update

.env

@@ -0,0 +1,2 @@
+DEEP_SEEK_API_KEY=
+DEBUG=False

.gitignore

@@ -9,3 +9,4 @@ wheels/
 # venv
 .venv
 .idea
+.env.local

app.py

@@ -2,13 +2,14 @@ import gradio as gr
 from langchain_openai import ChatOpenAI
 from langchain_core.messages import HumanMessage, AIMessage
 from llm import DeepSeekLLM
+from config import settings
 
-api_key = "sk-cd4f2925207a4d78bf6656d952ed46f3"
-deep_seek_llm = DeepSeekLLM(api_key=api_key)
-chat = ChatOpenAI(model="deepseek-chat", api_key=deep_seek_llm.api_key, base_url=deep_seek_llm.base_url)
+deep_seek_llm = DeepSeekLLM(api_key=settings.deep_seek_api_key)
+chat = ChatOpenAI(model=deep_seek_llm.default_model, api_key=deep_seek_llm.api_key, base_url=deep_seek_llm.base_url)
 
 
-def predict(message, history):
+def predict(message, history, model: str, temperature: float, max_tokens: int):
+    print('???model', model, temperature, max_tokens)
     history_messages = []
     for human, assistant in history:
         history_messages.append(HumanMessage(content=human))
@@ -21,38 +22,37 @@ def predict(message, history):
         yield response_message
 
 
-css = """
-.container {
-    # min-height: calc(100vh - 300px);
-}
-"""
-
-with gr.Blocks(css=css) as app:
-    with gr.Tab('Chat'):
+with gr.Blocks() as app:
+    with gr.Tab('聊天'):
         with gr.Row():
             with gr.Column(scale=2, min_width=600):
-                gr.ChatInterface(
+                chatbot = gr.ChatInterface(
                     predict,
                     multimodal=True,
                     chatbot=gr.Chatbot(elem_id="chatbot", height=600),
                     textbox=gr.MultimodalTextbox(),
-                )
-            with gr.Column(scale=1, min_width=300):
-                with gr.Accordion('Select Model', open=True):
-                    with gr.Column():
-                        gr.Dropdown(
-                            choices=deep_seek_llm.support_models,
-                            type="value",
-                            label="Model",
-                            key="model",
-                        )
+                    additional_inputs=[
+                        gr.Dropdown(choices=deep_seek_llm.support_models, label='模型'),
                         gr.Slider(
                             minimum=0.0,
                             maximum=1.0,
                             step=0.1,
                             label="Temperature",
                             key="temperature",
+                        ),
+                        gr.Number(
+                            minimum=1024,
+                            maximum=1024 * 20,
+                            step=128,
+                            value=4096,
+                            label="Max Tokens",
+                            key="max_tokens",
                         )
+                    ],
+                )
+            with gr.Column(scale=1, min_width=300):
+                with gr.Accordion('Select Model', open=True):
+                    with gr.Column():
                         gr.Number(
                             minimum=1024,
                             maximum=1024 * 20,
@@ -62,7 +62,7 @@ with gr.Blocks(css=css) as app:
                             key="max_tokens",
                         )
 
-    with gr.Tab('Text to Image'):
+    with gr.Tab('画图'):
         with gr.Row():
             with gr.Column(scale=2, min_width=600):
                 gr.Image(label="Input Image")
@@ -70,4 +70,4 @@ with gr.Blocks(css=css) as app:
                 gr.Textbox(label="LoRA")
 
 
-app.launch(debug=True)
+app.launch(debug=settings.debug)

config.py

@@ -1,17 +1,12 @@
-from typing import Any, Callable, Set
-
-from pydantic import (
-    AliasChoices,
-    AmqpDsn,
-    BaseModel,
-    Field,
-    ImportString,
-    PostgresDsn,
-    RedisDsn,
-)
-
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 
 class Settings(BaseSettings):
-    model_config = SettingsConfigDict(env_file='.env', env_file_encoding='utf-8')
+    deep_seek_api_key: str
+    debug: bool
+
+    model_config = SettingsConfigDict(env_file=('.env', '.env.local'), env_file_encoding='utf-8')
+
+
+settings = Settings()
+