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Update poetry lock (#1209) 

* Update the version of llama_index used to fix transient openai errors

* Update poetry.lock file

* Make `local` mode the default mode by default
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lopagela 2023-11-11 22:44:19 +01:00 committed by GitHub
parent a22969ad1f
commit a579c9bdc5
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14 changed files with 313 additions and 268 deletions
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@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.7.0 and should not be changed by hand.
[[package]]
name = "aiofiles"
@ -133,6 +133,20 @@ files = [
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frozenlist = ">=1.1.0"
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version = "0.5.2"
description = "Generator-based operators for asynchronous iteration"
optional = false
python-versions = ">=3.8"
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typing-extensions = "*"
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name = "altair"
version = "5.1.2"
@ -296,17 +310,17 @@ uvloop = ["uvloop (>=0.15.2)"]
[[package]]
name = "boto3"
version = "1.28.78"
version = "1.28.84"
description = "The AWS SDK for Python"
optional = false
python-versions = ">= 3.7"
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jmespath = ">=0.7.1,<2.0.0"
s3transfer = ">=0.7.0,<0.8.0"
@ -315,13 +329,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
[[package]]
name = "botocore"
version = "1.31.78"
version = "1.31.84"
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@ -330,7 +344,7 @@ python-dateutil = ">=2.1,<3.0.0"
urllib3 = {version = ">=1.25.4,<2.1", markers = "python_version >= \"3.10\""}
[package.extras]
crt = ["awscrt (==0.16.26)"]
crt = ["awscrt (==0.19.10)"]
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name = "cachetools"
@ -503,13 +517,13 @@ numpy = "*"
[[package]]
name = "chromadb"
version = "0.4.15"
version = "0.4.17"
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pydantic = ">=1.9"
pypika = ">=0.48.9"
PyYAML = ">=6.0.0"
requests = ">=2.28"
tenacity = ">=8.2.3"
tokenizers = ">=0.13.2"
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@ -1326,13 +1352,13 @@ files = [
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version = "1.0.2"
description = "A minimal low-level HTTP client."
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@ -1510,13 +1536,13 @@ testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs
[[package]]
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@ -1799,13 +1825,13 @@ adal = ["adal (>=1.0.2)"]
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description = "Building applications with LLMs through composability"
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dataclasses-json = ">=0.5.7,<0.7"
jsonpatch = ">=1.33,<2.0"
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langsmith = ">=0.0.62,<0.1.0"
numpy = ">=1,<2"
pydantic = ">=1,<3"
PyYAML = ">=5.3"
@ -1838,13 +1864,13 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
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version = "0.0.57"
version = "0.0.63"
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
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]
[[package]]
@ -5294,4 +5323,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
[metadata]
lock-version = "2.0"
python-versions = ">=3.11,<3.12"
content-hash = "2e11477e0b1a37de6711a1962d37b04f57760ab892815b46d089ae9e63cfd6d7"
content-hash = "3ea28113b04a06b1dfcbe6f43cdce086b596c714a53c10eb6501ab0c5d464412"

4
private_gpt/components/vector_store/batched_chroma.py
View File

@ -44,12 +44,12 @@ class BatchedChromaVectorStore(ChromaVectorStore):
)
self.chroma_client = chroma_client
def add(self, nodes: list[BaseNode]) -> list[str]:
def add(self, nodes: list[BaseNode], **add_kwargs: Any) -> list[str]:
"""Add nodes to index, batching the insertion to avoid issues.
Args:
nodes: List[BaseNode]: list of nodes with embeddings
add_kwargs: _
"""
if not self.chroma_client:
raise ValueError("Client not initialized")

7
private_gpt/components/vector_store/vector_store_component.py
View File

@ -46,8 +46,11 @@ class VectorStoreComponent:
"make_this_parameterizable_per_api_call"
) # TODO
self.vector_store = BatchedChromaVectorStore(
chroma_client=chroma_client, chroma_collection=chroma_collection
self.vector_store = typing.cast(
VectorStore,
BatchedChromaVectorStore(
chroma_client=chroma_client, chroma_collection=chroma_collection
),
)
@staticmethod

7
private_gpt/open_ai/openai_models.py
View File

@ -1,6 +1,7 @@
import time
import uuid
from collections.abc import Iterator
from typing import Literal
from llama_index.llms import ChatResponse, CompletionResponse
from pydantic import BaseModel, Field
@ -21,7 +22,7 @@ class OpenAIMessage(BaseModel):
(providing a default response, not AI generated).
"""
role: str = Field(default="user", enum=["assistant", "system", "user"])
role: Literal["assistant", "system", "user"] = Field(default="user")
content: str | None
@ -46,9 +47,9 @@ class OpenAICompletion(BaseModel):
"""
id: str
object: str = Field("completion", enum=["completion", "completion.chunk"])
object: Literal["completion", "completion.chunk"] = Field(default="completion")
created: int = Field(..., examples=[1623340000])
model: str = Field(enum=["private-gpt"])
model: Literal["private-gpt"]
choices: list[OpenAIChoice]
@classmethod

6
private_gpt/server/chunks/chunks_router.py
View File

@ -1,3 +1,5 @@
from typing import Literal
from fastapi import APIRouter
from pydantic import BaseModel, Field
@ -16,8 +18,8 @@ class ChunksBody(BaseModel):
class ChunksResponse(BaseModel):
object: str = Field(enum=["list"])
model: str = Field(enum=["private-gpt"])
object: Literal["list"]
model: Literal["private-gpt"]
data: list[Chunk]

4
private_gpt/server/chunks/chunks_service.py
View File

@ -1,4 +1,4 @@
from typing import TYPE_CHECKING
from typing import TYPE_CHECKING, Literal
from injector import inject, singleton
from llama_index import ServiceContext, StorageContext, VectorStoreIndex
@ -19,7 +19,7 @@ if TYPE_CHECKING:
class Chunk(BaseModel):
object: str = Field(enum=["context.chunk"])
object: Literal["context.chunk"]
score: float = Field(examples=[0.023])
document: IngestedDoc
text: str = Field(examples=["Outbound sales increased 20%, driven by new leads."])

8
private_gpt/server/embeddings/embeddings_router.py
View File

@ -1,5 +1,7 @@
from typing import Literal
from fastapi import APIRouter
from pydantic import BaseModel, Field
from pydantic import BaseModel
from private_gpt.di import root_injector
from private_gpt.server.embeddings.embeddings_service import (
@ -15,8 +17,8 @@ class EmbeddingsBody(BaseModel):
class EmbeddingsResponse(BaseModel):
object: str = Field(enum=["list"])
model: str = Field(enum=["private-gpt"])
object: Literal["list"]
model: Literal["private-gpt"]
data: list[Embedding]

4
private_gpt/server/embeddings/embeddings_service.py
View File

@ -1,3 +1,5 @@
from typing import Literal
from injector import inject, singleton
from pydantic import BaseModel, Field
@ -6,7 +8,7 @@ from private_gpt.components.embedding.embedding_component import EmbeddingCompon
class Embedding(BaseModel):
index: int
object: str = Field(enum=["embedding"])
object: Literal["embedding"]
embedding: list[float] = Field(examples=[[0.0023064255, -0.009327292]])

4
private_gpt/server/health/health_router.py
View File

@ -1,3 +1,5 @@
from typing import Literal
from fastapi import APIRouter
from pydantic import BaseModel, Field
@ -5,7 +7,7 @@ health_router = APIRouter()
class HealthResponse(BaseModel):
status: str = Field(enum=["ok"])
status: Literal["ok"] = Field(default="ok")
@health_router.get("/health", tags=["Health"])

8
private_gpt/server/ingest/ingest_router.py
View File

@ -1,5 +1,7 @@
from typing import Literal
from fastapi import APIRouter, HTTPException, UploadFile
from pydantic import BaseModel, Field
from pydantic import BaseModel
from private_gpt.di import root_injector
from private_gpt.server.ingest.ingest_service import IngestedDoc, IngestService
@ -8,8 +10,8 @@ ingest_router = APIRouter(prefix="/v1")
class IngestResponse(BaseModel):
object: str = Field(enum=["list"])
model: str = Field(enum=["private-gpt"])
object: Literal["list"]
model: Literal["private-gpt"]
data: list[IngestedDoc]

4
private_gpt/server/ingest/ingest_service.py
View File

@ -1,7 +1,7 @@
import logging
import tempfile
from pathlib import Path
from typing import TYPE_CHECKING, Any, AnyStr
from typing import TYPE_CHECKING, Any, AnyStr, Literal
from injector import inject, singleton
from llama_index import (
@ -40,7 +40,7 @@ logger = logging.getLogger(__name__)
class IngestedDoc(BaseModel):
object: str = Field(enum=["ingest.document"])
object: Literal["ingest.document"]
doc_id: str = Field(examples=["c202d5e6-7b69-4869-81cc-dd574ee8ee11"])
doc_metadata: dict[str, Any] | None = Field(
examples=[

4
private_gpt/settings/settings.py
View File

@ -1,3 +1,5 @@
from typing import Literal
from pydantic import BaseModel, Field
from private_gpt.settings.settings_loader import load_active_profiles
@ -57,7 +59,7 @@ class DataSettings(BaseModel):
class LLMSettings(BaseModel):
mode: str = Field(enum=["local", "open_ai", "sagemaker", "mock"])
mode: Literal["local", "open_ai", "sagemaker", "mock"]
class LocalSettings(BaseModel):

4
pyproject.toml
View File

@ -12,7 +12,7 @@ injector = "^0.21.0"
pyyaml = "^6.0.1"
python-multipart = "^0.0.6"
pypdf = "^3.16.2"
llama-index = "0.8.47"
llama-index = "0.8.67"
chromadb = "^0.4.13"
watchdog = "^3.0.0"
@ -138,4 +138,4 @@ asyncio_mode = "auto"
testpaths = ["tests"]
addopts = [
"--import-mode=importlib",
]
]

2
settings.yaml
View File

@ -15,7 +15,7 @@ ui:
path: /
llm:
mode: mock
mode: local
local:
llm_hf_repo_id: TheBloke/Mistral-7B-Instruct-v0.1-GGUF