text stringlengths 14 100k | source stringclasses 1
value | repo stringclasses 810
values | language stringclasses 13
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<|fim_prefix|>#!/usr/bin/env python3
"""Generate a static PEP 503-style package index from built distributions."""
from __future__ import annotations
import argparse
import hashlib
import html
import re
import tarfile
import zipfile
from collections import defaultdict
from dataclasses import dataclass
from email.pars... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import argparse
import json
import sys
import yaml
from uvicorn.importer import import_from_string
parser = argparse.ArgumentParser(prog="extract_openapi.py")
parser.add_argument("app", help='App import string. Eg. "main:app"', default="main:app")
parser.add_argument("--app-dir", help="Directory<|fim_su... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>#!/usr/bin/env python3
"""Generate the Homebrew formula for private-gpt."""
from __future__ import annotations
import argparse
from pathlib import Path
def render_formula(
*,
version: str,
source_url: str,
sha256: str,
homepage: str,
package_files_url: str,
extra: str,
) ->... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> raise ValueError(f"Folder {folder_path} is not allowed for ingestion")
def _find_all_files_in_folder(self, root_path: Path, ignored: list[str]) -> None:
"""Search all files under the root folder recursively.
Count them at the same time
"""
for file_path... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>#!/usr/bin/env python3
from __future__ import annotations
import argparse
import re
import subprocess
import sys
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parent.parent
VERSION_TXT = REPO_ROOT / "version.txt"
PYPROJECT = REPO_ROOT / "pyproject.toml"
def parse_args() -> argparse.Na... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>#!/usr/bin/env python3
"""Keep Claude-related specs in sync: OpenAPI spec URL and anthropic SDK version."""
import j<|fim_suffix|>tch.group(1) if match else "<not found>"
return spec_url
def current_anthropic_version() -> str:
source = PYPROJECT_FILE.read_text(encoding="utf-8")
match = re.s... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>"""Test<|fim_suffix|>""
<|fim_middle|>s."<|endoftext|> | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>is(app: Celery) -> None:
task = app.tasks["test_task"]
# Mock the celery settings to disable Redis
with patch("private_gpt.celery.base.celery_settings") as mock_settings:
mock_settings.backend_mode = "memory"
mock_settings.acks_late = True
result = task.apply_async().... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> ), # 0% into STEP_ONE should give 0% total progress
(
MockProgressStep.STEP_THREE,
50,
50,
), # 50% into STEP_ONE should give 50% total progress
(
MockProgressStep.STEP_THREE,
100,
100,
), # 10... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import Any
from unittest.mock import Mock
from pydantic import BaseModel
from private_gpt.celery.callback import task_after_return
from private_gpt.celery.celery import celery_app
from private_gpt.celery.error import CeleryError
from private_gpt.components.broker.broker_component import Brok... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import asyncio
import pytest
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from private_gpt.components.chat.processors.chat_history.memory.tldr_processor import (
CondenseResponse,
)
from private_gpt.components.chat.processors.chat_history.memory.tldr_utils import (
trim_... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from unittest.mock import patch
import pytest
from private_gpt.components.database.inspected_schema import (
InspectedColumn,
InspectedSchema,
InspectedTable,
TableType,
)
from private_gpt.components.tabular.database_query_generator import (
DatabaseQueryGenerator,
)
# Connections s... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import re
import pytest
from private_gpt.components.tabular.database_query_generator import (
DatabaseQueryGenerator,
)
SUPPORTED_CONNECTION_STRINGS = [
"postgresql://user:pass@localhost:5432/testdb",
"mssql+pyodbc://user:pass@server:1433/testdb?driver=ODBC+Driver+18+for+SQL+Server",
"m... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>)._create_embedding(_config())
_, kwargs = mock_embedding.call_args
assert kwargs["api_key"] == ""
<|fim_prefix|>from unittest.mock import patch
from private_gpt.components.embedding.factories.openai import OpenAIEmbeddingFactory
from private_gpt.settings.settings import (
EmbeddingModelConf... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>"search"}',
reasoning_tokens=["\n", "think"],
)
assert len(result["tools"]) == 1
assert "".join(result["reasoning"]) == "think"
def test_tool_then_reasoning_with_leading_space(self):
result = _run_tool_then_reasoning(
tool_token='{"tool": "searc... | fim | zylon-ai/private-gpt | python |
from collections.abc import AsyncGenerator, Generator
from typing import Any
from unittest.mock import MagicMock
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
LLMMetadata,
MessageRole,
)
from llama_index.core.llms.function_calli... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>True)
for filename in files:
(snap_path / filename).touch()
# Set mtime
mtime = now + mtime_offset
os.utime(snap_path, (mtime, mtime))
return repo_dir
return _create
<|fim_prefix|>"""Shared fixtures for model cache/discovery/d... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>"""Test broken and corrupted cache states.
Scenario 2: Broken/Corrupted State Scenarios
"""
from pathlib import Path
from private_gpt.components.llm.tokenizers.models.model_cache import (
find_local_cache_model,
find_repo_candidates,
validate_model_path,
)
class TestIncompleteCacheStates:
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>"""Test cache evolution and snapshot ordering.
Scenario 5: Cache Evolution Scenarios
"""
from pathlib import Path
from private_gpt.components.llm.tokenizers.models.model_cache import (
find_local_cache_model,
find_repo_candidates,
)
class TestSnapshotOrdering:
"""Scenario 5.3: Snapshot mti... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> create_hf_repo,
tokenizer_files: list[str],
mock_hf_hub_success,
):
"""First download tokenizer-only, second download full model."""
# Simulate first download: tokenizer only
repo_dir = create_hf_repo(
"incremental/test",
snapshots=[
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>"""Test download orchestration via HuggingFace Hub."""
from pathlib import Path
import pytest
from private_gpt.components.llm.tokenizers.models.model_downloader import (
download_from_hf,
download_model,
)
class TestNetworkFailures:
"""Network and dependency error handling."""
@pytes... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>"""Test validation logic for model cache.
Scenario 8: Validation Edge Cases
"""
from pathlib import Path
from private_gpt.components.llm.tokenizers.models.model_cache import (
has_all_safetensors,
has_tokenizer_files,
validate_model_path,
)
class TestTokenizerFileDetection:
"""Test has... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import Any
import pytest
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from private_gpt.components.chat.processors.chat_history.memory.utils.format import (
_guarantee_valid_user_block_sequence,
guarantee_valid_message_sequence,
)
@pytest.fixture
def system_... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import Any
import pytest
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from private_gpt.components.chat.processors.chat_history.memory.utils.repairs import (
repair_with_tools,
repair_without_tools,
)
@pytest.fixture
def system_message() -> ChatMessage:
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import pytest
from llama_index.core.base.llms.types impo<|fim_suffix|>-------------------
@pytest.mark.parametrize(
("chat_history", "expected_roles"),
[
# Right TLDR in middle of group → keep user + last run only (more is dropped)
(
[
_msg("user", "q1... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>st.mark.asyncio
@pytest.mark.parametrize(
("enable_preprocessing", "enable_evaluation", "expected_calls"),
[
(False, False, 6), # 1 strategy + 5 chunks
(True, False, 6), # 1 strategy + 5 chunks
(False, True, 11), # 1 strategy + 5 chunks * 2 (transcription + evaluation)
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import base64
import builtins
from typing import Any
import pytest
from llama_index.core.base.llms.types import ImageBlock
from llama_index.core.llms import ChatMessage
from pydantic import Field
from private_gpt.components.llm.custom.mock import FunctionCallingLLMMock
from private_gpt.components.multim... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>: ChatMessage
) -> None:
responses: list[MultimodalProcessingResponse] = []
async for response in preprocess_multimodal_message(
main_llm,
multimodal_message.model_copy(),
image_multimodal_llm=main_llm,
audio_multimodal_llm=main_llm,
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import uuid
import pytest
from llama_index.core.schema import (
NodeRelationship,
NodeWithScore,
RelatedNodeInfo,
TextNode,
)
from private_gpt.components.node_store.node_store_component import NodeStoreComponent
from private_gpt.components.postprocessor.prev_next_replacement import (
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import textwrap
import pytest
from private_gpt.components.ingest.metadata_helper import MetadataNode
from private_gpt.components.ingest.transformations.markdown_to_tree_transform import (
MarkdownTreeNodeParser,
)
from private_gpt.components.postprocessor.tree_expansion.document_expander import (
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import textwrap
import pytest
from private_gpt.components.ingest.metadata_helper import MetadataNode
from private_gpt.components.ingest.transformations.markdown_to_tree_transform import (
MarkdownTreeNodeParser,
)
from private_gpt.components.postprocessor.tree_expansion.paper_distance import (
P... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>btrees) == 1, "Tree without sections should not be split"
# Verify all content is preserved
original_nodes = list(tree.flatten())
result_nodes = list(subtrees[0].flatten())
assert len(result_nodes) >= len(
original_nodes
), "Content was lost in no-sections tree"
# Verify ... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>n", "Age", "null"],
["John", 25, "NY"],
["Jane", 30, "LA"],
["n/a", "n/a", "n/a"],
]
)
result = processor.preprocess_table(df)
assert "Unknown_1" in result.columns
assert len(result) == 2
def test_numeric_conversion() -> None:
"""Test impro... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from unittest.mock import Mock
import pytest
from llama_index.core import PromptTemplate
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from llama_index.core.schema import NodeWithScore, TextNode
from private_gpt.components.prompts.prompt_builder import PromptBuilderService
from p... | fim | zylon-ai/private-gpt | python |
import tempfile
from collections.abc import Generator
from pathlib import Path
from typing import Any
import pytest
from jinja2 import Template
from llama_index.core import BasePromptTemplate
from llama_index.core.llms import ChatMessage
from private_gpt.components.prompts.rich_template import RichPromptTemplate
@p... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import pandas as pd
from private_gpt.components.readers.nodes.diff_node import DiffNode
from private_gpt.components.readers.nodes.table_node import TableNode
from private_gpt.components.readers.nodes.text_node import TextNode
from private_gpt.components.readers.nodes.tree_node import TreeNode
def run_d... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> assert list_node.height == 2
assert list_item1.height == 0
assert list_item2.height == 1
assert nested_list_item.height == 0
# Check absolute index
for i, node in enumerate(root.flatten()):
assert node.abs_idx == i
def test_insert_node() -> None:
root = DocumentRootN... | fim | zylon-ai/private-gpt | python |
import re
from typing import Any
from unittest.mock import MagicMock, patch
import pytest
from llama_index.core.schema import BaseNode
from private_gpt.components.readers.nodes.utils import metadata_dict_to_tree_node
@patch("llama_index.core.vector_stores.utils.metadata_dict_to_node")
def test_legacy_node_type(mock... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>
assert content.strip() == expected_output.strip()
def test_table_row_position_with_partials() -> None:
df = pd.DataFrame({"Name": ["Alice", "Bob"], "Age": [25, 30]})
table = TableNode(df=df)
# Pattern: partial, row, row, partial
partial1 = PartialNode(type=TableRowNode.get_type())
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>ponent.register_reader_factory(
"failing-reader",
FailingReaderFactory(injector.get(Settings), injector.test_injector),
)
reader_component.register_reader_factory(
"stub-reader",
StubReaderFactory(injector.get(Settings), injector.test_injector),
)
try:
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import asyncio
import uuid
from pathlib import Path
from llama_index.core.schema import MetadataMode
from private_gpt.components.ingest.metadata_helper import MetadataKeys
from private_gpt.components.ingest.utils import convert_unsupported_file, get_file_info
from private_gpt.components.readers import R... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import json
from datetime import UTC, datetime
from types import SimpleNamespace
from unittest.mock import AsyncMock
import pytest
from private_gpt.components.skills.models.skill_entities import (
SkillEntity,
SkillFilter,
SkillFrontmatter,
SkillVersionEntity,
SkillVersionWithSkillEn... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import json
from datetime import UTC, datetime
from types import SimpleNamespace
from unittest.mock import AsyncMock
import pytest
from private_gpt.components.skills.models.skill_entities import (
SkillEntity,
SkillFilter,
SkillFrontmatter,
SkillVersionEntity,
SkillVersionWithSkillEn... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>ck(),
delete_prefix=AsyncMock(),
)
repo = SimpleNamespace(create_skill=AsyncMock())
service = _service(repo=repo, storage=storage)
await service.create_skill(
collection="tenant-a",
display_title="Skill",
source="custom",
loading="lazy",
rea... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>s=_settings(),
)
tool = builder.build_tool("corr-1")
result = await tool.async_fn(command="echo ok")
session.execute_bash.assert_awaited_once_with(
"echo ok",
timeout=None,
restart=False,
)
assert result[0].text == "exit_code: 0\n\nstdout:\nok"
@pytest.m... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from pathlib import Path
import pytest
from private_gpt.components.code_execution.local import LocalCodeExecutionProvider
from private_gpt.settings.settings import unsafe_typed_settings
def _settings(tmp_path: Path):
settings = unsafe_typed_settings.model_copy(deep=True)
settings.code_executio... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>b_extract_legacy_alias() -> None:
tool = ToolSpec(name="web_extract", type="web_extract_v1")
assert tool.get_original_tool_name() == WEB_FETCH_TOOL_NAME
<|fim_prefix|>from private_gpt.components.chat.models.chat_config_models import ToolSpec
from private_gpt.components.tools.tool_names import (
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>=TextEditorProcessor(text_editor_builder),
)
request = _request(
[
ToolSpec(
name="code_execution",
type="code_execution_v1",
input_schema={"type": "object", "properties": {}},
)
]
)
resolved = await p... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> TextNode(text="## Header\n\n- Item 1\n- Item 2"),
TextNode(text="- Item 3\n\n| Column1 | Column2 |\n|---------|---------|"),
TextNode(text="| Value1 | Value2 |\n\n```python\nprint('Hello')"),
TextNode(text="print('World')\n```\n\nAnother paragraph."),
]
expected = [
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from collections.abc import Iterator
import pandas as pd
import pytest
from private_gpt.components.ingest.metadata_helper import MetadataNode
from private_gpt.components.ingest.transformations.include_token_count_to_nodes_transform import (
IncludeTokenCountIntoNodesTransform,
)
from pri<|fim_suffix... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import pytest
from private_gpt.components.ingest.transformations.markdown_normalization_transform import (
MarkdownNormalizer,
)
def test_normalize_flat_list() -> None:
"""Test normalizing a flat Markdown list."""
normalizer = MarkdownNormalizer(target_indent=2)
content = "- Item 1\n -... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import TYPE_CHECKING
from llama_ind<|fim_suffix|> assert len(weights2) == 5
assert max(weights1) <= 1.0
assert min(weights1) > 0.0
def test_empty_input() -> None:
nodes: list[BaseNode] = []
transform = RemoveHeaderAndFooterTransform()
result = transform(nodes)
asse... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import unittest
from private_gpt.components.ingest.transformations.markdown_to_tree_transform import (
MarkdownTreeNodeParser,
)
from private_gpt.components.readers.nodes.tree_node import TreeMetadataMode, TreeNode
SAMPLE_MARKDOWN = """\
### Document Title
#### Subtitle
This is a sample document gen... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import pytest
from llama_index.core.node_parser import TokenTextSplitter
# Import the functions and classes from your modules.
from private_gpt.components.ingest.transformations.sentence_tree_node_parser import (
SentenceTreeNodeParser,
contains_arabic,
split_by_sentence_tokenizer,
split_... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import Any
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from private_gpt.components.web.web_search.providers.brave import (
BraveSearchProvider,
QuotaConsumed,
)
from private_gpt.settings.settings import Settings
@pytest.fixture
def mock_settings_factory():
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>3
assert all(len(user_results) == 2 for user_results in all_results)
# 6 total requests = 5 intervals of 1s
assert elapsed >= 5.0, f"Global rate limiting failed: elapsed={elapsed:.2f}s"
# Verify timestamps - each request should be separated by ~1s
for i in range(1... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>nitialized
# Call initialize again
service._initialize()
assert "WebSearchService already initialized, skipping" in caplog.text
@pytest.mark.parametrize(
("provider", "expected_class"),
[("brave", "BraveSearchProvider")],
)
def test_each_provider_init... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>te_summary_nodes(query_bundle, node)
assert result is not None
assert result.get_content() == "This is a valid summary."
<|fim_prefix|>from unittest.mock import AsyncMock, MagicMock
import pytest
from llama_index.core import QueryBundle
from llama_index.core.base.response.schema import Response
f... | fim | zylon-ai/private-gpt | python |
from typing import Any
from unittest.mock import MagicMock
import pytest
from llama_index.core.base.llms.types import LLMMetadata
from llama_index.core.llms import LLM
from llama_index.core.multi_modal_llms import MultiModalLLMMetadata
from private_gpt.components.llm.custom.base import ZylonLLM
from private_gpt.compo... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>g of life?")
input_event = CondenseInputEvent(query=query, chat_history=[])
result = await workflow.run(start_event=input_event)
assert isinstance(result, CondenseResultEvent)
assert result.condensed_query == query
assert result.original_query == query
@pytest.mark.asyncio
@pytest.m... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import Any
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.postprocessor import SimilarityPostprocessor
from llama_index.core.postprocessor.types import BaseNodePostprocessor
from llama_in... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from unittest.mock import AsyncMock, MagicMock
import pytest
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from llama_index.core.llms import LLM
from llama_index.core.postprocessor import SimilarityPostprocessor
from l... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import os
import pathlib
from glob import glob
root_path = pathlib.Path(__file__).parents[1]
# This is to prevent a bug in intellij t<|fim_suffix|>xture_path.replace("/", ".").replace("\\", ".").replace(".py", "")
pytest_plugins = [_as_module(fixture) for fixture in glob("tests/fixtures/[!_]*.py")]
<|f... | fim | zylon-ai/private-gpt | python |
from typing import Any
from unittest.mock import MagicMock
import pytest
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
MessageRole,
)
from llama_index.core.llms.function_calling import FunctionCallingLLM
from llama_index.core.llms.llm import ToolSelection
from private_gpt.compo... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from unittest.mock import Mock
import pytest
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.llms.types import (
ChatMessage,
MessageRole,
)
from llama_index.core.schema import MetadataMode, NodeWithScore
from private_gpt.components.engines.citations.for... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>[0]
assert error.error.message is not None
@pytest.mark.asyncio
async def test_multiple_citations_processing() -> None:
doc1 = create_document("DOC1", "First document content")
doc2 = create_document("DOC2", "Second document content")
documents = [doc1, doc2]
events = [
crea... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>()
unique_terms = analyzer.get_unique_terms(texts)
# Verify uniqueness
assert not any(
"revenue" in terms for terms in unique_terms
), "Revenue appears in multiple texts"
assert any("cost" in terms for terms in unique_terms), "Cost should be unique"
assert any("margin" in ... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>"""<|fim_suffix|>
<|fim_middle|>Global fixtures."""<|endoftext|> | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>)
<|fim_prefix|>import asyncio
import pytest
@pytest.fixture
def event_loop() -> asyncio.<|fim_middle|>AbstractEventLoop:
loop = asyncio.get_event_loop_policy().new_event_loop()
yield loop
loop.close(<|endoftext|> | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import contextlib
import pytest
from private_gpt.components.vector_store.vector_store_component import (
VectorStoreComponent,
)
from <|fim_suffix|>rt MockInjector
@pytest.fixture(autouse=True)
def _auto_close_vector_store_client(injector: MockInjector) -> None:
"""Auto close VectorStore clien... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>)
app_under_test.middleware("http")(inject_global_injector(injector))
return TestClient(app_under_test)
@pytest.fixture
async def async_test_client(
request: pytest.FixtureRequest, applied_migrations: MockInjector
) -> AsyncClient:
injector = applied_migrations
app_under_test = crea... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import base64
from pathlib import Path
import pytest
from fastapi.testclient import TestClient
from private_gpt.server.ingest.ingest_router import (
DeleteIngestedDocumentBody,
IngestBody,
IngestResponse,
)
from private_gpt.server.utils.artifact_input import FileArtifact
class IngestHelper... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>]] | list[str | ToolSelection] | None = None,
sleep_between_blocks: float = 0.0,
sleep_between_deltas: float = 0.0,
) -> FunctionCallingLLM:
if deltas is not None:
if not deltas:
raise ValueError("Deltas cannot be empty")
if isinstance(deltas, list) and all(
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>=scope)
return mock # type: ignore
def bind_settings(self, settings: dict[str, Any]) -> Settings:
merged = merge_settings([unsafe_settings, settings])
new_settings = Settings(**merged)
self.test_injector.binder.bind(Settings, new_settings)
return new_settings
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from dataclasses import dataclass
from typing import Any
import anthropic.types as sdk_types
from anthropic.types.raw_message_delta_event import Delta as SDKMessageDelta
from private_gpt.events.models import (
AudioBlock,
BinaryBlock,
CitationsDelta,
ContainerUploadBlock,
DirectCalle... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>ypeMapping) -> set[str]:
if not mapping.sdk_type:
return set()
return set(mapping.sdk_type.model_fields.keys())
def _is_optional_annotation(annotation: Any) -> bool:
"""Return True if the annotation is ``T | None`` / ``Optional[T]``."""
if get_origin(annotation) is typing.Union:
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>ve_schema_refs(fastapi_openapi_spec, local_components[local_name])
)
remote_schema = _normalize_schema(
_resolve_schema_refs(openapi_spec, remote_components[remote_name])
)
diffs = set(_schema_diff(local_schema, remote_schema, local_name))
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>type(s) detected: {names}. "
"Add TypeMapping entries to STREAMING_EVENT_REGISTRY in registry.py "
"and implement corresponding models in models.py."
)
if extra:
names = ", ".join(t.__name__ for t in extra)
messages.append(
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import Any
from tests.models.anthropic.registry import ALL_MAPPINGS, TypeMapping
def _strip_zylon_fields(data: Any, zylon_fields: frozenset[str]) -> Any:
if isinstance(data, dict):
return {
k: _strip_zylon_fields(v, zylon_fields)
for k, v in data.items()
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>) -> None:
tools = [create_semantic_tool([ingest_test_artifact(test_client)])]
setup_mock_llm(injector, tools, _DEFAULT_PING_INTERVAL + 1)
client = anthropic.AsyncAnthropic(**CLIENT_KWARGS)
client._client = create_mock_http_client(test_client, httpx_mock, is_async=True)
async with cl... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> pytest.param(
413,
"request_too_large",
1024,
"x" * 50_000,
id="request_too_large",
),
],
)
@pytest.mark.httpx_mock(assert_all_responses_were_requested=False)
def test_langchain_http_error_parsing_real(
injector: MockInjector,
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import math
from typing import Any
import pytest
from private_gpt.server.chat.interceptors.schema_coercing_tool_interceptor import (
SchemaCoercionError,
_coerce_kwargs,
)
_NULLABLE_STR: dict[str, Any] = {"type": ["string", "null"]}
_NULLABLE_INT: dict[str, Any] = {"type": ["integer", "null"]}
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>_skill", "unload_skill_v1"}),
# unversioned type: stripping produces the same string, so only one entry
("web_search", "web_search", {"web_search"}),
# name only (no type)
("semantic_search", None, {"semantic_search"}),
# whitespace and casing are normalised
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>llm=get_mock_function_calling_llm(["ok"]),
phase=InterceptorPhase.VALIDATION,
emit_fn=lambda _event: None,
)
await interceptor.intercept(context)
@pytest.mark.asyncio
async def test_rejects_tools_when_model_is_not_function_calling() -> None:
interceptor = _build_interceptor(
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import TYPE_CHECKING
import pytest
from httpx import AsyncClient
from private_gpt.chat.input_models import MessageInput
from private_gpt.components.streaming.providers.models import (
StreamStatus,
)
from private_gpt.server.chat.chat_router import ChatBody
from private_gpt.server.chat_as... | fim | zylon-ai/private-gpt | python |
import uuid
from typing import Any
import pytest
from httpx import AsyncClient
from llama_index.core.base.llms.types import ChatMessage
from llama_index.core.llms.llm import ToolSelection
from private_gpt.chat.extensions.context_filter import ContextFilter
from private_gpt.chat.input_models import (
Citations,
... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>arameter with underscore",
},
"normal_param": {"type": "boolean", "description": "Normal parameter"},
"class": {"type": "string", "description": "Keyword field"},
"match": {"type": "string", "description": "Soft keyword field"},
}... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import asyncio
import json
import uuid
from collections.abc import AsyncGenerator
from typing import Any
from unittest.mock import AsyncMock
import pytest
from httpx import AsyncClient
from llama_index.core.base.llms.types import ChatMessage, ChatResponse, MessageRole
from llama_index.core.llms.llm impor... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import json
import uuid
from typing import Any
import pytest
from httpx import AsyncClient
from llama_index.core.base.llms.types import ChatMessage
from llama_index.core.llms.llm import ToolSelection
from private_gpt.chat.input_models import MessageInput
from private_gpt.components.llm.llm_component imp... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>=MessageRole.USER)],
system=ResolvedSystemConfig(prompt="system"),
)
result = await service.chat(request)
assert isinstance(result, Completion)
assert result.exception is not None
assert "boom" in str(result.exception)
@pytest.mark.asyncio
async def test_validate_runs_befor... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>import asyncio
from typing import Any
import pytest
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from llama_index.core.base.llms.types import (
TextBlock as LITextBlock,
)
from llama_index.core.schema import NodeWithScore, TextNode
from pydantic import ValidationError
from p... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> """Test schema with multiple levels of nested objects."""
schema = {
"type": "object",
"properties": {
"level1": {
"type": "object",
"properties": {
"level2": {
... | fim | zylon-ai/private-gpt | python |
import uuid
from pathlib import Path
from fastapi.testclient import TestClient
from private_gpt.chat.extensions.context_filter import ContextFilter
from private_gpt.server.content.content_router import (
ChunkedContentResponse,
ContentBody,
ContentResponse,
)
from tests.fixtures.ingest_helper import Inges... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from fastapi.testclient import TestClient
from private_gpt.server.embeddings.embeddings_router import (
EmbeddingsBody,
EmbeddingsResponse,
)
def test_embeddings_generation(test_client: TestClient) -> None:
body = EmbeddingsBody(input="Embed me")
response = test_client.post("/v1/embeddi... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>mp": datetime.datetime(
2024,
1,
15,
10,
30,
0,
tzinfo=datetime.timezone(datetime.timedelta(hours=9)), # JST
),
},
{
... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from typing import Literal
import pytest
from private_gpt.events.models import (
AudioBlock,
BinaryBlock,
ImageBlock,
RawContentBlockDeltaEvent,
RawContentBlockStartEvent,
ResourceBlock,
ResourceLinkBlock,
SourceBlock,
SourceDelta,
TextBlock,
TextDelta,
Th... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>ication/pdf",
file_size=1024,
config={"error": "Failed to parse PDF"},
)
errors, warnings = IngestionHelper.validate_file_info(file_info)
assert IngestionValidationErrors.MALFORMED_FILE in errors
assert len(errors) == 1
assert len(warnings) == 0
# def test_validate_... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|>te the created temp file
ingest_helper.delete_file(collection, "file_to_keep")
def test_delete_async(
test_client: TestClient, injector: MockInjector, ingest_helper: IngestHelper
) -> None:
collection = str(uuid.uuid4())
# Mock broker to receive callback
broker_mock = Mock(BrokerComp... | fim | zylon-ai/private-gpt | python |
<|fim_prefix|>from pathlib import Path
from unittest.mock import patch
import pytest
from private_gpt.artifact_index.base_artifact_index import (
ArtifactIndexStatus,
IndexNotReadyException,
)
from private_gpt.server.ingest.ingest_service import IngestService
from tests.fixtures.mock_injector import MockInjec... | fim | zylon-ai/private-gpt | python |
<|fim_suffix|> return real_settings
mock_injector.get.side_effect = injector_get
with patch(
"private_gpt.di.get_global_injector",
return_value=mock_injector,
):
from private_gpt.celery.tasks.ingestion.extraction_tasks import (
ensure_to_remove_temporal_files,... | fim | zylon-ai/private-gpt | python |
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