github/privateGPT
1
0
Fork 1
mirror of https://github.com/imartinez/privateGPT.git synced 2025-05-09 00:37:28 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'main' of github.com:somashekhar161/private-gpt into feat/fireworks-integration

Browse Source
This commit is contained in:
Somashekar B R 2024-09-24 22:38:45 +05:30
commit 519c48b70b
9 changed files with 116 additions and 28 deletions

6
Dockerfile.llamacpp-cpu
View File

@ -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

6
Dockerfile.ollama
View File

@ -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

10
docker-compose.yaml
View File

@ -7,11 +7,12 @@ services:
# 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
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:
@ -26,11 +27,14 @@ services:
- ollama-cpu
- ollama-cuda
- ollama-api
depends_on:
- ollama
# 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
user: root
build:
context: .
dockerfile: Dockerfile.llamacpp-cpu
@ -43,7 +47,7 @@ services:
environment:
PORT: 8001
PGPT_PROFILES: local
HF_TOKEN: ${HF_TOKEN}
HF_TOKEN: ${HF_TOKEN:-}
profiles:
- llamacpp-cpu
@ -56,7 +60,7 @@ services:
ollama:
image: traefik:v2.10
ports:
- "8081:8080"
- "11434:11434"
command:
- "--providers.file.filename=/etc/router.yml"
- "--log.level=ERROR"

66
poetry.lock generated
View File

@ -2413,6 +2413,17 @@ files = [
{file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"},
]
[[package]]
name = "jsonpath-python"
version = "1.0.6"
description = "A more powerful JSONPath implementation in modern python"
optional = true
python-versions = ">=3.6"
files = [
{file = "jsonpath-python-1.0.6.tar.gz", hash = "sha256:dd5be4a72d8a2995c3f583cf82bf3cd1a9544cfdabf2d22595b67aff07349666"},
{file = "jsonpath_python-1.0.6-py3-none-any.whl", hash = "sha256:1e3b78df579f5efc23565293612decee04214609208a2335884b3ee3f786b575"},
]
[[package]]
name = "kiwisolver"
version = "1.4.7"
@ -2682,6 +2693,21 @@ huggingface-hub = {version = ">=0.19.0", extras = ["inference"]}
llama-index-core = ">=0.10.1,<0.11.0"
sentence-transformers = ">=2.6.1"
[[package]]
name = "llama-index-embeddings-mistralai"
version = "0.1.6"
description = "llama-index embeddings mistralai integration"
optional = true
python-versions = "<4.0,>=3.9"
files = [
{file = "llama_index_embeddings_mistralai-0.1.6-py3-none-any.whl", hash = "sha256:d69d6fc0be8a1772aaf890bc036f2d575af46070b375a2649803c0eb9736ea1b"},
{file = "llama_index_embeddings_mistralai-0.1.6.tar.gz", hash = "sha256:7c9cbf974b1e7d14ded34d3eb749a0d1a379fb151ab75115cc1ffdd08a96a045"},
]
[package.dependencies]
llama-index-core = ">=0.10.1,<0.11.0"
mistralai = ">=1.0.0"
[[package]]
name = "llama-index-embeddings-ollama"
version = "0.1.3"
@ -3221,16 +3247,37 @@ description = "An experimental Python binding of the Rust MiniJinja template eng
optional = true
python-versions = ">=3.8"
files = [
{file = "minijinja-2.2.0-cp38-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:e4154fcf72e81be01c2733b770e6cb3e584851cb2fa73c58e347b04967d3d7c0"},
{file = "minijinja-2.2.0-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4b05e0070c08b550fa9a09ff9c051f47424674332dd56cc54b997dd602887907"},
{file = "minijinja-2.2.0-cp38-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:360ea4a93fdf1fe327f3e70eed20ecb29f324ca28fae177de0605dcc29869300"},
{file = "minijinja-2.2.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9cad5ccb021ef25b6a271158f4d6636474edb08cd1dd49355aac6b68a48aebb"},
{file = "minijinja-2.2.0-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7a85c67c519b413fc4892854782927e1244a24cbbb3a3cb0ac5e57d9fdb1868c"},
{file = "minijinja-2.2.0-cp38-abi3-win32.whl", hash = "sha256:e431a2467dd6e1bcb7c511e9fbad012b02c6e5453acdd9fbd4c4af0d34a3d1c5"},
{file = "minijinja-2.2.0-cp38-abi3-win_amd64.whl", hash = "sha256:d4df7e4a09be4249c8243207fa89e6f4d22b853c2b565a99f48e478a30713822"},
{file = "minijinja-2.2.0.tar.gz", hash = "sha256:4411052c7a60f8d56468cc6d17d45d72be3d5e89e9578a04f8336cc56601523c"},
{file = "minijinja-2.0.1-cp38-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:063b291cb31f5c33eb77bb4cb457f67f14426ca1418232b8ae9f267155d330cc"},
{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4a4e9d639dd89ce7fef86e82147082ab3c248a36950fa3fbe793685ba322c1b7"},
{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a20373af4ee5430356c196c7fe5f19e3261a4fa16c944542b4de7a2349bac7a6"},
{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ade637bf4826258811a785ccc4e5d41cd2bdf4ec317b1ed3daa4dbbdd020f37d"},
{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d5ec956d777e0fee8e214af48363334c04f098e986038a9e8cb92a0564f81943"},
{file = "minijinja-2.0.1-cp38-abi3-win32.whl", hash = "sha256:039f4d1a1a73f90917cff1ed7c617eb56e2b2f91bbbdc551adaa448e1673e5c2"},
{file = "minijinja-2.0.1-cp38-abi3-win_amd64.whl", hash = "sha256:dca5d7689905dce340e36e47348b505c788daf297253b85a1aff506ea63ad1b8"},
{file = "minijinja-2.0.1.tar.gz", hash = "sha256:e774beffebfb8a1ad17e638ef70917cf5e94593f79acb8a8fff7d983169f3a4e"},
]
[[package]]
name = "mistralai"
version = "1.0.3"
description = "Python Client SDK for the Mistral AI API."
optional = true
python-versions = "<4.0,>=3.8"
files = [
{file = "mistralai-1.0.3-py3-none-any.whl", hash = "sha256:64af7c9192e64dc66b2da6d1c4d54a1324a881c21665a2f93d6b35d9de9f87c8"},
{file = "mistralai-1.0.3.tar.gz", hash = "sha256:84f1a217666c76fec9d477ae266399b813c3ac32a4a348d2ecd5fe1c039b0667"},
]
[package.dependencies]
httpx = ">=0.27.0,<0.28.0"
jsonpath-python = ">=1.0.6,<2.0.0"
pydantic = ">=2.8.2,<2.9.0"
python-dateutil = ">=2.9.0.post0,<3.0.0"
typing-inspect = ">=0.9.0,<0.10.0"
[package.extras]
gcp = ["google-auth (==2.27.0)", "requests (>=2.32.3,<3.0.0)"]
[[package]]
name = "mmh3"
version = "5.0.0"
@ -7010,6 +7057,7 @@ embeddings-azopenai = ["llama-index-embeddings-azure-openai"]
embeddings-fireworks = ["llama-index-embeddings-fireworks"]
embeddings-gemini = ["llama-index-embeddings-gemini"]
embeddings-huggingface = ["einops", "llama-index-embeddings-huggingface"]
embeddings-mistral = ["llama-index-embeddings-mistralai"]
embeddings-ollama = ["llama-index-embeddings-ollama", "ollama"]
embeddings-openai = ["llama-index-embeddings-openai"]
embeddings-sagemaker = ["boto3"]
@ -7033,4 +7081,4 @@ vector-stores-qdrant = ["llama-index-vector-stores-qdrant"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.11,<3.12"
content-hash = "43d568d296fc82dfe94a8b13877f0424d5e7980a0f0ca9d93dace983e9623584"
content-hash = "3fa6ef447847895b1a16b8b0422dd9e4fda1aaaadef3af71971eb412da89bf67"

17
private_gpt/components/embedding/embedding_component.py
View File

@ -157,6 +157,23 @@ 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

14
private_gpt/settings/settings.py
View File

@ -198,7 +198,15 @@ class HuggingFaceSettings(BaseModel):
class EmbeddingSettings(BaseModel):
mode: Literal[
"huggingface", "openai", "azopenai", "sagemaker", "ollama", "mock", "gemini","fireworks"
"huggingface",
"openai",
"azopenai",
"sagemaker",
"ollama",
"mock",
"gemini",
"mistralai",
"fireworks",
]
ingest_mode: Literal["simple", "batch", "parallel", "pipeline"] = Field(
"simple",
@ -366,6 +374,10 @@ 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.",

9
private_gpt/ui/ui.py
View File

@ -99,8 +99,11 @@ class PrivateGptUi:
self._selected_filename = None
# Initialize system prompt based on default mode
self.mode = MODES[0]
self._system_prompt = self._get_default_system_prompt(self.mode)
default_mode_map = {mode.value: mode for mode in Modes}
self._default_mode = default_mode_map.get(
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
@ -390,7 +393,7 @@ class PrivateGptUi:
with gr.Row(equal_height=False):
with gr.Column(scale=3):
default_mode = MODES[0]
default_mode = self._default_mode
mode = gr.Radio(
[mode.value for mode in MODES],
label="Mode",

2
pyproject.toml
View File

@ -30,6 +30,7 @@ llama-index-embeddings-huggingface = {version ="^0.2.2", optional = true}
llama-index-embeddings-openai = {version ="^0.1.10", optional = true}
llama-index-embeddings-azure-openai = {version ="^0.1.10", optional = true}
llama-index-embeddings-gemini = {version ="^0.1.8", optional = true}
llama-index-embeddings-mistralai = {version ="^0.1.6", optional = true}
llama-index-vector-stores-qdrant = {version ="^0.2.10", optional = true}
llama-index-vector-stores-milvus = {version ="^0.1.20", optional = true}
llama-index-vector-stores-chroma = {version ="^0.1.10", optional = true}
@ -86,6 +87,7 @@ 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"]

14
settings.yaml
View File

@ -25,21 +25,23 @@ 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.
If you know the answer but it is not based in the provided context, don't provide
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
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