Merge branch 'main' into mypy-poe-typecheck

README.md

@@ -150,8 +150,8 @@ To stay up-to-date on our [public roadmap](https://github.com/orgs/i-am-bee/proj
 BeeAI framework is open-source and we ❤️ contributions.<br>
 
 To help build BeeAI, take a look at our:
-- [Python contribution guidelines](/python/docs/CONTRIBUTING.md)
-- [TypeScript contribution guidelines](/typescript/docs/CONTRIBUTING.md)
+- [Python contribution guidelines](/python/CONTRIBUTING.md)
+- [TypeScript contribution guidelines](/typescript/CONTRIBUTING.md)
 
 ## Bugs
 

python/.env.example

@@ -38,3 +38,20 @@ BEEAI_LOG_LEVEL=INFO
 
 # XAI_API_KEY=your-xai-api-key
 # XAI_CHAT_MODEL=grok-2
+
+########################
+### Vertex AI specific configuration
+########################
+
+# GOOGLE_VERTEX_CHAT_MODEL=gemini-2.0-flash-lite-001
+# GOOGLE_VERTEX_PROJECT=""
+# GOOGLE_VERTEX_ENDPOINT=""
+
+########################
+### Amazon Bedrock specific configuration
+########################
+
+# AWS_ACCESS_KEY_ID=
+# AWS_SECRET_ACCESS_KEY=
+# AWS_REGION_NAME=
+# AWS_CHAT_MODEL=

python/CHANGELOG.md

@@ -1,3 +1,37 @@
+## python_v0.1.4 (2025-03-06)
+
+### Refactor
+
+- rename Bee agent to ReAct agent (#505)
+- move logger to the root (#504)
+- update user-facing event data to all be dict and add docs (#431)
+- **agents**: remove Bee branding from BaseAgent (#440)
+
+### Bug Fixes
+
+- improve decorated tool output (#499)
+- **backend**: correctly merge inference parameters (#496)
+- **backend**: tool calling, unify message content (#475)
+- **backend**: correctly merge inference parameters (#486)
+- **tools**: make emitter required (#461)
+- **workflows**: handle relative steps (#463)
+
+### Features
+
+- **adapters**: add Amazon Bedrock support (#466)
+- **examples**: adds logger examples and updates docs (#494)
+- **internals**: construct Pydantic model from JSON Schema (#502)
+- **adapters**: Add Google VertexAI support (#469)
+- **tools**: add MCP tool (#481)
+- langchain tool (#474)
+- **examples**: templates examples ts parity (#480)
+- **examples**: adds error examples and updates error docs (#490)
+- **agents**: simplify variable usage in prompt templates (#484)
+- improve PromptTemplate.render API (#476)
+- **examples**: Add custom_agent and bee_advanced examples (#462)
+- **agents**: handle message formatting (#470)
+- **adapters**: Add xAI backend (#445) (#446)
+
 ## python_v0.1.3 (2025-03-03)
 
 ### Features

python/README.md

@@ -73,7 +73,7 @@ import traceback
 
 from pydantic import ValidationError
 
-from beeai_framework.agents.bee.agent import AgentExecutionConfig
+from beeai_framework.agents.react.agent import AgentExecutionConfig
 from beeai_framework.backend.chat import ChatModel
 from beeai_framework.backend.message import UserMessage
 from beeai_framework.memory import UnconstrainedMemory

python/beeai_framework/__init__.py

@@ -14,7 +14,7 @@
 
 
 from beeai_framework.agents import BaseAgent
-from beeai_framework.agents.bee.agent import BeeAgent
+from beeai_framework.agents.react.agent import ReActAgent
 from beeai_framework.backend import (
     AssistantMessage,
     CustomMessage,
@@ -40,13 +40,13 @@
     "AssistantMessage",
     "BaseAgent",
     "BaseMemory",
-    "BeeAgent",
     "CustomMessage",
     "LoggerError",
     "Message",
     "OpenMeteoTool",
     "Prompt",
     "PromptTemplateError",
+    "ReActAgent",
     "ReadOnlyMemory",
     "Role",
     "Serializable",

python/beeai_framework/agents/bee/__init__.py → python/beeai_framework/adapters/amazon_bedrock/__init__.py

@@ -13,6 +13,3 @@
 # limitations under the License.
 
 
-from beeai_framework.agents.bee.agent import BeeAgent
-
-__all__ = ["BeeAgent"]

python/beeai_framework/adapters/amazon_bedrock/backend/README.md

@@ -0,0 +1,54 @@
+# Amazon Bedrock
+
+## Configuration
+
+Set the following environment variables
+
+* AWS_ACCESS_KEY_ID
+* AWS_SECRET_ACCESS_KEY
+* AWS_REGION_NAME
+
+## Tested Models
+
+Only Meta, Mistral, & Amazon Titan serverless models have been tested.
+
+Other models should work, as beeai_framework uses LiteLLM. See [docs](https://docs.litellm.ai/docs/providers/bedrock) for more information
+
+## Known Issues with tool use and structured output
+
+The following models report Tool use not supported:
+
+```text
+litellm.llms.bedrock.common_utils.BedrockError: {"message":"This model doesn't support tool use."}
+```
+
+* `meta.llama3-70b-instruct-v1:0`
+* `meta.llama3-8b-instruct-v1:0`
+
+The following fail to return structured output with beeai_framework. Initial investigation indicates that these models are not responding with structured JSON output when requested
+
+* `amazon.titan-text-express-v1`
+* `amazon.titan-text-lite-v1`
+* `mistral.mistral-7b-instruct-v0:2`
+* `mistral.mixtral-8x7b-instruct-v0:1`
+* `mistral.mistral-large-2402-v1:0`
+
+The following models fail with an exception:
+
+```text
+litellm.exceptions.BadRequestError: litellm.BadRequestError: BedrockException - {"message":"This model doesn't support the toolConfig.toolChoice.tool field. Remove toolConfig.toolChoice.tool and try again."}
+```
+
+* `mistral.mistral-large-2402-v1:0`
+
+## Quota limits
+
+Default quota limits on Amazon Bedrock are low, and can cause even
+simple examples to fail with:
+
+```text
+litellm.exceptions.RateLimitError: litellm.RateLimitError: BedrockException - {"message":"Too many requests, please wait before trying again."}
+```
+
+To increase quota limits, see [Amazon Bedrock #](https://aws.amazon.com/bedrock/#/) and
+[Amazon Bedrock quotas](https://docs.aws.amazon.com/bedrock/latest/userguide/quotas.html).

python/beeai_framework/adapters/amazon_bedrock/backend/__init__.py

@@ -0,0 +1,15 @@
+# Copyright 2025 IBM Corp.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+

python/beeai_framework/adapters/amazon_bedrock/backend/chat.py

@@ -0,0 +1,63 @@
+# Copyright 2025 IBM Corp.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import os
+
+from beeai_framework.adapters.litellm.chat import LiteLLMChatModel
+from beeai_framework.backend.constants import ProviderName
+from beeai_framework.logger import Logger
+
+logger = Logger(__name__)
+
+
+class AmazonBedrockChatModel(LiteLLMChatModel):
+    @property
+    def provider_id(self) -> ProviderName:
+        return "amazon_bedrock"
+
+    def __init__(self, model_id: str | None = None, settings: dict | None = None) -> None:
+        _settings = settings.copy() if settings is not None else {}
+
+        aws_access_key_id = _settings.get("aws_access_key_id", os.getenv("AWS_ACCESS_KEY_ID"))
+        if not aws_access_key_id:
+            raise ValueError(
+                "Access key is required for Amazon Bedrock model. Specify *aws_access_key_id* "
+                + "or set AWS_ACCESS_KEY_ID environment variable"
+            )
+
+        aws_secret_access_key = _settings.get("aws_secret_access_key", os.getenv("AWS_SECRET_ACCESS_KEY"))
+        if not aws_secret_access_key:
+            raise ValueError(
+                "Secret key is required for Amazon Bedrock model. Specify *aws_secret_access_key* "
+                + "or set AWS_SECRET_ACCESS_KEY environment variable"
+            )
+
+        aws_region_name = _settings.get("aws_region_name", os.getenv("AWS_REGION_NAME"))
+        if not aws_region_name:
+            raise ValueError(
+                "Region is required for Amazon Bedrock model. Specify *aws_region_name* "
+                + "or set AWS_REGION_NAME environment variable"
+            )
+
+        super().__init__(
+            (model_id if model_id else os.getenv("AWS_CHAT_MODEL", "llama-3.1-8b-instant")),
+            provider_id="bedrock",
+            settings=_settings
+            | {
+                "aws_access_key_id": aws_access_key_id,
+                "aws_secret_access_key": aws_secret_access_key,
+                "aws_region_name": aws_region_name,
+            },
+        )

python/beeai_framework/adapters/groq/backend/chat.py

@@ -17,9 +17,9 @@
 
 from beeai_framework.adapters.litellm.chat import LiteLLMChatModel
 from beeai_framework.backend.constants import ProviderName
-from beeai_framework.utils.custom_logger import BeeLogger
+from beeai_framework.logger import Logger
 
-logger = BeeLogger(__name__)
+logger = Logger(__name__)
 
 
 class GroqChatModel(LiteLLMChatModel):

python/beeai_framework/adapters/langchain/__init__.py

@@ -0,0 +1,15 @@
+# Copyright 2025 IBM Corp.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+

python/beeai_framework/adapters/langchain/tools.py

@@ -0,0 +1,78 @@
+# Copyright 2025 IBM Corp.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from typing import Any, TypeVar
+
+from langchain_core.callbacks import AsyncCallbackManagerForToolRun
+from langchain_core.runnables import RunnableConfig
+from langchain_core.tools import StructuredTool
+from langchain_core.tools import Tool as LangChainSimpleTool
+from pydantic import BaseModel, ConfigDict
+
+from beeai_framework.context import RunContext
+from beeai_framework.emitter.emitter import Emitter
+from beeai_framework.tools.tool import StringToolOutput, Tool, ToolRunOptions
+from beeai_framework.utils.strings import to_safe_word
+
+
+class LangChainToolRunOptions(ToolRunOptions):
+    langchain_runnable_config: RunnableConfig | None = None
+    model_config = ConfigDict(extra="allow", arbitrary_types_allowed=True)
+
+
+T = TypeVar("T", bound=BaseModel)
+
+
+class LangChainTool(Tool[T, LangChainToolRunOptions, StringToolOutput]):
+    @property
+    def name(self) -> str:
+        return self._tool.name
+
+    @property
+    def description(self) -> str:
+        return self._tool.description
+
+    @property
+    def input_schema(self) -> type[T]:
+        return self._tool.input_schema
+
+    def _create_emitter(self) -> Emitter:
+        return Emitter.root().child(
+            namespace=["tool", "langchain", to_safe_word(self._tool.name)],
+            creator=self,
+        )
+
+    def __init__(self, tool: StructuredTool | LangChainSimpleTool, options: dict[str, Any] | None = None) -> None:
+        super().__init__(options)
+        self._tool = tool
+
+    async def _run(self, input: T, options: LangChainToolRunOptions | None, context: RunContext) -> StringToolOutput:
+        langchain_runnable_config = options.langchain_runnable_config or {} if options else {}
+        args = (
+            input if isinstance(input, dict) else input.model_dump(),
+            {
+                **langchain_runnable_config,
+                "signal": context.signal or None if context else None,
+            },
+        )
+        is_async = (isinstance(self._tool, StructuredTool) and self._tool.coroutine) or (
+            isinstance(args[0].get("run_manager"), AsyncCallbackManagerForToolRun)
+        )
+        if is_async:
+            response = await self._tool.ainvoke(*args)
+        else:
+            response = self._tool.invoke(*args)
+
+        return StringToolOutput(result=str(response))