From a5d671904d4deebf147adc2b728bdc5b36627144 Mon Sep 17 00:00:00 2001
From: frdel <38891707+frdel@users.noreply.github.com>
Date: Sun, 27 Oct 2024 18:04:40 +0100
Subject: [PATCH 001/102] Settings prototype
Settings modal window managed from python - work in progress
---
initialize.py | 15 +-
models.py | 244 ++++++++++++++++++++++++------
python/helpers/settings.py | 273 ++++++++++++++++++++++++++++++++++
python/helpers/whisper_oai.py | 13 ++
run_ui.py | 47 +++++-
webui/index.html | 114 ++++++++++++++
webui/index.js | 2 +-
webui/settings.css | 231 ++++++++++++++++++++++++++++
webui/settings.js | 87 +++++++++++
9 files changed, 976 insertions(+), 50 deletions(-)
create mode 100644 python/helpers/settings.py
create mode 100644 python/helpers/whisper_oai.py
create mode 100644 webui/settings.css
create mode 100644 webui/settings.js
diff --git a/initialize.py b/initialize.py
index b741eae90..9c7103f00 100644
--- a/initialize.py
+++ b/initialize.py
@@ -1,11 +1,11 @@
import models
from agent import AgentConfig
-from python.helpers import files
+from python.helpers import files, settings
def initialize():
# main chat model used by agents (smarter, more accurate)
- chat_llm = models.get_openai_chat(model_name="gpt-4o-mini", temperature=0)
+ # chat_llm = models.get_openai_chat(model_name="gpt-4o-mini", temperature=0)
# chat_llm = models.get_ollama_chat(model_name="llama3.2:3b-instruct-fp16", temperature=0)
# chat_llm = models.get_lmstudio_chat(model_name="lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF", temperature=0)
# chat_llm = models.get_openrouter_chat(model_name="openai/o1-mini-2024-09-12")
@@ -15,22 +15,25 @@ def initialize():
# chat_llm = models.get_mistral_chat(model_name="mistral-small-latest", temperature=0)
# chat_llm = models.get_groq_chat(model_name="llama-3.2-90b-text-preview", temperature=0)
# chat_llm = models.get_sambanova_chat(model_name="Meta-Llama-3.1-70B-Instruct-8k", temperature=0)
+ chat_llm = settings.get_chat_model() # chat model from user settings
# utility model used for helper functions (cheaper, faster)
- utility_llm = chat_llm
+ # utility_llm = chat_llm
+ utility_llm = settings.get_utility_model() # utility model from user settings
# embedding model used for memory
- embedding_llm = models.get_openai_embedding(model_name="text-embedding-3-small")
+ # embedding_llm = models.get_openai_embedding(model_name="text-embedding-3-small")
# embedding_llm = models.get_ollama_embedding(model_name="nomic-embed-text")
# embedding_llm = models.get_huggingface_embedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
# embedding_llm = models.get_lmstudio_embedding(model_name="nomic-ai/nomic-embed-text-v1.5-GGUF")
-
+ embedding_llm = settings.get_embedding_model() # embedding model from user settings
+
# agent configuration
config = AgentConfig(
chat_model = chat_llm,
utility_model = utility_llm,
embeddings_model = embedding_llm,
- # prompts_subdir = "default",
+ prompts_subdir = "dianoia-xl",
# memory_subdir = "",
knowledge_subdirs = ["default","custom"],
auto_memory_count = 0,
diff --git a/models.py b/models.py
index fa7c8d032..8f773f94e 100644
--- a/models.py
+++ b/models.py
@@ -1,5 +1,13 @@
+from enum import Enum
import os
-from langchain_openai import ChatOpenAI, OpenAI, OpenAIEmbeddings, AzureChatOpenAI, AzureOpenAIEmbeddings, AzureOpenAI
+from langchain_openai import (
+ ChatOpenAI,
+ OpenAI,
+ OpenAIEmbeddings,
+ AzureChatOpenAI,
+ AzureOpenAIEmbeddings,
+ AzureOpenAI,
+)
from langchain_community.llms.ollama import Ollama
from langchain_ollama import ChatOllama
from langchain_community.embeddings import OllamaEmbeddings
@@ -17,74 +25,226 @@ load_dotenv()
# Configuration
DEFAULT_TEMPERATURE = 0.0
+
+class ModelType(Enum):
+ CHAT = "Chat"
+ EMBEDDING = "Embedding"
+
+
+class ModelProvider(Enum):
+ ANTHROPIC = "Anthropic"
+ HUGGINGFACE = "HuggingFace"
+ GOOGLE = "Google"
+ GROQ = "Groq"
+ LMSTUDIO = "LM Studio"
+ MISTRALAI = "Mistral AI"
+ OLLAMA = "Ollama"
+ OPENAI = "OpenAI"
+ OPENAI_AZURE = "OpenAI Azure"
+ OPENROUTER = "OpenRouter"
+ SAMBANOVA = "Sambanova"
+
+
# Utility function to get API keys from environment variables
def get_api_key(service):
- return os.getenv(f"API_KEY_{service.upper()}") or os.getenv(f"{service.upper()}_API_KEY")
+ return os.getenv(f"API_KEY_{service.upper()}") or os.getenv(
+ f"{service.upper()}_API_KEY"
+ )
+
+
+def get_model(type: ModelType, provider: ModelProvider, name: str, **kwargs):
+ fnc_name = f"get_{provider.name.lower()}_{type.name.lower()}" # function name of model getter
+ model = globals()[fnc_name](name, **kwargs) # call function by name
+ return model
# Ollama models
-def get_ollama_chat(model_name:str, temperature=DEFAULT_TEMPERATURE, base_url=os.getenv("OLLAMA_BASE_URL") or "http://127.0.0.1:11434", num_ctx=8192):
- return ChatOllama(model=model_name,temperature=temperature, base_url=base_url, num_ctx=num_ctx)
+def get_ollama_chat(
+ model_name: str,
+ temperature=DEFAULT_TEMPERATURE,
+ base_url=os.getenv("OLLAMA_BASE_URL") or "http://127.0.0.1:11434",
+ num_ctx=8192,
+ **kwargs,
+):
+ return ChatOllama(
+ model=model_name,
+ temperature=temperature,
+ base_url=base_url,
+ num_ctx=num_ctx,
+ **kwargs,
+ )
+
+
+def get_ollama_embedding(
+ model_name: str,
+ temperature=DEFAULT_TEMPERATURE,
+ base_url=os.getenv("OLLAMA_BASE_URL") or "http://127.0.0.1:11434",
+ **kwargs,
+):
+ return OllamaEmbeddings(
+ model=model_name, temperature=temperature, base_url=base_url, **kwargs
+ )
-def get_ollama_embedding(model_name:str, temperature=DEFAULT_TEMPERATURE, base_url=os.getenv("OLLAMA_BASE_URL") or "http://127.0.0.1:11434"):
-
- return OllamaEmbeddings(model=model_name,temperature=temperature, base_url=base_url)
# HuggingFace models
-def get_huggingface_embedding(model_name:str):
- return HuggingFaceEmbeddings(model_name=model_name)
+
+def get_huggingface_embedding(model_name: str, **kwargs):
+ return HuggingFaceEmbeddings(model_name=model_name, **kwargs)
+
# LM Studio and other OpenAI compatible interfaces
-def get_lmstudio_chat(model_name:str, temperature=DEFAULT_TEMPERATURE, base_url=os.getenv("LM_STUDIO_BASE_URL") or "http://127.0.0.1:1234/v1"):
- return ChatOpenAI(model_name=model_name, base_url=base_url, temperature=temperature, api_key="none") # type: ignore
+def get_lmstudio_chat(
+ model_name: str,
+ temperature=DEFAULT_TEMPERATURE,
+ base_url=os.getenv("LM_STUDIO_BASE_URL") or "http://127.0.0.1:1234/v1",
+ **kwargs,
+):
+ return ChatOpenAI(model_name=model_name, base_url=base_url, temperature=temperature, api_key="none", **kwargs) # type: ignore
+
+
+def get_lmstudio_embedding(
+ model_name: str,
+ base_url=os.getenv("LM_STUDIO_BASE_URL") or "http://127.0.0.1:1234/v1",
+ **kwargs,
+):
+ return OpenAIEmbeddings(model=model_name, api_key="none", base_url=base_url, check_embedding_ctx_length=False, **kwargs) # type: ignore
-def get_lmstudio_embedding(model_name:str, base_url=os.getenv("LM_STUDIO_BASE_URL") or "http://127.0.0.1:1234/v1"):
- return OpenAIEmbeddings(model=model_name, api_key="none", base_url=base_url, check_embedding_ctx_length=False) # type: ignore
# Anthropic models
-def get_anthropic_chat(model_name:str, api_key=get_api_key("anthropic"), temperature=DEFAULT_TEMPERATURE):
- return ChatAnthropic(model_name=model_name, temperature=temperature, api_key=api_key) # type: ignore
+def get_anthropic_chat(
+ model_name: str,
+ api_key=get_api_key("anthropic"),
+ temperature=DEFAULT_TEMPERATURE,
+ **kwargs,
+):
+ return ChatAnthropic(model_name=model_name, temperature=temperature, api_key=api_key, **kwargs) # type: ignore
+
# OpenAI models
-def get_openai_chat(model_name:str, api_key=get_api_key("openai"), temperature=DEFAULT_TEMPERATURE):
- return ChatOpenAI(model_name=model_name, temperature=temperature, api_key=api_key) # type: ignore
+def get_openai_chat(
+ model_name: str,
+ api_key=get_api_key("openai"),
+ temperature=DEFAULT_TEMPERATURE,
+ **kwargs,
+):
+ return ChatOpenAI(model_name=model_name, temperature=temperature, api_key=api_key, **kwargs) # type: ignore
-def get_openai_instruct(model_name:str, api_key=get_api_key("openai"), temperature=DEFAULT_TEMPERATURE):
- return OpenAI(model=model_name, temperature=temperature, api_key=api_key) # type: ignore
-def get_openai_embedding(model_name:str, api_key=get_api_key("openai")):
- return OpenAIEmbeddings(model=model_name, api_key=api_key) # type: ignore
+def get_openai_instruct(
+ model_name: str,
+ api_key=get_api_key("openai"),
+ temperature=DEFAULT_TEMPERATURE,
+ **kwargs,
+):
+ return OpenAI(model=model_name, temperature=temperature, api_key=api_key, **kwargs) # type: ignore
-def get_azure_openai_chat(deployment_name:str, api_key=get_api_key("openai_azure"), temperature=DEFAULT_TEMPERATURE, azure_endpoint=os.getenv("OPENAI_AZURE_ENDPOINT")):
- return AzureChatOpenAI(deployment_name=deployment_name, temperature=temperature, api_key=api_key, azure_endpoint=azure_endpoint) # type: ignore
-def get_azure_openai_instruct(deployment_name:str, api_key=get_api_key("openai_azure"), temperature=DEFAULT_TEMPERATURE, azure_endpoint=os.getenv("OPENAI_AZURE_ENDPOINT")):
- return AzureOpenAI(deployment_name=deployment_name, temperature=temperature, api_key=api_key, azure_endpoint=azure_endpoint) # type: ignore
+def get_openai_embedding(model_name: str, api_key=get_api_key("openai"), **kwargs):
+ return OpenAIEmbeddings(model=model_name, api_key=api_key, **kwargs) # type: ignore
+
+
+def get_azure_openai_chat(
+ deployment_name: str,
+ api_key=get_api_key("openai_azure"),
+ temperature=DEFAULT_TEMPERATURE,
+ azure_endpoint=os.getenv("OPENAI_AZURE_ENDPOINT"),
+ **kwargs,
+):
+ return AzureChatOpenAI(deployment_name=deployment_name, temperature=temperature, api_key=api_key, azure_endpoint=azure_endpoint, **kwargs) # type: ignore
+
+
+def get_azure_openai_instruct(
+ deployment_name: str,
+ api_key=get_api_key("openai_azure"),
+ temperature=DEFAULT_TEMPERATURE,
+ azure_endpoint=os.getenv("OPENAI_AZURE_ENDPOINT"),
+ **kwargs,
+):
+ return AzureOpenAI(deployment_name=deployment_name, temperature=temperature, api_key=api_key, azure_endpoint=azure_endpoint, **kwargs) # type: ignore
+
+
+def get_azure_openai_embedding(
+ deployment_name: str,
+ api_key=get_api_key("openai_azure"),
+ azure_endpoint=os.getenv("OPENAI_AZURE_ENDPOINT"),
+ **kwargs,
+):
+ return AzureOpenAIEmbeddings(deployment_name=deployment_name, api_key=api_key, azure_endpoint=azure_endpoint, **kwargs) # type: ignore
-def get_azure_openai_embedding(deployment_name:str, api_key=get_api_key("openai_azure"), azure_endpoint=os.getenv("OPENAI_AZURE_ENDPOINT")):
- return AzureOpenAIEmbeddings(deployment_name=deployment_name, api_key=api_key, azure_endpoint=azure_endpoint) # type: ignore
# Google models
-def get_google_chat(model_name:str, api_key=get_api_key("google"), temperature=DEFAULT_TEMPERATURE):
- return GoogleGenerativeAI(model=model_name, temperature=temperature, google_api_key=api_key, safety_settings={HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE }) # type: ignore
+def get_google_chat(
+ model_name: str,
+ api_key=get_api_key("google"),
+ temperature=DEFAULT_TEMPERATURE,
+ **kwargs,
+):
+ return GoogleGenerativeAI(model=model_name, temperature=temperature, google_api_key=api_key, safety_settings={HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE}, **kwargs) # type: ignore
+
# Mistral models
-def get_mistral_chat(model_name:str, api_key=get_api_key("mistral"), temperature=DEFAULT_TEMPERATURE):
- return ChatMistralAI(model=model_name, temperature=temperature, api_key=api_key) # type: ignore
+def get_mistral_chat(
+ model_name: str,
+ api_key=get_api_key("mistral"),
+ temperature=DEFAULT_TEMPERATURE,
+ **kwargs,
+):
+ return ChatMistralAI(model=model_name, temperature=temperature, api_key=api_key, **kwargs) # type: ignore
+
# Groq models
-def get_groq_chat(model_name:str, api_key=get_api_key("groq"), temperature=DEFAULT_TEMPERATURE):
- return ChatGroq(model_name=model_name, temperature=temperature, api_key=api_key) # type: ignore
-
+def get_groq_chat(
+ model_name: str,
+ api_key=get_api_key("groq"),
+ temperature=DEFAULT_TEMPERATURE,
+ **kwargs,
+):
+ return ChatGroq(model_name=model_name, temperature=temperature, api_key=api_key, **kwargs) # type: ignore
+
+
# OpenRouter models
-def get_openrouter_chat(model_name: str, api_key=get_api_key("openrouter"), temperature=DEFAULT_TEMPERATURE, base_url=os.getenv("OPEN_ROUTER_BASE_URL") or "https://openrouter.ai/api/v1"):
- return ChatOpenAI(api_key=api_key, model=model_name, temperature=temperature, base_url=base_url) # type: ignore
-
-def get_openrouter_embedding(model_name: str, api_key=get_api_key("openrouter"), base_url=os.getenv("OPEN_ROUTER_BASE_URL") or "https://openrouter.ai/api/v1"):
- return OpenAIEmbeddings(model=model_name, api_key=api_key, base_url=base_url) # type: ignore
+def get_openrouter_chat(
+ model_name: str,
+ api_key=get_api_key("openrouter"),
+ temperature=DEFAULT_TEMPERATURE,
+ base_url=os.getenv("OPEN_ROUTER_BASE_URL") or "https://openrouter.ai/api/v1",
+ **kwargs,
+):
+ return ChatOpenAI(api_key=api_key, model=model_name, temperature=temperature, base_url=base_url, **kwargs) # type: ignore
+
+
+def get_openrouter_embedding(
+ model_name: str,
+ api_key=get_api_key("openrouter"),
+ base_url=os.getenv("OPEN_ROUTER_BASE_URL") or "https://openrouter.ai/api/v1",
+ **kwargs,
+):
+ return OpenAIEmbeddings(model=model_name, api_key=api_key, base_url=base_url, **kwargs) # type: ignore
+
# Sambanova models
-def get_sambanova_chat(model_name: str, api_key=get_api_key("sambanova"), temperature=DEFAULT_TEMPERATURE, base_url=os.getenv("SAMBANOVA_BASE_URL") or "https://fast-api.snova.ai/v1", max_tokens=1024):
- return ChatOpenAI(api_key=api_key, model=model_name, temperature=temperature, base_url=base_url, max_tokens=max_tokens) # type: ignore
-
+def get_sambanova_chat(
+ model_name: str,
+ api_key=get_api_key("sambanova"),
+ temperature=DEFAULT_TEMPERATURE,
+ base_url=os.getenv("SAMBANOVA_BASE_URL") or "https://fast-api.snova.ai/v1",
+ max_tokens=1024,
+ **kwargs,
+):
+ return ChatOpenAI(api_key=api_key, model=model_name, temperature=temperature, base_url=base_url, max_tokens=max_tokens, **kwargs) # type: ignore
+
+
+# Other OpenAI compatible models
+def get_other_chat(
+ model_name: str,
+ api_key=None,
+ temperature=DEFAULT_TEMPERATURE,
+ base_url=None,
+ **kwargs,
+):
+ return ChatOpenAI(api_key=api_key, model=model_name, temperature=temperature, base_url=base_url, **kwargs) # type: ignore
+
+
+def get_other_embedding(model_name: str, api_key=None, base_url=None, **kwargs):
+ return OpenAIEmbeddings(model=model_name, api_key=api_key, base_url=base_url, **kwargs) # type: ignore
diff --git a/python/helpers/settings.py b/python/helpers/settings.py
new file mode 100644
index 000000000..dc8dc80eb
--- /dev/null
+++ b/python/helpers/settings.py
@@ -0,0 +1,273 @@
+import json
+import os
+import re
+from typing import Any, Optional, TypedDict
+from . import files
+from models import get_model, ModelProvider, ModelType
+from langchain_core.language_models.chat_models import BaseChatModel
+from langchain_core.embeddings import Embeddings
+
+class Settings(TypedDict):
+ chat_model_provider: str
+ chat_model_name: str
+ chat_model_temperature: float
+ chat_model_kwargs: dict[str, str]
+
+ util_model_provider: str
+ util_model_name: str
+ util_model_temperature: float
+ util_model_kwargs: dict[str, str]
+
+ embed_model_provider: str
+ embed_model_name: str
+ embed_model_temperature: float
+ embed_model_kwargs: dict[str, str]
+
+
+class PartialSettings(Settings, total=False):
+ pass
+
+
+SETTINGS_FILE = files.get_abs_path("tmp/settings.json")
+_settings: Settings | None = None
+
+
+def convert_out(settings: Settings) -> dict[str, Any]:
+
+ # main model section
+ chat_model_fields = []
+ chat_model_fields.append(
+ {
+ "id": "chat_model_provider",
+ "title": "Chat model provider",
+ "description": "Select provider for main chat model used by Agent Zero",
+ "type": "select",
+ "value": settings["chat_model_provider"],
+ "options": [{"value": p.name, "label": p.value} for p in ModelProvider],
+ }
+ )
+ chat_model_fields.append(
+ {
+ "id": "chat_model_name",
+ "title": "Chat model name",
+ "description": "Exact name of model from selected provider",
+ "type": "input",
+ "value": settings["chat_model_name"],
+ }
+ )
+
+ chat_model_fields.append(
+ {
+ "id": "chat_model_temperature",
+ "title": "Chat model temperature",
+ "description": "Determines the randomness of generated responses. 0 is deterministic, 1 is random",
+ "type": "range",
+ "min": 0,
+ "max": 1,
+ "step": 0.01,
+ "value": settings["chat_model_temperature"],
+ }
+ )
+
+ chat_model_fields.append(
+ {
+ "id": "chat_model_kwargs",
+ "title": "Chat model additional parameters",
+ "description": "Any other parameters supported by the model. Format is KEY=VALUE on individual lines, just like .env file.",
+ "type": "textarea",
+ "value": _dict_to_env(settings["chat_model_kwargs"]),
+ }
+ )
+
+ chat_model_seciton = {
+ "title": "Chat Model",
+ "description": "Selection and settings for main chat model used by Agent Zero",
+ "fields": chat_model_fields,
+ }
+
+ # main model section
+ util_model_fields = []
+ util_model_fields.append(
+ {
+ "id": "util_model_provider",
+ "title": "Utility model provider",
+ "description": "Select provider for utility model used by the framework",
+ "type": "select",
+ "value": settings["util_model_provider"],
+ "options": [{"value": p.name, "label": p.value} for p in ModelProvider],
+ }
+ )
+ util_model_fields.append(
+ {
+ "id": "util_model_name",
+ "title": "Utility model name",
+ "description": "Exact name of model from selected provider",
+ "type": "input",
+ "value": settings["util_model_name"],
+ }
+ )
+
+ util_model_fields.append(
+ {
+ "id": "util_model_temperature",
+ "title": "Utility model temperature",
+ "description": "Determines the randomness of generated responses. 0 is deterministic, 1 is random",
+ "type": "range",
+ "min": 0,
+ "max": 1,
+ "step": 0.01,
+ "value": settings["util_model_temperature"],
+ }
+ )
+
+ util_model_fields.append(
+ {
+ "id": "util_model_kwargs",
+ "title": "Utility model additional parameters",
+ "description": "Any other parameters supported by the model. Format is KEY=VALUE on individual lines, just like .env file.",
+ "type": "textarea",
+ "value": _dict_to_env(settings["util_model_kwargs"]),
+ }
+ )
+
+ util_model_seciton = {
+ "title": "Utility model",
+ "description": "Smaller, cheaper, faster model for handling utility tasks like organizing memory, preparing prompts, summarizing.",
+ "fields": util_model_fields,
+ }
+
+ result = {"sections": [chat_model_seciton, util_model_seciton]}
+ return result
+
+def convert_in(settings: dict[str, Any]) -> Settings:
+ current = get_settings()
+ for section in settings["sections"]:
+ for field in section["fields"]:
+ if field["id"].endswith("_kwargs"):
+ current[field["id"]] = _env_to_dict(field["value"]) #parse KWARGS from env format
+ else:
+ current[field["id"]] = field["value"]
+ return current
+
+
+def get_settings() -> Settings:
+ global _settings
+ if not _settings:
+ _settings = _read_settings_file()
+ if not _settings:
+ _settings = _get_default_settings()
+ return _settings.copy()
+
+
+def set_settings(settings: Settings):
+ global _settings
+ _settings = normalize_settings(settings)
+ _apply_settings()
+ _write_settings_file(_settings)
+
+
+def normalize_settings(settings: Settings) -> Settings:
+ copy = settings.copy()
+ default = _get_default_settings()
+ for key, value in default.items():
+ if key not in copy:
+ copy[key] = value
+ return copy
+
+
+def get_chat_model() -> BaseChatModel:
+ settings = get_settings()
+ return get_model(
+ type=ModelType.CHAT,
+ provider=ModelProvider[settings["chat_model_provider"]],
+ name=settings["chat_model_name"],
+ temperature=settings["chat_model_temperature"],
+ **settings["chat_model_kwargs"],
+ )
+
+
+def get_utility_model() -> BaseChatModel:
+ settings = get_settings()
+ return get_model(
+ type=ModelType.CHAT,
+ provider=ModelProvider[settings["util_model_provider"]],
+ name=settings["util_model_name"],
+ temperature=settings["util_model_temperature"],
+ **settings["util_model_kwargs"],
+ )
+
+
+def get_embedding_model() -> Embeddings:
+ settings = get_settings()
+ return get_model(
+ type=ModelType.EMBEDDING,
+ provider=ModelProvider[settings["embed_model_provider"]],
+ name=settings["embed_model_name"],
+ temperature=settings["embed_model_temperature"],
+ **settings["embed_model_kwargs"],
+ )
+
+
+def _read_settings_file() -> Settings | None:
+ if os.path.exists(SETTINGS_FILE):
+ content = files.read_file(SETTINGS_FILE)
+ parsed = json.loads(content)
+ return normalize_settings(parsed)
+
+
+def _write_settings_file(settings: Settings):
+ content = json.dumps(settings, indent=4)
+ files.write_file(SETTINGS_FILE, content)
+
+
+def _get_default_settings() -> Settings:
+ return Settings(
+ chat_model_provider=ModelProvider.OPENAI.name,
+ chat_model_name="gpt-4o-mini",
+ chat_model_temperature=0,
+ chat_model_kwargs={},
+ util_model_provider=ModelProvider.OPENAI.name,
+ util_model_name="gpt-4o-mini",
+ util_model_temperature=0,
+ util_model_kwargs={},
+ embed_model_provider=ModelProvider.OPENAI.name,
+ embed_model_name="text-embedding-3-small",
+ embed_model_temperature=0,
+ embed_model_kwargs={},
+ )
+
+def _apply_settings():
+ global _settings
+ if _settings:
+ from agent import AgentContext
+ from initialize import initialize
+
+ for ctx in AgentContext._contexts.values():
+ ctx.config = initialize() # reinitialize context config with new settings
+ #apply config to agents
+ agent = ctx.agent0
+ while agent:
+ agent.config = ctx.config
+ agent = agent.get_data("subordinate")
+
+def _env_to_dict(data:str):
+ env_dict = {}
+ line_pattern = re.compile(r'\s*([^#][^=]*)\s*=\s*(.*)')
+ for line in data.splitlines():
+ match = line_pattern.match(line)
+ if match:
+ key, value = match.groups()
+ # Remove optional surrounding quotes (single or double)
+ value = value.strip().strip('"').strip("'")
+ env_dict[key.strip()] = value
+ return env_dict
+
+def _dict_to_env(data_dict):
+ lines = []
+ for key, value in data_dict.items():
+ if '\n' in value:
+ value = f"'{value}'"
+ elif ' ' in value or value == '' or any(c in value for c in '"\''):
+ value = f'"{value}"'
+ lines.append(f"{key}={value}")
+ return "\n".join(lines)
\ No newline at end of file
diff --git a/python/helpers/whisper_oai.py b/python/helpers/whisper_oai.py
new file mode 100644
index 000000000..3c79f11c0
--- /dev/null
+++ b/python/helpers/whisper_oai.py
@@ -0,0 +1,13 @@
+# Import the necessary libraries
+import whisper
+import files
+
+# Load the base model from Whisper
+model = whisper.load_model("base")
+
+# Add your Audio File
+audio = files.get_abs_path("audio.ogg")
+
+# Transcribe the audio file
+result = model.transcribe(audio, fp16=False)
+print(result["text"])
\ No newline at end of file
diff --git a/run_ui.py b/run_ui.py
index a03eab9c5..713084068 100644
--- a/run_ui.py
+++ b/run_ui.py
@@ -12,7 +12,7 @@ from python.helpers import files
from python.helpers.files import get_abs_path
from python.helpers.print_style import PrintStyle
from python.helpers.dotenv import load_dotenv
-from python.helpers import persist_chat
+from python.helpers import persist_chat, settings
# initialize the internal Flask server
@@ -348,6 +348,51 @@ async def poll():
# return jsonify(response)
+# get current settings
+@app.route("/getSettings", methods=["POST"])
+async def get_settings():
+ try:
+
+ # data sent to the server
+ input = request.get_json()
+
+ set = settings.convert_out(settings.get_settings())
+
+ response = {"ok": True, "settings": set}
+
+ except Exception as e:
+ response = {
+ "ok": False,
+ "message": str(e),
+ }
+ PrintStyle.error(str(e))
+
+ # respond with json
+ return jsonify(response)
+
+# set current settings
+@app.route("/setSettings", methods=["POST"])
+async def set_settings():
+ try:
+
+ # data sent to the server
+ input = request.get_json()
+
+ set = settings.convert_in(input)
+ set = settings.set_settings(set)
+
+ response = {"ok": True, "settings": set}
+
+ except Exception as e:
+ response = {
+ "ok": False,
+ "message": str(e),
+ }
+ PrintStyle.error(str(e))
+
+ # respond with json
+ return jsonify(response)
+
def run():
print("Initializing framework...")
diff --git a/webui/index.html b/webui/index.html
index a350afb57..3e0727d52 100644
--- a/webui/index.html
+++ b/webui/index.html
@@ -7,6 +7,7 @@
Agent Zero
+
+
@@ -47,6 +49,8 @@
+
+
+
+
+