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+ logger.info("Streamlit app logger configured.")
+
+# --- Constants for Configuration ---
+# Define available providers and their models
+AVAILABLE_MODELS = {
+ "Google": [
+ "gemini-2.0-flash", "gemini-1.5-pro-latest", "gemini-1.5-flash-latest",
+ "gemini-1.0-pro", "gemini-1.0-flash", "gemini-2.5-pro-exp-03-25",
+ ],
+ "OpenAI": [
+ "gpt-4o-mini", "gpt-4o-mini-2024-07-18",
+ "gpt-4o", "gpt-4o-2024-08-06",
+ "o1-mini", "o1-mini-2024-09-12",
+ "o3-mini", "o3-mini-2025-01-31",
+ ],
+ "Groq": [
+ "llama3-8b-8192", "llama3-70b-8192", "llama-3.1-8b-instant",
+ "llama-3.2-1b-preview", "llama-3.2-3b-preview", "llama-3.3-70b-specdec",
+ "llama-3.3-70b-versatile", "mistral-saba-24b", "gemma2-9b-it",
+ "deepseek-r1-distill-llama-70b", "deepseek-r1-distill-qwen-32b",
+ "qwen-2.5-32b", "qwen-2.5-coder-32b", "qwen-qwq-32b",
+ "mixtral-8x7b-32768",
+ ],
+
+ "Anthropic": [
+ "claude-3-opus-20240229",
+ "claude-3-sonnet-20240229",
+ "claude-3-haiku-20240307",
+ "claude-3-5-haiku-latest",
+ "claude-3-5-sonnet-latest",
+ "claude-3-7-sonnet-latest"
+ ],
+ "xAI": [
+ "grok-1",
+ "grok-2-latest",
+ "grok-3",
+ "grok-3-mini"
+ ]
+}
+LLM_PROVIDERS = list(AVAILABLE_MODELS.keys())
+
+# --- Define Cycle Order and Stage-to-Cycle Mapping ---
+CYCLE_ORDER = [
+ "Requirements", "User Story", "Product Review", "Design", "UML",
+ "Code Generation", "Review & Security", "Testing", "Quality Analysis", "Deployment"
+]
+STAGE_TO_CYCLE = {
+ "initial_setup": "Requirements",
+ "run_generate_questions": "Requirements",
+ "collect_answers": "Requirements",
+ "run_refine_prompt": "Requirements",
+ "run_generate_initial_user_stories": "User Story",
+ "run_generate_user_story_feedback": "User Story",
+ "collect_user_story_human_feedback": "User Story",
+ "run_refine_user_stories": "User Story",
+ "collect_user_story_decision": "User Story",
+ "run_generate_initial_product_review": "Product Review",
+ "run_generate_product_review_feedback": "Product Review",
+ "collect_product_review_human_feedback": "Product Review",
+ "run_refine_product_review": "Product Review",
+ "collect_product_review_decision": "Product Review",
+ "run_generate_initial_design_doc": "Design",
+ "run_generate_design_doc_feedback": "Design",
+ "collect_design_doc_human_feedback": "Design",
+ "run_refine_design_doc": "Design",
+ "collect_design_doc_decision": "Design",
+ "run_select_uml_diagrams": "UML",
+ "run_generate_initial_uml_codes": "UML",
+ "run_generate_uml_feedback": "UML",
+ "collect_uml_human_feedback": "UML",
+ "run_refine_uml_codes": "UML",
+ "collect_uml_decision": "UML",
+ "run_generate_initial_code": "Code Generation",
+ "collect_code_human_input": "Code Generation",
+ "run_web_search_code": "Code Generation",
+ "run_generate_code_feedback": "Code Generation",
+ "collect_code_human_feedback": "Code Generation",
+ "run_refine_code": "Code Generation",
+ "collect_code_decision": "Code Generation",
+ "run_code_review": "Review & Security",
+ "run_security_check": "Review & Security",
+ "merge_review_security_feedback": "Review & Security", # Stage name from prompt
+ "collect_review_security_human_feedback": "Review & Security", # Hypothetical, check if needed
+ "run_refine_code_with_reviews": "Review & Security",
+ "collect_review_security_decision": "Review & Security",
+ "run_generate_initial_test_cases": "Testing",
+ "run_generate_test_cases_feedback": "Testing",
+ "collect_test_cases_human_feedback": "Testing",
+ "run_refine_test_cases_and_code": "Testing",
+ "run_save_testing_outputs": "Testing",
+ "run_generate_initial_quality_analysis": "Quality Analysis",
+ "run_generate_quality_feedback": "Quality Analysis",
+ "collect_quality_human_feedback": "Quality Analysis",
+ "run_refine_quality_and_code": "Quality Analysis",
+ "collect_quality_decision": "Quality Analysis",
+ "generate_initial_deployment": "Deployment", # Stage for form display
+ "run_generate_initial_deployment": "Deployment", # Stage for processing
+ "run_generate_deployment_feedback": "Deployment",
+ "collect_deployment_human_feedback": "Deployment",
+ "run_refine_deployment": "Deployment",
+ "collect_deployment_decision": "Deployment",
+ "END": "END" # Final stage marker
+}
+
+# --- Helper Functions ---
+
+def initialize_state():
+ """Initializes or resets the Streamlit session state."""
+ timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+ default_project_folder = f"ai_sdlc_project_{timestamp}"
+
+ # --- Existing Clear and Basic Init ---
+ st.session_state.clear() # Clear all session state keys
+ st.session_state.stage = "initial_setup"
+ st.session_state.workflow_state = {} # Master state dictionary
+ st.session_state.user_input = "" # Temporary storage for text area
+ st.session_state.display_content = "Welcome! Please configure API keys and project details to start." # Main display area content
+ st.session_state.project_folder_base = default_project_folder # Base folder name default
+ st.session_state.current_prefs = "" # For deployment preferences
+ # ZIP file paths for download buttons
+ st.session_state.zip_path = None # Full project zip
+ st.session_state.review_code_zip_path = None
+ st.session_state.testing_code_zip_path = None
+ st.session_state.final_code_zip_path = None
+ # Configuration state
+ st.session_state.config_applied = False
+ st.session_state.selected_provider = LLM_PROVIDERS[0]
+ st.session_state.selected_model = AVAILABLE_MODELS[LLM_PROVIDERS[0]][0]
+ st.session_state.llm_api_key = ""
+ st.session_state.tavily_api_key = ""
+ st.session_state.llm_instance = None
+ st.session_state.tavily_instance = None
+ # Chat history state for current cycle display
+ st.session_state.current_cycle_messages = [] # List to hold messages for display in the current cycle
+ st.session_state.previous_major_cycle = None # Track the previous cycle to detect changes
+
+ # --- >>> ADDED: Initialize Form Default Keys Directly Here <<< ---
+ # This ensures the keys exist when the initial setup form is rendered.
+ st.session_state.proj_name_default = "Multi-feature Web Application Example\n- User Authentication\n- Task Management\n- Reporting"
+ st.session_state.proj_cat_default = "Web Development\n- Full Stack"
+ st.session_state.proj_subcat_default = "Productivity Tool\n- Internal Business Application"
+ st.session_state.proj_lang_default = "Python (Flask Backend)\nJavaScript (React Frontend)\nDocker"
+ st.session_state.min_iter_default = 2
+ # --- >>> END ADDED BLOCK <<< ---
+
+ # --- Existing Initialization for MD/PDF Paths ---
+ st.session_state.refined_prompt_path = None
+ st.session_state.refined_prompt_pdf_path = None
+ st.session_state.final_user_story_path = None
+ st.session_state.final_user_story_pdf_path = None
+ st.session_state.final_product_review_path = None
+ st.session_state.final_product_review_pdf_path = None
+ st.session_state.final_design_document_path = None
+ st.session_state.final_design_document_pdf_path = None
+ st.session_state.final_quality_analysis_path = None
+ st.session_state.final_quality_analysis_pdf_path = None
+ st.session_state.final_deployment_path = None
+ st.session_state.final_deployment_pdf_path = None
+ # --- END ADDED --- # This comment was slightly misplaced, path init is correct
+
+ # --- Existing Initialization for Snapshot Paths ---
+ st.session_state.snapshot_path_codegen_initial = None
+ st.session_state.snapshot_path_codegen_refined = None
+ st.session_state.snapshot_path_review_refined = None
+ st.session_state.snapshot_path_testing_refined = None
+ st.session_state.snapshot_path_qa_polished = None
+ # Keep final folder paths (might point to last snapshot or dedicated folder)
+ st.session_state.review_code_snapshot_folder = None # Points to post_review snapshot
+ st.session_state.testing_passed_code_folder = None # Points to snapshot saved by save_testing_outputs
+ st.session_state.final_code_folder = None # Points to post_qa snapshot
+ # --- END ADDED/MODIFIED --- # This comment was slightly misplaced, path init is correct
+
+ logger.info("Streamlit session state initialized/reset including form defaults, PDF, and Snapshot paths.") # Keep the original log message or update if desired
+
+
+def update_display(new_content: str):
+ """Updates the main display area content in the session state."""
+ st.session_state.display_content = new_content
+ logger.debug("Main display content updated.")
+
+def create_download_button(file_path: str, label: str, mime: str, key_suffix: str, help_text: str = ""):
+ """Creates a download button for a given file path if it exists and is valid."""
+ if not file_path or not isinstance(file_path, str):
+ # logger.debug(f"Download button skipped for '{label}': Invalid path ({file_path}).")
+ return # Skip if path is invalid
+
+ abs_file_path = os.path.abspath(file_path)
+ if os.path.exists(abs_file_path) and os.path.isfile(abs_file_path):
+ try:
+ with open(abs_file_path, "rb") as fp:
+ # Sanitize label for key generation, keep it simple
+ safe_label_part = "".join(c for c in label if c.isalnum() or c in ['_']).lower()[:15]
+ button_key = f"dl_btn_{key_suffix}_{safe_label_part}" # Unique key per button
+ st.download_button(
+ label=f"Download {label}",
+ data=fp,
+ file_name=os.path.basename(abs_file_path),
+ mime=mime,
+ key=button_key,
+ help=help_text or f"Download the {label} file."
+ )
+ except FileNotFoundError:
+ # This shouldn't happen if os.path.exists passed, but handle defensively
+ logger.warning(f"File disappeared before download button creation: {abs_file_path}")
+ except Exception as e:
+ logger.error(f"Error preparing download button for '{abs_file_path}': {e}", exc_info=True)
+ # Show a less intrusive warning in the UI
+ st.warning(f"Could not create download for {label}. Error: {e}", icon="⚠️")
+ # else: logger.debug(f"Download button skipped for '{label}': File not found or not a file ({abs_file_path}).")
+
+
+def create_zip_and_download_button(folder_path_key: str, zip_path_key: str, zip_basename: str, button_label_prefix: str, sidebar_context):
+ """
+ Creates a button to generate a ZIP archive of a specified folder
+ and provides a download button for the generated ZIP file.
+
+ Args:
+ folder_path_key: Key in workflow_state holding the path to the folder to zip.
+ zip_path_key: Key in session_state where the path to the created zip file will be stored.
+ zip_basename: The base name for the output zip file (without .zip).
+ button_label_prefix: Prefix for the button labels (e.g., "Review Stage Code").
+ sidebar_context: The Streamlit container (e.g., st.sidebar) where buttons are placed.
+ """
+ folder_path = st.session_state.workflow_state.get(folder_path_key)
+ abs_folder_path = os.path.abspath(folder_path) if folder_path and isinstance(folder_path, str) else None
+
+ if abs_folder_path and os.path.exists(abs_folder_path) and os.path.isdir(abs_folder_path):
+ # --- Button to Generate ZIP ---
+ zip_label = f"Generate & Download {button_label_prefix} ZIP"
+ existing_zip = st.session_state.get(zip_path_key)
+ if existing_zip and os.path.exists(existing_zip):
+ zip_label = f"Download {button_label_prefix} ZIP" # Change label if ZIP exists
+
+ # Use a descriptive and unique key for the generation button
+ zip_gen_key = f"zip_gen_btn_{zip_path_key}"
+ if sidebar_context.button(zip_label, key=zip_gen_key, help=f"Package the {button_label_prefix} folder into a downloadable ZIP file."):
+ with st.spinner(f"Creating {button_label_prefix} archive..."):
+ try:
+ # Define output directory (same level as project folder) and base name
+ out_dir = os.path.dirname(abs_folder_path) # Place zip next to the folder being zipped
+ archive_base = os.path.join(out_dir, zip_basename) # e.g., ../ai_sdlc_project_xxx/code_snapshot_review
+
+ # Define the root directory and the directory to archive relative to the root
+ root_dir = os.path.dirname(abs_folder_path) # The parent directory of the folder to zip
+ base_dir = os.path.basename(abs_folder_path) # The name of the folder to zip
+
+ logger.info(f"Zipping: base_name='{archive_base}', format='zip', root_dir='{root_dir}', base_dir='{base_dir}'")
+
+ # Construct the expected output zip file path
+ zip_file_path = archive_base + ".zip"
+
+ # Remove old zip file if it exists to avoid conflicts
+ if os.path.exists(zip_file_path):
+ try:
+ os.remove(zip_file_path)
+ logger.info(f"Removed existing ZIP: {zip_file_path}")
+ except Exception as del_e:
+ logger.warning(f"Could not remove existing ZIP {zip_file_path}: {del_e}")
+
+ # Create the archive
+ archive_path = shutil.make_archive(
+ base_name=archive_base,
+ format='zip',
+ root_dir=root_dir,
+ base_dir=base_dir
+ )
+
+ # Verify the archive was created
+ if not os.path.exists(archive_path):
+ raise OSError(f"ZIP archive creation failed: File not found at {archive_path}")
+
+ # Store the path to the created zip file in session state
+ st.session_state[zip_path_key] = archive_path
+ st.success(f"{button_label_prefix} ZIP created successfully!")
+ logger.info(f"Successfully created ZIP archive: {archive_path}")
+ st.rerun() # Rerun to update the UI and show the download button
+
+ except Exception as e:
+ sidebar_context.error(f"ZIP Creation Error: {e}")
+ logger.error(f"ZIP creation failed for folder '{abs_folder_path}': {e}", exc_info=True)
+
+ # --- Download Button for Existing ZIP ---
+ generated_zip = st.session_state.get(zip_path_key)
+ if generated_zip and os.path.exists(generated_zip):
+ try:
+ with open(generated_zip, "rb") as fp:
+ # Use a descriptive and unique key for the download button
+ safe_prefix = "".join(c for c in button_label_prefix if c.isalnum()).lower()[:10]
+ dl_key = f"dl_zip_btn_{zip_path_key}_{safe_prefix}"
+ sidebar_context.download_button(
+ label=f"Download {button_label_prefix} ZIP",
+ data=fp,
+ file_name=os.path.basename(generated_zip),
+ mime="application/zip",
+ key=dl_key,
+ help=f"Download the generated {button_label_prefix} ZIP archive."
+ )
+ except Exception as e:
+ sidebar_context.warning(f"Error reading ZIP file for download: {e}")
+ logger.error(f"Error reading ZIP file {generated_zip} for download: {e}", exc_info=True)
+ # else: logger.debug(f"ZIP button skipped for '{button_label_prefix}': Folder path invalid or not found ({folder_path}).")
+
+# --- Initialize State if First Run ---
+if 'stage' not in st.session_state:
+ initialize_state()
+
+# --- Sidebar UI ---
+with st.sidebar:
+ st.header("AI SDLC Orchestrator")
+ st.caption("Automated workflow from requirements to deployment.")
+ st.divider()
+
+ # --- Configuration Expander ---
+ with st.expander("Configuration", expanded=not st.session_state.get('config_applied', False)):
+ st.subheader("LLM & API Keys")
+
+ # LLM Provider Selection
+ selected_provider = st.selectbox(
+ "Select LLM Provider",
+ options=LLM_PROVIDERS,
+ key="selected_provider", # Keep existing key for state consistency
+ index=LLM_PROVIDERS.index(st.session_state.selected_provider) if st.session_state.selected_provider in LLM_PROVIDERS else 0,
+ help="Choose the primary Large Language Model provider."
+ )
+
+ # Dynamically update available models based on provider
+ available_models = AVAILABLE_MODELS.get(selected_provider, ["N/A"])
+ current_model_selection = st.session_state.selected_model
+ model_index = available_models.index(current_model_selection) if current_model_selection in available_models else 0
+
+ selected_model = st.selectbox(
+ f"Select Model ({selected_provider})",
+ options=available_models,
+ key="selected_model", # Keep existing key
+ index=model_index,
+ help=f"Choose a specific model from {selected_provider}."
+ )
+
+ # API Key Inputs
+ llm_api_key_input = st.text_input(
+ f"{selected_provider} API Key",
+ type="password",
+ key="llm_api_key_input", # Keep existing key
+ help=f"Enter your API key for the selected {selected_provider} provider.",
+ value=st.session_state.get("llm_api_key", "") # Pre-fill if exists
+ )
+
+ tavily_api_key_input = st.text_input(
+ "Tavily API Key (Optional)",
+ type="password",
+ key="tavily_api_key_input", # Keep existing key
+ help="Enter your Tavily API key for enabling web search functionality.",
+ value=st.session_state.get("tavily_api_key", "") # Pre-fill if exists
+ )
+
+ # Apply Configuration Button
+ if st.button("Apply Configuration", key="apply_config_button"): # Changed key slightly to avoid potential conflicts if previous runs errored strangely
+ with st.spinner("Initializing LLM and Tavily clients..."):
+ # Store keys from inputs into session state
+ st.session_state.llm_api_key = llm_api_key_input
+ st.session_state.tavily_api_key = tavily_api_key_input
+
+ # Attempt to initialize clients using the backend function
+ llm_inst, tav_inst, error_msg = SDLC.initialize_llm_clients(
+ provider=st.session_state.selected_provider,
+ model_name=st.session_state.selected_model,
+ llm_api_key=st.session_state.llm_api_key,
+ tavily_api_key=st.session_state.tavily_api_key
+ )
+
+ # Update state based on initialization result
+ if llm_inst:
+ st.session_state.llm_instance = llm_inst
+ st.session_state.tavily_instance = tav_inst
+ st.session_state.config_applied = True
+ st.success("Configuration applied successfully!")
+ logger.info(f"LLM ({selected_provider}/{selected_model}) and Tavily clients configured via UI.")
+ time.sleep(1) # Brief pause for user to see success message
+ st.rerun() # Rerun to potentially collapse expander and enable main workflow
+ else:
+ st.session_state.config_applied = False
+ st.session_state.llm_instance = None
+ st.session_state.tavily_instance = None
+ error_display = f"Configuration Failed: {error_msg or 'An unknown error occurred.'}"
+ st.error(error_display)
+ logger.error(error_display)
+
+ st.divider()
+
+ # --- Downloads Section ---
+ st.header("Downloads")
+ st.caption("Access generated artifacts and code snapshots.")
+
+ # --- MODIFIED: Document Downloads (MD and PDF) ---
+ st.markdown("---")
+ st.subheader("Documents") # Combined header
+
+ # Refined Prompt (Appears after Q&A cycle is complete)
+ st.markdown("**Requirements Cycle:**") # Header for this artifact
+ create_download_button(st.session_state.workflow_state.get("refined_prompt_path"), "Refined Prompt (MD)", "text/markdown", "refined_prompt_md", help_text="The final prompt generated after Q&A.")
+ create_download_button(st.session_state.workflow_state.get("refined_prompt_pdf_path"), "Refined Prompt (PDF)", "application/pdf", "refined_prompt_pdf", help_text="PDF version of the refined prompt.")
+ st.markdown("---") # Separator
+
+ # User Story
+ st.markdown("**User Story Cycle:**")
+ create_download_button(st.session_state.workflow_state.get("final_user_story_path"), "User Story (MD)", "text/markdown", "final_us_md")
+ create_download_button(st.session_state.workflow_state.get("final_user_story_pdf_path"), "User Story (PDF)", "application/pdf", "final_us_pdf")
+ st.markdown("---")
+
+ # Product Review
+ st.markdown("**Product Review Cycle:**")
+ create_download_button(st.session_state.workflow_state.get("final_product_review_path"), "Product Review (MD)", "text/markdown", "final_pr_md")
+ create_download_button(st.session_state.workflow_state.get("final_product_review_pdf_path"), "Product Review (PDF)", "application/pdf", "final_pr_pdf")
+ st.markdown("---")
+
+ # Design Document
+ st.markdown("**Design Cycle:**")
+ create_download_button(st.session_state.workflow_state.get("final_design_document_path"), "Design Document (MD)", "text/markdown", "final_dd_md")
+ create_download_button(st.session_state.workflow_state.get("final_design_document_pdf_path"), "Design Document (PDF)", "application/pdf", "final_dd_pdf")
+ st.markdown("---")
+
+ # QA Report
+ st.markdown("**Quality Analysis Cycle:**")
+ create_download_button(st.session_state.workflow_state.get("final_quality_analysis_path"), "QA Report (MD)", "text/markdown", "final_qa_md")
+ create_download_button(st.session_state.workflow_state.get("final_quality_analysis_pdf_path"), "QA Report (PDF)", "application/pdf", "final_qa_pdf")
+ st.markdown("---")
+
+ # Deployment Plan
+ st.markdown("**Deployment Cycle:**")
+ create_download_button(st.session_state.workflow_state.get("final_deployment_path"), "Deployment Plan (MD)", "text/markdown", "final_deploy_md")
+ create_download_button(st.session_state.workflow_state.get("final_deployment_pdf_path"), "Deployment Plan (PDF)", "application/pdf", "final_deploy_pdf")
+ # --- END MODIFIED Document Downloads ---
+
+ # UML Diagram Downloads
+ st.markdown("---")
+ st.subheader("UML Diagrams")
+ uml_png_paths = st.session_state.workflow_state.get("final_uml_png_paths", [])
+ uml_folder = st.session_state.workflow_state.get("final_uml_diagram_folder")
+
+ if uml_png_paths:
+ st.caption("Download generated PNG images:")
+ # Create download buttons for each generated PNG
+ for i, png_path in enumerate(uml_png_paths):
+ # Attempt to create a meaningful label from the filename
+ try:
+ base_name = os.path.basename(png_path)
+ # Assumes format like 'diagram_01_class_diagram.png'
+ label_parts = base_name.split('_')[2:] # Get parts after 'diagram_xx_'
+ label = ' '.join(label_parts).replace('.png', '').replace('_', ' ').title()
+ if not label: label = f"Diagram {i+1}" # Fallback label
+ except Exception:
+ label = f"Diagram {i+1}" # Generic fallback
+
+ create_download_button(png_path, f"UML: {label}", "image/png", f"uml_png_{i}")
+ elif uml_folder and os.path.exists(uml_folder):
+ # Indicates UML stage ran but PNGs weren't generated or found
+ st.caption("*No PNG diagrams available for download (check PlantUML setup/server). Puml files might be available in the full project ZIP.*")
+ else:
+ # Indicates UML stage hasn't run or failed before saving
+ st.caption("*UML diagrams have not been generated yet.*")
+
+ # --- MODIFIED: Code Snapshot Downloads (ZIP) ---
+ st.markdown("---")
+ st.subheader("Code Snapshots (ZIP)")
+ st.caption("Download code versions from various stages.")
+
+ # Code Generation Cycle Snapshots
+ st.markdown("**Code Generation Cycle:**")
+ create_zip_and_download_button(
+ folder_path_key="snapshot_path_codegen_initial", # Use the new state key
+ zip_path_key="zip_path_cg_initial", # Unique key for session state zip path
+ zip_basename="snapshot_codegen_initial",
+ button_label_prefix="Initial Code",
+ sidebar_context=st.sidebar
+ )
+ create_zip_and_download_button(
+ folder_path_key="snapshot_path_codegen_refined", # Use the new state key
+ zip_path_key="zip_path_cg_refined", # Unique key
+ zip_basename="snapshot_codegen_refined",
+ button_label_prefix="Refined Code (Latest)", # Label indicates latest
+ sidebar_context=st.sidebar
+ )
+ st.markdown("---")
+
+ # Review & Security Cycle Snapshot
+ st.markdown("**Review & Security Cycle:**")
+ create_zip_and_download_button(
+ folder_path_key="snapshot_path_review_refined", # Use the new state key
+ zip_path_key="zip_path_review_refined", # Unique key
+ zip_basename="snapshot_review_refined",
+ button_label_prefix="Post-Review Code",
+ sidebar_context=st.sidebar
+ )
+ st.markdown("---")
+
+ # Testing Cycle Snapshots
+ st.markdown("**Testing Cycle:**")
+ create_zip_and_download_button(
+ folder_path_key="snapshot_path_testing_refined", # Use the new state key for failed refinement
+ zip_path_key="zip_path_testing_refined", # Unique key
+ zip_basename="snapshot_testing_refined",
+ button_label_prefix="Post-Failure Refined Code (Latest)",
+ sidebar_context=st.sidebar
+ )
+ create_zip_and_download_button(
+ folder_path_key="testing_passed_code_folder", # Keep the one saved on PASS
+ zip_path_key="zip_path_testing_passed", # Unique key
+ zip_basename="snapshot_testing_passed",
+ button_label_prefix="Passed Testing Code",
+ sidebar_context=st.sidebar
+ )
+ st.markdown("---")
+
+ # Quality Analysis Cycle Snapshot (Final Code)
+ st.markdown("**Quality Analysis Cycle:**")
+ create_zip_and_download_button(
+ folder_path_key="snapshot_path_qa_polished", # Use the new state key (points to final code)
+ zip_path_key="zip_path_qa_polished", # Unique key
+ zip_basename="snapshot_qa_polished_final",
+ button_label_prefix="Final Polished Code",
+ sidebar_context=st.sidebar
+ )
+ # --- END MODIFIED Code Snapshots ---
+
+ st.divider()
+
+ # --- Full Project ZIP (only appears at the end) ---
+ if st.session_state.stage == "END":
+ st.markdown("**Full Project Archive**")
+ st.caption("Download all generated artifacts and code snapshots in a single ZIP.")
+ proj_folder = st.session_state.workflow_state.get("project_folder")
+ abs_proj = os.path.abspath(proj_folder) if proj_folder and isinstance(proj_folder, str) else None
+
+ if abs_proj and os.path.isdir(abs_proj):
+ zip_label = "Generate & Download Full Project ZIP"
+ if st.session_state.get("zip_path") and os.path.exists(st.session_state.zip_path):
+ zip_label = "Download Full Project ZIP" # Change label if already generated
+
+ if st.sidebar.button(zip_label, key="zip_gen_final_project_btn"): # Unique key
+ with st.spinner("Creating full project archive..."):
+ try:
+ # Use the project_folder_base which is set at init and guaranteed unique
+ zip_base = os.path.abspath(st.session_state.project_folder_base)
+ out_dir = os.path.dirname(zip_base) # Place zip in parent dir
+ os.makedirs(out_dir, exist_ok=True)
+
+ root_dir = os.path.dirname(abs_proj) # Parent of the project folder
+ base_dir = os.path.basename(abs_proj) # Name of the project folder
+
+ logger.info(f"Zipping full project: base_name='{zip_base}', format='zip', root_dir='{root_dir}', base_dir='{base_dir}'")
+ zip_file_path = zip_base + ".zip"
+
+ # Remove old zip if exists
+ if os.path.exists(zip_file_path):
+ try:
+ os.remove(zip_file_path)
+ logger.info(f"Removed old final project ZIP: {zip_file_path}")
+ except Exception as del_e:
+ logger.warning(f"Could not remove old final project ZIP {zip_file_path}: {del_e}")
+
+ # Create the archive
+ archive_path = shutil.make_archive(
+ base_name=zip_base,
+ format='zip',
+ root_dir=root_dir,
+ base_dir=base_dir
+ )
+
+ # Verify creation
+ if not os.path.exists(archive_path):
+ raise OSError(f"Final project ZIP creation failed: File not found at {archive_path}")
+
+ st.session_state.zip_path = archive_path # Store path
+ st.success(f"Full project ZIP created: {os.path.basename(archive_path)}")
+ st.rerun() # Update UI
+
+ except Exception as e:
+ st.sidebar.error(f"Final Project ZIP Error: {e}")
+ logger.error(f"Final project ZIP creation failed: {e}", exc_info=True)
+
+ # Provide download button if zip exists
+ if st.session_state.get("zip_path") and os.path.exists(st.session_state.zip_path):
+ try:
+ with open(st.session_state.zip_path, "rb") as fp:
+ st.sidebar.download_button(
+ label="Download Full Project ZIP",
+ data=fp,
+ file_name=os.path.basename(st.session_state.zip_path),
+ mime="application/zip",
+ key="dl_zip_final_project_btn" # Unique key
+ )
+ except Exception as read_e:
+ st.sidebar.warning(f"Error reading final project ZIP: {read_e}")
+ logger.error(f"Error reading final project ZIP {st.session_state.zip_path}: {read_e}", exc_info=True)
+ elif proj_folder:
+ st.sidebar.warning(f"Project folder '{proj_folder}' not found for final ZIP.")
+ else:
+ st.sidebar.caption("*Project folder not yet defined.*")
+
+ st.divider()
+
+ # --- Restart Button ---
+ if st.sidebar.button("Restart Workflow", key="restart_workflow_button", help="Clear all progress and configuration, then start over."):
+ # Optional: Add confirmation dialog here if desired
+ logger.info("Workflow restart requested by user.")
+ # Clean up project directory if it exists
+ proj_folder_to_delete = st.session_state.workflow_state.get("project_folder")
+ if proj_folder_to_delete and os.path.isdir(proj_folder_to_delete):
+ try:
+ shutil.rmtree(proj_folder_to_delete)
+ logger.info(f"Removed project folder on restart: {proj_folder_to_delete}")
+ except Exception as e:
+ logger.warning(f"Could not remove project folder '{proj_folder_to_delete}' on restart: {e}")
+ initialize_state()
+ st.rerun()
+
+# ==============================================================================
+# --- Main Layout Area ---
+# ==============================================================================
+
+main_col, indicator_col = st.columns([4, 1]) # Main content area, Cycle indicator sidebar
+
+# --- Cycle Change Detection and History Reset ---
+current_stage = st.session_state.stage
+current_major_cycle = STAGE_TO_CYCLE.get(current_stage, "Unknown")
+
+# Initialize previous cycle tracker if it doesn't exist
+if 'previous_major_cycle' not in st.session_state:
+ st.session_state.previous_major_cycle = current_major_cycle
+
+# Check if the cycle has changed since the last run
+if st.session_state.previous_major_cycle != current_major_cycle and current_major_cycle != "Unknown":
+ logger.info(f"Detected cycle change: '{st.session_state.previous_major_cycle}' -> '{current_major_cycle}'. Clearing current cycle message display.")
+ st.session_state.current_cycle_messages = [] # Reset the list for the new cycle
+ st.session_state.previous_major_cycle = current_major_cycle # Update the tracker
+
+# --- Main Column Content ---
+with main_col:
+ # Display current stage and cycle title
+ stage_display_name = current_stage.replace('_', ' ').title()
+ if current_stage == "END":
+ st.header("🏁 Workflow Complete")
+ else:
+ st.header(f"Cycle: {current_major_cycle} | Stage: {stage_display_name}")
+
+ # --- Chat History Display Area (Current Cycle Only) ---
+ st.markdown("### Current Cycle Interaction History")
+ # Get the messages specifically for the current cycle display
+ current_cycle_messages_list = st.session_state.get("current_cycle_messages", [])
+
+ # Use a container with fixed height for scrollable chat
+ chat_container = st.container(height=350, border=True)
+ with chat_container:
+ if not current_cycle_messages_list:
+ st.caption("No interactions recorded for this cycle yet.")
+ else:
+ # Iterate through messages stored for the current cycle display
+ for msg in current_cycle_messages_list:
+ # Determine role based on message type
+ if isinstance(msg, AIMessage):
+ role = "assistant"
+ avatar = "🤖"
+ elif isinstance(msg, HumanMessage):
+ role = "user"
+ avatar = "🧑💻"
+ else:
+ role = "system" # Or handle other types if necessary
+ avatar = "⚙️"
+
+ with st.chat_message(role, avatar=avatar):
+ # Display message content using markdown
+ # Ensure content is string; handle potential non-string data safely
+ content_display = str(msg.content) if msg.content is not None else "[No Content]"
+ st.markdown(content_display, unsafe_allow_html=False) # Security best practice
+
+ st.divider() # Visual separator
+
+ # --- Current Task / Output Display ---
+ st.markdown("### Current Task / Latest Output:")
+ display_area = st.container(border=True) # Add border for visual separation
+ with display_area:
+ # Get content safely, default to a clear message
+ display_content_md = st.session_state.get("display_content", "Awaiting next step...")
+ # Ensure it's a string before displaying
+ if not isinstance(display_content_md, str):
+ display_content_md = str(display_content_md)
+ st.markdown(display_content_md, unsafe_allow_html=False) # Disable HTML rendering
+
+ st.divider() # Visual separator
+
+ # --- Input / Decision Widgets ---
+ # Only show workflow UI elements if configuration is applied
+ if not st.session_state.get('config_applied', False):
+ if st.session_state.stage != "initial_setup": # Don't show warning during initial setup itself
+ st.warning("👈 Please apply LLM & API Key configuration in the sidebar to start the workflow.")
+ else:
+ # Determine which UI elements to show based on the current stage
+ current_stage_ui = st.session_state.stage # Use a distinct variable for clarity
+
+ input_needed_stages = {
+ "collect_answers", "collect_user_story_human_feedback",
+ "collect_product_review_human_feedback", "collect_design_doc_human_feedback",
+ "collect_uml_human_feedback", "collect_code_human_input",
+ "collect_code_human_feedback", "merge_review_security_feedback", # This stage now collects feedback
+ "collect_quality_human_feedback", "collect_deployment_human_feedback"
+ }
+ decision_needed_stages = {
+ "collect_user_story_decision", "collect_product_review_decision",
+ "collect_design_doc_decision", "collect_uml_decision", "collect_code_decision",
+ "collect_review_security_decision", "collect_quality_decision",
+ "collect_deployment_decision"
+ }
+
+ show_initial_setup_form = (current_stage_ui == "initial_setup")
+ show_deployment_prefs_form = (current_stage_ui == "generate_initial_deployment")
+ show_input_box = current_stage_ui in input_needed_stages
+ show_test_feedback_area = (current_stage_ui == "collect_test_cases_human_feedback")
+ show_decision_buttons = current_stage_ui in decision_needed_stages
+
+ # --- Initial Setup Form ---
+ if show_initial_setup_form:
+ with st.form("initial_project_setup_form"): # Descriptive key
+ st.markdown("### Project Configuration")
+ st.info("Define the initial parameters for your software project.")
+
+ # --- Project Folder (Standard Input) ---
+ proj_folder = st.text_input(
+ "Project Folder Name",
+ value=st.session_state.project_folder_base,
+ key="proj_folder_input",
+ help="Directory name for saved outputs. Use valid filesystem characters (no spaces/special chars like /\\:*?\"<>| recommended)."
+ )
+
+ # --- Project Description (Text Area with Height) ---
+ proj_name = st.text_area( # MODIFIED: Use text_area
+ "Project Description",
+ value=st.session_state.proj_name_default, # Use a potentially multi-line default
+ key="proj_name_input",
+ height=300, # MODIFIED: Set height
+ help="A detailed description of the project's purpose, features, and goals."
+ )
+
+ # --- Category (Text Area with Height) ---
+ proj_cat = st.text_area( # MODIFIED: Use text_area
+ "Category",
+ value=st.session_state.proj_cat_default, # Use a potentially multi-line default
+ key="proj_cat_input",
+ height=150, # MODIFIED: Set height
+ help="Broad category (e.g., Web Development, Data Science). Can be multi-line if needed."
+ )
+
+ # --- Subcategory (Text Area with Height) ---
+ proj_subcat = st.text_area( # MODIFIED: Use text_area
+ "Subcategory",
+ value=st.session_state.proj_subcat_default, # Use a potentially multi-line default
+ key="proj_subcat_input",
+ height=150, # MODIFIED: Set height
+ help="More specific classification (e.g., API, Full-Stack App). Can be multi-line."
+ )
+
+ # --- Coding Language (Text Area with Height) ---
+ proj_lang = st.text_area( # MODIFIED: Use text_area
+ "Coding Language(s) / Tech Stack",
+ value=st.session_state.proj_lang_default, # Use a potentially multi-line default
+ key="proj_lang_input",
+ height=150, # MODIFIED: Set height
+ help="Primary language(s) and key technologies (e.g., Python, React, Docker). Can be multi-line."
+ )
+
+ # --- Min Iterations (Standard Number Input) ---
+ min_iter = st.number_input(
+ "Min Q&A Rounds",
+ min_value=1, max_value=10, # Increased max slightly
+ value=st.session_state.min_iter_default,
+ key="min_iter_input",
+ help="Minimum required rounds of questions and answers for requirements gathering."
+ )
+
+ # --- Submit Button ---
+ submitted = st.form_submit_button("Start Workflow")
+
+ # --- Post-Submission Logic (Your existing code) ---
+ if submitted:
+ # Validation checks
+ error_messages = []
+ # Trim whitespace from inputs before validation
+ proj_folder = proj_folder.strip()
+ proj_name = proj_name.strip()
+ proj_cat = proj_cat.strip()
+ proj_subcat = proj_subcat.strip()
+ proj_lang = proj_lang.strip()
+
+ if not all([proj_folder, proj_name, proj_cat, proj_subcat, proj_lang]):
+ error_messages.append("Please fill all configuration fields.")
+ # Basic check for invalid characters, can be expanded
+ invalid_chars = ['/', '\\', ':', '*', '?', '"', '<', '>', '|']
+ if any(c in proj_folder for c in invalid_chars) or ' ' in proj_folder:
+ error_messages.append("Project Folder Name should not contain spaces or special characters like /\\:*?\"<>|.")
+
+ if error_messages:
+ for msg in error_messages: st.error(msg)
+ else:
+ try:
+ # Prepare absolute path and check filesystem status
+ abs_proj_folder = os.path.abspath(proj_folder)
+ if os.path.exists(abs_proj_folder) and not os.path.isdir(abs_proj_folder):
+ st.error(f"Error: A file (not a folder) already exists with the name '{proj_folder}'. Please choose a different name.")
+ else:
+ # Create folder if it doesn't exist, warn if it does
+ if os.path.exists(abs_proj_folder):
+ st.warning(f"Warning: Project folder '{abs_proj_folder}' already exists. Files within might be overwritten during the workflow.")
+ else:
+ os.makedirs(abs_proj_folder, exist_ok=True)
+ st.success(f"Project folder created/confirmed: '{abs_proj_folder}'")
+ logger.info(f"Project folder ready: {abs_proj_folder}")
+
+ # --- Initialize workflow_state ---
+ # Use the (potentially multi-line) inputs directly
+ initial_human_message_content = f"Initial Setup:\n- Project: {proj_name}\n- Category: {proj_cat}/{proj_subcat}\n- Language: {proj_lang}\n- Min Q&A Rounds: {min_iter}"
+ initial_human_message = SDLC.HumanMessage(content=initial_human_message_content)
+
+ # Build the initial state dictionary carefully
+ initial_workflow_state = {
+ # Core instances (must be present if config applied)
+ "llm_instance": st.session_state.llm_instance,
+ "tavily_instance": st.session_state.tavily_instance,
+ # Communication history starts with the setup message
+ "messages": [initial_human_message],
+ # Project Configuration (using validated/stripped values)
+ "project_folder": proj_folder,
+ "project": proj_name,
+ "category": proj_cat,
+ "subcategory": proj_subcat,
+ "coding_language": proj_lang,
+ # Requirements Gathering State
+ "user_input_iteration": 0,
+ "user_input_min_iterations": min_iter,
+ "user_input_questions": [],
+ "user_input_answers": [],
+ "user_input_done": False,
+ "user_query_with_qa": "", # Will be built later
+ "refined_prompt": "",
+ # Initialize cycle states (using defaults where appropriate)
+ "user_story_current": "", "user_story_feedback": "", "user_story_human_feedback": "", "user_story_done": False,
+ "product_review_current": "", "product_review_feedback": "", "product_review_human_feedback": "", "product_review_done": False,
+ "design_doc_current": "", "design_doc_feedback": "", "design_doc_human_feedback": "", "design_doc_done": False,
+ "uml_selected_diagrams": [], "uml_current_codes": [], "uml_feedback": {}, "uml_human_feedback": {}, "uml_done": False,
+ # Use a valid default GeneratedCode object with placeholder instructions meeting min_length
+ "code_current": SDLC.GeneratedCode(files=[], instructions="[Placeholder - Code not generated yet.]"),
+ "code_human_input": "", "code_web_search_results": "", "code_feedback": "", "code_human_feedback": "", "code_done": False,
+ "code_review_current_feedback": "", "security_current_feedback": "", "review_security_human_feedback": "", "review_security_done": False,
+ "test_cases_current": [], "test_cases_feedback": "", "test_cases_human_feedback": "", "test_cases_passed": False,
+ "quality_current_analysis": "", "quality_feedback": "", "quality_human_feedback": "", "quality_done": False,
+ "deployment_current_process": "", "deployment_feedback": "", "deployment_human_feedback": "", "deployment_done": False,
+ # Final artifact storage (initialize as None or empty)
+ "final_user_story": "", "final_product_review": "", "final_design_document": "",
+ "final_uml_codes": [], "final_code_files": [], "final_code_review": "",
+ "final_security_issues": "", "final_test_code_files": [], "final_quality_analysis": "",
+ "final_deployment_process": "",
+ # --- ADDED/MODIFIED: Initialize MD/PDF paths ---
+ "refined_prompt_path": None,
+ "refined_prompt_pdf_path": None,
+ "final_user_story_path": None,
+ "final_user_story_pdf_path": None,
+ "final_product_review_path": None,
+ "final_product_review_pdf_path": None,
+ "final_design_document_path": None,
+ "final_design_document_pdf_path": None,
+ "final_uml_diagram_folder": None,
+ "final_uml_png_paths": [],
+ "final_review_security_folder": None,
+ "review_code_snapshot_folder": None,
+ "final_testing_folder": None,
+ "testing_passed_code_folder": None,
+ "final_quality_analysis_path": None, # MD path
+ "final_quality_analysis_pdf_path": None, # PDF path
+ "final_code_folder": None,
+ "final_deployment_path": None, # MD path
+ "final_deployment_pdf_path": None, # PDF path
+ # --- END ADDED/MODIFIED ---
+ # Intermediate Snapshot Paths
+ "snapshot_path_codegen_initial": None,
+ "snapshot_path_codegen_refined": None,
+ "snapshot_path_review_refined": None,
+ "snapshot_path_testing_refined": None,
+ "snapshot_path_qa_polished": None,
+ }
+
+ # Update the main session state variables
+ st.session_state.workflow_state = initial_workflow_state
+ st.session_state.project_folder_base = proj_folder # Update base if user changed it
+ st.session_state.stage = "run_generate_questions" # Move to the first processing stage
+
+ # Add the initial setup message to the current cycle display list
+ st.session_state.current_cycle_messages.append(initial_human_message)
+ # Ensure previous_major_cycle is set for the first cycle
+ if st.session_state.previous_major_cycle is None:
+ st.session_state.previous_major_cycle = STAGE_TO_CYCLE.get("initial_setup", "Requirements")
+
+ logger.info(f"Initial setup complete. Starting workflow for project '{proj_name}'.")
+ st.rerun() # Rerun to start the workflow execution
+
+ except OSError as oe:
+ st.error(f"Filesystem Error creating folder '{proj_folder}': {oe}. Check permissions or choose a different name.")
+ logger.error(f"OSError during initial setup folder creation: {oe}", exc_info=True)
+ except Exception as e:
+ st.error(f"An unexpected error occurred during setup: {e}")
+ logger.error(f"Unexpected error during initial setup: {e}", exc_info=True)
+
+ # --- Deployment Preferences Form ---
+ elif show_deployment_prefs_form:
+ with st.form("deployment_preferences_form"): # Descriptive key
+ st.markdown("### Deployment Preferences")
+ st.info("Specify your desired deployment target and any relevant details.")
+
+ # Common deployment targets
+ deploy_target = st.selectbox(
+ "Target Environment",
+ options=["Localhost (using Docker)", "Docker (generic)", "AWS EC2", "AWS ECS/Fargate", "AWS Lambda", "Google Cloud Run", "Google Kubernetes Engine (GKE)", "Azure App Service", "Azure Kubernetes Service (AKS)", "Other Cloud VM", "Other Serverless", "Other Container Orchestrator"],
+ key="deploy_target_select",
+ help="Choose the primary target environment for deployment."
+ )
+
+ deploy_details = st.text_area(
+ "Additional Details / Constraints:",
+ height=100,
+ key="deploy_details_input",
+ placeholder="e.g., Specific AWS region (us-east-1), use Nginx as reverse proxy, database connection string source, required OS, any existing infrastructure to leverage.",
+ help="Provide any specific requirements, configurations, or constraints for the deployment."
+ )
+
+ submitted = st.form_submit_button("Generate Deployment Plan")
+ if submitted:
+ # Combine preferences into a string for the backend
+ prefs = f"Target Environment: {deploy_target}\nAdditional Details: {deploy_details}"
+ st.session_state.current_prefs = prefs # Store for potential use/display later
+ st.session_state.stage = "run_generate_initial_deployment" # Move to the processing stage
+ logger.info(f"Deployment preferences collected: Target='{deploy_target}'")
+
+ # Add human message for context
+ deploy_prefs_message = SDLC.HumanMessage(content=f"Deployment Preferences Set:\n{prefs}")
+ st.session_state.workflow_state["messages"].append(deploy_prefs_message)
+ st.session_state.current_cycle_messages.append(deploy_prefs_message)
+
+ st.rerun()
+
+ # --- General Input/Feedback Text Area ---
+ elif show_input_box:
+ input_label = "Your Input / Feedback:"
+ input_help = "Provide your answers or feedback here. For Q&A, type '#DONE' on a new line when finished with the current round."
+ # Customize label/help based on stage if needed
+ if current_stage_ui == "collect_answers":
+ input_label = "Your Answers:"
+ elif current_stage_ui == "collect_code_human_input":
+ input_label = "Describe Issues / Provide Input for Code:"
+ input_help = "Describe any errors encountered, unexpected behavior, or specific inputs you want the AI to test/consider."
+ elif current_stage_ui == "merge_review_security_feedback":
+ input_label = "Your Feedback on Review/Security Reports:"
+ input_help = "Provide any comments, clarifications, or priorities regarding the code review and security findings."
+
+ input_key = f"text_input_{current_stage_ui}" # Stage-specific key
+ user_val = st.text_area(
+ input_label,
+ height=150,
+ key=input_key,
+ value=st.session_state.get('user_input', ''), # Use temporary storage if needed for complex edits
+ help=input_help
+ )
+
+ submit_key = f"submit_button_{current_stage_ui}" # Stage-specific key
+ if st.button("Submit", key=submit_key):
+ user_text = user_val.strip()
+ # Basic validation: Ensure input is not empty
+ if not user_text:
+ st.warning("Please enter some input before submitting.")
+ else:
+ state = st.session_state.workflow_state
+ # Validate state type
+ if not isinstance(state, dict):
+ st.error("Workflow state is invalid. Restarting.")
+ logger.critical("Workflow state became invalid (not a dict). Forcing restart.")
+ initialize_state()
+ st.rerun()
+ st.stop()
+
+ try:
+ next_stage = None # Initialize next stage
+ # Ensure message list exists in state
+ if 'messages' not in state or not isinstance(state['messages'], list):
+ state['messages'] = []
+
+ # Create the HumanMessage object
+ human_message = SDLC.HumanMessage(content=user_text)
+ # Add to master list
+ state["messages"].append(human_message)
+ # Add to current cycle display list
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.append(human_message)
+
+ # --- Map current stage to state key, next run stage, and input type ---
+ # Tuple format: (state_key_to_update, next_processing_stage, needs_list_append)
+ map_logic = {
+ "collect_answers": ("user_input_answers", "run_generate_questions", True),
+ "collect_user_story_human_feedback": ("user_story_human_feedback", "run_refine_user_stories", False),
+ "collect_product_review_human_feedback": ("product_review_human_feedback", "run_refine_product_review", False),
+ "collect_design_doc_human_feedback": ("design_doc_human_feedback", "run_refine_design_doc", False),
+ "collect_uml_human_feedback": ("uml_human_feedback", "run_refine_uml_codes", False), # Special dict handling below
+ "collect_code_human_input": ("code_human_input", "run_web_search_code", False),
+ "collect_code_human_feedback": ("code_human_feedback", "run_refine_code", False),
+ "merge_review_security_feedback": ("review_security_human_feedback", "run_refine_code_with_reviews", False),
+ "collect_quality_human_feedback": ("quality_human_feedback", "run_refine_quality_and_code", False),
+ "collect_deployment_human_feedback": ("deployment_human_feedback", "run_refine_deployment", False),
+ }
+
+ if current_stage_ui in map_logic:
+ key_to_update, next_process_stage, is_list_input = map_logic[current_stage_ui]
+
+ # Store the input text in the workflow state dictionary
+ if is_list_input:
+ # Append input to the list for this key
+ state[key_to_update] = state.get(key_to_update, []) + [user_text]
+ elif key_to_update == "uml_human_feedback":
+ # Store UML feedback in the expected dict format, using 'all' for simplicity
+ state[key_to_update] = {"all": user_text}
+ else:
+ # Overwrite state key with the new text value
+ state[key_to_update] = user_text
+
+ next_stage = next_process_stage # Set the next stage for processing
+
+ # --- Special Handling Logic ---
+
+ # Q&A Completion Check
+ if current_stage_ui == "collect_answers":
+ state["user_input_iteration"] = state.get("user_input_iteration", 0) + 1
+ min_iterations_required = state.get("user_input_min_iterations", 1)
+ # Check if #DONE is present (case-insensitive) in the last non-empty line
+ lines = [line.strip() for line in user_text.splitlines() if line.strip()]
+ is_done_signal_present = "#DONE" in lines[-1].upper() if lines else False
+
+ logger.debug(f"Q&A Iteration: {state['user_input_iteration']} / {min_iterations_required}. '#DONE' signal present: {is_done_signal_present}")
+
+ # Check if minimum iterations met AND done signal given
+ if state["user_input_iteration"] >= min_iterations_required and is_done_signal_present:
+ state["user_input_done"] = True
+ next_stage = "run_refine_prompt" # Override: Q&A phase is finished, move to refining the prompt
+ logger.info("Minimum Q&A iterations met and #DONE signal received. Proceeding to prompt refinement.")
+ else:
+ state["user_input_done"] = False
+ # next_stage remains 'run_generate_questions' (to ask more questions)
+ logger.info("Continuing Q&A round.")
+
+ # Skip Web Search if Tavily is not configured
+ if current_stage_ui == "collect_code_human_input" and not state.get('tavily_instance'):
+ state["code_web_search_results"] = "Skipped (Tavily client not configured)"
+ next_stage = "run_generate_code_feedback" # Skip web search and go directly to code feedback
+ logger.info("Tavily not configured. Skipping web search step.")
+
+ else:
+ # Fallback if stage logic is somehow missing
+ st.error(f"Internal Error: Input handling logic is undefined for stage '{current_stage_ui}'. Please report this.")
+ logger.error(f"Input handling logic missing for defined input stage: {current_stage_ui}")
+
+ # --- Transition to Next Stage ---
+ if next_stage:
+ st.session_state.workflow_state = state # Commit state changes
+ st.session_state.user_input = "" # Clear the temporary input box content on successful submission
+ st.session_state.stage = next_stage # Update the application stage
+ logger.info(f"User input submitted for stage '{current_stage_ui}'. Transitioning to stage '{next_stage}'.")
+ st.rerun() # Rerun Streamlit to reflect the new stage
+
+ except Exception as e:
+ st.error(f"An error occurred while processing your input: {e}")
+ logger.error(f"Error processing input for stage '{current_stage_ui}': {e}", exc_info=True)
+ # Keep the input in the text box on error by not clearing st.session_state.user_input
+
+ # --- Test Execution Feedback Area ---
+ elif show_test_feedback_area:
+ st.markdown("### Test Execution & Feedback")
+ st.info("Please execute the generated tests against the code. Then, provide feedback on the results and indicate if the core functionality passed.")
+
+ # Display AI feedback on the tests for context
+ ai_test_feedback = st.session_state.workflow_state.get("test_cases_feedback", "*No AI feedback on tests was generated.*")
+ with st.expander("View AI Feedback on Test Cases"):
+ st.markdown(ai_test_feedback)
+
+ # Input area for human feedback/results
+ human_fb_text = st.text_area(
+ "Your Feedback & Test Results:",
+ height=150,
+ key="test_case_human_feedback_input", # Unique key
+ help="Describe which tests passed/failed, provide any error messages, stack traces, or observations from running the tests."
+ )
+
+ # Radio button for overall PASS/FAIL status
+ pass_fail_status = st.radio(
+ "Did the core functionality pass the tests?",
+ options=("PASS", "FAIL"),
+ index=1, # Default to FAIL
+ key="test_case_pass_fail_radio", # Unique key
+ horizontal=True,
+ help="Select PASS only if the critical user stories are working as expected based on your testing."
+ )
+
+ # Action buttons
+ col1, col2 = st.columns(2)
+ with col1: # Submit Results button
+ submit_key_test = "submit_test_results_button" # Unique key
+ if st.button("Submit Test Results", key=submit_key_test):
+ state = st.session_state.workflow_state
+ # Ensure messages list exists
+ if 'messages' not in state or not isinstance(state['messages'], list): state['messages'] = []
+
+ # Format feedback and create HumanMessage
+ feedback_content = f"Test Execution Summary:\n- Overall Status: {pass_fail_status}\n- Detailed Feedback/Results:\n{human_fb_text}"
+ human_message = SDLC.HumanMessage(content=feedback_content)
+
+ # Add message to master list and current cycle display
+ state["messages"].append(human_message)
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.append(human_message)
+
+ # Update state with feedback and pass/fail status
+ state["test_cases_human_feedback"] = feedback_content
+ state["test_cases_passed"] = (pass_fail_status == "PASS")
+ logger.info(f"Test results submitted. Overall status: {pass_fail_status}.")
+
+ # Determine next stage based on pass/fail
+ next_stage_after_test = "run_save_testing_outputs" if state["test_cases_passed"] else "run_refine_test_cases_and_code"
+ st.session_state.stage = next_stage_after_test
+ st.session_state.workflow_state = state # Commit state changes
+ logger.info(f"Transitioning to stage '{next_stage_after_test}' based on test results.")
+ st.rerun()
+
+ with col2: # Submit & Regenerate Code button (optional, allows skipping refinement)
+ regen_key_test = "regenerate_code_from_testing_button" # Unique key
+ if st.button("Regenerate Code (If Stuck)", key=regen_key_test, help="Use this if refinement isn't working and you want the AI to try generating code again from scratch, incorporating this test feedback."):
+ state = st.session_state.workflow_state
+ if 'messages' not in state or not isinstance(state['messages'], list): state['messages'] = []
+
+ # Format feedback indicating regeneration request
+ feedback_content_regen = f"Test Execution Summary:\n- Overall Status: {pass_fail_status}\n- Detailed Feedback/Results:\n{human_fb_text}\n\nDecision: Requesting full code regeneration based on this feedback."
+ human_message_regen = SDLC.HumanMessage(content=feedback_content_regen)
+
+ # Add message to history
+ state["messages"].append(human_message_regen)
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.append(human_message_regen)
+
+ # Store feedback, ensure test_cases_passed is False
+ state["test_cases_human_feedback"] = feedback_content_regen # Store context
+ state["test_cases_passed"] = False # Force refinement/regen path
+ logger.info(f"Test feedback submitted ({pass_fail_status}), requesting code regeneration.")
+
+ # --- Prepare Context for Code Regeneration ---
+ # Package testing feedback to guide the *initial* code generation step again
+ regen_context = f"Context from Failed Testing Cycle:\n- Overall Status: {pass_fail_status}\n- User Feedback/Errors:\n{human_fb_text}\n- AI Feedback on Failed Tests:\n{ai_test_feedback}\n\nInstruction: Regenerate the entire codebase attempting to address these issues from the start."
+ state["code_human_input"] = regen_context # Use the input field of the code generation cycle
+
+ # Add context message (optional, can be verbose but useful for tracing)
+ context_message = SDLC.HumanMessage(content=f"Context Forwarded for Code Regeneration (from Testing): {regen_context[:300]}...")
+ state["messages"].append(context_message) # Add to master list
+ st.session_state.current_cycle_messages.append(context_message) # Add to cycle list
+
+ # --- Transition Back to Code Generation ---
+ # NOTE: This jumps back significantly. Consider if a less drastic jump is desired.
+ # For now, jumping back to the *input* stage before initial code gen.
+ st.session_state.stage = "run_generate_initial_code" # Go back to generate initial code
+ st.session_state.workflow_state = state # Commit state
+ logger.info("Transitioning back to 'run_generate_initial_code' for regeneration based on test feedback.")
+ st.rerun()
+
+ # --- Decision Buttons (Approve/Refine) ---
+ elif show_decision_buttons:
+ st.markdown("### Decision Point")
+ st.info("Review the latest output for this cycle. Choose whether to refine it further based on feedback or approve it and proceed to the next cycle.")
+
+ # Define mappings for Refine and Proceed actions based on the current stage
+ # Refine Map: current_decision_stage -> next_feedback_or_input_stage
+ refine_map = {
+ "collect_user_story_decision": "run_generate_user_story_feedback",
+ "collect_product_review_decision": "run_generate_product_review_feedback",
+ "collect_design_doc_decision": "run_generate_design_doc_feedback",
+ "collect_uml_decision": "run_generate_uml_feedback",
+ "collect_code_decision": "collect_code_human_input", # Refining code usually needs new input/issues
+ "collect_review_security_decision": "run_code_review", # Restart review cycle
+ "collect_quality_decision": "run_generate_quality_feedback",
+ "collect_deployment_decision": "run_generate_deployment_feedback",
+ }
+ # Proceed Map: current_decision_stage -> (done_flag_key, save_function or None, next_cycle_start_stage)
+ proceed_map = {
+ "collect_user_story_decision": ("user_story_done", SDLC.save_final_user_story, "run_generate_initial_product_review"),
+ "collect_product_review_decision": ("product_review_done", SDLC.save_final_product_review, "run_generate_initial_design_doc"),
+ "collect_design_doc_decision": ("design_doc_done", SDLC.save_final_design_doc, "run_select_uml_diagrams"),
+ "collect_uml_decision": ("uml_done", SDLC.save_final_uml_diagrams, "run_generate_initial_code"),
+ # Proceeding from Code Generation saves the current code to final_code_files
+ "collect_code_decision": ("code_done", None, "run_code_review"), # No specific save func here, handled in logic below
+ "collect_review_security_decision": ("review_security_done", SDLC.save_review_security_outputs, "run_generate_initial_test_cases"),
+ "collect_quality_decision": ("quality_done", SDLC.save_final_quality_analysis, "generate_initial_deployment"), # Go to deployment prefs form
+ "collect_deployment_decision": ("deployment_done", SDLC.save_final_deployment_plan, "END"), # End of workflow
+ }
+
+ # Determine button layout (add third button for QA code regen)
+ num_cols = 3 if current_stage_ui == "collect_quality_decision" else 2
+ cols = st.columns(num_cols)
+
+ # --- Refine Button ---
+ with cols[0]:
+ refine_key = f"refine_button_{current_stage_ui}" # Unique key
+ if st.button("Refine Further", key=refine_key, help="Go back and provide more feedback or request AI changes for the current artifact(s)."):
+ if current_stage_ui in refine_map:
+ state = st.session_state.workflow_state
+ # Mark as not done (to allow refinement loop)
+ done_key = current_stage_ui.replace("collect_", "").replace("_decision", "_done")
+ state[done_key] = False
+ next_refine_stage = refine_map[current_stage_ui]
+
+ # Add human message indicating decision
+ refine_message = SDLC.HumanMessage(content=f"Decision: Refine '{current_major_cycle}' cycle further.")
+ state['messages'] = state.get('messages', []) + [refine_message]
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.append(refine_message)
+
+ # Transition to the refinement starting stage
+ st.session_state.stage = next_refine_stage
+ st.session_state.workflow_state = state
+ logger.info(f"Decision made to Refine cycle '{current_major_cycle}'. Transitioning to stage '{next_refine_stage}'.")
+ st.rerun()
+ else:
+ st.warning(f"Refinement logic is not defined for stage '{current_stage_ui}'.")
+ logger.warning(f"Attempted to refine from stage '{current_stage_ui}' but no refine path is defined.")
+
+ # --- Proceed Button ---
+ with cols[1]:
+ proceed_key = f"proceed_button_{current_stage_ui}" # Unique key
+ if st.button("Approve & Proceed", key=proceed_key, help="Finalize the current cycle's artifacts and move to the next stage of the workflow."):
+ if current_stage_ui in proceed_map:
+ state = st.session_state.workflow_state
+ done_key, save_function, next_major_stage = proceed_map[current_stage_ui]
+ error_occurred = False
+
+ try:
+ # Mark the cycle as done
+ state[done_key] = True
+ logger.info(f"Decision made to Proceed from cycle '{current_major_cycle}'. Marked '{done_key}'=True.")
+
+ # Add human message indicating decision
+ proceed_message = SDLC.HumanMessage(content=f"Decision: Approve and proceed from '{current_major_cycle}' cycle.")
+ state['messages'] = state.get('messages', []) + [proceed_message]
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.append(proceed_message)
+
+ # --- Special Handling for Code Promotion ---
+ # When proceeding from Code Generation, store the current code as the baseline for Review/Security
+ if current_stage_ui == "collect_code_decision":
+ current_code_object = state.get("code_current")
+ if current_code_object and isinstance(current_code_object, SDLC.GeneratedCode) and current_code_object.files:
+ state["final_code_files"] = current_code_object.files # This becomes the input for the next stage
+ logger.info(f"Promoted {len(current_code_object.files)} code files from 'code_current' to 'final_code_files' for Review cycle.")
+ else:
+ st.warning("Proceeding from Code Generation, but the 'code_current' state seems invalid or empty. Review cycle might lack code.")
+ logger.warning("Proceeding from Code Generation, but 'code_current' is invalid or has no files. Setting 'final_code_files' to empty list.")
+ state["final_code_files"] = []
+
+ # --- Execute Save Function (if applicable) ---
+ if save_function:
+ save_func_name = getattr(save_function, '__name__', 'artifact_save_function')
+ logger.info(f"Executing save function: {save_func_name}")
+ with st.spinner(f"Saving {save_func_name.replace('save_final_', '').replace('_', ' ')}..."):
+ state = save_function(state) # Update state with results of save function (e.g., file paths)
+ st.session_state.workflow_state = state # Commit state update
+
+ # --- Post-Save Validation (Check if expected output path exists) ---
+ # Map save functions to the state keys where they store output paths
+ save_path_keys = {
+ SDLC.save_final_user_story: "final_user_story_path",
+ SDLC.save_final_product_review: "final_product_review_path",
+ SDLC.save_final_design_doc: "final_design_document_path",
+ SDLC.save_final_uml_diagrams: "final_uml_diagram_folder", # Check folder for UML
+ SDLC.save_review_security_outputs: "final_review_security_folder", # Check main folder
+ SDLC.save_testing_outputs: "final_testing_folder", # Check main folder
+ SDLC.save_final_quality_analysis: "final_quality_analysis_path", # Check report path
+ SDLC.save_final_deployment_plan: "final_deployment_path",
+ }
+ expected_path_key = save_path_keys.get(save_function)
+ saved_path_value = state.get(expected_path_key) if expected_path_key else True # Assume success if no path key expected
+
+ # Check if the path exists (and is a file/dir as appropriate)
+ save_successful = False
+ if expected_path_key:
+ if saved_path_value and isinstance(saved_path_value, str) and os.path.exists(saved_path_value):
+ # Basic check: path exists. Could add isfile/isdir if needed.
+ save_successful = True
+ else:
+ save_successful = True # No specific path to check
+
+ # Additionally check for QA saving the final code folder
+ if save_function == SDLC.save_final_quality_analysis:
+ final_code_folder_path = state.get("final_code_folder")
+ if not (final_code_folder_path and os.path.isdir(final_code_folder_path)):
+ save_successful = False # Mark as failed if final code didn't save properly
+
+ if not save_successful:
+ st.warning(f"Proceeding, but the save operation for '{current_major_cycle}' might have failed (output path invalid or missing). Check logs.")
+ logger.warning(f"Save check failed after running {save_func_name}. Expected path key: {expected_path_key}, Value: {saved_path_value}")
+ else:
+ logger.info(f"Save function {save_func_name} completed successfully and path validation passed (if applicable).")
+
+ except Exception as e:
+ st.error(f"An error occurred while finalizing cycle '{current_major_cycle}': {e}")
+ logger.error(f"Error during 'Proceed' action for stage '{current_stage_ui}': {e}", exc_info=True)
+ error_occurred = True
+
+ # Transition only if no errors occurred
+ if not error_occurred:
+ st.session_state.stage = next_major_stage
+ logger.info(f"Transitioning to the next cycle's start stage: '{next_major_stage}'")
+ st.rerun()
+ else:
+ st.warning(f"Proceed logic is not defined for stage '{current_stage_ui}'.")
+ logger.warning(f"Attempted to proceed from stage '{current_stage_ui}' but no proceed path is defined.")
+
+ # --- Regenerate Code Button (Only for QA Decision) ---
+ if current_stage_ui == "collect_quality_decision":
+ with cols[2]:
+ regen_key_qa = "regenerate_code_from_qa_button" # Unique key
+ if st.button("Regenerate Code", key=regen_key_qa, help="If QA revealed significant issues needing a code rewrite, use this to jump back to code generation, providing QA feedback as context."):
+ state = st.session_state.workflow_state
+ if 'messages' not in state or not isinstance(state['messages'], list): state['messages'] = []
+ logger.info("Decision: Requesting code regeneration based on QA findings.")
+
+ # Add human message
+ regen_message = SDLC.HumanMessage(content="Decision: Regenerate code based on Quality Analysis findings.")
+ state["messages"].append(regen_message)
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.append(regen_message)
+
+ # --- Prepare context for regeneration ---
+ qa_report_summary = state.get('quality_current_analysis', 'No QA report available.')[:1500] # Limit summary length
+ regen_context = f"Context from Quality Analysis Cycle:\n- Final QA Report Summary:\n{qa_report_summary}\n\nInstruction: Regenerate the codebase attempting to address the quality concerns raised in the report."
+ state["code_human_input"] = regen_context # Feed context into the code gen input
+
+ # Add context message to history
+ context_message = SDLC.HumanMessage(content=f"Context Forwarded for Code Regeneration (from QA): {regen_context[:300]}...")
+ state["messages"].append(context_message)
+ st.session_state.current_cycle_messages.append(context_message)
+
+ # --- Transition back to Code Generation ---
+ st.session_state.stage = "run_generate_initial_code" # Jump back
+ st.session_state.workflow_state = state
+ logger.info("Transitioning back to 'run_generate_initial_code' for regeneration based on QA feedback.")
+ st.rerun()
+
+ # --- End Stage ---
+ elif current_stage_ui == "END":
+ st.balloons()
+ final_message = "## 🎉 Workflow Completed Successfully! 🎉\n\nAll cycles have been processed.\n\nYou can download the final artifacts and code snapshots from the sidebar.\n\nUse the 'Restart Workflow' button in the sidebar to begin a new project."
+ update_display(final_message) # Update the display area as well
+ st.markdown(final_message)
+ logger.info("Workflow reached END stage.")
+
+ # --- Fallback for Unknown UI Stages ---
+ # This handles cases where the stage is not 'initial_setup', not a 'run_' stage,
+ # and not one of the known input/decision stages. Should ideally not happen.
+ elif not current_stage_ui.startswith("run_"):
+ st.error(f"Internal Error: Reached an unknown UI interaction stage: '{current_stage_ui}'. The workflow might be stuck. Consider restarting.")
+ logger.error(f"Reached unknown UI stage: {current_stage_ui}. State might be inconsistent.")
+
+
+# ==============================================================================
+# --- Cycle Indicator Column ---
+# ==============================================================================
+with indicator_col:
+ st.subheader("Workflow Cycles")
+ st.caption("Current progress through the SDLC.")
+
+ # Determine the current cycle index for highlighting
+ current_major_indicator = STAGE_TO_CYCLE.get(st.session_state.stage, "Unknown")
+ current_idx_indicator = -1 # Default if stage/cycle is unknown
+ if current_major_indicator == "END":
+ current_idx_indicator = len(CYCLE_ORDER) # Mark as completed
+ elif current_major_indicator in CYCLE_ORDER:
+ current_idx_indicator = CYCLE_ORDER.index(current_major_indicator)
+
+ # Simple CSS for styling the cycle list
+ st.markdown("""
+
+ """, unsafe_allow_html=True)
+
+ # Display the cycle list with indicators
+ # Optionally implement windowing/scrolling if list gets very long
+ # win_before, win_after = 2, 4 # Example windowing parameters
+ # start = max(0, current_idx_indicator - win_before)
+ # end = min(len(CYCLE_ORDER), start + win_before + win_after + 1)
+ # start = max(0, end - (win_before + win_after + 1)) # Adjust start if end was clamped
+
+ for i, cycle_name in enumerate(CYCLE_ORDER):
+ # if start <= i < end : # Apply windowing if uncommented above
+ css_class = "cycle-item"
+ display_name = cycle_name
+
+ if i < current_idx_indicator:
+ css_class += " cycle-past"
+ display_name = f"✓ {cycle_name}" # Indicate past cycles
+ elif i == current_idx_indicator and current_major_indicator != "END":
+ css_class += " cycle-current"
+ display_name = f"➡️ {cycle_name}" # Indicate current cycle
+ else: # Future cycles
+ css_class += " cycle-future"
+
+ # Render the cycle item using markdown with embedded HTML/CSS
+ st.markdown(f'{display_name}
', unsafe_allow_html=True)
+
+ # Display completion marker if workflow is finished
+ if current_major_indicator == "END":
+ st.markdown(f'✅ Workflow End
', unsafe_allow_html=True)
+
+
+# ==============================================================================
+# --- Invisible Stage Execution Logic ---
+# ==============================================================================
+
+def run_workflow_step(func, next_display_stage, *args):
+ """
+ Executes a backend workflow function (from SDLC.py), handles state updates,
+ manages display content, adds messages to history, and transitions the UI stage.
+
+ Args:
+ func: The backend function to execute (e.g., SDLC.generate_questions).
+ next_display_stage: The stage the UI should transition to after this step completes.
+ *args: Additional arguments required by the backend function.
+ """
+ state_before = st.session_state.workflow_state
+ messages_before_count = len(state_before.get('messages', []))
+
+ # --- Define a VALID default GeneratedCode object for safety ---
+ # This object includes the required 'instructions' field.
+ valid_default_code = SDLC.GeneratedCode(files=[], instructions="[Default Instructions - Code Not Generated or Error]")
+
+ # --- Pre-execution Checks ---
+ if not isinstance(state_before, dict):
+ st.error("Workflow state has become invalid. Please restart.")
+ logger.critical("Workflow state is not a dictionary. Halting execution.")
+ initialize_state() # Consider resetting state automatically or just stopping
+ st.rerun()
+ return # Stop execution
+
+ # Get function name for logging/display
+ func_name = getattr(func, '__name__', repr(func))
+ # Handle lambda function name (specifically for deployment)
+ if func_name == '': func_name = "generate_initial_deployment"
+
+ logger.info(f"Executing workflow step: {func_name}")
+ try:
+ # Show spinner during execution
+ with st.spinner(f"Running: {func_name.replace('_',' ').title()}..."):
+
+ # --- Check for Required Resources (LLM, Tavily) ---
+ needs_llm = func not in [
+ SDLC.save_final_user_story, SDLC.save_final_product_review,
+ SDLC.save_final_design_doc, SDLC.save_final_uml_diagrams,
+ SDLC.save_review_security_outputs, SDLC.save_testing_outputs,
+ SDLC.save_final_quality_analysis, SDLC.save_final_deployment_plan,
+ SDLC.web_search_code # Web search uses Tavily, checked separately
+ ]
+ if needs_llm and not state_before.get('llm_instance'):
+ raise ConnectionError("LLM client is not configured or initialized in the workflow state.")
+
+ # --- Handle Skippable Steps (e.g., Web Search) ---
+ if func == SDLC.web_search_code and not state_before.get('tavily_instance'):
+ logger.warning("Web search step called, but Tavily client is not available in state. Skipping step.")
+ state_before["code_web_search_results"] = "Skipped (Tavily client not configured or API key missing)"
+ # Add a message indicating the skip
+ skip_message = AIMessage(content="Web Search: Skipped (Tavily client unavailable)")
+ state_before["messages"] = state_before.get("messages", []) + [skip_message]
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.append(skip_message)
+
+ # Manually update state and transition
+ st.session_state.workflow_state = state_before
+ st.session_state.stage = "run_generate_code_feedback" # Define the stage *after* web search
+ logger.info("Skipped web search. Transitioning directly to 'run_generate_code_feedback'.")
+ st.rerun()
+ return # Exit this function call
+
+ # --- Special Handling for Sequential Review/Security Steps ---
+ # If the function is code_review, run it, update state, and immediately trigger security_check
+ if func == SDLC.code_review:
+ logger.info("Executing code review step...")
+ state_after_review = SDLC.code_review(state_before, *args)
+ if not isinstance(state_after_review, dict):
+ raise TypeError(f"Function 'code_review' did not return a dictionary state. Got: {type(state_after_review)}")
+
+ # Add any new messages from code_review to the cycle display
+ messages_after_review_count = len(state_after_review.get('messages', []))
+ new_review_messages = state_after_review.get('messages', [])[messages_before_count:messages_after_review_count]
+ if new_review_messages:
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.extend(new_review_messages)
+
+ # Update the main state
+ st.session_state.workflow_state = state_after_review
+ # Transition directly to the security check stage
+ st.session_state.stage = "run_security_check"
+ logger.info("Code review completed. Transitioning directly to 'run_security_check'.")
+ st.rerun()
+ return # Exit this function call, security check will run on the next rerun
+
+ # --- Normal Function Execution ---
+ updated_state = func(state_before, *args)
+
+ # --- Post-execution State Update and Validation ---
+ if not isinstance(updated_state, dict):
+ # This indicates a fundamental issue with the backend function
+ logger.error(f"Workflow function '{func_name}' returned an invalid type: {type(updated_state)}. Expected a dictionary.")
+ st.error(f"Internal Error: Step '{func_name}' failed due to an unexpected return type. Workflow halted.")
+ st.stop() # Halt execution as state is likely corrupted
+ return
+
+ st.session_state.workflow_state = updated_state
+ logger.debug(f"State successfully updated after executing {func_name}.")
+
+ # --- Add New AI Messages to Cycle Display ---
+ messages_after_count = len(updated_state.get('messages', []))
+ new_messages = updated_state.get('messages', [])[messages_before_count:messages_after_count]
+ if new_messages:
+ # Filter to only add AI messages generated by this step
+ new_ai_messages = [msg for msg in new_messages if isinstance(msg, AIMessage)]
+ if new_ai_messages:
+ if 'current_cycle_messages' not in st.session_state: st.session_state.current_cycle_messages = []
+ st.session_state.current_cycle_messages.extend(new_ai_messages)
+ logger.debug(f"Added {len(new_ai_messages)} new AI message(s) from {func_name} to cycle display.")
+
+ # --- Determine Display Content for the Next UI Stage ---
+ # (This complex block sets `display_text` and potentially overrides `next_display_stage`)
+ display_text = f"Completed step: {func_name}. Preparing for {next_display_stage}..." # Default message
+
+ if func == SDLC.generate_questions:
+ # Display the newly generated questions
+ questions = updated_state.get("user_input_questions", [])[-5:] # Get last 5 questions
+ if questions:
+ min_iter = updated_state.get('user_input_min_iterations', 1)
+ current_iter = updated_state.get("user_input_iteration", 0) # Iteration *before* answering these
+ is_min_met = (current_iter + 1 >= min_iter) # Check if *this round* meets the minimum
+ min_iter_msg = f"(Minimum {min_iter} rounds required)" if not is_min_met else ""
+ display_text = f"**Please answer the following questions {min_iter_msg}:**\n\n" + "\n".join(f"- {q}" for q in questions)
+ if is_min_met:
+ display_text += "\n\n*When finished answering, type **#DONE** on a new line to proceed.*"
+ next_display_stage = "collect_answers" # Ensure UI goes to answer collection
+ else:
+ # If no questions were generated (e.g., AI decided it's enough)
+ display_text = "The AI generated no further questions. Refining the project prompt based on the discussion..."
+ logger.info("No new questions generated by AI. Moving to refine prompt.")
+ next_display_stage = "run_refine_prompt" # Skip answer collection
+
+ elif func == SDLC.refine_prompt:
+ refined_prompt = updated_state.get('refined_prompt', '*Error: Refined prompt not found in state.*')
+ display_text = f"**Refined Project Prompt:**\n```markdown\n{refined_prompt}\n```\n\n*Generating initial User Stories based on this prompt...*"
+
+ elif func == SDLC.generate_initial_user_stories:
+ stories = updated_state.get('user_story_current', '*Error: User stories not found.*')
+ display_text = f"**Initial User Stories Generated:**\n\n{stories}\n\n*Generating AI feedback on these stories...*"
+
+ elif func == SDLC.generate_user_story_feedback:
+ current_stories = updated_state.get('user_story_current', '*N/A*')
+ ai_feedback = updated_state.get('user_story_feedback', '*N/A*')
+ display_text = f"**Current User Stories:**\n```\n{current_stories}\n```\n---\n**AI Feedback on Stories:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or desired changes below.*"
+ next_display_stage = "collect_user_story_human_feedback" # Ready for human input
+
+ elif func == SDLC.refine_user_stories:
+ refined_stories = updated_state.get('user_story_current', '*N/A*')
+ display_text = f"**Refined User Stories:**\n\n{refined_stories}\n\n*Please review the refined stories. Choose 'Refine Further' or 'Approve & Proceed' below.*"
+ next_display_stage = "collect_user_story_decision" # Ready for decision
+
+ elif func == SDLC.generate_initial_product_review:
+ review = updated_state.get('product_review_current', '*N/A*')
+ display_text = f"**Initial Product Owner Review Generated:**\n\n{review}\n\n*Generating AI feedback on this review...*"
+
+ elif func == SDLC.generate_product_review_feedback:
+ current_review = updated_state.get('product_review_current', '*N/A*')
+ ai_feedback = updated_state.get('product_review_feedback', '*N/A*')
+ display_text = f"**Current Product Review:**\n```\n{current_review}\n```\n---\n**AI Feedback on Review:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or desired changes below.*"
+ next_display_stage = "collect_product_review_human_feedback"
+
+ elif func == SDLC.refine_product_review:
+ refined_review = updated_state.get('product_review_current', '*N/A*')
+ display_text = f"**Refined Product Review:**\n\n{refined_review}\n\n*Please review the refined PO review. Choose 'Refine Further' or 'Approve & Proceed' below.*"
+ next_display_stage = "collect_product_review_decision"
+
+ elif func == SDLC.generate_initial_design_doc:
+ doc = updated_state.get('design_doc_current', '*N/A*')
+ display_text = f"**Initial Design Document Generated:**\n```markdown\n{doc}\n```\n\n*Generating AI feedback on this document...*"
+
+ elif func == SDLC.generate_design_doc_feedback:
+ current_doc = updated_state.get('design_doc_current', '*N/A*')
+ ai_feedback = updated_state.get('design_doc_feedback', '*N/A*')
+ display_text = f"**Current Design Document:**\n```markdown\n{current_doc}\n```\n---\n**AI Feedback on Design:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or desired changes below.*"
+ next_display_stage = "collect_design_doc_human_feedback"
+
+ elif func == SDLC.refine_design_doc:
+ refined_doc = updated_state.get('design_doc_current', '*N/A*')
+ display_text = f"**Refined Design Document:**\n```markdown\n{refined_doc}\n```\n\n*Please review the refined design. Choose 'Refine Further' or 'Approve & Proceed' below.*"
+ next_display_stage = "collect_design_doc_decision"
+
+ elif func == SDLC.select_uml_diagrams:
+ messages = updated_state.get('messages', [])
+ # Try to find the specific justification message from the AI
+ justification_msg_content = "Relevant UML diagram types selected based on the design." # Default
+ if messages and isinstance(messages[-1], AIMessage) and ("selected" in messages[-1].content.lower() or "recommend" in messages[-1].content.lower()):
+ justification_msg_content = messages[-1].content # Use the actual AI message content
+ display_text = f"**UML Diagram Selection:**\n\n{justification_msg_content}\n\n*Generating initial PlantUML code for selected diagrams...*"
+
+ elif func == SDLC.generate_initial_uml_codes:
+ codes = updated_state.get('uml_current_codes', [])
+ if codes:
+ codes_display = "\n\n".join([f"**{c.diagram_type}**:\n```plantuml\n{c.code}\n```" for c in codes])
+ else:
+ codes_display = "*No UML codes were generated.*"
+ display_text = f"**Generated Initial PlantUML Codes:**\n\n{codes_display}\n\n*Generating AI feedback on these diagrams...*"
+
+ elif func == SDLC.generate_uml_feedback:
+ codes = updated_state.get('uml_current_codes', [])
+ feedback_dict = updated_state.get('uml_feedback', {})
+ codes_display = "\n\n".join([f"**{c.diagram_type}**:\n```plantuml\n{c.code}\n```" for c in codes]) if codes else "*N/A*"
+ feedback_display = "\n\n".join([f"**Feedback for {dt}:**\n{fb}" for dt, fb in feedback_dict.items()]) if feedback_dict else "*N/A*"
+ display_text = f"**Current UML Codes:**\n{codes_display}\n---\n**AI Feedback on Diagrams:**\n{feedback_display}\n\n---\n*Provide your overall feedback or specific changes needed below.*"
+ next_display_stage = "collect_uml_human_feedback"
+
+ elif func == SDLC.refine_uml_codes:
+ codes = updated_state.get('uml_current_codes', [])
+ codes_display = "\n\n".join([f"**{c.diagram_type} (Refined):**\n```plantuml\n{c.code}\n```" for c in codes]) if codes else "*N/A*"
+ display_text = f"**Refined UML Codes:**\n\n{codes_display}\n\n*Please review the refined diagrams. Choose 'Refine Further' or 'Approve & Proceed' below.*"
+ next_display_stage = "collect_uml_decision"
+
+ elif func == SDLC.generate_initial_code:
+ code_data = updated_state.get("code_current", valid_default_code) # Use valid default here!
+ files_display = []
+ total_len, max_len = 0, 4000 # Limit display length
+ num_files = len(code_data.files) if code_data and code_data.files else 0
+ instr = code_data.instructions if code_data else "[Instructions not available]"
+
+ if num_files > 0:
+ for f in code_data.files:
+ header = f"**File: {f.filename}**:\n```\n"
+ footer = "\n```\n"
+ # Calculate max content preview length safely
+ max_content = max(0, max_len - total_len - len(header) - len(footer) - 50) # 50 char buffer
+ content_preview = f.content[:max_content] if f.content else ""
+ is_truncated = len(f.content) > len(content_preview) if f.content else False
+ preview_str = f"{header}{content_preview}{'... (content truncated)' if is_truncated else ''}{footer}"
+ files_display.append(preview_str)
+ total_len += len(preview_str)
+ if total_len >= max_len:
+ files_display.append("\n*...(Code file display truncated due to length)*")
+ break
+ code_files_str = "".join(files_display)
+ display_text = f"**Initial Code Generated ({num_files} file{'s' if num_files != 1 else ''}):**\n{code_files_str}\n---\n**Setup & Run Instructions:**\n```\n{instr}\n```\n\n---\n*Try to set up and run the code. Describe any errors or issues below.*"
+ else:
+ display_text = "Initial code generation step completed, but no code files were generated. This might indicate an issue with the request or the LLM's response.\n\n*Please describe the expected outcome or provide feedback below.*"
+ logger.warning("generate_initial_code resulted in a valid GeneratedCode structure but with an empty file list.")
+ next_display_stage = "collect_code_human_input"
+
+ elif func == SDLC.web_search_code:
+ results = updated_state.get('code_web_search_results', '*No web search results available.*')
+ display_text = f"**Web Search Results (if applicable):**\n\n{results}\n\n*Generating AI feedback on the code, considering your input and these search results...*"
+
+ elif func == SDLC.generate_code_feedback:
+ ai_feedback = updated_state.get('code_feedback', '*N/A*')
+ user_input = updated_state.get('code_human_input', None) # Get the input that triggered this
+ context_header = "**Context Provided (User Input/Issue):**\n" if user_input else ""
+ user_input_display = f"```\n{user_input}\n```\n---\n" if user_input else ""
+ display_text = f"{context_header}{user_input_display}**AI Code Feedback:**\n\n{ai_feedback}\n\n---\n*Please provide your comments on the AI's feedback below (e.g., 'Yes, suggestion 1 seems right', 'No, the issue is actually in file X').*"
+ next_display_stage = "collect_code_human_feedback"
+
+ elif func == SDLC.refine_code:
+ code_data = updated_state.get("code_current", valid_default_code) # Use valid default
+ files_display=[]; total_len, max_len=0, 4000
+ num_files = len(code_data.files) if code_data else 0
+ instr = code_data.instructions if code_data else "[Instructions not available]"
+ if num_files > 0:
+ for f in code_data.files:
+ header = f"**File: {f.filename} (Refined):**\n```\n"; footer = "\n```\n"
+ max_content = max(0, max_len - total_len - len(header) - len(footer) - 50)
+ content_preview = f.content[:max_content] if f.content else ""; is_truncated = len(f.content) > len(content_preview) if f.content else False
+ preview_str = f"{header}{content_preview}{'... (content truncated)' if is_truncated else ''}{footer}"
+ files_display.append(preview_str); total_len += len(preview_str)
+ if total_len >= max_len: files_display.append("\n*...(Code file display truncated)*"); break
+ code_files_str = "".join(files_display)
+ display_text = f"**Refined Code ({num_files} file{'s' if num_files != 1 else ''}):**\n{code_files_str}\n---\n**Setup/Run Instructions:**\n```\n{instr}\n```\n\n---\n*Please review the refined code. Choose 'Refine Further' or 'Approve & Proceed' below.*"
+ else:
+ display_text = "Code refinement step completed, but no files were found in the result. This might indicate an error.\n\n*Choose 'Refine Further' to provide input or 'Approve & Proceed' if this is expected.*"
+ logger.warning("refine_code resulted in a valid GeneratedCode structure but with an empty file list.")
+ next_display_stage = "collect_code_decision"
+
+ elif func == SDLC.security_check: # Display after security check completes (code review ran just before)
+ review_fb = updated_state.get('code_review_current_feedback', '*Code review feedback not available.*')
+ security_fb = updated_state.get('security_current_feedback', '*Security check feedback not available.*')
+ display_text = f"**Code Review Findings:**\n```\n{review_fb}\n```\n---\n**Security Check Findings:**\n```\n{security_fb}\n```\n---\n*Please provide your overall feedback on these reports below (e.g., prioritize fixes, accept risks).*";
+ next_display_stage = "merge_review_security_feedback" # Stage to collect feedback on both reports
+
+ elif func == SDLC.refine_code_with_reviews:
+ code_data = updated_state.get("code_current", valid_default_code) # Use valid default
+ files_display=[]; total_len, max_len=0, 4000
+ num_files = len(code_data.files) if code_data else 0
+ instr = code_data.instructions if code_data else "[Instructions not available]"
+ if num_files > 0:
+ for f in code_data.files:
+ header = f"**File: {f.filename} (Post-Review/Security):**\n```\n"; footer = "\n```\n"
+ max_content = max(0, max_len - total_len - len(header) - len(footer) - 50)
+ content_preview = f.content[:max_content] if f.content else ""; is_truncated = len(f.content) > len(content_preview) if f.content else False
+ preview_str = f"{header}{content_preview}{'... (content truncated)' if is_truncated else ''}{footer}"
+ files_display.append(preview_str); total_len += len(preview_str)
+ if total_len >= max_len: files_display.append("\n*...(Code file display truncated)*"); break
+ code_files_str = "".join(files_display)
+ display_text = f"**Code Refined Post-Review & Security ({num_files} file{'s' if num_files != 1 else ''}):**\n{code_files_str}\n---\n**Setup/Run Instructions:**\n```\n{instr}\n```\n\n---\n*This code incorporates feedback from the review cycle. Review the final code and decide below.*"
+ else:
+ display_text = "Code refinement post-review completed, but no files found. This likely indicates an error.\n\n*Choose 'Refine Further' (to restart review) or 'Approve & Proceed' if this was somehow expected.*"
+ logger.error("refine_code_with_reviews resulted in an empty file list.")
+ next_display_stage = "collect_review_security_decision"
+
+ elif func == SDLC.generate_initial_test_cases:
+ tests = updated_state.get('test_cases_current', [])
+ tests_display = "\n\n".join([f"**Test: {tc.description}**\n - Input: `{tc.input_data}`\n - Expected Output: `{tc.expected_output}`" for tc in tests]) if tests else "*No test cases generated.*"
+ display_text=f"**Generated Initial Test Cases ({len(tests)}):**\n\n{tests_display}\n\n*Generating AI feedback on these test cases...*"
+
+ elif func == SDLC.generate_test_cases_feedback:
+ tests = updated_state.get('test_cases_current', [])
+ ai_feedback = updated_state.get('test_cases_feedback', '*N/A*')
+ tests_display = "\n\n".join([f"**Test: {tc.description}**\n - Input: `{tc.input_data}`\n - Expected Output: `{tc.expected_output}`" for tc in tests]) if tests else "*N/A*"
+ display_text=f"**Current Test Cases ({len(tests)}):**\n{tests_display}\n---\n**AI Feedback on Tests:**\n\n{ai_feedback}\n\n---\n*Please execute these tests against the code and report the results/feedback below.*";
+ next_display_stage = "collect_test_cases_human_feedback"
+
+ elif func == SDLC.refine_test_cases_and_code:
+ tests = updated_state.get('test_cases_current', [])
+ code_data_after_test_refine = updated_state.get('code_current', valid_default_code) # Use valid default
+ files_count = len(code_data_after_test_refine.files) if code_data_after_test_refine else 0
+ code_update_msg = f"Code ({files_count} files) and {len(tests)} test case(s) were refined based on test failures." if files_count > 0 else f"{len(tests)} Test case(s) refined (code may not have changed)."
+ tests_display = "\n\n".join([f"**Test: {tc.description}**:\n - Input:`{tc.input_data}`\n - Expected:`{tc.expected_output}`" for tc in tests]) if tests else "*N/A*"
+ display_text = f"**Refinement After Test Failure:**\n*{code_update_msg}*\n\n**Refined Tests ({len(tests)}):**\n{tests_display}\n\n*Please execute the tests again using the refined code and provide results/feedback below.*";
+ next_display_stage = "collect_test_cases_human_feedback" # Loop back to collect results again
+
+ elif func == SDLC.save_testing_outputs:
+ display_text = f"Testing cycle completed (PASS). Final tests and passed code snapshot saved.\n\n*Generating overall Quality Analysis report...*"
+
+ elif func == SDLC.generate_initial_quality_analysis:
+ report = updated_state.get('quality_current_analysis', '*N/A*')
+ display_text=f"**Initial Quality Analysis Report Generated:**\n\n{report}\n\n*Generating AI feedback on this QA report...*"
+
+ elif func == SDLC.generate_quality_feedback:
+ current_report = updated_state.get('quality_current_analysis', '*N/A*')
+ ai_feedback = updated_state.get('quality_feedback', '*N/A*')
+ display_text=f"**Current QA Report:**\n```\n{current_report}\n```\n---\n**AI Feedback on QA Report:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback on the QA report below.*";
+ next_display_stage = "collect_quality_human_feedback"
+
+ elif func == SDLC.refine_quality_and_code:
+ report = updated_state.get('quality_current_analysis', '*N/A*')
+ code_data_qa_refined = updated_state.get('code_current', valid_default_code) # Use valid default
+ code_files_exist = bool(code_data_qa_refined and code_data_qa_refined.files)
+ code_update_msg = "*Minor, non-functional code polish may have been applied based on QA feedback.*" if code_files_exist else "*QA report refined (code unchanged).*"
+ display_text=f"**Refined Quality Analysis Report:**\n\n{report}\n\n{code_update_msg}\n\n*Please review the final QA report. Choose 'Refine Further', 'Approve & Proceed', or 'Regenerate Code' below.*";
+ next_display_stage = "collect_quality_decision"
+
+ elif func_name == "generate_initial_deployment": # Handle lambda name
+ plan = updated_state.get('deployment_current_process', '*N/A*')
+ # Retrieve prefs used from state if stored, otherwise use placeholder
+ prefs_used = st.session_state.get('current_prefs', '[Preferences used previously, not displayed]')
+ display_text = f"**Initial Deployment Plan Generated:**\n*Based on Preferences:*\n```\n{prefs_used}\n```\n*Generated Plan:*\n```markdown\n{plan}\n```\n\n*Generating AI feedback on this deployment plan...*";
+
+ elif func == SDLC.generate_deployment_feedback:
+ current_plan = updated_state.get('deployment_current_process', '*N/A*')
+ ai_feedback = updated_state.get('deployment_feedback', '*N/A*')
+ display_text=f"**Current Deployment Plan:**\n```markdown\n{current_plan}\n```\n---\n**AI Feedback on Plan:**\n\n{ai_feedback}\n\n---\n*Please provide your feedback or required changes for the deployment plan below.*";
+ next_display_stage = "collect_deployment_human_feedback"
+
+ elif func == SDLC.refine_deployment:
+ plan = updated_state.get('deployment_current_process', '*N/A*')
+ display_text = f"**Refined Deployment Plan:**\n```markdown\n{plan}\n```\n\n*Please review the refined deployment plan. Choose 'Refine Further' or 'Approve & Proceed' below.*";
+ next_display_stage = "collect_deployment_decision"
+
+ # Display logic for save functions
+ elif func in [SDLC.save_final_user_story, SDLC.save_final_product_review, SDLC.save_final_design_doc, SDLC.save_final_uml_diagrams, SDLC.save_review_security_outputs, SDLC.save_testing_outputs, SDLC.save_final_quality_analysis, SDLC.save_final_deployment_plan]:
+ # Determine artifact name from function name
+ artifact_name = func.__name__.replace('save_final_','').replace('_',' ').title()
+ # Determine next major action/cycle name
+ next_action_stage = next_display_stage # The stage name provided to run_workflow_step
+ next_action_cycle = STAGE_TO_CYCLE.get(next_action_stage, next_action_stage).replace('_',' ').title()
+ # Special case names for clarity
+ if next_action_stage == "generate_initial_deployment":
+ next_action_name = "Deployment Preferences Input"
+ elif next_action_stage == "END":
+ next_action_name = "Workflow End"
+ else:
+ next_action_name = f"{next_action_cycle} Cycle"
+
+ display_text = f"✅ **{artifact_name} saved successfully.**\n\n*Proceeding to: {next_action_name}...*"
+ logger.info(f"Artifact saved: {artifact_name}. Next step starts stage: {next_action_stage}")
+
+ # --- Update UI Display and Transition Stage ---
+ update_display(display_text)
+ st.session_state.stage = next_display_stage
+ logger.info(f"Completed step '{func_name}'. UI transitioning to stage '{next_display_stage}'.")
+ st.rerun() # Rerun Streamlit to reflect the changes
+
+ # --- Error Handling ---
+ except ConnectionError as ce:
+ error_msg = f"Connection Error during step '{func_name}': {ce}. Please check your API keys, network connection, and service status."
+ st.error(error_msg)
+ logger.critical(error_msg, exc_info=False) # Log as critical, but maybe don't need full traceback always
+ # Optionally add a retry button here specific to connection errors if desired
+ except pydantic_core.ValidationError as pve:
+ # Handle Pydantic errors (often from LLM structured output) gracefully
+ error_details = str(pve)
+ logger.error(f"Data Validation Error in step '{func_name}': {error_details}", exc_info=True)
+ # Check if it's the specific error related to the default GeneratedCode
+ if "GeneratedCode" in error_details and "instructions" in error_details and "Field required" in error_details:
+ error_msg = f"Internal Application Error: Failed processing a code object during step '{func_name}', likely due to a missing default value in the application code. Please report this issue. Details: {error_details}"
+ st.error(error_msg)
+ # Halt here as it's an app logic issue needing a fix in app.py
+ st.stop()
+ else:
+ # General Pydantic error
+ error_msg = f"Data Validation Error during step '{func_name}': The AI's response did not match the expected format. Details: {error_details}"
+ st.error(error_msg)
+ # Offer retry for general validation errors
+ retry_key_pve = f"retry_btn_pve_{func_name}_{int(time.time())}"
+ if st.button("Retry Last Step", key=retry_key_pve):
+ logger.info(f"User initiated retry after Pydantic error in {func_name}.")
+ st.rerun()
+ except TypeError as te:
+ # TypeErrors often indicate programming errors (e.g., wrong argument types)
+ error_msg = f"Type Error during step '{func_name}': {te}. This might indicate an internal application issue."
+ st.error(error_msg)
+ logger.error(f"TypeError executing step '{func_name}': {te}", exc_info=True)
+ st.stop() # Halt on TypeErrors as they usually require code fixes
+ except ValueError as ve:
+ # ValueErrors can be raised by backend logic for specific input issues
+ error_msg = f"Input Error during step '{func_name}': {ve}. Please check the inputs or previous steps."
+ st.error(error_msg)
+ logger.error(f"ValueError executing step '{func_name}': {ve}", exc_info=True)
+ # Offer retry for ValueErrors as they might be transient or fixable by adjusting input
+ retry_key_ve = f"retry_btn_ve_{func_name}_{int(time.time())}"
+ if st.button("Retry Last Step", key=retry_key_ve):
+ logger.info(f"User initiated retry after ValueError in {func_name}.")
+ st.rerun()
+ except Exception as e:
+ # Catch-all for other unexpected errors
+ error_msg = f"An unexpected error occurred during step '{func_name}': {e}"
+ st.error(error_msg)
+ logger.error(f"Unexpected error executing step '{func_name}': {e}", exc_info=True)
+ # Offer retry for general exceptions
+ retry_key_exc = f"retry_btn_exc_{func_name}_{int(time.time())}" # Ensure unique key
+ if st.button("Retry Last Step", key=retry_key_exc):
+ logger.info(f"User initiated retry after general exception in {func_name}.")
+ st.rerun()
+
+
+# ==============================================================================
+# --- Workflow Map Definition ---
+# Maps "run_*" stages to their backend function and the next UI stage
+# ==============================================================================
+workflow_map = {
+ # Requirements Cycle
+ "run_generate_questions": (SDLC.generate_questions, "collect_answers"),
+ "run_refine_prompt": (SDLC.refine_prompt, "run_generate_initial_user_stories"), # End of Requirements
+ # User Story Cycle
+ "run_generate_initial_user_stories": (SDLC.generate_initial_user_stories, "run_generate_user_story_feedback"),
+ "run_generate_user_story_feedback": (SDLC.generate_user_story_feedback, "collect_user_story_human_feedback"),
+ "run_refine_user_stories": (SDLC.refine_user_stories, "collect_user_story_decision"),
+ # Product Review Cycle
+ "run_generate_initial_product_review": (SDLC.generate_initial_product_review, "run_generate_product_review_feedback"),
+ "run_generate_product_review_feedback": (SDLC.generate_product_review_feedback, "collect_product_review_human_feedback"),
+ "run_refine_product_review": (SDLC.refine_product_review, "collect_product_review_decision"),
+ # Design Cycle
+ "run_generate_initial_design_doc": (SDLC.generate_initial_design_doc, "run_generate_design_doc_feedback"),
+ "run_generate_design_doc_feedback": (SDLC.generate_design_doc_feedback, "collect_design_doc_human_feedback"),
+ "run_refine_design_doc": (SDLC.refine_design_doc, "collect_design_doc_decision"),
+ # UML Cycle
+ "run_select_uml_diagrams": (SDLC.select_uml_diagrams, "run_generate_initial_uml_codes"),
+ "run_generate_initial_uml_codes": (SDLC.generate_initial_uml_codes, "run_generate_uml_feedback"),
+ "run_generate_uml_feedback": (SDLC.generate_uml_feedback, "collect_uml_human_feedback"),
+ "run_refine_uml_codes": (SDLC.refine_uml_codes, "collect_uml_decision"),
+ # Code Generation Cycle
+ "run_generate_initial_code": (SDLC.generate_initial_code, "collect_code_human_input"),
+ "run_web_search_code": (SDLC.web_search_code, "run_generate_code_feedback"), # Handled specially in run_workflow_step if skipped
+ "run_generate_code_feedback": (SDLC.generate_code_feedback, "collect_code_human_feedback"),
+ "run_refine_code": (SDLC.refine_code, "collect_code_decision"),
+ # Review & Security Cycle
+ "run_code_review": (SDLC.code_review, "run_security_check"), # Special handling: runs review then triggers security check
+ "run_security_check": (SDLC.security_check, "merge_review_security_feedback"), # Displays both reports, waits for feedback
+ "run_refine_code_with_reviews": (SDLC.refine_code_with_reviews, "collect_review_security_decision"),
+ # Testing Cycle
+ "run_generate_initial_test_cases": (SDLC.generate_initial_test_cases, "run_generate_test_cases_feedback"),
+ "run_generate_test_cases_feedback": (SDLC.generate_test_cases_feedback, "collect_test_cases_human_feedback"),
+ "run_refine_test_cases_and_code": (SDLC.refine_test_cases_and_code, "collect_test_cases_human_feedback"), # Loop back to test execution
+ "run_save_testing_outputs": (SDLC.save_testing_outputs, "run_generate_initial_quality_analysis"), # End of Testing
+ # Quality Analysis Cycle
+ "run_generate_initial_quality_analysis": (SDLC.generate_initial_quality_analysis, "run_generate_quality_feedback"),
+ "run_generate_quality_feedback": (SDLC.generate_quality_feedback, "collect_quality_human_feedback"),
+ "run_refine_quality_and_code": (SDLC.refine_quality_and_code, "collect_quality_decision"),
+ # Deployment Cycle
+ "run_generate_initial_deployment": (
+ lambda state: SDLC.generate_initial_deployment(state, st.session_state.get('current_prefs', '')), # Pass prefs via lambda
+ "run_generate_deployment_feedback"
+ ),
+ "run_generate_deployment_feedback": (SDLC.generate_deployment_feedback, "collect_deployment_human_feedback"),
+ "run_refine_deployment": (SDLC.refine_deployment, "collect_deployment_decision"),
+ }
+
+# ==============================================================================
+# --- Main Execution Logic ---
+# Checks the current stage and runs the corresponding backend function if it's a "run_" stage.
+# ==============================================================================
+if st.session_state.get('config_applied', False):
+ current_stage_to_run = st.session_state.stage # Get the current stage
+
+ # Check if the stage indicates a background processing step
+ if current_stage_to_run.startswith("run_"):
+ if current_stage_to_run in workflow_map:
+ # Retrieve the function and the next UI stage from the map
+ func_to_execute, next_ui_stage = workflow_map[current_stage_to_run]
+ # Call the central execution function
+ run_workflow_step(func_to_execute, next_ui_stage)
+ else:
+ # This indicates a potential error in the workflow definition or state
+ st.error(f"Internal Error: Unknown processing stage '{current_stage_to_run}' encountered. Workflow cannot proceed. Please restart.")
+ logger.critical(f"Workflow halted at unknown 'run_' stage: {current_stage_to_run}. Check workflow_map definition.")
+ # Optionally force a reset or stop execution
+ # initialize_state()
+ # st.rerun()
+ st.stop()
+ # elif current_stage_to_run == "END":
+ # Handled within the main column display logic
+ # pass # No processing needed for END stage
+ # else:
+ # Stage is likely an input/decision stage, handled by the UI widgets above
+ # pass
+
+# Display warning if configuration hasn't been applied, unless at the very start
+elif st.session_state.stage != "initial_setup":
+ logger.warning("Workflow cannot proceed because configuration has not been applied.")
# Warning is already displayed in the main column section
\ No newline at end of file