don't compute embeddings for names and other fixes see description (#126)

* serialize tools - 2

* fix int tests

* fix int test

* fix unit tests

chatbot_ui/app/run.py

@@ -1,5 +1,6 @@
+import json
 import os
-from openai import OpenAI
+from openai import OpenAI, DefaultHttpxClient
 import gradio as gr
 import logging as log
 from dotenv import load_dotenv
@@ -13,11 +14,13 @@ MODEL_NAME = os.getenv("MODEL_NAME", "gpt-3.5-turbo")
 
 log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
 
-client = OpenAI(api_key=OPENAI_API_KEY, base_url=CHAT_COMPLETION_ENDPOINT)
+client = OpenAI(api_key=OPENAI_API_KEY, base_url=CHAT_COMPLETION_ENDPOINT, http_client=DefaultHttpxClient(headers={"accept-encoding": "*"}))
 
-def predict(message, history):
+def predict(message, state):
+    if 'history' not in state:
+        state['history'] = []
+    history = state.get("history")
     history.append({"role": "user", "content": message})
-    log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
     log.info("history: ", history)
 
     # Custom headers
@@ -27,34 +30,42 @@ def predict(message, history):
         'x-arch-deterministic-provider': 'openai',
     }
 
+    metadata = None
+    if 'arch_state' in state:
+       metadata = {"x-arch-state": state['arch_state']}
+
     try:
-      response = client.chat.completions.create(model=MODEL_NAME,
-        messages= history,
+      raw_response = client.chat.completions.with_raw_response.create(model=MODEL_NAME,
+        messages = history,
         temperature=1.0,
+        metadata=metadata,
         extra_headers=custom_headers
       )
     except Exception as e:
       log.info(e)
       # remove last user message in case of exception
       history.pop()
-      log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
       log.info("Error calling gateway API: {}".format(e.message))
       raise gr.Error("Error calling gateway API: {}".format(e.message))
 
-    choices = response.choices
-    message = choices[0].message
-    content = message.content
-    history.append({"role": "assistant", "content": content})
-    history[-1]["model"] = response.model
+    response = raw_response.parse()
 
+    # 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
+    arch_state = json.loads(raw_response.text).get('metadata', {}).get('x-arch-state', None)
+    if arch_state:
+        state['arch_state'] = arch_state
+
+    content = response.choices[0].message.content
+
+    history.append({"role": "assistant", "content": content, "model": response.model})
     messages = [(history[i]["content"], history[i+1]["content"]) for i in range(0, len(history)-1, 2)]
-    return messages, history
-
+    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([])
+    state = gr.State({})
     with gr.Row():
         txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter", scale=1, autofocus=True)
 

chatbot_ui/requirements.txt

@@ -5,4 +5,4 @@ asyncio==3.4.3
 httpx==0.27.0
 python-dotenv==1.0.1
 pydantic==2.8.2
-openai==1.46.1
+openai==1.51.0