renamed flows to aiflows

README.md

@@ -53,13 +53,13 @@ whose default value is overwritten:
     - `frequency_penalty` (float): The higher this value, the more likely the model will repeat itself. Default: 0.0
     - `presence_penalty` (float): The higher this value, the less likely the model will talk about a new topic. Default: 0.0
 - `system_message_prompt_template` (Dict[str,Any]): The template of the system message. It is used to generate the system message.
-By default its of type flows.prompt_template.JinjaPrompt.
+By default its of type aiflows.prompt_template.JinjaPrompt.
 None of the parameters of the prompt are defined by default and therefore need to be defined if one wants to use the system prompt. 
-Default parameters are defined in flows.prompt_template.jinja2_prompts.JinjaPrompt.
+Default parameters are defined in aiflows.prompt_template.jinja2_prompts.JinjaPrompt.
 - `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. None of the parameters of the prompt are defined by default and therefore need to be defined if one
-wants to use the init_human_message_prompt_template. Default parameters are defined in flows.prompt_template.jinja2_prompts.JinjaPrompt.
+By default its of type aiflows.prompt_template.JinjaPrompt. None of the parameters of the prompt are defined by default and therefore need to be defined if one
+wants to use the init_human_message_prompt_template. Default parameters are defined in aiflows.prompt_template.jinja2_prompts.JinjaPrompt.
 - `previous_messages` (Dict[str,Any]): Defines which previous messages to include in the input of the LLM. Note that if `first_k`and `last_k` are both none,
 all the messages of the flows's history are added to the input of the LLM. Default:
     - `first_k` (int): If defined, adds the first_k earliest messages of the flow's chat history to the input of the LLM. Default: None

VisionAtomicFlow.py

@@ -1,7 +1,7 @@
 
 from typing import Dict, Any
 from flow_modules.aiflows.ChatFlowModule import ChatAtomicFlow
-from flows.utils.general_helpers import encode_image,encode_from_buffer
+from aiflows.utils.general_helpers import encode_image,encode_from_buffer
 import cv2
 
 
@@ -36,13 +36,13 @@ class VisionAtomicFlow(ChatAtomicFlow):
         - `frequency_penalty` (float): The higher this value, the more likely the model will repeat itself. Default: 0.0
         - `presence_penalty` (float): The higher this value, the less likely the model will talk about a new topic. Default: 0.0
     - `system_message_prompt_template` (Dict[str,Any]): The template of the system message. It is used to generate the system message.
-    By default its of type flows.prompt_template.JinjaPrompt.
+    By default its of type aiflows.prompt_template.JinjaPrompt.
     None of the parameters of the prompt are defined by default and therefore need to be defined if one wants to use the system prompt. 
-    Default parameters are defined in flows.prompt_template.jinja2_prompts.JinjaPrompt.
+    Default parameters are defined in aiflows.prompt_template.jinja2_prompts.JinjaPrompt.
     - `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. None of the parameters of the prompt are defined by default and therefore need to be defined if one
-    wants to use the init_human_message_prompt_template. Default parameters are defined in flows.prompt_template.jinja2_prompts.JinjaPrompt.
+    By default its of type aiflows.prompt_template.JinjaPrompt. None of the parameters of the prompt are defined by default and therefore need to be defined if one
+    wants to use the init_human_message_prompt_template. Default parameters are defined in aiflows.prompt_template.jinja2_prompts.JinjaPrompt.
     - `previous_messages` (Dict[str,Any]): Defines which previous messages to include in the input of the LLM. Note that if `first_k`and `last_k` are both none,
     all the messages of the flows's history are added to the input of the LLM. Default:
         - `first_k` (int): If defined, adds the first_k earliest messages of the flow's chat history to the input of the LLM. Default: None

VisionAtomicFlow.yaml

@@ -11,7 +11,7 @@ user_name: user
 assistant_name: assistant
 
 backend:
-  _target_: flows.backends.llm_lite.LiteLLMBackend
+  _target_: aiflows.backends.llm_lite.LiteLLMBackend
   api_infos: ???
   model_name: "gpt-4-vision-preview"
   n: 1
@@ -22,13 +22,13 @@ backend:
   presence_penalty: 0
 
 system_message_prompt_template:
-  _target_: flows.prompt_template.JinjaPrompt
+  _target_: aiflows.prompt_template.JinjaPrompt
 
 init_human_message_prompt_template:
-  _target_: flows.prompt_template.JinjaPrompt
+  _target_: aiflows.prompt_template.JinjaPrompt
 
 human_message_prompt_template:
-  _target_: flows.prompt_template.JinjaPrompt
+  _target_: aiflows.prompt_template.JinjaPrompt
   template: "{{query}}"
   input_variables:
     - "query"

__init__.py

@@ -2,6 +2,6 @@
 dependencies = [
     {"url": "aiflows/ChatFlowModule", "revision": "main"}
 ]
-from flows import flow_verse
+from aiflows import flow_verse
 flow_verse.sync_dependencies(dependencies)
 from .VisionAtomicFlow import VisionAtomicFlow

demo.yaml

@@ -1,5 +1,5 @@
 flow:
-  _target_: aiflows.VisionFlowModule.VisionAtomicFlow.instantiate_from_default_config
+  _target_: flow_modules.aiflows.VisionFlowModule.VisionAtomicFlow.instantiate_from_default_config
   name: "Demo Vision Flow"
   description: "A flow that, given a textual input, and a set of images and/or videos, generates a textual output."
   backend:

run.py

@@ -2,19 +2,19 @@ import os
 
 import hydra
 
-from flows.flow_launchers import FlowLauncher
-from flows.backends.api_info import ApiInfo
-from flows.utils.general_helpers import read_yaml_file
+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
 
 logging.set_verbosity_debug()  # Uncomment this line to see verbose logs
 
-from flows import flow_verse
+from aiflows import flow_verse
 
 dependencies = [
     {"url": "aiflows/VisionFlowModule", "revision": os.getcwd()},