mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Merge branch 'main' into feature-python-foundry-agents
This commit is contained in:
@@ -7,11 +7,29 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
## [1.0.0b251106] - 2025-11-06
|
||||
|
||||
### Changed
|
||||
|
||||
- **agent-framework-ag-ui**: export sample ag-ui agents ([#1927](https://github.com/microsoft/agent-framework/pull/1927))
|
||||
|
||||
## [1.0.0b251105] - 2025-11-05
|
||||
|
||||
### Added
|
||||
|
||||
- **agent-framework-ag-ui**: Initial release of AG-UI protocol integration for Agent Framework ([#1826](https://github.com/microsoft/agent-framework/pull/1826))
|
||||
- **agent-framework-chatkit**: ChatKit integration with a sample application ([#1273](https://github.com/microsoft/agent-framework/pull/1273))
|
||||
- Added parameter to disable agent cleanup in AzureAIAgentClient ([#1882](https://github.com/microsoft/agent-framework/pull/1882))
|
||||
- Add support for Python 3.14 ([#1904](https://github.com/microsoft/agent-framework/pull/1904))
|
||||
|
||||
### Changed
|
||||
|
||||
- [BREAKING] Replaced AIProjectClient with AgentsClient in Foundry ([#1936](https://github.com/microsoft/agent-framework/pull/1936))
|
||||
- Updates to Tools ([#1835](https://github.com/microsoft/agent-framework/pull/1835))
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fix missing packaging dependency ([#1929](https://github.com/microsoft/agent-framework/pull/1929))
|
||||
|
||||
## [1.0.0b251104] - 2025-11-04
|
||||
|
||||
|
||||
@@ -4,6 +4,7 @@
|
||||
|
||||
import argparse
|
||||
from enum import Enum
|
||||
import glob
|
||||
import logging
|
||||
import tempfile
|
||||
import subprocess # nosec
|
||||
@@ -32,6 +33,16 @@ def with_color(text: str, color: Colors) -> str:
|
||||
return f"{color.value}{text}{Colors.CEND.value}"
|
||||
|
||||
|
||||
def expand_file_patterns(patterns: list[str]) -> list[str]:
|
||||
"""Expand glob patterns to actual file paths."""
|
||||
all_files: list[str] = []
|
||||
for pattern in patterns:
|
||||
# Handle both relative and absolute paths
|
||||
matches = glob.glob(pattern, recursive=True)
|
||||
all_files.extend(matches)
|
||||
return sorted(set(all_files)) # Remove duplicates and sort
|
||||
|
||||
|
||||
def extract_python_code_blocks(markdown_file_path: str) -> list[tuple[str, int]]:
|
||||
"""Extract Python code blocks from a Markdown file."""
|
||||
with open(markdown_file_path, encoding="utf-8") as file:
|
||||
@@ -113,7 +124,10 @@ def check_code_blocks(markdown_file_paths: list[str], exclude_patterns: list[str
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description="Check code blocks in Markdown files for syntax errors.")
|
||||
# Argument is a list of markdown files containing glob patterns
|
||||
parser.add_argument("markdown_files", nargs="+", help="Markdown files to check.")
|
||||
parser.add_argument("markdown_files", nargs="+", help="Markdown files to check (supports glob patterns).")
|
||||
parser.add_argument("--exclude", action="append", help="Exclude files containing this pattern.")
|
||||
args = parser.parse_args()
|
||||
check_code_blocks(args.markdown_files, args.exclude)
|
||||
|
||||
# Expand glob patterns to actual file paths
|
||||
expanded_files = expand_file_patterns(args.markdown_files)
|
||||
check_code_blocks(expanded_files, args.exclude)
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "A2A integration for Microsoft Agent Framework."
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -1 +1,7 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
"""Example agents for AG-UI demonstration."""
|
||||
|
||||
from . import agents
|
||||
|
||||
__all__ = ["agents"]
|
||||
|
||||
@@ -1,3 +1,25 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
"""Example agents for AG-UI demonstration."""
|
||||
|
||||
from .document_writer_agent import document_writer_agent
|
||||
from .human_in_the_loop_agent import human_in_the_loop_agent
|
||||
from .recipe_agent import recipe_agent
|
||||
from .research_assistant_agent import research_assistant_agent
|
||||
from .simple_agent import agent as simple_agent
|
||||
from .task_planner_agent import task_planner_agent
|
||||
from .task_steps_agent import task_steps_agent_wrapped
|
||||
from .ui_generator_agent import ui_generator_agent
|
||||
from .weather_agent import weather_agent
|
||||
|
||||
__all__ = [
|
||||
"document_writer_agent",
|
||||
"human_in_the_loop_agent",
|
||||
"recipe_agent",
|
||||
"research_assistant_agent",
|
||||
"simple_agent",
|
||||
"task_planner_agent",
|
||||
"task_steps_agent_wrapped",
|
||||
"ui_generator_agent",
|
||||
"weather_agent",
|
||||
]
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[project]
|
||||
name = "agent-framework-ag-ui"
|
||||
version = "1.0.0b251105"
|
||||
version = "1.0.0b251106"
|
||||
description = "AG-UI protocol integration for Agent Framework"
|
||||
readme = "README.md"
|
||||
license-files = ["LICENSE"]
|
||||
@@ -41,6 +41,7 @@ build-backend = "hatchling.build"
|
||||
|
||||
[tool.hatch.build.targets.wheel]
|
||||
packages = ["agent_framework_ag_ui"]
|
||||
force-include = { "examples" = "agent_framework_ag_ui_examples" }
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
asyncio_mode = "auto"
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Anthropic integration for Microsoft Agent Framework."
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -2,8 +2,9 @@
|
||||
|
||||
import importlib.metadata
|
||||
|
||||
from ._chat_client import AzureAIAgentClient, AzureAISettings
|
||||
from ._chat_client import AzureAIAgentClient
|
||||
from ._client import AzureAIClient
|
||||
from ._shared import AzureAISettings
|
||||
|
||||
try:
|
||||
__version__ = importlib.metadata.version(__name__)
|
||||
|
||||
@@ -859,7 +859,7 @@ class AzureAIAgentClient(BaseChatClient):
|
||||
config_args["market"] = market
|
||||
if set_lang := additional_props.get("set_lang"):
|
||||
config_args["set_lang"] = set_lang
|
||||
# Bing Grounding (support both connection_id and connection_name)
|
||||
# Bing Grounding
|
||||
connection_id = additional_props.get("connection_id") or os.getenv("BING_CONNECTION_ID")
|
||||
# Custom Bing Search
|
||||
custom_connection_id = additional_props.get("custom_connection_id") or os.getenv(
|
||||
@@ -873,7 +873,7 @@ class AzureAIAgentClient(BaseChatClient):
|
||||
if connection_id:
|
||||
conn_id = connection_id
|
||||
else:
|
||||
raise ServiceInitializationError("Neither connection_id nor connection_name provided.")
|
||||
raise ServiceInitializationError("Parameter connection_id is not provided.")
|
||||
bing_search = BingGroundingTool(connection_id=conn_id, **config_args)
|
||||
if custom_connection_id and custom_instance_name:
|
||||
bing_search = BingCustomSearchTool(
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Azure AI Foundry integration for Microsoft Agent Framework."
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
@@ -26,6 +26,7 @@ dependencies = [
|
||||
"agent-framework-core",
|
||||
"azure-ai-projects >= 2.0.0a20251103001",
|
||||
"azure-ai-agents == 1.2.0b5",
|
||||
"aiohttp",
|
||||
]
|
||||
|
||||
[tool.uv]
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "OpenAI ChatKit integration for Microsoft Agent Framework."
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251001"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Copilot Studio integration for Microsoft Agent Framework."
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -17,7 +17,7 @@ from openai.types.chat import ChatCompletion, ChatCompletionChunk
|
||||
from openai.types.images_response import ImagesResponse
|
||||
from openai.types.responses.response import Response
|
||||
from openai.types.responses.response_stream_event import ResponseStreamEvent
|
||||
from packaging import version
|
||||
from packaging.version import parse
|
||||
from pydantic import SecretStr
|
||||
|
||||
from .._logging import get_logger
|
||||
@@ -58,8 +58,8 @@ def _check_openai_version_for_callable_api_key() -> None:
|
||||
If the version is too old, raise a ServiceInitializationError with helpful message.
|
||||
"""
|
||||
try:
|
||||
current_version = version.parse(openai.__version__)
|
||||
min_required_version = version.parse("1.106.0")
|
||||
current_version = parse(openai.__version__)
|
||||
min_required_version = parse("1.106.0")
|
||||
|
||||
if current_version < min_required_version:
|
||||
raise ServiceInitializationError(
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
@@ -36,6 +36,7 @@ dependencies = [
|
||||
"openai>=1.99.0",
|
||||
"azure-identity>=1,<2",
|
||||
"mcp[ws]>=1.13",
|
||||
"packaging>=24.1",
|
||||
]
|
||||
|
||||
[project.optional-dependencies]
|
||||
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -2,11 +2,11 @@
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<link rel="icon" type="image/svg+xml" href="/agentframework.svg" />
|
||||
<link rel="icon" type="image/svg+xml" href="agentframework.svg" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Agent Framework Dev UI</title>
|
||||
<script type="module" crossorigin src="/assets/index-D_Y1oSGu.js"></script>
|
||||
<link rel="stylesheet" crossorigin href="/assets/index-CE4pGoXh.css">
|
||||
<script type="module" crossorigin src="./assets/index.js"></script>
|
||||
<link rel="stylesheet" crossorigin href="./assets/index.css">
|
||||
</head>
|
||||
<body>
|
||||
<div id="root"></div>
|
||||
|
||||
@@ -1 +0,0 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>
|
||||
|
Before Width: | Height: | Size: 1.5 KiB |
@@ -2,12 +2,12 @@
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<link rel="icon" type="image/svg+xml" href="/agentframework.svg" />
|
||||
<link rel="icon" type="image/svg+xml" href="agentframework.svg" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Agent Framework Dev UI</title>
|
||||
</head>
|
||||
<body>
|
||||
<div id="root"></div>
|
||||
<script type="module" src="/src/main.tsx"></script>
|
||||
<script type="module" src="src/main.tsx"></script>
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -1 +0,0 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>
|
||||
|
Before Width: | Height: | Size: 1.5 KiB |
@@ -45,6 +45,7 @@ import type {
|
||||
ExtendedResponseStreamEvent,
|
||||
} from "@/types";
|
||||
import { useDevUIStore } from "@/stores";
|
||||
import { loadStreamingState } from "@/services/streaming-state";
|
||||
|
||||
type DebugEventHandler = (event: ExtendedResponseStreamEvent | "clear") => void;
|
||||
|
||||
@@ -229,7 +230,6 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
|
||||
const scrollAreaRef = useRef<HTMLDivElement>(null);
|
||||
const messagesEndRef = useRef<HTMLDivElement>(null);
|
||||
const accumulatedText = useRef<string>("");
|
||||
const textareaRef = useRef<HTMLTextAreaElement>(null);
|
||||
const currentMessageUsage = useRef<{
|
||||
total_tokens: number;
|
||||
@@ -237,6 +237,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
output_tokens: number;
|
||||
} | null>(null);
|
||||
const userJustSentMessage = useRef<boolean>(false);
|
||||
const accumulatedTextRef = useRef<string>("");
|
||||
|
||||
// Auto-scroll to bottom when new items arrive
|
||||
useEffect(() => {
|
||||
@@ -281,33 +282,270 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
|
||||
// Load conversations when agent changes
|
||||
useEffect(() => {
|
||||
// Resume streaming after page refresh
|
||||
const resumeStreaming = async (
|
||||
assistantMessage: import("@/types/openai").ConversationMessage,
|
||||
conversation: Conversation,
|
||||
agent: AgentInfo
|
||||
) => {
|
||||
// Load the stored state to get the response ID
|
||||
const storedState = loadStreamingState(conversation.id);
|
||||
if (!storedState || !storedState.responseId) {
|
||||
setIsStreaming(false);
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
// Use the stored responseId to resume the stream via GET /v1/responses/{responseId}
|
||||
const openAIRequest: import("@/types/agent-framework").AgentFrameworkRequest = {
|
||||
model: agent.id,
|
||||
input: [], // Not needed for resume (using GET)
|
||||
stream: true,
|
||||
conversation: conversation.id,
|
||||
};
|
||||
|
||||
// Pass the response ID explicitly to trigger GET request
|
||||
const streamGenerator = apiClient.streamAgentExecutionOpenAIDirect(
|
||||
agent.id,
|
||||
openAIRequest,
|
||||
conversation.id,
|
||||
storedState.responseId // Pass response ID for resume
|
||||
);
|
||||
|
||||
for await (const openAIEvent of streamGenerator) {
|
||||
// Pass all events to debug panel
|
||||
onDebugEvent(openAIEvent);
|
||||
|
||||
// Handle response.completed event
|
||||
if (openAIEvent.type === "response.completed") {
|
||||
const completedEvent = openAIEvent as import("@/types/openai").ResponseCompletedEvent;
|
||||
const usage = completedEvent.response?.usage;
|
||||
|
||||
if (usage) {
|
||||
currentMessageUsage.current = {
|
||||
input_tokens: usage.input_tokens,
|
||||
output_tokens: usage.output_tokens,
|
||||
total_tokens: usage.total_tokens,
|
||||
};
|
||||
}
|
||||
continue;
|
||||
}
|
||||
|
||||
// Handle response.failed event
|
||||
if (openAIEvent.type === "response.failed") {
|
||||
const failedEvent = openAIEvent as import("@/types/openai").ResponseFailedEvent;
|
||||
const error = failedEvent.response?.error;
|
||||
const errorMessage = error
|
||||
? typeof error === "object" && "message" in error
|
||||
? (error as any).message
|
||||
: JSON.stringify(error)
|
||||
: "Request failed";
|
||||
|
||||
const currentItems = useDevUIStore.getState().chatItems;
|
||||
setChatItems(currentItems.map((item) =>
|
||||
item.id === assistantMessage.id && item.type === "message"
|
||||
? {
|
||||
...item,
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: accumulatedTextRef.current || errorMessage,
|
||||
} as import("@/types/openai").MessageTextContent,
|
||||
],
|
||||
status: "incomplete" as const,
|
||||
}
|
||||
: item
|
||||
));
|
||||
setIsStreaming(false);
|
||||
return;
|
||||
}
|
||||
|
||||
// Handle function approval request events
|
||||
if (openAIEvent.type === "response.function_approval.requested") {
|
||||
const approvalEvent = openAIEvent as import("@/types/openai").ResponseFunctionApprovalRequestedEvent;
|
||||
setPendingApprovals([
|
||||
...useDevUIStore.getState().pendingApprovals,
|
||||
{
|
||||
request_id: approvalEvent.request_id,
|
||||
function_call: approvalEvent.function_call,
|
||||
},
|
||||
]);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Handle function approval response events
|
||||
if (openAIEvent.type === "response.function_approval.responded") {
|
||||
const responseEvent = openAIEvent as import("@/types/openai").ResponseFunctionApprovalRespondedEvent;
|
||||
setPendingApprovals(
|
||||
useDevUIStore.getState().pendingApprovals.filter((a) => a.request_id !== responseEvent.request_id)
|
||||
);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Handle error events
|
||||
if (openAIEvent.type === "error") {
|
||||
const errorEvent = openAIEvent as ExtendedResponseStreamEvent & { message?: string };
|
||||
const errorMessage = errorEvent.message || "An error occurred";
|
||||
|
||||
const currentItems = useDevUIStore.getState().chatItems;
|
||||
setChatItems(currentItems.map((item) =>
|
||||
item.id === assistantMessage.id && item.type === "message"
|
||||
? {
|
||||
...item,
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: accumulatedTextRef.current || errorMessage,
|
||||
} as import("@/types/openai").MessageTextContent,
|
||||
],
|
||||
status: "incomplete" as const,
|
||||
}
|
||||
: item
|
||||
));
|
||||
setIsStreaming(false);
|
||||
return;
|
||||
}
|
||||
|
||||
// Handle text delta events
|
||||
if (
|
||||
openAIEvent.type === "response.output_text.delta" &&
|
||||
"delta" in openAIEvent &&
|
||||
openAIEvent.delta
|
||||
) {
|
||||
accumulatedTextRef.current += openAIEvent.delta;
|
||||
|
||||
const currentItems = useDevUIStore.getState().chatItems;
|
||||
setChatItems(currentItems.map((item) =>
|
||||
item.id === assistantMessage.id && item.type === "message"
|
||||
? {
|
||||
...item,
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: accumulatedTextRef.current,
|
||||
} as import("@/types/openai").MessageTextContent,
|
||||
],
|
||||
status: "in_progress" as const,
|
||||
}
|
||||
: item
|
||||
));
|
||||
}
|
||||
}
|
||||
|
||||
// Stream ended - mark as complete
|
||||
const finalUsage = currentMessageUsage.current;
|
||||
|
||||
const currentItems = useDevUIStore.getState().chatItems;
|
||||
setChatItems(currentItems.map((item) =>
|
||||
item.id === assistantMessage.id && item.type === "message"
|
||||
? {
|
||||
...item,
|
||||
status: "completed" as const,
|
||||
usage: finalUsage || undefined,
|
||||
}
|
||||
: item
|
||||
));
|
||||
setIsStreaming(false);
|
||||
|
||||
if (finalUsage) {
|
||||
updateConversationUsage(finalUsage.total_tokens);
|
||||
}
|
||||
|
||||
currentMessageUsage.current = null;
|
||||
} catch (error) {
|
||||
const currentItems = useDevUIStore.getState().chatItems;
|
||||
setChatItems(currentItems.map((item) =>
|
||||
item.id === assistantMessage.id && item.type === "message"
|
||||
? {
|
||||
...item,
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error resuming stream: ${
|
||||
error instanceof Error ? error.message : "Unknown error"
|
||||
}`,
|
||||
} as import("@/types/openai").MessageTextContent,
|
||||
],
|
||||
status: "incomplete" as const,
|
||||
}
|
||||
: item
|
||||
));
|
||||
setIsStreaming(false);
|
||||
}
|
||||
};
|
||||
|
||||
const loadConversations = async () => {
|
||||
if (!selectedAgent) return;
|
||||
|
||||
setLoadingConversations(true);
|
||||
try {
|
||||
// Step 1: Try to list conversations from backend (DevUI extension)
|
||||
// This works with DevUI backend but fails with OpenAI/Azure (they don't have list endpoint)
|
||||
// Step 1: Always try to list conversations from backend first
|
||||
// This ensures we get the latest data from the server
|
||||
try {
|
||||
const { data: conversations } = await apiClient.listConversations(
|
||||
selectedAgent.id
|
||||
);
|
||||
|
||||
// Backend successfully returned conversations list
|
||||
setAvailableConversations(conversations);
|
||||
|
||||
if (conversations.length > 0) {
|
||||
// Found conversations on backend - use most recent
|
||||
const mostRecent = conversations[0];
|
||||
setAvailableConversations(conversations);
|
||||
setCurrentConversation(mostRecent);
|
||||
|
||||
// Load conversation items from backend
|
||||
try {
|
||||
const { data: items } = await apiClient.listConversationItems(
|
||||
mostRecent.id
|
||||
);
|
||||
// Load all conversation items with pagination
|
||||
let allItems: unknown[] = [];
|
||||
let hasMore = true;
|
||||
let after: string | undefined = undefined;
|
||||
|
||||
while (hasMore) {
|
||||
const result = await apiClient.listConversationItems(
|
||||
mostRecent.id,
|
||||
{ order: "asc", after } // Load in chronological order (oldest first)
|
||||
);
|
||||
allItems = allItems.concat(result.data);
|
||||
hasMore = result.has_more;
|
||||
|
||||
// Get the last item's ID for pagination
|
||||
if (hasMore && result.data.length > 0) {
|
||||
const lastItem = result.data[result.data.length - 1] as { id?: string };
|
||||
after = lastItem.id;
|
||||
}
|
||||
}
|
||||
|
||||
// Use OpenAI ConversationItems directly (no conversion!)
|
||||
setChatItems(items as import("@/types/openai").ConversationItem[]);
|
||||
setChatItems(allItems as import("@/types/openai").ConversationItem[]);
|
||||
setIsStreaming(false);
|
||||
|
||||
// Check for incomplete stream and resume if needed
|
||||
const state = loadStreamingState(mostRecent.id);
|
||||
|
||||
if (state && !state.completed) {
|
||||
accumulatedTextRef.current = state.accumulatedText || "";
|
||||
// Add assistant message with resumed text
|
||||
const assistantMsg: import("@/types/openai").ConversationMessage = {
|
||||
id: state.lastMessageId || `assistant-${Date.now()}`,
|
||||
type: "message",
|
||||
role: "assistant",
|
||||
content: state.accumulatedText ? [{ type: "text", text: state.accumulatedText }] : [],
|
||||
status: "in_progress",
|
||||
};
|
||||
setChatItems([...allItems as import("@/types/openai").ConversationItem[], assistantMsg]);
|
||||
setIsStreaming(true);
|
||||
|
||||
// Resume streaming from where we left off
|
||||
setTimeout(() => {
|
||||
resumeStreaming(assistantMsg, mostRecent, selectedAgent);
|
||||
}, 100);
|
||||
}
|
||||
|
||||
// Scroll to bottom after loading conversation
|
||||
setTimeout(() => {
|
||||
messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
|
||||
}, 100);
|
||||
} catch {
|
||||
// 404 means conversation exists but has no items yet (newly created)
|
||||
// This is normal - just start with empty chat
|
||||
@@ -316,11 +554,6 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
setIsStreaming(false);
|
||||
}
|
||||
|
||||
// Cache to localStorage for faster future loads
|
||||
localStorage.setItem(
|
||||
`devui_convs_${selectedAgent.id}`,
|
||||
JSON.stringify(conversations)
|
||||
);
|
||||
return;
|
||||
}
|
||||
} catch {
|
||||
@@ -371,9 +604,6 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
setAvailableConversations([newConversation]);
|
||||
setChatItems([]);
|
||||
setIsStreaming(false);
|
||||
|
||||
// Save to localStorage
|
||||
localStorage.setItem(cachedKey, JSON.stringify([newConversation]));
|
||||
} catch {
|
||||
setAvailableConversations([]);
|
||||
setChatItems([]);
|
||||
@@ -387,10 +617,12 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
setChatItems([]);
|
||||
setIsStreaming(false);
|
||||
setCurrentConversation(undefined);
|
||||
accumulatedText.current = "";
|
||||
accumulatedTextRef.current = "";
|
||||
|
||||
loadConversations();
|
||||
}, [selectedAgent, setLoadingConversations, setAvailableConversations, setCurrentConversation, setChatItems, setIsStreaming]);
|
||||
// currentConversation is intentionally excluded - this effect should only run when agent changes
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [selectedAgent, onDebugEvent, setChatItems, setIsStreaming, setLoadingConversations, setAvailableConversations, setCurrentConversation, setPendingApprovals, updateConversationUsage]);
|
||||
|
||||
// Handle file uploads
|
||||
const handleFilesSelected = async (files: File[]) => {
|
||||
@@ -626,16 +858,11 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
setIsStreaming(false);
|
||||
// Reset conversation usage by setting it to initial state
|
||||
useDevUIStore.setState({ conversationUsage: { total_tokens: 0, message_count: 0 } });
|
||||
accumulatedText.current = "";
|
||||
|
||||
// Update localStorage cache with new conversation
|
||||
const cachedKey = `devui_convs_${selectedAgent.id}`;
|
||||
const updated = [newConversation, ...availableConversations];
|
||||
localStorage.setItem(cachedKey, JSON.stringify(updated));
|
||||
accumulatedTextRef.current = "";
|
||||
} catch {
|
||||
// Failed to create conversation
|
||||
}
|
||||
}, [selectedAgent, availableConversations, setCurrentConversation, setAvailableConversations, setChatItems, setIsStreaming]);
|
||||
}, [selectedAgent, setCurrentConversation, setAvailableConversations, setChatItems, setIsStreaming]);
|
||||
|
||||
// Handle conversation deletion
|
||||
const handleDeleteConversation = useCallback(
|
||||
@@ -660,15 +887,6 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
);
|
||||
setAvailableConversations(updatedConversations);
|
||||
|
||||
// Update localStorage cache
|
||||
if (selectedAgent) {
|
||||
const cachedKey = `devui_convs_${selectedAgent.id}`;
|
||||
localStorage.setItem(
|
||||
cachedKey,
|
||||
JSON.stringify(updatedConversations)
|
||||
);
|
||||
}
|
||||
|
||||
// If deleted conversation was selected, switch to another conversation or clear chat
|
||||
if (currentConversation?.id === conversationId) {
|
||||
if (updatedConversations.length > 0) {
|
||||
@@ -683,7 +901,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
setChatItems([]);
|
||||
setIsStreaming(false);
|
||||
useDevUIStore.setState({ conversationUsage: { total_tokens: 0, message_count: 0 } });
|
||||
accumulatedText.current = "";
|
||||
accumulatedTextRef.current = "";
|
||||
}
|
||||
}
|
||||
|
||||
@@ -694,7 +912,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
alert("Failed to delete conversation. Please try again.");
|
||||
}
|
||||
},
|
||||
[availableConversations, currentConversation, selectedAgent, onDebugEvent, setAvailableConversations, setCurrentConversation, setChatItems, setIsStreaming]
|
||||
[availableConversations, currentConversation, onDebugEvent, setAvailableConversations, setCurrentConversation, setChatItems, setIsStreaming]
|
||||
);
|
||||
|
||||
// Handle conversation selection
|
||||
@@ -711,11 +929,28 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
onDebugEvent("clear");
|
||||
|
||||
try {
|
||||
// Load conversation history from backend
|
||||
const result = await apiClient.listConversationItems(conversationId);
|
||||
// Load conversation history from backend with pagination
|
||||
let allItems: unknown[] = [];
|
||||
let hasMore = true;
|
||||
let after: string | undefined = undefined;
|
||||
|
||||
while (hasMore) {
|
||||
const result = await apiClient.listConversationItems(conversationId, {
|
||||
order: "asc", // Load in chronological order (oldest first)
|
||||
after,
|
||||
});
|
||||
allItems = allItems.concat(result.data);
|
||||
hasMore = result.has_more;
|
||||
|
||||
// Get the last item's ID for pagination
|
||||
if (hasMore && result.data.length > 0) {
|
||||
const lastItem = result.data[result.data.length - 1] as { id?: string };
|
||||
after = lastItem.id;
|
||||
}
|
||||
}
|
||||
|
||||
// Use OpenAI ConversationItems directly (no conversion!)
|
||||
const items = result.data as import("@/types/openai").ConversationItem[];
|
||||
const items = allItems as import("@/types/openai").ConversationItem[];
|
||||
|
||||
setChatItems(items);
|
||||
setIsStreaming(false);
|
||||
@@ -727,6 +962,27 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
message_count: items.length,
|
||||
}
|
||||
});
|
||||
|
||||
// Check for incomplete stream and restore accumulated text
|
||||
const state = loadStreamingState(conversationId);
|
||||
if (state?.accumulatedText) {
|
||||
accumulatedTextRef.current = state.accumulatedText;
|
||||
// Add assistant message with resumed text - streaming will continue automatically
|
||||
const assistantMsg: import("@/types/openai").ConversationMessage = {
|
||||
id: `assistant-${Date.now()}`,
|
||||
type: "message",
|
||||
role: "assistant",
|
||||
content: [{ type: "output_text", text: state.accumulatedText }],
|
||||
status: "in_progress",
|
||||
};
|
||||
setChatItems([...items, assistantMsg]);
|
||||
setIsStreaming(true);
|
||||
}
|
||||
|
||||
// Scroll to bottom after loading conversation
|
||||
setTimeout(() => {
|
||||
messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
|
||||
}, 100);
|
||||
} catch {
|
||||
// 404 means conversation doesn't exist or has no items yet
|
||||
// This can happen if server restarted (in-memory store cleared)
|
||||
@@ -736,7 +992,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
useDevUIStore.setState({ conversationUsage: { total_tokens: 0, message_count: 0 } });
|
||||
}
|
||||
|
||||
accumulatedText.current = "";
|
||||
accumulatedTextRef.current = "";
|
||||
},
|
||||
[availableConversations, onDebugEvent, setCurrentConversation, setChatItems, setIsStreaming]
|
||||
);
|
||||
@@ -851,13 +1107,18 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
}
|
||||
}
|
||||
|
||||
// Clear any previous streaming state for this conversation before starting new message
|
||||
if (conversationToUse?.id) {
|
||||
apiClient.clearStreamingState(conversationToUse.id);
|
||||
}
|
||||
|
||||
const apiRequest = {
|
||||
input: request.input,
|
||||
conversation_id: conversationToUse?.id,
|
||||
};
|
||||
|
||||
// Clear text accumulator for new response
|
||||
accumulatedText.current = "";
|
||||
accumulatedTextRef.current = "";
|
||||
|
||||
// Use OpenAI-compatible API streaming - direct event handling
|
||||
const streamGenerator = apiClient.streamAgentExecutionOpenAI(
|
||||
@@ -884,6 +1145,35 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
continue; // Continue processing other events
|
||||
}
|
||||
|
||||
// Handle response.failed event
|
||||
if (openAIEvent.type === "response.failed") {
|
||||
const failedEvent = openAIEvent as import("@/types/openai").ResponseFailedEvent;
|
||||
const error = failedEvent.response?.error;
|
||||
const errorMessage = error
|
||||
? typeof error === "object" && "message" in error
|
||||
? (error as any).message
|
||||
: JSON.stringify(error)
|
||||
: "Request failed";
|
||||
|
||||
const currentItems = useDevUIStore.getState().chatItems;
|
||||
setChatItems(currentItems.map((item) =>
|
||||
item.id === assistantMessage.id && item.type === "message"
|
||||
? {
|
||||
...item,
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: accumulatedTextRef.current || errorMessage,
|
||||
} as import("@/types/openai").MessageTextContent,
|
||||
],
|
||||
status: "incomplete" as const,
|
||||
}
|
||||
: item
|
||||
));
|
||||
setIsStreaming(false);
|
||||
return;
|
||||
}
|
||||
|
||||
// Handle function approval request events
|
||||
if (openAIEvent.type === "response.function_approval.requested") {
|
||||
const approvalEvent = openAIEvent as import("@/types/openai").ResponseFunctionApprovalRequestedEvent;
|
||||
@@ -943,7 +1233,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
"delta" in openAIEvent &&
|
||||
openAIEvent.delta
|
||||
) {
|
||||
accumulatedText.current += openAIEvent.delta;
|
||||
accumulatedTextRef.current += openAIEvent.delta;
|
||||
|
||||
// Update assistant message with accumulated content
|
||||
const currentItems = useDevUIStore.getState().chatItems;
|
||||
@@ -954,7 +1244,7 @@ export function AgentView({ selectedAgent, onDebugEvent }: AgentViewProps) {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: accumulatedText.current,
|
||||
text: accumulatedTextRef.current,
|
||||
} as import("@/types/openai").MessageTextContent,
|
||||
],
|
||||
status: "in_progress" as const,
|
||||
|
||||
+3
-1
@@ -23,7 +23,7 @@ interface ContentRendererProps {
|
||||
|
||||
// Text content renderer
|
||||
function TextContentRenderer({ content, className, isStreaming }: ContentRendererProps) {
|
||||
if (content.type !== "text") return null;
|
||||
if (content.type !== "text" && content.type !== "input_text" && content.type !== "output_text") return null;
|
||||
|
||||
const text = content.text;
|
||||
|
||||
@@ -160,6 +160,8 @@ function FileContentRenderer({ content, className }: ContentRendererProps) {
|
||||
export function OpenAIContentRenderer({ content, className, isStreaming }: ContentRendererProps) {
|
||||
switch (content.type) {
|
||||
case "text":
|
||||
case "input_text":
|
||||
case "output_text":
|
||||
return <TextContentRenderer content={content} className={className} isStreaming={isStreaming} />;
|
||||
case "input_image":
|
||||
return <ImageContentRenderer content={content} className={className} />;
|
||||
|
||||
@@ -554,6 +554,10 @@ export function WorkflowView({
|
||||
try {
|
||||
const request = { input_data: inputData };
|
||||
|
||||
// Clear any previous streaming state before starting new workflow execution
|
||||
// Note: Workflows don't use conversation IDs, so we use workflow ID as the key
|
||||
apiClient.clearStreamingState(selectedWorkflow.id);
|
||||
|
||||
// Use OpenAI-compatible API streaming - direct event handling
|
||||
const streamGenerator = apiClient.streamWorkflowExecutionOpenAI(
|
||||
selectedWorkflow.id,
|
||||
|
||||
@@ -3,6 +3,10 @@ import { createRoot } from 'react-dom/client'
|
||||
import './index.css'
|
||||
import App from './App.tsx'
|
||||
import { ThemeProvider } from "./components/theme-provider"
|
||||
import { initStreamingState } from "./services/api"
|
||||
|
||||
// Initialize streaming state management (clears expired states)
|
||||
initStreamingState();
|
||||
|
||||
createRoot(document.getElementById('root')!).render(
|
||||
<StrictMode>
|
||||
|
||||
@@ -14,6 +14,12 @@ import type {
|
||||
} from "@/types";
|
||||
import type { AgentFrameworkRequest } from "@/types/agent-framework";
|
||||
import type { ExtendedResponseStreamEvent } from "@/types/openai";
|
||||
import {
|
||||
loadStreamingState,
|
||||
updateStreamingState,
|
||||
markStreamingCompleted,
|
||||
clearStreamingState,
|
||||
} from "./streaming-state";
|
||||
|
||||
// Backend API response type - polymorphic entity that can be agent or workflow
|
||||
// This matches the Python Pydantic EntityInfo model which has all fields optional
|
||||
@@ -57,9 +63,27 @@ const DEFAULT_API_BASE_URL =
|
||||
? import.meta.env.VITE_API_BASE_URL
|
||||
: "http://localhost:8080";
|
||||
|
||||
// Retry configuration for streaming
|
||||
const RETRY_INTERVAL_MS = 1000; // Retry every second
|
||||
const MAX_RETRY_ATTEMPTS = 600; // Max 600 retries (10 minutes total)
|
||||
|
||||
// Get backend URL from localStorage or default
|
||||
function getBackendUrl(): string {
|
||||
return localStorage.getItem("devui_backend_url") || DEFAULT_API_BASE_URL;
|
||||
const stored = localStorage.getItem("devui_backend_url");
|
||||
if (stored) return stored;
|
||||
|
||||
// If VITE_API_BASE_URL is explicitly set to empty string, use relative path
|
||||
// This allows the frontend to call the same host it's served from
|
||||
if (import.meta.env.VITE_API_BASE_URL === "") {
|
||||
return "";
|
||||
}
|
||||
|
||||
return DEFAULT_API_BASE_URL;
|
||||
}
|
||||
|
||||
// Helper to sleep for a given duration
|
||||
function sleep(ms: number): Promise<void> {
|
||||
return new Promise((resolve) => setTimeout(resolve, ms));
|
||||
}
|
||||
|
||||
class ApiClient {
|
||||
@@ -272,6 +296,8 @@ class ApiClient {
|
||||
await this.request(`/v1/conversations/${conversationId}`, {
|
||||
method: "DELETE",
|
||||
});
|
||||
// Clear streaming state when conversation is deleted
|
||||
clearStreamingState(conversationId);
|
||||
return true;
|
||||
} catch {
|
||||
return false;
|
||||
@@ -297,10 +323,230 @@ class ApiClient {
|
||||
|
||||
// OpenAI-compatible streaming methods using /v1/responses endpoint
|
||||
|
||||
// Private helper method that handles the actual streaming with retry logic
|
||||
private async *streamOpenAIResponse(
|
||||
openAIRequest: AgentFrameworkRequest,
|
||||
conversationId?: string,
|
||||
resumeResponseId?: string
|
||||
): AsyncGenerator<ExtendedResponseStreamEvent, void, unknown> {
|
||||
let lastSequenceNumber = -1;
|
||||
let retryCount = 0;
|
||||
let hasYieldedAnyEvent = false;
|
||||
let currentResponseId: string | undefined = resumeResponseId;
|
||||
let lastMessageId: string | undefined = undefined;
|
||||
|
||||
// Try to resume from stored state if conversation ID is provided
|
||||
if (conversationId) {
|
||||
const storedState = loadStreamingState(conversationId);
|
||||
if (storedState) {
|
||||
// Use stored response ID if no explicit one provided
|
||||
if (!resumeResponseId) {
|
||||
currentResponseId = storedState.responseId;
|
||||
}
|
||||
|
||||
lastSequenceNumber = storedState.lastSequenceNumber;
|
||||
lastMessageId = storedState.lastMessageId;
|
||||
|
||||
// Replay stored events only if we're not explicitly resuming
|
||||
// (explicit resume means the caller already has the events)
|
||||
if (!resumeResponseId) {
|
||||
for (const event of storedState.events) {
|
||||
hasYieldedAnyEvent = true;
|
||||
yield event;
|
||||
}
|
||||
} else {
|
||||
// Mark that we've already seen events up to this sequence number
|
||||
hasYieldedAnyEvent = storedState.events.length > 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
while (retryCount <= MAX_RETRY_ATTEMPTS) {
|
||||
try {
|
||||
// If we have a response_id from a previous attempt, use GET endpoint to resume
|
||||
// Otherwise, use POST to create a new response
|
||||
let response: Response;
|
||||
if (currentResponseId) {
|
||||
const params = new URLSearchParams();
|
||||
params.set("stream", "true");
|
||||
if (lastSequenceNumber >= 0) {
|
||||
params.set("starting_after", lastSequenceNumber.toString());
|
||||
}
|
||||
const url = `${this.baseUrl}/v1/responses/${currentResponseId}?${params.toString()}`;
|
||||
response = await fetch(url, {
|
||||
method: "GET",
|
||||
headers: {
|
||||
Accept: "text/event-stream",
|
||||
},
|
||||
});
|
||||
} else {
|
||||
const url = `${this.baseUrl}/v1/responses`;
|
||||
response = await fetch(url, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Accept: "text/event-stream",
|
||||
},
|
||||
body: JSON.stringify(openAIRequest),
|
||||
});
|
||||
}
|
||||
|
||||
if (!response.ok) {
|
||||
// Try to extract detailed error message from response body
|
||||
let errorMessage = `Request failed with status ${response.status}`;
|
||||
try {
|
||||
const errorBody = await response.json();
|
||||
if (errorBody.error && errorBody.error.message) {
|
||||
errorMessage = errorBody.error.message;
|
||||
} else if (errorBody.detail) {
|
||||
errorMessage = errorBody.detail;
|
||||
}
|
||||
} catch {
|
||||
// Fallback to generic message if parsing fails
|
||||
}
|
||||
throw new Error(errorMessage);
|
||||
}
|
||||
|
||||
const reader = response.body?.getReader();
|
||||
if (!reader) {
|
||||
throw new Error("Response body is not readable");
|
||||
}
|
||||
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = "";
|
||||
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
|
||||
if (done) {
|
||||
// Stream completed successfully
|
||||
if (conversationId) {
|
||||
markStreamingCompleted(conversationId);
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
buffer += decoder.decode(value, { stream: true });
|
||||
|
||||
// Parse SSE events
|
||||
const lines = buffer.split("\n");
|
||||
buffer = lines.pop() || ""; // Keep incomplete line in buffer
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith("data: ")) {
|
||||
const dataStr = line.slice(6);
|
||||
|
||||
// Handle [DONE] signal
|
||||
if (dataStr === "[DONE]") {
|
||||
if (conversationId) {
|
||||
markStreamingCompleted(conversationId);
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
const openAIEvent: ExtendedResponseStreamEvent =
|
||||
JSON.parse(dataStr);
|
||||
|
||||
// Capture response_id if present in the event for use in retries
|
||||
if ("response" in openAIEvent && openAIEvent.response && typeof openAIEvent.response === "object" && "id" in openAIEvent.response) {
|
||||
const newResponseId = openAIEvent.response.id as string;
|
||||
if (!currentResponseId || currentResponseId !== newResponseId) {
|
||||
currentResponseId = newResponseId;
|
||||
}
|
||||
} else if ("id" in openAIEvent && typeof openAIEvent.id === "string" && openAIEvent.id.startsWith("resp_")) {
|
||||
const newResponseId = openAIEvent.id;
|
||||
if (!currentResponseId || currentResponseId !== newResponseId) {
|
||||
currentResponseId = newResponseId;
|
||||
}
|
||||
}
|
||||
|
||||
// Track last message ID if present (for user/assistant messages)
|
||||
if ("item_id" in openAIEvent && openAIEvent.item_id) {
|
||||
lastMessageId = openAIEvent.item_id;
|
||||
}
|
||||
|
||||
// Check for sequence number restart (server restarted response)
|
||||
const eventSeq = "sequence_number" in openAIEvent ? openAIEvent.sequence_number : undefined;
|
||||
if (eventSeq !== undefined) {
|
||||
// If we've received events before and sequence restarted from 0/1
|
||||
if (hasYieldedAnyEvent && eventSeq <= 1 && lastSequenceNumber > 1) {
|
||||
// Server restarted the response - clear old state and start fresh
|
||||
if (conversationId) {
|
||||
clearStreamingState(conversationId);
|
||||
}
|
||||
yield {
|
||||
type: "error",
|
||||
message: "Connection lost - previous response failed. Starting new response.",
|
||||
} as ExtendedResponseStreamEvent;
|
||||
lastSequenceNumber = eventSeq;
|
||||
hasYieldedAnyEvent = true;
|
||||
|
||||
// Save new event to storage
|
||||
if (conversationId && currentResponseId) {
|
||||
updateStreamingState(conversationId, openAIEvent, currentResponseId, lastMessageId);
|
||||
}
|
||||
|
||||
yield openAIEvent;
|
||||
}
|
||||
// Skip events we've already seen (resume from last position)
|
||||
else if (eventSeq <= lastSequenceNumber) {
|
||||
continue; // Skip duplicate event
|
||||
} else {
|
||||
lastSequenceNumber = eventSeq;
|
||||
hasYieldedAnyEvent = true;
|
||||
|
||||
// Save event to storage before yielding
|
||||
if (conversationId && currentResponseId) {
|
||||
updateStreamingState(conversationId, openAIEvent, currentResponseId, lastMessageId);
|
||||
}
|
||||
|
||||
yield openAIEvent;
|
||||
}
|
||||
} else {
|
||||
// No sequence number - just yield the event
|
||||
hasYieldedAnyEvent = true;
|
||||
|
||||
// Still save to storage if we have conversation context
|
||||
if (conversationId && currentResponseId) {
|
||||
updateStreamingState(conversationId, openAIEvent, currentResponseId, lastMessageId);
|
||||
}
|
||||
|
||||
yield openAIEvent;
|
||||
}
|
||||
} catch (e) {
|
||||
console.error("Failed to parse OpenAI SSE event:", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
}
|
||||
} catch (error) {
|
||||
// Network error occurred - prepare to retry
|
||||
retryCount++;
|
||||
|
||||
if (retryCount > MAX_RETRY_ATTEMPTS) {
|
||||
// Max retries exceeded - give up
|
||||
throw new Error(
|
||||
`Connection failed after ${MAX_RETRY_ATTEMPTS} retry attempts: ${error instanceof Error ? error.message : String(error)}`
|
||||
);
|
||||
}
|
||||
|
||||
// Wait before retrying
|
||||
await sleep(RETRY_INTERVAL_MS);
|
||||
// Loop will retry with GET if we have response_id, otherwise POST
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Stream agent execution using OpenAI format with simplified routing
|
||||
async *streamAgentExecutionOpenAI(
|
||||
agentId: string,
|
||||
request: RunAgentRequest
|
||||
request: RunAgentRequest,
|
||||
resumeResponseId?: string
|
||||
): AsyncGenerator<ExtendedResponseStreamEvent, void, unknown> {
|
||||
const openAIRequest: AgentFrameworkRequest = {
|
||||
model: agentId, // Model IS the entity_id (simplified routing!)
|
||||
@@ -309,87 +555,20 @@ class ApiClient {
|
||||
conversation: request.conversation_id, // OpenAI standard conversation param
|
||||
};
|
||||
|
||||
return yield* this.streamAgentExecutionOpenAIDirect(agentId, openAIRequest);
|
||||
return yield* this.streamAgentExecutionOpenAIDirect(agentId, openAIRequest, request.conversation_id, resumeResponseId);
|
||||
}
|
||||
|
||||
// Stream agent execution using direct OpenAI format
|
||||
async *streamAgentExecutionOpenAIDirect(
|
||||
_agentId: string,
|
||||
openAIRequest: AgentFrameworkRequest
|
||||
openAIRequest: AgentFrameworkRequest,
|
||||
conversationId?: string,
|
||||
resumeResponseId?: string
|
||||
): AsyncGenerator<ExtendedResponseStreamEvent, void, unknown> {
|
||||
|
||||
const response = await fetch(`${this.baseUrl}/v1/responses`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Accept: "text/event-stream",
|
||||
},
|
||||
body: JSON.stringify(openAIRequest),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
// Try to extract detailed error message from response body
|
||||
let errorMessage = `Request failed with status ${response.status}`;
|
||||
try {
|
||||
const errorBody = await response.json();
|
||||
if (errorBody.error && errorBody.error.message) {
|
||||
errorMessage = errorBody.error.message;
|
||||
} else if (errorBody.detail) {
|
||||
errorMessage = errorBody.detail;
|
||||
}
|
||||
} catch {
|
||||
// Fallback to generic message if parsing fails
|
||||
}
|
||||
throw new Error(errorMessage);
|
||||
}
|
||||
|
||||
const reader = response.body?.getReader();
|
||||
if (!reader) {
|
||||
throw new Error("Response body is not readable");
|
||||
}
|
||||
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = "";
|
||||
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
|
||||
if (done) {
|
||||
break;
|
||||
}
|
||||
|
||||
buffer += decoder.decode(value, { stream: true });
|
||||
|
||||
// Parse SSE events
|
||||
const lines = buffer.split("\n");
|
||||
buffer = lines.pop() || ""; // Keep incomplete line in buffer
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith("data: ")) {
|
||||
const dataStr = line.slice(6);
|
||||
|
||||
// Handle [DONE] signal
|
||||
if (dataStr === "[DONE]") {
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
const openAIEvent: ExtendedResponseStreamEvent =
|
||||
JSON.parse(dataStr);
|
||||
yield openAIEvent; // Direct pass-through - no conversion!
|
||||
} catch (e) {
|
||||
console.error("Failed to parse OpenAI SSE event:", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
}
|
||||
yield* this.streamOpenAIResponse(openAIRequest, conversationId, resumeResponseId);
|
||||
}
|
||||
|
||||
// Stream workflow execution using OpenAI format - direct event pass-through
|
||||
// Stream workflow execution using OpenAI format
|
||||
async *streamWorkflowExecutionOpenAI(
|
||||
workflowId: string,
|
||||
request: RunWorkflowRequest
|
||||
@@ -402,75 +581,7 @@ class ApiClient {
|
||||
conversation: request.conversation_id, // Include conversation if present
|
||||
};
|
||||
|
||||
const response = await fetch(`${this.baseUrl}/v1/responses`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Accept: "text/event-stream",
|
||||
},
|
||||
body: JSON.stringify(openAIRequest),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
// Try to extract detailed error message from response body
|
||||
let errorMessage = `Request failed with status ${response.status}`;
|
||||
try {
|
||||
const errorBody = await response.json();
|
||||
if (errorBody.error && errorBody.error.message) {
|
||||
errorMessage = errorBody.error.message;
|
||||
} else if (errorBody.detail) {
|
||||
errorMessage = errorBody.detail;
|
||||
}
|
||||
} catch {
|
||||
// Fallback to generic message if parsing fails
|
||||
}
|
||||
throw new Error(errorMessage);
|
||||
}
|
||||
|
||||
const reader = response.body?.getReader();
|
||||
if (!reader) {
|
||||
throw new Error("Response body is not readable");
|
||||
}
|
||||
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = "";
|
||||
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
|
||||
if (done) {
|
||||
break;
|
||||
}
|
||||
|
||||
buffer += decoder.decode(value, { stream: true });
|
||||
|
||||
// Parse SSE events
|
||||
const lines = buffer.split("\n");
|
||||
buffer = lines.pop() || ""; // Keep incomplete line in buffer
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith("data: ")) {
|
||||
const dataStr = line.slice(6);
|
||||
|
||||
// Handle [DONE] signal
|
||||
if (dataStr === "[DONE]") {
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
const openAIEvent: ExtendedResponseStreamEvent =
|
||||
JSON.parse(dataStr);
|
||||
yield openAIEvent; // Direct pass-through - no conversion!
|
||||
} catch (e) {
|
||||
console.error("Failed to parse OpenAI SSE event:", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
}
|
||||
yield* this.streamOpenAIResponse(openAIRequest, request.conversation_id);
|
||||
}
|
||||
|
||||
// REMOVED: Legacy streaming methods - use streamAgentExecutionOpenAI and streamWorkflowExecutionOpenAI instead
|
||||
@@ -503,8 +614,16 @@ class ApiClient {
|
||||
body: JSON.stringify(request),
|
||||
});
|
||||
}
|
||||
|
||||
// Clear streaming state for a conversation (e.g., when starting a new message)
|
||||
clearStreamingState(conversationId: string): void {
|
||||
clearStreamingState(conversationId);
|
||||
}
|
||||
}
|
||||
|
||||
// Export singleton instance
|
||||
export const apiClient = new ApiClient();
|
||||
export { ApiClient };
|
||||
|
||||
// Export streaming state init function
|
||||
export { initStreamingState } from "./streaming-state";
|
||||
|
||||
@@ -0,0 +1,199 @@
|
||||
/**
|
||||
* Streaming State Persistence
|
||||
*
|
||||
* Manages browser storage of streaming response state to enable:
|
||||
* - Resume interrupted streams after page refresh
|
||||
* - Replay cached events before fetching new ones
|
||||
* - Graceful recovery from network disconnections
|
||||
*/
|
||||
|
||||
import type { ExtendedResponseStreamEvent } from "@/types/openai";
|
||||
|
||||
export interface StreamingState {
|
||||
conversationId: string;
|
||||
responseId: string;
|
||||
lastMessageId?: string;
|
||||
lastSequenceNumber: number;
|
||||
events: ExtendedResponseStreamEvent[];
|
||||
timestamp: number; // When this state was last updated
|
||||
completed: boolean; // Whether the stream completed successfully
|
||||
accumulatedText?: string; // Accumulated text content for quick restoration
|
||||
}
|
||||
|
||||
const STORAGE_KEY_PREFIX = "devui_streaming_state_";
|
||||
const STATE_EXPIRY_MS = 24 * 60 * 60 * 1000; // 24 hours
|
||||
|
||||
/**
|
||||
* Storage key for a specific conversation
|
||||
*/
|
||||
function getStorageKey(conversationId: string): string {
|
||||
return `${STORAGE_KEY_PREFIX}${conversationId}`;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract accumulated text from events (for quick restoration)
|
||||
*/
|
||||
function extractAccumulatedText(events: ExtendedResponseStreamEvent[]): string {
|
||||
let text = "";
|
||||
for (const event of events) {
|
||||
if (event.type === "response.output_text.delta" && "delta" in event) {
|
||||
text += event.delta;
|
||||
}
|
||||
}
|
||||
return text;
|
||||
}
|
||||
|
||||
/**
|
||||
* Save streaming state to browser storage
|
||||
*/
|
||||
export function saveStreamingState(state: StreamingState): void {
|
||||
try {
|
||||
const key = getStorageKey(state.conversationId);
|
||||
const data = JSON.stringify(state);
|
||||
localStorage.setItem(key, data);
|
||||
} catch (error) {
|
||||
console.error("Failed to save streaming state:", error);
|
||||
// If storage is full, try to clear old states
|
||||
try {
|
||||
clearExpiredStreamingStates();
|
||||
// Try again
|
||||
const key = getStorageKey(state.conversationId);
|
||||
const data = JSON.stringify(state);
|
||||
localStorage.setItem(key, data);
|
||||
} catch {
|
||||
console.error("Failed to save streaming state even after cleanup");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Load streaming state from browser storage
|
||||
*/
|
||||
export function loadStreamingState(conversationId: string): StreamingState | null {
|
||||
try {
|
||||
const key = getStorageKey(conversationId);
|
||||
const data = localStorage.getItem(key);
|
||||
|
||||
if (!data) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const state: StreamingState = JSON.parse(data);
|
||||
|
||||
// Check if state has expired
|
||||
const age = Date.now() - state.timestamp;
|
||||
if (age > STATE_EXPIRY_MS) {
|
||||
clearStreamingState(conversationId);
|
||||
return null;
|
||||
}
|
||||
|
||||
// If stream was completed, no need to resume
|
||||
if (state.completed) {
|
||||
return null;
|
||||
}
|
||||
|
||||
return state;
|
||||
} catch (error) {
|
||||
console.error("Failed to load streaming state:", error);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Update streaming state with a new event
|
||||
*/
|
||||
export function updateStreamingState(
|
||||
conversationId: string,
|
||||
event: ExtendedResponseStreamEvent,
|
||||
responseId: string,
|
||||
lastMessageId?: string
|
||||
): void {
|
||||
try {
|
||||
const existing = loadStreamingState(conversationId);
|
||||
const sequenceNumber = "sequence_number" in event ? event.sequence_number : undefined;
|
||||
|
||||
const newEvents = existing ? [...existing.events, event] : [event];
|
||||
|
||||
const state: StreamingState = {
|
||||
conversationId,
|
||||
responseId,
|
||||
lastMessageId,
|
||||
lastSequenceNumber: sequenceNumber ?? (existing?.lastSequenceNumber ?? -1),
|
||||
events: newEvents,
|
||||
timestamp: Date.now(),
|
||||
completed: event.type === "response.completed" || event.type === "response.failed",
|
||||
accumulatedText: extractAccumulatedText(newEvents),
|
||||
};
|
||||
|
||||
saveStreamingState(state);
|
||||
} catch (error) {
|
||||
console.error("Failed to update streaming state:", error);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Mark streaming state as completed
|
||||
*/
|
||||
export function markStreamingCompleted(conversationId: string): void {
|
||||
try {
|
||||
const existing = loadStreamingState(conversationId);
|
||||
if (existing) {
|
||||
existing.completed = true;
|
||||
existing.timestamp = Date.now();
|
||||
saveStreamingState(existing);
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Failed to mark streaming as completed:", error);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Clear streaming state for a conversation
|
||||
*/
|
||||
export function clearStreamingState(conversationId: string): void {
|
||||
try {
|
||||
const key = getStorageKey(conversationId);
|
||||
localStorage.removeItem(key);
|
||||
} catch (error) {
|
||||
console.error("Failed to clear streaming state:", error);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Clear all expired streaming states
|
||||
*/
|
||||
export function clearExpiredStreamingStates(): void {
|
||||
try {
|
||||
const keys = Object.keys(localStorage);
|
||||
const now = Date.now();
|
||||
|
||||
for (const key of keys) {
|
||||
if (key.startsWith(STORAGE_KEY_PREFIX)) {
|
||||
try {
|
||||
const data = localStorage.getItem(key);
|
||||
if (data) {
|
||||
const state: StreamingState = JSON.parse(data);
|
||||
const age = now - state.timestamp;
|
||||
|
||||
if (age > STATE_EXPIRY_MS || state.completed) {
|
||||
localStorage.removeItem(key);
|
||||
}
|
||||
}
|
||||
} catch {
|
||||
// Invalid state, remove it
|
||||
localStorage.removeItem(key);
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Failed to clear expired streaming states:", error);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize streaming state management (call on app startup)
|
||||
*/
|
||||
export function initStreamingState(): void {
|
||||
// Clear expired states on startup
|
||||
clearExpiredStreamingStates();
|
||||
}
|
||||
@@ -347,6 +347,18 @@ export interface MessageTextContent {
|
||||
text: string;
|
||||
}
|
||||
|
||||
export interface MessageInputTextContent {
|
||||
type: "input_text";
|
||||
text: string;
|
||||
}
|
||||
|
||||
export interface MessageOutputTextContent {
|
||||
type: "output_text";
|
||||
text: string;
|
||||
annotations?: any[];
|
||||
logprobs?: any[];
|
||||
}
|
||||
|
||||
export interface MessageInputImage {
|
||||
type: "input_image";
|
||||
image_url: string;
|
||||
@@ -376,6 +388,8 @@ export interface MessageFunctionApprovalResponseContent {
|
||||
|
||||
export type MessageContent =
|
||||
| MessageTextContent
|
||||
| MessageInputTextContent
|
||||
| MessageOutputTextContent
|
||||
| MessageInputImage
|
||||
| MessageInputFile
|
||||
| MessageFunctionApprovalResponseContent;
|
||||
|
||||
@@ -5,6 +5,7 @@ import path from "path";
|
||||
|
||||
// https://vite.dev/config/
|
||||
export default defineConfig({
|
||||
base: "",
|
||||
plugins: [react(), tailwindcss()],
|
||||
resolve: {
|
||||
alias: {
|
||||
@@ -12,12 +13,20 @@ export default defineConfig({
|
||||
},
|
||||
},
|
||||
build: {
|
||||
commonjsOptions: {
|
||||
// Enable deterministic builds, as per https://github.com/vitejs/vite/issues/13672#issuecomment-1784110536
|
||||
strictRequires: true,
|
||||
},
|
||||
outDir: "../agent_framework_devui/ui",
|
||||
emptyOutDir: true,
|
||||
rollupOptions: {
|
||||
output: {
|
||||
manualChunks: undefined,
|
||||
inlineDynamicImports: true,
|
||||
// Use static filenames instead of content hashes
|
||||
entryFileNames: "assets/index.js",
|
||||
chunkFileNames: "assets/[name].js",
|
||||
assetFileNames: "assets/[name].[ext]",
|
||||
},
|
||||
},
|
||||
},
|
||||
|
||||
@@ -24,7 +24,7 @@
|
||||
resolved "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.28.0.tgz"
|
||||
integrity sha512-60X7qkglvrap8mn1lh2ebxXdZYtUcpd7gsmy9kLaBJ4i/WdY8PqTSdxyA8qraikqKQK5C1KRBKXqznrVapyNaw==
|
||||
|
||||
"@babel/core@^7.28.3":
|
||||
"@babel/core@^7.0.0", "@babel/core@^7.0.0-0", "@babel/core@^7.28.3":
|
||||
version "7.28.3"
|
||||
resolved "https://registry.npmjs.org/@babel/core/-/core-7.28.3.tgz"
|
||||
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|
||||
@@ -168,156 +168,9 @@
|
||||
"@babel/helper-string-parser" "^7.27.1"
|
||||
"@babel/helper-validator-identifier" "^7.27.1"
|
||||
|
||||
"@emnapi/core@^1.4.3", "@emnapi/core@^1.4.5":
|
||||
version "1.5.0"
|
||||
resolved "https://registry.yarnpkg.com/@emnapi/core/-/core-1.5.0.tgz#85cd84537ec989cebb2343606a1ee663ce4edaf0"
|
||||
integrity sha512-sbP8GzB1WDzacS8fgNPpHlp6C9VZe+SJP3F90W9rLemaQj2PzIuTEl1qDOYQf58YIpyjViI24y9aPWCjEzY2cg==
|
||||
dependencies:
|
||||
"@emnapi/wasi-threads" "1.1.0"
|
||||
tslib "^2.4.0"
|
||||
|
||||
"@emnapi/runtime@^1.4.3", "@emnapi/runtime@^1.4.5":
|
||||
version "1.5.0"
|
||||
resolved "https://registry.yarnpkg.com/@emnapi/runtime/-/runtime-1.5.0.tgz#9aebfcb9b17195dce3ab53c86787a6b7d058db73"
|
||||
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|
||||
dependencies:
|
||||
tslib "^2.4.0"
|
||||
|
||||
"@emnapi/wasi-threads@1.1.0", "@emnapi/wasi-threads@^1.0.4":
|
||||
version "1.1.0"
|
||||
resolved "https://registry.yarnpkg.com/@emnapi/wasi-threads/-/wasi-threads-1.1.0.tgz#60b2102fddc9ccb78607e4a3cf8403ea69be41bf"
|
||||
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|
||||
dependencies:
|
||||
tslib "^2.4.0"
|
||||
|
||||
"@esbuild/aix-ppc64@0.25.9":
|
||||
version "0.25.9"
|
||||
resolved "https://registry.yarnpkg.com/@esbuild/aix-ppc64/-/aix-ppc64-0.25.9.tgz#bef96351f16520055c947aba28802eede3c9e9a9"
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||||
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|
||||
|
||||
"@esbuild/android-arm64@0.25.9":
|
||||
version "0.25.9"
|
||||
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||||
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||||
|
||||
"@esbuild/android-arm@0.25.9":
|
||||
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|
||||
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||||
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||||
|
||||
"@esbuild/android-x64@0.25.9":
|
||||
version "0.25.9"
|
||||
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||||
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||||
|
||||
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|
||||
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|
||||
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||||
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||||
|
||||
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|
||||
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|
||||
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||||
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||||
|
||||
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|
||||
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|
||||
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||||
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||||
|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
|
||||
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|
||||
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||||
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||||
|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
|
||||
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|
||||
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|
||||
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||||
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|
||||
|
||||
"@esbuild/netbsd-arm64@0.25.9":
|
||||
version "0.25.9"
|
||||
resolved "https://registry.yarnpkg.com/@esbuild/netbsd-arm64/-/netbsd-arm64-0.25.9.tgz#06f99d7eebe035fbbe43de01c9d7e98d2a0aa548"
|
||||
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|
||||
"@esbuild/netbsd-x64@0.25.9":
|
||||
version "0.25.9"
|
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|
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|
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version "0.25.9"
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resolved "https://registry.yarnpkg.com/@esbuild/win32-x64/-/win32-x64-0.25.9.tgz#585624dc829cfb6e7c0aa6c3ca7d7e6daa87e34f"
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|
||||
"@eslint-community/eslint-utils@^4.2.0", "@eslint-community/eslint-utils@^4.7.0":
|
||||
@@ -368,7 +221,7 @@
|
||||
minimatch "^3.1.2"
|
||||
strip-json-comments "^3.1.1"
|
||||
|
||||
"@eslint/js@9.33.0", "@eslint/js@^9.33.0":
|
||||
"@eslint/js@^9.33.0", "@eslint/js@9.33.0":
|
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|
||||
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|
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@@ -482,15 +335,6 @@
|
||||
"@jridgewell/resolve-uri" "^3.1.0"
|
||||
"@jridgewell/sourcemap-codec" "^1.4.14"
|
||||
|
||||
"@napi-rs/wasm-runtime@^0.2.12":
|
||||
version "0.2.12"
|
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resolved "https://registry.yarnpkg.com/@napi-rs/wasm-runtime/-/wasm-runtime-0.2.12.tgz#3e78a8b96e6c33a6c517e1894efbd5385a7cb6f2"
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dependencies:
|
||||
"@emnapi/core" "^1.4.3"
|
||||
"@emnapi/runtime" "^1.4.3"
|
||||
"@tybys/wasm-util" "^0.10.0"
|
||||
|
||||
"@nodelib/fs.scandir@2.1.5":
|
||||
version "2.1.5"
|
||||
resolved "https://registry.npmjs.org/@nodelib/fs.scandir/-/fs.scandir-2.1.5.tgz"
|
||||
@@ -499,7 +343,7 @@
|
||||
"@nodelib/fs.stat" "2.0.5"
|
||||
run-parallel "^1.1.9"
|
||||
|
||||
"@nodelib/fs.stat@2.0.5", "@nodelib/fs.stat@^2.0.2":
|
||||
"@nodelib/fs.stat@^2.0.2", "@nodelib/fs.stat@2.0.5":
|
||||
version "2.0.5"
|
||||
resolved "https://registry.npmjs.org/@nodelib/fs.stat/-/fs.stat-2.0.5.tgz"
|
||||
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|
||||
@@ -740,7 +584,7 @@
|
||||
aria-hidden "^1.2.4"
|
||||
react-remove-scroll "^2.6.3"
|
||||
|
||||
"@radix-ui/react-slot@1.2.3", "@radix-ui/react-slot@^1.2.3":
|
||||
"@radix-ui/react-slot@^1.2.3", "@radix-ui/react-slot@1.2.3":
|
||||
version "1.2.3"
|
||||
resolved "https://registry.npmjs.org/@radix-ui/react-slot/-/react-slot-1.2.3.tgz"
|
||||
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||||
@@ -829,104 +673,9 @@
|
||||
resolved "https://registry.npmjs.org/@rolldown/pluginutils/-/pluginutils-1.0.0-beta.32.tgz"
|
||||
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||||
|
||||
"@rollup/rollup-android-arm-eabi@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-android-arm-eabi/-/rollup-android-arm-eabi-4.47.1.tgz#6e236cd2fd29bb01a300ad4ff6ed0f1a17550e69"
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||||
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||||
|
||||
"@rollup/rollup-android-arm64@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-android-arm64/-/rollup-android-arm64-4.47.1.tgz#808f2c9c7e68161add613ebcb0eac5a058a0df3c"
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||||
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|
||||
"@rollup/rollup-darwin-arm64@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.npmjs.org/@rollup/rollup-darwin-arm64/-/rollup-darwin-arm64-4.47.1.tgz"
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||||
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"@rollup/rollup-darwin-x64@4.47.1":
|
||||
version "4.47.1"
|
||||
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||||
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|
||||
"@rollup/rollup-freebsd-arm64@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-freebsd-arm64/-/rollup-freebsd-arm64-4.47.1.tgz#9fc804264f7b7a7cdad3747950299f990163be1f"
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||||
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|
||||
"@rollup/rollup-freebsd-x64@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-freebsd-x64/-/rollup-freebsd-x64-4.47.1.tgz#933feaff864feb03bbbcd0c18ea351ade957cf79"
|
||||
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|
||||
"@rollup/rollup-linux-arm-gnueabihf@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-arm-gnueabihf/-/rollup-linux-arm-gnueabihf-4.47.1.tgz#02915e6b2c55fe5961c27404aba2d9c8ef48ac6c"
|
||||
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||||
|
||||
"@rollup/rollup-linux-arm-musleabihf@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-arm-musleabihf/-/rollup-linux-arm-musleabihf-4.47.1.tgz#1afef33191b26e76ae7f0d0dc767efc6be1285ce"
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||||
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|
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"@rollup/rollup-linux-arm64-gnu@4.47.1":
|
||||
version "4.47.1"
|
||||
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|
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"@rollup/rollup-linux-arm64-musl@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-arm64-musl/-/rollup-linux-arm64-musl-4.47.1.tgz#25ab09f14bbcba85a604bcee2962d2486db90794"
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||||
|
||||
"@rollup/rollup-linux-loongarch64-gnu@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-loongarch64-gnu/-/rollup-linux-loongarch64-gnu-4.47.1.tgz#d3e3a3fd61e21b2753094391dee9b515a2bc9ecd"
|
||||
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|
||||
"@rollup/rollup-linux-ppc64-gnu@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-ppc64-gnu/-/rollup-linux-ppc64-gnu-4.47.1.tgz#6b44445e2bd5866692010de241bf18d2ae8b0cb8"
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||||
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|
||||
"@rollup/rollup-linux-riscv64-gnu@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-riscv64-gnu/-/rollup-linux-riscv64-gnu-4.47.1.tgz#3ff412d20d3b157e6aadabf84788e8c5cb221ba7"
|
||||
integrity sha512-daoT0PMENNdjVYYU9xec30Y2prb1AbEIbb64sqkcQcSaR0zYuKkoPuhIztfxuqN82KYCKKrj+tQe4Gi7OSm1ow==
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|
||||
"@rollup/rollup-linux-riscv64-musl@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-riscv64-musl/-/rollup-linux-riscv64-musl-4.47.1.tgz#104f451497d53d82a49c6d08c13c59f5f30eed57"
|
||||
integrity sha512-JNyXaAhWtdzfXu5pUcHAuNwGQKevR+6z/poYQKVW+pLaYOj9G1meYc57/1Xv2u4uTxfu9qEWmNTjv/H/EpAisw==
|
||||
|
||||
"@rollup/rollup-linux-s390x-gnu@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-s390x-gnu/-/rollup-linux-s390x-gnu-4.47.1.tgz#d04de7b21d181f30750760cb3553946306506172"
|
||||
integrity sha512-U/CHbqKSwEQyZXjCpY43/GLYcTVKEXeRHw0rMBJP7fP3x6WpYG4LTJWR3ic6TeYKX6ZK7mrhltP4ppolyVhLVQ==
|
||||
|
||||
"@rollup/rollup-linux-x64-gnu@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-x64-gnu/-/rollup-linux-x64-gnu-4.47.1.tgz#a6ba88ff7480940a435b1e67ddbb3f207a7ae02f"
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||||
integrity sha512-uTLEakjxOTElfeZIGWkC34u2auLHB1AYS6wBjPGI00bWdxdLcCzK5awjs25YXpqB9lS8S0vbO0t9ZcBeNibA7g==
|
||||
|
||||
"@rollup/rollup-linux-x64-musl@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-linux-x64-musl/-/rollup-linux-x64-musl-4.47.1.tgz#c912c8ffa0c242ed3175cd91cdeaef98109afa54"
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||||
integrity sha512-Ft+d/9DXs30BK7CHCTX11FtQGHUdpNDLJW0HHLign4lgMgBcPFN3NkdIXhC5r9iwsMwYreBBc4Rho5ieOmKNVQ==
|
||||
|
||||
"@rollup/rollup-win32-arm64-msvc@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-win32-arm64-msvc/-/rollup-win32-arm64-msvc-4.47.1.tgz#ca5eaae89443554b461bb359112a056528cfdac0"
|
||||
integrity sha512-N9X5WqGYzZnjGAFsKSfYFtAShYjwOmFJoWbLg3dYixZOZqU7hdMq+/xyS14zKLhFhZDhP9VfkzQnsdk0ZDS9IA==
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||||
|
||||
"@rollup/rollup-win32-ia32-msvc@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-win32-ia32-msvc/-/rollup-win32-ia32-msvc-4.47.1.tgz#34e76172515fb4b374eb990d59f54faff938246e"
|
||||
integrity sha512-O+KcfeCORZADEY8oQJk4HK8wtEOCRE4MdOkb8qGZQNun3jzmj2nmhV/B/ZaaZOkPmJyvm/gW9n0gsB4eRa1eiQ==
|
||||
|
||||
"@rollup/rollup-win32-x64-msvc@4.47.1":
|
||||
version "4.47.1"
|
||||
resolved "https://registry.yarnpkg.com/@rollup/rollup-win32-x64-msvc/-/rollup-win32-x64-msvc-4.47.1.tgz#e5e0a0bae2c9d4858cc9b8dc508b2e10d7f0df8b"
|
||||
resolved "https://registry.npmjs.org/@rollup/rollup-win32-x64-msvc/-/rollup-win32-x64-msvc-4.47.1.tgz"
|
||||
integrity sha512-CpKnYa8eHthJa3c+C38v/E+/KZyF1Jdh2Cz3DyKZqEWYgrM1IHFArXNWvBLPQCKUEsAqqKX27tTqVEFbDNUcOA==
|
||||
|
||||
"@tailwindcss/node@4.1.12":
|
||||
@@ -942,71 +691,9 @@
|
||||
source-map-js "^1.2.1"
|
||||
tailwindcss "4.1.12"
|
||||
|
||||
"@tailwindcss/oxide-android-arm64@4.1.12":
|
||||
version "4.1.12"
|
||||
resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-android-arm64/-/oxide-android-arm64-4.1.12.tgz#27920fe61fa2743afe8a8ca296fa640b609d17d5"
|
||||
integrity sha512-oNY5pq+1gc4T6QVTsZKwZaGpBb2N1H1fsc1GD4o7yinFySqIuRZ2E4NvGasWc6PhYJwGK2+5YT1f9Tp80zUQZQ==
|
||||
|
||||
"@tailwindcss/oxide-darwin-arm64@4.1.12":
|
||||
version "4.1.12"
|
||||
resolved "https://registry.npmjs.org/@tailwindcss/oxide-darwin-arm64/-/oxide-darwin-arm64-4.1.12.tgz"
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||||
integrity sha512-cq1qmq2HEtDV9HvZlTtrj671mCdGB93bVY6J29mwCyaMYCP/JaUBXxrQQQm7Qn33AXXASPUb2HFZlWiiHWFytw==
|
||||
|
||||
"@tailwindcss/oxide-darwin-x64@4.1.12":
|
||||
version "4.1.12"
|
||||
resolved "https://registry.yarnpkg.com/@tailwindcss/oxide-darwin-x64/-/oxide-darwin-x64-4.1.12.tgz#8ddb7e5ddfd9b049ec84a2bda99f2b04a86859f5"
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dependencies:
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browserslist@^4.24.0:
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d3-color "1 - 3"
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type-check "~0.4.0"
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lightningcss@1.30.1:
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next-themes@^0.4.6:
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version "0.4.6"
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resolved "https://registry.yarnpkg.com/next-themes/-/next-themes-0.4.6.tgz#8d7e92d03b8fea6582892a50a928c9b23502e8b6"
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node-releases@^2.0.19:
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||||
@@ -2124,7 +1759,7 @@ picomatch@^2.3.1:
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resolved "https://registry.npmjs.org/picomatch/-/picomatch-2.3.1.tgz"
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picomatch@^4.0.3:
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"picomatch@^3 || ^4", picomatch@^4.0.3:
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version "4.0.3"
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resolved "https://registry.npmjs.org/queue-microtask/-/queue-microtask-1.2.3.tgz"
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react-dom@^19.1.1:
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||||
"react-dom@^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc", "react-dom@^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", react-dom@^19.1.1, react-dom@>=16.8.0, react-dom@>=17:
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@@ -2192,7 +1827,7 @@ react-style-singleton@^2.2.2, react-style-singleton@^2.2.3:
|
||||
get-nonce "^1.0.0"
|
||||
tslib "^2.0.0"
|
||||
|
||||
react@^19.1.1:
|
||||
"react@^16.5.1 || ^17.0.0 || ^18.0.0 || ^19.0.0", "react@^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc", "react@^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", "react@^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0", "react@^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc", react@^19.1.1, react@>=16.8, react@>=16.8.0, react@>=17, react@>=18.0.0:
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version "19.1.1"
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resolved "https://registry.npmjs.org/react/-/react-19.1.1.tgz"
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@@ -2292,7 +1927,7 @@ tailwind-merge@^3.3.1:
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resolved "https://registry.npmjs.org/tailwind-merge/-/tailwind-merge-3.3.1.tgz"
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integrity sha512-gBXpgUm/3rp1lMZZrM/w7D8GKqshif0zAymAhbCyIt8KMe+0v9DQ7cdYLR4FHH/cKpdTXb+A/tKKU3eolfsI+g==
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tailwindcss@4.1.12, tailwindcss@^4.1.12:
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tailwindcss@^4.1.12, tailwindcss@4.1.12:
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version "4.1.12"
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resolved "https://registry.npmjs.org/tailwindcss/-/tailwindcss-4.1.12.tgz"
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||||
@@ -2316,7 +1951,7 @@ tar@^7.4.3:
|
||||
|
||||
tinyglobby@^0.2.15:
|
||||
version "0.2.15"
|
||||
resolved "https://registry.yarnpkg.com/tinyglobby/-/tinyglobby-0.2.15.tgz#e228dd1e638cea993d2fdb4fcd2d4602a79951c2"
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resolved "https://registry.npmjs.org/tinyglobby/-/tinyglobby-0.2.15.tgz"
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dependencies:
|
||||
fdir "^6.5.0"
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||||
@@ -2334,7 +1969,7 @@ ts-api-utils@^2.1.0:
|
||||
resolved "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-2.1.0.tgz"
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integrity sha512-CUgTZL1irw8u29bzrOD/nH85jqyc74D6SshFgujOIA7osm2Rz7dYH77agkx7H4FBNxDq7Cjf+IjaX/8zwFW+ZQ==
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tslib@^2.0.0, tslib@^2.1.0, tslib@^2.4.0, tslib@^2.8.0:
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tslib@^2.0.0, tslib@^2.1.0:
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version "2.8.1"
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resolved "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz"
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||||
@@ -2361,7 +1996,7 @@ typescript-eslint@^8.39.1:
|
||||
"@typescript-eslint/typescript-estree" "8.40.0"
|
||||
"@typescript-eslint/utils" "8.40.0"
|
||||
|
||||
typescript@~5.8.3:
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||||
typescript@>=4.8.4, "typescript@>=4.8.4 <6.0.0", typescript@~5.8.3:
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version "5.8.3"
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resolved "https://registry.npmjs.org/typescript/-/typescript-5.8.3.tgz"
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@@ -2401,15 +2036,15 @@ use-sidecar@^1.1.3:
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detect-node-es "^1.1.0"
|
||||
tslib "^2.0.0"
|
||||
|
||||
use-sync-external-store@^1.2.2:
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use-sync-external-store@^1.2.2, use-sync-external-store@>=1.2.0:
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version "1.5.0"
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resolved "https://registry.npmjs.org/use-sync-external-store/-/use-sync-external-store-1.5.0.tgz"
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vite@^7.1.11:
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version "7.1.11"
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resolved "https://registry.yarnpkg.com/vite/-/vite-7.1.11.tgz#4d006746112fee056df64985191e846ebfb6007e"
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"vite@^4.2.0 || ^5.0.0 || ^6.0.0 || ^7.0.0", "vite@^5.2.0 || ^6 || ^7", vite@^7.1.11:
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version "7.1.12"
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resolved "https://registry.npmjs.org/vite/-/vite-7.1.12.tgz"
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|
||||
dependencies:
|
||||
esbuild "^0.25.0"
|
||||
fdir "^6.5.0"
|
||||
@@ -2456,5 +2091,5 @@ zustand@^4.4.0:
|
||||
|
||||
zustand@^5.0.8:
|
||||
version "5.0.8"
|
||||
resolved "https://registry.yarnpkg.com/zustand/-/zustand-5.0.8.tgz#b998a0c088c7027a20f2709141a91cb07ac57f8a"
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resolved "https://registry.npmjs.org/zustand/-/zustand-5.0.8.tgz"
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integrity sha512-gyPKpIaxY9XcO2vSMrLbiER7QMAMGOQZVRdJ6Zi782jkbzZygq5GI9nG8g+sMgitRtndwaBSl7uiqC49o1SSiw==
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Debug UI for Microsoft Agent Framework with OpenAI-compatible API
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://github.com/microsoft/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -10,8 +10,6 @@ Required Environment Variables:
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME: Name of the model deployment to use
|
||||
|
||||
Optional Environment Variables:
|
||||
BING_CONNECTION_NAME: Name of the Bing connection for web search
|
||||
OR
|
||||
BING_CONNECTION_ID: ID of the Bing connection for web search
|
||||
|
||||
Authentication:
|
||||
@@ -21,7 +19,7 @@ Authentication:
|
||||
Example:
|
||||
export AZURE_AI_PROJECT_ENDPOINT="https://your-project.azure.com"
|
||||
export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o"
|
||||
export BING_CONNECTION_NAME="bing-grounding-connection"
|
||||
export BING_CONNECTION_ID="connection-id"
|
||||
az login
|
||||
"""
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Experimental modules for Microsoft Agent Framework"
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Mem0 integration for Microsoft Agent Framework."
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Microsoft Purview (Graph dataSecurityAndGovernance) integration f
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://github.com/microsoft/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Redis integration for Microsoft Agent Framework."
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
|
||||
@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
|
||||
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
license-files = ["LICENSE"]
|
||||
urls.homepage = "https://aka.ms/agent-framework"
|
||||
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
|
||||
@@ -212,7 +212,7 @@ exclude_dirs = ["tests", "./run_tasks_in_packages_if_exists.py", "./check_md_cod
|
||||
executor.type = "uv"
|
||||
|
||||
[tool.poe.tasks]
|
||||
markdown-code-lint = """uv run python check_md_code_blocks.py README.md ./packages/**/README.md ./samples/**/*.md --exclude cookiecutter-agent-framework-lab --exclude tau2 --exclude packages/devui/frontend"""
|
||||
markdown-code-lint = "uv run python check_md_code_blocks.py 'README.md' './packages/**/README.md' './samples/**/*.md' --exclude cookiecutter-agent-framework-lab --exclude tau2 --exclude 'packages/devui/frontend'"
|
||||
docs-install = "uv sync --all-packages --all-extras --dev -U --prerelease=if-necessary-or-explicit --group=docs"
|
||||
docs-clean = "rm -rf docs/build"
|
||||
docs-build = "uv run python ./docs/generate_docs.py"
|
||||
|
||||
@@ -38,10 +38,8 @@ Before running the examples, you need to set up your environment variables. You
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME="your-model-deployment-name"
|
||||
```
|
||||
|
||||
3. For samples using Bing Grounding search (like `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`), you'll also need either:
|
||||
3. For samples using Bing Grounding search (like `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`), you'll also need:
|
||||
```
|
||||
BING_CONNECTION_NAME="bing-grounding-connection"
|
||||
# OR
|
||||
BING_CONNECTION_ID="your-bing-connection-id"
|
||||
```
|
||||
|
||||
@@ -49,7 +47,7 @@ Before running the examples, you need to set up your environment variables. You
|
||||
- Go to [Azure AI Foundry portal](https://ai.azure.com)
|
||||
- Navigate to your project's "Connected resources" section
|
||||
- Add a new connection for "Grounding with Bing Search"
|
||||
- Copy either the connection name or ID
|
||||
- Copy the ID
|
||||
|
||||
### Option 2: Using environment variables directly
|
||||
|
||||
@@ -58,9 +56,7 @@ Set the environment variables in your shell:
|
||||
```bash
|
||||
export AZURE_AI_PROJECT_ENDPOINT="your-project-endpoint"
|
||||
export AZURE_AI_MODEL_DEPLOYMENT_NAME="your-model-deployment-name"
|
||||
export BING_CONNECTION_NAME="your-bing-connection-name" # Optional, only needed for web search samples
|
||||
# OR
|
||||
export BING_CONNECTION_ID="your-bing-connection-id" # Alternative to BING_CONNECTION_NAME
|
||||
export BING_CONNECTION_ID="your-bing-connection-id"
|
||||
```
|
||||
|
||||
### Required Variables
|
||||
@@ -70,4 +66,4 @@ export BING_CONNECTION_ID="your-bing-connection-id" # Alternative to BING_CONNE
|
||||
|
||||
### Optional Variables
|
||||
|
||||
- `BING_CONNECTION_NAME` or `BING_CONNECTION_ID`: Your Bing connection name or ID (required for `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`)
|
||||
- `BING_CONNECTION_ID`: Your Bing connection ID (required for `azure_ai_with_bing_grounding.py` and `azure_ai_with_multiple_tools.py`)
|
||||
|
||||
+7
-5
@@ -5,6 +5,7 @@ import os
|
||||
|
||||
from agent_framework import ChatAgent, CitationAnnotation
|
||||
from agent_framework.azure import AzureAIAgentClient
|
||||
from azure.ai.agents.aio import AgentsClient
|
||||
from azure.ai.projects.aio import AIProjectClient
|
||||
from azure.ai.projects.models import ConnectionType
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
@@ -38,16 +39,17 @@ async def main() -> None:
|
||||
# Create the client and manually create an agent with Azure AI Search tool
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as client,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
|
||||
AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
|
||||
):
|
||||
ai_search_conn_id = ""
|
||||
async for connection in client.connections.list():
|
||||
async for connection in project_client.connections.list():
|
||||
if connection.type == ConnectionType.AZURE_AI_SEARCH:
|
||||
ai_search_conn_id = connection.id
|
||||
break
|
||||
|
||||
# 1. Create Azure AI agent with the search tool
|
||||
azure_ai_agent = await client.agents.create_agent(
|
||||
azure_ai_agent = await project_client.agents.create_agent(
|
||||
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
|
||||
name="HotelSearchAgent",
|
||||
instructions=(
|
||||
@@ -69,7 +71,7 @@ async def main() -> None:
|
||||
)
|
||||
|
||||
# 2. Create chat client with the existing agent
|
||||
chat_client = AzureAIAgentClient(project_client=client, agent_id=azure_ai_agent.id)
|
||||
chat_client = AzureAIAgentClient(agents_client=agents_client, agent_id=azure_ai_agent.id)
|
||||
|
||||
try:
|
||||
async with ChatAgent(
|
||||
@@ -112,7 +114,7 @@ async def main() -> None:
|
||||
|
||||
finally:
|
||||
# Clean up the agent manually
|
||||
await client.agents.delete_agent(azure_ai_agent.id)
|
||||
await project_client.agents.delete_agent(azure_ai_agent.id)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
+2
-3
@@ -12,8 +12,7 @@ uses Bing Grounding search to find real-time information from the web.
|
||||
|
||||
Prerequisites:
|
||||
1. A connected Grounding with Bing Search resource in your Azure AI project
|
||||
2. Set either BING_CONNECTION_NAME or BING_CONNECTION_ID environment variable
|
||||
Example: BING_CONNECTION_NAME="bing-grounding-connection"
|
||||
2. Set BING_CONNECTION_ID environment variable
|
||||
Example: BING_CONNECTION_ID="your-bing-connection-id"
|
||||
|
||||
To set up Bing Grounding:
|
||||
@@ -27,7 +26,7 @@ To set up Bing Grounding:
|
||||
async def main() -> None:
|
||||
"""Main function demonstrating Azure AI agent with Bing Grounding search."""
|
||||
# 1. Create Bing Grounding search tool using HostedWebSearchTool
|
||||
# The connection_name or ID will be automatically picked up from environment variable
|
||||
# The connection ID will be automatically picked up from environment variable
|
||||
bing_search_tool = HostedWebSearchTool(
|
||||
name="Bing Grounding Search",
|
||||
description="Search the web for current information using Bing",
|
||||
|
||||
+6
-4
@@ -5,6 +5,7 @@ import os
|
||||
|
||||
from agent_framework import ChatAgent
|
||||
from agent_framework.azure import AzureAIAgentClient
|
||||
from azure.ai.agents.aio import AgentsClient
|
||||
from azure.ai.projects.aio import AIProjectClient
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
|
||||
@@ -22,16 +23,17 @@ async def main() -> None:
|
||||
# Create the client
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as client,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
|
||||
AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
|
||||
):
|
||||
azure_ai_agent = await client.agents.create_agent(
|
||||
azure_ai_agent = await project_client.agents.create_agent(
|
||||
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
|
||||
# Create remote agent with default instructions
|
||||
# These instructions will persist on created agent for every run.
|
||||
instructions="End each response with [END].",
|
||||
)
|
||||
|
||||
chat_client = AzureAIAgentClient(project_client=client, agent_id=azure_ai_agent.id)
|
||||
chat_client = AzureAIAgentClient(agents_client=agents_client, agent_id=azure_ai_agent.id)
|
||||
|
||||
try:
|
||||
async with ChatAgent(
|
||||
@@ -50,7 +52,7 @@ async def main() -> None:
|
||||
print(f"Agent: {result}\n")
|
||||
finally:
|
||||
# Clean up the agent manually
|
||||
await client.agents.delete_agent(azure_ai_agent.id)
|
||||
await project_client.agents.delete_agent(azure_ai_agent.id)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
+5
-5
@@ -7,7 +7,7 @@ from typing import Annotated
|
||||
|
||||
from agent_framework import ChatAgent
|
||||
from agent_framework.azure import AzureAIAgentClient
|
||||
from azure.ai.projects.aio import AIProjectClient
|
||||
from azure.ai.agents.aio import AgentsClient
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
from pydantic import Field
|
||||
|
||||
@@ -33,16 +33,16 @@ async def main() -> None:
|
||||
# Create the client
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as client,
|
||||
AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
|
||||
):
|
||||
# Create an thread that will persist
|
||||
created_thread = await client.agents.threads.create()
|
||||
created_thread = await agents_client.threads.create()
|
||||
|
||||
try:
|
||||
async with ChatAgent(
|
||||
# passing in the client is optional here, so if you take the agent_id from the portal
|
||||
# you can use it directly without the two lines above.
|
||||
chat_client=AzureAIAgentClient(project_client=client),
|
||||
chat_client=AzureAIAgentClient(agents_client=agents_client),
|
||||
instructions="You are a helpful weather agent.",
|
||||
tools=get_weather,
|
||||
) as agent:
|
||||
@@ -52,7 +52,7 @@ async def main() -> None:
|
||||
print(f"Result: {result}\n")
|
||||
finally:
|
||||
# Clean up the thread manually
|
||||
await client.agents.threads.delete(created_thread.id)
|
||||
await agents_client.threads.delete(created_thread.id)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@@ -44,8 +44,6 @@ async def main() -> None:
|
||||
AzureCliCredential() as credential,
|
||||
AzureAIAgentClient(async_credential=credential) as chat_client,
|
||||
):
|
||||
# enable azure-ai observability
|
||||
await chat_client.setup_azure_ai_observability()
|
||||
agent = chat_client.create_agent(
|
||||
name="DocsAgent",
|
||||
instructions="You are a helpful assistant that can help with microsoft documentation questions.",
|
||||
|
||||
@@ -69,8 +69,6 @@ async def main() -> None:
|
||||
AzureCliCredential() as credential,
|
||||
AzureAIAgentClient(async_credential=credential) as chat_client,
|
||||
):
|
||||
# enable azure-ai observability
|
||||
await chat_client.setup_azure_ai_observability()
|
||||
agent = chat_client.create_agent(
|
||||
name="DocsAgent",
|
||||
instructions="You are a helpful assistant that can help with microsoft documentation questions.",
|
||||
|
||||
@@ -9,7 +9,9 @@ import dotenv
|
||||
from agent_framework import ChatAgent
|
||||
from agent_framework.azure import AzureAIAgentClient
|
||||
from agent_framework.observability import get_tracer
|
||||
from azure.ai.agents.aio import AgentsClient
|
||||
from azure.ai.projects.aio import AIProjectClient
|
||||
from azure.core.exceptions import ResourceNotFoundError
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
from opentelemetry.trace import SpanKind
|
||||
from opentelemetry.trace.span import format_trace_id
|
||||
@@ -38,16 +40,36 @@ async def get_weather(
|
||||
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
|
||||
|
||||
|
||||
async def setup_azure_ai_observability(
|
||||
project_client: AIProjectClient, enable_sensitive_data: bool | None = None
|
||||
) -> None:
|
||||
"""Use this method to setup tracing in your Azure AI Project.
|
||||
|
||||
This will take the connection string from the AIProjectClient.
|
||||
It will override any connection string that is set in the environment variables.
|
||||
It will disable any OTLP endpoint that might have been set.
|
||||
"""
|
||||
try:
|
||||
conn_string = await project_client.telemetry.get_application_insights_connection_string()
|
||||
except ResourceNotFoundError:
|
||||
print("No Application Insights connection string found for the Azure AI Project.")
|
||||
return
|
||||
from agent_framework.observability import setup_observability
|
||||
|
||||
setup_observability(applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data)
|
||||
|
||||
|
||||
async def main():
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project,
|
||||
AzureAIAgentClient(project_client=project) as client,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
|
||||
AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
|
||||
AzureAIAgentClient(agents_client=agents_client) as client,
|
||||
):
|
||||
# This will enable tracing and configure the application to send telemetry data to the
|
||||
# Application Insights instance attached to the Azure AI project.
|
||||
# This will override any existing configuration.
|
||||
await client.setup_azure_ai_observability()
|
||||
await setup_azure_ai_observability(project_client)
|
||||
|
||||
questions = ["What's the weather in Amsterdam?", "and in Paris, and which is better?", "Why is the sky blue?"]
|
||||
|
||||
|
||||
+25
-3
@@ -9,7 +9,9 @@ import dotenv
|
||||
from agent_framework import HostedCodeInterpreterTool
|
||||
from agent_framework.azure import AzureAIAgentClient
|
||||
from agent_framework.observability import get_tracer
|
||||
from azure.ai.agents.aio import AgentsClient
|
||||
from azure.ai.projects.aio import AIProjectClient
|
||||
from azure.core.exceptions import ResourceNotFoundError
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
from opentelemetry.trace import SpanKind
|
||||
from opentelemetry.trace.span import format_trace_id
|
||||
@@ -42,6 +44,25 @@ async def get_weather(
|
||||
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
|
||||
|
||||
|
||||
async def setup_azure_ai_observability(
|
||||
project_client: AIProjectClient, enable_sensitive_data: bool | None = None
|
||||
) -> None:
|
||||
"""Use this method to setup tracing in your Azure AI Project.
|
||||
|
||||
This will take the connection string from the AIProjectClient instance.
|
||||
It will override any connection string that is set in the environment variables.
|
||||
It will disable any OTLP endpoint that might have been set.
|
||||
"""
|
||||
try:
|
||||
conn_string = await project_client.telemetry.get_application_insights_connection_string()
|
||||
except ResourceNotFoundError:
|
||||
print("No Application Insights connection string found for the Azure AI Project.")
|
||||
return
|
||||
from agent_framework.observability import setup_observability
|
||||
|
||||
setup_observability(applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data)
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
"""Run an AI service.
|
||||
|
||||
@@ -62,13 +83,14 @@ async def main() -> None:
|
||||
]
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project,
|
||||
AzureAIAgentClient(project_client=project) as client,
|
||||
AIProjectClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as project_client,
|
||||
AgentsClient(endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=credential) as agents_client,
|
||||
AzureAIAgentClient(agents_client=agents_client) as client,
|
||||
):
|
||||
# This will enable tracing and configure the application to send telemetry data to the
|
||||
# Application Insights instance attached to the Azure AI project.
|
||||
# This will override any existing configuration.
|
||||
await client.setup_azure_ai_observability()
|
||||
await setup_azure_ai_observability(project_client)
|
||||
|
||||
with get_tracer().start_as_current_span(
|
||||
name="Foundry Telemetry from Agent Framework", kind=SpanKind.CLIENT
|
||||
|
||||
@@ -0,0 +1,103 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import asyncio
|
||||
from typing import Never
|
||||
|
||||
from agent_framework import (
|
||||
AgentExecutorResponse,
|
||||
Executor,
|
||||
HostedCodeInterpreterTool,
|
||||
WorkflowBuilder,
|
||||
WorkflowContext,
|
||||
handler,
|
||||
)
|
||||
from agent_framework.azure import AzureAIAgentClient
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
|
||||
"""
|
||||
This sample demonstrates how to create a workflow that combines an AI agent executor
|
||||
with a custom executor.
|
||||
|
||||
The workflow consists of two stages:
|
||||
1. An AI agent with code interpreter capabilities that generates and executes Python code
|
||||
2. An evaluator executor that reviews the agent's output and provides a final assessment
|
||||
|
||||
Key concepts demonstrated:
|
||||
- Creating an AI agent with tool capabilities (HostedCodeInterpreterTool)
|
||||
- Building workflows using WorkflowBuilder with an agent and a custom executor
|
||||
- Using the @handler decorator in the executor to process AgentExecutorResponse from the agent
|
||||
- Connecting workflow executors with edges to create a processing pipeline
|
||||
- Yielding final outputs from terminal executors
|
||||
- Non-streaming workflow execution and result collection
|
||||
|
||||
Prerequisites:
|
||||
- Azure AI services configured with required environment variables
|
||||
- Azure CLI authentication (run 'az login' before executing)
|
||||
- Basic understanding of async Python and workflow concepts
|
||||
"""
|
||||
|
||||
|
||||
class Evaluator(Executor):
|
||||
"""Custom executor that evaluates the output from an AI agent.
|
||||
|
||||
This executor demonstrates how to:
|
||||
- Create a custom workflow executor that processes agent responses
|
||||
- Use the @handler decorator to define the processing logic
|
||||
- Access agent execution details including response text and usage metrics
|
||||
- Yield final results to complete the workflow execution
|
||||
|
||||
The evaluator checks if the agent successfully generated the Fibonacci sequence
|
||||
and provides feedback on correctness along with resource consumption details.
|
||||
"""
|
||||
|
||||
@handler
|
||||
async def handle(self, message: AgentExecutorResponse, ctx: WorkflowContext[Never, str]) -> None:
|
||||
"""Evaluate the agent's response and complete the workflow with a final assessment.
|
||||
|
||||
This handler:
|
||||
1. Receives the AgentExecutorResponse containing the agent's complete interaction
|
||||
2. Checks if the expected Fibonacci sequence appears in the response text
|
||||
3. Extracts usage details (token consumption, execution time, etc.)
|
||||
4. Yields a final evaluation string to complete the workflow
|
||||
|
||||
Args:
|
||||
message: The response from the Azure AI agent containing text and metadata
|
||||
ctx: Workflow context for yielding the final output string
|
||||
"""
|
||||
target_text = "1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89"
|
||||
correctness = target_text in message.agent_run_response.text
|
||||
consumption = message.agent_run_response.usage_details
|
||||
await ctx.yield_output(f"Correctness: {correctness}, Consumption: {consumption}")
|
||||
|
||||
|
||||
async def main():
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AzureAIAgentClient(async_credential=credential) as chat_client,
|
||||
):
|
||||
# Create an agent with code interpretation capabilities
|
||||
agent = chat_client.create_agent(
|
||||
name="CodingAgent",
|
||||
instructions=("You are a helpful assistant that can write and execute Python code to solve problems."),
|
||||
tools=HostedCodeInterpreterTool(),
|
||||
)
|
||||
|
||||
# Build a workflow: Agent generates code -> Evaluator assesses results
|
||||
# The agent will be wrapped in a special agent executor which produces AgentExecutorResponse
|
||||
workflow = WorkflowBuilder().set_start_executor(agent).add_edge(agent, Evaluator(id="evaluator")).build()
|
||||
|
||||
# Execute the workflow with a specific coding task
|
||||
results = await workflow.run(
|
||||
"Generate the fibonacci numbers to 100 using python code, show the code and execute it."
|
||||
)
|
||||
|
||||
# Extract and display the final evaluation
|
||||
outputs = results.get_outputs()
|
||||
if isinstance(outputs, list) and len(outputs) == 1:
|
||||
print("Workflow results:", outputs[0])
|
||||
else:
|
||||
raise ValueError("Unexpected workflow outputs:", outputs)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
+4
-5
@@ -4,7 +4,6 @@ import asyncio
|
||||
from dataclasses import dataclass
|
||||
|
||||
from agent_framework import (
|
||||
AgentExecutor, # Executor that runs the agent
|
||||
AgentExecutorRequest, # Message bundle sent to an AgentExecutor
|
||||
AgentExecutorResponse, # Result returned by an AgentExecutor
|
||||
ChatMessage, # Chat message structure
|
||||
@@ -148,6 +147,7 @@ async def main() -> None:
|
||||
# response_format enforces that the model produces JSON compatible with GuessOutput.
|
||||
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
|
||||
agent = chat_client.create_agent(
|
||||
name="GuessingAgent",
|
||||
instructions=(
|
||||
"You guess a number between 1 and 10. "
|
||||
"If the user says 'higher' or 'lower', adjust your next guess. "
|
||||
@@ -158,16 +158,15 @@ async def main() -> None:
|
||||
response_format=GuessOutput,
|
||||
)
|
||||
|
||||
# Build a simple loop: TurnManager <-> AgentExecutor.
|
||||
# TurnManager coordinates and gathers human replies while AgentExecutor runs the model.
|
||||
turn_manager = TurnManager(id="turn_manager")
|
||||
agent_exec = AgentExecutor(agent=agent, id="agent")
|
||||
|
||||
# Build a simple loop: TurnManager <-> AgentExecutor.
|
||||
workflow = (
|
||||
WorkflowBuilder()
|
||||
.set_start_executor(turn_manager)
|
||||
.add_edge(turn_manager, agent_exec) # Ask agent to make/adjust a guess
|
||||
.add_edge(agent_exec, turn_manager) # Agent's response comes back to coordinator
|
||||
.add_edge(turn_manager, agent) # Ask agent to make/adjust a guess
|
||||
.add_edge(agent, turn_manager) # Agent's response comes back to coordinator
|
||||
).build()
|
||||
|
||||
# Human in the loop run: alternate between invoking the workflow and supplying collected responses.
|
||||
|
||||
Generated
+17
-13
@@ -87,7 +87,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { virtual = "." }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-a2a", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -178,7 +178,7 @@ docs = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-a2a"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/a2a" }
|
||||
dependencies = [
|
||||
{ name = "a2a-sdk", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -193,7 +193,7 @@ requires-dist = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-ag-ui"
|
||||
version = "1.0.0b251105"
|
||||
version = "1.0.0b251106"
|
||||
source = { editable = "packages/ag-ui" }
|
||||
dependencies = [
|
||||
{ name = "ag-ui-protocol", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -223,7 +223,7 @@ provides-extras = ["dev"]
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-anthropic"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/anthropic" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -238,10 +238,11 @@ requires-dist = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-azure-ai"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/azure-ai" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "aiohttp", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "azure-ai-agents", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "azure-ai-projects", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
]
|
||||
@@ -249,13 +250,14 @@ dependencies = [
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "agent-framework-core", editable = "packages/core" },
|
||||
{ name = "aiohttp" },
|
||||
{ name = "azure-ai-agents", specifier = "==1.2.0b5" },
|
||||
{ name = "azure-ai-projects", specifier = ">=2.0.0a20251103001", index = "https://pkgs.dev.azure.com/azure-sdk/public/_packaging/azure-sdk-for-python/pypi/simple" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-chatkit"
|
||||
version = "1.0.0b251001"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/chatkit" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -270,7 +272,7 @@ requires-dist = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-copilotstudio"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/copilotstudio" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -285,7 +287,7 @@ requires-dist = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-core"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/core" }
|
||||
dependencies = [
|
||||
{ name = "azure-identity", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -295,6 +297,7 @@ dependencies = [
|
||||
{ name = "opentelemetry-exporter-otlp-proto-grpc", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "opentelemetry-sdk", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "opentelemetry-semantic-conventions-ai", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "packaging", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "pydantic", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "pydantic-settings", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
{ name = "typing-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -329,6 +332,7 @@ requires-dist = [
|
||||
{ name = "opentelemetry-exporter-otlp-proto-grpc", specifier = ">=1.36.0" },
|
||||
{ name = "opentelemetry-sdk", specifier = ">=1.24" },
|
||||
{ name = "opentelemetry-semantic-conventions-ai", specifier = ">=0.4.13" },
|
||||
{ name = "packaging", specifier = ">=24.1" },
|
||||
{ name = "pydantic", specifier = ">=2,<3" },
|
||||
{ name = "pydantic-settings", specifier = ">=2,<3" },
|
||||
{ name = "typing-extensions" },
|
||||
@@ -337,7 +341,7 @@ provides-extras = ["all"]
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-devui"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/devui" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -371,7 +375,7 @@ provides-extras = ["dev", "all"]
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-lab"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/lab" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -462,7 +466,7 @@ dev = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-mem0"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/mem0" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -477,7 +481,7 @@ requires-dist = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-purview"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/purview" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
@@ -494,7 +498,7 @@ requires-dist = [
|
||||
|
||||
[[package]]
|
||||
name = "agent-framework-redis"
|
||||
version = "1.0.0b251104"
|
||||
version = "1.0.0b251105"
|
||||
source = { editable = "packages/redis" }
|
||||
dependencies = [
|
||||
{ name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
|
||||
Reference in New Issue
Block a user