38cdacbcb6
<!-- .github/pull_request_template.md --> ## Description Resolve Gemini Adapter issues: 1. resolve embedding batch issue, 2. Resolve slowness because gemini tokenizer was sending word per word to Googles API to count tokens (using OpenAI's local tokenizer to count tokens for Gemini now) 3. Update deprecated library and move to instructor ## Type of Change <!-- Please check the relevant option --> - [x] Bug fix (non-breaking change that fixes an issue) - [ ] New feature (non-breaking change that adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to change) - [ ] Documentation update - [ ] Code refactoring - [ ] Performance improvement - [ ] Other (please specify): ## Pre-submission Checklist <!-- Please check all boxes that apply before submitting your PR --> - [ ] **I have tested my changes thoroughly before submitting this PR** - [ ] **This PR contains minimal changes necessary to address the issue/feature** - [ ] My code follows the project's coding standards and style guidelines - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have added necessary documentation (if applicable) - [ ] All new and existing tests pass - [ ] I have searched existing PRs to ensure this change hasn't been submitted already - [ ] I have linked any relevant issues in the description - [ ] My commits have clear and descriptive messages ## DCO Affirmation I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin.
86 lines
2.5 KiB
YAML
86 lines
2.5 KiB
YAML
name: LLM Test Suites
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permissions:
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contents: read
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on:
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workflow_call:
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env:
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RUNTIME__LOG_LEVEL: ERROR
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ENV: 'dev'
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jobs:
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test-gemini:
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name: Run Gemini Test
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runs-on: ubuntu-22.04
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steps:
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- name: Check out repository
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uses: actions/checkout@v4
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- name: Cognee Setup
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uses: ./.github/actions/cognee_setup
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with:
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python-version: '3.11.x'
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- name: Run Gemini Simple Example
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env:
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LLM_PROVIDER: "gemini"
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LLM_API_KEY: ${{ secrets.GEMINI_API_KEY }}
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LLM_MODEL: "gemini/gemini-2.0-flash"
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EMBEDDING_PROVIDER: "gemini"
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EMBEDDING_API_KEY: ${{ secrets.GEMINI_API_KEY }}
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EMBEDDING_MODEL: "gemini/text-embedding-004"
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EMBEDDING_DIMENSIONS: "768"
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EMBEDDING_MAX_TOKENS: "8076"
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run: uv run python ./examples/python/simple_example.py
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test-fastembed:
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name: Run Fastembed Test
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runs-on: ubuntu-22.04
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steps:
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- name: Check out repository
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uses: actions/checkout@v4
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- name: Cognee Setup
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uses: ./.github/actions/cognee_setup
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with:
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python-version: '3.11.x'
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- name: Run Fastembed Simple Example
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env:
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LLM_PROVIDER: "openai"
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LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
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LLM_MODEL: ${{ secrets.LLM_MODEL }}
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LLM_ENDPOINT: ${{ secrets.LLM_ENDPOINT }}
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LLM_API_VERSION: ${{ secrets.LLM_API_VERSION }}
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EMBEDDING_PROVIDER: "fastembed"
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EMBEDDING_MODEL: "sentence-transformers/all-MiniLM-L6-v2"
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EMBEDDING_DIMENSIONS: "384"
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EMBEDDING_MAX_TOKENS: "256"
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run: uv run python ./examples/python/simple_example.py
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test-openrouter:
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name: Run OpenRouter Test
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runs-on: ubuntu-22.04
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steps:
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- name: Check out repository
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uses: actions/checkout@v4
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- name: Cognee Setup
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uses: ./.github/actions/cognee_setup
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with:
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python-version: '3.11.x'
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- name: Run OpenRouter Simple Example
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env:
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LLM_PROVIDER: "custom"
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LLM_API_KEY: ${{ secrets.OPENROUTER_API_KEY }}
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LLM_MODEL: "openrouter/x-ai/grok-code-fast-1"
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LLM_ENDPOINT: "https://openrouter.ai/api/v1"
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EMBEDDING_PROVIDER: "openai"
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EMBEDDING_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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EMBEDDING_MODEL: "openai/text-embedding-3-large"
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EMBEDDING_DIMENSIONS: "3072"
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EMBEDDING_MAX_TOKENS: "8191"
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run: uv run python ./examples/python/simple_example.py
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