diff --git a/.docker/router.yml b/.docker/router.yml new file mode 100644 index 000000000..3b55df9ef --- /dev/null +++ b/.docker/router.yml @@ -0,0 +1,16 @@ +http: + services: + ollama: + loadBalancer: + healthCheck: + interval: 5s + path: / + servers: + - url: http://ollama-cpu:11434 + - url: http://ollama-cuda:11434 + - url: http://host.docker.internal:11434 + + routers: + ollama-router: + rule: "PathPrefix(`/`)" + service: ollama \ No newline at end of file diff --git a/.github/ISSUE_TEMPLATE/bug.yml b/.github/ISSUE_TEMPLATE/bug.yml new file mode 100644 index 000000000..7901a79ce --- /dev/null +++ b/.github/ISSUE_TEMPLATE/bug.yml @@ -0,0 +1,105 @@ +name: Bug Report +description: Report a bug or issue with the project. +title: "[BUG] " +labels: ["bug"] + +body: + - type: markdown + attributes: + value: | + **Please describe the bug you encountered.** + + - type: checkboxes + id: pre-check + attributes: + label: Pre-check + description: Please confirm that you have searched for duplicate issues before creating this one. + options: + - label: I have searched the existing issues and none cover this bug. + required: true + + - type: textarea + id: description + attributes: + label: Description + description: Provide a detailed description of the bug. + placeholder: "Detailed description of the bug" + validations: + required: true + + - type: textarea + id: steps + attributes: + label: Steps to Reproduce + description: Provide the steps to reproduce the bug. + placeholder: "1. Step one\n2. Step two\n3. Step three" + validations: + required: true + + - type: input + id: expected + attributes: + label: Expected Behavior + description: Describe what you expected to happen. + placeholder: "Expected behavior" + validations: + required: true + + - type: input + id: actual + attributes: + label: Actual Behavior + description: Describe what actually happened. + placeholder: "Actual behavior" + validations: + required: true + + - type: input + id: environment + attributes: + label: Environment + description: Provide details about your environment (e.g., OS, GPU, profile, etc.). + placeholder: "Environment details" + validations: + required: true + + - type: input + id: additional + attributes: + label: Additional Information + description: Provide any additional information that may be relevant (e.g., logs, screenshots). + placeholder: "Any additional information that may be relevant" + + - type: input + id: version + attributes: + label: Version + description: Provide the version of the project where you encountered the bug. + placeholder: "Version number" + + - type: markdown + attributes: + value: | + **Please ensure the following setup checklist has been reviewed before submitting the bug report.** + + - type: checkboxes + id: general-setup-checklist + attributes: + label: Setup Checklist + description: Verify the following general aspects of your setup. + options: + - label: Confirm that you have followed the installation instructions in the project’s documentation. + - label: Check that you are using the latest version of the project. + - label: Verify disk space availability for model storage and data processing. + - label: Ensure that you have the necessary permissions to run the project. + + - type: checkboxes + id: nvidia-setup-checklist + attributes: + label: NVIDIA GPU Setup Checklist + description: Verify the following aspects of your NVIDIA GPU setup. + options: + - label: Check that the all CUDA dependencies are installed and are compatible with your GPU (refer to [CUDA's documentation](https://docs.nvidia.com/deploy/cuda-compatibility/#frequently-asked-questions)) + - label: Ensure an NVIDIA GPU is installed and recognized by the system (run `nvidia-smi` to verify). + - label: Ensure proper permissions are set for accessing GPU resources. + - label: Docker users - Verify that the NVIDIA Container Toolkit is configured correctly (e.g. run `sudo docker run --rm --gpus all nvidia/cuda:11.0.3-base-ubuntu20.04 nvidia-smi`) diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml new file mode 100644 index 000000000..eaae6e439 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/config.yml @@ -0,0 +1,8 @@ +blank_issues_enabled: false +contact_links: + - name: Documentation + url: https://docs.privategpt.dev + about: Please refer to our documentation for more details and guidance. + - name: Discord + url: https://discord.gg/bK6mRVpErU + about: Join our Discord community to ask questions and get help. diff --git a/.github/ISSUE_TEMPLATE/docs.yml b/.github/ISSUE_TEMPLATE/docs.yml new file mode 100644 index 000000000..e078bf2fc --- /dev/null +++ b/.github/ISSUE_TEMPLATE/docs.yml @@ -0,0 +1,19 @@ +name: Documentation +description: Suggest a change or addition to the documentation. +title: "[DOCS] " +labels: ["documentation"] + +body: + - type: markdown + attributes: + value: | + **Please describe the documentation change or addition you would like to suggest.** + + - type: textarea + id: description + attributes: + label: Description + description: Provide a detailed description of the documentation change. + placeholder: "Detailed description of the documentation change" + validations: + required: true diff --git a/.github/ISSUE_TEMPLATE/feature.yml b/.github/ISSUE_TEMPLATE/feature.yml new file mode 100644 index 000000000..648e19d21 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/feature.yml @@ -0,0 +1,37 @@ +name: Enhancement +description: Suggest an enhancement or improvement to the project. +title: "[FEATURE] " +labels: ["enhancement"] + +body: + - type: markdown + attributes: + value: | + **Please describe the enhancement or improvement you would like to suggest.** + + - type: textarea + id: feature_description + attributes: + label: Feature Description + description: Provide a detailed description of the enhancement. + placeholder: "Detailed description of the enhancement" + validations: + required: true + + - type: textarea + id: reason + attributes: + label: Reason + description: Explain the reason for this enhancement. + placeholder: "Reason for the enhancement" + validations: + required: true + + - type: textarea + id: value + attributes: + label: Value of Feature + description: Describe the value or benefits this feature will bring. + placeholder: "Value or benefits of the feature" + validations: + required: true diff --git a/.github/ISSUE_TEMPLATE/question.yml b/.github/ISSUE_TEMPLATE/question.yml new file mode 100644 index 000000000..bfd3003c4 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/question.yml @@ -0,0 +1,19 @@ +name: Question +description: Ask a question about the project. +title: "[QUESTION] " +labels: ["question"] + +body: + - type: markdown + attributes: + value: | + **Please describe your question in detail.** + + - type: textarea + id: question + attributes: + label: Question + description: Provide a detailed description of your question. + placeholder: "Detailed description of the question" + validations: + required: true diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md new file mode 100644 index 000000000..701ed1e31 --- /dev/null +++ b/.github/pull_request_template.md @@ -0,0 +1,37 @@ +# Description + +Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change. + +## Type of Change + +Please delete options that are not relevant. + +- [ ] Bug fix (non-breaking change which fixes an issue) +- [ ] New feature (non-breaking change which adds functionality) +- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected) +- [ ] This change requires a documentation update + +## How Has This Been Tested? + +Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration + +- [ ] Added new unit/integration tests +- [ ] I stared at the code and made sure it makes sense + +**Test Configuration**: +* Firmware version: +* Hardware: +* Toolchain: +* SDK: + +## Checklist: + +- [ ] My code follows the style guidelines of this project +- [ ] I have performed a self-review of my code +- [ ] I have commented my code, particularly in hard-to-understand areas +- [ ] I have made corresponding changes to the documentation +- [ ] My changes generate no new warnings +- [ ] I have added tests that prove my fix is effective or that my feature works +- [ ] New and existing unit tests pass locally with my changes +- [ ] Any dependent changes have been merged and published in downstream modules +- [ ] I ran `make check; make test` to ensure mypy and tests pass \ No newline at end of file diff --git a/.github/release_please/.release-please-config.json b/.github/release_please/.release-please-config.json new file mode 100644 index 000000000..97f317009 --- /dev/null +++ b/.github/release_please/.release-please-config.json @@ -0,0 +1,19 @@ +{ + "$schema": "https://raw.githubusercontent.com/googleapis/release-please/main/schemas/config.json", + "release-type": "simple", + "version-file": "version.txt", + "extra-files": [ + { + "type": "toml", + "path": "pyproject.toml", + "jsonpath": "$.tool.poetry.version" + }, + { + "type": "generic", + "path": "docker-compose.yaml" + } + ], + "packages": { + ".": {} + } + } \ No newline at end of file diff --git a/.github/release_please/.release-please-manifest.json b/.github/release_please/.release-please-manifest.json new file mode 100644 index 000000000..1b77f506d --- /dev/null +++ b/.github/release_please/.release-please-manifest.json @@ -0,0 +1,3 @@ +{ + ".": "0.7.0" +} \ No newline at end of file diff --git a/.github/workflows/actions/install_dependencies/action.yml b/.github/workflows/actions/install_dependencies/action.yml index 29234eeff..0d70dca77 100644 --- a/.github/workflows/actions/install_dependencies/action.yml +++ b/.github/workflows/actions/install_dependencies/action.yml @@ -8,7 +8,7 @@ inputs: poetry_version: required: true type: string - default: "1.5.1" + default: "1.8.3" runs: using: composite diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml deleted file mode 100644 index 259cf5da2..000000000 --- a/.github/workflows/docker.yml +++ /dev/null @@ -1,45 +0,0 @@ -name: docker - -on: - release: - types: [ published ] - workflow_dispatch: - -env: - REGISTRY: ghcr.io - IMAGE_NAME: ${{ github.repository }} - -jobs: - build-and-push-image: - runs-on: ubuntu-latest - permissions: - contents: read - packages: write - steps: - - name: Checkout repository - uses: actions/checkout@v4 - - name: Log in to the Container registry - uses: docker/login-action@v3 - with: - registry: ${{ env.REGISTRY }} - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - name: Extract metadata (tags, labels) for Docker - id: meta - uses: docker/metadata-action@v5 - with: - images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} - tags: | - type=ref,event=branch - type=ref,event=pr - type=semver,pattern={{version}} - type=semver,pattern={{major}}.{{minor}} - type=sha - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: Dockerfile.external - push: true - tags: ${{ steps.meta.outputs.tags }} - labels: ${{ steps.meta.outputs.labels }} diff --git a/.github/workflows/generate-release.yml b/.github/workflows/generate-release.yml new file mode 100644 index 000000000..36a95add5 --- /dev/null +++ b/.github/workflows/generate-release.yml @@ -0,0 +1,83 @@ +name: generate-release + +on: + release: + types: [ published ] + workflow_dispatch: + +env: + REGISTRY: docker.io + IMAGE_NAME: zylonai/private-gpt + platforms: linux/amd64,linux/arm64 + DEFAULT_TYPE: "ollama" + +jobs: + build-and-push-image: + runs-on: ubuntu-latest + + strategy: + matrix: + type: [ llamacpp-cpu, ollama ] + + permissions: + contents: read + packages: write + + outputs: + version: ${{ steps.version.outputs.version }} + + steps: + - name: Free Disk Space (Ubuntu) + uses: jlumbroso/free-disk-space@main + with: + tool-cache: false + android: true + dotnet: true + haskell: true + large-packages: true + docker-images: false + swap-storage: true + + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Set up QEMU + uses: docker/setup-qemu-action@v3 + + - name: Set up Docker Buildx + uses: docker/setup-buildx-action@v3 + + - name: Log in to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Extract metadata (tags, labels) for Docker + id: meta + uses: docker/metadata-action@v5 + with: + images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} + tags: | + type=semver,pattern={{version}},enable=${{ matrix.type == env.DEFAULT_TYPE }} + type=semver,pattern={{version}}-${{ matrix.type }} + type=semver,pattern={{major}}.{{minor}},enable=${{ matrix.type == env.DEFAULT_TYPE }} + type=semver,pattern={{major}}.{{minor}}-${{ matrix.type }} + type=raw,value=latest,enable=${{ matrix.type == env.DEFAULT_TYPE }} + type=sha + flavor: | + latest=false + + - name: Build and push Docker image + uses: docker/build-push-action@v6 + with: + context: . + file: Dockerfile.${{ matrix.type }} + platforms: ${{ env.platforms }} + push: true + tags: ${{ steps.meta.outputs.tags }} + labels: ${{ steps.meta.outputs.labels }} + + - name: Version output + id: version + run: echo "version=${{ steps.meta.outputs.version }}" >> "$GITHUB_OUTPUT" \ No newline at end of file diff --git a/.github/workflows/preview-docs.yml b/.github/workflows/preview-docs.yml index b865777ef..9afc1c9fa 100644 --- a/.github/workflows/preview-docs.yml +++ b/.github/workflows/preview-docs.yml @@ -11,13 +11,17 @@ jobs: preview-docs: runs-on: ubuntu-latest + permissions: + contents: read + pull-requests: write + steps: - name: Checkout repository uses: actions/checkout@v4 with: ref: refs/pull/${{ github.event.pull_request.number }}/merge - - name: Setup Node.js + - name: Setup Node.js uses: actions/setup-node@v4 with: node-version: "18" @@ -37,14 +41,14 @@ jobs: # Set the output for the step echo "::set-output name=preview_url::$preview_url" - name: Comment PR with URL using github-actions bot - uses: actions/github-script@v4 + uses: actions/github-script@v7 if: ${{ steps.generate_docs.outputs.preview_url }} with: script: | const preview_url = '${{ steps.generate_docs.outputs.preview_url }}'; - const issue_number = context.issue.number; - github.issues.createComment({ - ...context.repo, - issue_number: issue_number, + github.rest.issues.createComment({ + issue_number: context.issue.number, + owner: context.repo.owner, + repo: context.repo.repo, body: `Published docs preview URL: ${preview_url}` }) diff --git a/.github/workflows/release-please.yml b/.github/workflows/release-please.yml index b7b74e05d..1e3f05c66 100644 --- a/.github/workflows/release-please.yml +++ b/.github/workflows/release-please.yml @@ -13,7 +13,8 @@ jobs: release-please: runs-on: ubuntu-latest steps: - - uses: google-github-actions/release-please-action@v3 + - uses: google-github-actions/release-please-action@v4 + id: release with: - release-type: simple - version-file: version.txt \ No newline at end of file + config-file: .github/release_please/.release-please-config.json + manifest-file: .github/release_please/.release-please-manifest.json diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 6a450cbed..ad8450de7 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -14,7 +14,7 @@ jobs: setup: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - uses: ./.github/workflows/actions/install_dependencies checks: @@ -28,7 +28,7 @@ jobs: - ruff - mypy steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - uses: ./.github/workflows/actions/install_dependencies - name: run ${{ matrix.quality-command }} run: make ${{ matrix.quality-command }} @@ -38,7 +38,7 @@ jobs: runs-on: ubuntu-latest name: test steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - uses: ./.github/workflows/actions/install_dependencies - name: run test run: make test-coverage diff --git a/CHANGELOG.md b/CHANGELOG.md index 37e5dce34..98cd443fe 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,82 @@ # Changelog +## [0.7.0](https://github.com/zylon-ai/private-gpt/compare/v0.6.2...v0.7.0) (2024-10-17) + + +### Features + +* add retry connection to ollama ([#2084](https://github.com/zylon-ai/private-gpt/issues/2084)) ([77461b9](https://github.com/zylon-ai/private-gpt/commit/77461b96cf2e18b88b592fff441206a49826db97)) +* Adding MistralAI mode ([#2065](https://github.com/zylon-ai/private-gpt/issues/2065)) ([f9182b3](https://github.com/zylon-ai/private-gpt/commit/f9182b3a86d88af7c699b41b3a5f21401117acfc)) +* update llama-index + dependencies ([#2092](https://github.com/zylon-ai/private-gpt/issues/2092)) ([5851b02](https://github.com/zylon-ai/private-gpt/commit/5851b02378313f3dba315e0251cfd421af79dae6)) + + +### Bug Fixes + +* 503 when private gpt gets ollama service ([#2104](https://github.com/zylon-ai/private-gpt/issues/2104)) ([940bdd4](https://github.com/zylon-ai/private-gpt/commit/940bdd49af14d9c1e7fd4af54f12648b5fc1f9c0)) +* Add default mode option to settings ([#2078](https://github.com/zylon-ai/private-gpt/issues/2078)) ([fa3c306](https://github.com/zylon-ai/private-gpt/commit/fa3c30661d2ab04634361e20e7819365e3dd351a)) +* docker permissions ([#2059](https://github.com/zylon-ai/private-gpt/issues/2059)) ([8c12c68](https://github.com/zylon-ai/private-gpt/commit/8c12c6830b37851cccb3fea75faa820fce49284a)) +* naming image and ollama-cpu ([#2056](https://github.com/zylon-ai/private-gpt/issues/2056)) ([89477ea](https://github.com/zylon-ai/private-gpt/commit/89477ea9d3a83181b0222b732a81c71db9edf142)) +* Rectify ffmpy poetry config; update version from 0.3.2 to 0.4.0 ([#2062](https://github.com/zylon-ai/private-gpt/issues/2062)) ([7603b36](https://github.com/zylon-ai/private-gpt/commit/7603b3627d91aed1cce2e1ae407fec11ca1ad132)) +* Sanitize null bytes before ingestion ([#2090](https://github.com/zylon-ai/private-gpt/issues/2090)) ([5fbb402](https://github.com/zylon-ai/private-gpt/commit/5fbb402477c41e09f56a3e5adc32f316341772bf)) + +## [0.6.2](https://github.com/zylon-ai/private-gpt/compare/v0.6.1...v0.6.2) (2024-08-08) + + +### Bug Fixes + +* add numpy issue to troubleshooting ([#2048](https://github.com/zylon-ai/private-gpt/issues/2048)) ([4ca6d0c](https://github.com/zylon-ai/private-gpt/commit/4ca6d0cb556be7a598f7d3e3b00d2a29214ee1e8)) +* auto-update version ([#2052](https://github.com/zylon-ai/private-gpt/issues/2052)) ([7fefe40](https://github.com/zylon-ai/private-gpt/commit/7fefe408b4267684c6e3c1a43c5dc2b73ec61fe4)) +* publish image name ([#2043](https://github.com/zylon-ai/private-gpt/issues/2043)) ([b1acf9d](https://github.com/zylon-ai/private-gpt/commit/b1acf9dc2cbca2047cd0087f13254ff5cda6e570)) +* update matplotlib to 3.9.1-post1 to fix win install ([b16abbe](https://github.com/zylon-ai/private-gpt/commit/b16abbefe49527ac038d235659854b98345d5387)) + +## [0.6.1](https://github.com/zylon-ai/private-gpt/compare/v0.6.0...v0.6.1) (2024-08-05) + + +### Bug Fixes + +* add built image from DockerHub ([#2042](https://github.com/zylon-ai/private-gpt/issues/2042)) ([f09f6dd](https://github.com/zylon-ai/private-gpt/commit/f09f6dd2553077d4566dbe6b48a450e05c2f049e)) +* Adding azopenai to model list ([#2035](https://github.com/zylon-ai/private-gpt/issues/2035)) ([1c665f7](https://github.com/zylon-ai/private-gpt/commit/1c665f7900658144f62814b51f6e3434a6d7377f)) +* **deploy:** generate docker release when new version is released ([#2038](https://github.com/zylon-ai/private-gpt/issues/2038)) ([1d4c14d](https://github.com/zylon-ai/private-gpt/commit/1d4c14d7a3c383c874b323d934be01afbaca899e)) +* **deploy:** improve Docker-Compose and quickstart on Docker ([#2037](https://github.com/zylon-ai/private-gpt/issues/2037)) ([dae0727](https://github.com/zylon-ai/private-gpt/commit/dae0727a1b4abd35d2b0851fe30e0a4ed67e0fbb)) + +## [0.6.0](https://github.com/zylon-ai/private-gpt/compare/v0.5.0...v0.6.0) (2024-08-02) + + +### Features + +* bump dependencies ([#1987](https://github.com/zylon-ai/private-gpt/issues/1987)) ([b687dc8](https://github.com/zylon-ai/private-gpt/commit/b687dc852413404c52d26dcb94536351a63b169d)) +* **docs:** add privategpt-ts sdk ([#1924](https://github.com/zylon-ai/private-gpt/issues/1924)) ([d13029a](https://github.com/zylon-ai/private-gpt/commit/d13029a046f6e19e8ee65bef3acd96365c738df2)) +* **docs:** Fix setup docu ([#1926](https://github.com/zylon-ai/private-gpt/issues/1926)) ([067a5f1](https://github.com/zylon-ai/private-gpt/commit/067a5f144ca6e605c99d7dbe9ca7d8207ac8808d)) +* **docs:** update doc for ipex-llm ([#1968](https://github.com/zylon-ai/private-gpt/issues/1968)) ([19a7c06](https://github.com/zylon-ai/private-gpt/commit/19a7c065ef7f42b37f289dd28ac945f7afc0e73a)) +* **docs:** update documentation and fix preview-docs ([#2000](https://github.com/zylon-ai/private-gpt/issues/2000)) ([4523a30](https://github.com/zylon-ai/private-gpt/commit/4523a30c8f004aac7a7ae224671e2c45ec0cb973)) +* **llm:** add progress bar when ollama is pulling models ([#2031](https://github.com/zylon-ai/private-gpt/issues/2031)) ([cf61bf7](https://github.com/zylon-ai/private-gpt/commit/cf61bf780f8d122e4057d002abf03563bb45614a)) +* **llm:** autopull ollama models ([#2019](https://github.com/zylon-ai/private-gpt/issues/2019)) ([20bad17](https://github.com/zylon-ai/private-gpt/commit/20bad17c9857809158e689e9671402136c1e3d84)) +* **llm:** Support for Google Gemini LLMs and Embeddings ([#1965](https://github.com/zylon-ai/private-gpt/issues/1965)) ([fc13368](https://github.com/zylon-ai/private-gpt/commit/fc13368bc72d1f4c27644677431420ed77731c03)) +* make llama3.1 as default ([#2022](https://github.com/zylon-ai/private-gpt/issues/2022)) ([9027d69](https://github.com/zylon-ai/private-gpt/commit/9027d695c11fbb01e62424b855665de71d513417)) +* prompt_style applied to all LLMs + extra LLM params. ([#1835](https://github.com/zylon-ai/private-gpt/issues/1835)) ([e21bf20](https://github.com/zylon-ai/private-gpt/commit/e21bf20c10938b24711d9f2c765997f44d7e02a9)) +* **recipe:** add our first recipe `Summarize` ([#2028](https://github.com/zylon-ai/private-gpt/issues/2028)) ([8119842](https://github.com/zylon-ai/private-gpt/commit/8119842ae6f1f5ecfaf42b06fa0d1ffec675def4)) +* **vectordb:** Milvus vector db Integration ([#1996](https://github.com/zylon-ai/private-gpt/issues/1996)) ([43cc31f](https://github.com/zylon-ai/private-gpt/commit/43cc31f74015f8d8fcbf7a8ea7d7d9ecc66cf8c9)) +* **vectorstore:** Add clickhouse support as vectore store ([#1883](https://github.com/zylon-ai/private-gpt/issues/1883)) ([2612928](https://github.com/zylon-ai/private-gpt/commit/26129288394c7483e6fc0496a11dc35679528cc1)) + + +### Bug Fixes + +* "no such group" error in Dockerfile, added docx2txt and cryptography deps ([#1841](https://github.com/zylon-ai/private-gpt/issues/1841)) ([947e737](https://github.com/zylon-ai/private-gpt/commit/947e737f300adf621d2261d527192f36f3387f8e)) +* **config:** make tokenizer optional and include a troubleshooting doc ([#1998](https://github.com/zylon-ai/private-gpt/issues/1998)) ([01b7ccd](https://github.com/zylon-ai/private-gpt/commit/01b7ccd0648be032846647c9a184925d3682f612)) +* **docs:** Fix concepts.mdx referencing to installation page ([#1779](https://github.com/zylon-ai/private-gpt/issues/1779)) ([dde0224](https://github.com/zylon-ai/private-gpt/commit/dde02245bcd51a7ede7b6789c82ae217cac53d92)) +* **docs:** Update installation.mdx ([#1866](https://github.com/zylon-ai/private-gpt/issues/1866)) ([c1802e7](https://github.com/zylon-ai/private-gpt/commit/c1802e7cf0e56a2603213ec3b6a4af8fadb8a17a)) +* ffmpy dependency ([#2020](https://github.com/zylon-ai/private-gpt/issues/2020)) ([dabf556](https://github.com/zylon-ai/private-gpt/commit/dabf556dae9cb00fe0262270e5138d982585682e)) +* light mode ([#2025](https://github.com/zylon-ai/private-gpt/issues/2025)) ([1020cd5](https://github.com/zylon-ai/private-gpt/commit/1020cd53288af71a17882781f392512568f1b846)) +* **LLM:** mistral ignoring assistant messages ([#1954](https://github.com/zylon-ai/private-gpt/issues/1954)) ([c7212ac](https://github.com/zylon-ai/private-gpt/commit/c7212ac7cc891f9e3c713cc206ae9807c5dfdeb6)) +* **llm:** special tokens and leading space ([#1831](https://github.com/zylon-ai/private-gpt/issues/1831)) ([347be64](https://github.com/zylon-ai/private-gpt/commit/347be643f7929c56382a77c3f45f0867605e0e0a)) +* make embedding_api_base match api_base when on docker ([#1859](https://github.com/zylon-ai/private-gpt/issues/1859)) ([2a432bf](https://github.com/zylon-ai/private-gpt/commit/2a432bf9c5582a94eb4052b1e80cabdb118d298e)) +* nomic embeddings ([#2030](https://github.com/zylon-ai/private-gpt/issues/2030)) ([5465958](https://github.com/zylon-ai/private-gpt/commit/54659588b5b109a3dd17cca835e275240464d275)) +* prevent to ingest local files (by default) ([#2010](https://github.com/zylon-ai/private-gpt/issues/2010)) ([e54a8fe](https://github.com/zylon-ai/private-gpt/commit/e54a8fe0433252808d0a60f6a08a43c9f5a42f3b)) +* Replacing unsafe `eval()` with `json.loads()` ([#1890](https://github.com/zylon-ai/private-gpt/issues/1890)) ([9d0d614](https://github.com/zylon-ai/private-gpt/commit/9d0d614706581a8bfa57db45f62f84ab23d26f15)) +* **settings:** enable cors by default so it will work when using ts sdk (spa) ([#1925](https://github.com/zylon-ai/private-gpt/issues/1925)) ([966af47](https://github.com/zylon-ai/private-gpt/commit/966af4771dbe5cf3fdf554b5fdf8f732407859c4)) +* **ui:** gradio bug fixes ([#2021](https://github.com/zylon-ai/private-gpt/issues/2021)) ([d4375d0](https://github.com/zylon-ai/private-gpt/commit/d4375d078f18ba53562fd71651159f997fff865f)) +* unify embedding models ([#2027](https://github.com/zylon-ai/private-gpt/issues/2027)) ([40638a1](https://github.com/zylon-ai/private-gpt/commit/40638a18a5713d60fec8fe52796dcce66d88258c)) + ## [0.5.0](https://github.com/zylon-ai/private-gpt/compare/v0.4.0...v0.5.0) (2024-04-02) diff --git a/CITATION.cff b/CITATION.cff index 73a213df7..e077742e8 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -8,18 +8,9 @@ message: >- metadata from this file. type: software authors: - - given-names: Iván - family-names: Martínez Toro - email: ivanmartit@gmail.com - orcid: 'https://orcid.org/0009-0004-5065-2311' - - family-names: Gallego Vico - given-names: Daniel - email: danielgallegovico@gmail.com - orcid: 'https://orcid.org/0009-0006-8582-4384' - - given-names: Pablo - family-names: Orgaz - email: pabloogc+gh@gmail.com - orcid: 'https://orcid.org/0009-0008-0080-1437' -repository-code: 'https://github.com/imartinez/privateGPT' + - name: Zylon by PrivateGPT + address: hello@zylon.ai + website: 'https://www.zylon.ai/' +repository-code: 'https://github.com/zylon-ai/private-gpt' license: Apache-2.0 date-released: '2023-05-02' diff --git a/Dockerfile.external b/Dockerfile.external deleted file mode 100644 index 3e2530e09..000000000 --- a/Dockerfile.external +++ /dev/null @@ -1,40 +0,0 @@ -FROM python:3.11.6-slim-bookworm as base - -# Install poetry -RUN pip install pipx -RUN python3 -m pipx ensurepath -RUN pipx install poetry -ENV PATH="/root/.local/bin:$PATH" -ENV PATH=".venv/bin/:$PATH" - -# https://python-poetry.org/docs/configuration/#virtualenvsin-project -ENV POETRY_VIRTUALENVS_IN_PROJECT=true - -FROM base as dependencies -WORKDIR /home/worker/app -COPY pyproject.toml poetry.lock ./ - -RUN poetry install --extras "ui vector-stores-qdrant llms-ollama embeddings-ollama" - -FROM base as app - -ENV PYTHONUNBUFFERED=1 -ENV PORT=8080 -EXPOSE 8080 - -# Prepare a non-root user -RUN adduser --system worker -WORKDIR /home/worker/app - -RUN mkdir local_data; chown worker local_data -RUN mkdir models; chown worker models -COPY --chown=worker --from=dependencies /home/worker/app/.venv/ .venv -COPY --chown=worker private_gpt/ private_gpt -COPY --chown=worker fern/ fern -COPY --chown=worker *.yaml *.md ./ -COPY --chown=worker scripts/ scripts - -ENV PYTHONPATH="$PYTHONPATH:/private_gpt/" - -USER worker -ENTRYPOINT python -m private_gpt \ No newline at end of file diff --git a/Dockerfile.llamacpp-cpu b/Dockerfile.llamacpp-cpu new file mode 100644 index 000000000..feab1659b --- /dev/null +++ b/Dockerfile.llamacpp-cpu @@ -0,0 +1,62 @@ +### IMPORTANT, THIS IMAGE CAN ONLY BE RUN IN LINUX DOCKER +### You will run into a segfault in mac +FROM python:3.11.6-slim-bookworm AS base + +# Install poetry +RUN pip install pipx +RUN python3 -m pipx ensurepath +RUN pipx install poetry==1.8.3 +ENV PATH="/root/.local/bin:$PATH" +ENV PATH=".venv/bin/:$PATH" + +# Dependencies to build llama-cpp +RUN apt update && apt install -y \ + libopenblas-dev\ + ninja-build\ + build-essential\ + pkg-config\ + wget + +# https://python-poetry.org/docs/configuration/#virtualenvsin-project +ENV POETRY_VIRTUALENVS_IN_PROJECT=true + +FROM base AS dependencies +WORKDIR /home/worker/app +COPY pyproject.toml poetry.lock ./ + +ARG POETRY_EXTRAS="ui embeddings-huggingface llms-llama-cpp vector-stores-qdrant" +RUN poetry install --no-root --extras "${POETRY_EXTRAS}" + +FROM base AS app + +ENV PYTHONUNBUFFERED=1 +ENV PORT=8080 +ENV APP_ENV=prod +ENV PYTHONPATH="$PYTHONPATH:/home/worker/app/private_gpt/" +EXPOSE 8080 + +# Prepare a non-root user +# More info about how to configure UIDs and GIDs in Docker: +# https://github.com/systemd/systemd/blob/main/docs/UIDS-GIDS.md + +# Define the User ID (UID) for the non-root user +# UID 100 is chosen to avoid conflicts with existing system users +ARG UID=100 + +# Define the Group ID (GID) for the non-root user +# GID 65534 is often used for the 'nogroup' or 'nobody' group +ARG GID=65534 + +RUN adduser --system --gid ${GID} --uid ${UID} --home /home/worker worker +WORKDIR /home/worker/app + +RUN chown worker /home/worker/app +RUN mkdir local_data && chown worker local_data +RUN mkdir models && chown worker models +COPY --chown=worker --from=dependencies /home/worker/app/.venv/ .venv +COPY --chown=worker private_gpt/ private_gpt +COPY --chown=worker *.yaml ./ +COPY --chown=worker scripts/ scripts + +USER worker +ENTRYPOINT python -m private_gpt \ No newline at end of file diff --git a/Dockerfile.local b/Dockerfile.local deleted file mode 100644 index a52221164..000000000 --- a/Dockerfile.local +++ /dev/null @@ -1,50 +0,0 @@ -### IMPORTANT, THIS IMAGE CAN ONLY BE RUN IN LINUX DOCKER -### You will run into a segfault in mac -FROM python:3.11.6-slim-bookworm as base - -# Install poetry -RUN pip install pipx -RUN python3 -m pipx ensurepath -RUN pipx install poetry -ENV PATH="/root/.local/bin:$PATH" -ENV PATH=".venv/bin/:$PATH" - -# Dependencies to build llama-cpp -RUN apt update && apt install -y \ - libopenblas-dev\ - ninja-build\ - build-essential\ - pkg-config\ - wget - -# https://python-poetry.org/docs/configuration/#virtualenvsin-project -ENV POETRY_VIRTUALENVS_IN_PROJECT=true - -FROM base as dependencies -WORKDIR /home/worker/app -COPY pyproject.toml poetry.lock ./ - -RUN poetry install --extras "ui embeddings-huggingface llms-llama-cpp vector-stores-qdrant" - -FROM base as app - -ENV PYTHONUNBUFFERED=1 -ENV PORT=8080 -EXPOSE 8080 - -# Prepare a non-root user -RUN adduser --system worker -WORKDIR /home/worker/app - -RUN mkdir local_data; chown worker local_data -RUN mkdir models; chown worker models -COPY --chown=worker --from=dependencies /home/worker/app/.venv/ .venv -COPY --chown=worker private_gpt/ private_gpt -COPY --chown=worker fern/ fern -COPY --chown=worker *.yaml *.md ./ -COPY --chown=worker scripts/ scripts - -ENV PYTHONPATH="$PYTHONPATH:/private_gpt/" - -USER worker -ENTRYPOINT python -m private_gpt \ No newline at end of file diff --git a/Dockerfile.ollama b/Dockerfile.ollama new file mode 100644 index 000000000..83fd12976 --- /dev/null +++ b/Dockerfile.ollama @@ -0,0 +1,51 @@ +FROM python:3.11.6-slim-bookworm AS base + +# Install poetry +RUN pip install pipx +RUN python3 -m pipx ensurepath +RUN pipx install poetry==1.8.3 +ENV PATH="/root/.local/bin:$PATH" +ENV PATH=".venv/bin/:$PATH" + +# https://python-poetry.org/docs/configuration/#virtualenvsin-project +ENV POETRY_VIRTUALENVS_IN_PROJECT=true + +FROM base AS dependencies +WORKDIR /home/worker/app +COPY pyproject.toml poetry.lock ./ + +ARG POETRY_EXTRAS="ui vector-stores-qdrant llms-ollama embeddings-ollama" +RUN poetry install --no-root --extras "${POETRY_EXTRAS}" + +FROM base AS app +ENV PYTHONUNBUFFERED=1 +ENV PORT=8080 +ENV APP_ENV=prod +ENV PYTHONPATH="$PYTHONPATH:/home/worker/app/private_gpt/" +EXPOSE 8080 + +# Prepare a non-root user +# More info about how to configure UIDs and GIDs in Docker: +# https://github.com/systemd/systemd/blob/main/docs/UIDS-GIDS.md + +# Define the User ID (UID) for the non-root user +# UID 100 is chosen to avoid conflicts with existing system users +ARG UID=100 + +# Define the Group ID (GID) for the non-root user +# GID 65534 is often used for the 'nogroup' or 'nobody' group +ARG GID=65534 + +RUN adduser --system --gid ${GID} --uid ${UID} --home /home/worker worker +WORKDIR /home/worker/app + +RUN chown worker /home/worker/app +RUN mkdir local_data && chown worker local_data +RUN mkdir models && chown worker models +COPY --chown=worker --from=dependencies /home/worker/app/.venv/ .venv +COPY --chown=worker private_gpt/ private_gpt +COPY --chown=worker *.yaml . +COPY --chown=worker scripts/ scripts + +USER worker +ENTRYPOINT python -m private_gpt diff --git a/README.md b/README.md index 7d07f8dfd..b59ea28e9 100644 --- a/README.md +++ b/README.md @@ -1,22 +1,22 @@ # 🔒 PrivateGPT 📑 -[![Tests](https://github.com/imartinez/privateGPT/actions/workflows/tests.yml/badge.svg)](https://github.com/imartinez/privateGPT/actions/workflows/tests.yml?query=branch%3Amain) +[![Tests](https://github.com/zylon-ai/private-gpt/actions/workflows/tests.yml/badge.svg)](https://github.com/zylon-ai/private-gpt/actions/workflows/tests.yml?query=branch%3Amain) [![Website](https://img.shields.io/website?up_message=check%20it&down_message=down&url=https%3A%2F%2Fdocs.privategpt.dev%2F&label=Documentation)](https://docs.privategpt.dev/) - [![Discord](https://img.shields.io/discord/1164200432894234644?logo=discord&label=PrivateGPT)](https://discord.gg/bK6mRVpErU) [![X (formerly Twitter) Follow](https://img.shields.io/twitter/follow/ZylonPrivateGPT)](https://twitter.com/ZylonPrivateGPT) - -> Install & usage docs: https://docs.privategpt.dev/ -> -> Join the community: [Twitter](https://twitter.com/PrivateGPT_AI) & [Discord](https://discord.gg/bK6mRVpErU) - ![Gradio UI](/fern/docs/assets/ui.png?raw=true) PrivateGPT is a production-ready AI project that allows you to ask questions about your documents using the power of Large Language Models (LLMs), even in scenarios without an Internet connection. 100% private, no data leaves your execution environment at any point. +>[!TIP] +> If you are looking for an **enterprise-ready, fully private AI workspace** +> check out [Zylon's website](https://zylon.ai) or [request a demo](https://cal.com/zylon/demo?source=pgpt-readme). +> Crafted by the team behind PrivateGPT, Zylon is a best-in-class AI collaborative +> workspace that can be easily deployed on-premise (data center, bare metal...) or in your private cloud (AWS, GCP, Azure...). + The project provides an API offering all the primitives required to build private, context-aware AI applications. It follows and extends the [OpenAI API standard](https://openai.com/blog/openai-api), and supports both normal and streaming responses. @@ -38,13 +38,10 @@ In addition to this, a working [Gradio UI](https://www.gradio.app/) client is provided to test the API, together with a set of useful tools such as bulk model download script, ingestion script, documents folder watch, etc. -> 👂 **Need help applying PrivateGPT to your specific use case?** -> [Let us know more about it](https://forms.gle/4cSDmH13RZBHV9at7) -> and we'll try to help! We are refining PrivateGPT through your feedback. - ## 🎞️ Overview -DISCLAIMER: This README is not updated as frequently as the [documentation](https://docs.privategpt.dev/). -Please check it out for the latest updates! +>[!WARNING] +> This README is not updated as frequently as the [documentation](https://docs.privategpt.dev/). +> Please check it out for the latest updates! ### Motivation behind PrivateGPT Generative AI is a game changer for our society, but adoption in companies of all sizes and data-sensitive @@ -62,7 +59,7 @@ thus a simpler and more educational implementation to understand the basic conce to build a fully local -and therefore, private- chatGPT-like tool. If you want to keep experimenting with it, we have saved it in the -[primordial branch](https://github.com/imartinez/privateGPT/tree/primordial) of the project. +[primordial branch](https://github.com/zylon-ai/private-gpt/tree/primordial) of the project. > It is strongly recommended to do a clean clone and install of this new version of PrivateGPT if you come from the previous, primordial version. @@ -73,7 +70,7 @@ completions, document ingestion, RAG pipelines and other low-level building bloc We want to make it easier for any developer to build AI applications and experiences, as well as provide a suitable extensive architecture for the community to keep contributing. -Stay tuned to our [releases](https://github.com/imartinez/privateGPT/releases) to check out all the new features and changes included. +Stay tuned to our [releases](https://github.com/zylon-ai/private-gpt/releases) to check out all the new features and changes included. ## 📄 Documentation Full documentation on installation, dependencies, configuration, running the server, deployment options, @@ -132,19 +129,19 @@ Here are a couple of examples: #### BibTeX ```bibtex -@software{Martinez_Toro_PrivateGPT_2023, -author = {Martínez Toro, Iván and Gallego Vico, Daniel and Orgaz, Pablo}, +@software{Zylon_PrivateGPT_2023, +author = {Zylon by PrivateGPT}, license = {Apache-2.0}, month = may, title = {{PrivateGPT}}, -url = {https://github.com/imartinez/privateGPT}, +url = {https://github.com/zylon-ai/private-gpt}, year = {2023} } ``` #### APA ``` -Martínez Toro, I., Gallego Vico, D., & Orgaz, P. (2023). PrivateGPT [Computer software]. https://github.com/imartinez/privateGPT +Zylon by PrivateGPT (2023). PrivateGPT [Computer software]. https://github.com/zylon-ai/private-gpt ``` ## 🤗 Partners & Supporters diff --git a/docker-compose.yaml b/docker-compose.yaml index f12e1da95..ee40ebfa9 100644 --- a/docker-compose.yaml +++ b/docker-compose.yaml @@ -1,16 +1,116 @@ services: - private-gpt: + + #----------------------------------- + #---- Private-GPT services --------- + #----------------------------------- + + # Private-GPT service for the Ollama CPU and GPU modes + # This service builds from an external Dockerfile and runs the Ollama mode. + private-gpt-ollama: + image: ${PGPT_IMAGE:-zylonai/private-gpt}:${PGPT_TAG:-0.7.0}-ollama # x-release-please-version + user: root build: - dockerfile: Dockerfile.external + context: . + dockerfile: Dockerfile.ollama volumes: - - ./local_data/:/home/worker/app/local_data + - ./local_data:/home/worker/app/local_data ports: - - 8001:8080 + - "8001:8001" environment: - PORT: 8080 + PORT: 8001 PGPT_PROFILES: docker PGPT_MODE: ollama + PGPT_EMBED_MODE: ollama + PGPT_OLLAMA_API_BASE: http://ollama:11434 + HF_TOKEN: ${HF_TOKEN:-} + profiles: + - "" + - ollama-cpu + - ollama-cuda + - ollama-api + depends_on: + ollama: + condition: service_healthy + + # Private-GPT service for the local mode + # This service builds from a local Dockerfile and runs the application in local mode. + private-gpt-llamacpp-cpu: + image: ${PGPT_IMAGE:-zylonai/private-gpt}:${PGPT_TAG:-0.7.0}-llamacpp-cpu # x-release-please-version + user: root + build: + context: . + dockerfile: Dockerfile.llamacpp-cpu + volumes: + - ./local_data/:/home/worker/app/local_data + - ./models/:/home/worker/app/models + entrypoint: sh -c ".venv/bin/python scripts/setup && .venv/bin/python -m private_gpt" + ports: + - "8001:8001" + environment: + PORT: 8001 + PGPT_PROFILES: local + HF_TOKEN: ${HF_TOKEN:-} + profiles: + - llamacpp-cpu + + #----------------------------------- + #---- Ollama services -------------- + #----------------------------------- + + # Traefik reverse proxy for the Ollama service + # This will route requests to the Ollama service based on the profile. ollama: + image: traefik:v2.10 + healthcheck: + test: ["CMD", "sh", "-c", "wget -q --spider http://ollama:11434 || exit 1"] + interval: 10s + retries: 3 + start_period: 5s + timeout: 5s + ports: + - "8080:8080" + command: + - "--providers.file.filename=/etc/router.yml" + - "--log.level=ERROR" + - "--api.insecure=true" + - "--providers.docker=true" + - "--providers.docker.exposedbydefault=false" + - "--entrypoints.web.address=:11434" + volumes: + - /var/run/docker.sock:/var/run/docker.sock:ro + - ./.docker/router.yml:/etc/router.yml:ro + extra_hosts: + - "host.docker.internal:host-gateway" + profiles: + - "" + - ollama-cpu + - ollama-cuda + - ollama-api + + # Ollama service for the CPU mode + ollama-cpu: + image: ollama/ollama:latest + ports: + - "11434:11434" + volumes: + - ./models:/root/.ollama + profiles: + - "" + - ollama-cpu + + # Ollama service for the CUDA mode + ollama-cuda: image: ollama/ollama:latest + ports: + - "11434:11434" volumes: - ./models:/root/.ollama + deploy: + resources: + reservations: + devices: + - driver: nvidia + count: 1 + capabilities: [gpu] + profiles: + - ollama-cuda diff --git a/fern/README.md b/fern/README.md index 72fe9f11d..a00d1e46c 100644 --- a/fern/README.md +++ b/fern/README.md @@ -1,4 +1,4 @@ -# Documentation of privateGPT +# Documentation of PrivateGPT The documentation of this project is being rendered thanks to [fern](https://github.com/fern-api/fern). diff --git a/fern/docs.yml b/fern/docs.yml index be0d904c2..d13822c84 100644 --- a/fern/docs.yml +++ b/fern/docs.yml @@ -10,6 +10,9 @@ tabs: overview: display-name: Overview icon: "fa-solid fa-home" + quickstart: + display-name: Quickstart + icon: "fa-solid fa-rocket" installation: display-name: Installation icon: "fa-solid fa-download" @@ -32,7 +35,13 @@ navigation: contents: - page: Introduction path: ./docs/pages/overview/welcome.mdx - # How to install privateGPT, with FAQ and troubleshooting + - tab: quickstart + layout: + - section: Getting started + contents: + - page: Quickstart + path: ./docs/pages/quickstart/quickstart.mdx + # How to install PrivateGPT, with FAQ and troubleshooting - tab: installation layout: - section: Getting started @@ -41,7 +50,9 @@ navigation: path: ./docs/pages/installation/concepts.mdx - page: Installation path: ./docs/pages/installation/installation.mdx - # Manual of privateGPT: how to use it and configure it + - page: Troubleshooting + path: ./docs/pages/installation/troubleshooting.mdx + # Manual of PrivateGPT: how to use it and configure it - tab: manual layout: - section: General configuration @@ -68,17 +79,21 @@ navigation: path: ./docs/pages/manual/reranker.mdx - section: User Interface contents: - - page: User interface (Gradio) Manual - path: ./docs/pages/manual/ui.mdx - # Small code snippet or example of usage to help users + - page: Gradio Manual + path: ./docs/pages/ui/gradio.mdx + - page: Alternatives + path: ./docs/pages/ui/alternatives.mdx - tab: recipes layout: - - section: Choice of LLM + - section: Getting started + contents: + - page: Quickstart + path: ./docs/pages/recipes/quickstart.mdx + - section: General use cases contents: - # TODO: add recipes - - page: List of LLMs - path: ./docs/pages/recipes/list-llm.mdx - # More advanced usage of privateGPT, by API + - page: Summarize + path: ./docs/pages/recipes/summarize.mdx + # More advanced usage of PrivateGPT, by API - tab: api-reference layout: - section: Overview @@ -92,12 +107,11 @@ navigation: # Definition of the navbar, will be displayed in the top right corner. # `type:primary` is always displayed at the most right side of the navbar navbar-links: - - type: secondary - text: GitHub - url: "https://github.com/imartinez/privateGPT" - type: secondary text: Contact us url: "mailto:hello@zylon.ai" + - type: github + value: "https://github.com/zylon-ai/private-gpt" - type: primary text: Join the Discord url: https://discord.com/invite/bK6mRVpErU diff --git a/fern/docs/assets/ui.png b/fern/docs/assets/ui.png index 009427a51..c62c6d28c 100644 Binary files a/fern/docs/assets/ui.png and b/fern/docs/assets/ui.png differ diff --git a/fern/docs/pages/api-reference/sdks.mdx b/fern/docs/pages/api-reference/sdks.mdx index 0172d9d4e..897bb6b4f 100644 --- a/fern/docs/pages/api-reference/sdks.mdx +++ b/fern/docs/pages/api-reference/sdks.mdx @@ -8,14 +8,14 @@ The clients are kept up to date automatically, so we encourage you to use the la
@@ -26,12 +26,12 @@ The clients are kept up to date automatically, so we encourage you to use the la diff --git a/fern/docs/pages/installation/concepts.mdx b/fern/docs/pages/installation/concepts.mdx index 1ccb44682..0a8dc744b 100644 --- a/fern/docs/pages/installation/concepts.mdx +++ b/fern/docs/pages/installation/concepts.mdx @@ -8,20 +8,27 @@ It supports a variety of LLM providers, embeddings providers, and vector stores, ## Setup configurations available You get to decide the setup for these 3 main components: -- LLM: the large language model provider used for inference. It can be local, or remote, or even OpenAI. -- Embeddings: the embeddings provider used to encode the input, the documents and the users' queries. Same as the LLM, it can be local, or remote, or even OpenAI. -- Vector store: the store used to index and retrieve the documents. +- **LLM**: the large language model provider used for inference. It can be local, or remote, or even OpenAI. +- **Embeddings**: the embeddings provider used to encode the input, the documents and the users' queries. Same as the LLM, it can be local, or remote, or even OpenAI. +- **Vector store**: the store used to index and retrieve the documents. There is an extra component that can be enabled or disabled: the UI. It is a Gradio UI that allows to interact with the API in a more user-friendly way. + +A working **Gradio UI client** is provided to test the API, together with a set of useful tools such as bulk +model download script, ingestion script, documents folder watch, etc. Please refer to the [UI alternatives](/manual/user-interface/alternatives) page for more UI alternatives. + + ### Setups and Dependencies -Your setup will be the combination of the different options available. You'll find recommended setups in the [installation](/installation) section. +Your setup will be the combination of the different options available. You'll find recommended setups in the [installation](./installation) section. PrivateGPT uses poetry to manage its dependencies. You can install the dependencies for the different setups by running `poetry install --extras " ..."`. -Extras are the different options available for each component. For example, to install the dependencies for a a local setup with UI and qdrant as vector database, Ollama as LLM and HuggingFace as local embeddings, you would run +Extras are the different options available for each component. For example, to install the dependencies for a a local setup with UI and qdrant as vector database, Ollama as LLM and local embeddings, you would run: -`poetry install --extras "ui vector-stores-qdrant llms-ollama embeddings-huggingface"`. +```bash +poetry install --extras "ui vector-stores-qdrant llms-ollama embeddings-ollama" +``` -Refer to the [installation](/installation) section for more details. +Refer to the [installation](./installation) section for more details. ### Setups and Configuration PrivateGPT uses yaml to define its configuration in files named `settings-.yaml`. @@ -37,17 +44,6 @@ will load the configuration from `settings.yaml` and `settings-ollama.yaml`. ## About Fully Local Setups In order to run PrivateGPT in a fully local setup, you will need to run the LLM, Embeddings and Vector Store locally. -### Vector stores -The vector stores supported (Qdrant, ChromaDB and Postgres) run locally by default. -### Embeddings -For local Embeddings there are two options: -* (Recommended) You can use the 'ollama' option in PrivateGPT, which will connect to your local Ollama instance. Ollama simplifies a lot the installation of local LLMs. -* You can use the 'embeddings-huggingface' option in PrivateGPT, which will use HuggingFace. - -In order for HuggingFace LLM to work (the second option), you need to download the embeddings model to the `models` folder. You can do so by running the `setup` script: -```bash -poetry run python scripts/setup -``` ### LLM For local LLM there are two options: @@ -57,4 +53,15 @@ For local LLM there are two options: In order for LlamaCPP powered LLM to work (the second option), you need to download the LLM model to the `models` folder. You can do so by running the `setup` script: ```bash poetry run python scripts/setup -``` \ No newline at end of file +``` +### Embeddings +For local Embeddings there are two options: +* (Recommended) You can use the 'ollama' option in PrivateGPT, which will connect to your local Ollama instance. Ollama simplifies a lot the installation of local LLMs. +* You can use the 'embeddings-huggingface' option in PrivateGPT, which will use HuggingFace. + +In order for HuggingFace LLM to work (the second option), you need to download the embeddings model to the `models` folder. You can do so by running the `setup` script: +```bash +poetry run python scripts/setup +``` +### Vector stores +The vector stores supported (Qdrant, Milvus, ChromaDB and Postgres) run locally by default. \ No newline at end of file diff --git a/fern/docs/pages/installation/installation.mdx b/fern/docs/pages/installation/installation.mdx index 31a7953c3..e7f80c87d 100644 --- a/fern/docs/pages/installation/installation.mdx +++ b/fern/docs/pages/installation/installation.mdx @@ -1,63 +1,107 @@ -It is important that you review the Main Concepts before you start the installation process. +It is important that you review the [Main Concepts](../concepts) section to understand the different components of PrivateGPT and how they interact with each other. ## Base requirements to run PrivateGPT -* Clone PrivateGPT repository, and navigate to it: - +### 1. Clone the PrivateGPT Repository +Clone the repository and navigate to it: ```bash - git clone https://github.com/imartinez/privateGPT - cd privateGPT +git clone https://github.com/zylon-ai/private-gpt +cd private-gpt ``` -* Install Python `3.11` (*if you do not have it already*). Ideally through a python version manager like `pyenv`. - Earlier python versions are not supported. - * osx/linux: [pyenv](https://github.com/pyenv/pyenv) - * windows: [pyenv-win](https://github.com/pyenv-win/pyenv-win) - +### 2. Install Python 3.11 +If you do not have Python 3.11 installed, install it using a Python version manager like `pyenv`. Earlier Python versions are not supported. +#### macOS/Linux +Install and set Python 3.11 using [pyenv](https://github.com/pyenv/pyenv): +```bash +pyenv install 3.11 +pyenv local 3.11 +``` +#### Windows +Install and set Python 3.11 using [pyenv-win](https://github.com/pyenv-win/pyenv-win): ```bash pyenv install 3.11 pyenv local 3.11 ``` -* Install [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer) for dependency management: - -* Install `make` to be able to run the different scripts: - * osx: (Using homebrew): `brew install make` - * windows: (Using chocolatey) `choco install make` +### 3. Install `Poetry` +Install [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer) for dependency management: +Follow the instructions on the official Poetry website to install it. -## Install and run your desired setup + +A bug exists in Poetry versions 1.7.0 and earlier. We strongly recommend upgrading to a tested version. +To upgrade Poetry to latest tested version, run `poetry self update 1.8.3` after installing it. + -PrivateGPT allows to customize the setup -from fully local to cloud based- by deciding the modules to use. -Here are the different options available: +### 4. Optional: Install `make` +To run various scripts, you need to install `make`. Follow the instructions for your operating system: +#### macOS +(Using Homebrew): +```bash +brew install make +``` +#### Windows +(Using Chocolatey): +```bash +choco install make +``` -- LLM: "llama-cpp", "ollama", "sagemaker", "openai", "openailike", "azopenai" -- Embeddings: "huggingface", "openai", "sagemaker", "azopenai" -- Vector stores: "qdrant", "chroma", "postgres" -- UI: whether or not to enable UI (Gradio) or just go with the API +## Install and Run Your Desired Setup -In order to only install the required dependencies, PrivateGPT offers different `extras` that can be combined during the installation process: +PrivateGPT allows customization of the setup, from fully local to cloud-based, by deciding the modules to use. To install only the required dependencies, PrivateGPT offers different `extras` that can be combined during the installation process: ```bash poetry install --extras " ..." ``` +Where `` can be any of the following options described below. + +### Available Modules + +You need to choose one option per category (LLM, Embeddings, Vector Stores, UI). Below are the tables listing the available options for each category. + +#### LLM + +| **Option** | **Description** | **Extra** | +|--------------|------------------------------------------------------------------------|---------------------| +| **ollama** | Adds support for Ollama LLM, requires Ollama running locally | llms-ollama | +| llama-cpp | Adds support for local LLM using LlamaCPP | llms-llama-cpp | +| sagemaker | Adds support for Amazon Sagemaker LLM, requires Sagemaker endpoints | llms-sagemaker | +| openai | Adds support for OpenAI LLM, requires OpenAI API key | llms-openai | +| openailike | Adds support for 3rd party LLM providers compatible with OpenAI's API | llms-openai-like | +| azopenai | Adds support for Azure OpenAI LLM, requires Azure endpoints | llms-azopenai | +| gemini | Adds support for Gemini LLM, requires Gemini API key | llms-gemini | + +#### Embeddings -Where `` can be any of the following: - -- ui: adds support for UI using Gradio -- llms-ollama: adds support for Ollama LLM, the easiest way to get a local LLM running, requires Ollama running locally -- llms-llama-cpp: adds support for local LLM using LlamaCPP - expect a messy installation process on some platforms -- llms-sagemaker: adds support for Amazon Sagemaker LLM, requires Sagemaker inference endpoints -- llms-openai: adds support for OpenAI LLM, requires OpenAI API key -- llms-openai-like: adds support for 3rd party LLM providers that are compatible with OpenAI's API -- llms-azopenai: adds support for Azure OpenAI LLM, requires Azure OpenAI inference endpoints -- embeddings-ollama: adds support for Ollama Embeddings, requires Ollama running locally -- embeddings-huggingface: adds support for local Embeddings using HuggingFace -- embeddings-sagemaker: adds support for Amazon Sagemaker Embeddings, requires Sagemaker inference endpoints -- embeddings-openai = adds support for OpenAI Embeddings, requires OpenAI API key -- embeddings-azopenai = adds support for Azure OpenAI Embeddings, requires Azure OpenAI inference endpoints -- vector-stores-qdrant: adds support for Qdrant vector store -- vector-stores-chroma: adds support for Chroma DB vector store -- vector-stores-postgres: adds support for Postgres vector store +| **Option** | **Description** | **Extra** | +|------------------|--------------------------------------------------------------------------------|-------------------------| +| **ollama** | Adds support for Ollama Embeddings, requires Ollama running locally | embeddings-ollama | +| huggingface | Adds support for local Embeddings using HuggingFace | embeddings-huggingface | +| openai | Adds support for OpenAI Embeddings, requires OpenAI API key | embeddings-openai | +| sagemaker | Adds support for Amazon Sagemaker Embeddings, requires Sagemaker endpoints | embeddings-sagemaker | +| azopenai | Adds support for Azure OpenAI Embeddings, requires Azure endpoints | embeddings-azopenai | +| gemini | Adds support for Gemini Embeddings, requires Gemini API key | embeddings-gemini | + +#### Vector Stores + +| **Option** | **Description** | **Extra** | +|------------------|-----------------------------------------|-------------------------| +| **qdrant** | Adds support for Qdrant vector store | vector-stores-qdrant | +| milvus | Adds support for Milvus vector store | vector-stores-milvus | +| chroma | Adds support for Chroma DB vector store | vector-stores-chroma | +| postgres | Adds support for Postgres vector store | vector-stores-postgres | +| clickhouse | Adds support for Clickhouse vector store| vector-stores-clickhouse| + +#### UI + +| **Option** | **Description** | **Extra** | +|--------------|------------------------------------------|-----------| +| Gradio | Adds support for UI using Gradio | ui | + + +A working **Gradio UI client** is provided to test the API, together with a set of useful tools such as bulk +model download script, ingestion script, documents folder watch, etc. Please refer to the [UI alternatives](/manual/user-interface/alternatives) page for more UI alternatives. + ## Recommended Setups @@ -81,6 +125,8 @@ set PGPT_PROFILES=ollama make run ``` +Refer to the [troubleshooting](./troubleshooting) section for specific issues you might encounter. + ### Local, Ollama-powered setup - RECOMMENDED **The easiest way to run PrivateGPT fully locally** is to depend on Ollama for the LLM. Ollama provides local LLM and Embeddings super easy to install and use, abstracting the complexity of GPU support. It's the recommended setup for local development. @@ -89,16 +135,20 @@ Go to [ollama.ai](https://ollama.ai/) and follow the instructions to install Oll After the installation, make sure the Ollama desktop app is closed. -Install the models to be used, the default settings-ollama.yaml is configured to user `mistral 7b` LLM (~4GB) and `nomic-embed-text` Embeddings (~275MB). Therefore: - +Now, start Ollama service (it will start a local inference server, serving both the LLM and the Embeddings): ```bash -ollama pull mistral -ollama pull nomic-embed-text +ollama serve ``` -Now, start Ollama service (it will start a local inference server, serving both the LLM and the Embeddings): +Install the models to be used, the default settings-ollama.yaml is configured to user llama3.1 8b LLM (~4GB) and nomic-embed-text Embeddings (~275MB) + +By default, PGPT will automatically pull models as needed. This behavior can be changed by modifying the `ollama.autopull_models` property. + +In any case, if you want to manually pull models, run the following commands: + ```bash -ollama serve +ollama pull llama3.1 +ollama pull nomic-embed-text ``` Once done, on a different terminal, you can install PrivateGPT with the following command: @@ -257,11 +307,12 @@ If you have all required dependencies properly configured running the following powershell command should succeed. ```powershell -$env:CMAKE_ARGS='-DLLAMA_CUBLAS=on'; poetry run pip install --force-reinstall --no-cache-dir llama-cpp-python +$env:CMAKE_ARGS='-DLLAMA_CUBLAS=on'; poetry run pip install --force-reinstall --no-cache-dir llama-cpp-python numpy==1.26.0 ``` If your installation was correct, you should see a message similar to the following next -time you start the server `BLAS = 1`. +time you start the server `BLAS = 1`. If there is some issue, please refer to the +[troubleshooting](/installation/getting-started/troubleshooting#building-llama-cpp-with-nvidia-gpu-support) section. ```console llama_new_context_with_model: total VRAM used: 4857.93 MB (model: 4095.05 MB, context: 762.87 MB) @@ -289,11 +340,12 @@ Some tips: After that running the following command in the repository will install llama.cpp with GPU support: ```bash -CMAKE_ARGS='-DLLAMA_CUBLAS=on' poetry run pip install --force-reinstall --no-cache-dir llama-cpp-python +CMAKE_ARGS='-DLLAMA_CUBLAS=on' poetry run pip install --force-reinstall --no-cache-dir llama-cpp-python numpy==1.26.0 ``` If your installation was correct, you should see a message similar to the following next -time you start the server `BLAS = 1`. +time you start the server `BLAS = 1`. If there is some issue, please refer to the +[troubleshooting](/installation/getting-started/troubleshooting#building-llama-cpp-with-nvidia-gpu-support) section. ``` llama_new_context_with_model: total VRAM used: 4857.93 MB (model: 4095.05 MB, context: 762.87 MB) diff --git a/fern/docs/pages/installation/troubleshooting.mdx b/fern/docs/pages/installation/troubleshooting.mdx new file mode 100644 index 000000000..0b72526d2 --- /dev/null +++ b/fern/docs/pages/installation/troubleshooting.mdx @@ -0,0 +1,64 @@ +# Downloading Gated and Private Models +Many models are gated or private, requiring special access to use them. Follow these steps to gain access and set up your environment for using these models. +## Accessing Gated Models +1. **Request Access:** + Follow the instructions provided [here](https://huggingface.co/docs/hub/en/models-gated) to request access to the gated model. +2. **Generate a Token:** + Once you have access, generate a token by following the instructions [here](https://huggingface.co/docs/hub/en/security-tokens). +3. **Set the Token:** + Add the generated token to your `settings.yaml` file: + ```yaml + huggingface: + access_token: + ``` + Alternatively, set the `HF_TOKEN` environment variable: + ```bash + export HF_TOKEN= + ``` + +# Tokenizer Setup +PrivateGPT uses the `AutoTokenizer` library to tokenize input text accurately. It connects to HuggingFace's API to download the appropriate tokenizer for the specified model. + +## Configuring the Tokenizer +1. **Specify the Model:** + In your `settings.yaml` file, specify the model you want to use: + ```yaml + llm: + tokenizer: meta-llama/Meta-Llama-3.1-8B-Instruct + ``` +2. **Set Access Token for Gated Models:** + If you are using a gated model, ensure the `access_token` is set as mentioned in the previous section. +This configuration ensures that PrivateGPT can download and use the correct tokenizer for the model you are working with. + +# Embedding dimensions mismatch +If you encounter an error message like `Embedding dimensions mismatch`, it is likely due to the embedding model and +current vector dimension mismatch. To resolve this issue, ensure that the model and the input data have the same vector dimensions. + +By default, PrivateGPT uses `nomic-embed-text` embeddings, which have a vector dimension of 768. +If you are using a different embedding model, ensure that the vector dimensions match the model's output. + + +In versions below to 0.6.0, the default embedding model was `BAAI/bge-small-en-v1.5` in `huggingface` setup. +If you plan to reuse the old generated embeddings, you need to update the `settings.yaml` file to use the correct embedding model: +```yaml +huggingface: + embedding_hf_model_name: BAAI/bge-small-en-v1.5 +embedding: + embed_dim: 384 +``` + + +# Building Llama-cpp with NVIDIA GPU support + +## Out-of-memory error + +If you encounter an out-of-memory error while running `llama-cpp` with CUDA, you can try the following steps to resolve the issue: +1. **Set the next environment:** + ```bash + TOKENIZERS_PARALLELISM=true + ``` +2. **Run PrivateGPT:** + ```bash + poetry run python -m privategpt + ``` +Give thanks to [MarioRossiGithub](https://github.com/MarioRossiGithub) for providing the following solution. \ No newline at end of file diff --git a/fern/docs/pages/manual/ingestion.mdx b/fern/docs/pages/manual/ingestion.mdx index 053365592..9b10b9548 100644 --- a/fern/docs/pages/manual/ingestion.mdx +++ b/fern/docs/pages/manual/ingestion.mdx @@ -8,6 +8,14 @@ The ingestion of documents can be done in different ways: ## Bulk Local Ingestion +You will need to activate `data.local_ingestion.enabled` in your setting file to use this feature. Additionally, +it is probably a good idea to set `data.local_ingestion.allow_ingest_from` to specify which folders are allowed to be ingested. + + +Be careful enabling this feature in a production environment, as it can be a security risk, as it allows users to +ingest any local file with permissions. + + When you are running PrivateGPT in a fully local setup, you can ingest a complete folder for convenience (containing pdf, text files, etc.) and optionally watch changes on it with the command: @@ -93,7 +101,7 @@ time PGPT_PROFILES=mock python ./scripts/ingest_folder.py ~/my-dir/to-ingest/ ## Supported file formats -privateGPT by default supports all the file formats that contains clear text (for example, `.txt` files, `.html`, etc.). +PrivateGPT by default supports all the file formats that contains clear text (for example, `.txt` files, `.html`, etc.). However, these text based file formats as only considered as text files, and are not pre-processed in any other way. It also supports the following file formats: @@ -115,11 +123,15 @@ It also supports the following file formats: * `.ipynb` * `.json` -**Please note the following nuance**: while `privateGPT` supports these file formats, it **might** require additional + +While `PrivateGPT` supports these file formats, it **might** require additional dependencies to be installed in your python's virtual environment. -For example, if you try to ingest `.epub` files, `privateGPT` might fail to do it, and will instead display an +For example, if you try to ingest `.epub` files, `PrivateGPT` might fail to do it, and will instead display an explanatory error asking you to download the necessary dependencies to install this file format. + - + **Other file formats might work**, but they will be considered as plain text -files (in other words, they will be ingested as `.txt` files). \ No newline at end of file +files (in other words, they will be ingested as `.txt` files). + + diff --git a/fern/docs/pages/manual/llms.mdx b/fern/docs/pages/manual/llms.mdx index 8d9077eaa..c65944ef0 100644 --- a/fern/docs/pages/manual/llms.mdx +++ b/fern/docs/pages/manual/llms.mdx @@ -193,3 +193,42 @@ or When the server is started it will print a log *Application startup complete*. Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API. + +### Using IPEX-LLM + +For a fully private setup on Intel GPUs (such as a local PC with an iGPU, or discrete GPUs like Arc, Flex, and Max), you can use [IPEX-LLM](https://github.com/intel-analytics/ipex-llm). + +To deploy Ollama and pull models using IPEX-LLM, please refer to [this guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/ollama_quickstart.html). Then, follow the same steps outlined in the [Using Ollama](#using-ollama) section to create a `settings-ollama.yaml` profile and run the private-GPT server. + +### Using Gemini + +If you cannot run a local model (because you don't have a GPU, for example) or for testing purposes, you may +decide to run PrivateGPT using Gemini as the LLM and Embeddings model. In addition, you will benefit from +multimodal inputs, such as text and images, in a very large contextual window. + +In order to do so, create a profile `settings-gemini.yaml` with the following contents: + +```yaml +llm: + mode: gemini + +embedding: + mode: gemini + +gemini: + api_key: # You could skip this configuration and use the GEMINI_API_KEY env var instead + model: # Optional model to use. Default is models/gemini-pro" + embedding_model: # Optional model to use. Default is "models/embedding-001" +``` + +And run PrivateGPT loading that profile you just created: + +`PGPT_PROFILES=gemini make run` + +or + +`PGPT_PROFILES=gemini poetry run python -m private_gpt` + +When the server is started it will print a log *Application startup complete*. +Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API. + diff --git a/fern/docs/pages/manual/settings.mdx b/fern/docs/pages/manual/settings.mdx index 7f55cbfb0..09f6d151c 100644 --- a/fern/docs/pages/manual/settings.mdx +++ b/fern/docs/pages/manual/settings.mdx @@ -3,8 +3,8 @@ The configuration of your private GPT server is done thanks to `settings` files (more precisely `settings.yaml`). These text files are written using the [YAML](https://en.wikipedia.org/wiki/YAML) syntax. -While privateGPT is distributing safe and universal configuration files, you might want to quickly customize your -privateGPT, and this can be done using the `settings` files. +While PrivateGPT is distributing safe and universal configuration files, you might want to quickly customize your +PrivateGPT, and this can be done using the `settings` files. This project is defining the concept of **profiles** (or configuration profiles). This mechanism, using your environment variables, is giving you the ability to easily switch between @@ -30,15 +30,20 @@ For example, on **linux and macOS**, this gives: export PGPT_PROFILES=my_profile_name_here ``` -Windows Powershell(s) have a different syntax, one of them being: +Windows Command Prompt (cmd) has a different syntax: ```shell set PGPT_PROFILES=my_profile_name_here ``` + +Windows Powershell has a different syntax: +```shell +$env:PGPT_PROFILES="my_profile_name_here" +``` If the above is not working, you might want to try other ways to set an env variable in your window's terminal. --- -Once you've set this environment variable to the desired profile, you can simply launch your privateGPT, +Once you've set this environment variable to the desired profile, you can simply launch your PrivateGPT, and it will run using your profile on top of the default configuration. ## Reference diff --git a/fern/docs/pages/manual/vectordb.mdx b/fern/docs/pages/manual/vectordb.mdx index c98efea8a..ac3dffccd 100644 --- a/fern/docs/pages/manual/vectordb.mdx +++ b/fern/docs/pages/manual/vectordb.mdx @@ -1,7 +1,7 @@ ## Vectorstores -PrivateGPT supports [Qdrant](https://qdrant.tech/), [Chroma](https://www.trychroma.com/) and [PGVector](https://github.com/pgvector/pgvector) as vectorstore providers. Qdrant being the default. +PrivateGPT supports [Qdrant](https://qdrant.tech/), [Milvus](https://milvus.io/), [Chroma](https://www.trychroma.com/), [PGVector](https://github.com/pgvector/pgvector) and [ClickHouse](https://github.com/ClickHouse/ClickHouse) as vectorstore providers. Qdrant being the default. -In order to select one or the other, set the `vectorstore.database` property in the `settings.yaml` file to `qdrant`, `chroma` or `postgres`. +In order to select one or the other, set the `vectorstore.database` property in the `settings.yaml` file to `qdrant`, `milvus`, `chroma`, `postgres` and `clickhouse`. ```yaml vectorstore: @@ -39,6 +39,24 @@ qdrant: path: local_data/private_gpt/qdrant ``` +### Milvus configuration + +To enable Milvus, set the `vectorstore.database` property in the `settings.yaml` file to `milvus` and install the `milvus` extra. + +```bash +poetry install --extras vector-stores-milvus +``` + +The available configuration options are: +| Field | Description | +|--------------|-------------| +| uri | Default is set to "local_data/private_gpt/milvus/milvus_local.db" as a local file; you can also set up a more performant Milvus server on docker or k8s e.g.http://localhost:19530, as your uri; To use Zilliz Cloud, adjust the uri and token to Endpoint and Api key in Zilliz Cloud.| +| token | Pair with Milvus server on docker or k8s or zilliz cloud api key.| +| collection_name | The name of the collection, set to default "milvus_db".| +| overwrite | Overwrite the data in collection if it existed, set to default as True. | + +To obtain a local setup (disk-based database) without running a Milvus server, configure the uri value in settings.yaml, to store in local_data/private_gpt/milvus/milvus_local.db. + ### Chroma configuration To enable Chroma, set the `vectorstore.database` property in the `settings.yaml` file to `chroma` and install the `chroma` extra. @@ -101,3 +119,69 @@ Indexes: postgres=# ``` The dimensions of the embeddings columns will be set based on the `embedding.embed_dim` value. If the embedding model changes this table may need to be dropped and recreated to avoid a dimension mismatch. + +### ClickHouse + +To utilize ClickHouse as the vector store, a [ClickHouse](https://github.com/ClickHouse/ClickHouse) database must be employed. + +To enable ClickHouse, set the `vectorstore.database` property in the `settings.yaml` file to `clickhouse` and install the `vector-stores-clickhouse` extra. + +```bash +poetry install --extras vector-stores-clickhouse +``` + +ClickHouse settings can be configured by setting values to the `clickhouse` property in the `settings.yaml` file. + +The available configuration options are: +| Field | Description | +|----------------------|----------------------------------------------------------------| +| **host** | The server hosting the ClickHouse database. Default is `localhost` | +| **port** | The port on which the ClickHouse database is accessible. Default is `8123` | +| **username** | The username for database access. Default is `default` | +| **password** | The password for database access. (Optional) | +| **database** | The specific database to connect to. Default is `__default__` | +| **secure** | Use https/TLS for secure connection to the server. Default is `false` | +| **interface** | The protocol used for the connection, either 'http' or 'https'. (Optional) | +| **settings** | Specific ClickHouse server settings to be used with the session. (Optional) | +| **connect_timeout** | Timeout in seconds for establishing a connection. (Optional) | +| **send_receive_timeout** | Read timeout in seconds for http connection. (Optional) | +| **verify** | Verify the server certificate in secure/https mode. (Optional) | +| **ca_cert** | Path to Certificate Authority root certificate (.pem format). (Optional) | +| **client_cert** | Path to TLS Client certificate (.pem format). (Optional) | +| **client_cert_key** | Path to the private key for the TLS Client certificate. (Optional) | +| **http_proxy** | HTTP proxy address. (Optional) | +| **https_proxy** | HTTPS proxy address. (Optional) | +| **server_host_name** | Server host name to be checked against the TLS certificate. (Optional) | + +For example: +```yaml +vectorstore: + database: clickhouse + +clickhouse: + host: localhost + port: 8443 + username: admin + password: + database: embeddings + secure: false +``` + +The following table will be created in the database: +``` +clickhouse-client +:) \d embeddings.llama_index + Table "llama_index" + № | name | type | default_type | default_expression | comment | codec_expression | ttl_expression +----|-----------|----------------------------------------------|--------------|--------------------|---------|------------------|--------------- + 1 | id | String | | | | | + 2 | doc_id | String | | | | | + 3 | text | String | | | | | + 4 | vector | Array(Float32) | | | | | + 5 | node_info | Tuple(start Nullable(UInt64), end Nullable(UInt64)) | | | | | + 6 | metadata | String | | | | | + +clickhouse-client +``` + +The dimensions of the embeddings columns will be set based on the `embedding.embed_dim` value. If the embedding model changes, this table may need to be dropped and recreated to avoid a dimension mismatch. diff --git a/fern/docs/pages/overview/welcome.mdx b/fern/docs/pages/overview/welcome.mdx index b825a6548..801e4ccf6 100644 --- a/fern/docs/pages/overview/welcome.mdx +++ b/fern/docs/pages/overview/welcome.mdx @@ -1,8 +1,16 @@ PrivateGPT provides an **API** containing all the building blocks required to build **private, context-aware AI applications**. + + +If you are looking for an **enterprise-ready, fully private AI workspace** +check out [Zylon's website](https://zylon.ai) or [request a demo](https://cal.com/zylon/demo?source=pgpt-docs). +Crafted by the team behind PrivateGPT, Zylon is a best-in-class AI collaborative +workspace that can be easily deployed on-premise (data center, bare metal...) or in your private cloud (AWS, GCP, Azure...). + + The API follows and extends OpenAI API standard, and supports both normal and streaming responses. That means that, if you can use OpenAI API in one of your tools, you can use your own PrivateGPT API instead, -with no code changes, **and for free** if you are running privateGPT in a `local` setup. +with no code changes, **and for free** if you are running PrivateGPT in a `local` setup. Get started by understanding the [Main Concepts and Installation](/installation) and then dive into the [API Reference](/api-reference). @@ -31,10 +39,4 @@ Get started by understanding the [Main Concepts and Installation](/installation) /> -
- - - -A working **Gradio UI client** is provided to test the API, together with a set of useful tools such as bulk -model download script, ingestion script, documents folder watch, etc. - \ No newline at end of file +
\ No newline at end of file diff --git a/fern/docs/pages/quickstart/quickstart.mdx b/fern/docs/pages/quickstart/quickstart.mdx new file mode 100644 index 000000000..09877ce25 --- /dev/null +++ b/fern/docs/pages/quickstart/quickstart.mdx @@ -0,0 +1,105 @@ +This guide provides a quick start for running different profiles of PrivateGPT using Docker Compose. +The profiles cater to various environments, including Ollama setups (CPU, CUDA, MacOS), and a fully local setup. + +By default, Docker Compose will download pre-built images from a remote registry when starting the services. However, you have the option to build the images locally if needed. Details on building Docker image locally are provided at the end of this guide. + +If you want to run PrivateGPT locally without Docker, refer to the [Local Installation Guide](/installation). + +## Prerequisites +- **Docker and Docker Compose:** Ensure both are installed on your system. + [Installation Guide for Docker](https://docs.docker.com/get-docker/), [Installation Guide for Docker Compose](https://docs.docker.com/compose/install/). +- **Clone PrivateGPT Repository:** Clone the PrivateGPT repository to your machine and navigate to the directory: + ```sh + git clone https://github.com/zylon-ai/private-gpt.git + cd private-gpt + ``` + +## Setups + +### Ollama Setups (Recommended) + +#### 1. Default/Ollama CPU + +**Description:** +This profile runs the Ollama service using CPU resources. It is the standard configuration for running Ollama-based Private-GPT services without GPU acceleration. + +**Run:** +To start the services using pre-built images, run: +```sh +docker-compose up +``` +or with a specific profile: +```sh +docker-compose --profile ollama-cpu up +``` + +#### 2. Ollama Nvidia CUDA + +**Description:** +This profile leverages GPU acceleration with CUDA support, suitable for computationally intensive tasks that benefit from GPU resources. + +**Requirements:** +Ensure that your system has compatible GPU hardware and the necessary NVIDIA drivers installed. The installation process is detailed [here](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html). + +**Run:** +To start the services with CUDA support using pre-built images, run: +```sh +docker-compose --profile ollama-cuda up +``` + +#### 3. Ollama External API + +**Description:** +This profile is designed for running PrivateGPT using Ollama installed on the host machine. This setup is particularly useful for MacOS users, as Docker does not yet support Metal GPU. + +**Requirements:** +Install Ollama on your machine by following the instructions at [ollama.ai](https://ollama.ai/). + +**Run:** +To start the Ollama service, use: +```sh +OLLAMA_HOST=0.0.0.0 ollama serve +``` +To start the services with the host configuration using pre-built images, run: +```sh +docker-compose --profile ollama-api up +``` + +### Fully Local Setups + +#### 1. LlamaCPP CPU + +**Description:** +This profile runs the Private-GPT services locally using `llama-cpp` and Hugging Face models. + +**Requirements:** +A **Hugging Face Token (HF_TOKEN)** is required for accessing Hugging Face models. Obtain your token following [this guide](/installation/getting-started/troubleshooting#downloading-gated-and-private-models). + +**Run:** +Start the services with your Hugging Face token using pre-built images: +```sh +HF_TOKEN= docker-compose --profile llamacpp-cpu up +``` +Replace `` with your actual Hugging Face token. + +## Building Locally + +If you prefer to build Docker images locally, which is useful when making changes to the codebase or the Dockerfiles, follow these steps: + +### Building Locally +To build the Docker images locally, navigate to the cloned repository directory and run: +```sh +docker-compose build +``` +This command compiles the necessary Docker images based on the current codebase and Dockerfile configurations. + +### Forcing a Rebuild with --build +If you have made changes and need to ensure these changes are reflected in the Docker images, you can force a rebuild before starting the services: +```sh +docker-compose up --build +``` +or with a specific profile: +```sh +docker-compose --profile up --build +``` +Replace `` with the desired profile. \ No newline at end of file diff --git a/fern/docs/pages/recipes/list-llm.mdx b/fern/docs/pages/recipes/list-llm.mdx deleted file mode 100644 index 1e53804bb..000000000 --- a/fern/docs/pages/recipes/list-llm.mdx +++ /dev/null @@ -1,121 +0,0 @@ -# List of working LLM - -**Do you have any working combination of LLM and embeddings?** -Please open a PR to add it to the list, and come on our Discord to tell us about it! - -## Prompt style - -LLMs might have been trained with different prompt styles. -The prompt style is the way the prompt is written, and how the system message is injected in the prompt. - -For example, `llama2` looks like this: -```text -[INST] <> -{{ system_prompt }} -<> - -{{ user_message }} [/INST] -``` - -While `default` (the `llama_index` default) looks like this: -```text -system: {{ system_prompt }} -user: {{ user_message }} -assistant: {{ assistant_message }} -``` - -The "`tag`" style looks like this: - -```text -<|system|>: {{ system_prompt }} -<|user|>: {{ user_message }} -<|assistant|>: {{ assistant_message }} -``` - -The "`mistral`" style looks like this: - -```text -[INST] You are an AI assistant. [/INST][INST] Hello, how are you doing? [/INST] -``` - -The "`chatml`" style looks like this: -```text -<|im_start|>system -{{ system_prompt }}<|im_end|> -<|im_start|>user" -{{ user_message }}<|im_end|> -<|im_start|>assistant -{{ assistant_message }} -``` - -Some LLMs will not understand these prompt styles, and will not work (returning nothing). -You can try to change the prompt style to `default` (or `tag`) in the settings, and it will -change the way the messages are formatted to be passed to the LLM. - -## Example of configuration - -You might want to change the prompt depending on the language and model you are using. - -### English, with instructions - -`settings-en.yaml`: -```yml -local: - llm_hf_repo_id: TheBloke/Mistral-7B-Instruct-v0.1-GGUF - llm_hf_model_file: mistral-7b-instruct-v0.1.Q4_K_M.gguf - embedding_hf_model_name: BAAI/bge-small-en-v1.5 - prompt_style: "llama2" -``` - -### French, with instructions - -`settings-fr.yaml`: -```yml -local: - llm_hf_repo_id: TheBloke/Vigogne-2-7B-Instruct-GGUF - llm_hf_model_file: vigogne-2-7b-instruct.Q4_K_M.gguf - embedding_hf_model_name: dangvantuan/sentence-camembert-base - prompt_style: "default" - # prompt_style: "tag" # also works - # The default system prompt is injected only when the `prompt_style` != default, and there are no system message in the discussion - # default_system_prompt: Vous êtes un assistant IA qui répond à la question posée à la fin en utilisant le contexte suivant. Si vous ne connaissez pas la réponse, dites simplement que vous ne savez pas, n'essayez pas d'inventer une réponse. Veuillez répondre exclusivement en français. -``` - -You might want to change the prompt as the one above might not directly answer your question. -You can read online about how to write a good prompt, but in a nutshell, make it (extremely) directive. - -You can try and troubleshot your prompt by writing multiline requests in the UI, while -writing your interaction with the model, for example: - -```text -Tu es un programmeur senior qui programme en python et utilise le framework fastapi. Ecrit moi un serveur qui retourne "hello world". -``` - -Another example: -```text -Context: None -Situation: tu es au milieu d'un champ. -Tache: va a la rivière, en bas du champ. -Décrit comment aller a la rivière. -``` - -### Optimised Models -GodziLLa2-70B LLM (English, rank 2 on HuggingFace OpenLLM Leaderboard), bge large Embedding Model (rank 1 on HuggingFace MTEB Leaderboard) -`settings-optimised.yaml`: -```yml -local: - llm_hf_repo_id: TheBloke/GodziLLa2-70B-GGUF - llm_hf_model_file: godzilla2-70b.Q4_K_M.gguf - embedding_hf_model_name: BAAI/bge-large-en - prompt_style: "llama2" -``` -### German speaking model -`settings-de.yaml`: -```yml -local: - llm_hf_repo_id: TheBloke/em_german_leo_mistral-GGUF - llm_hf_model_file: em_german_leo_mistral.Q4_K_M.gguf - embedding_hf_model_name: T-Systems-onsite/german-roberta-sentence-transformer-v2 - #llama, default or tag - prompt_style: "default" -``` diff --git a/fern/docs/pages/recipes/quickstart.mdx b/fern/docs/pages/recipes/quickstart.mdx new file mode 100644 index 000000000..a0f6c877a --- /dev/null +++ b/fern/docs/pages/recipes/quickstart.mdx @@ -0,0 +1,23 @@ +# Recipes + +Recipes are predefined use cases that help users solve very specific tasks using PrivateGPT. +They provide a streamlined approach to achieve common goals with the platform, offering both a starting point and inspiration for further exploration. +The main goal of Recipes is to empower the community to create and share solutions, expanding the capabilities of PrivateGPT. + +## How to Create a New Recipe + +1. **Identify the Task**: Define a specific task or problem that the Recipe will address. +2. **Develop the Solution**: Create a clear and concise guide, including any necessary code snippets or configurations. +3. **Submit a PR**: Fork the PrivateGPT repository, add your Recipe to the appropriate section, and submit a PR for review. + +We encourage you to be creative and think outside the box! Your contributions help shape the future of PrivateGPT. + +## Available Recipes + + + + diff --git a/fern/docs/pages/recipes/summarize.mdx b/fern/docs/pages/recipes/summarize.mdx new file mode 100644 index 000000000..99594bf1b --- /dev/null +++ b/fern/docs/pages/recipes/summarize.mdx @@ -0,0 +1,20 @@ +The Summarize Recipe provides a method to extract concise summaries from ingested documents or texts using PrivateGPT. +This tool is particularly useful for quickly understanding large volumes of information by distilling key points and main ideas. + +## Use Case + +The primary use case for the `Summarize` tool is to automate the summarization of lengthy documents, +making it easier for users to grasp the essential information without reading through entire texts. +This can be applied in various scenarios, such as summarizing research papers, news articles, or business reports. + +## Key Features + +1. **Ingestion-compatible**: The user provides the text to be summarized. The text can be directly inputted or retrieved from ingested documents within the system. +2. **Customization**: The summary generation can be influenced by providing specific `instructions` or a `prompt`. These inputs guide the model on how to frame the summary, allowing for customization according to user needs. +3. **Streaming Support**: The tool supports streaming, allowing for real-time summary generation, which can be particularly useful for handling large texts or providing immediate feedback. + +## Contributing + +If you have ideas for improving the Summarize or want to add new features, feel free to contribute! +You can submit your enhancements via a pull request on our [GitHub repository](https://github.com/zylon-ai/private-gpt). + diff --git a/fern/docs/pages/ui/alternatives.mdx b/fern/docs/pages/ui/alternatives.mdx new file mode 100644 index 000000000..6dd89017e --- /dev/null +++ b/fern/docs/pages/ui/alternatives.mdx @@ -0,0 +1,21 @@ + +This page aims to present different user interface (UI) alternatives for integrating and using PrivateGPT. These alternatives range from demo applications to fully customizable UI setups that can be adapted to your specific needs. + +**Do you have any working demo project using PrivateGPT?** + +Please open a PR to add it to the list, and come on our Discord to tell us about it! + + +WIP: This page provides an overview of one of the UI alternatives available for PrivateGPT. More alternatives will be added to this page as they become available. + + +## [PrivateGPT SDK Demo App](https://github.com/frgarciames/privategpt-react) + +The PrivateGPT SDK demo app is a robust starting point for developers looking to integrate and customize PrivateGPT in their applications. Leveraging modern technologies like Tailwind, shadcn/ui, and Biomejs, it provides a smooth development experience and a highly customizable user interface. Refer to the [repository](https://github.com/frgarciames/privategpt-react) for more details and to get started. + +**Tech Stack:** + +- **Tailwind:** A utility-first CSS framework for rapid UI development. +- **shadcn/ui:** A set of high-quality, customizable UI components. +- **PrivateGPT Web SDK:** The core SDK for interacting with PrivateGPT. +- **Biomejs formatter/linter:** A tool for maintaining code quality and consistency. diff --git a/fern/docs/pages/manual/ui.mdx b/fern/docs/pages/ui/gradio.mdx similarity index 87% rename from fern/docs/pages/manual/ui.mdx rename to fern/docs/pages/ui/gradio.mdx index ed095fe25..8336ed648 100644 --- a/fern/docs/pages/manual/ui.mdx +++ b/fern/docs/pages/ui/gradio.mdx @@ -2,7 +2,12 @@ Gradio UI is a ready to use way of testing most of PrivateGPT API functionalities. -![Gradio PrivateGPT](https://lh3.googleusercontent.com/drive-viewer/AK7aPaD_Hc-A8A9ooMe-hPgm_eImgsbxAjb__8nFYj8b_WwzvL1Gy90oAnp1DfhPaN6yGiEHCOXs0r77W1bYHtPzlVwbV7fMsA=s1600) +![Gradio PrivateGPT](https://github.com/zylon-ai/private-gpt/raw/main/fern/docs/assets/ui.png?raw=true) + + +A working **Gradio UI client** is provided to test the API, together with a set of useful tools such as bulk +model download script, ingestion script, documents folder watch, etc. Please refer to the [UI alternatives](/manual/user-interface/alternatives) page for more UI alternatives. + ### Execution Modes diff --git a/fern/fern.config.json b/fern/fern.config.json index 2ed68270a..fe0eeacbc 100644 --- a/fern/fern.config.json +++ b/fern/fern.config.json @@ -1,4 +1,4 @@ { "organization": "privategpt", - "version": "0.19.10" + "version": "0.31.17" } \ No newline at end of file diff --git a/fern/openapi/openapi.json b/fern/openapi/openapi.json index af1646f1f..c17c4d123 100644 --- a/fern/openapi/openapi.json +++ b/fern/openapi/openapi.json @@ -339,6 +339,48 @@ } } }, + "/v1/summarize": { + "post": { + "tags": [ + "Recipes" + ], + "summary": "Summarize", + "description": "Given a text, the model will return a summary.\n\nOptionally include `instructions` to influence the way the summary is generated.\n\nIf `use_context`\nis set to `true`, the model will also use the content coming from the ingested\ndocuments in the summary. The documents being used can\nbe filtered by their metadata using the `context_filter`.\nIngested documents metadata can be found using `/ingest/list` endpoint.\nIf you want all ingested documents to be used, remove `context_filter` altogether.\n\nIf `prompt` is set, it will be used as the prompt for the summarization,\notherwise the default prompt will be used.\n\nWhen using `'stream': true`, the API will return data chunks following [OpenAI's\nstreaming model](https://platform.openai.com/docs/api-reference/chat/streaming):\n```\n{\"id\":\"12345\",\"object\":\"completion.chunk\",\"created\":1694268190,\n\"model\":\"private-gpt\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"Hello\"},\n\"finish_reason\":null}]}\n```", + "operationId": "summarize_v1_summarize_post", + "requestBody": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SummarizeBody" + } + } + }, + "required": true + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SummarizeResponse" + } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + }, "/v1/embeddings": { "post": { "tags": [ @@ -500,6 +542,10 @@ "Chunk": { "properties": { "object": { + "type": "string", + "enum": [ + "context.chunk" + ], "const": "context.chunk", "title": "Object" }, @@ -612,10 +658,18 @@ "ChunksResponse": { "properties": { "object": { + "type": "string", + "enum": [ + "list" + ], "const": "list", "title": "Object" }, "model": { + "type": "string", + "enum": [ + "private-gpt" + ], "const": "private-gpt", "title": "Model" }, @@ -728,6 +782,10 @@ "title": "Index" }, "object": { + "type": "string", + "enum": [ + "embedding" + ], "const": "embedding", "title": "Object" }, @@ -779,10 +837,18 @@ "EmbeddingsResponse": { "properties": { "object": { + "type": "string", + "enum": [ + "list" + ], "const": "list", "title": "Object" }, "model": { + "type": "string", + "enum": [ + "private-gpt" + ], "const": "private-gpt", "title": "Model" }, @@ -818,6 +884,10 @@ "HealthResponse": { "properties": { "status": { + "type": "string", + "enum": [ + "ok" + ], "const": "ok", "title": "Status", "default": "ok" @@ -829,10 +899,18 @@ "IngestResponse": { "properties": { "object": { + "type": "string", + "enum": [ + "list" + ], "const": "list", "title": "Object" }, "model": { + "type": "string", + "enum": [ + "private-gpt" + ], "const": "private-gpt", "title": "Model" }, @@ -879,6 +957,10 @@ "IngestedDoc": { "properties": { "object": { + "type": "string", + "enum": [ + "ingest.document" + ], "const": "ingest.document", "title": "Object" }, @@ -1001,6 +1083,10 @@ ] }, "model": { + "type": "string", + "enum": [ + "private-gpt" + ], "const": "private-gpt", "title": "Model" }, @@ -1074,6 +1160,78 @@ "title": "OpenAIMessage", "description": "Inference result, with the source of the message.\n\nRole could be the assistant or system\n(providing a default response, not AI generated)." }, + "SummarizeBody": { + "properties": { + "text": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Text" + }, + "use_context": { + "type": "boolean", + "title": "Use Context", + "default": false + }, + "context_filter": { + "anyOf": [ + { + "$ref": "#/components/schemas/ContextFilter" + }, + { + "type": "null" + } + ] + }, + "prompt": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Prompt" + }, + "instructions": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Instructions" + }, + "stream": { + "type": "boolean", + "title": "Stream", + "default": false + } + }, + "type": "object", + "title": "SummarizeBody" + }, + "SummarizeResponse": { + "properties": { + "summary": { + "type": "string", + "title": "Summary" + } + }, + "type": "object", + "required": [ + "summary" + ], + "title": "SummarizeResponse" + }, "ValidationError": { "properties": { "loc": { diff --git a/poetry.lock b/poetry.lock index 279707d85..c595edcb1 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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"llama-index-embeddings-huggingface"] +embeddings-mistral = ["llama-index-embeddings-mistralai"] embeddings-ollama = ["llama-index-embeddings-ollama"] embeddings-openai = ["llama-index-embeddings-openai"] embeddings-sagemaker = ["boto3"] llms-azopenai = ["llama-index-llms-azure-openai"] +llms-gemini = ["llama-index-llms-gemini"] llms-llama-cpp = ["llama-index-llms-llama-cpp"] llms-ollama = ["llama-index-llms-ollama"] llms-openai = ["llama-index-llms-openai"] @@ -6322,12 +7097,14 @@ llms-openai-like = ["llama-index-llms-openai-like"] llms-sagemaker = ["boto3"] rerank-sentence-transformers = ["sentence-transformers", "torch"] storage-nodestore-postgres = ["asyncpg", "llama-index-storage-docstore-postgres", "llama-index-storage-index-store-postgres", "psycopg2-binary"] -ui = ["gradio"] +ui = ["ffmpy", "gradio"] vector-stores-chroma = ["llama-index-vector-stores-chroma"] +vector-stores-clickhouse = ["clickhouse-connect", "llama-index-vector-stores-clickhouse"] +vector-stores-milvus = ["llama-index-vector-stores-milvus"] vector-stores-postgres = ["llama-index-vector-stores-postgres"] vector-stores-qdrant = ["llama-index-vector-stores-qdrant"] [metadata] lock-version = "2.0" python-versions = ">=3.11,<3.12" -content-hash = "0b3665bd11a604609249ff0267e4e5cf009881d16a84f9774fc54d45a1373e09" +content-hash = "16e3be4521aa64c936ee8fb841655f15090b71cf8faaeed7e73a4bcdf3fbdea2" diff --git a/private_gpt/components/embedding/embedding_component.py b/private_gpt/components/embedding/embedding_component.py index 77e8c3d46..b55cef873 100644 --- a/private_gpt/components/embedding/embedding_component.py +++ b/private_gpt/components/embedding/embedding_component.py @@ -31,6 +31,7 @@ def __init__(self, settings: Settings) -> None: self.embedding_model = HuggingFaceEmbedding( model_name=settings.huggingface.embedding_hf_model_name, cache_folder=str(models_cache_path), + trust_remote_code=settings.huggingface.trust_remote_code, ) case "sagemaker": try: @@ -55,23 +56,62 @@ def __init__(self, settings: Settings) -> None: "OpenAI dependencies not found, install with `poetry install --extras embeddings-openai`" ) from e - openai_settings = settings.openai.api_key - self.embedding_model = OpenAIEmbedding(api_key=openai_settings) + api_base = ( + settings.openai.embedding_api_base or settings.openai.api_base + ) + api_key = settings.openai.embedding_api_key or settings.openai.api_key + model = settings.openai.embedding_model + + self.embedding_model = OpenAIEmbedding( + api_base=api_base, + api_key=api_key, + model=model, + ) case "ollama": try: from llama_index.embeddings.ollama import ( # type: ignore OllamaEmbedding, ) + from ollama import Client # type: ignore except ImportError as e: raise ImportError( "Local dependencies not found, install with `poetry install --extras embeddings-ollama`" ) from e ollama_settings = settings.ollama + + # Calculate embedding model. If not provided tag, it will be use latest + model_name = ( + ollama_settings.embedding_model + ":latest" + if ":" not in ollama_settings.embedding_model + else ollama_settings.embedding_model + ) + self.embedding_model = OllamaEmbedding( - model_name=ollama_settings.embedding_model, + model_name=model_name, base_url=ollama_settings.embedding_api_base, ) + + if ollama_settings.autopull_models: + if ollama_settings.autopull_models: + from private_gpt.utils.ollama import ( + check_connection, + pull_model, + ) + + # TODO: Reuse llama-index client when llama-index is updated + client = Client( + host=ollama_settings.embedding_api_base, + timeout=ollama_settings.request_timeout, + ) + + if not check_connection(client): + raise ValueError( + f"Failed to connect to Ollama, " + f"check if Ollama server is running on {ollama_settings.api_base}" + ) + pull_model(client, model_name) + case "azopenai": try: from llama_index.embeddings.azure_openai import ( # type: ignore @@ -90,6 +130,37 @@ def __init__(self, settings: Settings) -> None: azure_endpoint=azopenai_settings.azure_endpoint, api_version=azopenai_settings.api_version, ) + case "gemini": + try: + from llama_index.embeddings.gemini import ( # type: ignore + GeminiEmbedding, + ) + except ImportError as e: + raise ImportError( + "Gemini dependencies not found, install with `poetry install --extras embeddings-gemini`" + ) from e + + self.embedding_model = GeminiEmbedding( + api_key=settings.gemini.api_key, + model_name=settings.gemini.embedding_model, + ) + case "mistralai": + try: + from llama_index.embeddings.mistralai import ( # type: ignore + MistralAIEmbedding, + ) + except ImportError as e: + raise ImportError( + "Mistral dependencies not found, install with `poetry install --extras embeddings-mistral`" + ) from e + + api_key = settings.openai.api_key + model = settings.openai.embedding_model + + self.embedding_model = MistralAIEmbedding( + api_key=api_key, + model=model, + ) case "mock": # Not a random number, is the dimensionality used by # the default embedding model diff --git a/private_gpt/components/ingest/ingest_component.py b/private_gpt/components/ingest/ingest_component.py index 5ed039590..77db9702e 100644 --- a/private_gpt/components/ingest/ingest_component.py +++ b/private_gpt/components/ingest/ingest_component.py @@ -403,7 +403,7 @@ def _doc_to_node_worker(self, file_name: str, documents: list[Document]) -> None self.transformations, show_progress=self.show_progress, ) - self.node_q.put(("process", file_name, documents, nodes)) + self.node_q.put(("process", file_name, documents, list(nodes))) finally: self.doc_semaphore.release() self.doc_q.task_done() # unblock Q joins diff --git a/private_gpt/components/ingest/ingest_helper.py b/private_gpt/components/ingest/ingest_helper.py index a11090702..da62568bc 100644 --- a/private_gpt/components/ingest/ingest_helper.py +++ b/private_gpt/components/ingest/ingest_helper.py @@ -92,7 +92,13 @@ def _load_file_to_documents(file_name: str, file_data: Path) -> list[Document]: return string_reader.load_data([file_data.read_text()]) logger.debug("Specific reader found for extension=%s", extension) - return reader_cls().load_data(file_data) + documents = reader_cls().load_data(file_data) + + # Sanitize NUL bytes in text which can't be stored in Postgres + for i in range(len(documents)): + documents[i].text = documents[i].text.replace("\u0000", "") + + return documents @staticmethod def _exclude_metadata(documents: list[Document]) -> None: diff --git a/private_gpt/components/llm/custom/sagemaker.py b/private_gpt/components/llm/custom/sagemaker.py index e20f53948..bd2aec18a 100644 --- a/private_gpt/components/llm/custom/sagemaker.py +++ b/private_gpt/components/llm/custom/sagemaker.py @@ -218,7 +218,7 @@ def complete(self, prompt: str, **kwargs: Any) -> CompletionResponse: response_body = resp["Body"] response_str = response_body.read().decode("utf-8") - response_dict = eval(response_str) + response_dict = json.loads(response_str) return CompletionResponse( text=response_dict[0]["generated_text"][len(prompt) :], raw=resp diff --git a/private_gpt/components/llm/llm_component.py b/private_gpt/components/llm/llm_component.py index dae997cc2..eb752e547 100644 --- a/private_gpt/components/llm/llm_component.py +++ b/private_gpt/components/llm/llm_component.py @@ -22,13 +22,24 @@ class LLMComponent: @inject def __init__(self, settings: Settings) -> None: llm_mode = settings.llm.mode - if settings.llm.tokenizer: - set_global_tokenizer( - AutoTokenizer.from_pretrained( - pretrained_model_name_or_path=settings.llm.tokenizer, - cache_dir=str(models_cache_path), + if settings.llm.tokenizer and settings.llm.mode != "mock": + # Try to download the tokenizer. If it fails, the LLM will still work + # using the default one, which is less accurate. + try: + set_global_tokenizer( + AutoTokenizer.from_pretrained( + pretrained_model_name_or_path=settings.llm.tokenizer, + cache_dir=str(models_cache_path), + token=settings.huggingface.access_token, + ) + ) + except Exception as e: + logger.warning( + f"Failed to download tokenizer {settings.llm.tokenizer}: {e!s}" + f"Please follow the instructions in the documentation to download it if needed: " + f"https://docs.privategpt.dev/installation/getting-started/troubleshooting#tokenizer-setup." + f"Falling back to default tokenizer." ) - ) logger.info("Initializing the LLM in mode=%s", llm_mode) match settings.llm.mode: @@ -40,7 +51,7 @@ def __init__(self, settings: Settings) -> None: "Local dependencies not found, install with `poetry install --extras llms-llama-cpp`" ) from e - prompt_style = get_prompt_style(settings.llamacpp.prompt_style) + prompt_style = get_prompt_style(settings.llm.prompt_style) settings_kwargs = { "tfs_z": settings.llamacpp.tfs_z, # ollama and llama-cpp "top_k": settings.llamacpp.top_k, # ollama and llama-cpp @@ -98,15 +109,22 @@ def __init__(self, settings: Settings) -> None: raise ImportError( "OpenAILike dependencies not found, install with `poetry install --extras llms-openai-like`" ) from e - + prompt_style = get_prompt_style(settings.llm.prompt_style) openai_settings = settings.openai self.llm = OpenAILike( api_base=openai_settings.api_base, api_key=openai_settings.api_key, model=openai_settings.model, is_chat_model=True, - max_tokens=None, + max_tokens=settings.llm.max_new_tokens, api_version="", + temperature=settings.llm.temperature, + context_window=settings.llm.context_window, + messages_to_prompt=prompt_style.messages_to_prompt, + completion_to_prompt=prompt_style.completion_to_prompt, + tokenizer=settings.llm.tokenizer, + timeout=openai_settings.request_timeout, + reuse_client=False, ) case "ollama": try: @@ -127,8 +145,15 @@ def __init__(self, settings: Settings) -> None: "repeat_penalty": ollama_settings.repeat_penalty, # ollama llama-cpp } - self.llm = Ollama( - model=ollama_settings.llm_model, + # calculate llm model. If not provided tag, it will be use latest + model_name = ( + ollama_settings.llm_model + ":latest" + if ":" not in ollama_settings.llm_model + else ollama_settings.llm_model + ) + + llm = Ollama( + model=model_name, base_url=ollama_settings.api_base, temperature=settings.llm.temperature, context_window=settings.llm.context_window, @@ -136,6 +161,16 @@ def __init__(self, settings: Settings) -> None: request_timeout=ollama_settings.request_timeout, ) + if ollama_settings.autopull_models: + from private_gpt.utils.ollama import check_connection, pull_model + + if not check_connection(llm.client): + raise ValueError( + f"Failed to connect to Ollama, " + f"check if Ollama server is running on {ollama_settings.api_base}" + ) + pull_model(llm.client, model_name) + if ( ollama_settings.keep_alive != ollama_settings.model_fields["keep_alive"].default @@ -148,10 +183,12 @@ def wrapper(*args: Any, **kwargs: Any) -> Any: return wrapper - Ollama.chat = add_keep_alive(Ollama.chat) - Ollama.stream_chat = add_keep_alive(Ollama.stream_chat) - Ollama.complete = add_keep_alive(Ollama.complete) - Ollama.stream_complete = add_keep_alive(Ollama.stream_complete) + Ollama.chat = add_keep_alive(Ollama.chat) # type: ignore + Ollama.stream_chat = add_keep_alive(Ollama.stream_chat) # type: ignore + Ollama.complete = add_keep_alive(Ollama.complete) # type: ignore + Ollama.stream_complete = add_keep_alive(Ollama.stream_complete) # type: ignore + + self.llm = llm case "azopenai": try: @@ -171,5 +208,18 @@ def wrapper(*args: Any, **kwargs: Any) -> Any: azure_endpoint=azopenai_settings.azure_endpoint, api_version=azopenai_settings.api_version, ) + case "gemini": + try: + from llama_index.llms.gemini import ( # type: ignore + Gemini, + ) + except ImportError as e: + raise ImportError( + "Google Gemini dependencies not found, install with `poetry install --extras llms-gemini`" + ) from e + gemini_settings = settings.gemini + self.llm = Gemini( + model_name=gemini_settings.model, api_key=gemini_settings.api_key + ) case "mock": self.llm = MockLLM() diff --git a/private_gpt/components/llm/prompt_helper.py b/private_gpt/components/llm/prompt_helper.py index 985d217bd..587541195 100644 --- a/private_gpt/components/llm/prompt_helper.py +++ b/private_gpt/components/llm/prompt_helper.py @@ -40,7 +40,8 @@ def messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: logger.debug("Got for messages='%s' the prompt='%s'", messages, prompt) return prompt - def completion_to_prompt(self, completion: str) -> str: + def completion_to_prompt(self, prompt: str) -> str: + completion = prompt # Fix: Llama-index parameter has to be named as prompt prompt = self._completion_to_prompt(completion) logger.debug("Got for completion='%s' the prompt='%s'", completion, prompt) return prompt @@ -138,6 +139,72 @@ def _completion_to_prompt(self, completion: str) -> str: ) +class Llama3PromptStyle(AbstractPromptStyle): + r"""Template for Meta's Llama 3.1. + + The format follows this structure: + <|begin_of_text|> + <|start_header_id|>system<|end_header_id|> + + [System message content]<|eot_id|> + <|start_header_id|>user<|end_header_id|> + + [User message content]<|eot_id|> + <|start_header_id|>assistant<|end_header_id|> + + [Assistant message content]<|eot_id|> + ... + (Repeat for each message, including possible 'ipython' role) + """ + + BOS, EOS = "<|begin_of_text|>", "<|end_of_text|>" + B_INST, E_INST = "<|start_header_id|>", "<|end_header_id|>" + EOT = "<|eot_id|>" + B_SYS, E_SYS = "<|start_header_id|>system<|end_header_id|>", "<|eot_id|>" + ASSISTANT_INST = "<|start_header_id|>assistant<|end_header_id|>" + DEFAULT_SYSTEM_PROMPT = """\ + You are a helpful, respectful and honest assistant. \ + Always answer as helpfully as possible and follow ALL given instructions. \ + Do not speculate or make up information. \ + Do not reference any given instructions or context. \ + """ + + def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: + prompt = "" + has_system_message = False + + for i, message in enumerate(messages): + if not message or message.content is None: + continue + if message.role == MessageRole.SYSTEM: + prompt += f"{self.B_SYS}\n\n{message.content.strip()}{self.E_SYS}" + has_system_message = True + else: + role_header = f"{self.B_INST}{message.role.value}{self.E_INST}" + prompt += f"{role_header}\n\n{message.content.strip()}{self.EOT}" + + # Add assistant header if the last message is not from the assistant + if i == len(messages) - 1 and message.role != MessageRole.ASSISTANT: + prompt += f"{self.ASSISTANT_INST}\n\n" + + # Add default system prompt if no system message was provided + if not has_system_message: + prompt = ( + f"{self.B_SYS}\n\n{self.DEFAULT_SYSTEM_PROMPT}{self.E_SYS}" + prompt + ) + + # TODO: Implement tool handling logic + + return prompt + + def _completion_to_prompt(self, completion: str) -> str: + return ( + f"{self.B_SYS}\n\n{self.DEFAULT_SYSTEM_PROMPT}{self.E_SYS}" + f"{self.B_INST}user{self.E_INST}\n\n{completion.strip()}{self.EOT}" + f"{self.ASSISTANT_INST}\n\n" + ) + + class TagPromptStyle(AbstractPromptStyle): """Tag prompt style (used by Vigogne) that uses the prompt style `<|ROLE|>`. @@ -173,18 +240,22 @@ def _completion_to_prompt(self, completion: str) -> str: class MistralPromptStyle(AbstractPromptStyle): def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str: - prompt = "" + inst_buffer = [] + text = "" for message in messages: - role = message.role - content = message.content or "" - if role.lower() == "system": - message_from_user = f"[INST] {content.strip()} [/INST]" - prompt += message_from_user - elif role.lower() == "user": - prompt += "" - message_from_user = f"[INST] {content.strip()} [/INST]" - prompt += message_from_user - return prompt + if message.role == MessageRole.SYSTEM or message.role == MessageRole.USER: + inst_buffer.append(str(message.content).strip()) + elif message.role == MessageRole.ASSISTANT: + text += "[INST] " + "\n".join(inst_buffer) + " [/INST]" + text += " " + str(message.content).strip() + "" + inst_buffer.clear() + else: + raise ValueError(f"Unknown message role {message.role}") + + if len(inst_buffer) > 0: + text += "[INST] " + "\n".join(inst_buffer) + " [/INST]" + + return text def _completion_to_prompt(self, completion: str) -> str: return self._messages_to_prompt( @@ -215,7 +286,9 @@ def _completion_to_prompt(self, completion: str) -> str: def get_prompt_style( - prompt_style: Literal["default", "llama2", "tag", "mistral", "chatml"] | None + prompt_style: ( + Literal["default", "llama2", "llama3", "tag", "mistral", "chatml"] | None + ) ) -> AbstractPromptStyle: """Get the prompt style to use from the given string. @@ -226,6 +299,8 @@ def get_prompt_style( return DefaultPromptStyle() elif prompt_style == "llama2": return Llama2PromptStyle() + elif prompt_style == "llama3": + return Llama3PromptStyle() elif prompt_style == "tag": return TagPromptStyle() elif prompt_style == "mistral": diff --git a/private_gpt/components/node_store/node_store_component.py b/private_gpt/components/node_store/node_store_component.py index f81ce7019..5cd0afbd0 100644 --- a/private_gpt/components/node_store/node_store_component.py +++ b/private_gpt/components/node_store/node_store_component.py @@ -38,10 +38,10 @@ def __init__(self, settings: Settings) -> None: case "postgres": try: - from llama_index.core.storage.docstore.postgres_docstore import ( + from llama_index.storage.docstore.postgres import ( # type: ignore PostgresDocumentStore, ) - from llama_index.core.storage.index_store.postgres_index_store import ( + from llama_index.storage.index_store.postgres import ( # type: ignore PostgresIndexStore, ) except ImportError: @@ -55,6 +55,7 @@ def __init__(self, settings: Settings) -> None: self.index_store = PostgresIndexStore.from_params( **settings.postgres.model_dump(exclude_none=True) ) + self.doc_store = PostgresDocumentStore.from_params( **settings.postgres.model_dump(exclude_none=True) ) diff --git a/private_gpt/components/vector_store/batched_chroma.py b/private_gpt/components/vector_store/batched_chroma.py index 4f9ea25bc..54dd04903 100644 --- a/private_gpt/components/vector_store/batched_chroma.py +++ b/private_gpt/components/vector_store/batched_chroma.py @@ -1,14 +1,17 @@ -from collections.abc import Generator -from typing import Any +from collections.abc import Generator, Sequence +from typing import TYPE_CHECKING, Any from llama_index.core.schema import BaseNode, MetadataMode from llama_index.core.vector_stores.utils import node_to_metadata_dict from llama_index.vector_stores.chroma import ChromaVectorStore # type: ignore +if TYPE_CHECKING: + from collections.abc import Mapping + def chunk_list( - lst: list[BaseNode], max_chunk_size: int -) -> Generator[list[BaseNode], None, None]: + lst: Sequence[BaseNode], max_chunk_size: int +) -> Generator[Sequence[BaseNode], None, None]: """Yield successive max_chunk_size-sized chunks from lst. Args: @@ -60,7 +63,7 @@ def __init__( ) self.chroma_client = chroma_client - def add(self, nodes: list[BaseNode], **add_kwargs: Any) -> list[str]: + def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> list[str]: """Add nodes to index, batching the insertion to avoid issues. Args: @@ -78,8 +81,8 @@ def add(self, nodes: list[BaseNode], **add_kwargs: Any) -> list[str]: all_ids = [] for node_chunk in node_chunks: - embeddings = [] - metadatas = [] + embeddings: list[Sequence[float]] = [] + metadatas: list[Mapping[str, Any]] = [] ids = [] documents = [] for node in node_chunk: diff --git a/private_gpt/components/vector_store/vector_store_component.py b/private_gpt/components/vector_store/vector_store_component.py index f9932b574..841a1182f 100644 --- a/private_gpt/components/vector_store/vector_store_component.py +++ b/private_gpt/components/vector_store/vector_store_component.py @@ -4,10 +4,10 @@ from injector import inject, singleton from llama_index.core.indices.vector_store import VectorIndexRetriever, VectorStoreIndex from llama_index.core.vector_stores.types import ( + BasePydanticVectorStore, FilterCondition, MetadataFilter, MetadataFilters, - VectorStore, ) from private_gpt.open_ai.extensions.context_filter import ContextFilter @@ -32,7 +32,7 @@ def _doc_id_metadata_filter( @singleton class VectorStoreComponent: settings: Settings - vector_store: VectorStore + vector_store: BasePydanticVectorStore @inject def __init__(self, settings: Settings) -> None: @@ -54,7 +54,7 @@ def __init__(self, settings: Settings) -> None: ) self.vector_store = typing.cast( - VectorStore, + BasePydanticVectorStore, PGVectorStore.from_params( **settings.postgres.model_dump(exclude_none=True), table_name="embeddings", @@ -87,7 +87,7 @@ def __init__(self, settings: Settings) -> None: ) # TODO self.vector_store = typing.cast( - VectorStore, + BasePydanticVectorStore, BatchedChromaVectorStore( chroma_client=chroma_client, chroma_collection=chroma_collection ), @@ -115,12 +115,78 @@ def __init__(self, settings: Settings) -> None: **settings.qdrant.model_dump(exclude_none=True) ) self.vector_store = typing.cast( - VectorStore, + BasePydanticVectorStore, QdrantVectorStore( client=client, collection_name="make_this_parameterizable_per_api_call", ), # TODO ) + + case "milvus": + try: + from llama_index.vector_stores.milvus import ( # type: ignore + MilvusVectorStore, + ) + except ImportError as e: + raise ImportError( + "Milvus dependencies not found, install with `poetry install --extras vector-stores-milvus`" + ) from e + + if settings.milvus is None: + logger.info( + "Milvus config not found. Using default settings.\n" + "Trying to connect to Milvus at local_data/private_gpt/milvus/milvus_local.db " + "with collection 'make_this_parameterizable_per_api_call'." + ) + + self.vector_store = typing.cast( + BasePydanticVectorStore, + MilvusVectorStore( + dim=settings.embedding.embed_dim, + collection_name="make_this_parameterizable_per_api_call", + overwrite=True, + ), + ) + + else: + self.vector_store = typing.cast( + BasePydanticVectorStore, + MilvusVectorStore( + dim=settings.embedding.embed_dim, + uri=settings.milvus.uri, + token=settings.milvus.token, + collection_name=settings.milvus.collection_name, + overwrite=settings.milvus.overwrite, + ), + ) + + case "clickhouse": + try: + from clickhouse_connect import ( # type: ignore + get_client, + ) + from llama_index.vector_stores.clickhouse import ( # type: ignore + ClickHouseVectorStore, + ) + except ImportError as e: + raise ImportError( + "ClickHouse dependencies not found, install with `poetry install --extras vector-stores-clickhouse`" + ) from e + + if settings.clickhouse is None: + raise ValueError( + "ClickHouse settings not found. Please provide settings." + ) + + clickhouse_client = get_client( + host=settings.clickhouse.host, + port=settings.clickhouse.port, + username=settings.clickhouse.username, + password=settings.clickhouse.password, + ) + self.vector_store = ClickHouseVectorStore( + clickhouse_client=clickhouse_client + ) case _: # Should be unreachable # The settings validator should have caught this diff --git a/private_gpt/launcher.py b/private_gpt/launcher.py index 43bd803a5..968baae46 100644 --- a/private_gpt/launcher.py +++ b/private_gpt/launcher.py @@ -15,6 +15,7 @@ from private_gpt.server.embeddings.embeddings_router import embeddings_router from private_gpt.server.health.health_router import health_router from private_gpt.server.ingest.ingest_router import ingest_router +from private_gpt.server.recipes.summarize.summarize_router import summarize_router from private_gpt.settings.settings import Settings logger = logging.getLogger(__name__) @@ -32,12 +33,14 @@ async def bind_injector_to_request(request: Request) -> None: app.include_router(chat_router) app.include_router(chunks_router) app.include_router(ingest_router) + app.include_router(summarize_router) app.include_router(embeddings_router) app.include_router(health_router) # Add LlamaIndex simple observability global_handler = create_global_handler("simple") - LlamaIndexSettings.callback_manager = CallbackManager([global_handler]) + if global_handler: + LlamaIndexSettings.callback_manager = CallbackManager([global_handler]) settings = root_injector.get(Settings) if settings.server.cors.enabled: diff --git a/private_gpt/server/chat/chat_service.py b/private_gpt/server/chat/chat_service.py index ae8cf0089..efa4a1940 100644 --- a/private_gpt/server/chat/chat_service.py +++ b/private_gpt/server/chat/chat_service.py @@ -1,4 +1,5 @@ from dataclasses import dataclass +from typing import TYPE_CHECKING from injector import inject, singleton from llama_index.core.chat_engine import ContextChatEngine, SimpleChatEngine @@ -26,6 +27,9 @@ from private_gpt.server.chunks.chunks_service import Chunk from private_gpt.settings.settings import Settings +if TYPE_CHECKING: + from llama_index.core.postprocessor.types import BaseNodePostprocessor + class Completion(BaseModel): response: str @@ -114,12 +118,15 @@ def _chat_engine( context_filter=context_filter, similarity_top_k=self.settings.rag.similarity_top_k, ) - node_postprocessors = [ + node_postprocessors: list[BaseNodePostprocessor] = [ MetadataReplacementPostProcessor(target_metadata_key="window"), - SimilarityPostprocessor( - similarity_cutoff=settings.rag.similarity_value - ), ] + if settings.rag.similarity_value: + node_postprocessors.append( + SimilarityPostprocessor( + similarity_cutoff=settings.rag.similarity_value + ) + ) if settings.rag.rerank.enabled: rerank_postprocessor = SentenceTransformerRerank( diff --git a/private_gpt/server/recipes/summarize/__init__.py b/private_gpt/server/recipes/summarize/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/private_gpt/server/recipes/summarize/summarize_router.py b/private_gpt/server/recipes/summarize/summarize_router.py new file mode 100644 index 000000000..c1770c3c0 --- /dev/null +++ b/private_gpt/server/recipes/summarize/summarize_router.py @@ -0,0 +1,86 @@ +from fastapi import APIRouter, Depends, Request +from pydantic import BaseModel +from starlette.responses import StreamingResponse + +from private_gpt.open_ai.extensions.context_filter import ContextFilter +from private_gpt.open_ai.openai_models import ( + to_openai_sse_stream, +) +from private_gpt.server.recipes.summarize.summarize_service import SummarizeService +from private_gpt.server.utils.auth import authenticated + +summarize_router = APIRouter(prefix="/v1", dependencies=[Depends(authenticated)]) + + +class SummarizeBody(BaseModel): + text: str | None = None + use_context: bool = False + context_filter: ContextFilter | None = None + prompt: str | None = None + instructions: str | None = None + stream: bool = False + + +class SummarizeResponse(BaseModel): + summary: str + + +@summarize_router.post( + "/summarize", + response_model=None, + summary="Summarize", + responses={200: {"model": SummarizeResponse}}, + tags=["Recipes"], +) +def summarize( + request: Request, body: SummarizeBody +) -> SummarizeResponse | StreamingResponse: + """Given a text, the model will return a summary. + + Optionally include `instructions` to influence the way the summary is generated. + + If `use_context` + is set to `true`, the model will also use the content coming from the ingested + documents in the summary. The documents being used can + be filtered by their metadata using the `context_filter`. + Ingested documents metadata can be found using `/ingest/list` endpoint. + If you want all ingested documents to be used, remove `context_filter` altogether. + + If `prompt` is set, it will be used as the prompt for the summarization, + otherwise the default prompt will be used. + + When using `'stream': true`, the API will return data chunks following [OpenAI's + streaming model](https://platform.openai.com/docs/api-reference/chat/streaming): + ``` + {"id":"12345","object":"completion.chunk","created":1694268190, + "model":"private-gpt","choices":[{"index":0,"delta":{"content":"Hello"}, + "finish_reason":null}]} + ``` + """ + service: SummarizeService = request.state.injector.get(SummarizeService) + + if body.stream: + completion_gen = service.stream_summarize( + text=body.text, + instructions=body.instructions, + use_context=body.use_context, + context_filter=body.context_filter, + prompt=body.prompt, + ) + return StreamingResponse( + to_openai_sse_stream( + response_generator=completion_gen, + ), + media_type="text/event-stream", + ) + else: + completion = service.summarize( + text=body.text, + instructions=body.instructions, + use_context=body.use_context, + context_filter=body.context_filter, + prompt=body.prompt, + ) + return SummarizeResponse( + summary=completion, + ) diff --git a/private_gpt/server/recipes/summarize/summarize_service.py b/private_gpt/server/recipes/summarize/summarize_service.py new file mode 100644 index 000000000..d19657cf7 --- /dev/null +++ b/private_gpt/server/recipes/summarize/summarize_service.py @@ -0,0 +1,172 @@ +from itertools import chain + +from injector import inject, singleton +from llama_index.core import ( + Document, + StorageContext, + SummaryIndex, +) +from llama_index.core.base.response.schema import Response, StreamingResponse +from llama_index.core.node_parser import SentenceSplitter +from llama_index.core.response_synthesizers import ResponseMode +from llama_index.core.storage.docstore.types import RefDocInfo +from llama_index.core.types import TokenGen + +from private_gpt.components.embedding.embedding_component import EmbeddingComponent +from private_gpt.components.llm.llm_component import LLMComponent +from private_gpt.components.node_store.node_store_component import NodeStoreComponent +from private_gpt.components.vector_store.vector_store_component import ( + VectorStoreComponent, +) +from private_gpt.open_ai.extensions.context_filter import ContextFilter +from private_gpt.settings.settings import Settings + +DEFAULT_SUMMARIZE_PROMPT = ( + "Provide a comprehensive summary of the provided context information. " + "The summary should cover all the key points and main ideas presented in " + "the original text, while also condensing the information into a concise " + "and easy-to-understand format. Please ensure that the summary includes " + "relevant details and examples that support the main ideas, while avoiding " + "any unnecessary information or repetition." +) + + +@singleton +class SummarizeService: + @inject + def __init__( + self, + settings: Settings, + llm_component: LLMComponent, + node_store_component: NodeStoreComponent, + vector_store_component: VectorStoreComponent, + embedding_component: EmbeddingComponent, + ) -> None: + self.settings = settings + self.llm_component = llm_component + self.node_store_component = node_store_component + self.vector_store_component = vector_store_component + self.embedding_component = embedding_component + self.storage_context = StorageContext.from_defaults( + vector_store=vector_store_component.vector_store, + docstore=node_store_component.doc_store, + index_store=node_store_component.index_store, + ) + + @staticmethod + def _filter_ref_docs( + ref_docs: dict[str, RefDocInfo], context_filter: ContextFilter | None + ) -> list[RefDocInfo]: + if context_filter is None or not context_filter.docs_ids: + return list(ref_docs.values()) + + return [ + ref_doc + for doc_id, ref_doc in ref_docs.items() + if doc_id in context_filter.docs_ids + ] + + def _summarize( + self, + use_context: bool = False, + stream: bool = False, + text: str | None = None, + instructions: str | None = None, + context_filter: ContextFilter | None = None, + prompt: str | None = None, + ) -> str | TokenGen: + + nodes_to_summarize = [] + + # Add text to summarize + if text: + text_documents = [Document(text=text)] + nodes_to_summarize += ( + SentenceSplitter.from_defaults().get_nodes_from_documents( + text_documents + ) + ) + + # Add context documents to summarize + if use_context: + # 1. Recover all ref docs + ref_docs: dict[str, RefDocInfo] | None = ( + self.storage_context.docstore.get_all_ref_doc_info() + ) + if ref_docs is None: + raise ValueError("No documents have been ingested yet.") + + # 2. Filter documents based on context_filter (if provided) + filtered_ref_docs = self._filter_ref_docs(ref_docs, context_filter) + + # 3. Get all nodes from the filtered documents + filtered_node_ids = chain.from_iterable( + [ref_doc.node_ids for ref_doc in filtered_ref_docs] + ) + filtered_nodes = self.storage_context.docstore.get_nodes( + node_ids=list(filtered_node_ids), + ) + + nodes_to_summarize += filtered_nodes + + # Create a SummaryIndex to summarize the nodes + summary_index = SummaryIndex( + nodes=nodes_to_summarize, + storage_context=StorageContext.from_defaults(), # In memory SummaryIndex + show_progress=True, + ) + + # Make a tree summarization query + # above the set of all candidate nodes + query_engine = summary_index.as_query_engine( + llm=self.llm_component.llm, + response_mode=ResponseMode.TREE_SUMMARIZE, + streaming=stream, + use_async=self.settings.summarize.use_async, + ) + + prompt = prompt or DEFAULT_SUMMARIZE_PROMPT + + summarize_query = prompt + "\n" + (instructions or "") + + response = query_engine.query(summarize_query) + if isinstance(response, Response): + return response.response or "" + elif isinstance(response, StreamingResponse): + return response.response_gen + else: + raise TypeError(f"The result is not of a supported type: {type(response)}") + + def summarize( + self, + use_context: bool = False, + text: str | None = None, + instructions: str | None = None, + context_filter: ContextFilter | None = None, + prompt: str | None = None, + ) -> str: + return self._summarize( + use_context=use_context, + stream=False, + text=text, + instructions=instructions, + context_filter=context_filter, + prompt=prompt, + ) # type: ignore + + def stream_summarize( + self, + use_context: bool = False, + text: str | None = None, + instructions: str | None = None, + context_filter: ContextFilter | None = None, + prompt: str | None = None, + ) -> TokenGen: + return self._summarize( + use_context=use_context, + stream=True, + text=text, + instructions=instructions, + context_filter=context_filter, + prompt=prompt, + ) # type: ignore diff --git a/private_gpt/settings/settings.py b/private_gpt/settings/settings.py index 5df681141..0589f13a3 100644 --- a/private_gpt/settings/settings.py +++ b/private_gpt/settings/settings.py @@ -1,4 +1,4 @@ -from typing import Literal +from typing import Any, Literal from pydantic import BaseModel, Field @@ -59,6 +59,27 @@ class AuthSettings(BaseModel): ) +class IngestionSettings(BaseModel): + """Ingestion configuration. + + This configuration is used to control the ingestion of data into the system + using non-server methods. This is useful for local development and testing; + or to ingest in bulk from a folder. + + Please note that this configuration is not secure and should be used in + a controlled environment only (setting right permissions, etc.). + """ + + enabled: bool = Field( + description="Flag indicating if local ingestion is enabled or not.", + default=False, + ) + allow_ingest_from: list[str] = Field( + description="A list of folders that should be permitted to make ingest requests.", + default=[], + ) + + class ServerSettings(BaseModel): env_name: str = Field( description="Name of the environment (prod, staging, local...)" @@ -74,6 +95,10 @@ class ServerSettings(BaseModel): class DataSettings(BaseModel): + local_ingestion: IngestionSettings = Field( + description="Ingestion configuration", + default_factory=lambda: IngestionSettings(allow_ingest_from=["*"]), + ) local_data_folder: str = Field( description="Path to local storage." "It will be treated as an absolute path if it starts with /" @@ -82,7 +107,14 @@ class DataSettings(BaseModel): class LLMSettings(BaseModel): mode: Literal[ - "llamacpp", "openai", "openailike", "azopenai", "sagemaker", "mock", "ollama" + "llamacpp", + "openai", + "openailike", + "azopenai", + "sagemaker", + "mock", + "ollama", + "gemini", ] max_new_tokens: int = Field( 256, @@ -104,10 +136,24 @@ class LLMSettings(BaseModel): 0.1, description="The temperature of the model. Increasing the temperature will make the model answer more creatively. A value of 0.1 would be more factual.", ) + prompt_style: Literal["default", "llama2", "llama3", "tag", "mistral", "chatml"] = ( + Field( + "llama2", + description=( + "The prompt style to use for the chat engine. " + "If `default` - use the default prompt style from the llama_index. It should look like `role: message`.\n" + "If `llama2` - use the llama2 prompt style from the llama_index. Based on ``, `[INST]` and `<>`.\n" + "If `llama3` - use the llama3 prompt style from the llama_index." + "If `tag` - use the `tag` prompt style. It should look like `<|role|>: message`. \n" + "If `mistral` - use the `mistral prompt style. It shoudl look like [INST] {System Prompt} [/INST][INST] { UserInstructions } [/INST]" + "`llama2` is the historic behaviour. `default` might work better with your custom models." + ), + ) + ) class VectorstoreSettings(BaseModel): - database: Literal["chroma", "qdrant", "postgres"] + database: Literal["chroma", "qdrant", "postgres", "clickhouse", "milvus"] class NodeStoreSettings(BaseModel): @@ -117,18 +163,6 @@ class NodeStoreSettings(BaseModel): class LlamaCPPSettings(BaseModel): llm_hf_repo_id: str llm_hf_model_file: str - prompt_style: Literal["default", "llama2", "tag", "mistral", "chatml"] = Field( - "llama2", - description=( - "The prompt style to use for the chat engine. " - "If `default` - use the default prompt style from the llama_index. It should look like `role: message`.\n" - "If `llama2` - use the llama2 prompt style from the llama_index. Based on ``, `[INST]` and `<>`.\n" - "If `tag` - use the `tag` prompt style. It should look like `<|role|>: message`. \n" - "If `mistral` - use the `mistral prompt style. It shoudl look like [INST] {System Prompt} [/INST][INST] { UserInstructions } [/INST]" - "`llama2` is the historic behaviour. `default` might work better with your custom models." - ), - ) - tfs_z: float = Field( 1.0, description="Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting.", @@ -151,10 +185,27 @@ class HuggingFaceSettings(BaseModel): embedding_hf_model_name: str = Field( description="Name of the HuggingFace model to use for embeddings" ) + access_token: str = Field( + None, + description="Huggingface access token, required to download some models", + ) + trust_remote_code: bool = Field( + False, + description="If set to True, the code from the remote model will be trusted and executed.", + ) class EmbeddingSettings(BaseModel): - mode: Literal["huggingface", "openai", "azopenai", "sagemaker", "ollama", "mock"] + mode: Literal[ + "huggingface", + "openai", + "azopenai", + "sagemaker", + "ollama", + "mock", + "gemini", + "mistralai", + ] ingest_mode: Literal["simple", "batch", "parallel", "pipeline"] = Field( "simple", description=( @@ -202,6 +253,31 @@ class OpenAISettings(BaseModel): "gpt-3.5-turbo", description="OpenAI Model to use. Example: 'gpt-4'.", ) + request_timeout: float = Field( + 120.0, + description="Time elapsed until openailike server times out the request. Default is 120s. Format is float. ", + ) + embedding_api_base: str = Field( + None, + description="Base URL of OpenAI API. Example: 'https://api.openai.com/v1'.", + ) + embedding_api_key: str + embedding_model: str = Field( + "text-embedding-ada-002", + description="OpenAI embedding Model to use. Example: 'text-embedding-3-large'.", + ) + + +class GeminiSettings(BaseModel): + api_key: str + model: str = Field( + "models/gemini-pro", + description="Google Model to use. Example: 'models/gemini-pro'.", + ) + embedding_model: str = Field( + "models/embedding-001", + description="Google Embedding Model to use. Example: 'models/embedding-001'.", + ) class OllamaSettings(BaseModel): @@ -253,6 +329,10 @@ class OllamaSettings(BaseModel): 120.0, description="Time elapsed until ollama times out the request. Default is 120s. Format is float. ", ) + autopull_models: bool = Field( + False, + description="If set to True, the Ollama will automatically pull the models from the API base.", + ) class AzureOpenAISettings(BaseModel): @@ -277,6 +357,10 @@ class AzureOpenAISettings(BaseModel): class UISettings(BaseModel): enabled: bool path: str + default_mode: Literal["RAG", "Search", "Basic", "Summarize"] = Field( + "RAG", + description="The default mode.", + ) default_chat_system_prompt: str = Field( None, description="The default system prompt to use for the chat mode.", @@ -284,6 +368,10 @@ class UISettings(BaseModel): default_query_system_prompt: str = Field( None, description="The default system prompt to use for the query mode." ) + default_summarization_system_prompt: str = Field( + None, + description="The default system prompt to use for the summarization mode.", + ) delete_file_button_enabled: bool = Field( True, description="If the button to delete a file is enabled or not." ) @@ -319,6 +407,84 @@ class RagSettings(BaseModel): rerank: RerankSettings +class SummarizeSettings(BaseModel): + use_async: bool = Field( + True, + description="If set to True, the summarization will be done asynchronously.", + ) + + +class ClickHouseSettings(BaseModel): + host: str = Field( + "localhost", + description="The server hosting the ClickHouse database", + ) + port: int = Field( + 8443, + description="The port on which the ClickHouse database is accessible", + ) + username: str = Field( + "default", + description="The username to use to connect to the ClickHouse database", + ) + password: str = Field( + "", + description="The password to use to connect to the ClickHouse database", + ) + database: str = Field( + "__default__", + description="The default database to use for connections", + ) + secure: bool | str = Field( + False, + description="Use https/TLS for secure connection to the server", + ) + interface: str | None = Field( + None, + description="Must be either 'http' or 'https'. Determines the protocol to use for the connection", + ) + settings: dict[str, Any] | None = Field( + None, + description="Specific ClickHouse server settings to be used with the session", + ) + connect_timeout: int | None = Field( + None, + description="Timeout in seconds for establishing a connection", + ) + send_receive_timeout: int | None = Field( + None, + description="Read timeout in seconds for http connection", + ) + verify: bool | None = Field( + None, + description="Verify the server certificate in secure/https mode", + ) + ca_cert: str | None = Field( + None, + description="Path to Certificate Authority root certificate (.pem format)", + ) + client_cert: str | None = Field( + None, + description="Path to TLS Client certificate (.pem format)", + ) + client_cert_key: str | None = Field( + None, + description="Path to the private key for the TLS Client certificate", + ) + http_proxy: str | None = Field( + None, + description="HTTP proxy address", + ) + https_proxy: str | None = Field( + None, + description="HTTPS proxy address", + ) + server_host_name: str | None = Field( + None, + description="Server host name to be checked against the TLS certificate", + ) + + class PostgresSettings(BaseModel): host: str = Field( "localhost", @@ -400,6 +566,27 @@ class QdrantSettings(BaseModel): ) +class MilvusSettings(BaseModel): + uri: str = Field( + "local_data/private_gpt/milvus/milvus_local.db", + description="The URI of the Milvus instance. For example: 'local_data/private_gpt/milvus/milvus_local.db' for Milvus Lite.", + ) + token: str = Field( + "", + description=( + "A valid access token to access the specified Milvus instance. " + "This can be used as a recommended alternative to setting user and password separately. " + ), + ) + collection_name: str = Field( + "make_this_parameterizable_per_api_call", + description="The name of the collection in Milvus. Default is 'make_this_parameterizable_per_api_call'.", + ) + overwrite: bool = Field( + True, description="Overwrite the previous collection schema if it exists." + ) + + class Settings(BaseModel): server: ServerSettings data: DataSettings @@ -410,13 +597,17 @@ class Settings(BaseModel): huggingface: HuggingFaceSettings sagemaker: SagemakerSettings openai: OpenAISettings + gemini: GeminiSettings ollama: OllamaSettings azopenai: AzureOpenAISettings vectorstore: VectorstoreSettings nodestore: NodeStoreSettings rag: RagSettings + summarize: SummarizeSettings qdrant: QdrantSettings | None = None postgres: PostgresSettings | None = None + clickhouse: ClickHouseSettings | None = None + milvus: MilvusSettings | None = None """ diff --git a/private_gpt/ui/ui.py b/private_gpt/ui/ui.py index 4206f6533..abdfb0c6d 100644 --- a/private_gpt/ui/ui.py +++ b/private_gpt/ui/ui.py @@ -1,9 +1,10 @@ """This file should be imported if and only if you want to run the UI locally.""" -import itertools +import base64 import logging import time from collections.abc import Iterable +from enum import Enum from pathlib import Path from typing import Any @@ -12,6 +13,7 @@ from gradio.themes.utils.colors import slate # type: ignore from injector import inject, singleton from llama_index.core.llms import ChatMessage, ChatResponse, MessageRole +from llama_index.core.types import TokenGen from pydantic import BaseModel from private_gpt.constants import PROJECT_ROOT_PATH @@ -20,6 +22,7 @@ from private_gpt.server.chat.chat_service import ChatService, CompletionGen from private_gpt.server.chunks.chunks_service import Chunk, ChunksService from private_gpt.server.ingest.ingest_service import IngestService +from private_gpt.server.recipes.summarize.summarize_service import SummarizeService from private_gpt.settings.settings import settings from private_gpt.ui.images import logo_svg @@ -31,9 +34,22 @@ UI_TAB_TITLE = "My Private GPT" -SOURCES_SEPARATOR = "\n\n Sources: \n" +SOURCES_SEPARATOR = "
Sources: \n" -MODES = ["Query Files", "Search Files", "LLM Chat (no context from files)"] + +class Modes(str, Enum): + RAG_MODE = "RAG" + SEARCH_MODE = "Search" + BASIC_CHAT_MODE = "Basic" + SUMMARIZE_MODE = "Summarize" + + +MODES: list[Modes] = [ + Modes.RAG_MODE, + Modes.SEARCH_MODE, + Modes.BASIC_CHAT_MODE, + Modes.SUMMARIZE_MODE, +] class Source(BaseModel): @@ -71,10 +87,12 @@ def __init__( ingest_service: IngestService, chat_service: ChatService, chunks_service: ChunksService, + summarizeService: SummarizeService, ) -> None: self._ingest_service = ingest_service self._chat_service = chat_service self._chunks_service = chunks_service + self._summarize_service = summarizeService # Cache the UI blocks self._ui_block = None @@ -82,10 +100,15 @@ def __init__( self._selected_filename = None # Initialize system prompt based on default mode - self.mode = MODES[0] - self._system_prompt = self._get_default_system_prompt(self.mode) - - def _chat(self, message: str, history: list[list[str]], mode: str, *_: Any) -> Any: + default_mode_map = {mode.value: mode for mode in Modes} + self._default_mode = default_mode_map.get( + settings().ui.default_mode, Modes.RAG_MODE + ) + self._system_prompt = self._get_default_system_prompt(self._default_mode) + + def _chat( + self, message: str, history: list[list[str]], mode: Modes, *_: Any + ) -> Any: def yield_deltas(completion_gen: CompletionGen) -> Iterable[str]: full_response: str = "" stream = completion_gen.response @@ -109,25 +132,31 @@ def yield_deltas(completion_gen: CompletionGen) -> Iterable[str]: + f"{index}. {source.file} (page {source.page}) \n\n" ) used_files.add(f"{source.file}-{source.page}") + sources_text += "
\n\n" full_response += sources_text yield full_response + def yield_tokens(token_gen: TokenGen) -> Iterable[str]: + full_response: str = "" + for token in token_gen: + full_response += str(token) + yield full_response + def build_history() -> list[ChatMessage]: - history_messages: list[ChatMessage] = list( - itertools.chain( - *[ - [ - ChatMessage(content=interaction[0], role=MessageRole.USER), - ChatMessage( - # Remove from history content the Sources information - content=interaction[1].split(SOURCES_SEPARATOR)[0], - role=MessageRole.ASSISTANT, - ), - ] - for interaction in history - ] + history_messages: list[ChatMessage] = [] + + for interaction in history: + history_messages.append( + ChatMessage(content=interaction[0], role=MessageRole.USER) ) - ) + if len(interaction) > 1 and interaction[1] is not None: + history_messages.append( + ChatMessage( + # Remove from history content the Sources information + content=interaction[1].split(SOURCES_SEPARATOR)[0], + role=MessageRole.ASSISTANT, + ) + ) # max 20 messages to try to avoid context overflow return history_messages[:20] @@ -144,8 +173,7 @@ def build_history() -> list[ChatMessage]: ), ) match mode: - case "Query Files": - + case Modes.RAG_MODE: # Use only the selected file for the query context_filter = None if self._selected_filename is not None: @@ -164,14 +192,14 @@ def build_history() -> list[ChatMessage]: context_filter=context_filter, ) yield from yield_deltas(query_stream) - case "LLM Chat (no context from files)": + case Modes.BASIC_CHAT_MODE: llm_stream = self._chat_service.stream_chat( messages=all_messages, use_context=False, ) yield from yield_deltas(llm_stream) - case "Search Files": + case Modes.SEARCH_MODE: response = self._chunks_service.retrieve_relevant( text=message, limit=4, prev_next_chunks=0 ) @@ -184,37 +212,76 @@ def build_history() -> list[ChatMessage]: f"{source.text}" for index, source in enumerate(sources, start=1) ) + case Modes.SUMMARIZE_MODE: + # Summarize the given message, optionally using selected files + context_filter = None + if self._selected_filename: + docs_ids = [] + for ingested_document in self._ingest_service.list_ingested(): + if ( + ingested_document.doc_metadata["file_name"] + == self._selected_filename + ): + docs_ids.append(ingested_document.doc_id) + context_filter = ContextFilter(docs_ids=docs_ids) + + summary_stream = self._summarize_service.stream_summarize( + use_context=True, + context_filter=context_filter, + instructions=message, + ) + yield from yield_tokens(summary_stream) # On initialization and on mode change, this function set the system prompt # to the default prompt based on the mode (and user settings). @staticmethod - def _get_default_system_prompt(mode: str) -> str: + def _get_default_system_prompt(mode: Modes) -> str: p = "" match mode: # For query chat mode, obtain default system prompt from settings - case "Query Files": + case Modes.RAG_MODE: p = settings().ui.default_query_system_prompt # For chat mode, obtain default system prompt from settings - case "LLM Chat (no context from files)": + case Modes.BASIC_CHAT_MODE: p = settings().ui.default_chat_system_prompt + # For summarization mode, obtain default system prompt from settings + case Modes.SUMMARIZE_MODE: + p = settings().ui.default_summarization_system_prompt # For any other mode, clear the system prompt case _: p = "" return p + @staticmethod + def _get_default_mode_explanation(mode: Modes) -> str: + match mode: + case Modes.RAG_MODE: + return "Get contextualized answers from selected files." + case Modes.SEARCH_MODE: + return "Find relevant chunks of text in selected files." + case Modes.BASIC_CHAT_MODE: + return "Chat with the LLM using its training data. Files are ignored." + case Modes.SUMMARIZE_MODE: + return "Generate a summary of the selected files. Prompt to customize the result." + case _: + return "" + def _set_system_prompt(self, system_prompt_input: str) -> None: logger.info(f"Setting system prompt to: {system_prompt_input}") self._system_prompt = system_prompt_input - def _set_current_mode(self, mode: str) -> Any: + def _set_explanatation_mode(self, explanation_mode: str) -> None: + self._explanation_mode = explanation_mode + + def _set_current_mode(self, mode: Modes) -> Any: self.mode = mode self._set_system_prompt(self._get_default_system_prompt(mode)) - # Update placeholder and allow interaction if default system prompt is set - if self._system_prompt: - return gr.update(placeholder=self._system_prompt, interactive=True) - # Update placeholder and disable interaction if no default system prompt is set - else: - return gr.update(placeholder=self._system_prompt, interactive=False) + self._set_explanatation_mode(self._get_default_mode_explanation(mode)) + interactive = self._system_prompt is not None + return [ + gr.update(placeholder=self._system_prompt, interactive=interactive), + gr.update(value=self._explanation_mode), + ] def _list_ingested_files(self) -> list[list[str]]: files = set() @@ -314,17 +381,30 @@ def _build_ui_blocks(self) -> gr.Blocks: ".contain { display: flex !important; flex-direction: column !important; }" "#component-0, #component-3, #component-10, #component-8 { height: 100% !important; }" "#chatbot { flex-grow: 1 !important; overflow: auto !important;}" - "#col { height: calc(100vh - 112px - 16px) !important; }", + "#col { height: calc(100vh - 112px - 16px) !important; }" + "hr { margin-top: 1em; margin-bottom: 1em; border: 0; border-top: 1px solid #FFF; }" + ".avatar-image { background-color: antiquewhite; border-radius: 2px; }" + ".footer { text-align: center; margin-top: 20px; font-size: 14px; display: flex; align-items: center; justify-content: center; }" + ".footer-zylon-link { display:flex; margin-left: 5px; text-decoration: auto; color: var(--body-text-color); }" + ".footer-zylon-link:hover { color: #C7BAFF; }" + ".footer-zylon-ico { height: 20px; margin-left: 5px; background-color: antiquewhite; border-radius: 2px; }", ) as blocks: with gr.Row(): gr.HTML(f"