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‎tests/cli_run/samples/1-simple-graph/langgraph.json

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{
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"dependencies": [
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"."
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],
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"graphs": {
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"agent": "./main.py:graph"
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},
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"env": ".env"
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}

‎tests/cli_run/samples/1-simple-graph/main.py

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import random
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from typing import Literal
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from langgraph.checkpoint.memory import MemorySaver
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from langgraph.graph import END, START, StateGraph
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from langgraph.types import interrupt
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from typing_extensions import TypedDict
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# State
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class State(TypedDict):
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graph_state: str
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# Conditional edge
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def decide_mood(state) -> Literal["node_2", "node_3"]:
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# Often, we will use state to decide on the next node to visit
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user_input = state["graph_state"]
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# Here, let's just do a 50 / 50 split between nodes 2, 3
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if random.random() < 0.5:
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# 50% of the time, we return Node 2
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return "node_2"
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# 50% of the time, we return Node 3
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return "node_3"
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# Nodes
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def node_1(state):
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print("---Node 1---")
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return {"graph_state": state["graph_state"] + " I am"}
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def node_2(state):
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print("---Node 2---")
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return {"graph_state": state["graph_state"] + " happy!"}
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def node_3(state):
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print("---Node 3---")
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return {"graph_state": state["graph_state"] + " sad!"}
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builder = StateGraph(State)
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builder.add_node("node_1", node_1)
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builder.add_node("node_2", node_2)
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builder.add_node("node_3", node_3)
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builder.add_edge(START, "node_1")
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builder.add_edge("node_1", "node_2")
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builder.add_edge("node_2", END)
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builder.add_edge("node_3", END)
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memory = MemorySaver()
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graph = builder.compile(checkpointer=memory)

‎tests/cli_run/samples/1-simple-graph/pyproject.toml

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[project]
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name = "c-host-in-uipath"
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version = "0.1.0"
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description = "Add your description here"
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readme = "README.md"
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authors = [{ name = "Eduard Stanculet", email = "[email protected]" }]
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requires-python = ">=3.13"
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dependencies = [
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"langchain-anthropic>=0.3.10",
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"langchain-community>=0.3.21",
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"langgraph>=0.3.29",
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"tavily-python>=0.5.4",
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"uipath>=2.0.8",
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"uipath-langchain>=0.0.88",
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]

‎tests/cli_run/samples/1-simple-graph/uipath.json

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{
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"entryPoints": [
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{
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"filePath": "agent",
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"uniqueId": "dcc7a309-fbcc-4999-af4f-2a75a844b49a",
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"type": "agent",
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"input": {
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"type": "string",
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"title": "graph_state"
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},
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"output": {}
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}
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],
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"bindings": {
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"version": "2.0",
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"resources": []
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}
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}

‎tests/cli_run/test_run_sample.py

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import os
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import sys
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from dotenv import load_dotenv
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from uipath_langchain._cli.cli_run import langgraph_run_middleware
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load_dotenv()
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def test_dummy():
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test_folder_path = os.path.dirname(os.path.abspath(__file__))
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sample_path = os.path.join(test_folder_path, "samples", "1-simple-graph")
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sys.path.append(sample_path)
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os.chdir(sample_path)
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result = langgraph_run_middleware(
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entrypoint=None,
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input='{ "graph_state": "GET Assets API does not enforce proper permissions Assets.View" }',
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resume=False,
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)
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assert result.error_message is None

‎tests/conftest.py

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import logging
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import os
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from os import environ as env
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from typing import Generator, Optional
5-
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import httpx
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import pytest
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from langchain.embeddings import CacheBackedEmbeddings
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from langchain.globals import set_llm_cache
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from langchain.storage import LocalFileStore
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from langchain_community.cache import SQLiteCache
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from uipath_langchain.embeddings import UiPathOpenAIEmbeddings
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from uipath_langchain.utils._settings import UiPathCachedPathsSettings
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test_cache_settings = UiPathCachedPathsSettings(
17-
CACHED_COMPLETION_DB="tests/llm_cache/tests_uipath_cache.sqlite",
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CACHED_EMBEDDINGS_DIR="tests/llm_cache/cached_embeddings",
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)
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21-
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def get_from_uipath_url():
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try:
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url = os.getenv("UIPATH_URL")
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if url:
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return "/".join(url.split("/", 3)[:3])
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except Exception:
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return None
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return None
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31-
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def get_token():
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url_get_token = f"{get_from_uipath_url().rstrip('/')}/identity_/connect/token"
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os.environ["UIPATH_REQUESTING_PRODUCT"] = "uipath-python-sdk"
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os.environ["UIPATH_REQUESTING_FEATURE"] = "langgraph-agent"
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os.environ["UIPATH_TESTS_CACHE_LLMGW"] = "true"
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token_credentials = {
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"client_id": env.get("UIPATH_CLIENT_ID"),
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"client_secret": env.get("UIPATH_CLIENT_SECRET"),
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"grant_type": "client_credentials",
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}
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try:
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with httpx.Client() as client:
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response = client.post(url_get_token, data=token_credentials)
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response.raise_for_status()
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res_json = response.json()
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token = res_json.get("access_token")
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if not token:
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pytest.skip("Authentication token is empty or missing")
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except (httpx.HTTPError, ValueError, KeyError) as e:
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pytest.skip(f"Failed to obtain authentication token: {str(e)}")
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return token
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@pytest.fixture(autouse=True)
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def setup_test_env():
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env["UIPATH_ACCESS_TOKEN"] = get_token()
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@pytest.fixture(scope="session")
66-
def cached_llmgw_calls() -> Generator[Optional[SQLiteCache], None, None]:
67-
if not os.environ.get("UIPATH_TESTS_CACHE_LLMGW"):
68-
yield None
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else:
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logging.info("Setting up LLMGW cache")
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db_path = test_cache_settings.cached_completion_db
72-
os.makedirs(os.path.dirname(db_path), exist_ok=True)
73-
cache = SQLiteCache(database_path=db_path)
74-
set_llm_cache(cache)
75-
yield cache
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set_llm_cache(None)
77-
return
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80-
@pytest.fixture(scope="session")
81-
def cached_embedder() -> Generator[Optional[CacheBackedEmbeddings], None, None]:
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if not os.environ.get("UIPATH_TESTS_CACHE_LLMGW"):
83-
yield None
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else:
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logging.info("Setting up embeddings cache")
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model = "text-embedding-3-large"
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embedder = CacheBackedEmbeddings.from_bytes_store(
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underlying_embeddings=UiPathOpenAIEmbeddings(model=model),
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document_embedding_cache=LocalFileStore(
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test_cache_settings.cached_embeddings_dir
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),
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namespace=model,
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)
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yield embedder
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return
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# import logging
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# import os
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# from os import environ as env
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# from typing import Generator, Optional
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# import httpx
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# import pytest
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# from langchain.embeddings import CacheBackedEmbeddings
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# from langchain.globals import set_llm_cache
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# from langchain.storage import LocalFileStore
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# from langchain_community.cache import SQLiteCache
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# from uipath_langchain.embeddings import UiPathOpenAIEmbeddings
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# from uipath_langchain.utils._settings import UiPathCachedPathsSettings
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# test_cache_settings = UiPathCachedPathsSettings(
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# CACHED_COMPLETION_DB="tests/llm_cache/tests_uipath_cache.sqlite",
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# CACHED_EMBEDDINGS_DIR="tests/llm_cache/cached_embeddings",
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# )
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# def get_from_uipath_url():
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# try:
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# url = os.getenv("UIPATH_URL", "https://cloud.uipath.com/dummyOrg/dummyTennant/")
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# if url:
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# return "/".join(url.split("/", 3)[:3])
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# except Exception:
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# return "https://cloud.uipath.com/dummyOrg/dummyTennant/"
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# return None
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# def get_token():
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# url_get_token = f"{get_from_uipath_url().rstrip('/')}/identity_/connect/token"
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# os.environ["UIPATH_REQUESTING_PRODUCT"] = "uipath-python-sdk"
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# os.environ["UIPATH_REQUESTING_FEATURE"] = "langgraph-agent"
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# os.environ["UIPATH_TESTS_CACHE_LLMGW"] = "true"
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# token_credentials = {
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# "client_id": env.get("UIPATH_CLIENT_ID"),
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# "client_secret": env.get("UIPATH_CLIENT_SECRET"),
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# "grant_type": "client_credentials",
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# }
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# try:
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# with httpx.Client() as client:
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# response = client.post(url_get_token, data=token_credentials)
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# response.raise_for_status()
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# res_json = response.json()
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# token = res_json.get("access_token")
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# if not token:
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# pytest.skip("Authentication token is empty or missing")
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# except (httpx.HTTPError, ValueError, KeyError) as e:
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# pytest.skip(f"Failed to obtain authentication token: {str(e)}")
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# return token
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# @pytest.fixture(autouse=True)
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# def setup_test_env():
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# env["UIPATH_ACCESS_TOKEN"] = get_token()
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64+
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# @pytest.fixture(scope="session")
66+
# def cached_llmgw_calls() -> Generator[Optional[SQLiteCache], None, None]:
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# if not os.environ.get("UIPATH_TESTS_CACHE_LLMGW"):
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# yield None
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# else:
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# logging.info("Setting up LLMGW cache")
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# db_path = test_cache_settings.cached_completion_db
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# os.makedirs(os.path.dirname(db_path), exist_ok=True)
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# cache = SQLiteCache(database_path=db_path)
74+
# set_llm_cache(cache)
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# yield cache
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# set_llm_cache(None)
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# return
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79+
80+
# @pytest.fixture(scope="session")
81+
# def cached_embedder() -> Generator[Optional[CacheBackedEmbeddings], None, None]:
82+
# if not os.environ.get("UIPATH_TESTS_CACHE_LLMGW"):
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# yield None
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# else:
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# logging.info("Setting up embeddings cache")
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# model = "text-embedding-3-large"
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# embedder = CacheBackedEmbeddings.from_bytes_store(
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# underlying_embeddings=UiPathOpenAIEmbeddings(model=model),
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# document_embedding_cache=LocalFileStore(
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# test_cache_settings.cached_embeddings_dir
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# ),
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# namespace=model,
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# )
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# yield embedder
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# return

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