diff --git a/.github/workflows/backend-license-checker.yml b/.github/workflows/backend-license-checker.yml new file mode 100644 index 00000000..8c72bcbe --- /dev/null +++ b/.github/workflows/backend-license-checker.yml @@ -0,0 +1,101 @@ +name: Check SPDX Licenses + +on: + workflow_dispatch: + workflow_call: + pull_request: + branches: + - "main" + - "staging" + types: + - opened + - reopened + - synchronize + - assigned + - review_requested + +jobs: + check-spdx-licenses: + runs-on: ubuntu-20.04 + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5.0.0 + with: + cache: "pip" + python-version: "3.8" + - name: Install copyright check tool + run: pip install git+https://github.com/espressif/check-copyright.git@master + - name: Check SPDX licenses + id: check_spdx_licenses + run: | + set +e + output=$(python -m check_copyright --verbose --dry-run --config ./check_copyright_config.yaml . 2>&1) + exit_code=$? + clean_output=$(echo "$output" | sed 's/\x1b\[[0-9;]*m//g') + echo "CLEAN_OUTPUT<> $GITHUB_ENV + echo "$clean_output" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + echo "EXIT_CODE=$exit_code" >> $GITHUB_ENV + exit 0 + - name: Debug Extracted Files + run: | + echo "Extracted Files:" + echo "$CLEAN_OUTPUT" + - name: Extract Files + id: extract_files + run: | + set +e + files=$(echo "$CLEAN_OUTPUT" | awk ' + /Files which failed the copyright check:/, /Additional information about this hook and copyright headers may be found here:/ { + if ($0 !~ /Files which failed the copyright check:/ && $0 !~ /Additional information about this hook and copyright headers may be found here:/) print + } + /Some files are without a copyright note and a license header needs to be added:/, /Additional information about this hook and copyright headers may be found here:/ { + if ($0 !~ /Some files are without a copyright note and a license header needs to be added:/ && $0 !~ /Additional information about this hook and copyright headers may be found here:/) print + }' | sed 's/^ *//' | sed '/^$/d' | grep '^.') + echo "FILES<> $GITHUB_ENV + echo "$files" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + echo "Extracted Files: $files" + exit 0 + - name: Debug Extracted Files + run: | + echo "Extracted Files:" + echo "$FILES" + + # Extract and clean file paths + - name: Extract File Paths + if: env.FILES != '' + run: | + # Extract lines starting with './' but ignore any paths following "Modified files:" until a stop marker + files_clean=$(echo "$FILES" | awk '/^Modified files:/ {ignore = 1} /^Above is a list of files/ {ignore = 0} !ignore && /^\.\// {print}' | sort | uniq) + # Save the cleaned files into a new environment variable 'FILES_CLEAN' + echo "FILES_CLEAN<> $GITHUB_ENV + echo "$files_clean" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + echo "Extracted Paths: $files_clean" + - name: Debug Extracted Paths + run: | + echo "Extracted Paths:" + echo "$FILES_CLEAN" + echo "---------------------------------" + - name: Comment on PR or Issue + if: env.FILES_CLEAN != '' + uses: actions/github-script@v7 + with: + script: | + const formattedOutput = process.env.FILES_CLEAN; + const issueNumber = context.issue.number || context.payload.pull_request.number; + const owner = context.repo.owner; + const repo = context.repo.repo; + if (formattedOutput) { + const commentBody = `Our automated SPDX license verification process has discovered that the following files are missing a license header:\n\`\`\`\n${formattedOutput}\n\`\`\`\nPlease ensure each indicated file includes a valid SPDX license identifier. This is essential for maintaining licensing compliance. Your attention and cooperation in updating these files are greatly appreciated. Thank you.`; + await github.rest.issues.createComment({ + issue_number: issueNumber, + owner: owner, + repo: repo, + body: commentBody + }); + core.setFailed("SPDX license issues found."); + } else { + console.log("No SPDX license issues found."); + } \ No newline at end of file diff --git a/.github/workflows/frontend-lint-license-checker.yml b/.github/workflows/frontend-lint-license-checker.yml new file mode 100644 index 00000000..1156cced --- /dev/null +++ b/.github/workflows/frontend-lint-license-checker.yml @@ -0,0 +1,148 @@ +name: Front-End Linter SPDX Licenses Checker + +on: + push: + branches: + - main + pull_request: + branches: + - "main" + - "staging" + types: + - opened + - reopened + - synchronize + - assigned + - review_requested + +jobs: + lint: + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + with: + token: ${{ secrets.GITHUB_TOKEN }} + + - name: Set up Node.js + uses: actions/setup-node@v3 + with: + node-version: '16' + + - name: Install dependencies + working-directory: app/frontend + run: npm install + + - name: Run ESLint with Auto-fix + working-directory: app/frontend + run: | + set +e + npm run lint || true # Run lint and allow the workflow to continue even if there are warnings/errors + + # Run ESLint and Capture Output + - name: Run ESLint and Capture Output + working-directory: app/frontend + id: run_eslint + run: | + set +e + output=$(npm run lint --silent 2>&1) + exit_code=$? + echo "$output" + clean_output=$(echo "$output" | sed 's/\x1b\[[0-9;]*m//g') # Remove ANSI escape codes + echo "CLEAN_OUTPUT<> $GITHUB_ENV + echo "$clean_output" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + + grouped_errors="" + current_file="" + errors_for_file="" + has_errors=false + missing_lc_headers=false + lc_flagged_files="" + + while IFS= read -r line; do + if echo "$line" | grep -q '^\s*\/'; then + if [ "$has_errors" = true ]; then + grouped_errors+="$current_file\n$errors_for_file\n------------------------------------------------------------------------------------------------------------------------------------------\n" + errors_for_file="" + has_errors=false + fi + current_file=$(echo "$line" | sed 's/\n//g') + elif echo "$line" | grep -q 'error'; then + errors_for_file+=" $line\n" + has_errors=true + + if echo "$line" | grep -q 'missing header'; then + missing_lc_headers=true + errors_for_file+="!Flagged: LC header missing\n" + lc_flagged_files+="${current_file}\n" + fi + fi + done <<< "$clean_output" + + if [ "$has_errors" = true ]; then + grouped_errors+="$current_file\n$errors_for_file\n" + fi + + if [ -n "$grouped_errors" ]; then + echo "Errors found." + echo "GROUPED_ERRORS<> $GITHUB_ENV + echo -e "$grouped_errors" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + echo "HAS_ERRORS=true" >> $GITHUB_ENV + else + echo "No relevant errors found." + echo "HAS_ERRORS=false" >> $GITHUB_ENV + fi + + if [ "$missing_lc_headers" = true ]; then + echo "LC headers missing in one or more files." + echo "MISSING_LC_HEADERS=true" >> $GITHUB_ENV + echo "LC_FLAGGED_FILES<> $GITHUB_ENV + echo -e "$(echo -e "$lc_flagged_files" | sed '/^\s*$/d')" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + else + echo "MISSING_LC_HEADERS=false" >> $GITHUB_ENV + fi + + exit 0 + + # Comment on PR with ESLint Errors and LC Headers + - name: Comment on PR with ESLint Errors and LC Headers + if: env.MISSING_LC_HEADERS == 'true' # Ensure we only comment if there are missing license headers + uses: actions/github-script@v7 + with: + script: | + const lintErrors = process.env.GROUPED_ERRORS; + const issueNumber = context.payload.pull_request.number; + const owner = context.repo.owner; + const repo = context.repo.repo; + + let commentBody = ""; + + if (process.env.MISSING_LC_HEADERS === 'true') { + const flaggedFiles = process.env.LC_FLAGGED_FILES.trim(); + commentBody += `## 🚨 SPDX-License Header Errors\n\nThe following files are missing the required license headers:\n\n\`\`\`\n${flaggedFiles}\n\`\`\`\nPlease ensure each of these files includes a valid SPDX license identifier to maintain licensing compliance.`; + } + + if (lintErrors && process.env.MISSING_LC_HEADERS === 'true') { + commentBody += `\n\n## Frontend Project: ESLint Errors\n\`\`\`\n${lintErrors}\n\`\`\`\nPlease review and resolve the ESLint errors.`; + } + + if (commentBody.trim() && issueNumber) { + await github.rest.issues.createComment({ + issue_number: issueNumber, + owner: owner, + repo: repo, + body: commentBody + }); + } else { + console.log("No relevant errors to report."); + } + + - name: Fail the Workflow if LC Headers Are Missing + if: env.MISSING_LC_HEADERS == 'true' + run: | + echo "Failing the workflow because LC headers are missing." + exit 1 diff --git a/.gitignore b/.gitignore index faf1926d..d1bce633 100644 --- a/.gitignore +++ b/.gitignore @@ -7,6 +7,7 @@ __pycache__ *egg-info *.whl +.venv/ # Virtual Environment env @@ -37,3 +38,6 @@ db.sqlite3 # unignore !requirements.txt +!app/frontend/third-party-licenses.txt +!requirements-dev.txt + diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 00000000..f09ba8c4 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,9 @@ +repos: +- repo: https://github.com/astral-sh/ruff-pre-commit + # Ruff version. + rev: v0.7.0 + hooks: + # Run the linter. + - id: ruff + # Run the formatter. + - id: ruff-format \ No newline at end of file diff --git a/FAQ.md b/FAQ.md new file mode 100644 index 00000000..42a1ef27 --- /dev/null +++ b/FAQ.md @@ -0,0 +1,41 @@ +# Frequently Asked Questions + +## Table of Contents +1. [Frontend Does Not Load](#frontend-does-not-load) +2. [Module not found](#module-not-found-error) + +## Frontend Does Not Load + +If the frontend app has not loaded despite running `docker compose up --build`, there is likely an issue with docker using cached files. Check if the `node_modules` directory has been created in `tt-studio/app/frontend`. If this directory is missing, this usually means that `npm (Node Package Manager)` did not successfully run and docker has skipped running this since it used layer caching. To resolve run the following: + +```bash +docker compose build --no-cache +docker compose up +``` + +## Module not found error + +This error often occurs due to missing or corrupted dependencies. Here's a quick fix: + +1. Delete `node_modules` and `package-lock.json`: + + +```shellscript +rm -rf node_modules package-lock.json +``` + +2. Reinstall dependencies: + + +```shellscript +cd frontend +npm i +``` + +3. Re-run App using docker: + + +```shellscript +docker compose down +docker compose up --build +``` diff --git a/HowToRun_vLLM_Models.md b/HowToRun_vLLM_Models.md new file mode 100644 index 00000000..fa30371d --- /dev/null +++ b/HowToRun_vLLM_Models.md @@ -0,0 +1,247 @@ +# Running Llama3.1-70B and Mock vLLM Models in TT-Studio + +This guide provides step-by-step instructions on setting up and deploying vLLM Llama3.1-70B and vLLM Mock models using TT-Studio. + +--- + +## Prerequisites + +1. **Docker**: Make sure Docker is installed on your system. Follow the [Docker installation guide](https://docs.docker.com/engine/install/). + +2. **Hugging Face Token**: Both models require authentication to Hugging Face repositories. To obtain a token, go to [Hugging Face Account](https://huggingface.co/settings/tokens) and generate a token. Additionally; make sure to accept the terms and conditions on Hugging Face for the Llama3.1 models by visiting [Hugging Face Meta-Llama Page](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct). + +3. **Model Access Weight**: To access specific models like Llama3.1, you may need to register with Meta to obtain download links for model weights. Visit [Llama Downloads](https://www.llama.com/llama-downloads/) for more information. +--- + +## Instructions Overview + +### **For Mock vLLM Model:** +1. [Clone repositories](#1-clone-required-repositories) +2. [Pull the mock model Docker image](#2-pull-the-desired-model-docker-images-using-docker-github-registry) +3. [Set up the Hugging Face (HF) token](#3-set-up-environment-variables-and-hugging-face-token) +4. [Run the mock vLLM model via the GUI](#7-deploy-and-run-the-model) + +### **For vLLM Llama3.1-70B Model:** +1. [Clone repositories](#1-clone-required-repositories) +2. [Pull the model Docker image](#2-pull-the-desired-model-docker-images-using-docker-github-registry) +3. [Set up the Hugging Face (HF) token in the TT-Studio `.env` file](#3-set-up-environment-variables-and-hugging-face-token) +4. [Run the model setup script](#4-run-the-setup-script-vllm-llama31-70b-only) +5. [Update the vLLM Environment Variable in Environment File](#6-add-the-vllm-environment-variable-in-environment-file--copy-the-file-over-to-tt-studio-persistent-volume) +6. [Deploy and run inference for the Llama3.1-70B model via the GUI](#7-deploy-and-run-the-model) + +--- + +## 1. Clone Required Repositories + +Start by cloning both the `tt-studio` and `tt-inference-server` repositories. + +```bash +# Clone tt-studio +git clone https://github.com/tenstorrent/tt-studio +cd tt-studio + +# Make the setup script executable +chmod +x startup.sh + +# Clone `tt-inference-server` into a separate directory +cd .. +git clone https://github.com/tenstorrent/tt-inference-server +``` + +--- + +## 2. Pull the Desired Model Docker Images Using Docker GitHub Registry + +1. **Navigate to the Docker Images:** + - Visit [TT-Inference-Server GitHub Packages](https://github.com/orgs/tenstorrent/packages?repo_name=tt-inference-server). + +2. **Pull the Docker Image:** + ```bash + docker pull ghcr.io/tenstorrent/tt-inference-server: + ``` + +3. **Authenticate Your Terminal (Optional):** + ```bash + echo YOUR_PAT | docker login ghcr.io -u YOUR_USERNAME --password-stdin + ``` + +--- + +## 3. Set Up Environment Variables and Hugging Face Token + +Add the Hugging Face Token within the `.env` file in the `tt-studio/app/` directory. + +```bash +HF_TOKEN=hf_******** +``` + +--- + +## 4. Run the Setup Script (vLLM Llama3.1-70B only) + +Follow these step-by-step instructions for a smooth automated process of model weights setup. + +1. **Navigate to the `vllm-tt-metal-llama3-70b/` folder** within the `tt-inference-server`. This folder contains the necessary files and scripts for model setup. + +2. **Run the automated setup script** as outlined in the [official documentation](https://github.com/tenstorrent/tt-inference-server/tree/main/vllm-tt-metal-llama3-70b#5-automated-setup-environment-variables-and-weights-files:~:text=70b/docs/development-,5.%20Automated%20Setup%3A%20environment%20variables%20and%20weights%20files,-The%20script%20vllm). This script handles key steps such as configuring environment variables, downloading weight files, repacking weights, and creating directories. + +**Note** During the setup process, you will see the following prompt: + + ``` + Enter your PERSISTENT_VOLUME_ROOT [default: tt-inference-server/tt_inference_server_persistent_volume]: + ``` + + **Do not accept the default path.** Instead, set the persistent volume path to `tt-studio/tt_studio_persistent_volume`. This ensures the configuration matches TT-Studio’s directory structure. Using the default path may result in incorrect configuration. + +By following these instructions, you will have a properly configured model infrastructure, ready for inference and further development. + + + +--- + +## 5. Folder Structure for Model Weights + +Verify that the weights are correctly stored in the following structure: + +```bash +/path/to/tt-studio/tt_studio_persistent_volume/ +└── volume_id_tt-metal-llama-3.1-70b-instructv0.0.1/ + β”œβ”€β”€ layers_0-4.pth + β”œβ”€β”€ layers_5-9.pth + β”œβ”€β”€ params.json + └── tokenizer.model +``` + +**What to Look For:** +- Ensure all expected weight files (e.g., `layers_0-4.pth`, `params.json`, `tokenizer.model`) are present. +- If any files are missing, re-run the `setup.sh` script to complete the download. + +This folder structure allows TT Studio to automatically recognize and access models without further configuration adjustments. For each model, verify that the weights are correctly copied to this directory to ensure proper access by TT Studio. + + +## 6. Copy the Environment File and Point to it in TT-Studio + +### Step 1: Copy the Environment File +During the model weights download process, an `.env` file will be automatically created. The path to the `.env` file might resemble the following example: + +``` +/path/to/tt-inference-server/vllm-tt-metal-llama3-70b/.env +``` + +To ensure the model can be deployed via the TT-Studio GUI, this `.env` file must be copied to the model's persistent storage location. For example: + +```bash +/path/to/tt_studio_persistent_volume/volume_id_tt-metal-llama-3.1-70b-instructv0.0.1/copied_env +``` + +The following command can be used as a reference (*replace paths as necessary*): + +```bash +sudo cp /$USR/tt-inference-server/vllm-tt-metal-llama3-70b/.env /$USR/tt_studio/tt_studio_persistent_volume/volume_id_tt-metal-llama-3.1-70b-instructv0.0.1/.env +``` + +### Step 2: Point to the Copied Environment File +The `VLLM_LLAMA31_ENV_FILE` variable within the TT-Studio `$USR/tt-studio/app/.env` file must point to *this* copied `.env` file. This should be a **relative path**, for example it can be set as follows: + +``` +VLLM_LLAMA31_ENV_FILE="/tt_studio_persistent_volume/volume_id_tt-metal-llama-3.1-70b-instructv0.0.1/.env" +``` +--- + +### Step 2: Update the TT-Studio Environment File +After copying the `.env` file, update the `VLLM_LLAMA31_ENV_FILE` variable in the `tt-studio/app/.env` file to point to the **copied file path**. This ensures TT-Studio uses the correct environment configuration for the model. + +```bash +VLLM_LLAMA31_ENV_FILE="/path/to/tt_studio_persistent_volume/volume_id_tt-metal-llama-3.1-70b-instructv0.0.1/copied_env" +``` + +--- +Here is an example of a complete `.env` file configuration for reference: + +```bash +TT_STUDIO_ROOT=/Users/**username**/tt-studio +HOST_PERSISTENT_STORAGE_VOLUME=${TT_STUDIO_ROOT}/tt_studio_persistent_volume +INTERNAL_PERSISTENT_STORAGE_VOLUME=/tt_studio_persistent_volume +BACKEND_API_HOSTNAME="tt-studio-backend-api" +VLLM_LLAMA31_ENV_FILE="/path/to/tt_studio_persistent_volume/volume_id_tt-metal-llama-3.1-70b-instructv0.0.1/**copied_env +# SECURITY WARNING: keep these secret in production! +JWT_SECRET=test-secret-456 +DJANGO_SECRET_KEY=django-insecure-default +HF_TOKEN=hf_**** +``` + +--- + +## 7. Deploy and Run the Model + +1. **Start TT-Studio:** Run TT-Studio using the startup command. +2. **Access Model Weights:** In the TT-Studio interface, navigate to the model weights section. +3. **Select Custom Weights:** Use the custom weights option to select the weights for Llama3.1-70B. +4. **Run the Model:** Start the model and wait for it to initialize. + +--- + +## Troubleshooting + +### Verify Model Container Functionality + +#### i. View Container Logs + +To view real-time logs from the container, use the following command: + +```bash +docker logs -f +``` + +During container initialization, you may encounter log entries like the following, which indicate that the vLLM server has started successfully: + +```bash +INFO 12-11 08:10:36 tt_executor.py:67] # TT blocks: 2068, # CPU blocks: 0 +INFO 12-11 08:10:36 tt_worker.py:66] Allocating kv caches +INFO 12-11 08:10:36 api_server.py:232] vLLM to use /tmp/tmp3ki28i0p as PROMETHEUS_MULTIPROC_DIR +INFO 12-11 08:10:36 launcher.py:19] Available routes are: +INFO 12-11 08:10:36 launcher.py:27] Route: /openapi.json, Methods: GET, HEAD +INFO 12-11 08:10:36 launcher.py:27] Route: /docs, Methods: GET, HEAD +INFO 12-11 08:10:36 launcher.py:27] Route: /docs/oauth2-redirect, Methods: GET, HEAD +INFO 12-11 08:10:36 launcher.py:27] Route: /redoc, Methods: GET, HEAD +INFO 12-11 08:10:36 launcher.py:27] Route: /health, Methods: GET +INFO 12-11 08:10:36 launcher.py:27] Route: /tokenize, Methods: POST +INFO 12-11 08:10:36 launcher.py:27] Route: /detokenize, Methods: POST +INFO 12-11 08:10:36 launcher.py:27] Route: /v1/models, Methods: GET +INFO 12-11 08:10:36 launcher.py:27] Route: /version, Methods: GET +INFO 12-11 08:10:36 launcher.py:27] Route: /v1/chat/completions, Methods: POST +INFO 12-11 08:10:36 launcher.py:27] Route: /v1/completions, Methods: POST +INFO: Application startup complete. +``` + +--- + +#### ii. Access the Container Shell + +To access the container's shell for debugging or manual inspection, use the following command: + +```bash +docker exec -it bash +``` + +Use `env` to check environment variables or run commands directly to inspect the environment. To verify if the server is running properly, you can attempt to manually start it by running: + +```bash +python ***_vllm_api_server.py +``` + +This will allow you to check for any startup errors or issues directly from the container's shell. + +--- + +#### iii. Send Test Requests to the vLLM Server + +```bash +curl -s --no-buffer -X POST "http://localhost:7000/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer $TOKEN" -d '{"model":"meta-llama/Llama-3.1-70B-Instruct","messages":[{"role":"system","content":"You are a helpful assistant."},{"role":"user","content":"Hi"}]}' +``` +If successful, you will receive a response from the model. + + +## You're All Set πŸŽ‰ + +With the setup complete, you’re ready to run inference on the vLLM models (or any other supported model(s)) within TT-Studio. Refer to the documentation and setup instructions in the repositories for further guidance. \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 00000000..6059935c --- /dev/null +++ b/LICENSE @@ -0,0 +1,202 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + +------------------------------------------------------------------------------- + Copyright (c) 2024 Tenstorrent AI ULC + +------------------------------------------------------------------------------- +Third-Party Dependencies: + +The following dependencies are utilized by this project but are not explicitly +distributed as part of the software: + +- Django [License available here](https://github.com/django/django/blob/main/LICENSE) +- Docker [License available here](https://github.com/docker/docs/blob/main/LICENSE) +- shadcn/ui [License available here](https://github.com/shadcn/ui/blob/main/LICENSE.md) +- Third Party Libraries used in Frontend Product [License available here](app/frontend/third-party-licenses.txt) \ No newline at end of file diff --git a/README.md b/README.md index 970f6877..e4a2cf4d 100644 --- a/README.md +++ b/README.md @@ -1,64 +1,169 @@ # TT-Studio -Deploy LLM inference servers locally as fast as possible using Tenstorrent hardware. +TT-Studio enables rapid deployment of TT Inference servers locally and is optimized for Tenstorrent hardware. This guide explains how to set up and use TT-Studio in both standard and development modes. -## Quick start +## Table of Contents -### 1. Download and run -```bash -git clone https://github.com/tenstorrent/tt-studio.git -cd tt-studio -. startup.sh -``` +1. [Prerequisites](#prerequisites) +2. [Overview](#overview) +3. [Quick Start](#quick-start) + - [For General Users](#for-general-users) + - [For Developers](#for-developers) +4. [Using `startup.sh`](#using-startupsh) + - [Basic Usage](#basic-usage) + - [Command-Line Options](#command-line-options) + - [Automatic Tenstorrent Hardware Detection](#automatic-tenstorrent-hardware-detection) +5. [Documentation](#documentation) + - [Frontend Documentation](#frontend-documentation) + - [Backend API Documentation](#backend-api-documentation) + - [Running Llama3.1-70B in TT-Studio](#running-llama31-70b-in-tt-studio) -## Running on machine with Tenstorrent hardware -You can check for connected Tenstorrent hardware via: -```bash -ls -l /dev/tenstorrent -``` +--- +## Prerequisites +1. Docker: Ensure that Docker is installed on your machine. You can refer to the installation guide [here](https://docs.docker.com/engine/install/). -__NOTE:__ For running ML models on Tenstorrent hardware you must uncomment the following lines in `app/docker-compose.yml`: -``` - # uncomment devices to use Tenstorrent hardware - # devices: - # # mount all tenstorrent devices to backend container - # - /dev/tenstorrent:/dev/tenstorrent -``` +--- +## Quick Start + +### For General Users + +To set up TT-Studio: + +1. **Clone the Repository**: + + ```bash + git clone https://github.com/tenstorrent/tt-studio.git + cd tt-studio + ``` + +2. **Run the Startup Script**: + + Run the `startup.sh` script: + + ```bash + ./startup.sh + ``` + + #### See this [section](#command-line-options) for more information on command-line arguments available within the startup script. + +3. **Access the Application**: + + The app will be available at [http://localhost:3000](http://localhost:3000). + +4. **Cleanup**: + - To stop and remove Docker services, run: + ```bash + ./startup.sh --cleanup + ``` +5. Running on a Remote Machine + + To forward traffic between your local machine and a remote server, enabling you to access the frontend application in your local browser, follow these steps: + + Use the following SSH command to port forward both the frontend and backend ports: + + ```bash + # Port forward frontend (3000) to allow local access from the remote server + ssh -L 3000:localhost:3000 @ + ``` + +> ⚠️ **Note**: To use Tenstorrent hardware, during the run of `startup.sh` script, select "yes" when prompted to mount hardware. This will automatically configure the necessary settings, eliminating manual edits to docker compose.yml. +--- + +### For Developers -## Running on remote machine +Developers can control and run the app directly via `docker compose`, keeping this running in a terminal allows for hot reload of the frontend app. For any backend changes its advisable to re restart the services. + +1. **Run in Development Mode**: + + ```bash + cd tt-studio/app + docker compose up --build + ``` + +2. **Stop the Services**: + + ```bash + docker compose down + ``` + +3. **Using the Mock vLLM Model**: + - For local testing, you can use the `Mock vLLM` model, which spits out random set of characters back . Instructions to run it are [here](HowToRun_vLLM_Models.md) + + +4. **Running on a Machine with Tenstorrent Hardware**: + + To run TT-Studio on a device with Tenstorrent hardware, you need to uncomment specific lines in the `app/docker-compose.yml` file. Follow these steps: + + 1. Navigate to the `app` directory: + + ```bash + cd app/ + ``` + + 2. Open the `docker-compose.yml` file in an editor (e.g., `vim` or a code editor like `VS CODE` ): + + ```bash + vim docker-compose.yml + # or + code docker-compose.yml + ``` + + 3. Uncomment the following lines that have a `! flag` in front of them to enable Tenstorrent hardware support: + ```yaml + #* DEV: Uncomment devices to use Tenstorrent hardware + #! devices: + #* mounts all Tenstorrent devices to the backend container + #! - /dev/tenstorrent:/dev/tenstorrent + ``` + By uncommenting these lines, Docker will mount the Tenstorrent device (`/dev/tenstorrent`) to the backend container. This allows the docker container to utilize the Tenstorrent hardware for running machine learning models directly on the card. + +--- + +## Using `startup.sh` + +The `startup.sh` script automates the TT-Studio setup process. It can be run with or without Docker, depending on your usage scenario. + +### Basic Usage + +To use the startup script, run: -To correct forward traffic to/from the remote server so that you can use the frontend GUI on your local browser: ```bash -# port forward frontend and backend ports to -ssh -L 3000:localhost:3000 @ +./startup.sh [options] ``` -## Run local for development +### Command-Line Options -To develop locally without running ML models you can keep commented out the following lines in `app/docker-compose.yml`: -``` - # uncomment devices to use Tenstorrent hardware - # devices: - # # mount all tenstorrent devices to backend container - # - /dev/tenstorrent:/dev/tenstorrent -``` +| Option | Description | +| --------------- | ------------------------------------------------------------- | +| `--help` | Display help message with usage details. | +| `--setup` | Run the `setup.sh` script with sudo privileges for all steps. | +| `--cleanup` | Stop and remove all Docker services. | -For local development use the echo model that implementats flask inference API server but merely repeats the prompt. On first run you will need to build that Docker image, see [models/dummy_echo_model/README.md](models/dummy_echo_model/README.md). +To display the same help section in the terminal, one can run: -# Documentation +```bash +./startup.sh --help +``` +##### Automatic Tenstorrent Hardware Detection -## Frontend +If a Tenstorrent device (`/dev/tenstorrent`) is detected, the script will prompt you to mount it. -See frontend usage and development docs: [app/frontend/README.md](app/frontend/README.md) +--- -## Backend API +## Documentation -The backend API is a Django Rest Framework (DRF) app that implements an API to manage the model implementations containers. +- **Frontend Documentation**: [app/frontend/README.md](app/frontend/README.md) + Detailed documentation about the frontend of TT Studio, including setup, development, and customization guides. -See API docs usage and development docs: [app/api/README.md](app/api/README.md) +- **Backend API Documentation**: [app/api/README.md](app/api/README.md) + Information on the backend API, powered by Django Rest Framework, including available endpoints and integration details. -## Model Implementations +- **Running vLLM Llama3.1-70B and vLLM Mock Model(s) in TT-Studio**: [HowToRun_vLLM_Models.md](HowToRun_vLLM_Models.md) + Step-by-step instructions on how to configure and run the vLLM model(s) using TT-Studio. -See model docs usage and development docs: [models/README.md](models/README.md) +- **Contribution Guide**: [CONTRIBUTING.md](CONTRIBUTING.md) + If you’re interested in contributing to the project, please refer to our contribution guidelines. This includes setting up a development environment, code standards, and the process for submitting pull requests. +- **Frequently Asked Questions (FAQ)**: [FAQ.md](FAQ.md) + A compilation of frequently asked questions to help users quickly solve common issues and understand key features of TT-Studio. diff --git a/add_spdx_header.py b/add_spdx_header.py new file mode 100644 index 00000000..a9886016 --- /dev/null +++ b/add_spdx_header.py @@ -0,0 +1,40 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from pathlib import Path +from datetime import datetime + +current_year = datetime.now().year + +SPDX_HEADER = f"""# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© {current_year} Tenstorrent AI ULC +""" + + +def add_spdx_header(file_path): + """ + Adds the SPDX header to the file if it doesn't already contain it. + """ + with open(file_path, "r+") as file: + content = file.read() + if "SPDX-License-Identifier" not in content: + file.seek(0, 0) + file.write(SPDX_HEADER + "\n" + content) + + +if __name__ == "__main__": + # Define the repo root and directories to process + repo_root = Path(__file__).resolve().parent.parent + directories_to_process = [ + repo_root / "tt-studio/app/api", + repo_root / "tt-studio/models", + ] + + # Walk through the directories and add the header to relevant files + for directory in directories_to_process: + for file_path in directory.rglob("*"): + # Check if the file is a Python file, Bash script, or Dockerfile + if file_path.suffix in (".py", ".sh") or file_path.name == "Dockerfile": + add_spdx_header(file_path) diff --git a/app/.env.default b/app/.env.default index e074f453..6b6f24ba 100644 --- a/app/.env.default +++ b/app/.env.default @@ -2,6 +2,8 @@ TT_STUDIO_ROOT= HOST_PERSISTENT_STORAGE_VOLUME=${TT_STUDIO_ROOT}/tt_studio_persistent_volume INTERNAL_PERSISTENT_STORAGE_VOLUME=/tt_studio_persistent_volume BACKEND_API_HOSTNAME="tt-studio-backend-api" +VLLM_LLAMA31_ENV_FILE="" # SECURITY WARNING: keep these secret in production! JWT_SECRET=test-secret-456 DJANGO_SECRET_KEY=django-insecure-default +HF_TOKEN= # Get this from Hugging Face diff --git a/app/README.md b/app/README.md index d463ef3f..666d140a 100644 --- a/app/README.md +++ b/app/README.md @@ -2,29 +2,32 @@ Manage your LLM inference server containers. -## Deployment +## Deployment The backend app uses docker-compose.yml to configure the connection with the host, this included the persistent storage volume, ports, etc + ```bash docker compose up ``` -The `startup.sh` script automates the management of the environment variables and docker networks that must be conifgured outside of docker compose. +The `startup.sh` script automates the management of the environment variables and docker networks that must be configured outside of docker compose. ### Environment variables Environment variables are defined in `.env`, `.env.default` is a template you can use + ```bash cp .env.default .env # edit JWT_SECRET vim .env ``` -Note: the backend runs inside a container, because of this it does not have access to the host file system directly to programmatically determine it's relative path. +Note: the backend runs inside a container, because of this it does not have access to the host file system directly to programmatically determine it's relative path. ## Clean up To remove all containers + ```bash # this stops all containers docker stop $(docker ps -q) @@ -35,11 +38,13 @@ docker container prune ## Development Run the backend and frontend server interactively: + ```bash docker compose up ``` To force rebuilding the Docker images: + ```bash docker compose up --build ``` @@ -50,5 +55,8 @@ The local files in `./api` are mounted to `/api` within the container for develo ./manage.py runserver 0.0.0.0:8000 ``` +# Models: +# Llama Model Setup and Inference Guide +For detailed instructions on setting up and running Llama models, including Llama 3.1 70B in TT Studio, refer to [this guide](../HowToRunLlama3.1-70b.md) diff --git a/app/api/Dockerfile b/app/api/Dockerfile index 969fd930..ed7b6d1f 100644 --- a/app/api/Dockerfile +++ b/app/api/Dockerfile @@ -1,15 +1,38 @@ -FROM python:3.12.1-slim-bullseye + + +FROM python:3.12.5-slim-bookworm + ENV PYTHONUNBUFFERED=1 EXPOSE 8000 # debug tools RUN apt-get update && \ - apt-get install -y \ - procps \ - net-tools \ - iputils-ping \ - dnsutils && \ - rm -rf /var/lib/apt/lists/* + apt-get install -y \ + procps \ + net-tools \ + iputils-ping \ + python3-dev \ + build-essential \ + libsqlite3-dev \ + dnsutils && \ + rm -rf /var/lib/apt/lists/* + +RUN apt-get update && \ + apt-get install -y \ + git \ + curl \ + cargo + +# Install Rust +RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y + +# Add Rust to PATH +ENV PATH="/root/.cargo/bin:${PATH}" + +# Clone and install tt-smi +RUN git clone https://github.com/tenstorrent/tt-smi /tmp/tt-smi && \ + cd /tmp/tt-smi && \ + pip3 install . WORKDIR /api COPY ./requirements.txt /api diff --git a/app/api/README.md b/app/api/README.md index 9b2244f6..63fa9f03 100644 --- a/app/api/README.md +++ b/app/api/README.md @@ -56,7 +56,7 @@ example JSON response: ] }, "networks": { - "llm_studio_network": { + "tt_studio_network": { "DNSNames": [ "dummy_echo_model_p8013", "1d1a274a7126" @@ -148,30 +148,21 @@ The environment variables MODEL_WEIGHTS_ID and MODEL_WEIGHTS_PATH are then set a docker build -t ghcr.io/tenstorrent/tt-studio/api:v0.0.0 . ``` -## Docker run +## Developing and running tests -Using docker-compose.yml is recommended for development, but `docker run` can be useful sometimes, here is an example: +### Docker compose + +```bash +# only start backend service, without deps +docker compose up --no-deps tt_studio_backend tt_studio_chroma +``` + +### Run tests + +enter the container with another shell (e.g. using `docker exec`): ```bash -cd app -source .env -docker run \ - --user user \ - --rm \ - --cap-add ALL \ - --detach \ - --env JWT_SECRET=test-secret-123 \ - --env CACHE_ROOT=/home/user/cache_root \ - --env HF_HOME=/home/user/cache_root/huggingface \ - --volume ${HOST_PERSISTENT_STORAGE_VOLUME}:${INTERNAL_PERSISTENT_STORAGE_VOLUME} \ - --volume /dev/hugepages-1G:/dev/hugepages-1G:rw \ - --volume /tt-studio/models/tt-metal-falcon-7b/src:/home/user/tt-metal-falcon-7b/src:rw \ - --shm-size 32G \ - --device /dev/tenstorrent/0:/dev/tenstorrent/0 \ - --publish 8001:7000 \ - --network llm_studio_network \ - --name tt-metal-falcon-7b_p8001 \ - --hostname tt-metal-falcon-7b_p8001 \ - ghcr.io/tenstorrent/tt-studio/tt-metal-falcon-7b:v0.0.13 sleep infinity +cd api +pytest --log-cli-level=INFO docker_control/test_docker_utils.py::test_deploy_mock_model ``` ## Development Notes @@ -182,6 +173,7 @@ Gunicorn is used for production but does not allow for easily adding breakpoints # run with --noreload to stop auto reload ``` +docker ps -q | grep -v CONTAINER_ID | xargs -r docker stop # Testing ```bash diff --git a/app/api/api/__init__.py b/app/api/api/__init__.py index e69de29b..4da24a6e 100644 --- a/app/api/api/__init__.py +++ b/app/api/api/__init__.py @@ -0,0 +1,4 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + diff --git a/app/api/api/asgi.py b/app/api/api/asgi.py index 57b0c31a..51260953 100644 --- a/app/api/api/asgi.py +++ b/app/api/api/asgi.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + """ ASGI config for api project. diff --git a/app/api/api/settings.py b/app/api/api/settings.py index 63a5dfb8..ea7dacb4 100644 --- a/app/api/api/settings.py +++ b/app/api/api/settings.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + """ Django settings for api project. @@ -10,15 +14,14 @@ https://docs.djangoproject.com/en/4.2/ref/settings/ """ -from pathlib import Path import os +from pathlib import Path from shared_config.backend_config import backend_config # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent - # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/4.2/howto/deployment/checklist/ @@ -52,7 +55,9 @@ "django.contrib.staticfiles", "docker_control", "model_control", + "vector_db_control", "corsheaders", + "logs_control", ] MIDDLEWARE = [ @@ -85,7 +90,7 @@ ] WSGI_APPLICATION = "api.wsgi.application" - +SESSIONS_ENGINE = "django.contrib.sessions.backends.cache" # Database # https://docs.djangoproject.com/en/4.2/ref/settings/#databases @@ -122,7 +127,6 @@ }, ] - # Internationalization # https://docs.djangoproject.com/en/4.2/topics/i18n/ @@ -134,7 +138,6 @@ USE_TZ = True - # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/4.2/howto/static-files/ @@ -144,3 +147,13 @@ # https://docs.djangoproject.com/en/4.2/ref/settings/#default-auto-field DEFAULT_AUTO_FIELD = "django.db.models.BigAutoField" + +CHROMA_DB_PORT = int(os.environ.get("CHROMA_DB_PORT", 8111)) +CHROMA_DB_HOST = os.environ.get("CHROMA_DB_HOST", "tt_studio_chromadb") +CHROMA_DB_EMBED_MODEL = "all-MiniLM-L6-v2" + +REST_FRAMEWORK = { + "DEFAULT_AUTHENTICATION_CLASSES": [], + "DEFAULT_PERMISSION_CLASSES": [], + "UNAUTHENTICATED_USER": None, +} diff --git a/app/api/api/urls.py b/app/api/api/urls.py index 628cc033..47b53d6c 100644 --- a/app/api/api/urls.py +++ b/app/api/api/urls.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + """ URL configuration for api project. @@ -16,10 +20,15 @@ """ from django.contrib import admin +from api.views import UpStatusView from django.urls import include, path urlpatterns = [ path("admin/", admin.site.urls), + path("up/", UpStatusView.as_view()), path("docker/", include("docker_control.urls")), path("models/", include("model_control.urls")), + path("reset_board/", include("docker_control.urls")), + path("collections/", include("vector_db_control.urls")), + path("logs/", include("logs_control.urls")), ] diff --git a/app/api/api/views.py b/app/api/api/views.py new file mode 100644 index 00000000..166573c7 --- /dev/null +++ b/app/api/api/views.py @@ -0,0 +1,11 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from rest_framework.views import APIView +from rest_framework.response import Response + + +class UpStatusView(APIView): + def get(self, request, *args, **kwargs): + return Response(status=200) diff --git a/app/api/api/wsgi.py b/app/api/api/wsgi.py index bfbc45aa..553e8d70 100644 --- a/app/api/api/wsgi.py +++ b/app/api/api/wsgi.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + """ WSGI config for api project. diff --git a/app/api/docker_control/__init__.py b/app/api/docker_control/__init__.py index e69de29b..4da24a6e 100644 --- a/app/api/docker_control/__init__.py +++ b/app/api/docker_control/__init__.py @@ -0,0 +1,4 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + diff --git a/app/api/docker_control/admin.py b/app/api/docker_control/admin.py index 8c38f3f3..2c79060a 100644 --- a/app/api/docker_control/admin.py +++ b/app/api/docker_control/admin.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.contrib import admin # Register your models here. diff --git a/app/api/docker_control/apps.py b/app/api/docker_control/apps.py index ffe5e2a1..995234d9 100644 --- a/app/api/docker_control/apps.py +++ b/app/api/docker_control/apps.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.apps import AppConfig diff --git a/app/api/docker_control/docker_utils.py b/app/api/docker_control/docker_utils.py index 9224a02b..c9d1cc56 100644 --- a/app/api/docker_control/docker_utils.py +++ b/app/api/docker_control/docker_utils.py @@ -1,5 +1,9 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + # docker_control/docker_utils.py -import socket +import socket, os, subprocess import copy from pathlib import Path @@ -11,9 +15,10 @@ from shared_config.model_config import model_implmentations from shared_config.backend_config import backend_config + +CONFIG_PATH = "/root/.config/tenstorrent/reset_config.json" logger = get_logger(__name__) logger.info(f"importing {__name__}") - client = docker.from_env() # docker internal bridge network used for models and applications. @@ -194,14 +199,20 @@ def update_deploy_cache(): con["model_id"] = model_impl.model_id con["weights_id"] = con["env_vars"].get("MODEL_WEIGHTS_ID") con["model_impl"] = model_impl - hostname = con["networks"][backend_config.docker_bridge_network_name][ - "DNSNames" - ][0] - con["internal_url"] = ( - f"{hostname}:{model_impl.service_port}{model_impl.service_route}" - ) - caches[backend_config.django_deploy_cache_name].set(con_id, con, timeout=None) - # TODO: validation + logger.info(f"con['networks']={con["networks"]}") + # handle containers not running within the tt-studio network + if backend_config.docker_bridge_network_name in con["networks"].keys(): + hostname = con["networks"][backend_config.docker_bridge_network_name][ + "DNSNames" + ][0] + con["internal_url"] = ( + f"{hostname}:{model_impl.service_port}{model_impl.service_route}" + ) + con["health_url"] = ( + f"{hostname}:{model_impl.service_port}{model_impl.health_route}" + ) + caches[backend_config.django_deploy_cache_name].set(con_id, con, timeout=None) + # TODO: validation def get_model_weights_path(weights_dir_path, weights_id): @@ -220,3 +231,97 @@ def remove_id_prefix(s): dir_name = remove_id_prefix(weights_id) return weights_dir_path.joinpath(dir_name) + + +def perform_reset(): + try: + logger.info("Running initial tt-smi command to check device detection.") + + # Initial check to see if Tenstorrent devices are detected + def check_device_detection(): + process = subprocess.Popen( + ["tt-smi"], + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, + stdin=subprocess.DEVNULL, # Prevents interactive command-line interface + text=True, + ) + output = [] + for line in iter(process.stdout.readline, ""): + logger.info(f"tt-smi output: {line.strip()}") + output.append(line) + if "No Tenstorrent devices detected" in line: + return { + "status": "error", + "message": "No Tenstorrent devices detected! Please check your hardware and try again.", + "output": "".join(output), + "http_status": 501, # Not Implemented + } + process.stdout.close() + return_code = process.wait() + if return_code != 0: + return { + "status": "error", + "message": f"tt-smi command failed with return code {return_code}.", + "output": "".join(output), + "http_status": 500, # Internal Server Error + } + return {"status": "success", "output": "".join(output)} + + # Run the device detection check + detection_result = check_device_detection() + if detection_result.get("status") == "error": + return detection_result + + logger.info("Running tt-smi reset command.") + + def stream_command_output(command): + logger.info(f"Executing command: {' '.join(command)}") + process = subprocess.Popen( + command, + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, + stdin=subprocess.DEVNULL, # Prevents interactive command-line interface + text=True, + ) + output = [] + for line in iter(process.stdout.readline, ""): + logger.info(f"Command output: {line.strip()}") + output.append(line) + process.stdout.close() + return_code = process.wait() + if return_code != 0: + logger.info(f"Command failed with return code {return_code}") + output.append(f"Command failed with return code {return_code}") + return { + "status": "error", + "output": "".join(output), + "http_status": 500, # Internal Server Error + } + else: + logger.info( + f"Command completed successfully with return code {return_code}" + ) + return {"status": "success", "output": "".join(output)} + + # Step 1: Check if the reset config JSON already exists + if not os.path.exists(CONFIG_PATH): + generate_result = stream_command_output(["tt-smi", "--generate_reset_json"]) + if generate_result.get("status") == "error": + return generate_result + + # Step 2: Run the reset using the generated JSON + reset_result = stream_command_output(["tt-smi", "-r", CONFIG_PATH]) + return reset_result or { + "status": "error", + "output": "No output from reset command", + } + + except Exception as e: + logger.exception("Exception occurred during reset operation.") + return { + "status": "error", + "message": str(e), + "output": "An exception occurred during the reset operation.", + "http_status": 500, + } diff --git a/app/api/docker_control/forms.py b/app/api/docker_control/forms.py index 4a4f27b7..d154af1f 100644 --- a/app/api/docker_control/forms.py +++ b/app/api/docker_control/forms.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + # docker_control/forms.py from django import forms from shared_config.model_config import model_implmentations diff --git a/app/api/docker_control/migrations/__init__.py b/app/api/docker_control/migrations/__init__.py index e69de29b..4da24a6e 100644 --- a/app/api/docker_control/migrations/__init__.py +++ b/app/api/docker_control/migrations/__init__.py @@ -0,0 +1,4 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + diff --git a/app/api/docker_control/models.py b/app/api/docker_control/models.py index 71a83623..2d29716d 100644 --- a/app/api/docker_control/models.py +++ b/app/api/docker_control/models.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.db import models # Create your models here. diff --git a/app/api/docker_control/serializers.py b/app/api/docker_control/serializers.py index c237e08e..38533557 100644 --- a/app/api/docker_control/serializers.py +++ b/app/api/docker_control/serializers.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from pathlib import Path from rest_framework import serializers diff --git a/app/api/docker_control/test_docker_control_api.py b/app/api/docker_control/test_docker_control_api.py index d44a0c55..c9636556 100644 --- a/app/api/docker_control/test_docker_control_api.py +++ b/app/api/docker_control/test_docker_control_api.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import json import time @@ -6,107 +10,111 @@ from shared_config.backend_config import backend_config from shared_config.logger_config import get_logger +from shared_config.model_config import model_implmentations + +from .test_docker_utils import ( + wait_for_vllm_healthy_endpoint, + valid_api_call, + valid_vllm_api_call, +) + logger = get_logger(__name__) logger.info(f"importing {__name__}") -on_bridge_network = False -if on_bridge_network: - backend_host = "http://tt_studio_backend_api:8000/" -else: - backend_host = "http://0.0.0.0:8000/" +def create_auth_token(): + json_payload = json.loads('{"team_id": "tenstorrent", "token_id":"debug-test"}') + return jwt.encode(json_payload, backend_config.jwt_secret, algorithm="HS256") -def test_model_life_cycle(): - json_payload = json.loads('{"team_id": "tenstorrent", "token_id":"debug-test"}') - encoded_jwt = jwt.encode(json_payload, backend_config.jwt_secret, algorithm="HS256") - # 1. get list of models - get_containers_route = f"{backend_host}docker/get_containers/" - logger.info(f"calling: {get_containers_route}") - response = requests.get(get_containers_route) - data = response.json() - logger.info(f"response json:= {data}") - assert data["0"] == "echo" - # 2. deploy echo model - deploy_route = f"{backend_host}docker/deploy/" - logger.info(f"calling: {deploy_route}") - response = requests.post(deploy_route, json={"model_id": "0"}) - data = response.json() - logger.info(f"response json:= {data}") - assert data["status"] == "success" - deployed_container_id = data["container_id"] - # 3. make api call - service_route = data["service_route"] - container_name = data["container_name"] - port_bindings = data["port_bindings"] - # service_port = port_bindings["7000/tcp"] - service_port = "7000" - host = container_name - model_api_url = f"http://{host}:{service_port}{service_route}" - headers = {"Authorization": f"Bearer {encoded_jwt}"} - logger.info(f"calling: {model_api_url}") - valid_api_call(model_api_url, headers) - # 4. get status -> container id - status_route = f"{backend_host}docker/status/" - logger.info(f"calling: {status_route}") - response = requests.get(status_route) +def get_available_models(backend_host): + route = f"{backend_host}docker/get_containers/" + logger.info(f"calling: {route}") + response = requests.get(route) data = response.json() logger.info(f"response json:= {data}") - assert deployed_container_id in data.keys() - # 5. stop echo model - stop_route = f"{backend_host}docker/stop/" - logger.info(f"calling: {stop_route}") - response = requests.post(stop_route, json={"container_id": deployed_container_id}) + assert isinstance(data[0], dict) + return data[0]["name"] + + +def deploy_model(backend_host, model_id): + route = f"{backend_host}docker/deploy/" + logger.info(f"calling: {route}") + response = requests.post(route, json={"model_id": model_id, "weights_path": ""}) data = response.json() logger.info(f"response json:= {data}") assert data["status"] == "success" + return data + + +def get_service_details(deployment_data, impl, on_bridge_network): + port_bindings = deployment_data["port_bindings"] + service_port = port_bindings["7000/tcp"] if on_bridge_network else impl.service_port + return { + "host": deployment_data["container_name"], + "port": service_port, + "container_id": deployment_data["container_id"], + "service_route": deployment_data["service_route"], + } -def test_deploy_api(): - deploy_route = f"{backend_host}docker/deploy/" - logger.info(f"calling: {deploy_route}") - # test weights_path - response = requests.post(deploy_route, json={"model_id": "0", "weights_path": ""}) +def verify_model_status(backend_host, container_id): + route = f"{backend_host}docker/status/" + logger.info(f"calling: {route}") + response = requests.get(route) data = response.json() logger.info(f"response json:= {data}") - assert data["status"] == "success" - deployed_container_id = data["container_id"] - stop_route = f"{backend_host}docker/stop/" - logger.info(f"calling: {stop_route}") - response = requests.post(stop_route, json={"container_id": deployed_container_id}) + assert container_id in data.keys() + + +def stop_model(backend_host, container_id): + route = f"{backend_host}docker/stop/" + logger.info(f"calling: {route}") + response = requests.post(route, json={"container_id": container_id}) data = response.json() logger.info(f"response json:= {data}") assert data["status"] == "success" -def valid_api_call(api_url, headers, prompt_extra="", print_output=True): - # set API prompt and optional parameters - json_data = { - "text": "What is in Austin Texas?" + prompt_extra, - "temperature": 1, - "top_k": 10, - "top_p": 0.9, - "max_tokens": 16, - "stop_sequence": None, - "return_prompt": None, - } - logger.info("waiting for containers HTTP server to become available ...") - time.sleep(2) - # using requests stream=True, make sure to set a timeout - response = requests.post( - api_url, json=json_data, headers=headers, stream=True, timeout=35 - ) - # Handle chunked response - if response.headers.get("transfer-encoding") == "chunked": - logger.info("processing chunks ...") - for idx, chunk in enumerate( - response.iter_content(chunk_size=None, decode_unicode=True) - ): - # Process each chunk of data as it's received - if print_output: - logger.info(chunk) +def test_model_life_cycle(): + # if running outside container, set on_bridge_network to False + on_bridge_network = False + if on_bridge_network: + backend_host = "http://tt_studio_backend_api:8000/" else: - # If not chunked, you can access the entire response body at once - logger.info("NOT CHUNKED!") - logger.info(response.text) + backend_host = "http://0.0.0.0:8000/" + model_id = "id_mock_vllm_modelv0.0.1" + encoded_jwt = create_auth_token() + + try: + # 1. Get available models + model_name = get_available_models(backend_host) + impl = model_implmentations[model_id] + + # 2. Deploy model + deployment_data = deploy_model(backend_host, model_id) + + # 3. Make API call + service = get_service_details(deployment_data, impl, on_bridge_network) + headers = {"Authorization": f"Bearer {encoded_jwt}"} + + health_url = f"http://{service['host']}:{service['port']}/health" + api_url = ( + f"http://{service['host']}:{service['port']}{service['service_route']}" + ) + + wait_for_vllm_healthy_endpoint(health_url, headers, timeout=30) + logger.info(f"calling: {api_url}") + valid_vllm_api_call(api_url, headers, vllm_model=model_name) + + # 4. Verify model status + verify_model_status(backend_host, service["container_id"]) + + except Exception as e: + logger.error(f"Error: {e}") + raise e + finally: + # 5. Stop model + if "service" in locals(): + stop_model(backend_host, service["container_id"]) diff --git a/app/api/docker_control/test_docker_utils.py b/app/api/docker_control/test_docker_utils.py index 96086757..55a4fd39 100644 --- a/app/api/docker_control/test_docker_utils.py +++ b/app/api/docker_control/test_docker_utils.py @@ -1,7 +1,14 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import json import time +from collections import defaultdict +from unittest.mock import patch import requests +from requests.exceptions import RequestException import jwt from shared_config.backend_config import backend_config @@ -14,13 +21,60 @@ logger.info(f"importing {__name__}") -def test_deploy_echo_model(): - impl = model_implmentations["0"] +# Simple dict-based cache mock +class MockCache: + def __init__(self): + self.store = {} + + def set(self, key, value, timeout=None): + self.store[key] = value + + def get(self, key, default=None): + return self.store.get(key, default) + + +@patch("docker_control.docker_utils.caches", defaultdict(MockCache)) +def test_deploy_mock_model(): + impl = model_implmentations["id_mock_vllm_modelv0.0.1"] + json_payload = json.loads('{"team_id": "tenstorrent", "token_id":"debug-test"}') + encoded_jwt = jwt.encode(json_payload, backend_config.jwt_secret, algorithm="HS256") + # 1. run container + logger.info(f"using impl:={impl}") + status = run_container(impl, weights_id=None) + logger.info(f"status:={status}") + assert status["status"] == "success" + try: + # 2. make valid API call to container + container_id = status["container_id"] + service_port = impl.service_port + service_route = status["service_route"] + host = status["container_name"] + api_url = f"http://{host}:{service_port}{service_route}" + health_url = f"http://{host}:{service_port}/health" + headers = {"Authorization": f"Bearer {encoded_jwt}"} + wait_for_vllm_healthy_endpoint(health_url, headers) + assert valid_vllm_api_call(api_url, headers, vllm_model=impl.model_name) + except Exception as e: + logger.error(f"Error: {e}") + has_error = True + # 3. stop container + logger.info(f"stop deployed container: container_id={container_id}") + stop_status = stop_container(container_id) + logger.info(f"status:={stop_status}") + if has_error: + raise e + assert stop_status["status"] == "success" + + +@patch("docker_control.docker_utils.caches", defaultdict(MockCache)) +def test_deploy_llama3_model(): + impl = model_implmentations["id_tt-metal-llama-3.1-70b-instructv0.0.1"] json_payload = json.loads('{"team_id": "tenstorrent", "token_id":"debug-test"}') encoded_jwt = jwt.encode(json_payload, backend_config.jwt_secret, algorithm="HS256") # 1. run container logger.info(f"using impl:={impl}") - status = run_container(impl) + weights_id = impl.docker_config["environment"]["MODEL_WEIGHTS_ID"] + status = run_container(impl, weights_id) logger.info(f"status:={status}") assert status["status"] == "success" # 2. make valid API call to container @@ -30,7 +84,7 @@ def test_deploy_echo_model(): host = status["container_name"] api_url = f"http://{host}:{service_port}{service_route}" headers = {"Authorization": f"Bearer {encoded_jwt}"} - assert valid_api_call(api_url, headers) + assert valid_vllm_api_call(api_url, headers) # 3. stop container logger.info(f"stop deployed container: container_id={container_id}") stop_status = stop_container(container_id) @@ -38,10 +92,10 @@ def test_deploy_echo_model(): assert stop_status["status"] == "success" -def valid_api_call(api_url, headers, prompt_extra="", print_output=True): +def valid_api_call(api_url, headers, print_output=True): # set API prompt and optional parameters json_data = { - "text": "What is in Austin Texas?" + prompt_extra, + "text": "What is Tenstorrent?", "temperature": 1, "top_k": 10, "top_p": 0.9, @@ -50,6 +104,7 @@ def valid_api_call(api_url, headers, prompt_extra="", print_output=True): "return_prompt": None, } logger.info("waiting for containers HTTP server to become available ...") + time.sleep(2) # using requests stream=True, make sure to set a timeout response = requests.post( @@ -68,9 +123,61 @@ def valid_api_call(api_url, headers, prompt_extra="", print_output=True): # If not chunked, you can access the entire response body at once logger.info("NOT CHUNKED!") logger.info(response.text) - passed = True - return passed + + +def wait_for_vllm_healthy_endpoint(health_url, headers, timeout=30): + logger.info( + f"waiting for healthy endpoint: {health_url}, timeout: {timeout} seconds" + ) + start_time = time.time() + while True: + try: + response = requests.get(health_url, headers=headers, timeout=10) + response.raise_for_status() + return True # Success case + + except RequestException as e: + elapsed = time.time() - start_time + if elapsed >= timeout: + raise TimeoutError( + f"Health check failed after {timeout} seconds: {str(e)}" + ) + + # Wait 1 second before retrying + time.sleep(1) + + +def valid_vllm_api_call(api_url, headers, vllm_model, print_output=True): + # set API prompt and optional parameters + json_data = { + "model": vllm_model, + "prompt": "What is Tenstorrent?", + "temperature": 1, + "top_k": 20, + "top_p": 0.9, + "max_tokens": 128, + "stream": True, + "stop": ["<|eot_id|>"], + } + req_time = time.time() + # using requests stream=True, make sure to set a timeout + response = requests.post( + api_url, json=json_data, headers=headers, stream=True, timeout=35 + ) + # Handle chunked response + if response.headers.get("transfer-encoding") == "chunked": + logger.info("processing chunks ...") + for idx, chunk in enumerate( + response.iter_content(chunk_size=None, decode_unicode=True) + ): + # Process each chunk of data as it's received + if print_output: + logger.info(chunk) + else: + # If not chunked, you can access the entire response body at once + logger.info("NOT CHUNKED!") + logger.info(response.text) if __name__ == "__main__": - test_deploy_echo_model() + test_deploy_mock_model() diff --git a/app/api/docker_control/tests.py b/app/api/docker_control/tests.py index 7ce503c2..eeaceac6 100644 --- a/app/api/docker_control/tests.py +++ b/app/api/docker_control/tests.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.test import TestCase # Create your tests here. diff --git a/app/api/docker_control/urls.py b/app/api/docker_control/urls.py index 8890de77..c644bb25 100644 --- a/app/api/docker_control/urls.py +++ b/app/api/docker_control/urls.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + # docker_control/urls.py from django.urls import path from . import views @@ -8,4 +12,5 @@ path("stop/", views.StopView.as_view()), path("status/", views.StatusView.as_view()), path("redeploy/", views.RedeployView.as_view()), + path("reset_board/", views.ResetBoardView.as_view()), ] diff --git a/app/api/docker_control/views.py b/app/api/docker_control/views.py index e04a1cc1..05e40f7f 100644 --- a/app/api/docker_control/views.py +++ b/app/api/docker_control/views.py @@ -1,15 +1,26 @@ -# docker_control/views.py -from django.shortcuts import render +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC -# from django.http import JsonResponse +from django.shortcuts import render +from django.http import StreamingHttpResponse from rest_framework import status from rest_framework.views import APIView from rest_framework.response import Response from .forms import DockerForm -from .docker_utils import run_container, stop_container, get_container_status +from .docker_utils import ( + run_container, + stop_container, + get_container_status, + perform_reset, +) from shared_config.model_config import model_implmentations from .serializers import DeploymentSerializer, StopSerializer +from shared_config.logger_config import get_logger + +logger = get_logger(__name__) +logger.info(f"importing {__name__}") class StopView(APIView): @@ -17,8 +28,51 @@ def post(self, request, *args, **kwargs): serializer = StopSerializer(data=request.data) if serializer.is_valid(): container_id = request.data.get("container_id") - response = stop_container(container_id) - return Response(response, status=status.HTTP_200_OK) + logger.info(f"Received request to stop container with ID: {container_id}") + + # Stop the container + stop_response = stop_container(container_id) + logger.info(f"Stop response: {stop_response}") + + # Perform reset if the stop was successful + reset_response = None + reset_status = "success" + + if stop_response.get("status") == "success": + reset_response = perform_reset() + logger.info(f"Reset response: {reset_response}") + + if reset_response.get("status") == "error": + error_message = reset_response.get( + "message", "An error occurred during reset." + ) + http_status = reset_response.get( + "http_status", status.HTTP_500_INTERNAL_SERVER_ERROR + ) + logger.warning(f"Reset failed: {error_message}") + reset_status = "error" + + # Ensure that we always return a status field + combined_status = ( + "success" if stop_response.get("status") == "success" else "error" + ) + + # Return the response, combining the stop and reset results + response_status = ( + status.HTTP_200_OK + if combined_status == "success" + else status.HTTP_500_INTERNAL_SERVER_ERROR + ) + logger.info(f"Returning responses: {stop_response}, {reset_response}") + return Response( + { + "status": combined_status, + "stop_response": stop_response, + "reset_response": reset_response, + "reset_status": reset_status, + }, + status=response_status, + ) else: return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) @@ -63,3 +117,35 @@ def post(self, request, *args, **kwargs): return Response(response, status=status.HTTP_201_CREATED) else: return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) + + +class ResetBoardView(APIView): + def post(self, request, *args, **kwargs): + try: + # Perform the reset + reset_response = perform_reset() + + # Determine the HTTP status based on the reset_response + if reset_response.get("status") == "error": + error_message = reset_response.get( + "message", "An error occurred during reset." + ) + http_status = reset_response.get( + "http_status", status.HTTP_500_INTERNAL_SERVER_ERROR + ) + return Response( + {"status": "error", "message": error_message}, status=http_status + ) + + # If successful, return a 200 OK with the output + output = reset_response.get("output", "Board reset successfully.") + return StreamingHttpResponse( + output, content_type="text/plain", status=status.HTTP_200_OK + ) + + except Exception as e: + logger.exception("Exception occurred during reset operation.") + return Response( + {"status": "error", "message": str(e)}, + status=status.HTTP_500_INTERNAL_SERVER_ERROR, + ) diff --git a/app/api/logs_control/__init__.py b/app/api/logs_control/__init__.py new file mode 100644 index 00000000..917beb36 --- /dev/null +++ b/app/api/logs_control/__init__.py @@ -0,0 +1,3 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC diff --git a/app/api/logs_control/urls.py b/app/api/logs_control/urls.py new file mode 100644 index 00000000..a5fe65c4 --- /dev/null +++ b/app/api/logs_control/urls.py @@ -0,0 +1,12 @@ +# SPDX-License-Identifier: Apache-2.0 +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from django.urls import path +from .views import ListLogsView, GetLogView + +urlpatterns = [ + path("", ListLogsView.as_view(), name="list_logs"), + path( + "/", GetLogView.as_view(), name="get_log" + ), # Use for multi-directory paths +] diff --git a/app/api/logs_control/views.py b/app/api/logs_control/views.py new file mode 100644 index 00000000..8ca3e734 --- /dev/null +++ b/app/api/logs_control/views.py @@ -0,0 +1,82 @@ +# SPDX-License-Identifier: Apache-2.0 +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +import os +from urllib.parse import unquote +from django.http import JsonResponse, HttpResponse, Http404 +from rest_framework.views import APIView +from shared_config.logger_config import get_logger + +# Setting up logger +logger = get_logger(__name__) + +# Use environment variable for the base storage volume +LOGS_ROOT = os.getenv("INTERNAL_PERSISTENT_STORAGE_VOLUME", "/path/to/fallback") + + +class ListLogsView(APIView): + """ + Lists all available directories and log files within the base logs directory + """ + + def get(self, request, *args, **kwargs): + logger.info("ListLogsView endpoint hit") + try: + logs_tree = self.build_logs_tree(LOGS_ROOT) + logger.info(f"Log tree built: {logs_tree}") + return JsonResponse({"logs": logs_tree}, status=200) + except Exception as e: + logger.error(f"Error listing logs: {e}") + return JsonResponse({"error": str(e)}, status=500) + + def build_logs_tree(self, directory): + """ + Recursively build a tree of directories and files. + """ + tree = [] + for entry in os.listdir(directory): + path = os.path.join(directory, entry) + if os.path.isdir(path): + tree.append( + { + "name": entry, + "type": "directory", + "children": self.build_logs_tree(path), + } + ) + elif entry.endswith(".log"): + tree.append({"name": entry, "type": "file"}) + return tree + + +class GetLogView(APIView): + """ + Retrieves the content of a specific log file from the logs directory. + """ + + def get(self, request, filename, *args, **kwargs): + decoded_filename = unquote(filename) + + file_path = os.path.normpath(os.path.join(LOGS_ROOT, decoded_filename)) + + # Security check: Ensure the resolved path is within LOGS_ROOT + if not file_path.startswith(os.path.abspath(LOGS_ROOT)): + logger.error(f"Invalid log file path: {file_path}") + raise Http404("Invalid file path.") + + logger.info(f"Looking for log file at: {file_path}") + + if os.path.exists(file_path) and os.path.isfile(file_path): + try: + with open(file_path, "r") as file: + content = file.read() + logger.info( + f"Successfully retrieved content for log: {decoded_filename}" + ) + return HttpResponse(content, content_type="text/plain") + except Exception as e: + logger.error(f"Error reading log file {decoded_filename}: {e}") + return JsonResponse({"error": str(e)}, status=500) + else: + logger.error(f"Log file {decoded_filename} not found at {file_path}") + raise Http404(f"Log file {decoded_filename} not found.") diff --git a/app/api/manage.py b/app/api/manage.py index 7fbe8935..c2564ca2 100755 --- a/app/api/manage.py +++ b/app/api/manage.py @@ -1,5 +1,10 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + #!/usr/bin/env python """Django's command-line utility for administrative tasks.""" + import os import sys diff --git a/app/api/model_control/__init__.py b/app/api/model_control/__init__.py index e69de29b..4da24a6e 100644 --- a/app/api/model_control/__init__.py +++ b/app/api/model_control/__init__.py @@ -0,0 +1,4 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + diff --git a/app/api/model_control/admin.py b/app/api/model_control/admin.py index 8c38f3f3..2c79060a 100644 --- a/app/api/model_control/admin.py +++ b/app/api/model_control/admin.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.contrib import admin # Register your models here. diff --git a/app/api/model_control/apps.py b/app/api/model_control/apps.py index 7442ab88..b310145a 100644 --- a/app/api/model_control/apps.py +++ b/app/api/model_control/apps.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.apps import AppConfig from shared_config.model_config import model_implmentations diff --git a/app/api/model_control/model_utils.py b/app/api/model_control/model_utils.py index b64508c2..28a390dd 100644 --- a/app/api/model_control/model_utils.py +++ b/app/api/model_control/model_utils.py @@ -1,5 +1,10 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import json import pickle +import time import requests import jwt @@ -31,20 +36,93 @@ def get_all_records(): return data +def health_check(url, json_data, timeout=5): + logger.info(f"calilng health_url:= {url}") + try: + headers = {"Authorization": f"Bearer {encoded_jwt}"} + response = requests.get(url, json=json_data, headers=headers, timeout=5) + response.raise_for_status() + logger.info(f"Health check passed: {response.status_code}") + return True, response.json() if response.content else {} + except requests.RequestException as e: + logger.error(f"Health check failed: {str(e)}") + return False, str(e) + + def stream_response_from_external_api(url, json_data): logger.info(f"stream_response_from_external_api to: url={url}") try: headers = {"Authorization": f"Bearer {encoded_jwt}"} + logger.info(f"stream_response_from_external_api headers:={headers}") + logger.info(f"stream_response_from_external_api json_data:={json_data}") + # TODO: remove once vllm implementation can support different topk/temperature in same batch + json_data["temperature"] = 1 + json_data["top_k"] = 20 + json_data["top_p"] = 0.9 + json_data["max_tokens"] = 512 + json_data["stream_options"] = {"include_usage": True, + "continuous_usage_stats": True} + logger.info(f"added extra token and temp:={json_data}") + + ttft = 0 + tpot = 0 + num_token_gen = 0 + prompt_tokens = 0 + ttft_start = time.time() + with requests.post( url, json=json_data, headers=headers, stream=True, timeout=None ) as response: + logger.info(f"stream_response_from_external_api response:={response}") response.raise_for_status() logger.info(f"response.headers:={response.headers}") logger.info(f"response.encoding:={response.encoding}") # only allow HTTP 1.1 chunked encoding assert response.headers.get("transfer-encoding") == "chunked" - # Note: chunk_size=None must be passed or it will chunk single chars + + # Stream chunks for chunk in response.iter_content(chunk_size=None, decode_unicode=True): - yield chunk + logger.info(f"stream_response_from_external_api chunk:={chunk}") + if chunk.startswith("data: "): + new_chunk = chunk[len("data: "):] # slice out the JSON object/dictionary + new_chunk = new_chunk.strip() + + if new_chunk == "[DONE]": + # Yield [DONE] to signal that streaming is complete + yield chunk + + # Now calculate and yield stats after [DONE] + stats = { + "ttft": ttft, + "tpot": tpot, + "tokens_decoded": num_token_gen, + "tokens_prefilled": prompt_tokens, + "context_length": prompt_tokens + num_token_gen + } + logger.info(f"ttft and tpot stats: {stats}") + yield "data: " + json.dumps(stats) + "\n\n" + + # Send the custom end of stream marker + yield "<>" # Custom marker to signal end of stream + break + + elif new_chunk != "": + chunk_dict = json.loads(new_chunk) + if chunk_dict.get("usage", {}).get("completion_tokens", 0) == 1: + ttft = time.time() - ttft_start # if first token is created + num_token_gen = 1 + tpot_start = time.time() + prompt_tokens = chunk_dict["usage"]["prompt_tokens"] + elif chunk_dict.get("usage", {}).get("completion_tokens", 0) > num_token_gen: + num_token_gen += 1 + tpot += (1 / num_token_gen) * (time.time() - tpot_start - tpot) # update average + tpot_start = time.time() + + # Yield the current chunk + yield chunk + + logger.info("stream_response_from_external done") + except requests.RequestException as e: - yield str(e) + logger.error(f"RequestException: {str(e)}") + yield f"error: {str(e)}" diff --git a/app/api/model_control/models.py b/app/api/model_control/models.py index 71a83623..2d29716d 100644 --- a/app/api/model_control/models.py +++ b/app/api/model_control/models.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.db import models # Create your models here. diff --git a/app/api/model_control/serializers.py b/app/api/model_control/serializers.py index 10cb26a5..ff370d2b 100644 --- a/app/api/model_control/serializers.py +++ b/app/api/model_control/serializers.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from pathlib import Path from rest_framework import serializers diff --git a/app/api/model_control/test_e2e.py b/app/api/model_control/test_e2e.py index e04bef47..3f8b9dd3 100644 --- a/app/api/model_control/test_e2e.py +++ b/app/api/model_control/test_e2e.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import json import time import os @@ -10,6 +14,7 @@ logger.setLevel(logging.INFO) logger.info(f"importing {__file__}") + def test_e2e(): # get all deployed_ids base_url = "http://localhost:3000" @@ -20,6 +25,7 @@ def test_e2e(): for deploy_id, v in deployed_data.items(): valid_api_call(inference_url, deploy_id) + def valid_api_call(api_url, deploy_id, prompt_extra="", print_output=True): # set API prompt and optional parameters headers = None diff --git a/app/api/model_control/test_model_api.py b/app/api/model_control/test_model_api.py index 204dda95..db507e45 100644 --- a/app/api/model_control/test_model_api.py +++ b/app/api/model_control/test_model_api.py @@ -1,7 +1,12 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import json import time import requests +from requests.exceptions import RequestException import jwt from shared_config.backend_config import backend_config @@ -18,40 +23,38 @@ else: backend_host = "http://0.0.0.0:8000/" -# enabled when running on gunicorn -streaming_enabled = False - def test_model_life_cycle(): json_payload = json.loads('{"team_id": "tenstorrent", "token_id":"debug-test"}') encoded_jwt = jwt.encode(json_payload, backend_config.jwt_secret, algorithm="HS256") + test_model_id = "id_mock_vllm_modelv0.0.1" # 1. get list of models get_containers_route = f"{backend_host}docker/get_containers/" logger.info(f"calling: {get_containers_route}") response = requests.get(get_containers_route) data = response.json() logger.info(f"response json:= {data}") - assert data[0]["name"] == "echo" + assert test_model_id == data[0]["id"] model_id = data[0]["id"] + vllm_model_name = data[0]["name"] # 1b. get model_weights model_weights_route = f"{backend_host}models/model_weights/" logger.info(f"calling: {model_weights_route}") - response = requests.get(model_weights_route, json={"model_id": model_id}) + response = requests.get(model_weights_route, params={"model_id": model_id}) data = response.json() - logger.info(f"response json:= {data}") - # assert data[0]["name"] == "echo" + logger.info(f"weights response json:= {data}") # 2. deploy echo model deploy_route = f"{backend_host}docker/deploy/" logger.info(f"calling: {deploy_route}") # 2a. test 400 on bad weights response = requests.post( - deploy_route, json={"model_id": model_id, "weights_id": "test_fail"} + deploy_route, json={"model_id": model_id, "weights_id": "test_fail_weights"} ) assert response.status_code == 400 # 2b. test default weights response = requests.post(deploy_route, json={"model_id": model_id}) data = response.json() - # logger.info(f"response json:= {data}") + logger.info(f"response json:= {data}") assert data["status"] == "success" deployed_container_id = data["container_id"] logger.info(f"deployed container: {deployed_container_id}") @@ -66,25 +69,26 @@ def test_model_life_cycle(): deploy_id = deployed_ids[-1] deploy_data = deployed_res[deploy_id] json_data = { - "text": "What is in Austin Texas?", + "model": vllm_model_name, + "prompt": "What is Tenstorrent?", "temperature": 1, - "top_k": 10, + "top_k": 20, "top_p": 0.9, - "max_tokens": 32, - "stop_sequence": None, - "return_prompt": None, + "max_tokens": 128, + "stream": True, + "stop": ["<|eot_id|>"], "deploy_id": deploy_id, } model_inference_route = f"{backend_host}models/inference/" + health_url = f"{backend_host}models/health/" # allow inference server to start up - time.sleep(1) + response = wait_for_model_health_endpoint(health_url, deploy_id=deploy_id) logger.info(f"calling: {model_inference_route}") - response = requests.post(url=model_inference_route, json=json_data, stream=True) + response = requests.post( + url=model_inference_route, json=json_data, stream=True, timeout=35 + ) logger.info(f'response.headers={response.headers.get("transfer-encoding")}') - if streaming_enabled: - assert response.headers.get("transfer-encoding") == "chunked" - all_chunks = "" - logger.info("processing chunks ...") + assert response.headers.get("transfer-encoding") == "chunked" for chunk_idx, chunk in enumerate( response.iter_content(chunk_size=None, decode_unicode=True) ): @@ -92,9 +96,6 @@ def test_model_life_cycle(): all_chunks += chunk logger.info(f"processed {chunk_idx} chunks.") logger.info(f"all_chunks:={all_chunks}") - if streaming_enabled: - assert chunk_idx > 1 - assert all_chunks == json_data["text"] + "<|endoftext|>" # 4. get status -> container id status_route = f"{backend_host}docker/status/" logger.info(f"calling: {status_route}") @@ -111,3 +112,31 @@ def test_model_life_cycle(): # logger.info(f"response json:= {data}") assert data["status"] == "success" logger.info(f"stopped container: {deployed_container_id}") + + +def wait_for_model_health_endpoint(health_url, deploy_id, timeout=30): + logger.info( + f"waiting for healthy endpoint: {health_url}, timeout: {timeout} seconds" + ) + start_time = time.time() + while True: + try: + response = requests.get( + health_url, json={"deploy_id": deploy_id}, timeout=10 + ) + response.raise_for_status() + return response # Success case + + except RequestException as e: + elapsed = time.time() - start_time + if elapsed >= timeout: + raise TimeoutError( + f"Health check failed after {timeout} seconds: {str(e)}" + ) + + # Wait 1 second before retrying + time.sleep(1) + + +if __name__ == "__main__": + test_model_life_cycle() diff --git a/app/api/model_control/test_model_utils.py b/app/api/model_control/test_model_utils.py index c0eaba25..cf9c25b2 100644 --- a/app/api/model_control/test_model_utils.py +++ b/app/api/model_control/test_model_utils.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import json import time import os diff --git a/app/api/model_control/tests.py b/app/api/model_control/tests.py index 7ce503c2..eeaceac6 100644 --- a/app/api/model_control/tests.py +++ b/app/api/model_control/tests.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from django.test import TestCase # Create your tests here. diff --git a/app/api/model_control/urls.py b/app/api/model_control/urls.py index 259a13d5..2e1f7847 100644 --- a/app/api/model_control/urls.py +++ b/app/api/model_control/urls.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + # model_control/urls.py from django.urls import path from . import views @@ -6,4 +10,5 @@ path("inference/", views.InferenceView.as_view()), path("deployed/", views.DeployedModelsView.as_view()), path("model_weights/", views.ModelWeightsView.as_view()), + path("health/", views.ModelHealthView.as_view()), ] diff --git a/app/api/model_control/views.py b/app/api/model_control/views.py index 479e1a4f..e5da3199 100644 --- a/app/api/model_control/views.py +++ b/app/api/model_control/views.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + # model_control/views.py from pathlib import Path @@ -10,6 +14,7 @@ from model_control.model_utils import ( get_deploy_cache, stream_response_from_external_api, + health_check, ) from shared_config.model_config import model_implmentations from shared_config.logger_config import get_logger @@ -27,11 +32,35 @@ def post(self, request, *args, **kwargs): deploy_id = data.pop("deploy_id") deploy = get_deploy_cache()[deploy_id] internal_url = "http://" + deploy["internal_url"] + logger.info(f"internal_url:= {internal_url}") + logger.info(f"using vllm model:= {deploy["model_impl"].model_name}") + data["model"] = deploy["model_impl"].hf_model_path response_stream = stream_response_from_external_api(internal_url, data) return StreamingHttpResponse(response_stream, content_type="text/plain") else: return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) +class ModelHealthView(APIView): + def get(self, request, *args, **kwargs): + data = request.query_params + logger.info(f"HealthView data:={data}") + serializer = InferenceSerializer(data=data) + if serializer.is_valid(): + deploy_id = data.get("deploy_id") + deploy = get_deploy_cache()[deploy_id] + health_url = "http://" + deploy["health_url"] + logger.info(f"health_url:= {health_url}") + check_passed, health_content = health_check(health_url, json_data=None) + if check_passed: + ret_status = status.HTTP_200_OK + content = {"message": "Healthy", "details": health_content} + else: + ret_status = status.HTTP_503_SERVICE_UNAVAILABLE + content = {"message": "Unavaliable", "details": health_content} + return Response(content, status=ret_status) + else: + return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) + class DeployedModelsView(APIView): def get(self, request, *args, **kwargs): @@ -53,7 +82,6 @@ def get(self, request, *args, **kwargs): class ModelWeightsView(APIView): def get(self, request, *args, **kwargs): - # TODO: add serializer data = request.query_params logger.info(f"request.query_params:={data}") serializer = ModelWeightsSerializer(data=data) @@ -61,9 +89,7 @@ def get(self, request, *args, **kwargs): model_id = data.get("model_id") impl = model_implmentations[model_id] weights_dir = impl.backend_weights_dir - assert ( - weights_dir.exists() - ), f"weights_dir:={weights_dir} does not exist. Check models API initiliazation." + assert weights_dir.exists(), f"weights_dir:={weights_dir} does not exist. Check models API initiliazation." weights = [ {"weights_id": f"id_{w.name}", "name": w.name} for w in weights_dir.iterdir() diff --git a/app/api/requirements.txt b/app/api/requirements.txt index 0d49d481..34ad2291 100644 --- a/app/api/requirements.txt +++ b/app/api/requirements.txt @@ -1,9 +1,23 @@ Django==5.0.4 -docker==7.0.0 -djangorestframework==3.14.0 django-cors-headers==4.3.1 -requests==2.31.0 -pyjwt==2.7.0 +djangorestframework==3.14.0 +docker==7.0.0 gunicorn==22.0.0 +numpy==1.26.4 +pyjwt==2.7.0 +pypdf==4.3.1 +requests==2.29.0 + # dev pytest==8.2.2 + +# Chroma loader dependencies +chromadb==0.5.3 +langchain==0.2.14 +langchain-core==0.2.33 +langchain-text-splitters==0.2.2 +langchain-chroma==0.1.3 +sentence-transformers==2.7.0 +chroma-hnswlib==0.7.3 +--no-binary=chroma-hnswlib +pysqlite3==0.5.3 diff --git a/app/api/shared_config/__init__.py b/app/api/shared_config/__init__.py index e69de29b..4da24a6e 100644 --- a/app/api/shared_config/__init__.py +++ b/app/api/shared_config/__init__.py @@ -0,0 +1,4 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + diff --git a/app/api/shared_config/backend_config.py b/app/api/shared_config/backend_config.py index d5057642..88cd722c 100644 --- a/app/api/shared_config/backend_config.py +++ b/app/api/shared_config/backend_config.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from dataclasses import dataclass import os from pathlib import Path @@ -14,6 +18,7 @@ class BackendConfig: weights_dir: str model_container_cache_root: str jwt_secret: str + hf_token: str # environment variables are ideally terminated on import to fail-fast and provide obvious @@ -27,10 +32,11 @@ class BackendConfig: "backend_volume" ), django_deploy_cache_name="deploy_cache", - docker_bridge_network_name="llm_studio_network", + docker_bridge_network_name="tt_studio_network", weights_dir="model_weights", model_container_cache_root="/home/user/cache_root", jwt_secret=os.environ["JWT_SECRET"], + hf_token=os.environ["HF_TOKEN"], ) # make backend volume if not existing diff --git a/app/api/shared_config/device_config.py b/app/api/shared_config/device_config.py index 3d0fee4f..1bdd2971 100644 --- a/app/api/shared_config/device_config.py +++ b/app/api/shared_config/device_config.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + from enum import Enum, auto diff --git a/app/api/shared_config/logger_config.py b/app/api/shared_config/logger_config.py index be1a42d7..3f3722b1 100644 --- a/app/api/shared_config/logger_config.py +++ b/app/api/shared_config/logger_config.py @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import logging import os from datetime import datetime diff --git a/app/api/shared_config/model_config.py b/app/api/shared_config/model_config.py index b95dd1f7..2675453e 100644 --- a/app/api/shared_config/model_config.py +++ b/app/api/shared_config/model_config.py @@ -1,6 +1,10 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + import os from dataclasses import dataclass, asdict -from typing import Set, Dict, Any +from typing import Set, Dict, Any, Union from pathlib import Path from shared_config.device_config import DeviceConfigurations @@ -11,6 +15,22 @@ logger.info(f"importing {__name__}") +def load_dotenv_dict(env_path: Union[str, Path]) -> Dict[str, str]: + env_path = Path(env_path) + if not env_path.exists(): + logger.error(f"Env file not found: {env_path}") + env_dict = {} + with open(env_path) as f: + lines = f.readlines() + for line in lines: + if line.strip() and not line.startswith('#'): + key, value = line.strip().split('=', 1) + # expand any $VAR or ${VAR} and ~ + value = os.path.expandvars(value) + env_dict[key] = value + return env_dict + + @dataclass(frozen=True) class ModelImpl: """ @@ -21,22 +41,36 @@ class ModelImpl: model_id: str image_name: str image_tag: str - device_configurations: Set[ - "DeviceConfigurations" - ] # Assuming DeviceConfigurations is an enum or similar + hf_model_path: str + device_configurations: Set["DeviceConfigurations"] docker_config: Dict[str, Any] user_uid: int # user inside docker container uid (for file permissions) user_gid: int # user inside docker container gid (for file permissions) shm_size: str service_port: int service_route: str + env_file: str = "" + health_route: str = "/health" def __post_init__(self): self.docker_config.update({"volumes": self.get_volume_mounts()}) self.docker_config["shm_size"] = self.shm_size + self.docker_config["environment"]["HF_MODEL_PATH"] = self.hf_model_path self.docker_config["environment"]["HF_HOME"] = Path( backend_config.model_container_cache_root ).joinpath("huggingface") + + # Set environment variable if N150 or N300x4 is in the device configurations + if DeviceConfigurations.N150 in self.device_configurations or DeviceConfigurations.N300x4 in self.device_configurations: + self.docker_config["environment"]["WH_ARCH_YAML"] = "wormhole_b0_80_arch_eth_dispatch.yaml" + + if self.env_file: + logger.info(f"Using env file: {self.env_file}") + # env file should be in persistent volume mounted + env_dict = load_dotenv_dict(self.env_file) + # env file overrides any existing docker environment variables + self.docker_config["environment"].update(env_dict) + @property def image_version(self) -> str: @@ -113,6 +147,7 @@ def base_docker_config(): "environment": { "JWT_SECRET": backend_config.jwt_secret, "CACHE_ROOT": backend_config.model_container_cache_root, + "HF_TOKEN": backend_config.hf_token, }, } @@ -121,23 +156,25 @@ def base_docker_config(): # using friendly strings prefixed with id_ is more helpful for debugging model_implmentations_list = [ ModelImpl( - model_name="echo", - model_id="id_dummy_echo_modelv0.0.1", - image_name="dummy_echo_model", - image_tag="v0.0.1", + model_name="Mock-Llama-3.1-70B-Instruct", + model_id="id_mock_vllm_modelv0.0.1", + image_name="ghcr.io/tenstorrent/tt-inference-server/mock.vllm.openai.api", + image_tag="v0.0.1-tt-metal-385904186f81-384f1790c3be", + hf_model_path="meta-llama/Llama-3.1-70B-Instruct", device_configurations={DeviceConfigurations.CPU}, docker_config=base_docker_config(), user_uid=1000, user_gid=1000, shm_size="1G", service_port=7000, - service_route="/inference/dummy_echo", + service_route="/v1/chat/completions", ), ModelImpl( model_name="Falcon-7B-Instruct", model_id="id_tt-metal-falcon-7bv0.0.13", image_name="tt-metal-falcon-7b", image_tag="v0.0.13", + hf_model_path="tiiuae/falcon-7b-instruct", device_configurations={DeviceConfigurations.N150}, docker_config=base_docker_config(), user_uid=1000, @@ -146,9 +183,53 @@ def base_docker_config(): service_port=7000, service_route="/inference/falcon7b", ), + ModelImpl( + model_name="Llama-3.1-70B-Instruct", + model_id="id_tt-metal-llama-3.1-70b-instructv0.0.1", + image_name="ghcr.io/tenstorrent/tt-inference-server/tt-metal-llama3-70b-src-base-vllm", + image_tag="v0.0.3-tt-metal-385904186f81-384f1790c3be", + hf_model_path="meta-llama/Llama-3.1-70B-Instruct", + device_configurations={DeviceConfigurations.N300x4}, + docker_config=base_docker_config(), + user_uid=1000, + user_gid=1000, + shm_size="32G", + service_port=7000, + service_route="/v1/chat/completions", + env_file=os.environ.get("VLLM_LLAMA31_ENV_FILE"), + ), + ModelImpl( + model_name="Mistral7B-instruct-v0.2", + model_id="id_tt-metal-mistral-7bv0.0.2", + image_name="ghcr.io/tenstorrent/tt-inference-server/tt-metal-mistral-7b-src-base", + image_tag="v0.0.3-tt-metal-v0.52.0-rc33", + hf_model_path="mistralai/Mistral-7B-Instruct-v0.2", + device_configurations={DeviceConfigurations.N300x4}, + docker_config=base_docker_config(), + user_uid=1000, + user_gid=1000, + shm_size="32G", + service_port=7000, + service_route="/inference/mistral7b", + ), + #! Add new model vLLM model implementations here + # ModelImpl( + # model_name="", #? Add the model name for the vLLM model based on persistent storage + # model_id="", #? Add the model id for the vLLM model based on persistent storage + # image_name="ghcr.io/tenstorrent/tt-inference-server/tt-metal-llama3-70b-src-base-vllm", + # image_tag="v0.0.1-tt-metal-685ef1303b5a-54b9157d852b", + # hf_model_path="meta-llama/Llama-3.1-70B-Instruct", + # device_configurations={DeviceConfigurations.N300x4}, + # docker_config=base_docker_config(), + # user_uid=1000, + # user_gid=1000, + # shm_size="32G", + # service_port=7000, + # service_route="/inference/**", #? Add the correct route for the vLLM model + # env_file=os.environ.get("VLLM_LLAMA31_ENV_FILE"), + # ) ] - def validate_model_implemenation_config(impl): # no / in model_id strings, model_id will be used in path names assert not "/" in impl.model_id @@ -158,4 +239,4 @@ def validate_model_implemenation_config(impl): model_implmentations = {} for impl in model_implmentations_list: validate_model_implemenation_config(impl) - model_implmentations[impl.model_id] = impl + model_implmentations[impl.model_id] = impl \ No newline at end of file diff --git a/app/api/vector_db_control/__init__.py b/app/api/vector_db_control/__init__.py new file mode 100644 index 00000000..e7729454 --- /dev/null +++ b/app/api/vector_db_control/__init__.py @@ -0,0 +1,5 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +default_app_config = "api.apps.vector_db.apps.VectorDbConfig" diff --git a/app/api/vector_db_control/apps.py b/app/api/vector_db_control/apps.py new file mode 100644 index 00000000..402c8581 --- /dev/null +++ b/app/api/vector_db_control/apps.py @@ -0,0 +1,23 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from django.apps import AppConfig + +from shared_config.logger_config import get_logger + +logger = get_logger(__name__) +from vector_db_control.singletons import ChromaClient, get_embedding_function + + +class VectorDbConfig(AppConfig): + name = "vector_db_control" + default_auto_field = "django.db.models.BigAutoField" + + def ready(self): + from django.conf import settings + + logger.info(f"{__name__} ready.") + # Preload the singleton to initialize the model at startup + get_embedding_function(model_name=settings.CHROMA_DB_EMBED_MODEL) + ChromaClient(host=settings.CHROMA_DB_HOST, port=settings.CHROMA_DB_PORT) diff --git a/app/api/vector_db_control/chroma.py b/app/api/vector_db_control/chroma.py new file mode 100644 index 00000000..2ec1d389 --- /dev/null +++ b/app/api/vector_db_control/chroma.py @@ -0,0 +1,105 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from datetime import datetime +from itertools import batched +from typing import List + +from chromadb.types import Collection + +# your_app/singleton.py +from shared_config.logger_config import get_logger + +logger = get_logger(__name__) +from vector_db_control.singletons import ChromaClient, get_embedding_function + + +def list_collections(filter_func=None): + chroma_collections = ChromaClient().list_collections() + if filter_func: + return filter(filter_func, chroma_collections) + return chroma_collections + + +def delete_collection(collection_name: str): + ChromaClient().delete_collection(name=collection_name) + + +def get_collection(collection_name: str, embedding_func_name: str): + embedding_func = get_embedding_function(model_name=embedding_func_name) + return ChromaClient().get_collection( + name=collection_name, embedding_function=embedding_func + ) + + +def create_collection( + collection_name: str, + embedding_func_name: str, + metadata=None, + distance_func_name: str = "cosine", +): + # Metadata could be used in the future to filter our collections. + # For instance - ` metadata = { 'target_models' : "X, Y, Z" } + embedding_func = get_embedding_function(model_name=embedding_func_name) + metadata = metadata or {} + metadata.update( + {"hnsw:space": distance_func_name, "embedding_func_name": embedding_func_name} + ) + metadata.update({"created_at": datetime.now()}) + return ChromaClient().create_collection( + name=collection_name, embedding_function=embedding_func, metadata=metadata + ) + + +def delete_collection(collection_name: str): + if not ChromaClient().get_collection(collection_name): + raise ValueError("Collection does not exist") + ChromaClient().delete_collection(collection_name) + + +def query_collection( + collection_name: str, embedding_func_name: str, query_texts: List[str] +): + embedding_func = get_embedding_function(model_name=embedding_func_name) + target_collection = ChromaClient().get_collection( + name=collection_name, embedding_function=embedding_func + ) + return target_collection.query(query_texts=query_texts) + + +def serialize_collection(collection: Collection): + return { + "id": str(collection.id), + "metadata": collection.metadata, + "name": collection.name, + } + + +def insert_to_chroma_collection( + collection_name: str, + embedding_func_name: str, + ids: list[str], + documents: list[str], + metadatas: list[dict], +): + embedding_func = get_embedding_function(model_name=embedding_func_name) + + target_collection = ChromaClient().get_collection( + name=collection_name, + embedding_function=embedding_func, + ) + + document_indices = list(range(len(documents))) + + for batch in batched(document_indices, 166): + start_idx = batch[0] + end_idx = batch[-1] + 1 + metadatas = ( + metadatas[start_idx:end_idx] if metadatas and len(metadatas) else None + ) + target_collection.add( + ids=ids[start_idx:end_idx], + documents=documents[start_idx:end_idx], + metadatas=metadatas, + ) diff --git a/app/api/vector_db_control/data.py b/app/api/vector_db_control/data.py new file mode 100644 index 00000000..7569c0c0 --- /dev/null +++ b/app/api/vector_db_control/data.py @@ -0,0 +1,33 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +LINCOLN_TOWN_CAR = """ +The Lincoln Town Car is a model line of full-size luxury sedans that was marketed by the Lincoln division of the American automaker Ford Motor Company. Deriving its name from a limousine body style, Lincoln marketed the Town Car from 1981 to 2011, with the nameplate previously serving as the flagship trim of the Lincoln Continental. Produced across three generations for thirty model years, the Town Car was marketed directly against luxury sedans from Cadillac and Chrysler.[1] +Marketed nearly exclusively as a four-door sedan (a two-door sedan was offered for 1981 only), many examples of the Town Car were used for fleet and livery (limousine) service. From 1983 to its 2011 discontinuation, the Town Car was the longest car produced by Ford worldwide, becoming the longest mass-production car sold in North America from 1997 to 2011. While not a direct successor of the Town Car, the Lincoln MKS would become the longest American sedan until 2016 (overtaken by the Cadillac CT6). +From 1980 until 2007, the Lincoln Town Car was assembled in Wixom, Michigan, (Wixom Assembly) alongside the Lincoln Continental, LS, and Mark VI, VII, and VIII. After Wixom's closure, Town Car production moved to Southwold, Ontario, (St. Thomas Assembly) alongside the similar Ford Crown Victoria and the Mercury Grand Marquis. The final Lincoln Town Car was produced on August 29, 2011.[2] +Within the Lincoln model line, the Town Car was not directly replaced; the nameplate was used from 2012 to 2019 to denote livery/limousine/hearse variants of the Lincoln MKT. For 2017, the revived Continental replaced the MKS, closely matching the Town Car in wheelbase and width. +""" + +APPLES = """ +An apple is a round, edible fruit produced by an apple tree (Malus spp., among them the domestic or orchard apple; Malus domestica). Apple trees are cultivated worldwide and are the most widely grown species in the genus Malus. The tree originated in Central Asia, where its wild ancestor, Malus sieversii, is still found. Apples have been grown for thousands of years in Eurasia and were introduced to North America by European colonists. Apples have religious and mythological significance +in many cultures, including Norse, Greek, and European Christian tradition. +Apples grown from seed tend to be very different from those of their parents, and the resultant fruit frequently lacks desired characteristics. For commercial purposes, including botanical evaluation, apple cultivars are propagated by clonal grafting onto rootstocks. Apple trees grown without rootstocks tend to be larger and much slower to fruit after planting. Rootstocks are used to control the speed of growth and the size of the resulting tree, allowing for easier harvesting. +There are more than 7,500 cultivars of apples. Different cultivars are bred for various tastes and uses, including cooking, eating raw, and cider or apple juice production. Trees and fruit are prone to fungal, bacterial, and pest problems, which can be controlled by a number of organic and non-organic means. In 2010, the fruit's genome was sequenced as part of research on disease control and selective breeding in apple production. +""" + + +HEBREW = """ +Hebrew (Hebrew alphabet: Χ’Φ΄Χ‘Φ°Χ¨Φ΄Χ™Χͺβ€Ž, ΚΏΔͺvrΔ«t, pronounced [ivˈʁit] β“˜ or [Κ•ivˈrit] β“˜; Samaritan script: ࠏࠨࠁࠬࠓΰ ͺΰ ‰ΰ •β€Ž ʿÎbrit) is a Northwest Semitic language within the Afroasiatic language family. A regional dialect of the Canaanite languages, it was natively spoken by the Israelites and remained in regular use as a first language until after 200 CE and as the liturgical language of Judaism (since the Second Temple period) and Samaritanism.[14] The language was revived as a spoken language in the 19th century, and is the only successful large-scale example of linguistic revival. It is the only Canaanite language, as well as one of only two Northwest Semitic languages, with the other being Aramaic, still spoken today.[15][16] +The earliest examples of written Paleo-Hebrew date back to the 10th century BCE.[17] Nearly all of the Hebrew Bible is written in Biblical Hebrew, with much of its present form in the dialect that scholars believe flourished around the 6th century BCE, during the time of the Babylonian captivity. For this reason, Hebrew has been referred to by Jews as Lashon Hakodesh (ΧœΦ°Χ©ΧΧ•ΦΉΧŸ Χ”Φ·Χ§ΦΉΦΌΧ“ΦΆΧ©, lit. 'the holy tongue' or 'the tongue [of] holiness') since ancient times. The language was not referred to by the name Hebrew in the Bible, but as Yehudit (transl. 'Judean') or SΙ™paαΉ― KΙ™na'an (transl. "the language of Canaan").[1][note 2] Mishnah Gittin 9:8 refers to the language as Ivrit, meaning Hebrew; however, Mishnah Megillah refers + to the language as Ashurit, meaning Assyrian, which is derived from the name of the alphabet used, in contrast to Ivrit, meaning the Paleo-Hebrew alphabet.[18] +Hebrew ceased to be a regular spoken language sometime between 200 and 400 CE, as it declined in the aftermath of the unsuccessful Bar Kokhba revolt, which was carried out against the Roman Empire by the Jews of Judaea.[19][20][note 3] Aramaic and, to a lesser extent, Greek were already in use as international languages, especially among societal elites and immigrants.[22] Hebrew survived into the medieval period as the language of Jewish liturgy, rabbinic literature, intra-Jewish commerce, and Jewish poetic literature. The first dated book printed in Hebrew was published by Abraham Garton in Reggio (Calabria, Italy) in 1475.[23] +With the rise of Zionism in the 19th century, the Hebrew language experienced a full-scale revival as a spoken and literary language. The creation of a modern version of the ancient language was led by Eliezer Ben-Yehuda. Modern Hebrew (Ivrit) became the main language of the Yishuv in Palestine, and subsequently the official language of the State of Israel. Estimates of worldwide usage include five million speakers in 1998,[4] and over nine million people in 2013.[24] After Israel, the United States has the largest Hebrew-speaking population, with approximately 220,000 fluent speakers (see Israeli Americans and Jewish Americans).[25] +Modern Hebrew is the official language of the State of Israel,[26][27] while pre-revival forms of Hebrew are used for prayer or study in Jewish and Samaritan communities around the world today; the latter group utilizes the Samaritan dialect as their liturgical tongue. As a non-first language, it is studied mostly by non-Israeli Jews and students in Israel, by archaeologists and linguists specializing in the Middle East and its civilizations, and by theologians in Christian seminaries. +""" + +SAMPLE_DATA = [ + LINCOLN_TOWN_CAR, + HEBREW, + APPLES, +] diff --git a/app/api/vector_db_control/documents.py b/app/api/vector_db_control/documents.py new file mode 100644 index 00000000..42089e80 --- /dev/null +++ b/app/api/vector_db_control/documents.py @@ -0,0 +1,25 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from langchain_core.documents import Document +from langchain_text_splitters import RecursiveCharacterTextSplitter + + +def chunk_pdf_document( + loaded_document, extraction_mode="plain", chunk_size=1000, chunk_overlap=100 +): + loaded_documents = [] + metadata = loaded_document.metadata + for page in loaded_document.pages: + loaded_documents.append( + Document( + page_content=page.extract_text(extraction_mode=extraction_mode), + metadata=metadata, + ) + ) + text_splitter = RecursiveCharacterTextSplitter( + chunk_size=chunk_size, chunk_overlap=chunk_overlap + ) + chunked_document = text_splitter.split_documents(loaded_documents) + return chunked_document diff --git a/app/api/vector_db_control/singletons.py b/app/api/vector_db_control/singletons.py new file mode 100644 index 00000000..a7bad3c3 --- /dev/null +++ b/app/api/vector_db_control/singletons.py @@ -0,0 +1,53 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from threading import Lock +from typing import Optional + +from chromadb import HttpClient, Settings, ClientAPI +from chromadb.utils import embedding_functions + +from shared_config.logger_config import get_logger + +logger = get_logger(__name__) + +# Dictionary to store singleton instances +_instances = {} +# Lock for thread safety during initialization +_lock = Lock() + + +def get_embedding_function(model_name: str): + """ + Returns the singleton instance of the SentenceTransformer model. + Ensures that the model is loaded only once in a thread-safe manner. + """ + + # Check if the model instance already exists + if model_name not in _instances: + with _lock: # Ensure that only one thread can initialize the model + # Double-check pattern to avoid race condition + if model_name not in _instances: + _instances[model_name] = ( + embedding_functions.SentenceTransformerEmbeddingFunction( + model_name=model_name + ) + ) + + return _instances[model_name] + + +class ChromaClient: + _instance: Optional[ClientAPI] = None + _lock = Lock() + + def __new__(cls, host=None, port=None): + if cls._instance is None: + with cls._lock: + if cls._instance is None: + logger.info(f"Initializing ChromaDB connection {host}:{port}") + cls._instance = HttpClient( + host=host, port=port, settings=Settings() + ) + return cls._instance diff --git a/app/api/vector_db_control/urls.py b/app/api/vector_db_control/urls.py new file mode 100644 index 00000000..a4602cb0 --- /dev/null +++ b/app/api/vector_db_control/urls.py @@ -0,0 +1,15 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +from django.urls import path +from rest_framework import routers + +from .views import VectorCollectionsAPIView + +app_name = "rag" + +router = routers.DefaultRouter(trailing_slash=False) +router.register("", VectorCollectionsAPIView, basename="collections") + +urlpatterns = router.urls diff --git a/app/api/vector_db_control/views.py b/app/api/vector_db_control/views.py new file mode 100644 index 00000000..53d1168d --- /dev/null +++ b/app/api/vector_db_control/views.py @@ -0,0 +1,94 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + +import uuid +from typing import List + +import pypdf +from chromadb.types import Collection +from django.conf import settings +from rest_framework import status +from rest_framework.decorators import action +from rest_framework.response import Response +from rest_framework.viewsets import ViewSet + +from vector_db_control.chroma import ( + list_collections, + create_collection, + get_collection, + query_collection, + insert_to_chroma_collection, + serialize_collection, + delete_collection, +) +from vector_db_control.documents import chunk_pdf_document + + +class VectorCollectionsAPIView(ViewSet): + EMBED_MODEL = None + chromadb_client = None + query_results_limit = 2 + + def __init__(self, **kwargs): + super().__init__(**kwargs) + if hasattr(settings, "CHROMA_DB_EMBED_MODEL"): + self.EMBED_MODEL = settings.CHROMA_DB_EMBED_MODEL + + def list(self, request): + collections: List[Collection] = list_collections() + return Response(data=map(serialize_collection, collections)) + + def post(self, request): + name = request.data["name"] + collection = create_collection( + collection_name=name, + metadata=request.data.get("metadata", dict()), + embedding_func_name=self.EMBED_MODEL, + ) + return Response(data=serialize_collection(collection)) + + def retrieve(self, request, pk=None): + if not pk: + return self.list(request) + collection = get_collection( + collection_name=pk, embedding_func_name=self.EMBED_MODEL + ) + return Response(data=serialize_collection(collection)) + + @action(methods=["DELETE"], detail=True) + def delete(self, request, pk=None): + if not pk: + return Response( + status=status.HTTP_500_INTERNAL_SERVER_ERROR, + data={"error": "No collection name provided"}, + ) + delete_collection(collection_name=pk) + return Response(status=200) + + @action(methods=["POST"], detail=True) + def insert_document(self, request, pk=None): + file = request.FILES["file"] + loaded_document = pypdf.PdfReader(stream=file) + chunks = chunk_pdf_document(loaded_document) + ids = [str(uuid.uuid4()) for i in range(0, len(chunks))] + documents = [chunk.page_content for chunk in chunks] + insert_to_chroma_collection( + collection_name=pk, + documents=documents, + ids=ids, + metadatas=[], + embedding_func_name=self.EMBED_MODEL, + ) + + return Response(status=200) + + @action(methods=["GET"], detail=True, url_path="query") + def query(self, request, pk=None): + query = request.query_params.get("query") + if isinstance(query, str): + query = [query] + query_result = query_collection( + collection_name=pk, embedding_func_name=self.EMBED_MODEL, query_texts=query + ) + return Response(data=query_result) diff --git a/app/docker-compose.tt-hardware.yml b/app/docker-compose.tt-hardware.yml new file mode 100644 index 00000000..eaadc14f --- /dev/null +++ b/app/docker-compose.tt-hardware.yml @@ -0,0 +1,4 @@ +services: + tt_studio_backend: + devices: + - /dev/tenstorrent:/dev/tenstorrent diff --git a/app/docker-compose.yml b/app/docker-compose.yml index 90a354b5..bd7e85bc 100644 --- a/app/docker-compose.yml +++ b/app/docker-compose.yml @@ -1,3 +1,7 @@ +# SPDX-License-Identifier: Apache-2.0 +# +# SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC + services: tt_studio_backend: container_name: tt_studio_backend_api @@ -5,55 +9,103 @@ services: hostname: tt-studio-backend-api image: ghcr.io/tenstorrent/tt-studio/api:v0.0.0 build: ./api - # uncomment devices to use Tenstorrent hardware - # devices: - # # mount all tenstorrent devices to backend container - # - /dev/tenstorrent:/dev/tenstorrent + #* DEV: Uncomment devices to use Tenstorrent hardware + #! devices: + #* mounts all tenstorrent devices to backend container + #! - /dev/tenstorrent:/dev/tenstorrent + # note that `network_mode: host` does not work on mac OS - networks: - - llm_studio_network + networks: + - tt_studio_network ports: - "8000:8000" # command: bash # dev server can be used for breakpoint debugging, does not support streaming # command: ./manage.py runserver 0.0.0.0:8000 # gunicorn is used from production, supports streaming - command: gunicorn --workers 3 --bind 0.0.0.0:8000 --timeout 1200 api.wsgi:application + + command: gunicorn --workers 3 --bind 0.0.0.0:8000 --preload --timeout 1200 api.wsgi:application + depends_on: + tt_studio_chroma: + condition: service_healthy stdin_open: true tty: true environment: # env vars are defined in .env file, use .env.default as template + - CHROMA_DB_HOST=tt_studio_chroma + - CHROMA_DB_PORT=8111 - TT_STUDIO_ROOT - HOST_PERSISTENT_STORAGE_VOLUME - INTERNAL_PERSISTENT_STORAGE_VOLUME - BACKEND_API_HOSTNAME + - VLLM_LLAMA31_ENV_FILE - JWT_SECRET + - HF_TOKEN volumes: # mounting docker unix socket allows for backend container to run docker cmds - /var/run/docker.sock:/var/run/docker.sock - ${HOST_PERSISTENT_STORAGE_VOLUME}:${INTERNAL_PERSISTENT_STORAGE_VOLUME} # for development mount api changes - - ./api:/api + # - ./api:/api + + healthcheck: + # On first application load resources for transformers/etc + # are downloaded. The UI should not start until these resources + # have been downloaded. Adjust timeout if on a very slow connection + test: ["CMD", "curl", "-f", "http://localhost:8000/up/"] + timeout: 120s + interval: 10s + retries: 5 tt_studio_frontend: container_name: tt_studio_frontend hostname: tt-studio-frontend image: ghcr.io/tenstorrent/tt-studio/frontend:v0.0.0 build: ./frontend - networks: - - llm_studio_network + depends_on: + tt_studio_backend: + condition: service_healthy + networks: + - tt_studio_network ports: - "3000:3000" - volumes: - # for development mount api changes - - ./frontend:/frontend + # volumes: + #! for development mount api changes + # - ./frontend:/frontend # command: sh command: bash -c "npm i && npm run dev" + tt_studio_chroma: + image: chromadb/chroma:0.5.3 + volumes: + # Be aware that indexed data are located in "/chroma/chroma/" + # Default configuration for persist_directory in chromadb/config.py + # Read more about deployments: https://docs.trychroma.com/deployment + - ${HOST_PERSISTENT_STORAGE_VOLUME}/chroma:/chroma/chroma + command: "--workers 1 --host 0.0.0.0 --port 8111 --proxy-headers --log-config chromadb/log_config.yml --timeout-keep-alive 30" + environment: + - IS_PERSISTENT=TRUE + # - CHROMA_AUTH_TOKEN_TRANSPORT_HEADER=${CHROMA_AUTH_TOKEN_TRANSPORT_HEADER} + # - PERSIST_DIRECTORY=${INTERNAL_PERSISTENT_STORAGE_VOLUME}/chroma + - CHROMA_SERVER_CORS_ALLOW_ORIGINS=["http://localhost:3000", "http://tt_studio_frontend", "http://localhost:8000"] + restart: unless-stopped # possible values are: "no", always", "on-failure", "unless-stopped" + ports: + - "8111:8111" + healthcheck: + # Adjust below to match your container port + test: ["CMD", "curl", "-f", "http://localhost:8111/api/v1/heartbeat"] + interval: 10s + timeout: 10s + retries: 3 + container_name: tt_studio_chroma + + networks: + - tt_studio_network + networks: - llm_studio_network: + tt_studio_network: # need external flag to allow for the backend to manage the docker network # otherwise, docker compose will create an app_* network for the backend container # to avoid colliding existing docker networks external: true - name: llm_studio_network + name: tt_studio_network diff --git a/app/frontend/.eslintrc.cjs b/app/frontend/.eslintrc.cjs index d6c95379..464eccb4 100644 --- a/app/frontend/.eslintrc.cjs +++ b/app/frontend/.eslintrc.cjs @@ -1,18 +1,29 @@ module.exports = { root: true, - env: { browser: true, es2020: true }, + env: { browser: true, es2020: true, node: true }, extends: [ - 'eslint:recommended', - 'plugin:@typescript-eslint/recommended', - 'plugin:react-hooks/recommended', + "eslint:recommended", + "plugin:@typescript-eslint/recommended", + "plugin:react-hooks/recommended", + "plugin:prettier/recommended", // Prettier as a plugin ], - ignorePatterns: ['dist', '.eslintrc.cjs'], - parser: '@typescript-eslint/parser', - plugins: ['react-refresh'], + ignorePatterns: ["dist", ".eslintrc.cjs", "vite-env.d.ts","src/components/ui"], + parser: "@typescript-eslint/parser", + plugins: ["react-refresh", "header", "prettier"], rules: { - 'react-refresh/only-export-components': [ - 'warn', + "react-refresh/only-export-components": [ + "warn", { allowConstantExport: true }, ], + "header/header": [ + "error", + "line", + [ + " SPDX-License-Identifier: Apache-2.0", + " SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC", + ], + ], + "prettier/prettier": "error", // Ensures Prettier rules are followed + }, -} +}; diff --git a/app/frontend/README.md b/app/frontend/README.md index 3bc8af12..6a9be167 100644 --- a/app/frontend/README.md +++ b/app/frontend/README.md @@ -90,3 +90,17 @@ Currently, two official plugins are available: - [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react/README.md) uses [Babel](https://babeljs.io/) for Fast Refresh - [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react-swc) uses [SWC](https://swc.rs/) for Fast Refresh + + +## Prettier and ESLint Configuration +The project uses Prettier and ESLint with specific VS Code plugins to ensure code quality and consistency. Additionally, these tools are configured to automatically add the Tenstorrent license headers to the files in the project. + +## Auto-Adding License Headers +To ensure that the correct Tenstorrent license headers are added to each file, the project includes configurations for Prettier, ESLint, and specific VS Code plugins. The required SPDX license headers will be added automatically upon saving or formatting the files. + +The license headers should look like this: + +```js +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC +``` diff --git a/app/frontend/index.html b/app/frontend/index.html index 383f2f4e..73ca136c 100644 --- a/app/frontend/index.html +++ b/app/frontend/index.html @@ -1,10 +1,10 @@ - + - llm studio v0.0 + TT-Studio v1.0
diff --git a/app/frontend/package-lock.json b/app/frontend/package-lock.json index bbccd811..ffbd099d 100644 --- a/app/frontend/package-lock.json +++ b/app/frontend/package-lock.json @@ -8,60 +8,82 @@ "name": "llm-studio-frontend", "version": "0.0.0", "dependencies": { - "@hookform/resolvers": "^3.3.4", - "@radix-ui/react-collapsible": "^1.0.3", - "@radix-ui/react-dialog": "^1.0.5", - "@radix-ui/react-dropdown-menu": "^2.0.6", - "@radix-ui/react-icons": "^1.3.0", - "@radix-ui/react-label": "^2.0.2", - "@radix-ui/react-navigation-menu": "^1.1.4", - "@radix-ui/react-popover": "^1.0.7", - "@radix-ui/react-progress": "^1.0.3", - "@radix-ui/react-scroll-area": "^1.0.5", - "@radix-ui/react-select": "^2.0.0", - "@radix-ui/react-separator": "^1.0.3", - "@radix-ui/react-slot": "^1.0.2", - "@radix-ui/react-tooltip": "^1.0.7", - "@tanstack/react-query": "^5.35.1", - "axios": "^1.6.8", + "@hookform/resolvers": "^3.9.1", + "@llm-ui/code": "^0.13.3", + "@llm-ui/markdown": "^0.13.3", + "@llm-ui/react": "^0.13.3", + "@radix-ui/react-accordion": "^1.2.1", + "@radix-ui/react-alert-dialog": "^1.1.2", + "@radix-ui/react-aspect-ratio": "^1.1.0", + "@radix-ui/react-collapsible": "^1.1.1", + "@radix-ui/react-dialog": "^1.1.2", + "@radix-ui/react-dropdown-menu": "^2.1.2", + "@radix-ui/react-label": "^2.1.0", + "@radix-ui/react-menubar": "^1.1.2", + "@radix-ui/react-navigation-menu": "^1.2.1", + "@radix-ui/react-popover": "^1.1.2", + "@radix-ui/react-progress": "^1.1.0", + "@radix-ui/react-scroll-area": "^1.2.1", + "@radix-ui/react-select": "^2.1.2", + "@radix-ui/react-separator": "^1.1.0", + "@radix-ui/react-slot": "^1.1.0", + "@radix-ui/react-tooltip": "^1.1.4", + "autoprefixer": "^10.4.20", + "axios": "^1.7.7", "class-variance-authority": "^0.7.0", "clsx": "^2.1.1", - "cmdk": "^1.0.0", - "framer-motion": "^11.1.9", - "lucide-react": "^0.378.0", + "cmdk": "^1.0.4", + "framer-motion": "^11.11.17", + "html-react-parser": "^5.1.18", + "lucide-react": "^0.460.0", "mini-svg-data-uri": "^1.4.4", - "react": "^18.2.0", + "react": "^18.3.1", "react-code-blocks": "^0.1.6", - "react-dom": "^18.2.0", - "react-hook-form": "^7.51.4", + "react-dom": "^18.3.1", + "react-hook-form": "^7.53.2", "react-hot-toast": "^2.4.1", - "react-router-dom": "^6.23.0", - "tailwind-merge": "^2.3.0", + "react-markdown": "^9.0.1", + "react-query": "^3.39.3", + "react-router-dom": "^6.28.0", + "react-virtualized-auto-sizer": "^1.0.24", + "react-window": "^1.8.10", + "remark-gfm": "^4.0.0", + "shiki": "^1.23.1", + "tailwind-merge": "^2.5.4", "tailwindcss-animate": "^1.0.7", - "vaul": "^0.9.1", - "zod": "^3.23.6" + "uuid": "^11.0.3", + "vaul": "^1.1.1", + "zod": "^3.23.8" }, "devDependencies": { - "@types/node": "^20.12.8", - "@types/react": "^18.2.66", - "@types/react-dom": "^18.2.22", - "@typescript-eslint/eslint-plugin": "^7.2.0", - "@typescript-eslint/parser": "^7.2.0", - "@vitejs/plugin-react-swc": "^3.5.0", - "autoprefixer": "^10.4.19", - "eslint": "^8.57.0", - 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"sha512-BN22B5eaMMI9UMtjrGd5g5eCYPpCPDUy0FJXbYsaT5zYxjFOckS53SQDE3pWkVoWpHXVb3BrYcEN4Twa55B5cA==", "dev": true, + "license": "MIT", "engines": { "node": ">=0.10.0" } @@ -5424,6 +10384,7 @@ "version": "8.1.0", "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-8.1.0.tgz", "integrity": "sha512-si7QWI6zUMq56bESFvagtmzMdGOtoxfR+Sez11Mobfc7tm+VkUckk9bW2UeffTGVUbOksxmSw0AA2gs8g71NCQ==", + "license": "MIT", "dependencies": { "ansi-styles": "^6.1.0", "string-width": "^5.0.1", @@ -5441,6 +10402,7 @@ "version": "7.0.0", "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz", "integrity": "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==", + "license": "MIT", "dependencies": { "ansi-styles": "^4.0.0", "string-width": "^4.1.0", @@ -5456,12 +10418,14 @@ "node_modules/wrap-ansi-cjs/node_modules/emoji-regex": { "version": "8.0.0", "resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-8.0.0.tgz", - "integrity": "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==" + "integrity": "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==", + "license": "MIT" }, "node_modules/wrap-ansi-cjs/node_modules/string-width": { "version": "4.2.3", "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz", "integrity": "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==", + "license": "MIT", "dependencies": { "emoji-regex": "^8.0.0", "is-fullwidth-code-point": "^3.0.0", @@ -5472,9 +10436,10 @@ } }, "node_modules/wrap-ansi/node_modules/ansi-regex": { - "version": "6.0.1", - "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.0.1.tgz", - "integrity": "sha512-n5M855fKb2SsfMIiFFoVrABHJC8QtHwVx+mHWP3QcEqBHYienj5dHSgjbxtC0WEZXYt4wcD6zrQElDPhFuZgfA==", + "version": "6.1.0", + "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.1.0.tgz", + "integrity": "sha512-7HSX4QQb4CspciLpVFwyRe79O3xsIZDDLER21kERQ71oaPodF8jL725AgJMFAYbooIqolJoRLuM81SpeUkpkvA==", + "license": "MIT", "engines": { "node": ">=12" }, @@ -5486,6 +10451,7 @@ "version": "6.2.1", "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-6.2.1.tgz", "integrity": "sha512-bN798gFfQX+viw3R7yrGWRqnrN2oRkEkUjjl4JNn4E8GxxbjtG3FbrEIIY3l8/hrwUwIeCZvi4QuOTP4MErVug==", + "license": "MIT", "engines": { "node": ">=12" }, @@ -5497,6 +10463,7 @@ "version": "7.1.0", "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.0.tgz", "integrity": "sha512-iq6eVVI64nQQTRYq2KtEg2d2uU7LElhTJwsH4YzIHZshxlgZms/wIc4VoDQTlG/IvVIrBKG06CrZnp0qv7hkcQ==", + "license": "MIT", "dependencies": { "ansi-regex": "^6.0.1" }, @@ -5511,26 +10478,46 @@ "version": "1.0.2", "resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz", "integrity": "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ==", - "dev": true + "license": "ISC" + }, + "node_modules/write-file-atomic": { + "version": "6.0.0", + "resolved": "https://registry.npmjs.org/write-file-atomic/-/write-file-atomic-6.0.0.tgz", + "integrity": "sha512-GmqrO8WJ1NuzJ2DrziEI2o57jKAVIQNf8a18W3nCYU3H7PNWqCCVTeH6/NQE93CIllIgQS98rrmVkYgTX9fFJQ==", + "dev": true, + "license": "ISC", + "dependencies": { + "imurmurhash": "^0.1.4", + "signal-exit": "^4.0.1" + }, + "engines": { + "node": "^18.17.0 || >=20.5.0" + } }, "node_modules/xtend": { "version": "4.0.2", "resolved": "https://registry.npmjs.org/xtend/-/xtend-4.0.2.tgz", "integrity": "sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ==", + "license": "MIT", "engines": { "node": ">=0.4" } }, "node_modules/yallist": { - "version": "4.0.0", - "resolved": "https://registry.npmjs.org/yallist/-/yallist-4.0.0.tgz", - "integrity": "sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==", - "dev": true + "version": "5.0.0", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-5.0.0.tgz", + "integrity": "sha512-YgvUTfwqyc7UXVMrB+SImsVYSmTS8X/tSrtdNZMImM+n7+QTriRXyXim0mBrTXNeqzVF0KWGgHPeiyViFFrNDw==", + "dev": true, + "license": "BlueOak-1.0.0", + "engines": { + "node": ">=18" + } }, "node_modules/yaml": { - "version": "2.4.2", - "resolved": "https://registry.npmjs.org/yaml/-/yaml-2.4.2.tgz", - "integrity": "sha512-B3VqDZ+JAg1nZpaEmWtTXUlBneoGx6CPM9b0TENK6aoSu5t73dItudwdgmi6tHlIZZId4dZ9skcAQ2UbcyAeVA==", + "version": "2.6.1", + "resolved": "https://registry.npmjs.org/yaml/-/yaml-2.6.1.tgz", + "integrity": "sha512-7r0XPzioN/Q9kXBro/XPnA6kznR73DHq+GXh5ON7ZozRO6aMjbmiBuKste2wslTFkC5d1dw0GooOCepZXJ2SAg==", + "license": "ISC", "bin": { "yaml": "bin.mjs" }, @@ -5543,6 +10530,7 @@ "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz", "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==", "dev": true, + "license": "MIT", "engines": { "node": ">=10" }, @@ -5551,12 +10539,23 @@ } }, "node_modules/zod": { - "version": "3.23.6", - "resolved": "https://registry.npmjs.org/zod/-/zod-3.23.6.tgz", - "integrity": "sha512-RTHJlZhsRbuA8Hmp/iNL7jnfc4nZishjsanDAfEY1QpDQZCahUp3xDzl+zfweE9BklxMUcgBgS1b7Lvie/ZVwA==", + "version": "3.24.0", + "resolved": "https://registry.npmjs.org/zod/-/zod-3.24.0.tgz", + "integrity": "sha512-Hz+wiY8yD0VLA2k/+nsg2Abez674dDGTai33SwNvMPuf9uIrBC9eFgIMQxBBbHFxVXi8W+5nX9DcAh9YNSQm/w==", + "license": "MIT", "funding": { "url": "https://github.com/sponsors/colinhacks" } + }, + "node_modules/zwitch": { + "version": "2.0.4", + "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz", + "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } } } } diff --git a/app/frontend/package.json b/app/frontend/package.json index d2fd9bf9..ed177dd6 100644 --- a/app/frontend/package.json +++ b/app/frontend/package.json @@ -4,59 +4,82 @@ "version": "0.0.0", "type": "module", "scripts": { - "dev": "vite", + "dev": "vite ", "build": "tsc && vite build", "lint": "eslint . --ext ts,tsx --report-unused-disable-directives --max-warnings 0", - "preview": "vite preview" + "lint-fix": "eslint . --ext ts,tsx --report-unused-disable-directives --max-warnings 0 --fix", + "preview": "vite preview", + "generate-license": "npx generate-license-file --input package.json --output ./third-party-licenses.txt" }, "dependencies": { - "@hookform/resolvers": "^3.3.4", - "@radix-ui/react-collapsible": "^1.0.3", - "@radix-ui/react-dialog": "^1.0.5", - "@radix-ui/react-dropdown-menu": "^2.0.6", - "@radix-ui/react-icons": "^1.3.0", - "@radix-ui/react-label": "^2.0.2", - "@radix-ui/react-navigation-menu": "^1.1.4", - "@radix-ui/react-popover": "^1.0.7", - "@radix-ui/react-progress": "^1.0.3", - "@radix-ui/react-scroll-area": "^1.0.5", - "@radix-ui/react-select": "^2.0.0", - "@radix-ui/react-separator": "^1.0.3", - "@radix-ui/react-slot": "^1.0.2", - "@radix-ui/react-tooltip": "^1.0.7", - "@tanstack/react-query": "^5.35.1", - "axios": "^1.6.8", + "@hookform/resolvers": "^3.9.1", + "@llm-ui/code": "^0.13.3", + "@llm-ui/markdown": "^0.13.3", + "@llm-ui/react": "^0.13.3", + "@radix-ui/react-accordion": "^1.2.1", + "@radix-ui/react-alert-dialog": "^1.1.2", + "@radix-ui/react-aspect-ratio": "^1.1.0", + "@radix-ui/react-collapsible": "^1.1.1", + "@radix-ui/react-dialog": "^1.1.2", + "@radix-ui/react-dropdown-menu": "^2.1.2", + "@radix-ui/react-label": "^2.1.0", + "@radix-ui/react-menubar": "^1.1.2", + "@radix-ui/react-navigation-menu": "^1.2.1", + "@radix-ui/react-popover": "^1.1.2", + "@radix-ui/react-progress": "^1.1.0", + "@radix-ui/react-scroll-area": "^1.2.1", + "@radix-ui/react-select": "^2.1.2", + "@radix-ui/react-separator": "^1.1.0", + "@radix-ui/react-slot": "^1.1.0", + "@radix-ui/react-tooltip": "^1.1.4", + "autoprefixer": "^10.4.20", + "axios": "^1.7.7", "class-variance-authority": "^0.7.0", "clsx": "^2.1.1", - "cmdk": "^1.0.0", - "framer-motion": "^11.1.9", - "lucide-react": "^0.378.0", + "cmdk": "^1.0.4", + "framer-motion": "^11.11.17", + "html-react-parser": "^5.1.18", + "lucide-react": "^0.460.0", "mini-svg-data-uri": "^1.4.4", - "react": "^18.2.0", + "react": "^18.3.1", "react-code-blocks": "^0.1.6", - "react-dom": "^18.2.0", - "react-hook-form": "^7.51.4", + "react-dom": "^18.3.1", + "react-hook-form": "^7.53.2", "react-hot-toast": "^2.4.1", - "react-router-dom": "^6.23.0", - "tailwind-merge": "^2.3.0", + "react-markdown": "^9.0.1", + "react-query": "^3.39.3", + "react-router-dom": "^6.28.0", + "react-virtualized-auto-sizer": "^1.0.24", + "react-window": "^1.8.10", + "remark-gfm": "^4.0.0", + "shiki": "^1.23.1", + "tailwind-merge": "^2.5.4", "tailwindcss-animate": "^1.0.7", - "vaul": "^0.9.1", - "zod": "^3.23.6" + "uuid": "^11.0.3", + "vaul": "^1.1.1", + "zod": "^3.23.8" }, "devDependencies": { - "@types/node": "^20.12.8", - "@types/react": "^18.2.66", - "@types/react-dom": "^18.2.22", - "@typescript-eslint/eslint-plugin": "^7.2.0", - "@typescript-eslint/parser": "^7.2.0", - "@vitejs/plugin-react-swc": "^3.5.0", - "autoprefixer": "^10.4.19", - "eslint": "^8.57.0", - "eslint-plugin-react-hooks": "^4.6.0", - "eslint-plugin-react-refresh": "^0.4.6", - "postcss": "^8.4.38", - "tailwindcss": "^3.4.3", - "typescript": "^5.2.2", - "vite": "^5.2.0" + "@types/node": "^22.9.1", + "@types/nunjucks": "^3.2.6", + "@types/react": "^18.3.12", + "@types/react-dom": "^18.3.1", + "@types/react-syntax-highlighter": "^15.5.13", + "@types/react-window": "^1.8.8", + "@typescript-eslint/eslint-plugin": "^8.15.0", + "@typescript-eslint/parser": "^8.15.0", + "@vitejs/plugin-react-swc": "^3.7.1", + "daisyui": "^4.12.14", + "eslint": "^9.15.0", + "eslint-config-prettier": "^9.1.0", + "eslint-plugin-header": "^3.1.1", + "eslint-plugin-prettier": "^5.2.1", + "eslint-plugin-react-hooks": "^5.0.0", + "eslint-plugin-react-refresh": "^0.4.14", + "generate-license-file": "^3.6.0", + "nunjucks": "^3.2.4", + "tailwindcss": "^3.4.15", + "typescript": "^5.6.3", + "vite": "^5.4.11" } } diff --git a/app/frontend/postcss.config.js b/app/frontend/postcss.config.js index 2e7af2b7..3d5ec0e2 100644 --- a/app/frontend/postcss.config.js +++ b/app/frontend/postcss.config.js @@ -1,6 +1,8 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC export default { plugins: { tailwindcss: {}, autoprefixer: {}, }, -} +}; diff --git a/app/frontend/src/App.tsx b/app/frontend/src/App.tsx index 4a8c3c22..2fa6dbd4 100644 --- a/app/frontend/src/App.tsx +++ b/app/frontend/src/App.tsx @@ -1,12 +1,21 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC import "./App.css"; import { ThemeProvider } from "./providers/ThemeProvider"; import AppRouter from "./routes/index.tsx"; +import { QueryClient, QueryClientProvider } from "react-query"; function App() { + const client = new QueryClient({ + defaultOptions: {}, + }); + return ( <> {/*
*/} - + + + {/*
*/} diff --git a/app/frontend/src/api/modelsDeployedApis.ts b/app/frontend/src/api/modelsDeployedApis.ts index 75c2752e..5c4c2bca 100644 --- a/app/frontend/src/api/modelsDeployedApis.ts +++ b/app/frontend/src/api/modelsDeployedApis.ts @@ -1,4 +1,5 @@ -// Summary: API functions for fetching and deleting models deployed on the models deployed component. +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Β© 2024 Tenstorrent AI ULC import axios from "axios"; import { customToast } from "../components/CustomToaster"; import { NavigateFunction } from "react-router-dom"; @@ -11,9 +12,11 @@ interface PortBinding { HostIp: string; HostPort: string; } + interface Network { DNSNames: string[]; } + interface ContainerData { name: string; status: string; @@ -24,6 +27,7 @@ interface ContainerData { port_bindings: { [key: string]: PortBinding[] }; networks: { [key: string]: Network }; } + interface Model { id: string; image: string; @@ -33,20 +37,31 @@ interface Model { name: string; } +interface StopResponse { + status: string; + stop_response: { + status: string; + output?: string; + }; + reset_response?: { + status: string; + output?: string; + }; +} + export const fetchModels = async (): Promise => { try { const response = await axios.get<{ [key: string]: ContainerData }>( - statusURl + statusURl, ); const data = response.data; - console.log("Data fetched for tables:", data); const models: Model[] = Object.keys(data).map((key) => { const container = data[key]; const portMapping = Object.keys(container.port_bindings) .map( (port) => - `${container.port_bindings[port][0].HostIp}:${container.port_bindings[port][0].HostPort}->${port}` + `${container.port_bindings[port][0].HostIp}:${container.port_bindings[port][0].HostPort}->${port}`, ) .join(", "); @@ -68,40 +83,67 @@ export const fetchModels = async (): Promise => { } }; -export const deleteModel = async (modelId: string): Promise => { +export const deleteModel = async (modelId: string): Promise => { const truncatedModelId = modelId.substring(0, 4); try { const payload = JSON.stringify({ container_id: modelId }); console.log("Payload:", payload); - const response = await axios.post(stopModelsURL, payload, { + const response = await axios.post(stopModelsURL, payload, { headers: { "Content-Type": "application/json", }, }); - console.log("Response:", response); + console.log("Response: on ts from backend", response); - if (response.data.status !== "success") { + if ( + response.data.status !== "success" || + !response.data.stop_response || + response.data.stop_response.status !== "success" + ) { customToast.error("Failed to stop the container"); throw new Error("Failed to stop the container"); + } else { + customToast.success( + `Model ID: ${truncatedModelId} has been deleted successfully.`, + ); + + if ( + response.data.reset_response && + response.data.reset_response.status === "success" + ) { + customToast.success( + `Model ID: ${truncatedModelId} has been reset successfully.`, + ); + } else { + customToast.error(`Board Reset failed.`); + } + + console.log( + `Reset Output: ${ + response.data.reset_response?.output || "No reset output available" + }`, + ); } + + return response.data; } catch (error) { if (axios.isAxiosError(error)) { console.error("Error stopping the container:", error.response?.data); customToast.error( `Failed to delete Model ID: ${truncatedModelId} - ${ error.response?.data.message || error.message - }` + }`, ); } else if (error instanceof Error) { console.error("Error stopping the container:", error.message); customToast.error( - `Failed to delete Model ID: ${truncatedModelId} - ${error.message}` + `Failed to delete Model ID: ${truncatedModelId} - ${error.message}`, ); } else { console.error("Unknown error stopping the container", error); customToast.error( - `Failed to delete Model ID: ${truncatedModelId} - Unknown error` + `Failed to delete Model ID: ${truncatedModelId} - Unknown error`, ); } throw error; @@ -109,19 +151,18 @@ export const deleteModel = async (modelId: string): Promise => { }; export const handleRedeploy = (modelName: string): void => { - console.log(`Redeploy button clicked for model: ${modelName}`); customToast.success(`Model ${modelName} has been redeployed.`); }; export const handleChatUI = ( modelID: string, - navigate: NavigateFunction + modelName: string, + navigate: NavigateFunction, ): void => { - console.log(`ChatUI button clicked for model: ${modelID}`); - console.log("Opening Chat UI for model"); - customToast.success(`Chat UI for model ${modelID} opened.`); - - navigate("/chat-ui", { state: { containerID: modelID } }); + customToast.success(`Chat UI page opened!`); + navigate("/chat-ui", { + state: { containerID: modelID, modelName: modelName }, + }); console.log("Navigated to chat-ui page"); }; diff --git a/app/frontend/src/assets/tt_line_graphics_1.png b/app/frontend/src/assets/tt_line_graphics_1.png new file mode 100644 index 00000000..d572ba97 Binary files /dev/null and b/app/frontend/src/assets/tt_line_graphics_1.png differ diff --git a/app/frontend/src/assets/tt_logo.svg b/app/frontend/src/assets/tt_logo.svg index 093f4be2..d20f8628 100644 --- a/app/frontend/src/assets/tt_logo.svg +++ b/app/frontend/src/assets/tt_logo.svg @@ -1,9 +1,18 @@ - - - - - - - - - + +image/svg+xml + \ No newline at end of file diff --git a/app/frontend/src/components/ChatComponent.tsx b/app/frontend/src/components/ChatComponent.tsx deleted file mode 100644 index 080bcdad..00000000 --- a/app/frontend/src/components/ChatComponent.tsx +++ /dev/null @@ -1,285 +0,0 @@ -import React, { useEffect, useState, useRef } from "react"; -import { Card } from "./ui/card"; -import { Button } from "./ui/button"; -import { ScrollArea } from "./ui/scroll-area"; -import { useLocation } from "react-router-dom"; -import { Spinner } from "./ui/spinner"; -import { - Smile, - Sun, - User, - Angry, - DollarSign, - CircleArrowUp, - ChevronDown, -} from "lucide-react"; -import { Textarea } from "./ui/textarea"; -import logo from "../assets/tt_logo.svg"; - -interface InferenceRequest { - deploy_id: string; - text: string; -} - -interface ChatMessage { - sender: "user" | "assistant"; - text: string; -} - -const modelAPIURL = "/models-api/"; -const inferenceUrl = `${modelAPIURL}/inference/`; - -const ChatComponent: React.FC = () => { - const location = useLocation(); - const [textInput, setTextInput] = useState(""); - const [chatHistory, setChatHistory] = useState([]); - const [modelID, setModelID] = useState(location.state.containerID); - const [isStreaming, setIsStreaming] = useState(false); - const scrollAreaRef = useRef(null); - const bottomRef = useRef(null); - const [isScrollButtonVisible, setIsScrollButtonVisible] = useState(false); - - useEffect(() => { - setModelID(location.state.containerID); - }, [location.state.containerID]); - - const scrollToBottom = () => { - if (bottomRef.current) { - bottomRef.current.scrollIntoView({ behavior: "smooth" }); - } - }; - - useEffect(() => { - scrollToBottom(); - }, [chatHistory]); - - const handleScroll = () => { - if (scrollAreaRef.current) { - const isAtBottom = - scrollAreaRef.current.scrollHeight - scrollAreaRef.current.scrollTop <= - scrollAreaRef.current.clientHeight + 1; - setIsScrollButtonVisible(!isAtBottom); - } - }; - - const runInference = async (request: InferenceRequest) => { - try { - setIsStreaming(true); - const response = await fetch(inferenceUrl, { - method: "POST", - headers: { - "Content-Type": "application/json", - }, - body: JSON.stringify(request), - }); - - const reader = response.body?.getReader(); - - // Add user input to chat history - setChatHistory((prevHistory) => [ - ...prevHistory, - { sender: "user", text: textInput }, - ]); - setTextInput(""); - - let result = ""; - if (reader) { - while (true) { - const { done, value } = await reader.read(); - if (done) break; - - const decoder = new TextDecoder(); - const chunk = decoder.decode(value); - result += chunk; - const cleanedResult = result.replace(/<\|endoftext\|>/g, ""); - setChatHistory((prevHistory) => { - const lastMessage = prevHistory[prevHistory.length - 1]; - if (lastMessage && lastMessage.sender === "assistant") { - const updatedHistory = [...prevHistory]; - updatedHistory[updatedHistory.length - 1] = { - ...lastMessage, - text: cleanedResult, - }; - return updatedHistory; - } else { - return [ - ...prevHistory, - { sender: "assistant", text: cleanedResult }, - ]; - } - }); - scrollToBottom(); // Ensure scroll to bottom while streaming - } - } - - setIsStreaming(false); - } catch (error) { - console.error("Error running inference:", error); - setIsStreaming(false); - } - }; - - const handleInference = () => { - if (textInput.trim() === "") return; - - const inferenceRequest: InferenceRequest = { - deploy_id: modelID, - text: textInput, - }; - console.log("Inference Request:", inferenceRequest); - - // Special case for the predefined question - if (textInput === "When will Tenstorrent out sell Nvidia?") { - setChatHistory((prevHistory) => [ - ...prevHistory, - { sender: "user", text: textInput }, - { sender: "assistant", text: "2024, that was a silly question." }, - ]); - setTextInput(""); - scrollToBottom(); // Ensure scroll to bottom after adding special response - return; - } - - runInference(inferenceRequest); - }; - - const handleKeyPress = (e: React.KeyboardEvent) => { - if (e.key === "Enter" && !e.shiftKey) { - e.preventDefault(); - handleInference(); - } - }; - - return ( -
- -
- {chatHistory.length === 0 && ( -
- Tenstorrent Logo -

- Start a conversation with LLM Studio Chat... -

-
-
- setTextInput("Hello, how are you today?")} - > - - Hello, how are you today? - - setTextInput("Can you tell me a joke?")} - > - - Can you tell me a joke? - - setTextInput("What's the weather like?")} - > - - What's the weather like? - - - setTextInput("When will Tenstorrent out sell Nvidia?") - } - > - - When will Tenstorrent out sell Nvidia? - -
-
-
- )} - {chatHistory.length > 0 && ( -
- -

Chat Responses:

- {chatHistory.map((message, index) => ( -
-
- {message.sender === "user" ? ( - - ) : ( - Tenstorrent Logo - )} - {message.text} -
-
- ))} -
- - {isScrollButtonVisible && ( - - )} -
- )} -
-