mirror of
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GPT4All API Scaffolding. Matches OpenAI OpenAPI spec for chats and completions (#839)
* GPT4All API Scaffolding. Matches OpenAI OpenAI spec for engines, chats and completions * Edits for docker building * FastAPI app builds and pydantic models are accurate * Added groovy download into dockerfile * improved dockerfile * Chat completions endpoint edits * API uni test sketch * Working example of groovy inference with open ai api * Added lines to test * Set default to mpt
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112
gpt4all-api/.gitignore
vendored
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gpt4all-api/.gitignore
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# Byte-compiled / optimized / DLL files
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__pycache__/
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app/__pycache__/
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gpt4all_api/__pycache__/
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gpt4all_api/app/api_v1/__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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||||
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||||
# VS Code
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.vscode/
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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||||
# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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||||
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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||||
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||||
# Django stuff:
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*.log
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||||
local_settings.py
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db.sqlite3
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||||
# Flask stuff:
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instance/
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.webassets-cache
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||||
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# Scrapy stuff:
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||||
.scrapy
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||||
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||||
# Sphinx documentation
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docs/_build/
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||||
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# PyBuilder
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target/
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||||
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||||
# Jupyter Notebook
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.ipynb_checkpoints
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||||
# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule
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# SageMath parsed files
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*.sage.py
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|
||||
# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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||||
|
||||
# Spyder project settings
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.spyderproject
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.spyproject
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||||
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||||
# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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*.lock
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*.cache
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13
gpt4all-api/LICENSE
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gpt4all-api/LICENSE
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Copyright 2023 Nomic, Inc.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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|
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http://www.apache.org/licenses/LICENSE-2.0
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|
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Unless required by applicable law or agreed to in writing, software
|
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distributed under the License is distributed on an "AS IS" BASIS,
|
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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@ -1,2 +1,47 @@
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# GPT4All API
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This directory will contain code to build out a RESTful API for GPT4All models. Exact details TBD, but as an MVP, user should be able to send requests to list, download, and generate text with different models.
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# WIP - not yet ready.
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# GPT4All REST API
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This directory contains the source code to run and build docker images that run a FastAPI app
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for serving inference from GPT4All models. The API matches the OpenAI API spec.
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## Tutorial
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### Starting the app
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First build the FastAPI docker image. You only have to do this on initial build or when you add new dependencies to the requirements.txt file:
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```bash
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DOCKER_BUILDKIT=1 docker build -t gpt4all_api --progress plain -f gpt4all_api/Dockerfile.buildkit .
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```
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Then, start the backend with:
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```bash
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docker compose up --build
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```
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#### Spinning up your app
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Run `docker compose up` to spin up the backend. Monitor the logs for errors in-case you forgot to set an environment variable above.
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#### Development
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Run
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```bash
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docker compose up --build
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```
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and edit files in the `api` directory. The api will hot-reload on changes.
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You can run the unit tests with
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```bash
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make test
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```
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#### Viewing API documentation
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Once the FastAPI ap is started you can access its documentation and test the search endpoint by going to:
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```
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localhost:80/docs
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```
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This documentation should match the OpenAI OpenAPI spec located at https://github.com/openai/openai-openapi/blob/master/openapi.yaml
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18
gpt4all-api/docker-compose.yaml
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gpt4all-api/docker-compose.yaml
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version: "3.5"
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services:
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gpt4all_api:
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image: gpt4all_api
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container_name: gpt4all_api
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restart: always #restart on error (usually code compilation from save during bad state)
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ports:
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- "4891:4891"
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environment:
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- APP_ENVIRONMENT=dev
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- WEB_CONCURRENCY=2
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- LOGLEVEL=debug
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- PORT=4891
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- model=ggml-mpt-7b-chat.bin
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volumes:
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- './gpt4all_api/app:/app'
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command: ["/start-reload.sh"]
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23
gpt4all-api/gpt4all_api/Dockerfile.buildkit
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gpt4all-api/gpt4all_api/Dockerfile.buildkit
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# syntax=docker/dockerfile:1.0.0-experimental
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FROM tiangolo/uvicorn-gunicorn:python3.11
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ARG MODEL_BIN=ggml-mpt-7b-chat.bin
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# Put first so anytime this file changes other cached layers are invalidated.
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COPY gpt4all_api/requirements.txt /requirements.txt
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RUN pip install --upgrade pip
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# Run various pip install commands with ssh keys from host machine.
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RUN --mount=type=ssh pip install -r /requirements.txt && \
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rm -Rf /root/.cache && rm -Rf /tmp/pip-install*
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# Finally, copy app and client.
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COPY gpt4all_api/app /app
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RUN mkdir -p /models
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# Include the following line to bake a model into the image and not have to download it on API start.
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RUN wget -q --show-progress=off https://gpt4all.io/models/${MODEL_BIN} -P /models \
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&& md5sum /models/${MODEL_BIN}
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1
gpt4all-api/gpt4all_api/README.md
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1
gpt4all-api/gpt4all_api/README.md
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# FastAPI app for serving GPT4All models
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0
gpt4all-api/gpt4all_api/app/__init__.py
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0
gpt4all-api/gpt4all_api/app/__init__.py
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0
gpt4all-api/gpt4all_api/app/api_v1/__init__.py
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0
gpt4all-api/gpt4all_api/app/api_v1/__init__.py
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8
gpt4all-api/gpt4all_api/app/api_v1/api.py
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8
gpt4all-api/gpt4all_api/app/api_v1/api.py
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from api_v1.routes import chat, completions, engines
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from fastapi import APIRouter
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router = APIRouter()
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router.include_router(chat.router)
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router.include_router(completions.router)
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router.include_router(engines.router)
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26
gpt4all-api/gpt4all_api/app/api_v1/events.py
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gpt4all-api/gpt4all_api/app/api_v1/events.py
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import logging
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from fastapi import HTTPException
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from fastapi.responses import JSONResponse
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from starlette.requests import Request
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from api_v1.settings import settings
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log = logging.getLogger(__name__)
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startup_msg_fmt = """
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Starting up GPT4All API
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"""
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async def on_http_error(request: Request, exc: HTTPException):
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return JSONResponse({'detail': exc.detail}, status_code=exc.status_code)
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async def on_startup(app):
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startup_msg = startup_msg_fmt.format(settings=settings)
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log.info(startup_msg)
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def startup_event_handler(app):
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async def start_app() -> None:
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await on_startup(app)
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return start_app
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63
gpt4all-api/gpt4all_api/app/api_v1/routes/chat.py
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gpt4all-api/gpt4all_api/app/api_v1/routes/chat.py
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from fastapi import APIRouter, Depends, Response, Security, status
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from pydantic import BaseModel, Field
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from typing import List, Dict
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import logging
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import time
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from api_v1.settings import settings
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.DEBUG)
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### This should follow https://github.com/openai/openai-openapi/blob/master/openapi.yaml
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class ChatCompletionMessage(BaseModel):
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role: str
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content: str
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class ChatCompletionRequest(BaseModel):
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model: str = Field(..., description='The model to generate a completion from.')
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messages: List[ChatCompletionMessage] = Field(..., description='The model to generate a completion from.')
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class ChatCompletionChoice(BaseModel):
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message: ChatCompletionMessage
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index: int
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finish_reason: str
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class ChatCompletionUsage(BaseModel):
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prompt_tokens: int
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completion_tokens: int
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total_tokens: int
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class ChatCompletionResponse(BaseModel):
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id: str
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object: str = 'text_completion'
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created: int
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model: str
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choices: List[ChatCompletionChoice]
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usage: ChatCompletionUsage
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router = APIRouter(prefix="/chat", tags=["Completions Endpoints"])
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@router.post("/completions", response_model=ChatCompletionResponse)
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async def chat_completion(request: ChatCompletionRequest):
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'''
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Completes a GPT4All model response.
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'''
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return ChatCompletionResponse(
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id='asdf',
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created=time.time(),
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model=request.model,
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choices=[{}],
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usage={
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'prompt_tokens': 0,
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'completion_tokens': 0,
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'total_tokens': 0
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}
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)
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86
gpt4all-api/gpt4all_api/app/api_v1/routes/completions.py
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gpt4all-api/gpt4all_api/app/api_v1/routes/completions.py
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from fastapi import APIRouter, Depends, Response, Security, status
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from pydantic import BaseModel, Field
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from typing import List, Dict
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import logging
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from uuid import uuid4
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from api_v1.settings import settings
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from gpt4all import GPT4All
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import time
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.DEBUG)
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### This should follow https://github.com/openai/openai-openapi/blob/master/openapi.yaml
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class CompletionRequest(BaseModel):
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model: str = Field(..., description='The model to generate a completion from.')
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prompt: str = Field(..., description='The prompt to begin completing from.')
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max_tokens: int = Field(7, description='Max tokens to generate')
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temperature: float = Field(0, description='Model temperature')
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top_p: float = Field(1.0, description='top_p')
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n: int = Field(1, description='')
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stream: bool = Field(False, description='Stream responses')
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class CompletionChoice(BaseModel):
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text: str
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index: int
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logprobs: float
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finish_reason: str
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class CompletionUsage(BaseModel):
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prompt_tokens: int
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completion_tokens: int
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total_tokens: int
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class CompletionResponse(BaseModel):
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id: str
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object: str = 'text_completion'
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created: int
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model: str
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choices: List[CompletionChoice]
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usage: CompletionUsage
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router = APIRouter(prefix="/completions", tags=["Completion Endpoints"])
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@router.post("/", response_model=CompletionResponse)
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async def completions(request: CompletionRequest):
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'''
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Completes a GPT4All model response.
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'''
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# global model
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if request.stream:
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raise NotImplementedError("Streaming is not yet implements")
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model = GPT4All(model_name=settings.model, model_path=settings.gpt4all_path)
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output = model.generate(prompt=request.prompt,
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n_predict = request.max_tokens,
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top_k = 20,
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top_p = request.top_p,
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temp=request.temperature,
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n_batch = 1024,
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repeat_penalty = 1.2,
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repeat_last_n = 10,
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context_erase = 0)
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return CompletionResponse(
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id=str(uuid4()),
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created=time.time(),
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model=request.model,
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choices=[dict(CompletionChoice(
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text=output,
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index=0,
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logprobs=-1,
|
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finish_reason='stop'
|
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))],
|
||||
usage={
|
||||
'prompt_tokens': 0, #TODO how to compute this?
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'completion_tokens': 0,
|
||||
'total_tokens': 0
|
||||
}
|
||||
)
|
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|
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|
38
gpt4all-api/gpt4all_api/app/api_v1/routes/engines.py
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38
gpt4all-api/gpt4all_api/app/api_v1/routes/engines.py
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|
||||
from fastapi import APIRouter, Depends, Response, Security, status
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||||
from pydantic import BaseModel, Field
|
||||
from typing import List, Dict
|
||||
import logging
|
||||
from api_v1.settings import settings
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
logger.setLevel(logging.DEBUG)
|
||||
|
||||
### This should follow https://github.com/openai/openai-openapi/blob/master/openapi.yaml
|
||||
|
||||
class ListEnginesResponse(BaseModel):
|
||||
data: List[Dict] = Field(..., description="All available models.")
|
||||
|
||||
class EngineResponse(BaseModel):
|
||||
data: List[Dict] = Field(..., description="All available models.")
|
||||
|
||||
router = APIRouter(prefix="/engines", tags=["Search Endpoints"])
|
||||
|
||||
@router.get("/", response_model=ListEnginesResponse)
|
||||
async def list_engines():
|
||||
'''
|
||||
List all available GPT4All models from
|
||||
https://raw.githubusercontent.com/nomic-ai/gpt4all/main/gpt4all-chat/metadata/models.json
|
||||
'''
|
||||
raise NotImplementedError()
|
||||
return ListEnginesResponse(data=[])
|
||||
|
||||
|
||||
@router.get("/{engine_id}", response_model=EngineResponse)
|
||||
async def retrieve_engine(engine_id: str):
|
||||
'''
|
||||
|
||||
'''
|
||||
|
||||
raise NotImplementedError()
|
||||
return EngineResponse()
|
||||
|
12
gpt4all-api/gpt4all_api/app/api_v1/routes/health.py
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12
gpt4all-api/gpt4all_api/app/api_v1/routes/health.py
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|
||||
import logging
|
||||
from fastapi import APIRouter
|
||||
from fastapi.responses import JSONResponse
|
||||
log = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/health", tags=["Health"])
|
||||
|
||||
|
||||
@router.get('/', response_class=JSONResponse)
|
||||
async def health_check():
|
||||
"""Runs a health check on this instance of the API."""
|
||||
return JSONResponse({'status': 'ok'}, headers={'Access-Control-Allow-Origin': '*'})
|
10
gpt4all-api/gpt4all_api/app/api_v1/settings.py
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10
gpt4all-api/gpt4all_api/app/api_v1/settings.py
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|
||||
from pydantic import BaseSettings
|
||||
|
||||
|
||||
class Settings(BaseSettings):
|
||||
app_environment = 'dev'
|
||||
model: str = 'ggml-mpt-7b-chat.bin'
|
||||
gpt4all_path: str = '/models'
|
||||
|
||||
|
||||
settings = Settings()
|
3
gpt4all-api/gpt4all_api/app/docs.py
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3
gpt4all-api/gpt4all_api/app/docs.py
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|
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desc = 'GPT4All API'
|
||||
|
||||
endpoint_paths = {'health': '/health'}
|
61
gpt4all-api/gpt4all_api/app/main.py
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61
gpt4all-api/gpt4all_api/app/main.py
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|
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import os
|
||||
import docs
|
||||
import logging
|
||||
from fastapi import FastAPI, HTTPException, Request
|
||||
from starlette.middleware.cors import CORSMiddleware
|
||||
from fastapi.logger import logger as fastapi_logger
|
||||
from api_v1.settings import settings
|
||||
from api_v1.api import router as v1_router
|
||||
from api_v1 import events
|
||||
import os
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
app = FastAPI(title='GPT4All API', description=docs.desc)
|
||||
|
||||
#CORS Configuration (in-case you want to deploy)
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["GET", "POST", "OPTIONS"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
logger.info('Adding v1 endpoints..')
|
||||
|
||||
# add v1
|
||||
app.include_router(v1_router, prefix='/v1')
|
||||
app.add_event_handler('startup', events.startup_event_handler(app))
|
||||
app.add_exception_handler(HTTPException, events.on_http_error)
|
||||
|
||||
@app.on_event("startup")
|
||||
async def startup():
|
||||
global model
|
||||
logger.info(f"Downloading/fetching model: {os.path.join(settings.gpt4all_path, settings.model)}")
|
||||
from gpt4all import GPT4All
|
||||
model = GPT4All(model_name=settings.model, model_path=settings.gpt4all_path)
|
||||
|
||||
logger.info("GPT4All API is ready.")
|
||||
|
||||
@app.on_event("shutdown")
|
||||
async def shutdown():
|
||||
logger.info("Shutting down API")
|
||||
|
||||
|
||||
# This is needed to get logs to show up in the app
|
||||
if "gunicorn" in os.environ.get("SERVER_SOFTWARE", ""):
|
||||
gunicorn_error_logger = logging.getLogger("gunicorn.error")
|
||||
gunicorn_logger = logging.getLogger("gunicorn")
|
||||
|
||||
root_logger = logging.getLogger()
|
||||
fastapi_logger.setLevel(gunicorn_logger.level)
|
||||
fastapi_logger.handlers = gunicorn_error_logger.handlers
|
||||
root_logger.setLevel(gunicorn_logger.level)
|
||||
|
||||
uvicorn_logger = logging.getLogger("uvicorn.access")
|
||||
uvicorn_logger.handlers = gunicorn_error_logger.handlers
|
||||
else:
|
||||
# https://github.com/tiangolo/fastapi/issues/2019
|
||||
LOG_FORMAT2 = "[%(asctime)s %(process)d:%(threadName)s] %(name)s - %(levelname)s - %(message)s | %(filename)s:%(lineno)d"
|
||||
logging.basicConfig(level=logging.INFO, format=LOG_FORMAT2)
|
35
gpt4all-api/gpt4all_api/app/tests/test_endpoints.py
Normal file
35
gpt4all-api/gpt4all_api/app/tests/test_endpoints.py
Normal file
@ -0,0 +1,35 @@
|
||||
"""
|
||||
Use the OpenAI python API to test gpt4all models.
|
||||
"""
|
||||
import openai
|
||||
openai.api_base = "http://localhost:4891/v1"
|
||||
|
||||
openai.api_key = "not needed for a local LLM"
|
||||
|
||||
|
||||
def test_completion():
|
||||
model = "gpt4all-j-v1.3-groovy"
|
||||
prompt = "Who is Michael Jordan?"
|
||||
response = openai.Completion.create(
|
||||
model=model,
|
||||
prompt=prompt,
|
||||
max_tokens=50,
|
||||
temperature=0.28,
|
||||
top_p=0.95,
|
||||
n=1,
|
||||
echo=True,
|
||||
stream=False
|
||||
)
|
||||
assert len(response['choices'][0]['text']) > len(prompt)
|
||||
print(response)
|
||||
|
||||
# def test_chat_completions():
|
||||
# model = "gpt4all-j-v1.3-groovy"
|
||||
# prompt = "Who is Michael Jordan?"
|
||||
# response = openai.ChatCompletion.create(
|
||||
# model=model,
|
||||
# messages=[]
|
||||
# )
|
||||
|
||||
|
||||
|
10
gpt4all-api/gpt4all_api/requirements.txt
Normal file
10
gpt4all-api/gpt4all_api/requirements.txt
Normal file
@ -0,0 +1,10 @@
|
||||
aiohttp>=3.6.2
|
||||
aiofiles
|
||||
pydantic>=1.4.0
|
||||
requests>=2.24.0
|
||||
ujson>=2.0.2
|
||||
fastapi>=0.95.0
|
||||
Jinja2>=3.0
|
||||
gpt4all==0.2.3
|
||||
pytest
|
||||
openai
|
37
gpt4all-api/makefile
Normal file
37
gpt4all-api/makefile
Normal file
@ -0,0 +1,37 @@
|
||||
ROOT_DIR:=$(shell dirname $(realpath $(lastword $(MAKEFILE_LIST))))
|
||||
APP_NAME:=gpt4all_api
|
||||
PYTHON:=python3.8
|
||||
|
||||
all: dependencies
|
||||
|
||||
fresh: clean dependencies
|
||||
|
||||
testenv: clean_testenv test_build
|
||||
docker compose up --build
|
||||
|
||||
testenv_d: clean_testenv test_build
|
||||
docker compose up --build -d
|
||||
|
||||
test:
|
||||
docker compose exec gpt4all_api pytest -svv --disable-warnings -p no:cacheprovider /app/tests
|
||||
|
||||
test_build:
|
||||
DOCKER_BUILDKIT=1 docker build -t gpt4all_api --progress plain -f gpt4all_api/Dockerfile.buildkit .
|
||||
|
||||
clean_testenv:
|
||||
docker compose down -v
|
||||
|
||||
fresh_testenv: clean_testenv testenv
|
||||
|
||||
venv:
|
||||
if [ ! -d $(ROOT_DIR)/env ]; then $(PYTHON) -m venv $(ROOT_DIR)/env; fi
|
||||
|
||||
dependencies: venv
|
||||
source $(ROOT_DIR)/env/bin/activate; yes w | python -m pip install -r $(ROOT_DIR)/atlas_api/requirements.txt
|
||||
|
||||
clean: clean_testenv
|
||||
# Remove existing environment
|
||||
rm -rf $(ROOT_DIR)/env;
|
||||
rm -rf $(ROOT_DIR)/$(APP_NAME)/*.pyc;
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user