feat: attachment context for LLM, markdown rendering, mobile layout with back arrow

app/plugins/builtins/ai_assistant/services.py

@@ -352,6 +352,57 @@ async def execute_tool_call(
         return f"Error executing tool '{tool.name}': {exc}"
 
 
+async def _extract_attachment_content(
+    db: AsyncSession,
+    session_id: uuid.UUID,
+    tenant_id: uuid.UUID,
+) -> str:
+    """Extract text content from session attachments for LLM context."""
+    result = await db.execute(
+        select(AIChatAttachment)
+        .where(AIChatAttachment.session_id == session_id)
+        .where(AIChatAttachment.tenant_id == tenant_id)
+        .order_by(AIChatAttachment.created_at.asc())
+    )
+    attachments = list(result.scalars().all())
+    if not attachments:
+        return ""
+
+    parts: list[str] = []
+    for att in attachments:
+        try:
+            with open(att.storage_path, "rb") as f:
+                content = f.read()
+
+            text_content = ""
+            mime = att.mime_type.lower()
+
+            if mime.startswith("text/") or att.filename.endswith((".txt", ".md", ".csv", ".json", ".yaml", ".yml", ".py", ".js", ".ts", ".html", ".xml")):
+                text_content = content.decode("utf-8", errors="replace")
+            elif mime == "application/pdf" or att.filename.endswith(".pdf"):
+                try:
+                    import fitz
+                    doc = fitz.open(stream=content, filetype="pdf")
+                    text_content = "\n".join(page.get_text() for page in doc)
+                    doc.close()
+                except ImportError:
+                    text_content = f"[PDF file: {att.filename} - extraction not available]"
+            elif mime.startswith("image/"):
+                text_content = f"[Image file: {att.filename} ({att.mime_type}, {att.size_bytes} bytes)]"
+            else:
+                text_content = f"[Binary file: {att.filename} ({att.mime_type}, {att.size_bytes} bytes)]"
+
+            if len(text_content) > 10000:
+                text_content = text_content[:10000] + "\n... [truncated]"
+
+            parts.append(f"--- Attachment: {att.filename} ---\n{text_content}")
+        except Exception as exc:
+            logger.warning("Failed to extract attachment %s: %s", att.filename, exc)
+            parts.append(f"--- Attachment: {att.filename} (extraction failed) ---")
+
+    return "\n\n".join(parts)
+
+
 async def stream_chat(
     db: AsyncSession,
     session: AIChatSession,
@@ -360,18 +411,18 @@ async def stream_chat(
     user_context: dict[str, Any],
     tenant_id: uuid.UUID,
 ) -> AsyncGenerator[str, None]:
-    """Stream chat response via SSE with tool-calling loop.
-
-    Yields SSE-formatted strings.
-    """
-    # Load conversation history
+    """Stream chat response via SSE with tool-calling loop."""
     history = await get_session_messages(db, session.id, tenant_id)
     messages: list[dict[str, Any]] = []
     for msg in history:
         messages.append({"role": msg.role, "content": msg.content})
 
-    # Add user message
-    messages.append({"role": "user", "content": user_message})
+    attachment_content = await _extract_attachment_content(db, session.id, tenant_id)
+    full_message = user_message
+    if attachment_content:
+        full_message = f"{user_message}\n\n--- Attached Files ---\n{attachment_content}"
+
+    messages.append({"role": "user", "content": full_message})
     await save_message(db, session.id, "user", user_message, tenant_id)
 
     # Get agent tools