renamed flows to aiflows

ControllerAtomicFlow.py

@@ -34,17 +34,17 @@ class ControllerAtomicFlow(ChatAtomicFlow):
         - `commands` (List[Dict[str,Any]]): A list of commands that the controller can call. Default: []
         - `finish` (Dict[str,Any]): The configuration of the finish command. Default parameters: No default parameters.
         - `system_message_prompt_template` (Dict[str, Any]): The prompt template used to generate the system message.
-        By default, it's type is flows.prompt_template.JinjaPrompt. It's default parameters are:
+        By default, it's type is aiflows.prompt_template.JinjaPrompt. It's default parameters are:
             - `template` (str): The template of the prompt. Default: see ControllerAtomicFlow.yaml for the default template.
             - `input_variables` (List[str]): The input variables of the prompt. Default: ["commands"]. Note that the commands are the commands of the executor 
             (subflows of branching flow) and are actually to the system prompt template via the `_build_commands_manual` function of this class.
         - `human_message_prompt_template` (Dict[str, Any]): The prompt template of the human/user message (message used everytime the except the first time in).
-        It's passed as the user message to the LLM. By default its of type flows.prompt_template.JinjaPrompt and has the following parameters:
+        It's passed as the user message to the LLM. By default its of type aiflows.prompt_template.JinjaPrompt and has the following parameters:
             - `template` (str): The template of the prompt. Default: see ControllerAtomicFlow.yaml for the default template.
             - `input_variables` (List[str]): The input variables of the prompt. Default: ["observation"]
         - init_human_message_prompt_template` (Dict[str, Any]):  The prompt template of the human/user message used to initialize the conversation
         (first time in). It is used to generate the human message. It's passed as the user message to the LLM.
-        By default its of type flows.prompt_template.JinjaPrompt and has the following parameters:
+        By default its of type aiflows.prompt_template.JinjaPrompt and has the following parameters:
             - `template` (str): The template of the prompt. Default: see ControllerAtomicFlow.yaml for the default template.
             - `input_variables` (List[str]): The input variables of the prompt. Default: ["goal"]
         - All other parameters are inherited from the default configuration of ChatAtomicFlow (see Flowcard, i.e. README.md, of ChatAtomicFlowModule).

ControllerAtomicFlow.yaml

@@ -28,7 +28,7 @@ output_interface:
 #######################################################
 # ToDo: Some parts of the prompt don't make sense -- update them
 system_message_prompt_template:
-  _target_: flows.prompt_template.JinjaPrompt
+  _target_: aiflows.prompt_template.JinjaPrompt
   template: |2-
     You are a smart AI assistant. 
     
@@ -69,7 +69,7 @@ system_message_prompt_template:
   input_variables: ["commands"]
 
 human_message_prompt_template:
-  _target_: flows.prompt_template.JinjaPrompt
+  _target_: aiflows.prompt_template.JinjaPrompt
   template: |2-
     Here is the response to your last action:
     {{observation}}
@@ -77,7 +77,7 @@ human_message_prompt_template:
     - "observation"
 
 init_human_message_prompt_template:
-  _target_: flows.prompt_template.JinjaPrompt
+  _target_: aiflows.prompt_template.JinjaPrompt
   template: |2-
     Here is the goal you need to achieve:
     {{goal}}

ControllerExecutorFlow.py

@@ -1,7 +1,7 @@
 from typing import Dict, Any
 
-from flows.base_flows import CircularFlow
-from flows.utils import logging
+from aiflows.base_flows import CircularFlow
+from aiflows.utils import logging
 
 from .ControllerAtomicFlow import ControllerAtomicFlow
 

ControllerExecutorFlow.yaml

@@ -12,7 +12,7 @@ output_interface:
 ### Subflows specification
 subflows_config:
   Controller:
-    _target_: aiflows.ControllerAtomicFlow.instantiate_from_default_config
+    _target_: flow_modules.aiflows.ControllerAtomicFlow.instantiate_from_default_config
     finish:
       description: "Signal that the objective has been satisfied, and returns the answer to the user."
       input_args: ["answer"]
@@ -24,7 +24,7 @@ subflows_config:
 
 
   Executor:
-    _target_: flows.base_flows.BranchingFlow.instantiate_from_default_config
+    _target_: aiflows.base_flows.BranchingFlow.instantiate_from_default_config
 # E.g.,
 #    subflows_config:
 #      wiki_search:
@@ -36,9 +36,9 @@ early_exit_key: "EARLY_EXIT"
 topology:
   - goal: "Select the next action and prepare the input for the executor."
     input_interface:
-      _target_: flows.interfaces.KeyInterface
+      _target_: aiflows.interfaces.KeyInterface
       additional_transformations:
-        - _target_: flows.data_transformations.KeyMatchInput
+        - _target_: aiflows.data_transformations.KeyMatchInput
     flow: Controller
     output_interface:
       _target_: ControllerExecutorFlow.detect_finish_or_continue
@@ -46,14 +46,14 @@ topology:
 
   - goal: "Execute the action specified by the Controller."
     input_interface:
-      _target_: flows.interfaces.KeyInterface
+      _target_: aiflows.interfaces.KeyInterface
       keys_to_rename:
         command: branch
         command_args: branch_input_data
       keys_to_select: ["branch", "branch_input_data"]
     flow: Executor
     output_interface:
-      _target_: flows.interfaces.KeyInterface
+      _target_: aiflows.interfaces.KeyInterface
       keys_to_rename:
         branch_output_data: observation
       keys_to_select: ["observation"]

README.md

@@ -62,17 +62,17 @@ Default: "Proposes the next action to take towards achieving the goal, and prepa
 - `commands` (List[Dict[str,Any]]): A list of commands that the controller can call. Default: []
 - `finish` (Dict[str,Any]): The configuration of the finish command. Default parameters: No default parameters.
 - `system_message_prompt_template` (Dict[str, Any]): The prompt template used to generate the system message.
-By default, it's type is flows.prompt_template.JinjaPrompt. It's default parameters are:
+By default, it's type is aiflows.prompt_template.JinjaPrompt. It's default parameters are:
     - `template` (str): The template of the prompt. Default: see ControllerAtomicFlow.yaml for the default template.
     - `input_variables` (List[str]): The input variables of the prompt. Default: ["commands"]. Note that the commands are the commands of the executor 
     (subflows of branching flow) and are actually to the system prompt template via the `_build_commands_manual` function of this class.
 - `human_message_prompt_template` (Dict[str, Any]): The prompt template of the human/user message (message used everytime the except the first time in).
-It's passed as the user message to the LLM. By default its of type flows.prompt_template.JinjaPrompt and has the following parameters:
+It's passed as the user message to the LLM. By default its of type aiflows.prompt_template.JinjaPrompt and has the following parameters:
     - `template` (str): The template of the prompt. Default: see ControllerAtomicFlow.yaml for the default template.
     - `input_variables` (List[str]): The input variables of the prompt. Default: ["observation"]
 - init_human_message_prompt_template` (Dict[str, Any]):  The prompt template of the human/user message used to initialize the conversation
 (first time in). It is used to generate the human message. It's passed as the user message to the LLM.
-By default its of type flows.prompt_template.JinjaPrompt and has the following parameters:
+By default its of type aiflows.prompt_template.JinjaPrompt and has the following parameters:
     - `template` (str): The template of the prompt. Default: see ControllerAtomicFlow.yaml for the default template.
     - `input_variables` (List[str]): The input variables of the prompt. Default: ["goal"]
 - All other parameters are inherited from the default configuration of ChatAtomicFlow (see Flowcard, i.e. README.md, of ChatAtomicFlowModule).

WikiSearchAtomicFlow.py

@@ -2,9 +2,9 @@ from copy import deepcopy
 
 from typing import List, Dict, Optional, Any
 
-from flows.base_flows import AtomicFlow
+from aiflows.base_flows import AtomicFlow
 
-from flows.utils import logging
+from aiflows.utils import logging
 from .wikipediaAPI import WikipediaAPIWrapper
 
 log = logging.get_logger(__name__)

__init__.py

@@ -2,7 +2,7 @@
 dependencies = [
     {"url": "aiflows/ChatFlowModule", "revision": "main"},
 ]
-from flows import flow_verse
+from aiflows import flow_verse
 
 flow_verse.sync_dependencies(dependencies)
 # ~~~

demo.yaml

@@ -1,11 +1,11 @@
 flow:
-  _target_: aiflows.ControllerExecutorFlowModule.ControllerExecutorFlow.instantiate_from_default_config
+  _target_: flow_modules.aiflows.ControllerExecutorFlowModule.ControllerExecutorFlow.instantiate_from_default_config
   max_rounds: 30
 
   ### Subflows specification
   subflows_config:
     Controller:
-      _target_: aiflows.ControllerExecutorFlowModule.ControllerAtomicFlow.instantiate_from_default_config
+      _target_: flow_modules.aiflows.ControllerExecutorFlowModule.ControllerAtomicFlow.instantiate_from_default_config
       commands:
         wiki_search:
           description: "Performs a search on Wikipedia."
@@ -14,14 +14,14 @@ flow:
           description: "Signal that the objective has been satisfied, and returns the answer to the user."
           input_args: [ "answer" ]
       backend:
-        _target_: flows.backends.llm_lite.LiteLLMBackend
+        _target_: aiflows.backends.llm_lite.LiteLLMBackend
         api_infos: ???
         model_name: 
           openai: "gpt-3.5-turbo"
           azure: "azure/gpt-4"
 
     Executor:
-      _target_: flows.base_flows.BranchingFlow.instantiate_from_default_config
+      _target_: aiflows.base_flows.BranchingFlow.instantiate_from_default_config
       subflows_config:
         wiki_search:
-          _target_: aiflows.ControllerExecutorFlowModule.WikiSearchAtomicFlow.instantiate_from_default_config
+          _target_: flow_modules.aiflows.ControllerExecutorFlowModule.WikiSearchAtomicFlow.instantiate_from_default_config

run.py

@@ -2,13 +2,13 @@ import os
 
 import hydra
 
-import flows
-from flows.flow_launchers import FlowLauncher
-from flows.backends.api_info import ApiInfo
-from flows.utils.general_helpers import read_yaml_file
+import aiflows
+from aiflows.flow_launchers import FlowLauncher
+from aiflows.backends.api_info import ApiInfo
+from aiflows.utils.general_helpers import read_yaml_file
 
-from flows import logging
-from flows.flow_cache import CACHING_PARAMETERS, clear_cache
+from aiflows import logging
+from aiflows.flow_cache import CACHING_PARAMETERS, clear_cache
 
 CACHING_PARAMETERS.do_caching = False  # Set to True in order to disable caching
 # clear_cache() # Uncomment this line to clear the cache
@@ -18,7 +18,7 @@ logging.set_verbosity_debug()
 dependencies = [
     {"url": "aiflows/ControllerExecutorFlowModule", "revision": os.getcwd()},
 ]
-from flows import flow_verse
+from aiflows import flow_verse
 
 flow_verse.sync_dependencies(dependencies)