code stringlengths 141 97.3k | apis listlengths 1 24 | extract_api stringlengths 113 214k |
|---|---|---|
"""Base object types."""
import pickle
import warnings
from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.query_pipeline.query import (
ChainableMixin,
InputKeys,
OutputKeys,
QueryComp... | [
"llama_index.core.objects.base_node_mapping.SimpleObjectNodeMapping.from_persist_dir",
"llama_index.core.base.query_pipeline.query.InputKeys.from_keys",
"llama_index.core.objects.base_node_mapping.SimpleObjectNodeMapping.from_objects",
"llama_index.core.bridge.pydantic.Field",
"llama_index.core.base.query_p... | [((897, 910), 'typing.TypeVar', 'TypeVar', (['"""OT"""'], {}), "('OT')\n", (904, 910), False, 'from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar\n'), ((2032, 2068), 'llama_index.core.bridge.pydantic.Field', 'Field', (['...'], {'description': '"""Retriever."""'}), "(..., description='Retriev... |
"""Base object types."""
import pickle
import warnings
from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.query_pipeline.query import (
ChainableMixin,
InputKeys,
OutputKeys,
QueryComp... | [
"llama_index.core.objects.base_node_mapping.SimpleObjectNodeMapping.from_persist_dir",
"llama_index.core.base.query_pipeline.query.InputKeys.from_keys",
"llama_index.core.objects.base_node_mapping.SimpleObjectNodeMapping.from_objects",
"llama_index.core.bridge.pydantic.Field",
"llama_index.core.base.query_p... | [((897, 910), 'typing.TypeVar', 'TypeVar', (['"""OT"""'], {}), "('OT')\n", (904, 910), False, 'from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar\n'), ((2032, 2068), 'llama_index.core.bridge.pydantic.Field', 'Field', (['...'], {'description': '"""Retriever."""'}), "(..., description='Retriev... |
"""Base object types."""
import pickle
import warnings
from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.query_pipeline.query import (
ChainableMixin,
InputKeys,
OutputKeys,
QueryComp... | [
"llama_index.core.objects.base_node_mapping.SimpleObjectNodeMapping.from_persist_dir",
"llama_index.core.base.query_pipeline.query.InputKeys.from_keys",
"llama_index.core.objects.base_node_mapping.SimpleObjectNodeMapping.from_objects",
"llama_index.core.bridge.pydantic.Field",
"llama_index.core.base.query_p... | [((897, 910), 'typing.TypeVar', 'TypeVar', (['"""OT"""'], {}), "('OT')\n", (904, 910), False, 'from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar\n'), ((2032, 2068), 'llama_index.core.bridge.pydantic.Field', 'Field', (['...'], {'description': '"""Retriever."""'}), "(..., description='Retriev... |
from typing import Any, Callable, Optional, Sequence
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
CompletionResponse,
CompletionResponseGen,
LLMMetadata,
)
from llama_index.legacy.llms.base import llm_completion_callback
from lla... | [
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.core.llms.types.CompletionResponse"
] | [((1537, 1562), 'llama_index.legacy.llms.base.llm_completion_callback', 'llm_completion_callback', ([], {}), '()\n', (1560, 1562), False, 'from llama_index.legacy.llms.base import llm_completion_callback\n'), ((1876, 1901), 'llama_index.legacy.llms.base.llm_completion_callback', 'llm_completion_callback', ([], {}), '()... |
from typing import Any, Callable, Optional, Sequence
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
CompletionResponse,
CompletionResponseGen,
LLMMetadata,
)
from llama_index.legacy.llms.base import llm_completion_callback
from lla... | [
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.core.llms.types.CompletionResponse"
] | [((1537, 1562), 'llama_index.legacy.llms.base.llm_completion_callback', 'llm_completion_callback', ([], {}), '()\n', (1560, 1562), False, 'from llama_index.legacy.llms.base import llm_completion_callback\n'), ((1876, 1901), 'llama_index.legacy.llms.base.llm_completion_callback', 'llm_completion_callback', ([], {}), '()... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset("MiniCovidQaDataset", "./data")
... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 319), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""MiniCovidQaDataset"""', '"""./data"""'], {}), "('MiniCovidQaDataset', './data')\n", (287, 319), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((364, 416), 'llama_index.core.VectorStore... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset("MiniCovidQaDataset", "./data")
... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 319), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""MiniCovidQaDataset"""', '"""./data"""'], {}), "('MiniCovidQaDataset', './data')\n", (287, 319), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((364, 416), 'llama_index.core.VectorStore... |
"""Palm API."""
import os
from typing import Any, Callable, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types import (
Ch... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.bridge.pydantic.PrivateAttr"
] | [((708, 779), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': 'DEFAULT_PALM_MODEL', 'description': '"""The PaLM model to use."""'}), "(default=DEFAULT_PALM_MODEL, description='The PaLM model to use.')\n", (713, 779), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseGen,
CompletionResponse,
Comp... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.bridge.pydantic.PrivateAttr",
"llama_index.legacy.llms.generic_utils.get_from_p... | [((827, 870), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The AI21 model to use."""'}), "(description='The AI21 model to use.')\n", (832, 870), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((892, 954), 'llama_index.legacy.bridge.pydantic.Field', 'Field... |
import json
from typing import Any, Callable, Dict, List, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatR... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.vllm_utils.post_http_request",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.generic_utils.stream_com... | [((1015, 1065), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The HuggingFace Model to use."""'}), "(description='The HuggingFace Model to use.')\n", (1020, 1065), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1092, 1149), 'llama_index.legacy.bridge.pyd... |
import json
from typing import Any, Callable, Dict, List, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatR... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.vllm_utils.post_http_request",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.generic_utils.stream_com... | [((1015, 1065), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The HuggingFace Model to use."""'}), "(description='The HuggingFace Model to use.')\n", (1020, 1065), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1092, 1149), 'llama_index.legacy.bridge.pyd... |
"""Prompts."""
from abc import ABC, abstractmethod
from copy import deepcopy
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
)
from llama_index.core.bridge.pydantic import Field
if TYPE_CHECKING:
from llama_index.core.bridge.lan... | [
"llama_index.core.base.llms.generic_utils.prompt_to_messages",
"llama_index.llms.langchain.utils.from_lc_messages",
"llama_index.core.base.llms.types.ChatMessage.from_str",
"llama_index.core.bridge.langchain.ConditionalPromptSelector",
"llama_index.core.bridge.pydantic.Field",
"llama_index.core.base.query... | [((1473, 1559), 'llama_index.core.bridge.pydantic.Field', 'Field', ([], {'default_factory': 'dict', 'description': '"""Template variable mappings (Optional)."""'}), "(default_factory=dict, description=\n 'Template variable mappings (Optional).')\n", (1478, 1559), False, 'from llama_index.core.bridge.pydantic import ... |
"""Prompts."""
from abc import ABC, abstractmethod
from copy import deepcopy
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
)
from llama_index.core.bridge.pydantic import Field
if TYPE_CHECKING:
from llama_index.core.bridge.lan... | [
"llama_index.core.base.llms.generic_utils.prompt_to_messages",
"llama_index.llms.langchain.utils.from_lc_messages",
"llama_index.core.base.llms.types.ChatMessage.from_str",
"llama_index.core.bridge.langchain.ConditionalPromptSelector",
"llama_index.core.bridge.pydantic.Field",
"llama_index.core.base.query... | [((1473, 1559), 'llama_index.core.bridge.pydantic.Field', 'Field', ([], {'default_factory': 'dict', 'description': '"""Template variable mappings (Optional)."""'}), "(default_factory=dict, description=\n 'Template variable mappings (Optional).')\n", (1478, 1559), False, 'from llama_index.core.bridge.pydantic import ... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
from llama_index.llms import OpenAI
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_data... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents",
"llama_index.llms.OpenAI"
] | [((301, 371), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""Uber10KDataset2021"""', '"""./uber10k_2021_dataset"""'], {}), "('Uber10KDataset2021', './uber10k_2021_dataset')\n", (323, 371), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((430, 482... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
from llama_index.llms import OpenAI
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_data... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents",
"llama_index.llms.OpenAI"
] | [((301, 371), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""Uber10KDataset2021"""', '"""./uber10k_2021_dataset"""'], {}), "('Uber10KDataset2021', './uber10k_2021_dataset')\n", (323, 371), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((430, 482... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core.evaluation import PairwiseComparisonEvaluator
from llama_index.llms import OpenAI, Gemini
from llama_index.core import ServiceContext
import pandas as pd
... | [
"llama_index.llms.Gemini",
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.llms.OpenAI",
"llama_index.core.evaluation.PairwiseComparisonEvaluator"
] | [((402, 475), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""MtBenchHumanJudgementDataset"""', '"""./mt_bench_data"""'], {}), "('MtBenchHumanJudgementDataset', './mt_bench_data')\n", (424, 475), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((16... |
from abc import abstractmethod
from typing import (
Any,
Sequence,
)
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
CompletionResponse,
CompletionResponseAsyncGen,
CompletionResponseGen,
LLMMetadata,
)
from llama_... | [
"llama_index.core.callbacks.CallbackManager",
"llama_index.core.bridge.pydantic.validator",
"llama_index.core.bridge.pydantic.Field"
] | [((669, 721), 'llama_index.core.bridge.pydantic.Field', 'Field', ([], {'default_factory': 'CallbackManager', 'exclude': '(True)'}), '(default_factory=CallbackManager, exclude=True)\n', (674, 721), False, 'from llama_index.core.bridge.pydantic import Field, validator\n'), ((800, 839), 'llama_index.core.bridge.pydantic.v... |
from abc import abstractmethod
from typing import (
Any,
Sequence,
)
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
CompletionResponse,
CompletionResponseAsyncGen,
CompletionResponseGen,
LLMMetadata,
)
from llama_... | [
"llama_index.core.callbacks.CallbackManager",
"llama_index.core.bridge.pydantic.validator",
"llama_index.core.bridge.pydantic.Field"
] | [((669, 721), 'llama_index.core.bridge.pydantic.Field', 'Field', ([], {'default_factory': 'CallbackManager', 'exclude': '(True)'}), '(default_factory=CallbackManager, exclude=True)\n', (674, 721), False, 'from llama_index.core.bridge.pydantic import Field, validator\n'), ((800, 839), 'llama_index.core.bridge.pydantic.v... |
from abc import abstractmethod
from typing import (
Any,
Sequence,
)
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
CompletionResponse,
CompletionResponseAsyncGen,
CompletionResponseGen,
LLMMetadata,
)
from llama_... | [
"llama_index.core.callbacks.CallbackManager",
"llama_index.core.bridge.pydantic.validator",
"llama_index.core.bridge.pydantic.Field"
] | [((669, 721), 'llama_index.core.bridge.pydantic.Field', 'Field', ([], {'default_factory': 'CallbackManager', 'exclude': '(True)'}), '(default_factory=CallbackManager, exclude=True)\n', (674, 721), False, 'from llama_index.core.bridge.pydantic import Field, validator\n'), ((800, 839), 'llama_index.core.bridge.pydantic.v... |
from abc import abstractmethod
from typing import Any, List, Sequence, Union
from llama_index.core.base.query_pipeline.query import (
ChainableMixin,
QueryComponent,
)
from llama_index.core.bridge.pydantic import BaseModel
from llama_index.core.prompts.mixin import PromptMixin, PromptMixinType
from llama_index... | [
"llama_index.core.query_pipeline.components.router.SelectorComponent",
"llama_index.core.schema.QueryBundle",
"llama_index.core.tools.types.ToolMetadata"
] | [((3300, 3332), 'llama_index.core.query_pipeline.components.router.SelectorComponent', 'SelectorComponent', ([], {'selector': 'self'}), '(selector=self)\n', (3317, 3332), False, 'from llama_index.core.query_pipeline.components.router import SelectorComponent\n'), ((1653, 1685), 'llama_index.core.tools.types.ToolMetadat... |
from abc import abstractmethod
from typing import Any, List, Sequence, Union
from llama_index.core.base.query_pipeline.query import (
ChainableMixin,
QueryComponent,
)
from llama_index.core.bridge.pydantic import BaseModel
from llama_index.core.prompts.mixin import PromptMixin, PromptMixinType
from llama_index... | [
"llama_index.core.query_pipeline.components.router.SelectorComponent",
"llama_index.core.schema.QueryBundle",
"llama_index.core.tools.types.ToolMetadata"
] | [((3300, 3332), 'llama_index.core.query_pipeline.components.router.SelectorComponent', 'SelectorComponent', ([], {'selector': 'self'}), '(selector=self)\n', (3317, 3332), False, 'from llama_index.core.query_pipeline.components.router import SelectorComponent\n'), ((1653, 1685), 'llama_index.core.tools.types.ToolMetadat... |
from abc import abstractmethod
from typing import Any, List, Sequence, Union
from llama_index.core.base.query_pipeline.query import (
ChainableMixin,
QueryComponent,
)
from llama_index.core.bridge.pydantic import BaseModel
from llama_index.core.prompts.mixin import PromptMixin, PromptMixinType
from llama_index... | [
"llama_index.core.query_pipeline.components.router.SelectorComponent",
"llama_index.core.schema.QueryBundle",
"llama_index.core.tools.types.ToolMetadata"
] | [((3300, 3332), 'llama_index.core.query_pipeline.components.router.SelectorComponent', 'SelectorComponent', ([], {'selector': 'self'}), '(selector=self)\n', (3317, 3332), False, 'from llama_index.core.query_pipeline.components.router import SelectorComponent\n'), ((1653, 1685), 'llama_index.core.tools.types.ToolMetadat... |
"""Base agent type."""
import uuid
from abc import abstractmethod
from typing import Any, Dict, List, Optional
from llama_index.legacy.bridge.pydantic import BaseModel, Field
from llama_index.legacy.callbacks import CallbackManager, trace_method
from llama_index.legacy.chat_engine.types import (
BaseChatEngine,
... | [
"llama_index.legacy.callbacks.trace_method",
"llama_index.legacy.bridge.pydantic.Field"
] | [((1310, 1331), 'llama_index.legacy.callbacks.trace_method', 'trace_method', (['"""query"""'], {}), "('query')\n", (1322, 1331), False, 'from llama_index.legacy.callbacks import CallbackManager, trace_method\n'), ((1633, 1654), 'llama_index.legacy.callbacks.trace_method', 'trace_method', (['"""query"""'], {}), "('query... |
import json
from typing import Any, Dict, Sequence, Tuple
import httpx
from httpx import Timeout
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.constants import DEFAULT_CONTEXT_WINDOW, DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,... | [
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field"
] | [((816, 911), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': '"""http://localhost:11434"""', 'description': '"""Base url the model is hosted under."""'}), "(default='http://localhost:11434', description=\n 'Base url the model is hosted under.')\n", (821, 911), False, 'from llama_index.legacy.b... |
import json
from typing import Any, Dict, Sequence, Tuple
import httpx
from httpx import Timeout
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.constants import DEFAULT_CONTEXT_WINDOW, DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,... | [
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field"
] | [((816, 911), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': '"""http://localhost:11434"""', 'description': '"""Base url the model is hosted under."""'}), "(default='http://localhost:11434', description=\n 'Base url the model is hosted under.')\n", (821, 911), False, 'from llama_index.legacy.b... |
import warnings
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatRes... | [
"llama_index.legacy.llms.cohere_utils.messages_to_cohere_history",
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.cohere_utils.cohere_modelname_to_contextsize",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.leg... | [((897, 942), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The cohere model to use."""'}), "(description='The cohere model to use.')\n", (902, 942), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((968, 1025), 'llama_index.legacy.bridge.pydantic.Field', '... |
import warnings
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatRes... | [
"llama_index.legacy.llms.cohere_utils.messages_to_cohere_history",
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.cohere_utils.cohere_modelname_to_contextsize",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.leg... | [((897, 942), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The cohere model to use."""'}), "(description='The cohere model to use.')\n", (902, 942), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((968, 1025), 'llama_index.legacy.bridge.pydantic.Field', '... |
from abc import abstractmethod
from typing import List
from llama_index.core.indices.query.schema import QueryBundle, QueryType
from llama_index.core.prompts.mixin import PromptMixin
from llama_index.core.schema import NodeWithScore
class BaseImageRetriever(PromptMixin):
"""Base Image Retriever Abstraction."""
... | [
"llama_index.core.indices.query.schema.QueryBundle"
] | [((706, 748), 'llama_index.core.indices.query.schema.QueryBundle', 'QueryBundle', ([], {'query_str': 'str_or_query_bundle'}), '(query_str=str_or_query_bundle)\n', (717, 748), False, 'from llama_index.core.indices.query.schema import QueryBundle, QueryType\n'), ((1525, 1582), 'llama_index.core.indices.query.schema.Query... |
from abc import abstractmethod
from typing import List
from llama_index.core.indices.query.schema import QueryBundle, QueryType
from llama_index.core.prompts.mixin import PromptMixin
from llama_index.core.schema import NodeWithScore
class BaseImageRetriever(PromptMixin):
"""Base Image Retriever Abstraction."""
... | [
"llama_index.core.indices.query.schema.QueryBundle"
] | [((706, 748), 'llama_index.core.indices.query.schema.QueryBundle', 'QueryBundle', ([], {'query_str': 'str_or_query_bundle'}), '(query_str=str_or_query_bundle)\n', (717, 748), False, 'from llama_index.core.indices.query.schema import QueryBundle, QueryType\n'), ((1525, 1582), 'llama_index.core.indices.query.schema.Query... |
import json
from abc import abstractmethod
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, Dict, Optional, Type
if TYPE_CHECKING:
from llama_index.legacy.bridge.langchain import StructuredTool, Tool
from deprecated import deprecated
from llama_index.legacy.bridge.pydantic import BaseModel... | [
"llama_index.legacy.bridge.langchain.Tool.from_function",
"llama_index.legacy.bridge.langchain.StructuredTool.from_function"
] | [((1586, 1675), 'deprecated.deprecated', 'deprecated', (['"""Deprecated in favor of `to_openai_tool`, which should be used instead."""'], {}), "(\n 'Deprecated in favor of `to_openai_tool`, which should be used instead.')\n", (1596, 1675), False, 'from deprecated import deprecated\n'), ((1400, 1422), 'json.dumps', '... |
import json
from abc import abstractmethod
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, Dict, Optional, Type
if TYPE_CHECKING:
from llama_index.legacy.bridge.langchain import StructuredTool, Tool
from deprecated import deprecated
from llama_index.legacy.bridge.pydantic import BaseModel... | [
"llama_index.legacy.bridge.langchain.Tool.from_function",
"llama_index.legacy.bridge.langchain.StructuredTool.from_function"
] | [((1586, 1675), 'deprecated.deprecated', 'deprecated', (['"""Deprecated in favor of `to_openai_tool`, which should be used instead."""'], {}), "(\n 'Deprecated in favor of `to_openai_tool`, which should be used instead.')\n", (1596, 1675), False, 'from deprecated import deprecated\n'), ((1400, 1422), 'json.dumps', '... |
import logging
from dataclasses import dataclass
from typing import Any, List, Optional, cast
from deprecated import deprecated
import llama_index.core
from llama_index.core.bridge.pydantic import BaseModel
from llama_index.core.callbacks.base import CallbackManager
from llama_index.core.base.embeddings.base import B... | [
"llama_index.core.embeddings.utils.resolve_embed_model",
"llama_index.core.node_parser.loading.load_parser",
"llama_index.core.extractors.loading.load_extractor",
"llama_index.core.callbacks.base.CallbackManager",
"llama_index.core.indices.prompt_helper.PromptHelper.from_llm_metadata",
"llama_index.core.s... | [((1138, 1165), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (1155, 1165), False, 'import logging\n'), ((1940, 1997), 'llama_index.core.indices.prompt_helper.PromptHelper.from_llm_metadata', 'PromptHelper.from_llm_metadata', ([], {'llm_metadata': 'llm_metadata'}), '(llm_metadata=llm_met... |
import logging
from dataclasses import dataclass
from typing import Any, List, Optional, cast
from deprecated import deprecated
import llama_index.core
from llama_index.core.bridge.pydantic import BaseModel
from llama_index.core.callbacks.base import CallbackManager
from llama_index.core.base.embeddings.base import B... | [
"llama_index.core.embeddings.utils.resolve_embed_model",
"llama_index.core.node_parser.loading.load_parser",
"llama_index.core.extractors.loading.load_extractor",
"llama_index.core.callbacks.base.CallbackManager",
"llama_index.core.indices.prompt_helper.PromptHelper.from_llm_metadata",
"llama_index.core.s... | [((1138, 1165), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (1155, 1165), False, 'import logging\n'), ((1940, 1997), 'llama_index.core.indices.prompt_helper.PromptHelper.from_llm_metadata', 'PromptHelper.from_llm_metadata', ([], {'llm_metadata': 'llm_metadata'}), '(llm_metadata=llm_met... |
from typing import List, Optional
import fsspec
from llama_index.core.bridge.pydantic import BaseModel, Field
from llama_index.core.schema import BaseNode
from llama_index.core.storage.docstore.utils import doc_to_json, json_to_doc
from llama_index.core.storage.kvstore import (
SimpleKVStore as SimpleCache,
)
from... | [
"llama_index.core.storage.docstore.utils.json_to_doc",
"llama_index.core.storage.docstore.utils.doc_to_json",
"llama_index.core.storage.kvstore.SimpleKVStore.from_persist_path",
"llama_index.core.bridge.pydantic.Field"
] | [((577, 655), 'llama_index.core.bridge.pydantic.Field', 'Field', ([], {'default': 'DEFAULT_CACHE_NAME', 'description': '"""Collection name of the cache."""'}), "(default=DEFAULT_CACHE_NAME, description='Collection name of the cache.')\n", (582, 655), False, 'from llama_index.core.bridge.pydantic import BaseModel, Field... |
from typing import List, Optional
import fsspec
from llama_index.core.bridge.pydantic import BaseModel, Field
from llama_index.core.schema import BaseNode
from llama_index.core.storage.docstore.utils import doc_to_json, json_to_doc
from llama_index.core.storage.kvstore import (
SimpleKVStore as SimpleCache,
)
from... | [
"llama_index.core.storage.docstore.utils.json_to_doc",
"llama_index.core.storage.docstore.utils.doc_to_json",
"llama_index.core.storage.kvstore.SimpleKVStore.from_persist_path",
"llama_index.core.bridge.pydantic.Field"
] | [((577, 655), 'llama_index.core.bridge.pydantic.Field', 'Field', ([], {'default': 'DEFAULT_CACHE_NAME', 'description': '"""Collection name of the cache."""'}), "(default=DEFAULT_CACHE_NAME, description='Collection name of the cache.')\n", (582, 655), False, 'from llama_index.core.bridge.pydantic import BaseModel, Field... |
"""Base object types."""
import pickle
import warnings
from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.core.base_retriever import BaseRetriever
from... | [
"llama_index.legacy.core.query_pipeline.query_component.OutputKeys.from_keys",
"llama_index.legacy.objects.base_node_mapping.SimpleObjectNodeMapping.from_objects",
"llama_index.legacy.core.query_pipeline.query_component.InputKeys.from_keys",
"llama_index.legacy.objects.base_node_mapping.SimpleObjectNodeMappin... | [((925, 938), 'typing.TypeVar', 'TypeVar', (['"""OT"""'], {}), "('OT')\n", (932, 938), False, 'from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar\n'), ((2060, 2096), 'llama_index.legacy.bridge.pydantic.Field', 'Field', (['...'], {'description': '"""Retriever."""'}), "(..., description='Retri... |
"""Base object types."""
import pickle
import warnings
from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.core.base_retriever import BaseRetriever
from... | [
"llama_index.legacy.core.query_pipeline.query_component.OutputKeys.from_keys",
"llama_index.legacy.objects.base_node_mapping.SimpleObjectNodeMapping.from_objects",
"llama_index.legacy.core.query_pipeline.query_component.InputKeys.from_keys",
"llama_index.legacy.objects.base_node_mapping.SimpleObjectNodeMappin... | [((925, 938), 'typing.TypeVar', 'TypeVar', (['"""OT"""'], {}), "('OT')\n", (932, 938), False, 'from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar\n'), ((2060, 2096), 'llama_index.legacy.bridge.pydantic.Field', 'Field', (['...'], {'description': '"""Retriever."""'}), "(..., description='Retri... |
"""Base reader class."""
from abc import ABC
from typing import TYPE_CHECKING, Any, Dict, Iterable, List
if TYPE_CHECKING:
from llama_index.legacy.bridge.langchain import Document as LCDocument
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.schema import BaseComponent, Document
cla... | [
"llama_index.legacy.bridge.pydantic.Field"
] | [((1225, 1327), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': '(False)', 'description': '"""Whether the data is loaded from a remote API or a local file."""'}), "(default=False, description=\n 'Whether the data is loaded from a remote API or a local file.')\n", (1230, 1327), False, 'from llam... |
"""Base reader class."""
from abc import ABC
from typing import TYPE_CHECKING, Any, Dict, Iterable, List
if TYPE_CHECKING:
from llama_index.legacy.bridge.langchain import Document as LCDocument
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.schema import BaseComponent, Document
cla... | [
"llama_index.legacy.bridge.pydantic.Field"
] | [((1225, 1327), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': '(False)', 'description': '"""Whether the data is loaded from a remote API or a local file."""'}), "(default=False, description=\n 'Whether the data is loaded from a remote API or a local file.')\n", (1230, 1327), False, 'from llam... |
"""
Portkey integration with Llama_index for enhanced monitoring.
"""
from typing import TYPE_CHECKING, Any, Callable, List, Optional, Sequence, Union, cast
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatRes... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.generic_utils.stream_completion_to_chat_decorator",
"llama_index.legacy.llms.portkey_utils.is_chat_model",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llm... | [((1284, 1347), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The mode for using the Portkey integration"""'}), "(description='The mode for using the Portkey integration')\n", (1289, 1347), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1390, 1426), 'lla... |
"""
Portkey integration with Llama_index for enhanced monitoring.
"""
from typing import TYPE_CHECKING, Any, Callable, List, Optional, Sequence, Union, cast
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatRes... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.generic_utils.stream_completion_to_chat_decorator",
"llama_index.legacy.llms.portkey_utils.is_chat_model",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llm... | [((1284, 1347), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The mode for using the Portkey integration"""'}), "(description='The mode for using the Portkey integration')\n", (1289, 1347), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1390, 1426), 'lla... |
"""Query plan tool."""
from typing import Any, Dict, List, Optional
from llama_index.core.bridge.pydantic import BaseModel, Field
from llama_index.core.response_synthesizers import (
BaseSynthesizer,
get_response_synthesizer,
)
from llama_index.core.schema import NodeWithScore, TextNode
from llama_index.core.... | [
"llama_index.core.tools.types.ToolMetadata",
"llama_index.core.utils.print_text",
"llama_index.core.response_synthesizers.get_response_synthesizer",
"llama_index.core.bridge.pydantic.Field",
"llama_index.core.schema.TextNode",
"llama_index.core.schema.NodeWithScore"
] | [((1418, 1465), 'llama_index.core.bridge.pydantic.Field', 'Field', (['...'], {'description': '"""ID of the query node."""'}), "(..., description='ID of the query node.')\n", (1423, 1465), False, 'from llama_index.core.bridge.pydantic import BaseModel, Field\n'), ((1487, 1535), 'llama_index.core.bridge.pydantic.Field', ... |
"""Query plan tool."""
from typing import Any, Dict, List, Optional
from llama_index.core.bridge.pydantic import BaseModel, Field
from llama_index.core.response_synthesizers import (
BaseSynthesizer,
get_response_synthesizer,
)
from llama_index.core.schema import NodeWithScore, TextNode
from llama_index.core.... | [
"llama_index.core.tools.types.ToolMetadata",
"llama_index.core.utils.print_text",
"llama_index.core.response_synthesizers.get_response_synthesizer",
"llama_index.core.bridge.pydantic.Field",
"llama_index.core.schema.TextNode",
"llama_index.core.schema.NodeWithScore"
] | [((1418, 1465), 'llama_index.core.bridge.pydantic.Field', 'Field', (['...'], {'description': '"""ID of the query node."""'}), "(..., description='ID of the query node.')\n", (1423, 1465), False, 'from llama_index.core.bridge.pydantic import BaseModel, Field\n'), ((1487, 1535), 'llama_index.core.bridge.pydantic.Field', ... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
Co... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.generic_utils.stream_completion_to_chat_decorator",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.watsonx_utils.get_from_param_or_env_without_error",
"... | [((968, 1006), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The Model to use."""'}), "(description='The Model to use.')\n", (973, 1006), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1033, 1095), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([]... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
Co... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.generic_utils.stream_completion_to_chat_decorator",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.watsonx_utils.get_from_param_or_env_without_error",
"... | [((968, 1006), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The Model to use."""'}), "(description='The Model to use.')\n", (973, 1006), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1033, 1095), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([]... |
from typing import Any, Awaitable, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_TEMPERATURE
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResp... | [
"llama_index.legacy.llms.generic_utils.astream_completion_to_chat_decorator",
"llama_index.legacy.llms.generic_utils.astream_chat_to_completion_decorator",
"llama_index.legacy.llms.generic_utils.acompletion_to_chat_decorator",
"llama_index.legacy.llms.generic_utils.stream_completion_to_chat_decorator",
"lla... | [((1378, 1535), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': 'DEFAULT_LITELLM_MODEL', 'description': '"""The LiteLLM model to use. For complete list of providers https://docs.litellm.ai/docs/providers"""'}), "(default=DEFAULT_LITELLM_MODEL, description=\n 'The LiteLLM model to use. For compl... |
from typing import Any, Awaitable, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_TEMPERATURE
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResp... | [
"llama_index.legacy.llms.generic_utils.astream_completion_to_chat_decorator",
"llama_index.legacy.llms.generic_utils.astream_chat_to_completion_decorator",
"llama_index.legacy.llms.generic_utils.acompletion_to_chat_decorator",
"llama_index.legacy.llms.generic_utils.stream_completion_to_chat_decorator",
"lla... | [((1378, 1535), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': 'DEFAULT_LITELLM_MODEL', 'description': '"""The LiteLLM model to use. For complete list of providers https://docs.litellm.ai/docs/providers"""'}), "(default=DEFAULT_LITELLM_MODEL, description=\n 'The LiteLLM model to use. For compl... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset("MiniTruthfulQADataset", "./data... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 322), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""MiniTruthfulQADataset"""', '"""./data"""'], {}), "('MiniTruthfulQADataset', './data')\n", (287, 322), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((367, 419), 'llama_index.core.Vecto... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset("MiniTruthfulQADataset", "./data... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 322), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""MiniTruthfulQADataset"""', '"""./data"""'], {}), "('MiniTruthfulQADataset', './data')\n", (287, 322), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((367, 419), 'llama_index.core.Vecto... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_TEMPERATURE
# from mistralai.models.chat_completion import ChatMessage
from llama_index... | [
"llama_index.legacy.llms.generic_utils.astream_chat_to_completion_decorator",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.generic_utils.stream_chat_to_completion_decorator",
"llama_index.legacy.llms.base.llm_completion_callback",
"... | [((1271, 1357), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': 'DEFAULT_MISTRALAI_MODEL', 'description': '"""The mistralai model to use."""'}), "(default=DEFAULT_MISTRALAI_MODEL, description=\n 'The mistralai model to use.')\n", (1276, 1357), False, 'from llama_index.legacy.bridge.pydantic imp... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_TEMPERATURE
# from mistralai.models.chat_completion import ChatMessage
from llama_index... | [
"llama_index.legacy.llms.generic_utils.astream_chat_to_completion_decorator",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.generic_utils.stream_chat_to_completion_decorator",
"llama_index.legacy.llms.base.llm_completion_callback",
"... | [((1271, 1357), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'default': 'DEFAULT_MISTRALAI_MODEL', 'description': '"""The mistralai model to use."""'}), "(default=DEFAULT_MISTRALAI_MODEL, description=\n 'The mistralai model to use.')\n", (1276, 1357), False, 'from llama_index.legacy.bridge.pydantic imp... |
"""Base index classes."""
import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar, cast
from llama_index.legacy.chat_engine.types import BaseChatEngine, ChatMode
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
from llama_i... | [
"llama_index.legacy.agent.AgentRunner.from_llm",
"llama_index.legacy.ingestion.run_transformations",
"llama_index.legacy.query_engine.retriever_query_engine.RetrieverQueryEngine.from_args",
"llama_index.legacy.tools.query_engine.QueryEngineTool.from_defaults",
"llama_index.legacy.storage.storage_context.Sto... | [((793, 825), 'typing.TypeVar', 'TypeVar', (['"""IS"""'], {'bound': 'IndexStruct'}), "('IS', bound=IndexStruct)\n", (800, 825), False, 'from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar, cast\n'), ((838, 877), 'typing.TypeVar', 'TypeVar', (['"""IndexType"""'], {'bound': '"""BaseIndex"""'}),... |
"""Base index classes."""
import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar, cast
from llama_index.legacy.chat_engine.types import BaseChatEngine, ChatMode
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
from llama_i... | [
"llama_index.legacy.agent.AgentRunner.from_llm",
"llama_index.legacy.ingestion.run_transformations",
"llama_index.legacy.query_engine.retriever_query_engine.RetrieverQueryEngine.from_args",
"llama_index.legacy.tools.query_engine.QueryEngineTool.from_defaults",
"llama_index.legacy.storage.storage_context.Sto... | [((793, 825), 'typing.TypeVar', 'TypeVar', (['"""IS"""'], {'bound': 'IndexStruct'}), "('IS', bound=IndexStruct)\n", (800, 825), False, 'from typing import Any, Dict, Generic, List, Optional, Sequence, Type, TypeVar, cast\n'), ((838, 877), 'typing.TypeVar', 'TypeVar', (['"""IndexType"""'], {'bound': '"""BaseIndex"""'}),... |
import json
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import (
DEFAULT_TEMPERATURE,
)
from llama_index.legacy.core.llms.types import (
Ch... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.generic_utils.stream_completion_response_to_chat_response",
"llama_index.legacy.... | [((1084, 1145), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The modelId of the Bedrock model to use."""'}), "(description='The modelId of the Bedrock model to use.')\n", (1089, 1145), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1171, 1228), 'llama_i... |
import json
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import (
DEFAULT_TEMPERATURE,
)
from llama_index.legacy.core.llms.types import (
Ch... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.generic_utils.stream_completion_response_to_chat_response",
"llama_index.legacy.... | [((1084, 1145), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The modelId of the Bedrock model to use."""'}), "(description='The modelId of the Bedrock model to use.')\n", (1089, 1145), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((1171, 1228), 'llama_i... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset(
"BraintrustCodaHelpDesk... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 344), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""BraintrustCodaHelpDeskDataset"""', '"""./braintrust_codahdd"""'], {}), "('BraintrustCodaHelpDeskDataset', './braintrust_codahdd')\n", (287, 344), False, 'from llama_index.core.llama_dataset import download_llama_datas... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset(
"BraintrustCodaHelpDesk... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 344), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""BraintrustCodaHelpDeskDataset"""', '"""./braintrust_codahdd"""'], {}), "('BraintrustCodaHelpDeskDataset', './braintrust_codahdd')\n", (287, 344), False, 'from llama_index.core.llama_dataset import download_llama_datas... |
from typing import Any, Dict, Optional
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.constants import (
DEFAULT_NUM_OUTPUTS,
DEFAULT_TEMPERATURE,
)
from llama_index.legacy.core.llms.types import LLMMetadata
from llama_index.legacy.llms.generic_utils import get_from_param_or_env
f... | [
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.generic_utils.get_from_param_or_env"
] | [((548, 659), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The Neutrino router to use. See https://docs.neutrinoapp.com/router for details."""'}), "(description=\n 'The Neutrino router to use. See https://docs.neutrinoapp.com/router for details.'\n )\n", (553, 659), False, 'from l... |
"""Tree-based index."""
from enum import Enum
from typing import Any, Dict, Optional, Sequence, Union
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.embeddings.base import BaseEmbedding
# from llama_index.core.data_structs.data_structs import IndexGraph
from llama_index.cor... | [
"llama_index.core.settings.llm_from_settings_or_context",
"llama_index.core.indices.tree.tree_root_retriever.TreeRootRetriever",
"llama_index.core.indices.tree.select_leaf_retriever.TreeSelectLeafRetriever",
"llama_index.core.indices.tree.inserter.TreeIndexInserter",
"llama_index.core.indices.tree.select_le... | [((5992, 6202), 'llama_index.core.indices.common_tree.base.GPTTreeIndexBuilder', 'GPTTreeIndexBuilder', (['self.num_children', 'self.summary_template'], {'service_context': 'self.service_context', 'llm': 'self._llm', 'use_async': 'self._use_async', 'show_progress': 'self._show_progress', 'docstore': 'self._docstore'}),... |
"""Tree-based index."""
from enum import Enum
from typing import Any, Dict, Optional, Sequence, Union
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.embeddings.base import BaseEmbedding
# from llama_index.core.data_structs.data_structs import IndexGraph
from llama_index.cor... | [
"llama_index.core.settings.llm_from_settings_or_context",
"llama_index.core.indices.tree.tree_root_retriever.TreeRootRetriever",
"llama_index.core.indices.tree.select_leaf_retriever.TreeSelectLeafRetriever",
"llama_index.core.indices.tree.inserter.TreeIndexInserter",
"llama_index.core.indices.tree.select_le... | [((5992, 6202), 'llama_index.core.indices.common_tree.base.GPTTreeIndexBuilder', 'GPTTreeIndexBuilder', (['self.num_children', 'self.summary_template'], {'service_context': 'self.service_context', 'llm': 'self._llm', 'use_async': 'self._use_async', 'show_progress': 'self._show_progress', 'docstore': 'self._docstore'}),... |
"""Tree-based index."""
from enum import Enum
from typing import Any, Dict, Optional, Sequence, Union
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.base.embeddings.base import BaseEmbedding
# from llama_index.core.data_structs.data_structs import IndexGraph
from llama_index.cor... | [
"llama_index.core.settings.llm_from_settings_or_context",
"llama_index.core.indices.tree.tree_root_retriever.TreeRootRetriever",
"llama_index.core.indices.tree.select_leaf_retriever.TreeSelectLeafRetriever",
"llama_index.core.indices.tree.inserter.TreeIndexInserter",
"llama_index.core.indices.tree.select_le... | [((5992, 6202), 'llama_index.core.indices.common_tree.base.GPTTreeIndexBuilder', 'GPTTreeIndexBuilder', (['self.num_children', 'self.summary_template'], {'service_context': 'self.service_context', 'llm': 'self._llm', 'use_async': 'self._use_async', 'show_progress': 'self._show_progress', 'docstore': 'self._docstore'}),... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
Co... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.core.llms.types.ChatMessage",... | [((762, 827), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': 'f"""Full URL of the model. e.g. `{EXAMPLE_URL}`"""'}), "(description=f'Full URL of the model. e.g. `{EXAMPLE_URL}`')\n", (767, 827), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((880, 918), 'llama... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
Co... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.core.llms.types.ChatMessage",... | [((762, 827), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': 'f"""Full URL of the model. e.g. `{EXAMPLE_URL}`"""'}), "(description=f'Full URL of the model. e.g. `{EXAMPLE_URL}`')\n", (767, 827), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((880, 918), 'llama... |
"""PII postprocessor."""
import json
from copy import deepcopy
from typing import Callable, Dict, List, Optional, Tuple
from llama_index.core.llms.llm import LLM
from llama_index.core.postprocessor.types import BaseNodePostprocessor
from llama_index.core.prompts.base import PromptTemplate
from llama_index.core.schema ... | [
"llama_index.core.prompts.base.PromptTemplate",
"llama_index.core.schema.NodeWithScore"
] | [((2092, 2125), 'llama_index.core.prompts.base.PromptTemplate', 'PromptTemplate', (['self.pii_str_tmpl'], {}), '(self.pii_str_tmpl)\n', (2106, 2125), False, 'from llama_index.core.prompts.base import PromptTemplate\n'), ((2560, 2587), 'json.loads', 'json.loads', (['json_str_output'], {}), '(json_str_output)\n', (2570, ... |
"""PII postprocessor."""
import json
from copy import deepcopy
from typing import Callable, Dict, List, Optional, Tuple
from llama_index.core.llms.llm import LLM
from llama_index.core.postprocessor.types import BaseNodePostprocessor
from llama_index.core.prompts.base import PromptTemplate
from llama_index.core.schema ... | [
"llama_index.core.prompts.base.PromptTemplate",
"llama_index.core.schema.NodeWithScore"
] | [((2092, 2125), 'llama_index.core.prompts.base.PromptTemplate', 'PromptTemplate', (['self.pii_str_tmpl'], {}), '(self.pii_str_tmpl)\n', (2106, 2125), False, 'from llama_index.core.prompts.base import PromptTemplate\n'), ((2560, 2587), 'json.loads', 'json.loads', (['json_str_output'], {}), '(json_str_output)\n', (2570, ... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_NUM_OUTPUTS, DEFAULT_TEMPERATURE
from llama_index.legacy.core.llms.types import ChatMessage, LLMMetadata
from llama_index.legacy.llms.everlyai_utils impor... | [
"llama_index.legacy.callbacks.CallbackManager",
"llama_index.legacy.llms.generic_utils.get_from_param_or_env",
"llama_index.legacy.llms.everlyai_utils.everlyai_modelname_to_contextsize"
] | [((1525, 1586), 'llama_index.legacy.llms.generic_utils.get_from_param_or_env', 'get_from_param_or_env', (['"""api_key"""', 'api_key', '"""EverlyAI_API_KEY"""'], {}), "('api_key', api_key, 'EverlyAI_API_KEY')\n", (1546, 1586), False, 'from llama_index.legacy.llms.generic_utils import get_from_param_or_env\n'), ((1486, 1... |
"""txtai reader."""
from typing import Any, Dict, List
import numpy as np
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
class TxtaiReader(BaseReader):
"""txtai reader.
Retrieves documents through an existing in-memory txtai index.
These documents... | [
"llama_index.legacy.schema.Document"
] | [((2425, 2444), 'llama_index.legacy.schema.Document', 'Document', ([], {'text': 'text'}), '(text=text)\n', (2433, 2444), False, 'from llama_index.legacy.schema import Document\n'), ((2194, 2213), 'llama_index.legacy.schema.Document', 'Document', ([], {'text': 'text'}), '(text=text)\n', (2202, 2213), False, 'from llama_... |
"""txtai reader."""
from typing import Any, Dict, List
import numpy as np
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
class TxtaiReader(BaseReader):
"""txtai reader.
Retrieves documents through an existing in-memory txtai index.
These documents... | [
"llama_index.legacy.schema.Document"
] | [((2425, 2444), 'llama_index.legacy.schema.Document', 'Document', ([], {'text': 'text'}), '(text=text)\n', (2433, 2444), False, 'from llama_index.legacy.schema import Document\n'), ((2194, 2213), 'llama_index.legacy.schema.Document', 'Document', ([], {'text': 'text'}), '(text=text)\n', (2202, 2213), False, 'from llama_... |
from llama_index.core.prompts.base import PromptTemplate
from llama_index.core.prompts.prompt_type import PromptType
"""Single select prompt.
PromptTemplate to select one out of `num_choices` options provided in `context_list`,
given a query `query_str`.
Required template variables: `num_chunks`, `context_list`, `qu... | [
"llama_index.core.prompts.base.PromptTemplate"
] | [((1156, 1257), 'llama_index.core.prompts.base.PromptTemplate', 'PromptTemplate', ([], {'template': 'DEFAULT_SINGLE_SELECT_PROMPT_TMPL', 'prompt_type': 'PromptType.SINGLE_SELECT'}), '(template=DEFAULT_SINGLE_SELECT_PROMPT_TMPL, prompt_type=\n PromptType.SINGLE_SELECT)\n', (1170, 1257), False, 'from llama_index.core.... |
from llama_index.core.prompts.base import PromptTemplate
from llama_index.core.prompts.prompt_type import PromptType
"""Single select prompt.
PromptTemplate to select one out of `num_choices` options provided in `context_list`,
given a query `query_str`.
Required template variables: `num_chunks`, `context_list`, `qu... | [
"llama_index.core.prompts.base.PromptTemplate"
] | [((1156, 1257), 'llama_index.core.prompts.base.PromptTemplate', 'PromptTemplate', ([], {'template': 'DEFAULT_SINGLE_SELECT_PROMPT_TMPL', 'prompt_type': 'PromptType.SINGLE_SELECT'}), '(template=DEFAULT_SINGLE_SELECT_PROMPT_TMPL, prompt_type=\n PromptType.SINGLE_SELECT)\n', (1170, 1257), False, 'from llama_index.core.... |
from llama_index.core.prompts.base import PromptTemplate
from llama_index.core.prompts.prompt_type import PromptType
"""Single select prompt.
PromptTemplate to select one out of `num_choices` options provided in `context_list`,
given a query `query_str`.
Required template variables: `num_chunks`, `context_list`, `qu... | [
"llama_index.core.prompts.base.PromptTemplate"
] | [((1156, 1257), 'llama_index.core.prompts.base.PromptTemplate', 'PromptTemplate', ([], {'template': 'DEFAULT_SINGLE_SELECT_PROMPT_TMPL', 'prompt_type': 'PromptType.SINGLE_SELECT'}), '(template=DEFAULT_SINGLE_SELECT_PROMPT_TMPL, prompt_type=\n PromptType.SINGLE_SELECT)\n', (1170, 1257), False, 'from llama_index.core.... |
"""Awadb reader."""
from typing import Any, List
import numpy as np
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
class AwadbReader(BaseReader):
"""Awadb reader.
Retrieves documents through an existing awadb client.
These documents ... | [
"llama_index.legacy.schema.Document"
] | [((1780, 1824), 'llama_index.legacy.schema.Document', 'Document', ([], {'text': "item_detail['embedding_text']"}), "(text=item_detail['embedding_text'])\n", (1788, 1824), False, 'from llama_index.legacy.schema import Document\n'), ((2042, 2061), 'llama_index.legacy.schema.Document', 'Document', ([], {'text': 'text'}), ... |
"""Mongo client."""
from typing import Dict, Iterable, List, Optional, Union
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
class SimpleMongoReader(BaseReader):
"""Simple mongo reader.
Concatenates each Mongo doc into Document used by LlamaIndex.
... | [
"llama_index.legacy.schema.Document"
] | [((887, 903), 'pymongo.MongoClient', 'MongoClient', (['uri'], {}), '(uri)\n', (898, 903), False, 'from pymongo import MongoClient\n'), ((953, 976), 'pymongo.MongoClient', 'MongoClient', (['host', 'port'], {}), '(host, port)\n', (964, 976), False, 'from pymongo import MongoClient\n'), ((3133, 3152), 'llama_index.legacy.... |
"""Mongo client."""
from typing import Dict, Iterable, List, Optional, Union
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
class SimpleMongoReader(BaseReader):
"""Simple mongo reader.
Concatenates each Mongo doc into Document used by LlamaIndex.
... | [
"llama_index.legacy.schema.Document"
] | [((887, 903), 'pymongo.MongoClient', 'MongoClient', (['uri'], {}), '(uri)\n', (898, 903), False, 'from pymongo import MongoClient\n'), ((953, 976), 'pymongo.MongoClient', 'MongoClient', (['host', 'port'], {}), '(host, port)\n', (964, 976), False, 'from pymongo import MongoClient\n'), ((3133, 3152), 'llama_index.legacy.... |
from typing import Any, Callable, Optional, Sequence
from typing_extensions import override
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types im... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.bridge.pydantic.PrivateAttr"
] | [((660, 673), 'llama_index.legacy.bridge.pydantic.PrivateAttr', 'PrivateAttr', ([], {}), '()\n', (671, 673), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((687, 700), 'llama_index.legacy.bridge.pydantic.PrivateAttr', 'PrivateAttr', ([], {}), '()\n', (698, 700), False, 'from llama_index... |
from typing import Any, Callable, Optional, Sequence
from typing_extensions import override
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types im... | [
"llama_index.legacy.core.llms.types.CompletionResponse",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.bridge.pydantic.PrivateAttr"
] | [((660, 673), 'llama_index.legacy.bridge.pydantic.PrivateAttr', 'PrivateAttr', ([], {}), '()\n', (671, 673), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((687, 700), 'llama_index.legacy.bridge.pydantic.PrivateAttr', 'PrivateAttr', ([], {}), '()\n', (698, 700), False, 'from llama_index... |
from typing import Dict, Type
from llama_index.core.base.embeddings.base import BaseEmbedding
from llama_index.core.embeddings.mock_embed_model import MockEmbedding
RECOGNIZED_EMBEDDINGS: Dict[str, Type[BaseEmbedding]] = {
MockEmbedding.class_name(): MockEmbedding,
}
# conditionals for llama-cloud support
try:
... | [
"llama_index.core.embeddings.mock_embed_model.MockEmbedding.class_name",
"llama_index.embeddings.huggingface.HuggingFaceInferenceAPIEmbedding.class_name",
"llama_index.embeddings.openai.OpenAIEmbedding.class_name",
"llama_index.embeddings.azure_openai.AzureOpenAIEmbedding.class_name"
] | [((229, 255), 'llama_index.core.embeddings.mock_embed_model.MockEmbedding.class_name', 'MockEmbedding.class_name', ([], {}), '()\n', (253, 255), False, 'from llama_index.core.embeddings.mock_embed_model import MockEmbedding\n'), ((431, 459), 'llama_index.embeddings.openai.OpenAIEmbedding.class_name', 'OpenAIEmbedding.c... |
from typing import Dict, Type
from llama_index.core.base.embeddings.base import BaseEmbedding
from llama_index.core.embeddings.mock_embed_model import MockEmbedding
RECOGNIZED_EMBEDDINGS: Dict[str, Type[BaseEmbedding]] = {
MockEmbedding.class_name(): MockEmbedding,
}
# conditionals for llama-cloud support
try:
... | [
"llama_index.core.embeddings.mock_embed_model.MockEmbedding.class_name",
"llama_index.embeddings.huggingface.HuggingFaceInferenceAPIEmbedding.class_name",
"llama_index.embeddings.openai.OpenAIEmbedding.class_name",
"llama_index.embeddings.azure_openai.AzureOpenAIEmbedding.class_name"
] | [((229, 255), 'llama_index.core.embeddings.mock_embed_model.MockEmbedding.class_name', 'MockEmbedding.class_name', ([], {}), '()\n', (253, 255), False, 'from llama_index.core.embeddings.mock_embed_model import MockEmbedding\n'), ((431, 459), 'llama_index.embeddings.openai.OpenAIEmbedding.class_name', 'OpenAIEmbedding.c... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core.evaluation import CorrectnessEvaluator
from llama_index.llms import OpenAI, Gemini
from llama_index.core import ServiceContext
import pandas as pd
async d... | [
"llama_index.llms.Gemini",
"llama_index.core.evaluation.CorrectnessEvaluator",
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.llms.OpenAI"
] | [((386, 471), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""MiniMtBenchSingleGradingDataset"""', '"""./mini_mt_bench_data"""'], {}), "('MiniMtBenchSingleGradingDataset',\n './mini_mt_bench_data')\n", (408, 471), False, 'from llama_index.core.llama_dataset import download_ll... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset(
"PaulGrahamEssayDataset... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 330), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""PaulGrahamEssayDataset"""', '"""./paul_graham"""'], {}), "('PaulGrahamEssayDataset', './paul_graham')\n", (287, 330), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((389, 441), 'llama_... |
import asyncio
from llama_index.core.llama_dataset import download_llama_dataset
from llama_index.core.llama_pack import download_llama_pack
from llama_index.core import VectorStoreIndex
async def main():
# DOWNLOAD LLAMADATASET
rag_dataset, documents = download_llama_dataset(
"PaulGrahamEssayDataset... | [
"llama_index.core.llama_dataset.download_llama_dataset",
"llama_index.core.llama_pack.download_llama_pack",
"llama_index.core.VectorStoreIndex.from_documents"
] | [((265, 330), 'llama_index.core.llama_dataset.download_llama_dataset', 'download_llama_dataset', (['"""PaulGrahamEssayDataset"""', '"""./paul_graham"""'], {}), "('PaulGrahamEssayDataset', './paul_graham')\n", (287, 330), False, 'from llama_index.core.llama_dataset import download_llama_dataset\n'), ((389, 441), 'llama_... |
from typing import TYPE_CHECKING, Any, Optional
from llama_index.core.base.base_query_engine import BaseQueryEngine
if TYPE_CHECKING:
from llama_index.core.langchain_helpers.agents.tools import (
LlamaIndexTool,
)
from llama_index.core.tools.types import AsyncBaseTool, ToolMetadata, ToolOutput
DEFAUL... | [
"llama_index.core.langchain_helpers.agents.tools.LlamaIndexTool.from_tool_config",
"llama_index.core.langchain_helpers.agents.tools.IndexToolConfig",
"llama_index.core.tools.types.ToolMetadata"
] | [((1402, 1450), 'llama_index.core.tools.types.ToolMetadata', 'ToolMetadata', ([], {'name': 'name', 'description': 'description'}), '(name=name, description=description)\n', (1414, 1450), False, 'from llama_index.core.tools.types import AsyncBaseTool, ToolMetadata, ToolOutput\n'), ((3560, 3675), 'llama_index.core.langch... |
from typing import TYPE_CHECKING, Any, Optional
from llama_index.core.base.base_query_engine import BaseQueryEngine
if TYPE_CHECKING:
from llama_index.core.langchain_helpers.agents.tools import (
LlamaIndexTool,
)
from llama_index.core.tools.types import AsyncBaseTool, ToolMetadata, ToolOutput
DEFAUL... | [
"llama_index.core.langchain_helpers.agents.tools.LlamaIndexTool.from_tool_config",
"llama_index.core.langchain_helpers.agents.tools.IndexToolConfig",
"llama_index.core.tools.types.ToolMetadata"
] | [((1402, 1450), 'llama_index.core.tools.types.ToolMetadata', 'ToolMetadata', ([], {'name': 'name', 'description': 'description'}), '(name=name, description=description)\n', (1414, 1450), False, 'from llama_index.core.tools.types import AsyncBaseTool, ToolMetadata, ToolOutput\n'), ((3560, 3675), 'llama_index.core.langch... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatRe... | [
"llama_index.legacy.llms.openai_utils.from_openai_message_dict",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.bridge.pydantic.Priva... | [((868, 916), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The llama-api model to use."""'}), "(description='The llama-api model to use.')\n", (873, 916), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((942, 999), 'llama_index.legacy.bridge.pydantic.Fiel... |
from typing import Any, Callable, Dict, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatRe... | [
"llama_index.legacy.llms.openai_utils.from_openai_message_dict",
"llama_index.legacy.llms.base.llm_chat_callback",
"llama_index.legacy.bridge.pydantic.Field",
"llama_index.legacy.core.llms.types.LLMMetadata",
"llama_index.legacy.llms.base.llm_completion_callback",
"llama_index.legacy.bridge.pydantic.Priva... | [((868, 916), 'llama_index.legacy.bridge.pydantic.Field', 'Field', ([], {'description': '"""The llama-api model to use."""'}), "(description='The llama-api model to use.')\n", (873, 916), False, 'from llama_index.legacy.bridge.pydantic import Field, PrivateAttr\n'), ((942, 999), 'llama_index.legacy.bridge.pydantic.Fiel... |
"""Download tool from Llama Hub."""
from typing import Optional, Type
from llama_index.legacy.download.module import (
LLAMA_HUB_URL,
MODULE_TYPE,
download_llama_module,
track_download,
)
from llama_index.legacy.tools.tool_spec.base import BaseToolSpec
def download_tool(
tool_class: str,
lla... | [
"llama_index.legacy.download.module.download_llama_module",
"llama_index.legacy.download.module.track_download"
] | [((867, 1047), 'llama_index.legacy.download.module.download_llama_module', 'download_llama_module', (['tool_class'], {'llama_hub_url': 'llama_hub_url', 'refresh_cache': 'refresh_cache', 'custom_dir': '"""tools"""', 'custom_path': 'custom_path', 'library_path': '"""tools/library.json"""'}), "(tool_class, llama_hub_url=l... |
"""Simple Engine."""
import json
import os
from typing import Any, Optional, Union
from llama_index.core import SimpleDirectoryReader, VectorStoreIndex
from llama_index.core.callbacks.base import CallbackManager
from llama_index.core.embeddings import BaseEmbedding
from llama_index.core.embeddings.mock_embed_model im... | [
"llama_index.core.node_parser.SentenceSplitter",
"llama_index.core.embeddings.mock_embed_model.MockEmbedding",
"llama_index.core.response_synthesizers.get_response_synthesizer",
"llama_index.core.ingestion.pipeline.run_transformations",
"llama_index.core.SimpleDirectoryReader",
"llama_index.core.schema.Qu... | [((7145, 7220), 'llama_index.core.ingestion.pipeline.run_transformations', 'run_transformations', (['documents'], {'transformations': 'self.index._transformations'}), '(documents, transformations=self.index._transformations)\n', (7164, 7220), False, 'from llama_index.core.ingestion.pipeline import run_transformations\n... |
import os
from typing import Optional, Dict
import openai
import pandas as pd
import llama_index
from llama_index.llms.openai import OpenAI
from llama_index.readers.schema.base import Document
from llama_index.readers import SimpleWebPageReader
from llama_index.prompts import PromptTemplate
from llama_index import Se... | [
"llama_index.OpenAIEmbedding",
"llama_index.ServiceContext.from_defaults",
"llama_index.StorageContext.from_defaults",
"llama_index.prompts.PromptTemplate",
"llama_index.readers.schema.base.Document",
"llama_index.readers.SimpleWebPageReader",
"llama_index.load_index_from_storage",
"llama_index.llms.o... | [((9647, 9699), 'llama_index.StorageContext.from_defaults', 'StorageContext.from_defaults', ([], {'persist_dir': 'index_path'}), '(persist_dir=index_path)\n', (9675, 9699), False, 'from llama_index import ServiceContext, StorageContext, load_index_from_storage\n'), ((9770, 9843), 'llama_index.load_index_from_storage', ... |
# SPDX-FileCopyrightText: Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: MIT
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without res... | [
"llama_index.llms.base.LLMMetadata",
"llama_index.bridge.pydantic.Field",
"llama_index.llms.base.llm_completion_callback",
"llama_index.bridge.pydantic.PrivateAttr",
"llama_index.llms.base.llm_chat_callback",
"llama_index.llms.generic_utils.completion_response_to_chat_response"
] | [((2151, 2199), 'llama_index.bridge.pydantic.Field', 'Field', ([], {'description': '"""The path to the trt engine."""'}), "(description='The path to the trt engine.')\n", (2156, 2199), False, 'from llama_index.bridge.pydantic import Field, PrivateAttr\n'), ((2239, 2296), 'llama_index.bridge.pydantic.Field', 'Field', ([... |
from llama_index.core.callbacks.schema import CBEventType, EventPayload
from llama_index.core.llms import ChatMessage, ChatResponse
from llama_index.core.schema import NodeWithScore, TextNode
import chainlit as cl
@cl.on_chat_start
async def start():
await cl.Message(content="LlamaIndexCb").send()
cb = cl.L... | [
"llama_index.core.schema.TextNode",
"llama_index.core.llms.ChatMessage"
] | [((316, 346), 'chainlit.LlamaIndexCallbackHandler', 'cl.LlamaIndexCallbackHandler', ([], {}), '()\n', (344, 346), True, 'import chainlit as cl\n'), ((415, 428), 'chainlit.sleep', 'cl.sleep', (['(0.2)'], {}), '(0.2)\n', (423, 428), True, 'import chainlit as cl\n'), ((691, 704), 'chainlit.sleep', 'cl.sleep', (['(0.2)'], ... |
import requests
from bs4 import BeautifulSoup
from llama_index import GPTSimpleVectorIndex
from llama_index.readers.database import DatabaseReader
from env import settings
from logger import logger
from .base import BaseToolSet, SessionGetter, ToolScope, tool
class RequestsGet(BaseToolSet):
@tool(
name=... | [
"llama_index.readers.database.DatabaseReader",
"llama_index.GPTSimpleVectorIndex"
] | [((713, 732), 'bs4.BeautifulSoup', 'BeautifulSoup', (['html'], {}), '(html)\n', (726, 732), False, 'from bs4 import BeautifulSoup\n'), ((1073, 1166), 'logger.logger.debug', 'logger.debug', (['f"""\nProcessed RequestsGet, Input Url: {url} Output Contents: {content}"""'], {}), '(\n f"""\nProcessed RequestsGet, Input U... |
try:
from llama_index import Document
from llama_index.text_splitter import SentenceSplitter
except ImportError:
from llama_index.core import Document
from llama_index.core.text_splitter import SentenceSplitter
def llama_index_sentence_splitter(
documents: list[str], document_ids: list[str], chunk... | [
"llama_index.core.text_splitter.SentenceSplitter",
"llama_index.core.Document"
] | [((432, 500), 'llama_index.core.text_splitter.SentenceSplitter', 'SentenceSplitter', ([], {'chunk_size': 'chunk_size', 'chunk_overlap': 'chunk_overlap'}), '(chunk_size=chunk_size, chunk_overlap=chunk_overlap)\n', (448, 500), False, 'from llama_index.core.text_splitter import SentenceSplitter\n'), ((514, 532), 'llama_in... |
"""
Creates RAG dataset for tutorial notebooks and persists to disk.
"""
import argparse
import logging
import sys
from typing import List, Optional
import llama_index
import numpy as np
import pandas as pd
from gcsfs import GCSFileSystem
from llama_index import ServiceContext, StorageContext, load_index_from_storage... | [
"llama_index.callbacks.OpenInferenceCallbackHandler",
"llama_index.StorageContext.from_defaults",
"llama_index.llms.OpenAI",
"llama_index.load_index_from_storage",
"llama_index.callbacks.CallbackManager",
"llama_index.embeddings.openai.OpenAIEmbedding"
] | [((1235, 1270), 'numpy.array', 'np.array', (['first_document_relevances'], {}), '(first_document_relevances)\n', (1243, 1270), True, 'import numpy as np\n'), ((1310, 1346), 'numpy.array', 'np.array', (['second_document_relevances'], {}), '(second_document_relevances)\n', (1318, 1346), True, 'import numpy as np\n'), ((1... |
import logging
import os
import time
import typing
import uuid
from typing import TYPE_CHECKING, Any, Iterable, List, Optional
import numpy as np
from llama_index.core.schema import BaseNode, MetadataMode, TextNode
from llama_index.core.vector_stores.types import (
VectorStore,
VectorStoreQuery,
VectorSto... | [
"llama_index.core.vector_stores.types.VectorStoreQueryResult",
"llama_index.core.vector_stores.utils.node_to_metadata_dict",
"llama_index.core.vector_stores.utils.metadata_dict_to_node",
"llama_index.core.vector_stores.utils.legacy_metadata_dict_to_node"
] | [((524, 551), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (541, 551), False, 'import logging\n'), ((8582, 8767), 'vearch.GammaVectorInfo', 'vearch.GammaVectorInfo', ([], {'name': '"""text_embedding"""', 'type': 'vearch.dataType.VECTOR', 'is_index': '(True)', 'dimension': 'dim', 'model_... |
# ENTER YOUR OPENAPI KEY IN OPENAI_API_KEY ENV VAR FIRST
from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader, LLMPredictor, download_loader
savePath = f'/{os.path.dirname(__file__)}/indexes/index.json'
#
# index = GPTSimpleVectorIndex(documents)#, llm_predictor=llm_predictor)
index = GPTSimpleVectorIn... | [
"llama_index.GPTSimpleVectorIndex.load_from_disk"
] | [((303, 348), 'llama_index.GPTSimpleVectorIndex.load_from_disk', 'GPTSimpleVectorIndex.load_from_disk', (['savePath'], {}), '(savePath)\n', (338, 348), False, 'from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader, LLMPredictor, download_loader\n')] |
from typing import Optional, Union
from llama_index import ServiceContext
from llama_index.callbacks import CallbackManager
from llama_index.embeddings.utils import EmbedType
from llama_index.extractors import (
EntityExtractor,
KeywordExtractor,
QuestionsAnsweredExtractor,
SummaryExtractor,
TitleE... | [
"llama_index.extractors.TitleExtractor",
"llama_index.extractors.QuestionsAnsweredExtractor",
"llama_index.ServiceContext.from_defaults",
"llama_index.prompts.PromptTemplate",
"llama_index.extractors.SummaryExtractor",
"llama_index.extractors.EntityExtractor",
"llama_index.extractors.KeywordExtractor",
... | [((3952, 4020), 'llama_index.text_splitter.SentenceSplitter', 'SentenceSplitter', ([], {'chunk_size': 'chunk_size', 'chunk_overlap': 'chunk_overlap'}), '(chunk_size=chunk_size, chunk_overlap=chunk_overlap)\n', (3968, 4020), False, 'from llama_index.text_splitter import SentenceSplitter\n'), ((4643, 4954), 'llama_index.... |
from rag.agents.interface import Pipeline
from llama_index.core.program import LLMTextCompletionProgram
import json
from llama_index.llms.ollama import Ollama
from typing import List
from pydantic import create_model
from rich.progress import Progress, SpinnerColumn, TextColumn
import requests
import warnings
import bo... | [
"llama_index.core.program.LLMTextCompletionProgram.from_defaults",
"llama_index.llms.ollama.Ollama"
] | [((396, 458), 'warnings.filterwarnings', 'warnings.filterwarnings', (['"""ignore"""'], {'category': 'DeprecationWarning'}), "('ignore', category=DeprecationWarning)\n", (419, 458), False, 'import warnings\n'), ((459, 514), 'warnings.filterwarnings', 'warnings.filterwarnings', (['"""ignore"""'], {'category': 'UserWarnin... |
import asyncio
import chromadb
import os
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, StorageContext
from llama_index.vector_stores.chroma import ChromaVectorStore
from llama_index.embeddings.huggingface import HuggingFaceEmbedding
from traceloop.sdk import Traceloop
os.environ["TOKENIZERS_P... | [
"llama_index.core.StorageContext.from_defaults",
"llama_index.embeddings.huggingface.HuggingFaceEmbedding",
"llama_index.core.VectorStoreIndex.from_documents",
"llama_index.vector_stores.chroma.ChromaVectorStore",
"llama_index.core.SimpleDirectoryReader"
] | [((344, 390), 'traceloop.sdk.Traceloop.init', 'Traceloop.init', ([], {'app_name': '"""llama_index_example"""'}), "(app_name='llama_index_example')\n", (358, 390), False, 'from traceloop.sdk import Traceloop\n'), ((408, 434), 'chromadb.EphemeralClient', 'chromadb.EphemeralClient', ([], {}), '()\n', (432, 434), False, 'i... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ================================================== #
# This file is a part of PYGPT package #
# Website: https://pygpt.net #
# GitHub: https://github.com/szczyglis-dev/py-gpt #
# MIT License ... | [
"llama_index.core.StorageContext.from_defaults",
"llama_index.core.load_index_from_storage"
] | [((3275, 3321), 'llama_index.core.StorageContext.from_defaults', 'StorageContext.from_defaults', ([], {'persist_dir': 'path'}), '(persist_dir=path)\n', (3303, 3321), False, 'from llama_index.core import StorageContext, load_index_from_storage\n'), ((3384, 3457), 'llama_index.core.load_index_from_storage', 'load_index_f... |
import streamlit as st
from sqlalchemy import create_engine, inspect, text
from typing import Dict, Any
from llama_index import (
VectorStoreIndex,
ServiceContext,
download_loader,
)
from llama_index.llama_pack.base import BaseLlamaPack
from llama_index.llms import OpenAI
import openai
import os
import pan... | [
"llama_index.llms.OpenAI",
"llama_index.ServiceContext.from_defaults",
"llama_index.indices.struct_store.NLSQLTableQueryEngine",
"llama_index.SQLDatabase"
] | [((1194, 1309), 'streamlit.set_page_config', 'st.set_page_config', ([], {'page_title': 'f"""{self.page}"""', 'layout': '"""centered"""', 'initial_sidebar_state': '"""auto"""', 'menu_items': 'None'}), "(page_title=f'{self.page}', layout='centered',\n initial_sidebar_state='auto', menu_items=None)\n", (1212, 1309), Tr... |
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