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

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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
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6
Dockerfile.llamacpp-cpu
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@ -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
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@ -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"]

2
settings.yaml
View File

@ -25,6 +25,8 @@ 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.
Always answer as helpfully as possible and follow ALL given instructions.