Merge branch 'main' into debug-streaming-v2

chatbot_ui/.vscode/settings.json

@@ -1,3 +0,0 @@
-{
-  "python.defaultInterpreterPath": "${workspaceFolder}/venv/bin/python",
-}

chatbot_ui/app/run.py

@@ -1,8 +1,11 @@
 import json
 import os
-from openai import OpenAI, DefaultHttpxClient
-import gradio as gr
 import logging
+import yaml
+import gradio as gr
+
+from typing import List, Optional, Tuple
+from openai import OpenAI, DefaultHttpxClient
 from dotenv import load_dotenv
 
 load_dotenv()
@@ -15,9 +18,22 @@ logging.basicConfig(
 log = logging.getLogger(__name__)
 
 CHAT_COMPLETION_ENDPOINT = os.getenv("CHAT_COMPLETION_ENDPOINT")
-ARCH_STATE_HEADER = "x-arch-state"
 log.info(f"CHAT_COMPLETION_ENDPOINT: {CHAT_COMPLETION_ENDPOINT}")
 
+ARCH_STATE_HEADER = "x-arch-state"
+
+CSS_STYLE = """
+.json-container {
+    height: 95vh !important;
+    overflow-y: auto !important;
+}
+.chatbot {
+    height: calc(95vh - 100px) !important;
+    overflow-y: auto !important;
+}
+footer {visibility: hidden}
+"""
+
 client = OpenAI(
     api_key="--",
     base_url=CHAT_COMPLETION_ENDPOINT,
@@ -25,11 +41,56 @@ client = OpenAI(
 )
 
 
-def predict(message, state):
+def convert_prompt_target_to_openai_format(target):
+    tool = {
+        "description": target["description"],
+        "parameters": {"type": "object", "properties": {}, "required": []},
+    }
+
+    if "parameters" in target:
+        for param_info in target["parameters"]:
+            parameter = {
+                "type": param_info["type"],
+                "description": param_info["description"],
+            }
+
+            for key in ["default", "format", "enum", "items", "minimum", "maximum"]:
+                if key in param_info:
+                    parameter[key] = param_info[key]
+
+            tool["parameters"]["properties"][param_info["name"]] = parameter
+
+            required = param_info.get("required", False)
+            if required:
+                tool["parameters"]["required"].append(param_info["name"])
+
+    return {"name": target["name"], "info": tool}
+
+
+def get_prompt_targets():
+    try:
+        with open("arch_config.yaml", "r") as file:
+            config = yaml.safe_load(file)
+
+            available_tools = []
+            for target in config["prompt_targets"]:
+                if not target.get("default", False):
+                    available_tools.append(
+                        convert_prompt_target_to_openai_format(target)
+                    )
+
+            return {tool["name"]: tool["info"] for tool in available_tools}
+    except Exception as e:
+        log.info(e)
+        return None
+
+
+def chat(query: Optional[str], conversation: Optional[List[Tuple[str, str]]], state):
     if "history" not in state:
         state["history"] = []
+
     history = state.get("history")
-    history.append({"role": "user", "content": message})
+    history.append({"role": "user", "content": query})
     log.info(f"history: {history}")
 
     # Custom headers
@@ -58,7 +119,8 @@ def predict(message, state):
     # extract arch_state from metadata and store it in gradio session state
     # this state must be passed back to the gateway in the next request
     response_json = json.loads(raw_response.text)
-    if response_json:
+    log.info(response_json)
+    if response_json and "metadata" in response_json:
         # load arch_state from metadata
         arch_state_str = response_json.get("metadata", {}).get(ARCH_STATE_HEADER, "{}")
         # parse arch_state into json object
@@ -78,25 +140,53 @@ def predict(message, state):
     # for gradio UI we don't want to show raw tool calls and messages from developer application
     # so we're filtering those out
     history_view = [h for h in history if h["role"] != "tool" and "content" in h]
+
     messages = [
         (history_view[i]["content"], history_view[i + 1]["content"])
         for i in range(0, len(history_view) - 1, 2)
     ]
-    return messages, state
+
+    return "", messages, state
 
 
-with gr.Blocks(fill_height=True, css="footer {visibility: hidden}") as demo:
-    print("Starting Demo...")
-    chatbot = gr.Chatbot(label="Arch Chatbot", scale=1)
-    state = gr.State({})
-    with gr.Row():
-        txt = gr.Textbox(
-            show_label=False,
-            placeholder="Enter text and press enter",
-            scale=1,
-            autofocus=True,
-        )
+def main():
+    with gr.Blocks(
+        theme=gr.themes.Default(
+            font_mono=[gr.themes.GoogleFont("IBM Plex Mono"), "Arial", "sans-serif"]
+        ),
+        fill_height=True,
+        css=CSS_STYLE,
+    ) as demo:
+        with gr.Row(equal_height=True):
+            state = gr.State({})
 
-    txt.submit(predict, [txt, state], [chatbot, state])
+            with gr.Column(scale=4):
+                gr.JSON(
+                    value=get_prompt_targets(),
+                    open=True,
+                    show_indices=False,
+                    label="Available Tools",
+                    scale=1,
+                    min_height="95vh",
+                    elem_classes="json-container",
+                )
+            with gr.Column(scale=6):
+                chatbot = gr.Chatbot(
+                    label="Arch Chatbot",
+                    scale=1,
+                    elem_classes="chatbot",
+                )
+                textbox = gr.Textbox(
+                    show_label=False,
+                    placeholder="Enter text and press enter",
+                    scale=1,
+                    autofocus=True,
+                )
 
-demo.launch(server_name="0.0.0.0", server_port=8080, show_error=True, debug=True)
+            textbox.submit(chat, [textbox, chatbot, state], [textbox, chatbot, state])
+
+    demo.launch(server_name="0.0.0.0", server_port=8080, show_error=True, debug=True)
+
+
+if __name__ == "__main__":
+    main()

chatbot_ui/requirements.txt

@@ -1,4 +1,4 @@
-gradio==4.44.1
+gradio==5.3.0
 async_timeout==4.0.3
 loguru==0.7.2
 asyncio==3.4.3