Add file analysis and answer feedback

SovereignAI-Starter/app/database.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import os
+import hashlib
 import sqlite3
 from uuid import UUID
 from pathlib import Path
@@ -89,6 +90,19 @@ def initialize_database() -> None:
                 content TEXT NOT NULL,
                 PRIMARY KEY(message_id, version_index)
             );
+
+            CREATE TABLE IF NOT EXISTS answer_feedback (
+                user_id TEXT NOT NULL REFERENCES users(id) ON DELETE CASCADE,
+                conversation_id TEXT NOT NULL REFERENCES conversations(id) ON DELETE CASCADE,
+                message_index INTEGER NOT NULL CHECK(message_index >= 0),
+                version_index INTEGER NOT NULL CHECK(version_index >= 0),
+                answer_hash TEXT NOT NULL,
+                rating INTEGER NOT NULL CHECK(rating IN (-1, 1)),
+                updated_at TEXT NOT NULL DEFAULT CURRENT_TIMESTAMP,
+                PRIMARY KEY(user_id, conversation_id, message_index, version_index, answer_hash)
+            );
+            CREATE INDEX IF NOT EXISTS idx_answer_feedback_user
+                ON answer_feedback(user_id, updated_at DESC);
             """
         )
         message_columns = {
@@ -148,13 +162,25 @@ def get_conversation(user_id: str, conversation_id: str) -> dict[str, Any] | Non
             """,
             (conversation_id,),
         ).fetchall()
-    versions_by_message: dict[int, list[str]] = {}
+        versions_by_message: dict[int, list[str]] = {}
     for version in versions:
         versions_by_message.setdefault(version["message_id"], []).append(
             version["content"]
         )
+    feedback_by_answer: dict[tuple[int, int, str], int] = {}
+    with _connect() as connection:
+        feedback_rows = connection.execute(
+            """
+            SELECT message_index, version_index, answer_hash, rating
+            FROM answer_feedback
+            WHERE user_id = ? AND conversation_id = ?
+            """,
+            (user_id, conversation_id),
+        ).fetchall()
+    for row in feedback_rows:
+        feedback_by_answer[(row["message_index"], row["version_index"], row["answer_hash"])] = row["rating"]
     saved_messages = []
-    for message in messages:
+    for message_index, message in enumerate(messages):
         message_versions = versions_by_message.get(message["id"], [])
         if message["role"] == "assistant" and not message_versions:
             message_versions = [message["content"]]
@@ -164,6 +190,20 @@ def get_conversation(user_id: str, conversation_id: str) -> dict[str, Any] | Non
                 "content": message["content"],
                 "selected_version": message["selected_version"],
                 "versions": message_versions,
+                "feedback_versions": (
+                    [
+                        feedback_by_answer.get(
+                            (
+                                message_index,
+                                version_index,
+                                hashlib.sha256(content.encode("utf-8")).hexdigest(),
+                            )
+                        )
+                        for version_index, content in enumerate(message_versions)
+                    ]
+                    if message["role"] == "assistant"
+                    else []
+                ),
                 "created_at": message["created_at"],
             }
         )
@@ -233,4 +273,50 @@ def delete_conversation(user_id: str, conversation_id: str) -> bool:
         return cursor.rowcount > 0
 
 
+def save_answer_feedback(
+    user_id: str,
+    conversation_id: str,
+    message_index: int,
+    version_index: int,
+    rating: int,
+    timestamp: str,
+) -> None:
+    """Store a user's rating for the exact assistant answer version."""
+    with _connect() as connection:
+        messages = connection.execute(
+            "SELECT id, role, content FROM messages WHERE conversation_id = ? ORDER BY id",
+            (conversation_id,),
+        ).fetchall()
+        if message_index >= len(messages):
+            raise ValueError("Message index does not exist.")
+        message = messages[message_index]
+        if message["role"] != "assistant":
+            raise ValueError("Feedback can only be attached to assistant messages.")
+        version = connection.execute(
+            "SELECT content FROM message_versions WHERE message_id = ? AND version_index = ?",
+            (message["id"], version_index),
+        ).fetchone()
+        if version is None:
+            if version_index != 0:
+                raise ValueError("Answer version does not exist.")
+            answer = message["content"]
+        else:
+            answer = version["content"]
+        answer_hash = hashlib.sha256(answer.encode("utf-8")).hexdigest()
+        connection.execute(
+            """
+            INSERT INTO answer_feedback(
+                user_id, conversation_id, message_index, version_index,
+                answer_hash, rating, updated_at
+            ) VALUES (?, ?, ?, ?, ?, ?, ?)
+            ON CONFLICT(user_id, conversation_id, message_index, version_index, answer_hash)
+            DO UPDATE SET rating = excluded.rating, updated_at = excluded.updated_at
+            """,
+            (
+                user_id, conversation_id, message_index, version_index,
+                answer_hash, rating, timestamp,
+            ),
+        )
+
+
 initialize_database()