Set-up basic gradio template.

.gitignore

@@ -7,4 +7,8 @@ wheels/
 *.egg-info
 
 # Virtual environments
-.venv
+.venv
+
+# application files
+.gradio
+*.log

app.py

@@ -0,0 +1,54 @@
+from typing import Any
+
+import gradio as gr
+import structlog
+
+import logging_config as _
+
+# Create a logger instance
+logger = structlog.get_logger(__name__)
+
+with open("static/style.css", "r") as f:
+    css = f.read()
+    logger.info("Successfully loaded styles.")
+
+
+def bot(message, history) -> list[Any]:
+    """Generate bot response and history from message.
+    
+    With multi-modal inputs text and each file is treated as separate message.
+    """
+    logger.info("This is the history", history=history)
+    
+    # enable message edit
+    if isinstance(message, str):
+        message = {"text": message}
+    
+    # create text response
+    response = []
+    response.append("You wrote: '" + message.get("text") + "' and uploaded:")
+    
+    # display files (exemplary)
+    if message.get("files"):
+        for file in message.get("files"):
+            response.append(gr.File(value=file))
+
+    logger.info(response=response)
+    return response
+
+
+demo = gr.ChatInterface(
+    bot,
+    type="messages",
+    flagging_mode="manual",
+    editable=True, 
+    flagging_options=["Like", "Dislike", "Spam", "Inappropriate", "Other"],
+    multimodal=True,
+    textbox=gr.MultimodalTextbox(file_count="multiple"),
+    title="DEval Prototype 1",
+    description="I am a playground to test Citation and the Basic set-up.",
+    css=css
+)
+
+if __name__ == "__main__":
+    demo.launch(share=False, server_name="0.0.0.0")

config.py

@@ -0,0 +1,45 @@
+from pydantic_settings import (
+    BaseSettings,
+    PydanticBaseSettingsSource,
+    SettingsConfigDict,
+    PyprojectTomlConfigSettingsSource,
+)
+from typing import Tuple, Type
+
+
+class Settings(BaseSettings):
+    @classmethod
+    def settings_customise_sources(
+        cls,
+        settings_cls: Type[BaseSettings],
+        init_settings: PydanticBaseSettingsSource,
+        env_settings: PydanticBaseSettingsSource,
+        dotenv_settings: PydanticBaseSettingsSource,
+        file_secret_settings: PydanticBaseSettingsSource,
+    ) -> Tuple[PydanticBaseSettingsSource, ...]:
+        return (
+            init_settings,
+            PyprojectTomlConfigSettingsSource(settings_cls),
+            env_settings,
+            dotenv_settings,
+            file_secret_settings,
+        )
+
+
+class AppSettings(Settings):
+    # backend
+    llm_model: str
+    embedding_url: str
+    embedding_model: str
+    vector_db_url: str
+    vector_db_collection_name: str
+
+    # secrets
+    llm_api_key: str
+
+    model_config = SettingsConfigDict(
+        pyproject_toml_table_header=("tool", "app_config"),
+        env_file=".env",
+        env_file_encoding="utf-8",
+        extra="ignore",
+    )

main.py

@@ -1,6 +0,0 @@
-def main():
-    print("Hello from deval-ai4kontextanalysen!")
-
-
-if __name__ == "__main__":
-    main()

pyproject.toml

@@ -4,4 +4,18 @@ version = "0.1.0"
 description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.13"
-dependencies = []
+dependencies = [
+    "gradio>=5.33.0",
+    "pydantic>=2.11.5",
+    "pydantic-settings>=2.9.1",
+    "structlog>=25.4.0",
+]
+
+
+[tool.app_config]
+# shared
+llm_model = "gpt-4o"
+embedding_model = "BAAI/bge-m3"
+embedding_url = "http://tei:80"
+vector_db_url = ":memory:"
+vector_db_collection_name = "bgem3_store_multilingual"

static/style.css

@@ -0,0 +1 @@
+footer { display: none !important; }