Revert "Tenant provisioning in the dataplane (#2590)" (#2691)

This reverts commit 87eb4ad.

backend/danswer/auth/users.py

@@ -8,7 +8,6 @@
 from typing import Optional
 from typing import Tuple
 
-import jwt
 from email_validator import EmailNotValidError
 from email_validator import validate_email
 from fastapi import APIRouter
@@ -38,10 +37,8 @@
 from danswer.auth.schemas import UserRole
 from danswer.auth.schemas import UserUpdate
 from danswer.configs.app_configs import AUTH_TYPE
-from danswer.configs.app_configs import DATA_PLANE_SECRET
 from danswer.configs.app_configs import DISABLE_AUTH
 from danswer.configs.app_configs import EMAIL_FROM
-from danswer.configs.app_configs import EXPECTED_API_KEY
 from danswer.configs.app_configs import REQUIRE_EMAIL_VERIFICATION
 from danswer.configs.app_configs import SESSION_EXPIRE_TIME_SECONDS
 from danswer.configs.app_configs import SMTP_PASS
@@ -508,28 +505,3 @@ async def current_admin_user(user: User | None = Depends(current_user)) -> User
 def get_default_admin_user_emails_() -> list[str]:
     # No default seeding available for Danswer MIT
     return []
-
-
-async def control_plane_dep(request: Request) -> None:
-    api_key = request.headers.get("X-API-KEY")
-    if api_key != EXPECTED_API_KEY:
-        logger.warning("Invalid API key")
-        raise HTTPException(status_code=401, detail="Invalid API key")
-
-    auth_header = request.headers.get("Authorization")
-    if not auth_header or not auth_header.startswith("Bearer "):
-        logger.warning("Invalid authorization header")
-        raise HTTPException(status_code=401, detail="Invalid authorization header")
-
-    token = auth_header.split(" ")[1]
-    try:
-        payload = jwt.decode(token, DATA_PLANE_SECRET, algorithms=["HS256"])
-        if payload.get("scope") != "tenant:create":
-            logger.warning("Insufficient permissions")
-            raise HTTPException(status_code=403, detail="Insufficient permissions")
-    except jwt.ExpiredSignatureError:
-        logger.warning("Token has expired")
-        raise HTTPException(status_code=401, detail="Token has expired")
-    except jwt.InvalidTokenError:
-        logger.warning("Invalid token")
-        raise HTTPException(status_code=401, detail="Invalid token")

backend/danswer/chat/load_yamls.py

@@ -6,6 +6,7 @@
 from danswer.configs.chat_configs import PERSONAS_YAML
 from danswer.configs.chat_configs import PROMPTS_YAML
 from danswer.db.document_set import get_or_create_document_set_by_name
+from danswer.db.engine import get_sqlalchemy_engine
 from danswer.db.input_prompt import insert_input_prompt_if_not_exists
 from danswer.db.models import DocumentSet as DocumentSetDBModel
 from danswer.db.models import Persona
@@ -17,150 +18,148 @@
 from danswer.search.enums import RecencyBiasSetting
 
 
-def load_prompts_from_yaml(
-    db_session: Session, prompts_yaml: str = PROMPTS_YAML
-) -> None:
+def load_prompts_from_yaml(prompts_yaml: str = PROMPTS_YAML) -> None:
     with open(prompts_yaml, "r") as file:
         data = yaml.safe_load(file)
 
     all_prompts = data.get("prompts", [])
-    for prompt in all_prompts:
-        upsert_prompt(
-            user=None,
-            prompt_id=prompt.get("id"),
-            name=prompt["name"],
-            description=prompt["description"].strip(),
-            system_prompt=prompt["system"].strip(),
-            task_prompt=prompt["task"].strip(),
-            include_citations=prompt["include_citations"],
-            datetime_aware=prompt.get("datetime_aware", True),
-            default_prompt=True,
-            personas=None,
-            db_session=db_session,
-            commit=True,
-        )
+    with Session(get_sqlalchemy_engine()) as db_session:
+        for prompt in all_prompts:
+            upsert_prompt(
+                user=None,
+                prompt_id=prompt.get("id"),
+                name=prompt["name"],
+                description=prompt["description"].strip(),
+                system_prompt=prompt["system"].strip(),
+                task_prompt=prompt["task"].strip(),
+                include_citations=prompt["include_citations"],
+                datetime_aware=prompt.get("datetime_aware", True),
+                default_prompt=True,
+                personas=None,
+                db_session=db_session,
+                commit=True,
+            )
 
 
 def load_personas_from_yaml(
-    db_session: Session,
     personas_yaml: str = PERSONAS_YAML,
     default_chunks: float = MAX_CHUNKS_FED_TO_CHAT,
 ) -> None:
     with open(personas_yaml, "r") as file:
         data = yaml.safe_load(file)
 
     all_personas = data.get("personas", [])
-    for persona in all_personas:
-        doc_set_names = persona["document_sets"]
-        doc_sets: list[DocumentSetDBModel] = [
-            get_or_create_document_set_by_name(db_session, name)
-            for name in doc_set_names
-        ]
-
-        # Assume if user hasn't set any document sets for the persona, the user may want
-        # to later attach document sets to the persona manually, therefore, don't overwrite/reset
-        # the document sets for the persona
-        doc_set_ids: list[int] | None = None
-        if doc_sets:
-            doc_set_ids = [doc_set.id for doc_set in doc_sets]
-        else:
-            doc_set_ids = None
-
-        prompt_ids: list[int] | None = None
-        prompt_set_names = persona["prompts"]
-        if prompt_set_names:
-            prompts: list[PromptDBModel | None] = [
-                get_prompt_by_name(prompt_name, user=None, db_session=db_session)
-                for prompt_name in prompt_set_names
+    with Session(get_sqlalchemy_engine()) as db_session:
+        for persona in all_personas:
+            doc_set_names = persona["document_sets"]
+            doc_sets: list[DocumentSetDBModel] = [
+                get_or_create_document_set_by_name(db_session, name)
+                for name in doc_set_names
             ]
-            if any([prompt is None for prompt in prompts]):
-                raise ValueError("Invalid Persona configs, not all prompts exist")
-
-            if prompts:
-                prompt_ids = [prompt.id for prompt in prompts if prompt is not None]
-
-        p_id = persona.get("id")
-        tool_ids = []
-        if persona.get("image_generation"):
-            image_gen_tool = (
-                db_session.query(ToolDBModel)
-                .filter(ToolDBModel.name == "ImageGenerationTool")
+
+            # Assume if user hasn't set any document sets for the persona, the user may want
+            # to later attach document sets to the persona manually, therefore, don't overwrite/reset
+            # the document sets for the persona
+            doc_set_ids: list[int] | None = None
+            if doc_sets:
+                doc_set_ids = [doc_set.id for doc_set in doc_sets]
+            else:
+                doc_set_ids = None
+
+            prompt_ids: list[int] | None = None
+            prompt_set_names = persona["prompts"]
+            if prompt_set_names:
+                prompts: list[PromptDBModel | None] = [
+                    get_prompt_by_name(prompt_name, user=None, db_session=db_session)
+                    for prompt_name in prompt_set_names
+                ]
+                if any([prompt is None for prompt in prompts]):
+                    raise ValueError("Invalid Persona configs, not all prompts exist")
+
+                if prompts:
+                    prompt_ids = [prompt.id for prompt in prompts if prompt is not None]
+
+            p_id = persona.get("id")
+            tool_ids = []
+            if persona.get("image_generation"):
+                image_gen_tool = (
+                    db_session.query(ToolDBModel)
+                    .filter(ToolDBModel.name == "ImageGenerationTool")
+                    .first()
+                )
+                if image_gen_tool:
+                    tool_ids.append(image_gen_tool.id)
+
+            llm_model_provider_override = persona.get("llm_model_provider_override")
+            llm_model_version_override = persona.get("llm_model_version_override")
+
+            # Set specific overrides for image generation persona
+            if persona.get("image_generation"):
+                llm_model_version_override = "gpt-4o"
+
+            existing_persona = (
+                db_session.query(Persona)
+                .filter(Persona.name == persona["name"])
                 .first()
             )
-            if image_gen_tool:
-                tool_ids.append(image_gen_tool.id)
-
-        llm_model_provider_override = persona.get("llm_model_provider_override")
-        llm_model_version_override = persona.get("llm_model_version_override")
-
-        # Set specific overrides for image generation persona
-        if persona.get("image_generation"):
-            llm_model_version_override = "gpt-4o"
-
-        existing_persona = (
-            db_session.query(Persona).filter(Persona.name == persona["name"]).first()
-        )
-
-        upsert_persona(
-            user=None,
-            persona_id=(-1 * p_id) if p_id is not None else None,
-            name=persona["name"],
-            description=persona["description"],
-            num_chunks=persona.get("num_chunks")
-            if persona.get("num_chunks") is not None
-            else default_chunks,
-            llm_relevance_filter=persona.get("llm_relevance_filter"),
-            starter_messages=persona.get("starter_messages"),
-            llm_filter_extraction=persona.get("llm_filter_extraction"),
-            icon_shape=persona.get("icon_shape"),
-            icon_color=persona.get("icon_color"),
-            llm_model_provider_override=llm_model_provider_override,
-            llm_model_version_override=llm_model_version_override,
-            recency_bias=RecencyBiasSetting(persona["recency_bias"]),
-            prompt_ids=prompt_ids,
-            document_set_ids=doc_set_ids,
-            tool_ids=tool_ids,
-            builtin_persona=True,
-            is_public=True,
-            display_priority=existing_persona.display_priority
-            if existing_persona is not None
-            else persona.get("display_priority"),
-            is_visible=existing_persona.is_visible
-            if existing_persona is not None
-            else persona.get("is_visible"),
-            db_session=db_session,
-        )
-
-
-def load_input_prompts_from_yaml(
-    db_session: Session, input_prompts_yaml: str = INPUT_PROMPT_YAML
-) -> None:
+
+            upsert_persona(
+                user=None,
+                persona_id=(-1 * p_id) if p_id is not None else None,
+                name=persona["name"],
+                description=persona["description"],
+                num_chunks=persona.get("num_chunks")
+                if persona.get("num_chunks") is not None
+                else default_chunks,
+                llm_relevance_filter=persona.get("llm_relevance_filter"),
+                starter_messages=persona.get("starter_messages"),
+                llm_filter_extraction=persona.get("llm_filter_extraction"),
+                icon_shape=persona.get("icon_shape"),
+                icon_color=persona.get("icon_color"),
+                llm_model_provider_override=llm_model_provider_override,
+                llm_model_version_override=llm_model_version_override,
+                recency_bias=RecencyBiasSetting(persona["recency_bias"]),
+                prompt_ids=prompt_ids,
+                document_set_ids=doc_set_ids,
+                tool_ids=tool_ids,
+                builtin_persona=True,
+                is_public=True,
+                display_priority=existing_persona.display_priority
+                if existing_persona is not None
+                else persona.get("display_priority"),
+                is_visible=existing_persona.is_visible
+                if existing_persona is not None
+                else persona.get("is_visible"),
+                db_session=db_session,
+            )
+
+
+def load_input_prompts_from_yaml(input_prompts_yaml: str = INPUT_PROMPT_YAML) -> None:
     with open(input_prompts_yaml, "r") as file:
         data = yaml.safe_load(file)
 
     all_input_prompts = data.get("input_prompts", [])
-    for input_prompt in all_input_prompts:
-        # If these prompts are deleted (which is a hard delete in the DB), on server startup
-        # they will be recreated, but the user can always just deactivate them, just a light inconvenience
-
-        insert_input_prompt_if_not_exists(
-            user=None,
-            input_prompt_id=input_prompt.get("id"),
-            prompt=input_prompt["prompt"],
-            content=input_prompt["content"],
-            is_public=input_prompt["is_public"],
-            active=input_prompt.get("active", True),
-            db_session=db_session,
-            commit=True,
-        )
+    with Session(get_sqlalchemy_engine()) as db_session:
+        for input_prompt in all_input_prompts:
+            # If these prompts are deleted (which is a hard delete in the DB), on server startup
+            # they will be recreated, but the user can always just deactivate them, just a light inconvenience
+            insert_input_prompt_if_not_exists(
+                user=None,
+                input_prompt_id=input_prompt.get("id"),
+                prompt=input_prompt["prompt"],
+                content=input_prompt["content"],
+                is_public=input_prompt["is_public"],
+                active=input_prompt.get("active", True),
+                db_session=db_session,
+                commit=True,
+            )
 
 
 def load_chat_yamls(
-    db_session: Session,
     prompt_yaml: str = PROMPTS_YAML,
     personas_yaml: str = PERSONAS_YAML,
     input_prompts_yaml: str = INPUT_PROMPT_YAML,
 ) -> None:
-    load_prompts_from_yaml(db_session, prompt_yaml)
-    load_personas_from_yaml(db_session, personas_yaml)
-    load_input_prompts_from_yaml(db_session, input_prompts_yaml)
+    load_prompts_from_yaml(prompt_yaml)
+    load_personas_from_yaml(personas_yaml)
+    load_input_prompts_from_yaml(input_prompts_yaml)

backend/danswer/configs/app_configs.py

@@ -392,7 +392,3 @@
 
 MULTI_TENANT = os.environ.get("MULTI_TENANT", "").lower() == "true"
 SECRET_JWT_KEY = os.environ.get("SECRET_JWT_KEY", "")
-
-
-DATA_PLANE_SECRET = os.environ.get("DATA_PLANE_SECRET", "")
-EXPECTED_API_KEY = os.environ.get("EXPECTED_API_KEY", "")

backend/danswer/db/engine.py

@@ -115,7 +115,7 @@ def get_db_current_time(db_session: Session) -> datetime:
 
 
 # Regular expression to validate schema names to prevent SQL injection
-SCHEMA_NAME_REGEX = re.compile(r"^[a-zA-Z0-9_-]+$")
+SCHEMA_NAME_REGEX = re.compile(r"^[a-zA-Z_][a-zA-Z0-9_]*$")
 
 
 def is_valid_schema_name(name: str) -> bool:
@@ -273,7 +273,6 @@ def get_session_with_tenant(tenant_id: str | None = None) -> Session:
         tenant_id = current_tenant_id.get()
 
     if not is_valid_schema_name(tenant_id):
-        logger.error(f"Invalid tenant ID: {tenant_id}")
         raise Exception("Invalid tenant ID")
 
     engine = SqlEngine.get_engine()