renamed flows to aiflow

ChromaDBFlow.py

@@ -7,7 +7,7 @@ from langchain.embeddings import OpenAIEmbeddings
 
 from chromadb import Client as ChromaClient
 
-from flows.base_flows import AtomicFlow
+from aiflows.base_flows import AtomicFlow
 
 import hydra
 
@@ -20,7 +20,7 @@ class ChromaDBFlow(AtomicFlow):
     - `description` (str): A description of the flow. This description is used to generate the help message of the flow. 
     Default: "ChromaDB is a document store that uses vector embeddings to store and retrieve documents."
     - `backend` (Dict[str, Any]): The configuration of the backend which is used to fetch api keys. Default: LiteLLMBackend with the
-    default parameters of LiteLLMBackend (see flows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten:
+    default parameters of LiteLLMBackend (see aiflows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten:
         - `api_infos` (List[Dict[str, Any]]): The list of api infos. Default: No default value, this parameter is required.
         - `model_name` (str): The name of the model. Default: "". In the current implementation, this parameter is not used.
     - `n_results` (int): The number of results to retrieve when reading from the database. Default: 5

ChromaDBFlow.yaml

@@ -2,7 +2,7 @@ name: chroma_db
 description: ChromaDB is a document store that uses vector embeddings to store and retrieve documents
 
 backend:
-  _target_: flows.backends.llm_lite.LiteLLMBackend
+  _target_: aiflows.backends.llm_lite.LiteLLMBackend
   api_infos: ???
   model_name: "" #Not used in current implementation
 input_interface:

README.md

@@ -42,7 +42,7 @@ A flow that uses the ChromaDB model to write and read memories stored in a datab
 - `description` (str): A description of the flow. This description is used to generate the help message of the flow. 
 Default: "ChromaDB is a document store that uses vector embeddings to store and retrieve documents."
 - `backend` (Dict[str, Any]): The configuration of the backend which is used to fetch api keys. Default: LiteLLMBackend with the
-default parameters of LiteLLMBackend (see flows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten:
+default parameters of LiteLLMBackend (see aiflows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten:
     - `api_infos` (List[Dict[str, Any]]): The list of api infos. Default: No default value, this parameter is required.
     - `model_name` (str): The name of the model. Default: "". In the current implementation, this parameter is not used.
 - `n_results` (int): The number of results to retrieve when reading from the database. Default: 5
@@ -147,7 +147,7 @@ A flow that uses the VectorStore model to write and read memories stored in a da
 - `description` (str): A description of the flow. This description is used to generate the help message of the flow.
 Default: "VectorStoreFlow"
 - `backend` (Dict[str, Any]): The configuration of the backend which is used to fetch api keys. Default: LiteLLMBackend with the
-default parameters of LiteLLMBackend (see flows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten:
+default parameters of LiteLLMBackend (see aiflows.backends.LiteLLMBackend). Except for the following parameter whose default value is overwritten:
     - `api_infos` (List[Dict[str, Any]]): The list of api infos. Default: No default value, this parameter is required.
     - `model_name` (str): The name of the model. Default: "". In the current implementation, this parameter is not used.
 - `type` (str): The type of the vector store. It can be "chroma" or "faiss". Default: "chroma"
@@ -169,7 +169,7 @@ default parameters of LiteLLMBackend (see flows.backends.LiteLLMBackend). Except
 - `backend` (`LiteLLMBackend`): The backend of the flow (used to retrieve the API key)
 - `vector_db` (`VectorStoreRetriever`): The vector store retriever
 - `type` (`str`): The type of the vector store
-- `\**kwargs`: Additional arguments to pass to the flow. See :class:`flows.base_flows.AtomicFlow` for more details.
+- `\**kwargs`: Additional arguments to pass to the flow. See :class:`aiflows.base_flows.AtomicFlow` for more details.
 
 <a id="VectorStoreFlow.VectorStoreFlow.instantiate_from_config"></a>
 

VectorStoreFlow.py

@@ -9,7 +9,7 @@ from langchain.schema import Document
 from langchain.vectorstores import Chroma, FAISS
 from langchain.vectorstores.base import VectorStoreRetriever
 
-from flows.base_flows import AtomicFlow
+from aiflows.base_flows import AtomicFlow
 import hydra
 
 
@@ -45,7 +45,7 @@ class VectorStoreFlow(AtomicFlow):
     :type vector_db: VectorStoreRetriever
     :param type: The type of the vector store
     :type type: str
-    :param \**kwargs: Additional arguments to pass to the flow. See :class:`flows.base_flows.AtomicFlow` for more details.
+    :param \**kwargs: Additional arguments to pass to the flow. See :class:`aiflows.base_flows.AtomicFlow` for more details.
     """
     REQUIRED_KEYS_CONFIG = ["type"]
 

VectorStoreFlow.yaml

@@ -2,7 +2,7 @@ name: "VectorStoreFlow"
 description: "VectorStoreFlow"
 
 backend:
-  _target_: flows.backends.llm_lite.LiteLLMBackend
+  _target_: aiflows.backends.llm_lite.LiteLLMBackend
   api_infos: ???
   model_name: "" #Not used in current implementation
   

demo.yaml

@@ -4,29 +4,29 @@ chroma_demo_flow:
     - "content"
   output_interface:
     - "retrieved"
-  _target_: flows.base_flows.SequentialFlow.instantiate_from_default_config
+  _target_: aiflows.base_flows.SequentialFlow.instantiate_from_default_config
   name: "demoChromaDBFlow"
   description: "An example flow of how to read and writed in a ChromaDBFlowModule."
   subflows_config:
     chroma_db:
       input_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_select: ["operation","content"]
-      _target_: aiflows.VectorStoreFlowModule.ChromaDBFlow.instantiate_from_default_config
+      _target_: flow_modules.aiflows.VectorStoreFlowModule.ChromaDBFlow.instantiate_from_default_config
       
       backend:
-        _target_: flows.backends.llm_lite.LiteLLMBackend
+        _target_: aiflows.backends.llm_lite.LiteLLMBackend
         api_infos: ???
         model_name: "" #Not used in current implementation
       n_results: 1 # number of results to retrieve when query
   topology:
     - goal: Write content to the ChromaDB
       input_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_select: ["operation","content"]
       flow: chroma_db
       output_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_set:
             operation: "read"
         keys_to_rename:
@@ -35,11 +35,11 @@ chroma_demo_flow:
 
     - goal: Read content from the ChromaDB
       input_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_select: ["operation","content"]
       flow: chroma_db
       output_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_select: ["retrieved"]
 
 vector_store_demo_flow:
@@ -50,24 +50,24 @@ vector_store_demo_flow:
     - "retrieved"
   name: "demoVectorStoreFlow"
   description: "An example flow of how to read and write in a VectorStoreFlowModule."
-  _target_: flows.base_flows.SequentialFlow.instantiate_from_default_config
+  _target_: aiflows.base_flows.SequentialFlow.instantiate_from_default_config
   subflows_config:
     
     vs_db:
-      _target_: aiflows.VectorStoreFlowModule.VectorStoreFlow.instantiate_from_default_config
+      _target_: flow_modules.aiflows.VectorStoreFlowModule.VectorStoreFlow.instantiate_from_default_config
       backend:
-        _target_: flows.backends.llm_lite.LiteLLMBackend
+        _target_: aiflows.backends.llm_lite.LiteLLMBackend
         api_infos: ???
         model_name: "" #Not used in current implementation
 
   topology:
     - goal: Write content to the VectorStore
       input_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_select: ["operation","content"]
       flow: vs_db
       output_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_set:
             operation: "read"
         keys_to_rename:
@@ -76,10 +76,10 @@ vector_store_demo_flow:
 
     - goal: Read content from the VectorStore
       input_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_select: ["operation","content"]
       flow: vs_db
       output_interface:
-        _target_: flows.interfaces.KeyInterface
+        _target_: aiflows.interfaces.KeyInterface
         keys_to_select: ["retrieved"]
   

run.py

@@ -3,12 +3,12 @@ import os
 
 import hydra
 
-import flows
-from flows.flow_launchers import FlowLauncher
-from flows.utils.general_helpers import read_yaml_file
-from flows.backends.api_info import ApiInfo
-from flows import logging
-from flows.flow_cache import CACHING_PARAMETERS, clear_cache
+import aiflows
+from aiflows.flow_launchers import FlowLauncher
+from aiflows.utils.general_helpers import read_yaml_file
+from aiflows.backends.api_info import ApiInfo
+from aiflows import logging
+from aiflows.flow_cache import CACHING_PARAMETERS, clear_cache
 
 CACHING_PARAMETERS.do_caching = False  # Set to True to enable caching
 # clear_cache() # Uncomment this line to clear the cache
@@ -18,7 +18,7 @@ logging.set_verbosity_debug()
 dependencies = [
     {"url": "aiflows/VectorStoreFlowModule", "revision": os.getcwd()},
 ]
-from flows import flow_verse
+from aiflows import flow_verse
 flow_verse.sync_dependencies(dependencies)
 
 if __name__ == "__main__":