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Release 1.2.14 (#2731)
# Changelog ## Improvements: - **Improved Github Tools**: Added many more capabilities to `GithubTools`. - **Windows Scripts Support**: Converted all the utility scripts to be Windows compatible. - **MongoDB VectorDB Async Support**: MongoDB can now be used in async knowledge bases. ## Bug Fixes: - **Gemini Tool Formatting**: Fixed various cases where functions would not be parsed correctly when used with Gemini. - **ChromaDB Version Compatibility:** Fix to ensure that ChromaDB and Agno are compatible with newer versions of ChromaDB. - **Team-Member Interactions**: Fixed issue where if members respond with empty content the team would halt. This is now be resolved. - **Claude Empty Response:** Fixed a case when the response did not include any content with tool calls resulting in an error from the Anthropic API
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‎.github/workflows/test_on_release.yml‎

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Original file line numberDiff line numberDiff line change
@@ -3,7 +3,8 @@ name: Main Validation
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on:
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push:
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branches:
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- '*release*' # Run on release
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- '*release*' # Run on release-* format
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- 'release/*' # Run on release/1.2.3 branch format
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jobs:
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style-check:

‎libs/agno/agno/models/xai/xai.py‎

Lines changed: 127 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,9 +1,20 @@
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from collections.abc import AsyncIterator
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from dataclasses import dataclass
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from os import getenv
3-
from typing import Optional
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from typing import Iterator, List, Optional
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from agno.exceptions import ModelProviderError
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from agno.models.message import Message
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from agno.models.openai.like import OpenAILike
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from agno.utils.log import log_error
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try:
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from openai import APIConnectionError, APIStatusError, RateLimitError
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from openai.types.chat.chat_completion_chunk import (
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ChatCompletionChunk,
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)
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except (ImportError, ModuleNotFoundError):
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raise ImportError("`openai` not installed. Please install using `pip install openai`")
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@dataclass
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class xAI(OpenAILike):
@@ -24,3 +35,118 @@ class xAI(OpenAILike):
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api_key: Optional[str] = getenv("XAI_API_KEY")
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base_url: Optional[str] = "https://api.x.ai/v1"
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def invoke_stream(self, messages: List[Message]) -> Iterator[ChatCompletionChunk]:
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"""
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Send a streaming chat completion request to the OpenAI API.
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Args:
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messages (List[Message]): A list of messages to send to the model.
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Returns:
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Iterator[ChatCompletionChunk]: An iterator of chat completion chunks.
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"""
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try:
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yield from self.get_client().chat.completions.create(
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model=self.id,
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messages=[self._format_message(m) for m in messages], # type: ignore
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stream=True,
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**self.request_kwargs,
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) # type: ignore
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except RateLimitError as e:
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log_error(f"Rate limit error from OpenAI API: {e}")
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error_message = e.response.json().get("error", {})
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error_message = (
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error_message.get("message", "Unknown model error")
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if isinstance(error_message, dict)
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else error_message
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)
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raise ModelProviderError(
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message=error_message,
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status_code=e.response.status_code,
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model_name=self.name,
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model_id=self.id,
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) from e
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except APIConnectionError as e:
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log_error(f"API connection error from OpenAI API: {e}")
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raise ModelProviderError(message=str(e), model_name=self.name, model_id=self.id) from e
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except APIStatusError as e:
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log_error(f"API status error from OpenAI API: {e}")
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try:
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error_message = e.response.json().get("error", {})
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except Exception:
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error_message = e.response.text
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error_message = (
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error_message.get("message", "Unknown model error")
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if isinstance(error_message, dict)
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else error_message
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)
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raise ModelProviderError(
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message=error_message,
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status_code=e.response.status_code,
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model_name=self.name,
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model_id=self.id,
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) from e
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except Exception as e:
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log_error(f"Error from OpenAI API: {e}")
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raise ModelProviderError(message=str(e), model_name=self.name, model_id=self.id) from e
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async def ainvoke_stream(self, messages: List[Message]) -> AsyncIterator[ChatCompletionChunk]:
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"""
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Sends an asynchronous streaming chat completion request to the OpenAI API.
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Args:
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messages (List[Message]): A list of messages to send to the model.
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Returns:
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Any: An asynchronous iterator of chat completion chunks.
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"""
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try:
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async_stream = await self.get_async_client().chat.completions.create(
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model=self.id,
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messages=[self._format_message(m) for m in messages], # type: ignore
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stream=True,
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**self.request_kwargs,
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)
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async for chunk in async_stream:
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yield chunk
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except RateLimitError as e:
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log_error(f"Rate limit error from OpenAI API: {e}")
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error_message = e.response.json().get("error", {})
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error_message = (
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error_message.get("message", "Unknown model error")
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if isinstance(error_message, dict)
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else error_message
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)
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raise ModelProviderError(
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message=error_message,
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status_code=e.response.status_code,
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model_name=self.name,
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model_id=self.id,
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) from e
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except APIConnectionError as e:
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log_error(f"API connection error from OpenAI API: {e}")
132+
raise ModelProviderError(message=str(e), model_name=self.name, model_id=self.id) from e
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except APIStatusError as e:
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log_error(f"API status error from OpenAI API: {e}")
135+
try:
136+
error_message = e.response.json().get("error", {})
137+
except Exception:
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error_message = e.response.text
139+
error_message = (
140+
error_message.get("message", "Unknown model error")
141+
if isinstance(error_message, dict)
142+
else error_message
143+
)
144+
raise ModelProviderError(
145+
message=error_message,
146+
status_code=e.response.status_code,
147+
model_name=self.name,
148+
model_id=self.id,
149+
) from e
150+
except Exception as e:
151+
log_error(f"Error from OpenAI API: {e}")
152+
raise ModelProviderError(message=str(e), model_name=self.name, model_id=self.id) from e

‎libs/agno/pyproject.toml‎

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Original file line numberDiff line numberDiff line change
@@ -1,6 +1,6 @@
11
[project]
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name = "agno"
3-
version = "1.2.13"
3+
version = "1.2.14"
44
description = "Agno: a lightweight framework for building Multimodal Agents"
55
requires-python = ">=3.7,<4"
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readme = "README.md"

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