Merge branch 'main' into feature/scratchpad-tool

Author: ezelanza

docs/modules/backend.mdx

@@ -257,7 +257,7 @@ import { ChatModelError } from "beeai-framework/backend/errors";
 import { OpenMeteoTool } from "beeai-framework/tools/weather/openMeteo";
 
 const llm = new OpenAIChatModel(
-  "gpt-4o",
+  "gpt-5-nano",
   {},
   // {
   //   baseURL: "OPENAI_BASE_URL",
@@ -269,13 +269,12 @@ const llm = new OpenAIChatModel(
 
 llm.config({
   parameters: {
-    temperature: 0,
-    topP: 1,
+    maxTokens: 2048,
   },
 });
 
 async function openaiFromName() {
-  const openaiLLM = await ChatModel.fromName("openai:gpt-4o");
+  const openaiLLM = await ChatModel.fromName("openai:gpt-5-nano");
   const response = await openaiLLM.create({
     messages: [new UserMessage("what states are part of New England?")],
   });

docs/yarn.lock

@@ -5438,9 +5438,9 @@ __metadata:
   linkType: hard
 
 "lodash@npm:^4.17.21, lodash@npm:~4.17.21":
-  version: 4.17.21
-  resolution: "lodash@npm:4.17.21"
-  checksum: 10c0/d8cbea072bb08655bb4c989da418994b073a608dffa608b09ac04b43a791b12aeae7cd7ad919aa4c925f33b48490b5cfe6c1f71d827956071dae2e7bb3a6b74c
+  version: 4.17.23
+  resolution: "lodash@npm:4.17.23"
+  checksum: 10c0/1264a90469f5bb95d4739c43eb6277d15b6d9e186df4ac68c3620443160fc669e2f14c11e7d8b2ccf078b81d06147c01a8ccced9aab9f9f63d50dcf8cace6bf6
   languageName: node
   linkType: hard
 

python/CHANGELOG.md

@@ -1,3 +1,10 @@
+## python_v0.1.77 (2026-02-11)
+
+### Features
+
+- extend VectorStore parameters
+- update agentstack-sdk (#1405)
+
 ## python_v0.1.76 (2026-01-20)
 
 ### Features

python/beeai_framework/adapters/agentstack/agents/agent.py

@@ -152,9 +152,18 @@ async def _get_metadata(self, client: PlatformClient) -> dict[str, Any]:
 
         context_token = await self._agent_stack_context.generate_token(
             client=client,
-            grant_global_permissions=Permissions(llm={"*"}, embeddings={"*"}, a2a_proxy={"*"}, contexts={"read"}),
+            grant_global_permissions=Permissions(
+                llm={"*"},
+                embeddings={"*"},
+                a2a_proxy={"*"},
+                contexts={"read"},
+                model_providers={"read"},
+                providers={"read"},
+            ),
             grant_context_permissions=ContextPermissions(files={"*"}, vector_stores={"*"}, context_data={"*"}),
         )
+        client.headers["Authorization"] = f"Bearer {context_token.token.get_secret_value()}"
+
         llm_spec = LLMServiceExtensionSpec.from_agent_card(self._agent.agent_card)
         embedding_spec = EmbeddingServiceExtensionSpec.from_agent_card(self._agent.agent_card)
         agent_stack_extension_spec = PlatformApiExtensionSpec.from_agent_card(self._agent.agent_card)

python/beeai_framework/adapters/agentstack/serve/_dummy_context_store.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 from collections.abc import AsyncIterator
+from uuid import UUID
 
 try:
     import a2a.types as a2a_types
@@ -23,6 +24,9 @@ async def load_history(self) -> AsyncIterator[a2a_types.Message | a2a_types.Arti
     async def store(self, data: a2a_types.Message | a2a_types.Artifact) -> None:
         pass
 
+    async def delete_history_from_id(self, from_id: UUID) -> None:
+        pass
+
 
 class DummyContextStore(agentstack_context_store.ContextStore):
     _cs = DummyContextStoreInstance()

python/beeai_framework/adapters/agentstack/serve/factories.py

@@ -1,6 +1,5 @@
 # Copyright 2025 © BeeAI a Series of LF Projects, LLC
 # SPDX-License-Identifier: Apache-2.0
-import uuid
 from collections.abc import AsyncGenerator
 from typing import Annotated, Any, Unpack, cast
 
@@ -87,17 +86,16 @@ async def run(
             embedding=extra_extensions.get("embedding"),
             extra_extensions=extra_extensions,  # type: ignore[arg-type]
         ) as stack_context:
-            artifact_id = uuid.uuid4()
-            append = False
+            stream = False
 
             @cloned_agent.emitter.on("partial_update")
             async def on_partial_update(data: ReActAgentUpdateEvent, _: EventMeta) -> None:
-                nonlocal append
+                nonlocal stream
                 if data.update.key == "final_answer":
                     update = data.update.value
                     update = update.get_text_content() if hasattr(update, "get_text_content") else str(update)
-                    await _send_final_answer_update(context, artifact_id, update, append=append)
-                    append = True
+                    await context.yield_async(update)
+                    stream = True
 
             @cloned_agent.emitter.on("update")
             async def on_update(data: ReActAgentUpdateEvent, _: EventMeta) -> None:
@@ -117,9 +115,7 @@ async def on_update(data: ReActAgentUpdateEvent, _: EventMeta) -> None:
                 await context.store(message)
                 await context.store(agent_response)
 
-            if append:
-                await _send_final_answer_update(context, artifact_id, last_chunk=True)
-            else:
+            if not stream:
                 yield agent_response
 
     return agentstack_agent.agent(**agent_metadata)(run)
@@ -207,14 +203,13 @@ async def run(
             embedding=extra_extensions.get("embedding"),
             extra_extensions=extra_extensions,  # type: ignore[arg-type]
         ) as stack_context:
-            artifact_id = uuid.uuid4()
-            append = False
+            stream = False
 
             @cloned_agent.emitter.on("final_answer")
             async def on_final_answer(data: RequirementAgentFinalAnswerEvent, _: EventMeta) -> None:
-                nonlocal append
-                await _send_final_answer_update(context, artifact_id, data.delta, append=append)
-                append = True
+                nonlocal stream
+                await context.yield_async(data.delta)
+                stream = True
 
             result = await cloned_agent.run([convert_a2a_to_framework_message(message)]).middleware(
                 create_tool_trajectory_middleware(stack_context)
@@ -225,37 +220,12 @@ async def on_final_answer(data: RequirementAgentFinalAnswerEvent, _: EventMeta)
                 await context.store(message)
                 await context.store(agent_response)
 
-            if append:
-                await _send_final_answer_update(context, artifact_id, last_chunk=True)
-            else:
+            if not stream:
                 yield agent_response
 
     return agentstack_agent.agent(**agent_metadata)(run)
 
 
-async def _send_final_answer_update(
-    context: agentstack_context.RunContext,
-    artifact_id: uuid.UUID,
-    update: str = "",
-    *,
-    append: bool = True,
-    last_chunk: bool = False,
-) -> None:
-    await context.yield_async(
-        a2a_types.TaskArtifactUpdateEvent(
-            append=append,
-            context_id=context.context_id,
-            task_id=context.task_id,
-            last_chunk=last_chunk,
-            artifact=a2a_types.Artifact(
-                name="final_answer",
-                artifact_id=str(artifact_id),
-                parts=[a2a_types.Part(root=a2a_types.TextPart(text=update))],
-            ),
-        )
-    )
-
-
 def _runnable_factory(
     runnable: Runnable[Any], *, metadata: AgentStackServerMetadata | None = None, memory_manager: MemoryManager
 ) -> agentstack_agent.AgentFactory:

python/beeai_framework/adapters/langchain/backend/vector_store.py

@@ -30,9 +30,9 @@ def __init__(self, *, vector_store: LCVectorStore) -> None:
         super().__init__()
         self.vector_store: LCVectorStore = vector_store
 
-    async def add_documents(self, documents: list[Document]) -> list[str]:
+    async def add_documents(self, documents: list[Document], **kwargs: Any) -> list[str]:
         lc_documents = [document_to_lc_document(document) for document in documents]
-        return await self.vector_store.aadd_documents(lc_documents)
+        return await self.vector_store.aadd_documents(lc_documents, **kwargs)
 
     async def search(self, query: QueryLike, k: int = 4, **kwargs: Any) -> list[DocumentWithScore]:
         query_str = str(query)

python/beeai_framework/adapters/langchain/mappers/documents.py

@@ -13,8 +13,8 @@
 
 
 def lc_document_to_document(lc_document: Document) -> VectorStoreDocument:
-    return VectorStoreDocument(content=lc_document.page_content, metadata=lc_document.metadata)
+    return VectorStoreDocument(id=lc_document.id, content=lc_document.page_content, metadata=lc_document.metadata)
 
 
 def document_to_lc_document(document: VectorStoreDocument) -> Document:
-    return Document(page_content=document.content, metadata=document.metadata)
+    return Document(id=document.id, page_content=document.content, metadata=document.metadata)

python/beeai_framework/backend/types.py

@@ -247,14 +247,19 @@ class EmbeddingModelOutput(BaseModel):
 
 
 class Document(BaseModel):
+    model_config = ConfigDict(extra="allow")
+
+    id: str | None = Field(default=None, coerce_numbers_to_str=True)
+    metadata: dict[str, str | int | float | bool] = Field(default_factory=dict)
     content: str
-    metadata: dict[str, str | int | float | bool]
 
     def __str__(self) -> str:
         return self.content
 
 
 class DocumentWithScore(BaseModel):
+    model_config = ConfigDict(extra="allow")
+
     document: Document
     score: float
 

python/beeai_framework/backend/vector_store.py

@@ -17,6 +17,7 @@ class QueryLike(Protocol):
     Any object that implements the `__str__` method can be used as a query
     for vector store searches.
     """
+
     def __str__(self) -> str: ...