Repository: i-am-bee/beeai-framework
Pull request #691: fallback to structured decoding in environments without proper tool choice support
Author: login: Tomas2D
Labels: name: python
description: Python related functionality
Created: 2025-03-27T21:15:45Z | Merged: 2025-03-28T18:14:57Z

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### Which issue(s) does this pull-request address?

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Closes: #689

### Description

This PR does the following:

- simulate `tool_choice=required` and `tool_choice=my_tool` for environments where it is not supported
- adds tool calling capabilities to those for which their providers do not support it (eg: deepseek), by setting `model_supports_tool_calling=False` and `tool_choice=required` or `tool_choice=my_tool`
- improve schema parsing
- refactor ChatModelKwargs
- fix dict parsing in UserMessage

### Checklist

#### General
- [ ] I have read the appropriate contributor guide: [Python](https://github.com/i-am-bee/beeai-framework/blob/main/CONTRIBUTING.md)
/ [TypeScript](https://github.com/i-am-bee/beeai-framework/blob/main/CONTRIBUTING.md)
- [ ] I have signed off on my commit: [Python instructions](https://github.com/i-am-bee/beeai-framework/blob/main/python/CONTRIBUTING.md#developer-certificate-of-origin-dco) / [TypeScript instructions](https://github.com/i-am-bee/beeai-framework/blob/main/typescript/CONTRIBUTING.md#developer-certificate-of-origin-dco)
- [ ] Commit messages and PR title follow [conventional commits](https://www.conventionalcommits.org/en/v1.0.0/#summary)
- [ ] Appropriate label(s) added to PR: `Python` for Python changes, `TypeScript` for TypeScript changes

#### Code quality checks
- [ ] Linting passes: Python `poe lint` or `poe lint --fix` / TypeScript `yarn lint` or `yarn lint:fix`
- [ ] Formatting is applied: Python `poe format` or `poe format --fix` / TypeScript: `yarn format` or `yarn format:fix`
- [ ] Static type checks pass: Python `poe type-check`

#### Testing
- [ ] Unit tests pass: Python `poe test --type unit` / TypeScript `yarn test:unit`
- [ ] E2E tests pass: Python `poe test --type e2e` / TypeScript: `yarn test:e2e`
- [ ] Integration tests pass: Python `poe test --type integration`
- [ ] Tests are included (for bug fixes or new features)

#### Documentation
- [ ] Documentation is updated
- [ ] Embedme embeds code examples in docs. To update after edits, run: Python `poe docs --type build`



Diff:
diff --git a/python/beeai_framework/adapters/litellm/chat.py b/python/beeai_framework/adapters/litellm/chat.py
index bd033017c..09a11a22e 100644
--- a/python/beeai_framework/adapters/litellm/chat.py
+++ b/python/beeai_framework/adapters/litellm/chat.py
@@ -27,13 +27,16 @@
 from litellm.types.utils import StreamingChoices
 from openai.lib._pydantic import to_strict_json_schema
 from pydantic import BaseModel
+from typing_extensions import Unpack
 
 from beeai_framework.backend.chat import (
     ChatModel,
+    ChatModelKwargs,
 )
 from beeai_framework.backend.errors import ChatModelError
 from beeai_framework.backend.message import (
     AssistantMessage,
+    MessageTextContent,
     MessageToolCallContent,
     ToolMessage,
 )
@@ -49,6 +52,7 @@
 from beeai_framework.logger import Logger
 from beeai_framework.tools.tool import Tool
 from beeai_framework.utils.dicts import exclude_keys, exclude_none, include_keys
+from beeai_framework.utils.strings import to_json
 
 logger = Logger(__name__)
 
@@ -58,8 +62,15 @@ class LiteLLMChatModel(ChatModel, ABC):
     def model_id(self) -> str:
         return self._model_id
 
-    def __init__(self, model_id: str, *, provider_id: str, settings: dict[str, Any] | None = None) -> None:
-        super().__init__()
+    def __init__(
+        self,
+        model_id: str,
+        *,
+        provider_id: str,
+        settings: dict[str, Any] | None = None,
+        **kwargs: Unpack[ChatModelKwargs],
+    ) -> None:
+        super().__init__(**kwargs)
         self._model_id = model_id
         self._litellm_provider_id = provider_id
         self.supported_params = get_supported_openai_params(model=self.model_id, custom_llm_provider=provider_id) or []
@@ -130,53 +141,69 @@ def _transform_input(self, input: ChatModelInput) -> dict[str, Any]:
         for message in input.messages:
             if isinstance(message, ToolMessage):
                 for content in message.content:
-                    messages.append(
+                    new_msg = (
                         {
                             "tool_call_id": content.tool_call_id,
                             "role": "tool",
                             "name": content.tool_name,
                             "content": content.result,
                         }
-                    )
-            elif isinstance(message, AssistantMessage):
-                messages.append(
-                    exclude_none(
-                        {
+                        if self.model_supports_tool_calling
+                        else {
                             "role": "assistant",
-                            "content": [t.model_dump() for t in message.get_text_messages()] or None,
-                            "tool_calls": [
-                                {
-                                    "id": call.id,
-                                    "type": "function",
-                                    "function": {
-                                        "arguments": call.args,
-                                        "name": call.tool_name,
-                                    },
-                                }
-                                for call in message.get_tool_calls()
-                            ]
-                            or None,
+                            "content": to_json(
+                                {"tool_call_id": content.tool_call_id, "result": content.result}, indent=2
+                            ),
                         }
                     )
+                    messages.append(new_msg)
+
+            elif isinstance(message, AssistantMessage):
+                msg_text_content = [t.model_dump() for t in message.get_text_messages()]
+                msg_tool_calls = [
+                    {
+                        "id": call.id,
+                        "type": "function",
+                        "function": {
+                            "arguments": call.args,
+                            "name": call.tool_name,
+                        },
+                    }
+                    for call in message.get_tool_calls()
+                ]
+
+                new_msg = (
+                    {
+                        "role": "assistant",
+                        "content": msg_text_content or None,
+                        "tool_calls": msg_tool_calls or None,
+                    }
+                    if self.model_supports_tool_calling
+                    else {
+                        "role": "assistant",
+                        "content": [
+                            *msg_text_content,
+                            *[MessageTextContent(text=to_json(t, indent=2)).model_dump() for t in msg_tool_calls],
+                        ]
+                        or None,
+                    }
                 )
+
+                messages.append(exclude_none(new_msg))
             else:
                 messages.append(message.to_plain())
 
-        tools = (
-            [
-                {
-                    "type": "function",
-                    "function": {
-                        "name": tool.name,
-                        "description": tool.description,
-                        "parameters": self._format_tool_model(tool.input_schema),
-                    },
-                }
-                for tool in input.tools
-            ]
-            if input.tools
-            else None
-        )
+        tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": tool.name,
+                    "description": tool.description,
+                    "parameters": self._format_tool_model(tool.input_schema),
+                },
+            }
+            for tool in input.tools or []
+        ]
 
         settings = exclude_keys(
             self._settings | input.model_dump(exclude_unset=True),
@@ -196,17 +223,17 @@ def _transform_input(self, input: ChatModelInput) -> dict[str, Any]:
             else input.tool_choice
         )
 
-        return (
+        return exclude_none(
             exclude_none(settings)
             | exclude_none(params)
             | {
                 "model": f"{self._litellm_provider_id}/{self.model_id}",
                 "messages": messages,
-                "tools": tools,
+                "tools": tools if tools else None,
                 "response_format": self._format_response_model(input.response_format)
                 if input.response_format
                 else None,
-                "tool_choice": tool_choice,
+                "tool_choice": tool_choice if tools else None,
             }
         )
 
diff --git a/python/beeai_framework/adapters/ollama/backend/chat.py b/python/beeai_framework/adapters/ollama/backend/chat.py
index 3b032e7a5..5e7f581d8 100644
--- a/python/beeai_framework/adapters/ollama/backend/chat.py
+++ b/python/beeai_framework/adapters/ollama/backend/chat.py
@@ -12,13 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-
 import os
-from typing import Any
+from typing import Any, ClassVar
 
 from pydantic import BaseModel
+from typing_extensions import Unpack
 
 from beeai_framework.adapters.litellm.chat import LiteLLMChatModel
+from beeai_framework.backend.chat import ChatModelKwargs
 from beeai_framework.backend.constants import ProviderName
 from beeai_framework.logger import Logger
 
@@ -26,11 +27,15 @@
 
 
 class OllamaChatModel(LiteLLMChatModel):
+    tool_choice_support: ClassVar[set[str]] = set()
+
     @property
     def provider_id(self) -> ProviderName:
         return "ollama"
 
-    def __init__(self, model_id: str | None = None, settings: dict[str, Any] | None = None) -> None:
+    def __init__(
+        self, model_id: str | None = None, settings: dict[str, Any] | None = None, **kwargs: Unpack[ChatModelKwargs]
+    ) -> None:
         settings = settings.copy() if settings is not None else {}
 
         api_key = settings.get("api_key", os.getenv("OLLAMA_API_KEY") or "ollama")
@@ -42,13 +47,15 @@ def __init__(self, model_id: str | None = None, settings: dict[str, Any] | None
             model_id if model_id else os.getenv("OLLAMA_CHAT_MODEL", "llama3.1"),
             provider_id="openai",
             settings=settings | {"api_key": api_key, "base_url": base_url},
+            **kwargs,
         )
 
     def _format_response_model(self, model: type[BaseModel] | dict[str, Any]) -> dict[str, Any]:
-        if isinstance(model, dict):
-            return model
-
         return {
             "type": "json_schema",
-            "json_schema": {"schema": model.model_json_schema(), "name": model.__name__, "strict": True},
+            "json_schema": {
+                "schema": model if isinstance(model, dict) else model.model_json_schema(),
+                "name": "schema" if isinstance(model, dict) else model.__name__,
+                "strict": True,
+            },
         }
diff --git a/python/beeai_framework/adapters/watsonx/backend/chat.py b/python/beeai_framework/adapters/watsonx/backend/chat.py
index b19227e53..582b26628 100644
--- a/python/beeai_framework/adapters/watsonx/backend/chat.py
+++ b/python/beeai_framework/adapters/watsonx/backend/chat.py
@@ -14,7 +14,7 @@
 
 
 import os
-from typing import Any
+from typing import Any, ClassVar
 
 from beeai_framework.adapters.litellm.chat import LiteLLMChatModel
 from beeai_framework.backend.constants import ProviderName
@@ -24,6 +24,8 @@
 
 
 class WatsonxChatModel(LiteLLMChatModel):
+    tool_choice_support: ClassVar[set[str]] = {"none", "single", "auto"}
+
     @property
     def provider_id(self) -> ProviderName:
         return "watsonx"
diff --git a/python/beeai_framework/backend/chat.py b/python/beeai_framework/backend/chat.py
index 705e5701d..1d1c919b8 100644
--- a/python/beeai_framework/backend/chat.py
+++ b/python/beeai_framework/backend/chat.py
@@ -12,12 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import json
 from abc import ABC, abstractmethod
 from collections.abc import AsyncGenerator, Callable
 from functools import cached_property
-from typing import Any, Literal, TypeVar
+from typing import Any, ClassVar, Literal, TypeVar
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field, InstanceOf, TypeAdapter
+from typing_extensions import TypedDict, Unpack
 
 from beeai_framework.backend.constants import ProviderName
 from beeai_framework.backend.errors import ChatModelError
@@ -28,7 +30,7 @@
     ChatModelSuccessEvent,
     chat_model_event_types,
 )
-from beeai_framework.backend.message import AnyMessage, SystemMessage
+from beeai_framework.backend.message import AnyMessage, MessageToolCallContent, SystemMessage
 from beeai_framework.backend.types import (
     ChatModelCache,
     ChatModelInput,
@@ -36,9 +38,15 @@
     ChatModelParameters,
     ChatModelStructureInput,
     ChatModelStructureOutput,
+    ChatModelToolChoice,
+)
+from beeai_framework.backend.utils import (
+    filter_tools_by_tool_choice,
+    generate_tool_union_schema,
+    load_model,
+    parse_broken_json,
+    parse_model,
 )
-from beeai_framework.backend.utils import load_model, parse_broken_json, parse_model
-from beeai_framework.cache.base import BaseCache
 from beeai_framework.cache.null_cache import NullCache
 from beeai_framework.cancellation import AbortController, AbortSignal
 from beeai_framework.context import Run, RunContext
@@ -46,17 +54,34 @@
 from beeai_framework.logger import Logger
 from beeai_framework.retryable import Retryable, RetryableConfig, RetryableContext, RetryableInput
 from beeai_framework.template import PromptTemplate, PromptTemplateInput
-from beeai_framework.tools.tool import AnyTool
+from beeai_framework.tools.tool import AnyTool, Tool
 from beeai_framework.utils.asynchronous import to_async_generator
 from beeai_framework.utils.models import ModelLike
-from beeai_framework.utils.strings import to_json
+from beeai_framework.utils.strings import generate_random_string, to_json
 
 T = TypeVar("T", bound=BaseModel)
+TTool = TypeVar("TTool", bound=AnyTool)
 ChatModelFinishReason: Literal["stop", "length", "function_call", "content_filter", "null"]
 logger = Logger(__name__)
 
 
+class ChatModelKwargs(TypedDict, total=False):
+    tool_call_fallback_via_response_format: bool
+    model_supports_tool_calling: bool
+    parameters: InstanceOf[ChatModelParameters]
+    cache: InstanceOf[ChatModelCache]
+
+    __pydantic_config__ = ConfigDict(extra="forbid")  # type: ignore
+
+
+_ChatModelKwargsAdapter = TypeAdapter(ChatModelKwargs)
+
+
 class ChatModel(ABC):
+    tool_choice_support: ClassVar[set[str]] = {"required", "none", "single", "auto"}
+    tool_call_fallback_via_response_format: bool
+    model_supports_tool_calling: bool
+
     @property
     @abstractmethod
     def model_id(self) -> str:
@@ -67,9 +92,12 @@ def model_id(self) -> str:
     def provider_id(self) -> ProviderName:
         pass
 
-    def __init__(self) -> None:
-        self.parameters = ChatModelParameters()
-        self.cache: ChatModelCache = NullCache[list[ChatModelOutput]]()
+    def __init__(self, **kwargs: Unpack[ChatModelKwargs]) -> None:
+        kwargs = _ChatModelKwargsAdapter.validate_python(kwargs)
+        self.parameters = kwargs.get("parameters", ChatModelParameters())
+        self.cache = kwargs.get("cache", NullCache[list[ChatModelOutput]]())
+        self.tool_call_fallback_via_response_format = kwargs.get("tool_call_fallback_via_response_format", True)
+        self.model_supports_tool_calling = kwargs.get("model_supports_tool_calling", True)
 
     @cached_property
     def emitter(self) -> Emitter:
@@ -104,9 +132,11 @@ async def _create_structure(
         input: ChatModelStructureInput[T],
         run: RunContext,
     ) -> ChatModelStructureOutput:
-        schema: type[T] = input.input_schema
-
-        json_schema = schema.model_json_schema(mode="serialization") if issubclass(schema, BaseModel) else schema
+        json_schema: dict[str, Any] = (
+            input.input_schema
+            if isinstance(input.input_schema, dict)
+            else input.input_schema.model_json_schema(mode="serialization")
+        )
 
         class DefaultChatModelStructureSchema(BaseModel):
             input_schema: type[str] = Field(..., alias="schema")
@@ -166,26 +196,36 @@ def create(
         *,
         messages: list[AnyMessage],
         tools: list[AnyTool] | None = None,
-        tool_choice: AnyTool | Literal["required"] | Literal["none"] | None = None,
+        tool_choice: ChatModelToolChoice | None = None,
         abort_signal: AbortSignal | None = None,
         stop_sequences: list[str] | None = None,
         response_format: dict[str, Any] | type[BaseModel] | None = None,
         stream: bool | None = None,
         **kwargs: Any,
     ) -> Run[ChatModelOutput]:
+        force_tool_call_via_response_format = self._force_tool_call_via_response_format(
+            tool_choice=tool_choice,
+            tools=tools or [],
+            has_custom_response_format=bool(response_format),
+        )
+
         model_input = ChatModelInput(
             messages=messages,
-            tools=tools or [],
+            tools=tools if self.model_supports_tool_calling else None,
+            tool_choice=tool_choice,
             abort_signal=abort_signal,
             stop_sequences=stop_sequences,
-            response_format=response_format,
+            response_format=(
+                generate_tool_union_schema(filter_tools_by_tool_choice(tools, tool_choice))
+                if force_tool_call_via_response_format and tools
+                else response_format
+            ),
             stream=stream,
-            tool_choice=tool_choice,
             **kwargs,
         )
 
         async def handler(context: RunContext) -> ChatModelOutput:
-            cache_key = BaseCache.generate_key(model_input, {"messages": [m.to_plain() for m in model_input.messages]})
+            cache_key = self.cache.generate_key(model_input, {"messages": [m.to_plain() for m in model_input.messages]})
             cache_hit = await self.cache.get(cache_key)
 
             try:
@@ -210,11 +250,25 @@ async def handler(context: RunContext) -> ChatModelOutput:
                     result = ChatModelOutput.from_chunks(chunks)
                 else:
                     if cache_hit:
-                        result = cache_hit[0]
+                        result = cache_hit[0].model_copy()
                     else:
                         result = await self._create(model_input, context)
                         await self.cache.set(cache_key, [result])
 
+                if force_tool_call_via_response_format and not result.get_tool_calls():
+                    msg = result.messages[-1]
+                    tool_call: dict[str, Any] = parse_broken_json(msg.text)
+                    if not tool_call:
+                        raise ChatModelError(f"Failed to produce a valid tool call. Generated output: '{msg.text}'")
+
+                    tool_call_content = MessageToolCallContent(
+                        id=f"call_{generate_random_string(8).lower()}",
+                        tool_name=tool_call["name"],
+                        args=json.dumps(tool_call["parameters"]),
+                    )
+                    msg.content.clear()
+                    msg.content.append(tool_call_content)
+
                 await context.emitter.emit("success", ChatModelSuccessEvent(value=result))
                 return result
             except Exception as ex:
@@ -236,7 +290,7 @@ async def handler(context: RunContext) -> ChatModelOutput:
     def create_structure(
         self,
         *,
-        schema: type[T],
+        schema: type[T] | dict[str, Any],
         messages: list[AnyMessage],
         abort_signal: AbortSignal | None = None,
         max_retries: int | None = None,
@@ -268,10 +322,37 @@ def config(
             self.parameters = parameters(self.parameters) if callable(parameters) else parameters
 
     @staticmethod
-    def from_name(name: str | ProviderName, options: ModelLike[ChatModelParameters] | None = None) -> "ChatModel":
+    def from_name(
+        name: str | ProviderName, options: ModelLike[ChatModelParameters] | None = None, **kwargs: Any
+    ) -> "ChatModel":
         parsed_model = parse_model(name)
         TargetChatModel = load_model(parsed_model.provider_id, "chat")  # type: ignore # noqa: N806
 
         settings = options.model_dump() if isinstance(options, ChatModelParameters) else options
 
-        return TargetChatModel(parsed_model.model_id, settings=settings or {})  # type: ignore
+        return TargetChatModel(parsed_model.model_id, settings=settings or {}, **kwargs)  # type: ignore
+
+    def _force_tool_call_via_response_format(
+        self,
+        *,
+        tool_choice: ChatModelToolChoice | None,
+        tools: list[AnyTool],
+        has_custom_response_format: bool,
+    ) -> bool:
+        if (
+            not tools
+            or tool_choice == "none"
+            or tool_choice == "auto"
+            or tool_choice is None
+            or has_custom_response_format
+            or not self.tool_call_fallback_via_response_format
+        ):
+            return False
+
+        tool_choice_supported = not tool_choice or (
+            "single" in self.tool_choice_support
+            if isinstance(tool_choice, Tool)
+            else tool_choice in self.tool_choice_support
+        )
+
+        return not self.model_supports_tool_calling or not tool_choice_supported
diff --git a/python/beeai_framework/backend/message.py b/python/beeai_framework/backend/message.py
index 33844f5fd..69efb0f85 100644
--- a/python/beeai_framework/backend/message.py
+++ b/python/beeai_framework/backend/message.py
@@ -27,6 +27,7 @@
 from beeai_framework.utils.models import to_any_model, to_model
 
 T = TypeVar("T", bound=BaseModel)
+T2 = TypeVar("T2")
 MessageMeta = dict[str, Any]
 
 
@@ -107,6 +108,9 @@ def text(self) -> str:
     def get_texts(self) -> list[MessageTextContent]:
         return [cont for cont in self.content if isinstance(cont, MessageTextContent)]
 
+    def get_by_type(self, tp: type[T2]) -> list[T2]:
+        return [cont for cont in self.content if isinstance(cont, tp)]
+
     def to_plain(self) -> dict[str, Any]:
         return {
             "role": self.role.value if isinstance(self.role, enum.Enum) else self.role,
@@ -193,7 +197,7 @@ def __init__(
             [
                 MessageTextContent(text=c)
                 if isinstance(c, str)
-                else to_any_model([MessageToolCallContent, MessageTextContent], cast(UserMessageContent, c))
+                else to_any_model([MessageImageContent, MessageTextContent], cast(UserMessageContent, c))
                 for c in cast_list(content)
             ],
             meta,
diff --git a/python/beeai_framework/backend/types.py b/python/beeai_framework/backend/types.py
index 2dbb912aa..913099f17 100644
--- a/python/beeai_framework/backend/types.py
+++ b/python/beeai_framework/backend/types.py
@@ -23,6 +23,7 @@
 from beeai_framework.utils.lists import flatten
 
 T = TypeVar("T", bound=BaseModel)
+ChatModelToolChoice = AnyTool | Literal["required"] | Literal["none"] | Literal["auto"]
 
 
 class ChatModelParameters(BaseModel):
@@ -39,7 +40,7 @@ class ChatModelParameters(BaseModel):
 
 
 class ChatModelStructureInput(ChatModelParameters, Generic[T]):
-    input_schema: type[T] = Field(..., alias="schema")
+    input_schema: type[T] | dict[str, Any] = Field(..., alias="schema")
     messages: list[InstanceOf[AnyMessage]] = Field(..., min_length=1)
     abort_signal: AbortSignal | None = None
     max_retries: int | None = None
@@ -50,6 +51,8 @@ class ChatModelStructureOutput(BaseModel):
 
 
 class ChatModelInput(ChatModelParameters):
+    model_config = ConfigDict(frozen=True)
+
     tools: list[InstanceOf[AnyTool]] | None = None
     tool_choice: InstanceOf[AnyTool] | Literal["required"] | Literal["auto"] | Literal["none"] | None = None
     abort_signal: AbortSignal | None = None
@@ -61,8 +64,6 @@ class ChatModelInput(ChatModelParameters):
         frozen=True,
     )
 
-    model_config = ConfigDict(frozen=True)
-
 
 class ChatModelUsage(BaseModel):
     prompt_tokens: int
diff --git a/python/beeai_framework/backend/utils.py b/python/beeai_framework/backend/utils.py
index b80dd3d67..60923db18 100644
--- a/python/beeai_framework/backend/utils.py
+++ b/python/beeai_framework/backend/utils.py
@@ -14,9 +14,11 @@
 
 
 from importlib import import_module
-from typing import Any, Literal, TypeVar
+from typing import Any, Literal, TypeVar, Union
 
 import json_repair
+import jsonref  # type: ignore
+from pydantic import ConfigDict, Field, RootModel, create_model
 
 from beeai_framework.backend.constants import (
     BackendProviders,
@@ -25,6 +27,8 @@
     ProviderName,
 )
 from beeai_framework.backend.errors import BackendError
+from beeai_framework.backend.types import ChatModelToolChoice
+from beeai_framework.tools.tool import AnyTool, Tool
 
 T = TypeVar("T")
 
@@ -72,3 +76,59 @@ def load_model(name: ProviderName | str, model_type: Literal["embedding", "chat"
 
 def parse_broken_json(input: str) -> Any:
     return json_repair.loads(input)
+
+
+def inline_schema_refs(schema: dict[str, Any]) -> dict[str, Any]:
+    if schema.get("$defs") is not None:
+        schema = jsonref.replace_refs(
+            schema, base_uri="", load_on_repr=True, merge_props=True, proxies=False, lazy_load=False
+        )
+        schema.pop("$defs", None)
+
+    return schema
+
+
+def generate_tool_union_schema(tools: list[AnyTool]) -> dict[str, Any]:
+    if not tools:
+        raise ValueError("No tools provided!")
+
+    tool_schemas = [
+        create_model(  # type: ignore
+            tool.name,
+            __module__="fn",
+            __config__=ConfigDict(extra="forbid", populate_by_name=True, title=tool.name),
+            **{
+                "name": (Literal[tool.name], Field(description="Tool Name")),
+                "parameters": (tool.input_schema, Field(description="Tool Parameters")),
+            },
+        )
+        for tool in tools
+    ]
+
+    if len(tool_schemas) == 1:
+        schema = tool_schemas[0].model_json_schema()
+    else:
+
+        class AvailableTools(RootModel[Union[*tool_schemas]]):  # type: ignore
+            pass
+
+        schema = AvailableTools.model_json_schema()
+
+    return inline_schema_refs(schema)
+
+
+def filter_tools_by_tool_choice(tools: list[AnyTool], value: ChatModelToolChoice | None) -> list[AnyTool]:
+    if value == "none":
+        return []
+
+    if value == "required" or value == "auto" or value is None:
+        return tools
+
+    if isinstance(value, Tool):
+        tool = [tool for tool in tools if tool is value]
+        if not tool:
+            raise ValueError("Invalid tool choice provided! Tool was not found.")
+
+        return tool
+
+    raise RuntimeError(f"Unknown tool choice: {value}")
diff --git a/python/beeai_framework/utils/strings.py b/python/beeai_framework/utils/strings.py
index b3581bc4e..f59595cfa 100644
--- a/python/beeai_framework/utils/strings.py
+++ b/python/beeai_framework/utils/strings.py
@@ -13,7 +13,9 @@
 # limitations under the License.
 
 import json
+import random
 import re
+import string
 from collections.abc import Sequence
 from enum import StrEnum
 from typing import Any, cast
@@ -51,3 +53,7 @@ def to_json(input: Any, *, indent: int | None = None) -> str:
 def to_safe_word(phrase: str) -> str:
     # replace any non-alphanumeric char with _
     return re.sub(r"\W+", "_", phrase).lower()
+
+
+def generate_random_string(length: int) -> str:
+    return "".join(random.choices(string.ascii_uppercase + string.digits, k=length))
diff --git a/python/examples/backend/providers/ollama.py b/python/examples/backend/providers/ollama.py
index 57d268aa2..d3ed5ec47 100644
--- a/python/examples/backend/providers/ollama.py
+++ b/python/examples/backend/providers/ollama.py
@@ -1,18 +1,22 @@
 import asyncio
+import json
 import sys
 import traceback
+from datetime import UTC, datetime
 
 from pydantic import BaseModel, Field
 
+from beeai_framework import SystemMessage
 from beeai_framework.adapters.ollama.backend.chat import OllamaChatModel
 from beeai_framework.backend.chat import ChatModel
 from beeai_framework.backend.events import ChatModelNewTokenEvent
-from beeai_framework.backend.message import UserMessage
+from beeai_framework.backend.message import AnyMessage, MessageToolResultContent, ToolMessage, UserMessage
 from beeai_framework.cancellation import AbortSignal
 from beeai_framework.emitter import EventMeta
 from beeai_framework.errors import AbortError, FrameworkError
 from beeai_framework.parsers.field import ParserField
 from beeai_framework.parsers.line_prefix import LinePrefixParser, LinePrefixParserNode
+from beeai_framework.tools.weather.openmeteo import OpenMeteoTool
 
 
 async def ollama_from_name() -> None:
@@ -90,6 +94,32 @@ async def on_new_token(data: ChatModelNewTokenEvent, event: EventMeta) -> None:
     print(result)
 
 
+async def ollama_tool_calling() -> None:
+    llm = OllamaChatModel("llama3.1")
+    weather_tool = OpenMeteoTool()
+    messages: list[AnyMessage] = [
+        SystemMessage(
+            f"""You are a helpful assistant that uses tools to provide answers.
+Current date is {datetime.now(tz=UTC).date()!s}
+"""
+        ),
+        UserMessage("What is the current weather in Berlin?"),
+    ]
+    response = await llm.create(messages=messages, tools=[weather_tool], tool_choice="required")
+    messages.extend(response.messages)
+    tool_call_msg = response.get_tool_calls()[0]
+    print(tool_call_msg.model_dump())
+    tool_response = await weather_tool.run(json.loads(tool_call_msg.args))
+    tool_response_msg = ToolMessage(
+        MessageToolResultContent(
+            result=tool_response.get_text_content(), tool_name=tool_call_msg.tool_name, tool_call_id=tool_call_msg.id
+        )
+    )
+    print(tool_response_msg.to_plain())
+    final_response = await llm.create(messages=[*messages, tool_response_msg], tools=[])
+    print(final_response.get_text_content())
+
+
 async def main() -> None:
     print("*" * 10, "ollama_from_name")
     await ollama_from_name()
@@ -105,6 +135,8 @@ async def main() -> None:
     await ollama_structure()
     print("*" * 10, "ollama_stream_parser")
     await ollama_stream_parser()
+    print("*" * 10, "ollama_tool_calling")
+    await ollama_tool_calling()
 
 
 if __name__ == "__main__":
diff --git a/python/poetry.lock b/python/poetry.lock
index 61bff9184..e96abbc14 100644
--- a/python/poetry.lock
+++ b/python/poetry.lock
@@ -253,18 +253,18 @@ tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" a
 
 [[package]]
 name = "boto3"
-version = "1.37.19"
+version = "1.37.22"
 description = "The AWS SDK for Python"
 optional = true
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "boto3-1.37.19-py3-none-any.whl", hash = "sha256:fbfc2c43ad686b63c8aa02aee634c269f856eed68941d8e570cc45950be52130"},
-    {file = "boto3-1.37.19.tar.gz", hash = "sha256:c69c90500f18fd72d782d1612170b7d3db9a98ed51a4da3bebe38e693497ebf8"},
+    {file = "boto3-1.37.22-py3-none-any.whl", hash = "sha256:a14324d5fa5f4fea00c0e3c69754cbd28100f7fe194693eeecf2dc07446cf4ef"},
+    {file = "boto3-1.37.22.tar.gz", hash = "sha256:78a0ec0aafbf6044104c98ad80b69e6d1c83d8233fda2c2d241029e6c705c510"},
 ]
 
 [package.dependencies]
-botocore = ">=1.37.19,<1.38.0"
+botocore = ">=1.37.22,<1.38.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.11.0,<0.12.0"
 
@@ -273,14 +273,14 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.37.19"
+version = "1.37.22"
 description = "Low-level, data-driven core of boto 3."
 optional = true
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "botocore-1.37.19-py3-none-any.whl", hash = "sha256:6e1337e73a6b8146c1ec20a6a72d67e2809bd4c0af076431fe6e1561e0c89415"},
-    {file = "botocore-1.37.19.tar.gz", hash = "sha256:eadcdc37de09df25cf1e62e8106660c61f60a68e984acfc1a8d43fb6267e53b8"},
+    {file = "botocore-1.37.22-py3-none-any.whl", hash = "sha256:184db7c9314d13002bc827f511a5140574b5da1acda342d51e093dad6317de98"},
+    {file = "botocore-1.37.22.tar.gz", hash = "sha256:b3b26f1a90236bcd17d4092f8c85a256b44e9955a16b633319a2f5678d605e9f"},
 ]
 
 [package.dependencies]
@@ -739,14 +739,14 @@ files = [
 
 [[package]]
 name = "duckduckgo-search"
-version = "7.5.3"
+version = "7.5.5"
 description = "Search for words, documents, images, news, maps and text translation using the DuckDuckGo.com search engine."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "duckduckgo_search-7.5.3-py3-none-any.whl", hash = "sha256:0a5ae49f437d12caeb2ddf2f639057801b8dd7114fa1d1bda3aca15c31eae93f"},
-    {file = "duckduckgo_search-7.5.3.tar.gz", hash = "sha256:401757168f9c3521919bfc5e11b4e1a28cc6cde94c5326ff0eed683d27830fa9"},
+    {file = "duckduckgo_search-7.5.5-py3-none-any.whl", hash = "sha256:c71a0661aa436f215d9a05d653af424affb58825ab3e79f3b788053cbdee9ebc"},
+    {file = "duckduckgo_search-7.5.5.tar.gz", hash = "sha256:44ef03bfa5484bada786590f2d4c213251131765721383a177a0da6fa5c5e41a"},
 ]
 
 [package.dependencies]
@@ -1349,6 +1349,18 @@ files = [
     {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
 ]
 
+[[package]]
+name = "jsonref"
+version = "1.1.0"
+description = "jsonref is a library for automatic dereferencing of JSON Reference objects for Python."
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "jsonref-1.1.0-py3-none-any.whl", hash = "sha256:590dc7773df6c21cbf948b5dac07a72a251db28b0238ceecce0a2abfa8ec30a9"},
+    {file = "jsonref-1.1.0.tar.gz", hash = "sha256:32fe8e1d85af0fdefbebce950af85590b22b60f9e95443176adbde4e1ecea552"},
+]
+
 [[package]]
 name = "jsonschema"
 version = "4.23.0"
@@ -1476,15 +1488,15 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.48"
+version = "0.3.49"
 description = "Building applications with LLMs through composability"
 optional = true
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 markers = "extra == \"langchain\""
 files = [
-    {file = "langchain_core-0.3.48-py3-none-any.whl", hash = "sha256:21e4fe84262b9c7ad8aefe7816439ede130893f8a64b8c965cd9695c2be91c73"},
-    {file = "langchain_core-0.3.48.tar.gz", hash = "sha256:be4b2fe36d8a11fb4b6b13e0808b12aea9f25e345624ffafe1d606afb6059f21"},
+    {file = "langchain_core-0.3.49-py3-none-any.whl", hash = "sha256:893ee42c9af13bf2a2d8c2ec15ba00a5c73cccde21a2bd005234ee0e78a2bdf8"},
+    {file = "langchain_core-0.3.49.tar.gz", hash = "sha256:d9dbff9bac0021463a986355c13864d6a68c41f8559dbbd399a68e1ebd9b04b9"},
 ]
 
 [package.dependencies]
@@ -1517,15 +1529,15 @@ langchain-core = ">=0.3.45,<1.0.0"
 
 [[package]]
 name = "langsmith"
-version = "0.3.18"
+version = "0.3.19"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = true
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 markers = "extra == \"langchain\""
 files = [
-    {file = "langsmith-0.3.18-py3-none-any.whl", hash = "sha256:7ad65ec26084312a039885ef625ae72a69ad089818b64bacf7ce6daff672353a"},
-    {file = "langsmith-0.3.18.tar.gz", hash = "sha256:18ff2d8f2e77b375485e4fb3d0dbf7b30fabbd438c7347c3534470e9b7d187b8"},
+    {file = "langsmith-0.3.19-py3-none-any.whl", hash = "sha256:a306962ab53562c4094192f1da964309b48aac7898f82d1d421c3fb9c3f29367"},
+    {file = "langsmith-0.3.19.tar.gz", hash = "sha256:0133676689b5e1b879ed05a18e18570daf0dd05e0cefc397342656a58ebecbc5"},
 ]
 
 [package.dependencies]
@@ -1542,20 +1554,20 @@ zstandard = ">=0.23.0,<0.24.0"
 
 [package.extras]
 langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
-openai-agents = ["openai-agents (>=0.0.3,<0.0.4)"]
+openai-agents = ["openai-agents (>=0.0.3,<0.1)"]
 otel = ["opentelemetry-api (>=1.30.0,<2.0.0)", "opentelemetry-exporter-otlp-proto-http (>=1.30.0,<2.0.0)", "opentelemetry-sdk (>=1.30.0,<2.0.0)"]
 pytest = ["pytest (>=7.0.0)", "rich (>=13.9.4,<14.0.0)"]
 
 [[package]]
 name = "litellm"
-version = "1.63.14"
+version = "1.64.1"
 description = "Library to easily interface with LLM API providers"
 optional = false
 python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
 groups = ["main"]
 files = [
-    {file = "litellm-1.63.14-py3-none-any.whl", hash = "sha256:d4c469f5990e142cc23dfa06c3fddd627001928e4df43682001f453af6a1fb51"},
-    {file = "litellm-1.63.14.tar.gz", hash = "sha256:9cffe19d8140c33a2f777c5b2e8b8175ffe03979aac341b8538d6e6d143bd640"},
+    {file = "litellm-1.64.1-py3-none-any.whl", hash = "sha256:bd7cb4977dee121551f0322d48b4e51e9a508fc2ac2273e7c5405ca69354e352"},
+    {file = "litellm-1.64.1.tar.gz", hash = "sha256:73bac891b1fbd77ada4d691e967657c53f48c207d9c3ba414ad0ffe3e7ec8f89"},
 ]
 
 [package.dependencies]
@@ -1572,8 +1584,8 @@ tiktoken = ">=0.7.0"
 tokenizers = "*"
 
 [package.extras]
-extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "resend (>=0.8.0,<0.9.0)"]
-proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "boto3 (==1.34.34)", "cryptography (>=43.0.1,<44.0.0)", "fastapi (>=0.115.5,<0.116.0)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=23.0.0,<24.0.0)", "orjson (>=3.9.7,<4.0.0)", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rq", "uvicorn (>=0.29.0,<0.30.0)", "uvloop (>=0.21.0,<0.22.0)", "websockets (>=13.1.0,<14.0.0)"]
+extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "redisvl (>=0.4.1,<0.5.0) ; python_version >= \"3.9\" and python_version < \"3.14\"", "resend (>=0.8.0,<0.9.0)"]
+proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "boto3 (==1.34.34)", "cryptography (>=43.0.1,<44.0.0)", "fastapi (>=0.115.5,<0.116.0)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=23.0.0,<24.0.0)", "mcp (==1.5.0) ; python_version >= \"3.10\"", "orjson (>=3.9.7,<4.0.0)", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rq", "uvicorn (>=0.29.0,<0.30.0)", "uvloop (>=0.21.0,<0.22.0)", "websockets (>=13.1.0,<14.0.0)"]
 
 [[package]]
 name = "lxml"
@@ -1836,14 +1848,14 @@ files = [
 
 [[package]]
 name = "mcp"
-version = "1.5.0"
+version = "1.6.0"
 description = "Model Context Protocol SDK"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "mcp-1.5.0-py3-none-any.whl", hash = "sha256:51c3f35ce93cb702f7513c12406bbea9665ef75a08db909200b07da9db641527"},
-    {file = "mcp-1.5.0.tar.gz", hash = "sha256:5b2766c05e68e01a2034875e250139839498c61792163a7b221fc170c12f5aa9"},
+    {file = "mcp-1.6.0-py3-none-any.whl", hash = "sha256:7bd24c6ea042dbec44c754f100984d186620d8b841ec30f1b19eda9b93a634d0"},
+    {file = "mcp-1.6.0.tar.gz", hash = "sha256:d9324876de2c5637369f43161cd71eebfd803df5a95e46225cab8d280e366723"},
 ]
 
 [package.dependencies]
@@ -2134,14 +2146,14 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.68.2"
+version = "1.69.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "openai-1.68.2-py3-none-any.whl", hash = "sha256:24484cb5c9a33b58576fdc5acf0e5f92603024a4e39d0b99793dfa1eb14c2b36"},
-    {file = "openai-1.68.2.tar.gz", hash = "sha256:b720f0a95a1dbe1429c0d9bb62096a0d98057bcda82516f6e8af10284bdd5b19"},
+    {file = "openai-1.69.0-py3-none-any.whl", hash = "sha256:73c4b2ddfd050060f8d93c70367189bd891e70a5adb6d69c04c3571f4fea5627"},
+    {file = "openai-1.69.0.tar.gz", hash = "sha256:7b8a10a8ff77e1ae827e5e4c8480410af2070fb68bc973d6c994cf8218f1f98d"},
 ]
 
 [package.dependencies]
@@ -2369,110 +2381,110 @@ wcwidth = "*"
 
 [[package]]
 name = "propcache"
-version = "0.3.0"
+version = "0.3.1"
 description = "Accelerated property cache"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "propcache-0.3.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:efa44f64c37cc30c9f05932c740a8b40ce359f51882c70883cc95feac842da4d"},
-    {file = "propcache-0.3.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:2383a17385d9800b6eb5855c2f05ee550f803878f344f58b6e194de08b96352c"},
-    {file = "propcache-0.3.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d3e7420211f5a65a54675fd860ea04173cde60a7cc20ccfbafcccd155225f8bc"},
-    {file = "propcache-0.3.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3302c5287e504d23bb0e64d2a921d1eb4a03fb93a0a0aa3b53de059f5a5d737d"},
-    {file = "propcache-0.3.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7e2e068a83552ddf7a39a99488bcba05ac13454fb205c847674da0352602082f"},
-    {file = "propcache-0.3.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2d913d36bdaf368637b4f88d554fb9cb9d53d6920b9c5563846555938d5450bf"},
-    {file = "propcache-0.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8ee1983728964d6070ab443399c476de93d5d741f71e8f6e7880a065f878e0b9"},
-    {file = "propcache-0.3.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:36ca5e9a21822cc1746023e88f5c0af6fce3af3b85d4520efb1ce4221bed75cc"},
-    {file = "propcache-0.3.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:9ecde3671e62eeb99e977f5221abcf40c208f69b5eb986b061ccec317c82ebd0"},
-    {file = "propcache-0.3.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:d383bf5e045d7f9d239b38e6acadd7b7fdf6c0087259a84ae3475d18e9a2ae8b"},
-    {file = "propcache-0.3.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:8cb625bcb5add899cb8ba7bf716ec1d3e8f7cdea9b0713fa99eadf73b6d4986f"},
-    {file = "propcache-0.3.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5fa159dcee5dba00c1def3231c249cf261185189205073bde13797e57dd7540a"},
-    {file = "propcache-0.3.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:a7080b0159ce05f179cfac592cda1a82898ca9cd097dacf8ea20ae33474fbb25"},
-    {file = "propcache-0.3.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:ed7161bccab7696a473fe7ddb619c1d75963732b37da4618ba12e60899fefe4f"},
-    {file = "propcache-0.3.0-cp310-cp310-win32.whl", hash = "sha256:bf0d9a171908f32d54f651648c7290397b8792f4303821c42a74e7805bfb813c"},
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 [package.dependencies]
@@ -3045,115 +3057,126 @@ requests = ">=2.0.1,<3.0.0"
 
 [[package]]
 name = "rpds-py"
-version = "0.23.1"
+version = "0.24.0"
 description = "Python bindings to Rust's persistent data structures (rpds)"
 optional = false
 python-versions = ">=3.9"
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-aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
-asyncio = ["greenlet (!=0.4.17)"]
-asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
+aiomysql = ["aiomysql (>=0.2.0)", "greenlet (>=1)"]
+aioodbc = ["aioodbc", "greenlet (>=1)"]
+aiosqlite = ["aiosqlite", "greenlet (>=1)", "typing_extensions (!=3.10.0.1)"]
+asyncio = ["greenlet (>=1)"]
+asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (>=1)"]
 mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5,!=1.1.10)"]
 mssql = ["pyodbc"]
 mssql-pymssql = ["pymssql"]
@@ -3335,7 +3358,7 @@ mysql-connector = ["mysql-connector-python"]
 oracle = ["cx_oracle (>=8)"]
 oracle-oracledb = ["oracledb (>=1.0.1)"]
 postgresql = ["psycopg2 (>=2.7)"]
-postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
+postgresql-asyncpg = ["asyncpg", "greenlet (>=1)"]
 postgresql-pg8000 = ["pg8000 (>=1.29.1)"]
 postgresql-psycopg = ["psycopg (>=3.0.7)"]
 postgresql-psycopg2binary = ["psycopg2-binary"]
@@ -3509,14 +3532,14 @@ files = [
 
 [[package]]
 name = "tox"
-version = "4.24.2"
+version = "4.25.0"
 description = "tox is a generic virtualenv management and test command line tool"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
 files = [
-    {file = "tox-4.24.2-py3-none-any.whl", hash = "sha256:92e8290e76ad4e15748860a205865696409a2d014eedeb796a34a0f3b5e7336e"},
-    {file = "tox-4.24.2.tar.gz", hash = "sha256:d5948b350f76fae436d6545a5e87c2b676ab7a0d7d88c1308651245eadbe8aea"},
+    {file = "tox-4.25.0-py3-none-any.whl", hash = "sha256:4dfdc7ba2cc6fdc6688dde1b21e7b46ff6c41795fb54586c91a3533317b5255c"},
+    {file = "tox-4.25.0.tar.gz", hash = "sha256:dd67f030317b80722cf52b246ff42aafd3ed27ddf331c415612d084304cf5e52"},
 ]
 
 [package.dependencies]
@@ -3612,14 +3635,14 @@ urllib3 = ">=2"
 
 [[package]]
 name = "typing-extensions"
-version = "4.12.2"
+version = "4.13.0"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
 files = [
-    {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
-    {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
+    {file = "typing_extensions-4.13.0-py3-none-any.whl", hash = "sha256:c8dd92cc0d6425a97c18fbb9d1954e5ff92c1ca881a309c45f06ebc0b79058e5"},
+    {file = "typing_extensions-4.13.0.tar.gz", hash = "sha256:0a4ac55a5820789d87e297727d229866c9650f6521b64206413c4fbada24d95b"},
 ]
 
 [[package]]
@@ -3639,6 +3662,21 @@ files = [
 mypy-extensions = ">=0.3.0"
 typing-extensions = ">=3.7.4"
 
+[[package]]
+name = "typing-inspection"
+version = "0.4.0"
+description = "Runtime typing introspection tools"
+optional = false
+python-versions = ">=3.9"
+groups = ["main", "dev"]
+files = [
+    {file = "typing_inspection-0.4.0-py3-none-any.whl", hash = "sha256:50e72559fcd2a6367a19f7a7e610e6afcb9fac940c650290eed893d61386832f"},
+    {file = "typing_inspection-0.4.0.tar.gz", hash = "sha256:9765c87de36671694a67904bf2c96e395be9c6439bb6c87b5142569dcdd65122"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.12.0"
+
 [[package]]
 name = "urllib3"
 version = "2.3.0"
@@ -4050,4 +4088,4 @@ langchain = ["langchain-community", "langchain-core"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">= 3.11,<4.0"
-content-hash = "68916726fb3b656b14425737fbceef65768b71e6b0f68e8c1ebb3427d919f7a1"
+content-hash = "ab15ef3000279695aebd18e4271502b2e5237c7586fc34cb032fd909007b9178"
diff --git a/python/pyproject.toml b/python/pyproject.toml
index 091c02d25..717ca30a4 100644
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -39,6 +39,7 @@ langchain-community = {version = "^0.3.19", optional = true}
 boto3 = {version = "^1.37.5", optional = true}
 acp-sdk = "^0.0.5"
 cachetools = "^5.5.2"
+jsonref = "^1.1.0"
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^8.3.4"


Reviews:
user: login: planetf1
state: CHANGES_REQUESTED
author_association: CONTRIBUTOR
submitted_at: 2025-03-28T11:07:32Z
user: login: planetf1
state: COMMENTED
author_association: CONTRIBUTOR
submitted_at: 2025-03-28T11:55:11Z
user: login: michael-desmond
state: APPROVED
author_association: MEMBER
submitted_at: 2025-03-28T18:09:45Z

Review comments:
diff_hunk: @@ -739,18 +762,20 @@ files = [
 
 [[package]]
 name = "duckduckgo-search"
-version = "7.5.3"
+version = "7.5.6"
path: python/poetry.lock
user: login: planetf1
body: This fails for me due - 7.5.6 is not available 

```
(beeai-framework-py3.13) ➜  python git:(temp) pip install duckduckgo-search==7.5.6
ERROR: Could not find a version that satisfies the requirement duckduckgo-search==7.5.6 (from versions: 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.9.5, 1.0, 1.1, 1.2, 1.3, 1.3.5, 1.4, 1.5, 1.5.1, 1.5.2, 1.6, 1.6.2, 1.7.1, 1.8, 1.8.1, 1.8.2, 2.0.2, 2.1.3, 2.2.0, 2.2.2, 2.3.0, 2.3.1, 2.4.0, 2.5.0, 2.6.0, 2.6.1, 2.7.0, 2.8.0, 2.8.1, 2.8.3, 2.8.4, 2.8.5, 2.8.6, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.9.4, 2.9.5, 3.0.2, 3.1.1, 3.2.0, 3.3.0, 3.4.1, 3.5.0, 3.6.0, 3.7.0, 3.7.1, 3.8.0, 3.8.1, 3.8.2, 3.8.3, 3.8.4, 3.8.5, 3.8.6, 3.9.3, 3.9.4, 3.9.5, 3.9.6, 3.9.8, 3.9.9, 3.9.10, 3.9.11, 4.0.0, 4.1.0, 4.1.1, 4.2, 4.3, 4.3.1, 4.4, 4.4.1, 4.4.2, 4.4.3, 4.5.0, 5.0b0, 5.0b1, 5.0, 5.1.0, 5.2.0, 5.2.1, 5.2.2, 5.3.0b1, 5.3.0b2, 5.3.0b3, 5.3.0b4, 5.3.0, 5.3.1b1, 5.3.1, 6.0.0, 6.1.0, 6.1.1, 6.1.2, 6.1.3, 6.1.4, 6.1.5, 6.1.6, 6.1.7, 6.1.8, 6.1.9, 6.1.11, 6.1.12, 6.2.0, 6.2.1, 6.2.2, 6.2.3, 6.2.4, 6.2.5, 6.2.6, 6.2.7, 6.2.8b1, 6.2.8, 6.2.9, 6.2.10, 6.2.11b1, 6.2.12, 6.2.13, 6.3.0, 6.3.1, 6.3.2, 6.3.3, 6.3.4, 6.3.5, 6.3.6, 6.3.7, 6.4.2, 7.0.1, 7.0.2, 7.1.0, 7.1.1, 7.2.0, 7.2.1, 7.3.0, 7.3.1, 7.3.2, 7.4.2, 7.4.3, 7.4.4, 7.4.5, 7.5.0, 7.5.1, 7.5.2, 7.5.3, 7.5.4, 7.5.5)

[notice] A new release of pip is available: 24.3.1 -> 25.0.1
[notice] To update, run: pip install --upgrade pip
ERROR: No matching distribution found for duckduckgo-search==7.5.6
```
created_at: 2025-03-28T11:04:23Z
author_association: CONTRIBUTOR
diff_hunk: @@ -739,18 +762,20 @@ files = [
 
 [[package]]
 name = "duckduckgo-search"
-version = "7.5.3"
+version = "7.5.6"
path: python/poetry.lock
user: login: planetf1
body: This fails for me on `poetry sync` due to 7.5.6 is not available 
```
  - Updating duckduckgo-search (7.5.1 -> 7.5.6): Failed
```

```
(beeai-framework-py3.13) ➜  python git:(temp) pip install duckduckgo-search==7.5.6
ERROR: Could not find a version that satisfies the requirement duckduckgo-search==7.5.6 (from versions: 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.9.5, 1.0, 1.1, 1.2, 1.3, 1.3.5, 1.4, 1.5, 1.5.1, 1.5.2, 1.6, 1.6.2, 1.7.1, 1.8, 1.8.1, 1.8.2, 2.0.2, 2.1.3, 2.2.0, 2.2.2, 2.3.0, 2.3.1, 2.4.0, 2.5.0, 2.6.0, 2.6.1, 2.7.0, 2.8.0, 2.8.1, 2.8.3, 2.8.4, 2.8.5, 2.8.6, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.9.4, 2.9.5, 3.0.2, 3.1.1, 3.2.0, 3.3.0, 3.4.1, 3.5.0, 3.6.0, 3.7.0, 3.7.1, 3.8.0, 3.8.1, 3.8.2, 3.8.3, 3.8.4, 3.8.5, 3.8.6, 3.9.3, 3.9.4, 3.9.5, 3.9.6, 3.9.8, 3.9.9, 3.9.10, 3.9.11, 4.0.0, 4.1.0, 4.1.1, 4.2, 4.3, 4.3.1, 4.4, 4.4.1, 4.4.2, 4.4.3, 4.5.0, 5.0b0, 5.0b1, 5.0, 5.1.0, 5.2.0, 5.2.1, 5.2.2, 5.3.0b1, 5.3.0b2, 5.3.0b3, 5.3.0b4, 5.3.0, 5.3.1b1, 5.3.1, 6.0.0, 6.1.0, 6.1.1, 6.1.2, 6.1.3, 6.1.4, 6.1.5, 6.1.6, 6.1.7, 6.1.8, 6.1.9, 6.1.11, 6.1.12, 6.2.0, 6.2.1, 6.2.2, 6.2.3, 6.2.4, 6.2.5, 6.2.6, 6.2.7, 6.2.8b1, 6.2.8, 6.2.9, 6.2.10, 6.2.11b1, 6.2.12, 6.2.13, 6.3.0, 6.3.1, 6.3.2, 6.3.3, 6.3.4, 6.3.5, 6.3.6, 6.3.7, 6.4.2, 7.0.1, 7.0.2, 7.1.0, 7.1.1, 7.2.0, 7.2.1, 7.3.0, 7.3.1, 7.3.2, 7.4.2, 7.4.3, 7.4.4, 7.4.5, 7.5.0, 7.5.1, 7.5.2, 7.5.3, 7.5.4, 7.5.5)

[notice] A new release of pip is available: 24.3.1 -> 25.0.1
[notice] To update, run: pip install --upgrade pip
ERROR: No matching distribution found for duckduckgo-search==7.5.6
```

If I rebuild the lock file, I get resolution to 7.5.5

PyPi agrees with this -> https://pypi.org/project/duckduckgo-search/

created_at: 2025-03-28T11:07:26Z
author_association: CONTRIBUTOR
diff_hunk: @@ -739,18 +762,20 @@ files = [
 
 [[package]]
 name = "duckduckgo-search"
-version = "7.5.3"
+version = "7.5.6"
path: python/poetry.lock
user: login: planetf1
body: update fixes this
created_at: 2025-03-28T11:55:11Z
author_association: CONTRIBUTOR

PR comments:
user: login: ajbozarth
created_at: 2025-03-27T22:43:10Z
body: I'll take a deeper look in the AM, but I do see the following pytest failures when run locally:
```
FAILED tests/examples/test_examples.py::test_example_execution[agents/custom_agent.py] - SystemExit: FrameworkError(beeai_framework.errors): Framework error
FAILED tests/examples/test_examples.py::test_example_execution[backend/providers/ollama.py] - SystemExit: FrameworkError(beeai_framework.errors): Framework error
FAILED tests/examples/test_examples.py::test_example_execution[backend/structured.py] - SystemExit: FrameworkError(beeai_framework.errors): Framework error
FAILED tests/examples/test_examples.py::test_example_execution[workflows/remote.py] - SystemExit: AgentError(beeai_framework.agents.errors): Can't connect to Beeai Platform.
```
author_association: MEMBER
user: login: Tomas2D
created_at: 2025-03-28T11:12:22Z
body: I updated the implementation and the generated lock file.
author_association: CONTRIBUTOR
user: login: planetf1
created_at: 2025-03-28T11:55:32Z
body: > I updated the implementation and the generated lock file.

Thanks - looks fine now.
author_association: CONTRIBUTOR
user: login: ajbozarth
created_at: 2025-03-28T17:13:11Z
body: Sorry I accidentally committed to the wrong branch without noticing. I'll fix it in a sec with a force push

author_association: MEMBER