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original_archon/iterations/v4-streamlit-ui-overhaul/utils/site_pages.sql

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+-- Enable the pgvector extension
+create extension if not exists vector;
+
+-- Create the documentation chunks table
+create table site_pages (
+    id bigserial primary key,
+    url varchar not null,
+    chunk_number integer not null,
+    title varchar not null,
+    summary varchar not null,
+    content text not null,  -- Added content column
+    metadata jsonb not null default '{}'::jsonb,  -- Added metadata column
+    embedding vector(1536),  -- OpenAI embeddings are 1536 dimensions
+    created_at timestamp with time zone default timezone('utc'::text, now()) not null,
+    
+    -- Add a unique constraint to prevent duplicate chunks for the same URL
+    unique(url, chunk_number)
+);
+
+-- Create an index for better vector similarity search performance
+create index on site_pages using ivfflat (embedding vector_cosine_ops);
+
+-- Create an index on metadata for faster filtering
+create index idx_site_pages_metadata on site_pages using gin (metadata);
+
+-- Create a function to search for documentation chunks
+create function match_site_pages (
+  query_embedding vector(1536),
+  match_count int default 10,
+  filter jsonb DEFAULT '{}'::jsonb
+) returns table (
+  id bigint,
+  url varchar,
+  chunk_number integer,
+  title varchar,
+  summary varchar,
+  content text,
+  metadata jsonb,
+  similarity float
+)
+language plpgsql
+as $$
+#variable_conflict use_column
+begin
+  return query
+  select
+    id,
+    url,
+    chunk_number,
+    title,
+    summary,
+    content,
+    metadata,
+    1 - (site_pages.embedding <=> query_embedding) as similarity
+  from site_pages
+  where metadata @> filter
+  order by site_pages.embedding <=> query_embedding
+  limit match_count;
+end;
+$$;
+
+-- Everything above will work for any PostgreSQL database. The below commands are for Supabase security
+
+-- Enable RLS on the table
+alter table site_pages enable row level security;
+
+-- Create a policy that allows anyone to read
+create policy "Allow public read access"
+  on site_pages
+  for select
+  to public
+  using (true);

original_archon/iterations/v4-streamlit-ui-overhaul/utils/utils.py

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+import os
+from datetime import datetime
+from functools import wraps
+import inspect
+import json
+from typing import Optional
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+def write_to_log(message: str):
+    """Write a message to the logs.txt file in the workbench directory.
+    
+    Args:
+        message: The message to log
+    """
+    # Get the directory one level up from the current file
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    parent_dir = os.path.dirname(current_dir)
+    workbench_dir = os.path.join(parent_dir, "workbench")
+    log_path = os.path.join(workbench_dir, "logs.txt")
+    os.makedirs(workbench_dir, exist_ok=True)
+
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    log_entry = f"[{timestamp}] {message}\n"
+
+    with open(log_path, "a", encoding="utf-8") as f:
+        f.write(log_entry)
+
+def get_env_var(var_name: str) -> Optional[str]:
+    """Get an environment variable from the saved JSON file or from environment variables.
+    
+    Args:
+        var_name: The name of the environment variable to retrieve
+        
+    Returns:
+        The value of the environment variable or None if not found
+    """
+    # Path to the JSON file storing environment variables
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    parent_dir = os.path.dirname(current_dir)
+    env_file_path = os.path.join(current_dir, "env_vars.json")
+    
+    # First try to get from JSON file
+    if os.path.exists(env_file_path):
+        try:
+            with open(env_file_path, "r") as f:
+                env_vars = json.load(f)
+                if var_name in env_vars and env_vars[var_name]:
+                    return env_vars[var_name]
+        except (json.JSONDecodeError, IOError) as e:
+            write_to_log(f"Error reading env_vars.json: {str(e)}")
+    
+    # If not found in JSON, try to get from environment variables
+    return os.environ.get(var_name)
+
+def save_env_var(var_name: str, value: str) -> bool:
+    """Save an environment variable to the JSON file.
+    
+    Args:
+        var_name: The name of the environment variable
+        value: The value to save
+        
+    Returns:
+        True if successful, False otherwise
+    """
+    # Path to the JSON file storing environment variables
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    env_file_path = os.path.join(current_dir, "env_vars.json")
+    
+    # Load existing env vars or create empty dict
+    env_vars = {}
+    if os.path.exists(env_file_path):
+        try:
+            with open(env_file_path, "r") as f:
+                env_vars = json.load(f)
+        except (json.JSONDecodeError, IOError) as e:
+            write_to_log(f"Error reading env_vars.json: {str(e)}")
+            # Continue with empty dict if file is corrupted
+    
+    # Update the variable
+    env_vars[var_name] = value
+    
+    # Save back to file
+    try:
+        with open(env_file_path, "w") as f:
+            json.dump(env_vars, f, indent=2)
+        return True
+    except IOError as e:
+        write_to_log(f"Error writing to env_vars.json: {str(e)}")
+        return False
+
+def log_node_execution(func):
+    """Decorator to log the start and end of graph node execution.
+    
+    Args:
+        func: The async function to wrap
+    """
+    @wraps(func)
+    async def wrapper(*args, **kwargs):
+        func_name = func.__name__
+        write_to_log(f"Starting node: {func_name}")
+        try:
+            result = await func(*args, **kwargs)
+            write_to_log(f"Completed node: {func_name}")
+            return result
+        except Exception as e:
+            write_to_log(f"Error in node {func_name}: {str(e)}")
+            raise
+    return wrapper