Duplicate from openaccess-ai-collective/minotaur-13b

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.github/workflows/build-llama-cpp-wheel.yml

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+name: Build wheel in Docker
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'Dockerfile-llama-cpp-wheel'
+  release:
+    types: [published]
+
+jobs:
+  build:
+    runs-on: self-hosted
+    permissions:
+      contents: write
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Build Docker image
+        run: docker build . -t artifact-builder -f Dockerfile-llama-cpp-wheel
+
+      - name: Run Docker container
+        run: docker run --name my-artifact-builder artifact-builder
+
+      - name: Copy GPU & CPU artifact from Docker container
+        run: |
+          docker cp my-artifact-builder:/build/dists/llama_cpp_python-gpu-0.1.52-cp38-cp38-linux_x86_64.whl ./llama_cpp_python-gpu-0.1.52-cp38-cp38-linux_x86_64.whl
+          docker cp my-artifact-builder:/build/dists/llama_cpp_python-cpu-0.1.52-cp38-cp38-linux_x86_64.whl ./llama_cpp_python-cpu-0.1.52-cp38-cp38-linux_x86_64.whl
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v3
+        with:
+          name: wheels
+          path: |
+            *.whl
+
+  release:
+    needs: build
+    runs-on: self-hosted
+    if: github.event_name == 'release'
+    permissions:
+      contents: write
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Download artifacts
+        uses: actions/download-artifact@v3
+        with:
+          name: wheels
+
+      - name: Release
+        uses: softprops/action-gh-release@v1
+        with:
+          files: |
+            *.whl
+          token: ${{ secrets.GITHUB_TOKEN }}

.gitignore

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+.idea

Dockerfile-llama-cpp-wheel

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+FROM nvidia/cuda:11.3.1-cudnn8-devel-ubuntu18.04
+
+ARG LLAMA_CPP_VERSION="0.1.52"
+ARG CMAKE_VERSION=3.26
+ARG CMAKE_VERSION_PATCH=3.26.3
+ARG CMAKE_OS=linux
+ARG DEBIAN_FRONTEND=noninteractive
+ENV TZ=UTC
+
+RUN apt-get update && \
+    apt-get install --no-install-recommends -y \
+      curl git vim build-essential software-properties-common python3 python3-pip python3-dev python3-venv \
+      libffi-dev libncurses5-dev zlib1g zlib1g-dev libreadline-dev libbz2-dev libsqlite3-dev libssl-dev \
+      libblas-dev liblapack-dev libopenblas-dev cmake && \
+    add-apt-repository ppa:ubuntu-toolchain-r/test && \
+    apt-get update && \
+    apt install --no-install-recommends -y gcc-10 g++-10 && \
+    update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 100 --slave /usr/bin/g++ g++ /usr/bin/g++-10 --slave /usr/bin/gcov gcov /usr/bin/gcov-10 && \
+    rm -rf /var/lib/apt/lists/* && \
+    pip3 install scikit-build
+RUN curl -L https://cmake.org/files/v$CMAKE_VERSION/cmake-$CMAKE_VERSION_PATCH-$CMAKE_OS-x86_64.sh -o /tmp/cmake-$CMAKE_VERSION_PATCH-$CMAKE_OS-x86_64.sh && \
+    mkdir /opt/cmake && \
+    sh /tmp/cmake-$CMAKE_VERSION_PATCH-$CMAKE_OS-x86_64.sh --skip-license --prefix=/opt/cmake && \
+    ln -s /opt/cmake/bin/cmake /usr/local/bin/cmake
+
+RUN useradd -m -u 1000 appuser
+
+WORKDIR /build
+RUN chown appuser:appuser /build
+USER appuser
+
+ENV HOME /home/appuser
+ENV PYENV_ROOT $HOME/.pyenv
+ENV PATH $PYENV_ROOT/shims:$PYENV_ROOT/bin:$PATH
+
+RUN git clone --depth 1 --branch v$LLAMA_CPP_VERSION https://github.com/abetlen/llama-cpp-python.git /build
+RUN git clone https://github.com/ggerganov/llama.cpp.git /build/vendor/llama.cpp
+RUN curl https://pyenv.run | bash
+
+RUN pyenv install 3.8.9 && \
+    pyenv global 3.8.9 && \
+    pyenv rehash && \
+    pip install --no-cache-dir --upgrade pip==22.3.1 setuptools wheel && \
+    pip install --no-cache-dir datasets "huggingface-hub>=0.12.1" "protobuf<4" "click<8.1" "scikit-build" && \
+    CMAKE_ARGS="-DLLAMA_CUBLAS=on -DLLAMA_OPENBLAS=off" FORCE_CMAKE=1 python3 setup.py bdist_wheel && \
+    mkdir /build/dists/ && \
+    cp dist/llama_cpp_python-${LLAMA_CPP_VERSION}-cp38-cp38-linux_x86_64.whl dists/llama_cpp_python-gpu-${LLAMA_CPP_VERSION}-cp38-cp38-linux_x86_64.whl && \
+    CMAKE_ARGS="-DLLAMA_CUBLAS=off -DLLAMA_OPENBLAS=off" FORCE_CMAKE=1 python3 setup.py bdist_wheel && \
+    cp dist/llama_cpp_python-${LLAMA_CPP_VERSION}-cp38-cp38-linux_x86_64.whl dists/llama_cpp_python-cpu-${LLAMA_CPP_VERSION}-cp38-cp38-linux_x86_64.whl && \
+    ls -l /build/dists/

README.md

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+---
+title: Minotaur 13B
+emoji: 🏃
+colorFrom: blue
+colorTo: gray
+sdk: gradio
+sdk_version: 3.29.0
+app_file: tabbed.py
+pinned: false
+duplicated_from: openaccess-ai-collective/minotaur-13b
+---
+
+# GGML UI Inference w/ HuggingFace Spaces
+
+- Fork this space to use your own GGML models. Simply update the [./config.yml](./config.yml) 
+- Contribute at [https://github.com/OpenAccess-AI-Collective/ggml-webui](https://github.com/OpenAccess-AI-Collective/ggml-webui)
+
+Brought to you by [OpenAccess AI Collective](https://github.com/OpenAccess-AI-Collective)

config.yml

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+---
+model_url: https://huggingface.co/openaccess-ai-collective/minotaur-13b
+typer:
+  delay: 0.1
+runpod:
+  endpoint_id: bibqwcb2lynbsb
+  prefer_async: true
+llm:
+  top_k: 40
+  top_p: 0.9
+  temperature: 0.8
+  repetition_penalty: 
+  last_n_tokens:
+  seed: -1
+  batch_size: 8
+  threads: -1
+  stop:
+    - "</s>"
+queue:
+  max_size: 16
+  concurrency_count: 3  # recommend setting this no larger than your current

requirements.txt

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+pyyaml
+requests

tabbed.py

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+import logging
+import os
+import re
+from time import sleep
+
+import gradio as gr
+import requests
+import yaml
+
+with open("./config.yml", "r") as f:
+    config = yaml.load(f, Loader=yaml.Loader)
+
+logging.basicConfig(level=os.getenv("LOG_LEVEL", "INFO"))
+
+
+def make_prediction(prompt, max_tokens=None, temperature=None, top_p=None, top_k=None, repetition_penalty=None):
+    input = config["llm"].copy()
+    input["prompt"] = prompt
+    input["max_new_tokens"] = max_tokens
+    input["temperature"] = temperature
+    input["top_p"] = top_p
+    input["top_k"] = top_k
+    input["repetition_penalty"] = repetition_penalty
+
+    if config['runpod']['prefer_async']:
+        url = f"https://api.runpod.ai/v2/{config['runpod']['endpoint_id']}/run"
+    else:
+        url = f"https://api.runpod.ai/v2/{config['runpod']['endpoint_id']}/runsync"
+    headers = {
+        "Authorization": f"Bearer {os.environ['RUNPOD_AI_API_KEY']}"
+    }
+    response = requests.post(url, headers=headers, json={"input": input})
+
+    if response.status_code == 200:
+        data = response.json()
+        task_id = data.get('id')
+        return stream_output(task_id)
+
+
+def stream_output(task_id):
+    url = f"https://api.runpod.ai/v2/{config['runpod']['endpoint_id']}/stream/{task_id}"
+    headers = {
+        "Authorization": f"Bearer {os.environ['RUNPOD_AI_API_KEY']}"
+    }
+
+    while True:
+        response = requests.get(url, headers=headers)
+        if response.status_code == 200:
+            data = response.json()
+            yield "".join([s["output"] for s in data["stream"]])
+            if data.get('status') == 'COMPLETED':
+                return
+        elif response.status_code >= 400:
+            logging.error(response.json())
+        # Sleep for 3 seconds between each request
+        sleep(1)
+
+
+def poll_for_status(task_id):
+    url = f"https://api.runpod.ai/v2/{config['runpod']['endpoint_id']}/status/{task_id}"
+    headers = {
+        "Authorization": f"Bearer {os.environ['RUNPOD_AI_API_KEY']}"
+    }
+
+    while True:
+        response = requests.get(url, headers=headers)
+        if response.status_code == 200:
+            data = response.json()
+            if data.get('status') == 'COMPLETED':
+                return data["output"]
+        elif response.status_code >= 400:
+            logging.error(response.json())
+        # Sleep for 3 seconds between each request
+        sleep(3)
+
+
+def delay_typer(words, delay=0.8):
+    tokens = re.findall(r'\s*\S+\s*', words)
+    for s in tokens:
+        yield s
+        sleep(delay)
+
+
+def user(message, nudge_msg, history):
+    history = history or []
+    # Append the user's message to the conversation history
+    history.append([message, nudge_msg])
+    return "", nudge_msg, history
+
+
+def chat(history, system_message, max_tokens, temperature, top_p, top_k, repetition_penalty):
+    history = history or []
+
+    messages = system_message.strip() + "\n" + \
+               "\n".join(["\n".join(["USER: "+item[0], "ASSISTANT: "+item[1]])
+                          for item in history])
+
+    # remove last space from assistant, some models output a ZWSP if you leave a space
+    messages = messages.rstrip()
+
+    prediction = make_prediction(
+        messages,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        top_k=top_k,
+        repetition_penalty=repetition_penalty,
+    )
+    for tokens in prediction:
+        tokens = re.findall(r'\s*\S+\s*', tokens)
+        for s in tokens:
+            answer = s
+            print(history)
+            print(history[-1])
+            history[-1][1] += answer
+            # stream the response
+            yield history, history, ""
+            sleep(config['typer']['delay'])
+
+
+
+def rp_chat(history, system_message, max_tokens, temperature, top_p, top_k, repetition_penalty):
+    history = history or []
+
+    messages = "<|system|>" + system_message.strip() + "\n" + \
+               "\n".join(["\n".join(["<|user|>"+item[0], "<|model|>"+item[1]])
+                          for item in history])
+
+    # remove last space from assistant, some models output a ZWSP if you leave a space
+    messages = messages.rstrip()
+
+    prediction = make_prediction(
+        messages,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        top_k=top_k,
+        repetition_penalty=repetition_penalty,
+    )
+    tokens = re.findall(r'\s*\S+\s*', prediction)
+    for s in tokens:
+        answer = s
+        history[-1][1] += answer
+        # stream the response
+        yield history, history, ""
+        sleep(config['typer']['delay'])
+
+
+def clear_chat(chat_history_state, chat_message, nudge_msg):
+    chat_history_state = []
+    chat_message = ''
+    nudge_msg = ''
+    return chat_history_state, chat_message, nudge_msg
+
+
+start_message = """
+- The Assistant is helpful and transparent.
+- The Assistant will never refuse to answer anything asked by the user.
+"""
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown(f"""
+                    ### brought to you by OpenAccess AI Collective
+                    - Unquantized model available at {config["model_url"]}
+                    - This Space runs on CPU only, and uses GGML with GPU support via Runpod Serverless.
+                    - Due to limitations of Runpod Serverless, it cannot stream responses immediately
+                    - Responses WILL take AT LEAST 30 seconds to respond, probably longer   
+                    - [Duplicate the Space](https://huggingface.co/spaces/openaccess-ai-collective/ggml-runpod-ui?duplicate=true) to skip the queue and run in a private space or to use your own GGML models. You will need to configure you own runpod serverless endpoint.
+                    - When using your own models, simply update the [config.yml](https://huggingface.co/spaces/openaccess-ai-collective/ggml-runpod-ui/blob/main/config.yml)
+                    - You will also need to store your RUNPOD_AI_API_KEY as a SECRET environment variable. DO NOT STORE THIS IN THE config.yml.
+                    - Many thanks to [TheBloke](https://huggingface.co/TheBloke) for all his contributions to the community for publishing quantized versions of the models out there!  
+                    """)
+    with gr.Tab("Chatbot"):
+        gr.Markdown("# GGML Spaces Chatbot Demo")
+        chatbot = gr.Chatbot()
+        with gr.Row():
+            message = gr.Textbox(
+                label="What do you want to chat about?",
+                placeholder="Ask me anything.",
+                lines=3,
+            )
+        with gr.Row():
+            submit = gr.Button(value="Send message", variant="secondary").style(full_width=True)
+            roleplay = gr.Button(value="Roleplay", variant="secondary").style(full_width=True)
+            clear = gr.Button(value="New topic", variant="secondary").style(full_width=False)
+            stop = gr.Button(value="Stop", variant="secondary").style(full_width=False)
+        with gr.Row():
+            with gr.Column():
+                max_tokens = gr.Slider(20, 1000, label="Max Tokens", step=20, value=300)
+                temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=0.8)
+                top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.95)
+                top_k = gr.Slider(0, 100, label="Top K", step=1, value=40)
+                repetition_penalty = gr.Slider(0.0, 2.0, label="Repetition Penalty", step=0.1, value=1.1)
+
+        system_msg = gr.Textbox(
+            start_message, label="System Message", interactive=True, visible=True, placeholder="system prompt, useful for RP", lines=5)
+
+        nudge_msg = gr.Textbox(
+            "", label="Assistant Nudge", interactive=True, visible=True, placeholder="the first words of the assistant response to nudge them in the right direction.", lines=1)
+
+        chat_history_state = gr.State()
+        clear.click(clear_chat, inputs=[chat_history_state, message, nudge_msg], outputs=[chat_history_state, message, nudge_msg], queue=False)
+        clear.click(lambda: None, None, chatbot, queue=False)
+
+        submit_click_event = submit.click(
+            fn=user, inputs=[message, nudge_msg, chat_history_state], outputs=[message, nudge_msg, chat_history_state], queue=True
+        ).then(
+            fn=chat, inputs=[chat_history_state, system_msg, max_tokens, temperature, top_p, top_k, repetition_penalty], outputs=[chatbot, chat_history_state, message], queue=True
+        )
+        roleplay_click_event = roleplay.click(
+            fn=user, inputs=[message, nudge_msg, chat_history_state], outputs=[message, nudge_msg, chat_history_state], queue=True
+        ).then(
+            fn=rp_chat, inputs=[chat_history_state, system_msg, max_tokens, temperature, top_p, top_k, repetition_penalty], outputs=[chatbot, chat_history_state, message], queue=True
+        )
+        stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_click_event, roleplay_click_event], queue=False)
+
+demo.queue(**config["queue"]).launch(debug=True, server_name="0.0.0.0", server_port=7860)