collect all agents for cleanup

llama_cloud_services/extract/extract.py

@@ -137,15 +137,9 @@ def run_in_thread(
 
 
 def _extraction_config_warning(config: ExtractConfig) -> None:
-    if config.use_reasoning:
+    if config.cite_sources or config.confidence_scores:
         warnings.warn(
-            "`use_reasoning` is an experimental feature. Results will be available in "
-            "the `extraction_metadata` field for the extraction run.",
-            ExperimentalWarning,
-        )
-    if config.cite_sources:
-        warnings.warn(
-            "`cite_sources` is an experimental feature. This may greatly increase the "
+            "`cite_sources`/`confidence_scores` could greatly increase the "
             "size of the response, and slow down the extraction. Results will be "
             "available in the `extraction_metadata` field for the extraction run.",
             ExperimentalWarning,

llama_parse/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "llama-parse"
-version = "0.6.47"
+version = "0.6.48"
 description = "Parse files into RAG-Optimized formats."
 authors = ["Logan Markewich <logan@llamaindex.ai>"]
 license = "MIT"
@@ -13,7 +13,7 @@ packages = [{include = "llama_parse"}]
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-llama-cloud-services = ">=0.6.47"
+llama-cloud-services = ">=0.6.48"
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^8.0.0"

poetry.lock

@@ -1925,14 +1925,14 @@ rapidfuzz = ">=3.9.0,<4.0.0"
 
 [[package]]
 name = "llama-cloud"
-version = "0.1.33"
+version = "0.1.34"
 description = ""
 optional = false
 python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
-    {file = "llama_cloud-0.1.33-py3-none-any.whl", hash = "sha256:35b7d4a30b013f0a343f7e09126b531c697d65bffd4eb4d2d79bf7d65f256178"},
-    {file = "llama_cloud-0.1.33.tar.gz", hash = "sha256:a0bb900d5a6e86f8c767b48686c5253679ad7ca1b57612dc39b0767e57ad3d78"},
+    {file = "llama_cloud-0.1.34-py3-none-any.whl", hash = "sha256:9b06fb109b1d9f652095a11732ae3dbe84e48cc00c580b2eeb19e71e901267be"},
+    {file = "llama_cloud-0.1.34.tar.gz", hash = "sha256:6866e4bab47d2c1840bdf169c13c06176931c1d30697ac1fa71bab7942a041e9"},
 ]
 
 [package.dependencies]
@@ -4623,4 +4623,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.9,<4.0"
-content-hash = "487717a0bbe7ff67360e3e9f187e15a33c77e4942a7c909cb37b95425a81544c"
+content-hash = "62bbed6ef774d11a0e775524ea3fc86e840fc35823c199dbbe1980ce9c81d2a1"

pyproject.toml

@@ -8,7 +8,7 @@ python_version = "3.10"
 
 [tool.poetry]
 name = "llama-cloud-services"
-version = "0.6.47"
+version = "0.6.48"
 description = "Tailored SDK clients for LlamaCloud services."
 authors = ["Logan Markewich <logan@runllama.ai>"]
 license = "MIT"
@@ -18,7 +18,7 @@ packages = [{include = "llama_cloud_services"}]
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
 llama-index-core = ">=0.12.0"
-llama-cloud = "==0.1.33"
+llama-cloud = "==0.1.34"
 pydantic = ">=2.8,!=2.10"
 click = "^8.1.7"
 python-dotenv = "^1.0.1"

tests/extract/test_extract_e2e.py

@@ -8,6 +8,7 @@ import uuid
 from llama_cloud.types import ExtractConfig, ExtractMode
 from deepdiff import DeepDiff
 from tests.extract.util import json_subset_match_score, load_test_dotenv
+from .conftest import register_agent_for_cleanup
 
 load_test_dotenv()
 
@@ -115,13 +116,11 @@ def extraction_agent(test_case: TestCase, extractor: LlamaExtract):
 
     # Create new agent
     agent = extractor.create_agent(agent_name, schema, config=test_case.config)
-    yield agent
 
-    # Cleanup after test
-    try:
-        extractor.delete_agent(agent.id)
-    except Exception as e:
-        print(f"Warning: Failed to delete agent {agent.id}: {str(e)}")
+    # Register agent for cleanup at the end of the test session
+    register_agent_for_cleanup(agent.id)
+
+    yield agent
 
 
 @pytest.mark.skipif(
@@ -130,7 +129,7 @@ def extraction_agent(test_case: TestCase, extractor: LlamaExtract):
 )
 @pytest.mark.parametrize("test_case", get_test_cases(), ids=lambda x: x.name)
 def test_extraction(test_case: TestCase, extraction_agent: ExtractionAgent) -> None:
-    result = extraction_agent.extract(test_case.input_file).data
+    result = extraction_agent.extract(test_case.input_file).data  # type: ignore
     with open(test_case.expected_output, "r") as f:
         expected = json.load(f)
     # TODO: fix the saas_slide test