.github/workflows/tests.yml

@@ -14,7 +14,7 @@ jobs:
   setup:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v3
       - uses: ./.github/workflows/actions/install_dependencies
 
   checks:
@@ -28,7 +28,7 @@ jobs:
           - ruff
           - mypy
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v3
       - uses: ./.github/workflows/actions/install_dependencies
       - name: run ${{ matrix.quality-command }}
         run: make ${{ matrix.quality-command }}
@@ -38,7 +38,7 @@ jobs:
     runs-on: ubuntu-latest
     name: test
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v3
       - uses: ./.github/workflows/actions/install_dependencies
       - name: run test
         run: make test-coverage

Dockerfile.llamacpp-cpu

@@ -1,6 +1,6 @@
 ### IMPORTANT, THIS IMAGE CAN ONLY BE RUN IN LINUX DOCKER
 ### You will run into a segfault in mac
-FROM python:3.11.6-slim-bookworm AS base
+FROM python:3.11.6-slim-bookworm as base
 
 # Install poetry
 RUN pip install pipx
@@ -20,14 +20,14 @@ RUN apt update && apt install -y \
 # https://python-poetry.org/docs/configuration/#virtualenvsin-project
 ENV POETRY_VIRTUALENVS_IN_PROJECT=true
 
-FROM base AS dependencies
+FROM base as dependencies
 WORKDIR /home/worker/app
 COPY pyproject.toml poetry.lock ./
 
 ARG POETRY_EXTRAS="ui embeddings-huggingface llms-llama-cpp vector-stores-qdrant"
 RUN poetry install --no-root --extras "${POETRY_EXTRAS}"
 
-FROM base AS app
+FROM base as app
 
 ENV PYTHONUNBUFFERED=1
 ENV PORT=8080

Dockerfile.ollama

@@ -1,4 +1,4 @@
-FROM python:3.11.6-slim-bookworm AS base
+FROM python:3.11.6-slim-bookworm as base
 
 # Install poetry
 RUN pip install pipx
@@ -10,14 +10,14 @@ ENV PATH=".venv/bin/:$PATH"
 # https://python-poetry.org/docs/configuration/#virtualenvsin-project
 ENV POETRY_VIRTUALENVS_IN_PROJECT=true
 
-FROM base AS dependencies
+FROM base as dependencies
 WORKDIR /home/worker/app
 COPY pyproject.toml poetry.lock ./
 
 ARG POETRY_EXTRAS="ui vector-stores-qdrant llms-ollama embeddings-ollama"
 RUN poetry install --no-root --extras "${POETRY_EXTRAS}"
 
-FROM base AS app
+FROM base as app
 ENV PYTHONUNBUFFERED=1
 ENV PORT=8080
 ENV APP_ENV=prod

README.md

@@ -1,6 +1,4 @@
-# PrivateGPT 
+# 🔒 PrivateGPT 📑
-
-<a href="https://trendshift.io/repositories/2601" target="_blank"><img src="https://trendshift.io/api/badge/repositories/2601" alt="imartinez%2FprivateGPT | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 
 [![Tests](https://github.com/zylon-ai/private-gpt/actions/workflows/tests.yml/badge.svg)](https://github.com/zylon-ai/private-gpt/actions/workflows/tests.yml?query=branch%3Amain)
 [![Website](https://img.shields.io/website?up_message=check%20it&down_message=down&url=https%3A%2F%2Fdocs.privategpt.dev%2F&label=Documentation)](https://docs.privategpt.dev/)

docker-compose.yaml

@@ -7,13 +7,12 @@ services:
   # Private-GPT service for the Ollama CPU and GPU modes
   # This service builds from an external Dockerfile and runs the Ollama mode.
   private-gpt-ollama:
-    image: ${PGPT_IMAGE:-zylonai/private-gpt}:${PGPT_TAG:-0.6.2}-ollama  # x-release-please-version
+    image: ${PGPT_IMAGE:-zylonai/private-gpt}${PGPT_TAG:-0.6.2}-ollama  # x-release-please-version
-    user: root
     build:
       context: .
       dockerfile: Dockerfile.ollama
     volumes:
-      - ./local_data:/home/worker/app/local_data
+      - ./local_data/:/home/worker/app/local_data
     ports:
       - "8001:8001"
     environment:
@@ -28,15 +27,11 @@ services:
       - ollama-cpu
       - ollama-cuda
       - ollama-api
-    depends_on:
-      ollama:
-        condition: service_healthy
 
   # Private-GPT service for the local mode
   # This service builds from a local Dockerfile and runs the application in local mode.
   private-gpt-llamacpp-cpu:
-    image: ${PGPT_IMAGE:-zylonai/private-gpt}:${PGPT_TAG:-0.6.2}-llamacpp-cpu # x-release-please-version
+    image: ${PGPT_IMAGE:-zylonai/private-gpt}${PGPT_TAG:-0.6.2}-llamacpp-cpu # x-release-please-version
-    user: root
     build:
       context: .
       dockerfile: Dockerfile.llamacpp-cpu
@@ -49,7 +44,7 @@ services:
     environment:
       PORT: 8001
       PGPT_PROFILES: local
-      HF_TOKEN: ${HF_TOKEN:-}
+      HF_TOKEN: ${HF_TOKEN}
     profiles:
       - llamacpp-cpu
 
@@ -61,14 +56,9 @@ services:
   # This will route requests to the Ollama service based on the profile.
   ollama:
     image: traefik:v2.10
-    healthcheck:
-      test: ["CMD", "sh", "-c", "wget -q --spider http://ollama:11434 || exit 1"]
-      interval: 10s
-      retries: 3
-      start_period: 5s
-      timeout: 5s
     ports:
-      - "8080:8080"
+      - "11435:11434"
+      - "8081:8080"
     command:
       - "--providers.file.filename=/etc/router.yml"
       - "--log.level=ERROR"
@@ -90,19 +80,15 @@ services:
   # Ollama service for the CPU mode
   ollama-cpu:
     image: ollama/ollama:latest
-    ports:
-      - "11434:11434"
     volumes:
       - ./models:/root/.ollama
     profiles:
       - ""
-      - ollama-cpu
+      - ollama
 
   # Ollama service for the CUDA mode
   ollama-cuda:
     image: ollama/ollama:latest
-    ports:
-      - "11434:11434"
     volumes:
       - ./models:/root/.ollama
     deploy:
@@ -113,4 +99,4 @@ services:
               count: 1
               capabilities: [gpu]
     profiles:
-      - ollama-cuda
+      - ollama-cuda

private_gpt/components/embedding/embedding_component.py

@@ -144,23 +144,6 @@ class EmbeddingComponent:
                     api_key=settings.gemini.api_key,
                     model_name=settings.gemini.embedding_model,
                 )
-            case "mistralai":
-                try:
-                    from llama_index.embeddings.mistralai import (  # type: ignore
-                        MistralAIEmbedding,
-                    )
-                except ImportError as e:
-                    raise ImportError(
-                        "Mistral dependencies not found, install with `poetry install --extras embeddings-mistral`"
-                    ) from e
-
-                api_key = settings.openai.api_key
-                model = settings.openai.embedding_model
-
-                self.embedding_model = MistralAIEmbedding(
-                    api_key=api_key,
-                    model=model,
-                )
             case "mock":
                 # Not a random number, is the dimensionality used by
                 # the default embedding model

private_gpt/components/ingest/ingest_component.py

@@ -403,7 +403,7 @@ class PipelineIngestComponent(BaseIngestComponentWithIndex):
                 self.transformations,
                 show_progress=self.show_progress,
             )
-            self.node_q.put(("process", file_name, documents, list(nodes)))
+            self.node_q.put(("process", file_name, documents, nodes))
         finally:
             self.doc_semaphore.release()
             self.doc_q.task_done()  # unblock Q joins

private_gpt/components/ingest/ingest_helper.py

@@ -92,13 +92,7 @@ class IngestionHelper:
             return string_reader.load_data([file_data.read_text()])
 
         logger.debug("Specific reader found for extension=%s", extension)
-        documents = reader_cls().load_data(file_data)
+        return reader_cls().load_data(file_data)
-
-        # Sanitize NUL bytes in text which can't be stored in Postgres
-        for i in range(len(documents)):
-            documents[i].text = documents[i].text.replace("\u0000", "")
-
-        return documents
 
     @staticmethod
     def _exclude_metadata(documents: list[Document]) -> None:

private_gpt/components/llm/llm_component.py

@@ -120,6 +120,7 @@ class LLMComponent:
                     api_version="",
                     temperature=settings.llm.temperature,
                     context_window=settings.llm.context_window,
+                    max_new_tokens=settings.llm.max_new_tokens,
                     messages_to_prompt=prompt_style.messages_to_prompt,
                     completion_to_prompt=prompt_style.completion_to_prompt,
                     tokenizer=settings.llm.tokenizer,
@@ -183,10 +184,10 @@ class LLMComponent:
 
                         return wrapper
 
-                    Ollama.chat = add_keep_alive(Ollama.chat)  # type: ignore
+                    Ollama.chat = add_keep_alive(Ollama.chat)
-                    Ollama.stream_chat = add_keep_alive(Ollama.stream_chat)  # type: ignore
+                    Ollama.stream_chat = add_keep_alive(Ollama.stream_chat)
-                    Ollama.complete = add_keep_alive(Ollama.complete)  # type: ignore
+                    Ollama.complete = add_keep_alive(Ollama.complete)
-                    Ollama.stream_complete = add_keep_alive(Ollama.stream_complete)  # type: ignore
+                    Ollama.stream_complete = add_keep_alive(Ollama.stream_complete)
 
                 self.llm = llm
 

private_gpt/components/llm/prompt_helper.py

@@ -40,8 +40,7 @@ class AbstractPromptStyle(abc.ABC):
         logger.debug("Got for messages='%s' the prompt='%s'", messages, prompt)
         return prompt
 
-    def completion_to_prompt(self, prompt: str) -> str:
+    def completion_to_prompt(self, completion: str) -> str:
-        completion = prompt  # Fix: Llama-index parameter has to be named as prompt
         prompt = self._completion_to_prompt(completion)
         logger.debug("Got for completion='%s' the prompt='%s'", completion, prompt)
         return prompt
@@ -286,9 +285,8 @@ class ChatMLPromptStyle(AbstractPromptStyle):
 
 
 def get_prompt_style(
-    prompt_style: (
+    prompt_style: Literal["default", "llama2", "llama3", "tag", "mistral", "chatml"]
-        Literal["default", "llama2", "llama3", "tag", "mistral", "chatml"] | None
+    | None
-    )
 ) -> AbstractPromptStyle:
     """Get the prompt style to use from the given string.
 

private_gpt/components/node_store/node_store_component.py

@@ -38,10 +38,10 @@ class NodeStoreComponent:
 
             case "postgres":
                 try:
-                    from llama_index.storage.docstore.postgres import (  # type: ignore
+                    from llama_index.core.storage.docstore.postgres_docstore import (
                         PostgresDocumentStore,
                     )
-                    from llama_index.storage.index_store.postgres import (  # type: ignore
+                    from llama_index.core.storage.index_store.postgres_index_store import (
                         PostgresIndexStore,
                     )
                 except ImportError:
@@ -55,7 +55,6 @@ class NodeStoreComponent:
                 self.index_store = PostgresIndexStore.from_params(
                     **settings.postgres.model_dump(exclude_none=True)
                 )
-
                 self.doc_store = PostgresDocumentStore.from_params(
                     **settings.postgres.model_dump(exclude_none=True)
                 )

private_gpt/components/vector_store/batched_chroma.py

@@ -1,17 +1,14 @@
-from collections.abc import Generator, Sequence
+from collections.abc import Generator
-from typing import TYPE_CHECKING, Any
+from typing import Any
 
 from llama_index.core.schema import BaseNode, MetadataMode
 from llama_index.core.vector_stores.utils import node_to_metadata_dict
 from llama_index.vector_stores.chroma import ChromaVectorStore  # type: ignore
 
-if TYPE_CHECKING:
-    from collections.abc import Mapping
-
 
 def chunk_list(
-    lst: Sequence[BaseNode], max_chunk_size: int
+    lst: list[BaseNode], max_chunk_size: int
-) -> Generator[Sequence[BaseNode], None, None]:
+) -> Generator[list[BaseNode], None, None]:
     """Yield successive max_chunk_size-sized chunks from lst.
 
     Args:
@@ -63,7 +60,7 @@ class BatchedChromaVectorStore(ChromaVectorStore):  # type: ignore
         )
         self.chroma_client = chroma_client
 
-    def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> list[str]:
+    def add(self, nodes: list[BaseNode], **add_kwargs: Any) -> list[str]:
         """Add nodes to index, batching the insertion to avoid issues.
 
         Args:
@@ -81,8 +78,8 @@ class BatchedChromaVectorStore(ChromaVectorStore):  # type: ignore
 
         all_ids = []
         for node_chunk in node_chunks:
-            embeddings: list[Sequence[float]] = []
+            embeddings = []
-            metadatas: list[Mapping[str, Any]] = []
+            metadatas = []
             ids = []
             documents = []
             for node in node_chunk:

private_gpt/server/chat/chat_service.py

@@ -1,5 +1,4 @@
 from dataclasses import dataclass
-from typing import TYPE_CHECKING
 
 from injector import inject, singleton
 from llama_index.core.chat_engine import ContextChatEngine, SimpleChatEngine
@@ -27,9 +26,6 @@ from private_gpt.open_ai.extensions.context_filter import ContextFilter
 from private_gpt.server.chunks.chunks_service import Chunk
 from private_gpt.settings.settings import Settings
 
-if TYPE_CHECKING:
-    from llama_index.core.postprocessor.types import BaseNodePostprocessor
-
 
 class Completion(BaseModel):
     response: str
@@ -118,15 +114,12 @@ class ChatService:
                 context_filter=context_filter,
                 similarity_top_k=self.settings.rag.similarity_top_k,
             )
-            node_postprocessors: list[BaseNodePostprocessor] = [
+            node_postprocessors = [
                 MetadataReplacementPostProcessor(target_metadata_key="window"),
+                SimilarityPostprocessor(
+                    similarity_cutoff=settings.rag.similarity_value
+                ),
             ]
-            if settings.rag.similarity_value:
-                node_postprocessors.append(
-                    SimilarityPostprocessor(
-                        similarity_cutoff=settings.rag.similarity_value
-                    )
-                )
 
             if settings.rag.rerank.enabled:
                 rerank_postprocessor = SentenceTransformerRerank(

private_gpt/server/recipes/summarize/summarize_service.py

@@ -90,9 +90,9 @@ class SummarizeService:
         # Add context documents to summarize
         if use_context:
             # 1. Recover all ref docs
-            ref_docs: dict[str, RefDocInfo] | None = (
+            ref_docs: dict[
-                self.storage_context.docstore.get_all_ref_doc_info()
+                str, RefDocInfo
-            )
+            ] | None = self.storage_context.docstore.get_all_ref_doc_info()
             if ref_docs is None:
                 raise ValueError("No documents have been ingested yet.")
 

private_gpt/settings/settings.py

@@ -136,19 +136,19 @@ class LLMSettings(BaseModel):
         0.1,
         description="The temperature of the model. Increasing the temperature will make the model answer more creatively. A value of 0.1 would be more factual.",
     )
-    prompt_style: Literal["default", "llama2", "llama3", "tag", "mistral", "chatml"] = (
+    prompt_style: Literal[
-        Field(
+        "default", "llama2", "llama3", "tag", "mistral", "chatml"
-            "llama2",
+    ] = Field(
-            description=(
+        "llama2",
-                "The prompt style to use for the chat engine. "
+        description=(
-                "If `default` - use the default prompt style from the llama_index. It should look like `role: message`.\n"
+            "The prompt style to use for the chat engine. "
-                "If `llama2` - use the llama2 prompt style from the llama_index. Based on `<s>`, `[INST]` and `<<SYS>>`.\n"
+            "If `default` - use the default prompt style from the llama_index. It should look like `role: message`.\n"
-                "If `llama3` - use the llama3 prompt style from the llama_index."
+            "If `llama2` - use the llama2 prompt style from the llama_index. Based on `<s>`, `[INST]` and `<<SYS>>`.\n"
-                "If `tag` - use the `tag` prompt style. It should look like `<|role|>: message`. \n"
+            "If `llama3` - use the llama3 prompt style from the llama_index."
-                "If `mistral` - use the `mistral prompt style. It shoudl look like <s>[INST] {System Prompt} [/INST]</s>[INST] { UserInstructions } [/INST]"
+            "If `tag` - use the `tag` prompt style. It should look like `<|role|>: message`. \n"
-                "`llama2` is the historic behaviour. `default` might work better with your custom models."
+            "If `mistral` - use the `mistral prompt style. It shoudl look like <s>[INST] {System Prompt} [/INST]</s>[INST] { UserInstructions } [/INST]"
-            ),
+            "`llama2` is the historic behaviour. `default` might work better with your custom models."
-        )
+        ),
     )
 
 
@@ -197,14 +197,7 @@ class HuggingFaceSettings(BaseModel):
 
 class EmbeddingSettings(BaseModel):
     mode: Literal[
-        "huggingface",
+        "huggingface", "openai", "azopenai", "sagemaker", "ollama", "mock", "gemini"
-        "openai",
-        "azopenai",
-        "sagemaker",
-        "ollama",
-        "mock",
-        "gemini",
-        "mistralai",
     ]
     ingest_mode: Literal["simple", "batch", "parallel", "pipeline"] = Field(
         "simple",
@@ -357,10 +350,6 @@ class AzureOpenAISettings(BaseModel):
 class UISettings(BaseModel):
     enabled: bool
     path: str
-    default_mode: Literal["RAG", "Search", "Basic", "Summarize"] = Field(
-        "RAG",
-        description="The default mode.",
-    )
     default_chat_system_prompt: str = Field(
         None,
         description="The default system prompt to use for the chat mode.",

private_gpt/ui/ui.py

@@ -1,5 +1,4 @@
 """This file should be imported if and only if you want to run the UI locally."""
-
 import base64
 import logging
 import time
@@ -100,11 +99,8 @@ class PrivateGptUi:
         self._selected_filename = None
 
         # Initialize system prompt based on default mode
-        default_mode_map = {mode.value: mode for mode in Modes}
+        self.mode = MODES[0]
-        self._default_mode = default_mode_map.get(
+        self._system_prompt = self._get_default_system_prompt(self.mode)
-            settings().ui.default_mode, Modes.RAG_MODE
-        )
-        self._system_prompt = self._get_default_system_prompt(self._default_mode)
 
     def _chat(
         self, message: str, history: list[list[str]], mode: Modes, *_: Any
@@ -394,7 +390,7 @@ class PrivateGptUi:
 
             with gr.Row(equal_height=False):
                 with gr.Column(scale=3):
-                    default_mode = self._default_mode
+                    default_mode = MODES[0]
                     mode = gr.Radio(
                         [mode.value for mode in MODES],
                         label="Mode",

private_gpt/utils/ollama.py

@@ -3,13 +3,10 @@ from collections import deque
 from collections.abc import Iterator, Mapping
 from typing import Any
 
-from httpx import ConnectError
 from tqdm import tqdm  # type: ignore
 
-from private_gpt.utils.retry import retry
-
 try:
-    from ollama import Client, ResponseError  # type: ignore
+    from ollama import Client  # type: ignore
 except ImportError as e:
     raise ImportError(
         "Ollama dependencies not found, install with `poetry install --extras llms-ollama or embeddings-ollama`"
@@ -17,25 +14,13 @@ except ImportError as e:
 
 logger = logging.getLogger(__name__)
 
-_MAX_RETRIES = 5
-_JITTER = (3.0, 10.0)
 
-
-@retry(
-    is_async=False,
-    exceptions=(ConnectError, ResponseError),
-    tries=_MAX_RETRIES,
-    jitter=_JITTER,
-    logger=logger,
-)
 def check_connection(client: Client) -> bool:
     try:
         client.list()
         return True
-    except (ConnectError, ResponseError) as e:
-        raise e
     except Exception as e:
-        logger.error(f"Failed to connect to Ollama: {type(e).__name__}: {e!s}")
+        logger.error(f"Failed to connect to Ollama: {e!s}")
         return False
 
 

private_gpt/utils/retry.py

@@ -1,31 +0,0 @@
-import logging
-from collections.abc import Callable
-from typing import Any
-
-from retry_async import retry as retry_untyped  # type: ignore
-
-retry_logger = logging.getLogger(__name__)
-
-
-def retry(
-    exceptions: Any = Exception,
-    *,
-    is_async: bool = False,
-    tries: int = -1,
-    delay: float = 0,
-    max_delay: float | None = None,
-    backoff: float = 1,
-    jitter: float | tuple[float, float] = 0,
-    logger: logging.Logger = retry_logger,
-) -> Callable[..., Any]:
-    wrapped = retry_untyped(
-        exceptions=exceptions,
-        is_async=is_async,
-        tries=tries,
-        delay=delay,
-        max_delay=max_delay,
-        backoff=backoff,
-        jitter=jitter,
-        logger=logger,
-    )
-    return wrapped  # type: ignore

pyproject.toml

@@ -7,75 +7,82 @@ authors = ["Zylon <hi@zylon.ai>"]
 [tool.poetry.dependencies]
 python = ">=3.11,<3.12"
 # PrivateGPT
-fastapi = { extras = ["all"], version = "^0.115.0" }
+fastapi = { extras = ["all"], version = "^0.111.0" }
-python-multipart = "^0.0.10"
+python-multipart = "^0.0.9"
-injector = "^0.22.0"
+injector = "^0.21.0"
-pyyaml = "^6.0.2"
+pyyaml = "^6.0.1"
 watchdog = "^4.0.1"
-transformers = "^4.44.2"
+transformers = "^4.42.3"
 docx2txt = "^0.8"
 cryptography = "^3.1"
 # LlamaIndex core libs
-llama-index-core = ">=0.11.2,<0.12.0"
+llama-index-core = "^0.10.52"
-llama-index-readers-file = "*"
+llama-index-readers-file = "^0.1.27"
 # Optional LlamaIndex integration libs
-llama-index-llms-llama-cpp = {version = "*", optional = true}
+llama-index-llms-llama-cpp = {version = "^0.1.4", optional = true}
-llama-index-llms-openai = {version ="*", optional = true}
+llama-index-llms-openai = {version = "^0.1.25", optional = true}
-llama-index-llms-openai-like = {version ="*", optional = true}
+llama-index-llms-openai-like = {version ="^0.1.3", optional = true}
-llama-index-llms-ollama = {version ="*", optional = true}
+llama-index-llms-ollama = {version ="^0.2.2", optional = true}
-llama-index-llms-azure-openai = {version ="*", optional = true}
+llama-index-llms-azure-openai = {version ="^0.1.8", optional = true}
-llama-index-llms-gemini = {version ="*", optional = true}
+llama-index-llms-gemini = {version ="^0.1.11", optional = true}
-llama-index-embeddings-ollama = {version ="*", optional = true}
+llama-index-embeddings-ollama = {version ="^0.1.2", optional = true}
-llama-index-embeddings-huggingface = {version ="*", optional = true}
+llama-index-embeddings-huggingface = {version ="^0.2.2", optional = true}
-llama-index-embeddings-openai = {version ="*", optional = true}
+llama-index-embeddings-openai = {version ="^0.1.10", optional = true}
-llama-index-embeddings-azure-openai = {version ="*", optional = true}
+llama-index-embeddings-azure-openai = {version ="^0.1.10", optional = true}
-llama-index-embeddings-gemini = {version ="*", optional = true}
+llama-index-embeddings-gemini = {version ="^0.1.8", optional = true}
-llama-index-embeddings-mistralai = {version ="*", optional = true}
+llama-index-vector-stores-qdrant = {version ="^0.2.10", optional = true}
-llama-index-vector-stores-qdrant = {version ="*", optional = true}
+llama-index-vector-stores-milvus = {version ="^0.1.20", optional = true}
-llama-index-vector-stores-milvus = {version ="*", optional = true}
+llama-index-vector-stores-chroma = {version ="^0.1.10", optional = true}
-llama-index-vector-stores-chroma = {version ="*", optional = true}
+llama-index-vector-stores-postgres = {version ="^0.1.11", optional = true}
-llama-index-vector-stores-postgres = {version ="*", optional = true}
+llama-index-vector-stores-clickhouse = {version ="^0.1.3", optional = true}
-llama-index-vector-stores-clickhouse = {version ="*", optional = true}
+llama-index-storage-docstore-postgres = {version ="^0.1.3", optional = true}
-llama-index-storage-docstore-postgres = {version ="*", optional = true}
+llama-index-storage-index-store-postgres = {version ="^0.1.4", optional = true}
-llama-index-storage-index-store-postgres = {version ="*", optional = true}
 # Postgres
 psycopg2-binary = {version ="^2.9.9", optional = true}
 asyncpg = {version="^0.29.0", optional = true}
 
 # ClickHouse
-clickhouse-connect = {version = "^0.7.19", optional = true}
+clickhouse-connect = {version = "^0.7.15", optional = true}
 
 # Optional Sagemaker dependency
-boto3 = {version ="^1.35.26", optional = true}
+boto3 = {version ="^1.34.139", optional = true}
+
+# Optional Qdrant client
+qdrant-client = {version ="^1.9.0", optional = true}
 
 # Optional Reranker dependencies
-torch = {version ="^2.4.1", optional = true}
+torch = {version ="^2.3.1", optional = true}
-sentence-transformers = {version ="^3.1.1", optional = true}
+sentence-transformers = {version ="^3.0.1", optional = true}
 
 # Optional UI
-gradio = {version ="^4.44.0", optional = true}
+gradio = {version ="^4.37.2", optional = true}
-ffmpy = {version ="^0.4.0", optional = true}
+# Fix: https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/16289#issuecomment-2255106490
+ffmpy = {git = "https://github.com/EuDs63/ffmpy.git", rev = "333a19ee4d21f32537c0508aa1942ef1aa7afe24", optional = true}
+
+# Optional Google Gemini dependency
+google-generativeai = {version ="^0.5.4", optional = true}
+
+# Optional Ollama client
+ollama = {version ="^0.3.0", optional = true}
 
 # Optional HF Transformers
 einops = {version = "^0.8.0", optional = true}
-retry-async = "^0.1.4"
 
 [tool.poetry.extras]
 ui = ["gradio", "ffmpy"]
 llms-llama-cpp = ["llama-index-llms-llama-cpp"]
 llms-openai = ["llama-index-llms-openai"]
 llms-openai-like = ["llama-index-llms-openai-like"]
-llms-ollama = ["llama-index-llms-ollama"]
+llms-ollama = ["llama-index-llms-ollama", "ollama"]
 llms-sagemaker = ["boto3"]
 llms-azopenai = ["llama-index-llms-azure-openai"]
-llms-gemini = ["llama-index-llms-gemini"]
+llms-gemini = ["llama-index-llms-gemini", "google-generativeai"]
-embeddings-ollama = ["llama-index-embeddings-ollama"]
+embeddings-ollama = ["llama-index-embeddings-ollama", "ollama"]
 embeddings-huggingface = ["llama-index-embeddings-huggingface", "einops"]
 embeddings-openai = ["llama-index-embeddings-openai"]
 embeddings-sagemaker = ["boto3"]
 embeddings-azopenai = ["llama-index-embeddings-azure-openai"]
 embeddings-gemini = ["llama-index-embeddings-gemini"]
-embeddings-mistral = ["llama-index-embeddings-mistralai"]
 vector-stores-qdrant = ["llama-index-vector-stores-qdrant"]
 vector-stores-clickhouse = ["llama-index-vector-stores-clickhouse", "clickhouse_connect"]
 vector-stores-chroma = ["llama-index-vector-stores-chroma"]
@@ -85,14 +92,14 @@ storage-nodestore-postgres = ["llama-index-storage-docstore-postgres","llama-ind
 rerank-sentence-transformers = ["torch", "sentence-transformers"]
 
 [tool.poetry.group.dev.dependencies]
-black = "^24"
+black = "^22"
-mypy = "^1.11"
+mypy = "^1.2"
-pre-commit = "^3"
+pre-commit = "^2"
-pytest = "^8"
+pytest = "^7"
-pytest-cov = "^5"
+pytest-cov = "^3"
 ruff = "^0"
-pytest-asyncio = "^0.24.0"
+pytest-asyncio = "^0.21.1"
-types-pyyaml = "^6.0.12.20240917"
+types-pyyaml = "^6.0.12.12"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

settings.yaml

@@ -25,23 +25,21 @@ data:
 ui:
   enabled: true
   path: /
-  # "RAG", "Search", "Basic", or "Summarize"
-  default_mode: "RAG"
   default_chat_system_prompt: >
-    You are a helpful, respectful and honest assistant.
+    You are a helpful, respectful and honest assistant. 
     Always answer as helpfully as possible and follow ALL given instructions.
     Do not speculate or make up information.
     Do not reference any given instructions or context.
   default_query_system_prompt: >
-    You can only answer questions about the provided context.
+    You can only answer questions about the provided context. 
-    If you know the answer but it is not based in the provided context, don't provide
+    If you know the answer but it is not based in the provided context, don't provide 
     the answer, just state the answer is not in the context provided.
   default_summarization_system_prompt: >
-    Provide a comprehensive summary of the provided context information.
+    Provide a comprehensive summary of the provided context information. 
     The summary should cover all the key points and main ideas presented in
-    the original text, while also condensing the information into a concise
+    the original text, while also condensing the information into a concise 
     and easy-to-understand format. Please ensure that the summary includes
-    relevant details and examples that support the main ideas, while avoiding
+    relevant details and examples that support the main ideas, while avoiding 
     any unnecessary information or repetition.
   delete_file_button_enabled: true
   delete_all_files_button_enabled: true

tests/fixtures/fast_api_test_client.py

@@ -5,7 +5,7 @@ from private_gpt.launcher import create_app
 from tests.fixtures.mock_injector import MockInjector
 
 
-@pytest.fixture
+@pytest.fixture()
 def test_client(request: pytest.FixtureRequest, injector: MockInjector) -> TestClient:
     if request is not None and hasattr(request, "param"):
         injector.bind_settings(request.param or {})

tests/fixtures/ingest_helper.py

@@ -19,6 +19,6 @@ class IngestHelper:
         return ingest_result
 
 
-@pytest.fixture
+@pytest.fixture()
 def ingest_helper(test_client: TestClient) -> IngestHelper:
     return IngestHelper(test_client)

tests/fixtures/mock_injector.py

@@ -37,6 +37,6 @@ class MockInjector:
         return self.test_injector.get(interface)
 
 
-@pytest.fixture
+@pytest.fixture()
 def injector() -> MockInjector:
     return MockInjector()

tests/server/ingest/test_local_ingest.py

@@ -6,7 +6,7 @@ import pytest
 from fastapi.testclient import TestClient
 
 
-@pytest.fixture
+@pytest.fixture()
 def file_path() -> str:
     return "test.txt"