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--- |
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license: mit |
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--- |
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# Table of Contents |
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* [run](#run) |
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* [ChromaDBFlow](#ChromaDBFlow) |
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* [ChromaDBFlow](#ChromaDBFlow.ChromaDBFlow) |
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* [instantiate\_from\_config](#ChromaDBFlow.ChromaDBFlow.instantiate_from_config) |
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* [get\_input\_keys](#ChromaDBFlow.ChromaDBFlow.get_input_keys) |
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* [get\_output\_keys](#ChromaDBFlow.ChromaDBFlow.get_output_keys) |
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* [run](#ChromaDBFlow.ChromaDBFlow.run) |
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* [VectorStoreFlow](#VectorStoreFlow) |
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* [VectorStoreFlow](#VectorStoreFlow.VectorStoreFlow) |
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* [instantiate\_from\_config](#VectorStoreFlow.VectorStoreFlow.instantiate_from_config) |
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* [package\_documents](#VectorStoreFlow.VectorStoreFlow.package_documents) |
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* [run](#VectorStoreFlow.VectorStoreFlow.run) |
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* [\_\_init\_\_](#__init__) |
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<a id="run"></a> |
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# run |
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<a id="ChromaDBFlow"></a> |
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# ChromaDBFlow |
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<a id="ChromaDBFlow.ChromaDBFlow"></a> |
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## ChromaDBFlow Objects |
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```python |
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class ChromaDBFlow(AtomicFlow) |
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``` |
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A flow that uses the ChromaDB model to write and read memories stored in a database |
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*Configuration Parameters*: |
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- `name` (str): The name of the flow. Default: "chroma_db" |
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- `description` (str): A description of the flow. This description is used to generate the help message of the flow. |
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Default: "ChromaDB is a document store that uses vector embeddings to store and retrieve documents." |
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- `backend` (Dict[str, Any]): The configuration of the backend which is used to fetch api keys. Default: LiteLLMBackend with the |
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default parameters of LiteLLMBackend (see aiflows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten: |
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- `api_infos` (List[Dict[str, Any]]): The list of api infos. Default: No default value, this parameter is required. |
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- `model_name` (str): The name of the model. Default: "". In the current implementation, this parameter is not used. |
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- `n_results` (int): The number of results to retrieve when reading from the database. Default: 5 |
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- Other parameters are inherited from the default configuration of AtomicFlow (see AtomicFlow) |
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*Input Interface*: |
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- `operation` (str): The operation to perform. It can be "write" or "read". |
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- `content` (str or List[str]): The content to write or read. If operation is "write", it must be a string or a list of strings. If operation is "read", it must be a string. |
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*Output Interface*: |
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- `retrieved` (str or List[str]): The retrieved content. If operation is "write", it is an empty string. If operation is "read", it is a string or a list of strings. |
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**Arguments**: |
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- `backend` (`LiteLLMBackend`): The backend of the flow (used to retrieve the API key) |
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- `\**kwargs`: Additional arguments to pass to the flow. |
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<a id="ChromaDBFlow.ChromaDBFlow.instantiate_from_config"></a> |
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#### instantiate\_from\_config |
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```python |
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@classmethod |
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def instantiate_from_config(cls, config) |
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``` |
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This method instantiates the flow from a configuration file |
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**Arguments**: |
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- `config` (`Dict[str, Any]`): The configuration of the flow. |
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**Returns**: |
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`ChromaDBFlow`: The instantiated flow. |
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<a id="ChromaDBFlow.ChromaDBFlow.get_input_keys"></a> |
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#### get\_input\_keys |
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```python |
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def get_input_keys() -> List[str] |
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``` |
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This method returns the input keys of the flow. |
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**Returns**: |
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`List[str]`: The input keys of the flow. |
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<a id="ChromaDBFlow.ChromaDBFlow.get_output_keys"></a> |
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#### get\_output\_keys |
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```python |
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def get_output_keys() -> List[str] |
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``` |
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This method returns the output keys of the flow. |
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**Returns**: |
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`List[str]`: The output keys of the flow. |
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<a id="ChromaDBFlow.ChromaDBFlow.run"></a> |
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#### run |
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```python |
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def run(input_data: Dict[str, Any]) -> Dict[str, Any] |
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``` |
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This method runs the flow. It runs the ChromaDBFlow. It either writes or reads memories from the database. |
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**Arguments**: |
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- `input_data` (`Dict[str, Any]`): The input data of the flow. |
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**Returns**: |
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`Dict[str, Any]`: The output data of the flow. |
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<a id="VectorStoreFlow"></a> |
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# VectorStoreFlow |
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<a id="VectorStoreFlow.VectorStoreFlow"></a> |
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## VectorStoreFlow Objects |
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```python |
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class VectorStoreFlow(AtomicFlow) |
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``` |
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A flow that uses the VectorStore model to write and read memories stored in a database (see VectorStoreFlow.yaml for the default configuration) |
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*Configuration Parameters*: |
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- `name` (str): The name of the flow. Default: "VecotrStoreFlow" |
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- `description` (str): A description of the flow. This description is used to generate the help message of the flow. |
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Default: "VectorStoreFlow" |
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- `backend` (Dict[str, Any]): The configuration of the backend which is used to fetch api keys. Default: LiteLLMBackend with the |
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default parameters of LiteLLMBackend (see aiflows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten: |
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- `api_infos` (List[Dict[str, Any]]): The list of api infos. Default: No default value, this parameter is required. |
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- `model_name` (str): The name of the model. Default: "". In the current implementation, this parameter is not used. |
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- `type` (str): The type of the vector store. It can be "chroma" or "faiss". Default: "chroma" |
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- `embedding_size` (int): The size of the embeddings (only for faiss). Default: 1536 |
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- `retriever_config` (Dict[str, Any]): The configuration of the retriever. Default: empty dictionary |
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- Other parameters are inherited from the default configuration of AtomicFlow (see AtomicFlow) |
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*Input Interface*: |
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- `operation` (str): The operation to perform. It can be "write" or "read". |
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- `content` (str or List[str]): The content to write or read. If operation is "write", it must be a string or a list of strings. If operation is "read", it must be a string. |
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*Output Interface*: |
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- `retrieved` (str or List[str]): The retrieved content. If operation is "write", it is an empty string. If operation is "read", it is a string or a list of strings. |
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**Arguments**: |
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- `backend` (`LiteLLMBackend`): The backend of the flow (used to retrieve the API key) |
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- `vector_db` (`VectorStoreRetriever`): The vector store retriever |
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- `type` (`str`): The type of the vector store |
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- `\**kwargs`: Additional arguments to pass to the flow. See :class:`aiflows.base_flows.AtomicFlow` for more details. |
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<a id="VectorStoreFlow.VectorStoreFlow.instantiate_from_config"></a> |
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#### instantiate\_from\_config |
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```python |
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@classmethod |
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def instantiate_from_config(cls, config: Dict[str, Any]) |
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``` |
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This method instantiates the flow from a configuration file |
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**Arguments**: |
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- `config` (`Dict[str, Any]`): The configuration of the flow. |
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**Returns**: |
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`VectorStoreFlow`: The instantiated flow. |
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<a id="VectorStoreFlow.VectorStoreFlow.package_documents"></a> |
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#### package\_documents |
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```python |
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@staticmethod |
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def package_documents(documents: List[str]) -> List[Document] |
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``` |
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This method packages the documents in a list of Documents. |
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**Arguments**: |
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- `documents` (`List[str]`): The documents to package. |
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**Returns**: |
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`List[Document]`: The packaged documents. |
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<a id="VectorStoreFlow.VectorStoreFlow.run"></a> |
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#### run |
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```python |
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def run(input_data: Dict[str, Any]) -> Dict[str, Any] |
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``` |
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This method runs the flow. It either writes or reads memories from the database. |
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**Arguments**: |
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- `input_data` (`Dict[str, Any]`): The input data of the flow. |
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**Returns**: |
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`Dict[str, Any]`: The output data of the flow. |
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<a id="__init__"></a> |
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# \_\_init\_\_ |
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