refactor: Add StreamURL and Log types to schema.py and update ChatOutputResponse in utils/schemas.py

src/backend/base/langflow/api/v1/chat.py

@@ -17,12 +17,12 @@ from langflow.api.utils import (
 from langflow.api.v1.schemas import (
     FlowDataRequest,
     InputValueRequest,
-    Log,
     ResultDataResponse,
     StreamData,
     VertexBuildResponse,
     VerticesOrderResponse,
 )
+from langflow.schema.schema import Log
 from langflow.services.auth.utils import get_current_active_user
 from langflow.services.chat.service import ChatService
 from langflow.services.deps import get_chat_service, get_session, get_session_service
@@ -161,6 +161,7 @@ async def build_vertex(
         else:
             graph = cache.get("result")
         vertex = graph.get_vertex(vertex_id)
+        log_object = None
         try:
             lock = chat_service._cache_locks[flow_id_str]
             (
@@ -179,6 +180,7 @@ async def build_vertex(
                 inputs_dict=inputs.model_dump() if inputs else {},
                 files=files,
             )
+
             result_data_response = ResultDataResponse(**result_dict.model_dump())
 
         except Exception as exc:
@@ -187,12 +189,12 @@ async def build_vertex(
             log_type = type(exc).__name__
             valid = False
             result_data_response = ResultDataResponse(results={})
+            log_object = Log(message=log_message, type=log_type)
 
             # If there's an error building the vertex
             # we need to clear the cache
             await chat_service.clear_cache(flow_id_str)
 
-        log_object = Log(message=log_message, type=log_type)
         result_data_response.logs.append(log_object)
 
         # Log the vertex build

src/backend/base/langflow/api/v1/schemas.py

@@ -2,8 +2,6 @@ from datetime import datetime, timezone
 from enum import Enum
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Union
-from langflow.utils.schemas import ChatOutputResponse
-from typing_extensions import TypedDict
 from uuid import UUID
 
 from pydantic import BaseModel, ConfigDict, Field, field_validator, model_serializer
@@ -11,11 +9,12 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_serial
 from langflow.graph.schema import RunOutputs
 from langflow.schema import dotdict
 from langflow.schema.graph import Tweaks
-from langflow.schema.schema import InputType, OutputType
+from langflow.schema.schema import InputType, Log, OutputType
 from langflow.services.database.models.api_key.model import ApiKeyRead
 from langflow.services.database.models.base import orjson_dumps
 from langflow.services.database.models.flow import FlowCreate, FlowRead
 from langflow.services.database.models.user import UserRead
+from langflow.utils.schemas import ChatOutputResponse
 
 
 class BuildStatus(Enum):
@@ -245,11 +244,6 @@ class VerticesOrderResponse(BaseModel):
     vertices_to_run: List[str]
 
 
-class Log(TypedDict):
-    message: Union[dict, str]
-    type: str
-
-
 class ResultDataResponse(BaseModel):
     results: Optional[Any] = Field(default_factory=dict)
     logs: List[Log | None] = Field(default_factory=list)

src/backend/base/langflow/graph/graph/base.py

@@ -17,7 +17,6 @@ from langflow.graph.vertex.base import Vertex
 from langflow.graph.vertex.types import InterfaceVertex, StateVertex
 from langflow.schema import Record
 from langflow.schema.schema import INPUT_FIELD_NAME, InputType
-from langflow.services.cache.utils import CacheMiss
 from langflow.services.chat.service import ChatService
 from langflow.services.deps import get_chat_service
 from langflow.services.monitor.utils import log_transaction
@@ -734,7 +733,9 @@ class Graph:
         vertex = self.get_vertex(vertex_id)
         try:
             if not vertex.frozen or not vertex._built:
-                await vertex.build(user_id=user_id, inputs=inputs_dict,files=files, fallback_to_env_vars=fallback_to_env_vars)
+                await vertex.build(
+                    user_id=user_id, inputs=inputs_dict, files=files, fallback_to_env_vars=fallback_to_env_vars
+                )
 
             if vertex.result is not None:
                 params = vertex.artifacts_raw

src/backend/base/langflow/graph/schema.py

@@ -1,15 +1,17 @@
 from enum import Enum
 from typing import Any, List, Optional
 
-from pydantic import BaseModel, Field, field_serializer
+from pydantic import BaseModel, Field, field_serializer, model_validator
 
 from langflow.graph.utils import serialize_field
+from langflow.schema.schema import Log, StreamURL
 from langflow.utils.schemas import ChatOutputResponse, ContainsEnumMeta
 
 
 class ResultData(BaseModel):
     results: Optional[Any] = Field(default_factory=dict)
     artifacts: Optional[Any] = Field(default_factory=dict)
+    logs: Optional[List[dict]] = Field(default_factory=list)
     messages: Optional[list[ChatOutputResponse]] = Field(default_factory=list)
     timedelta: Optional[float] = None
     duration: Optional[str] = None
@@ -23,6 +25,19 @@ class ResultData(BaseModel):
             return {key: serialize_field(val) for key, val in value.items()}
         return serialize_field(value)
 
+    @model_validator(mode="before")
+    @classmethod
+    def validate_model(cls, values):
+        if not values.get("logs") and values.get("artifacts"):
+            # Build the log from the artifacts
+            message = values["artifacts"]
+            if "stream_url" in message:
+                stream_url = StreamURL(location=message["stream_url"])
+                values["logs"] = [Log(message=stream_url, type=message["type"])]
+            else:
+                values["logs"] = [Log(message=message, type=message["type"])]
+        return values
+
 
 class InterfaceComponentTypes(str, Enum, metaclass=ContainsEnumMeta):
     # ChatInput and ChatOutput are the only ones that are

src/backend/base/langflow/graph/utils.py

@@ -1,11 +1,11 @@
-from typing import Any, Union, Generator
 from enum import Enum
+from typing import Any, Generator, Union
 
 from langchain_core.documents import Document
-from langflow.schema.schema import Record
 from pydantic import BaseModel
 
 from langflow.interface.utils import extract_input_variables_from_prompt
+from langflow.schema.schema import Record
 
 
 class UnbuiltObject:
@@ -79,9 +79,15 @@ def get_artifact_type(custom_component, build_result) -> str:
         case list():
             result = ArtifactType.ARRAY
 
-
     if result == ArtifactType.UNKNOWN:
         if isinstance(build_result, Generator):
             result = ArtifactType.STREAM
 
     return result.value
+
+
+def post_process_raw(raw, artifact_type: str):
+    if artifact_type == ArtifactType.STREAM.value:
+        raw = ""
+
+    return raw

src/backend/base/langflow/graph/vertex/base.py

@@ -9,7 +9,7 @@ from typing import TYPE_CHECKING, Any, AsyncIterator, Callable, Dict, Iterator,
 from loguru import logger
 
 from langflow.graph.schema import INPUT_COMPONENTS, OUTPUT_COMPONENTS, InterfaceComponentTypes, ResultData
-from langflow.graph.utils import UnbuiltObject, UnbuiltResult, ArtifactType
+from langflow.graph.utils import ArtifactType, UnbuiltObject, UnbuiltResult
 from langflow.graph.vertex.utils import log_transaction
 from langflow.interface.initialize import loading
 from langflow.interface.listing import lazy_load_dict
@@ -428,8 +428,10 @@ class Vertex:
                     sender=artifacts.get("sender"),
                     sender_name=artifacts.get("sender_name"),
                     session_id=artifacts.get("session_id"),
+                    stream_url=artifacts.get("stream_url"),
                     files=[{"path": file} if isinstance(file, str) else file for file in artifacts.get("files", [])],
                     component_id=self.id,
+                    type=self.artifacts_type,
                 ).model_dump(exclude_none=True)
             ]
         except KeyError:
@@ -447,7 +449,6 @@ class Vertex:
             messages = self.extract_messages_from_artifacts(artifacts)
         else:
             messages = []
-
         result_dict = ResultData(
             results=result_dict,
             artifacts=artifacts,

src/backend/base/langflow/graph/vertex/types.py

@@ -2,11 +2,11 @@ import json
 from typing import AsyncIterator, Dict, Iterator, List
 
 import yaml
-from langchain_core.messages import AIMessage
+from langchain_core.messages import AIMessage, AIMessageChunk
 from loguru import logger
 
 from langflow.graph.schema import CHAT_COMPONENTS, RECORDS_COMPONENTS, InterfaceComponentTypes
-from langflow.graph.utils import UnbuiltObject, serialize_field
+from langflow.graph.utils import ArtifactType, UnbuiltObject, serialize_field
 from langflow.graph.vertex.base import Vertex
 from langflow.schema import Record
 from langflow.schema.schema import INPUT_FIELD_NAME
@@ -87,7 +87,7 @@ class InterfaceVertex(Vertex):
         if isinstance(message, str):
             message = unescape_string(message)
         stream_url = None
-        if isinstance(self._built_object, AIMessage):
+        if isinstance(self._built_object, (AIMessage, AIMessageChunk)):
             artifacts = ChatOutputResponse.from_message(
                 self._built_object,
                 sender=sender,
@@ -109,13 +109,14 @@ class InterfaceVertex(Vertex):
             # it means that it is a stream of messages
             else:
                 message = self._built_object
-
+            artifact_type = ArtifactType.STREAM if stream_url is not None else ArtifactType.OBJECT
             artifacts = ChatOutputResponse(
                 message=message,
                 sender=sender,
                 sender_name=sender_name,
                 stream_url=stream_url,
-                files=files
+                files=files,
+                type=artifact_type.value,
             )
 
             self.will_stream = stream_url is not None
@@ -198,6 +199,7 @@ class InterfaceVertex(Vertex):
             sender=self.params.get("sender", ""),
             sender_name=self.params.get("sender_name", ""),
             files=[{"path": file} if isinstance(file, str) else file for file in self.params.get("files", [])],
+            type=ArtifactType.OBJECT.value,
         ).model_dump()
         self.params[INPUT_FIELD_NAME] = complete_message
         self._built_object = Record(text=complete_message, data=self.artifacts)

src/backend/base/langflow/interface/initialize/loading.py

@@ -7,9 +7,8 @@ import orjson
 from loguru import logger
 
 from langflow.custom.eval import eval_custom_component_code
+from langflow.graph.utils import get_artifact_type, post_process_raw
 from langflow.schema.schema import Record
-from langflow.graph.utils import get_artifact_type
-
 
 if TYPE_CHECKING:
     from langflow.custom import CustomComponent
@@ -134,5 +133,7 @@ async def instantiate_custom_component(params, user_id, vertex, fallback_to_env_
     elif hasattr(raw, "model_dump"):
         raw = raw.model_dump()
 
-    artifact = {"repr": custom_repr, "raw": raw, "type": get_artifact_type(custom_component, build_result)}
+    artifact_type = get_artifact_type(custom_component, build_result)
+    raw = post_process_raw(raw, artifact_type)
+    artifact = {"repr": custom_repr, "raw": raw, "type": artifact_type}
     return custom_component, build_result, artifact