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.gitignore
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.gitignore
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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.idea/
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56
README.md
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README.md
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# LangChain gpt4free
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LangChain gpt4free is an open-source project that assists in building applications using LLM (Large Language Models) and provides free access to GPT4/3.5.
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## Installation
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To install langchain_g4f, run the following command:
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```shell
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pip install git+https://github.com/MIDORIBIN/langchain-gpt4free.git
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```
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This command will install langchain_g4f.
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## Usage
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Here is an example of how to use langchain_g4f
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```python
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from g4f import Provider, Model
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from langchain.llms.base import LLM
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from langchain_g4f import G4FLLM
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def main():
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llm: LLM = G4FLLM(
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model=Model.gpt_35_turbo,
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provider=Provider.Aichat,
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)
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res = llm('hello')
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print(res) # Hello! How can I assist you today?
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if __name__ == '__main__':
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main()
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```
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The above sample code demonstrates the basic usage of langchain_g4f. Choose the appropriate model and provider, initialize the LLM, and then pass input text to the LLM object to obtain the result.
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## Support and Bug Reports
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For support and bug reports, please use the GitHub Issues page.
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Access the GitHub Issues page and create a new issue. Select the appropriate label and provide detailed information.
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## Contributing
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To contribute to langchain_g4f, follow these steps to submit a pull request:
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1. Fork the project repository.
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2. Clone the forked repository to your local machine.
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3. Make the necessary changes.
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4. Commit the changes and push to your forked repository.
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5. Create a pull request towards the original project repository.
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49
langchain_g4f/G4FLLM.py
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langchain_g4f/G4FLLM.py
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from types import ModuleType
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from typing import Optional, List, Any, Mapping, Union
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import g4f
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from langchain.callbacks.manager import CallbackManagerForLLMRun
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from langchain.llms.base import LLM
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from langchain.llms.utils import enforce_stop_tokens
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class G4FLLM(LLM):
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# Model.model or str
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model: Union[type, str]
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# Provider.Provider
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provider: Optional[ModuleType] = None
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auth: Optional[Union[str, bool]] = None
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create_kwargs: Optional[dict] = None
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@property
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def _llm_type(self) -> str:
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return 'custom'
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def _call(self, prompt: str, stop: Optional[List[str]] = None,
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run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any) -> str:
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create_kwargs = {} if self.create_kwargs is None else self.create_kwargs.copy()
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if self.model is not None:
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create_kwargs['model'] = self.model
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if self.provider is not None:
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create_kwargs['provider'] = self.provider
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if self.auth is not None:
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create_kwargs['auth'] = self.auth
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text = g4f.ChatCompletion.create(
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messages=[{'role': 'user', 'content': prompt}],
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**create_kwargs,
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)
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if stop is not None:
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text = enforce_stop_tokens(text, stop)
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return text
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@property
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def _identifying_params(self) -> Mapping[str, Any]:
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"""Get the identifying parameters."""
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return {
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'model': self.model,
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'provider': self.provider,
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'auth': self.auth,
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'create_kwargs': self.create_kwargs,
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}
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1
langchain_g4f/__init__.py
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from .G4FLLM import G4FLLM
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pyproject.toml
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[build-system]
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requires = ["setuptools", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "langchain_g4f"
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version = "1.0.0"
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description = ""
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authors = []
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readme = "README.md"
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requires-python = ">=3.10"
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dependencies = [
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"langchain>=0.0.225",
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"gpt4free @ git+https://github.com/xtekky/gpt4free.git",
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]
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[tool.setuptools.packages.find]
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include = ["langchain_g4f"]
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sample.py
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from g4f import Provider, Model
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from langchain.llms.base import LLM
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from langchain_g4f import G4FLLM
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def main():
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llm: LLM = G4FLLM(
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model=Model.gpt_35_turbo,
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provider=Provider.Aichat,
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)
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res = llm('hello')
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print(res) # Hello! How can I assist you today?
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if __name__ == '__main__':
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main()
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