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https://github.com/nomic-ai/gpt4all.git
synced 2024-07-15 00:50:31 +03:00
Update .gitignore and Dockerfile, add .env file
and modify test batch
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parent
f3eaa33ce7
commit
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5
.gitignore
vendored
5
.gitignore
vendored
@ -183,4 +183,7 @@ build_*
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build-*
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# IntelliJ
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.idea/
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.idea/
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# LLM models
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*.gguf
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@ -7,14 +7,16 @@ services:
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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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env_file:
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- .env
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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=${MODEL_ID}
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- model=${MODEL_BIN} # using variable from .env file
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- inference_mode=cpu
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volumes:
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- './gpt4all_api/app:/app'
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- './gpt4all_api/models:/models'
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- './gpt4all_api/models:/models' # models are mounted in the container
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command: ["/start-reload.sh"]
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@ -1,8 +1,6 @@
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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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@ -17,7 +15,3 @@ 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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@ -2,16 +2,26 @@
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Use the OpenAI python API to test gpt4all models.
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"""
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from typing import List, get_args
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import os
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from dotenv import load_dotenv
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import openai
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openai.api_base = "http://localhost:4891/v1"
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openai.api_key = "not needed for a local LLM"
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# Load the .env file
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env_path = 'gpt4all-api/gpt4all_api/.env'
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load_dotenv(dotenv_path=env_path)
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# Fetch MODEL_ID from .env file
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model_id = os.getenv('MODEL_BIN', 'default_model_id')
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embedding = os.getenv('EMBEDDING', 'default_embedding_model_id')
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print (model_id)
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print (embedding)
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def test_completion():
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model = "ggml-mpt-7b-chat.bin"
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model = model_id
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prompt = "Who is Michael Jordan?"
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response = openai.Completion.create(
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model=model, prompt=prompt, max_tokens=50, temperature=0.28, top_p=0.95, n=1, echo=True, stream=False
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@ -19,7 +29,7 @@ def test_completion():
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assert len(response['choices'][0]['text']) > len(prompt)
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def test_streaming_completion():
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model = "ggml-mpt-7b-chat.bin"
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model = model_id
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prompt = "Who is Michael Jordan?"
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tokens = []
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for resp in openai.Completion.create(
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@ -36,19 +46,27 @@ def test_streaming_completion():
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assert (len(tokens) > 0)
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assert (len("".join(tokens)) > len(prompt))
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# Modified test batch, problems with keyerror in response
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def test_batched_completion():
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model = "ggml-mpt-7b-chat.bin"
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model = model_id # replace with your specific model ID
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prompt = "Who is Michael Jordan?"
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response = openai.Completion.create(
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model=model, prompt=[prompt] * 3, max_tokens=50, temperature=0.28, top_p=0.95, n=1, echo=True, stream=False
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)
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assert len(response['choices'][0]['text']) > len(prompt)
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assert len(response['choices']) == 3
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responses = []
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# Loop to create completions one at a time
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for _ in range(3):
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response = openai.Completion.create(
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model=model, prompt=prompt, max_tokens=50, temperature=0.28, top_p=0.95, n=1, echo=True, stream=False
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)
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responses.append(response)
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# Assertions to check the responses
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for response in responses:
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assert len(response['choices'][0]['text']) > len(prompt)
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assert len(responses) == 3
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def test_embedding():
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model = "ggml-all-MiniLM-L6-v2-f16.bin"
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model = embedding
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prompt = "Who is Michael Jordan?"
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response = openai.Embedding.create(model=model, input=prompt)
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output = response["data"][0]["embedding"]
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@ -56,4 +74,4 @@ def test_embedding():
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assert response["model"] == model
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assert isinstance(output, list)
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assert all(isinstance(x, args) for x in output)
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assert all(isinstance(x, args) for x in output)
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@ -1 +1 @@
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# Drop GGUF compatible models here, make sure it matches MODEL_BIN on your .env file
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### Drop GGUF compatible models here, make sure it matches MODEL_BIN on your .env file
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@ -7,6 +7,7 @@ fastapi>=0.95.0
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Jinja2>=3.0
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gpt4all>=1.0.0
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pytest
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openai
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openai==0.28.0
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black
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isort
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isort
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python-dotenv
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@ -14,7 +14,7 @@ testenv_gpu: clean_testenv test_build
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docker compose -f docker-compose.yaml -f docker-compose.gpu.yaml up --build
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testenv_d: clean_testenv test_build
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docker compose up --build -d
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docker compose env up --build -d
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test:
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docker compose exec $(APP_NAME) pytest -svv --disable-warnings -p no:cacheprovider /app/tests
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@ -28,19 +28,19 @@ clean_testenv:
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fresh_testenv: clean_testenv testenv
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venv:
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if [ ! -d $(ROOT_DIR)/env ]; then $(PYTHON) -m venv $(ROOT_DIR)/env; fi
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if [ ! -d $(ROOT_DIR)/venv ]; then $(PYTHON) -m venv $(ROOT_DIR)/venv; fi
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dependencies: venv
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source $(ROOT_DIR)/env/bin/activate; $(PYTHON) -m pip install -r $(ROOT_DIR)/$(APP_NAME)/requirements.txt
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source $(ROOT_DIR)/venv/bin/activate; $(PYTHON) -m pip install -r $(ROOT_DIR)/$(APP_NAME)/requirements.txt
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clean: clean_testenv
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# Remove existing environment
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rm -rf $(ROOT_DIR)/env;
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rm -rf $(ROOT_DIR)/venv;
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rm -rf $(ROOT_DIR)/$(APP_NAME)/*.pyc;
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black:
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source $(ROOT_DIR)/env/bin/activate; black -l 120 -S --target-version py38 $(APP_NAME)
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source $(ROOT_DIR)/venv/bin/activate; black -l 120 -S --target-version py38 $(APP_NAME)
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isort:
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source $(ROOT_DIR)/env/bin/activate; isort --ignore-whitespace --atomic -w 120 $(APP_NAME)
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source $(ROOT_DIR)/venv/bin/activate; isort --ignore-whitespace --atomic -w 120 $(APP_NAME)
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