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docs: cleanup README and improve agent guides (#17003)
* docs: cleanup README and improve AI agent guides - Remove obsolete version warnings (openai>=1.0.0, pydantic>=2.0.0) - Add note about Responses API in README - Add GitHub templates section to CLAUDE.md, GEMINI.md, and AGENTS.md - Remove temporary test file test_pydantic_fields.py * update files * update Gemini file
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AGENTS.md

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Use `poetry run python script.py` to run Python scripts in the project environment (for non-test files).
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## GITHUB TEMPLATES
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When opening issues or pull requests, follow these templates:
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### Bug Reports (`.github/ISSUE_TEMPLATE/bug_report.yml`)
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- Describe what happened vs. expected behavior
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- Include relevant log output
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- Specify LiteLLM version
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- Indicate if you're part of an ML Ops team (helps with prioritization)
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### Feature Requests (`.github/ISSUE_TEMPLATE/feature_request.yml`)
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- Clearly describe the feature
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- Explain motivation and use case with concrete examples
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### Pull Requests (`.github/pull_request_template.md`)
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- Add at least 1 test in `tests/litellm/`
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- Ensure `make test-unit` passes
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## TESTING CONSIDERATIONS
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1. **Provider Tests**: Test against real provider APIs when possible

CLAUDE.md

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### Running Scripts
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- `poetry run python script.py` - Run Python scripts (use for non-test files)
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### GitHub Issue & PR Templates
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When contributing to the project, use the appropriate templates:
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**Bug Reports** (`.github/ISSUE_TEMPLATE/bug_report.yml`):
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- Describe what happened vs. what you expected
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- Include relevant log output
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- Specify your LiteLLM version
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**Feature Requests** (`.github/ISSUE_TEMPLATE/feature_request.yml`):
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- Describe the feature clearly
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- Explain the motivation and use case
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**Pull Requests** (`.github/pull_request_template.md`):
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- Add at least 1 test in `tests/litellm/`
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- Ensure `make test-unit` passes
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## Architecture Overview
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LiteLLM is a unified interface for 100+ LLM providers with two main components:

GEMINI.md

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- `poetry run pytest tests/path/to/test_file.py -v` - Run specific test file
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- `poetry run pytest tests/path/to/test_file.py::test_function -v` - Run specific test
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### Running Scripts
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- `poetry run python script.py` - Run Python scripts (use for non-test files)
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### GitHub Issue & PR Templates
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When contributing to the project, use the appropriate templates:
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**Bug Reports** (`.github/ISSUE_TEMPLATE/bug_report.yml`):
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- Describe what happened vs. what you expected
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- Include relevant log output
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- Specify your LiteLLM version
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**Feature Requests** (`.github/ISSUE_TEMPLATE/feature_request.yml`):
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- Describe the feature clearly
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- Explain the motivation and use case
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**Pull Requests** (`.github/pull_request_template.md`):
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- Add at least 1 test in `tests/litellm/`
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- Ensure `make test-unit` passes
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## Architecture Overview
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LiteLLM is a unified interface for 100+ LLM providers with two main components:

README.md

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# Usage ([**Docs**](https://docs.litellm.ai/docs/))
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> [!IMPORTANT]
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> LiteLLM v1.0.0 now requires `openai>=1.0.0`. Migration guide [here](https://docs.litellm.ai/docs/migration)
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> LiteLLM v1.40.14+ now requires `pydantic>=2.0.0`. No changes required.
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<a target="_blank" href="https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/liteLLM_Getting_Started.ipynb">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
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</a>
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```
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> **Note:** LiteLLM also supports the [Responses API](https://docs.litellm.ai/docs/response_api) (`litellm.responses()`)
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Call any model supported by a provider, with `model=<provider_name>/<model_name>`. There might be provider-specific details here, so refer to [provider docs for more information](https://docs.litellm.ai/docs/providers)
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## Async ([Docs](https://docs.litellm.ai/docs/completion/stream#async-completion))

test_pydantic_fields.py

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