add function infra

app.py

@@ -1,45 +1,100 @@
 import streamlit as st
 import os
 from openai import AzureOpenAI
-# Test comment
+
+from functions import call_function
 
 st.title("Support Chat UI")
+# when will my order be delivered?, colin.flueck@gmail.com W123123
+
+functions = [
+    {
+        "name": "order_tracking_status",
+        "description": "Retrieves the status of an order based on **both** the email address and order number.",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "email_address": {
+                    "type": "string",
+                    "description": "The email address associated with the order"
+                },
+                "order_number": {
+                    "type": "string",
+                    "description": "The order number. For online orders, this starts with either the letter W or C. "
+                                   "For in-store orders, this starts with the letter H. You can find your order "
+                                   "number in your confirmation email or your receipt."
+                },
+            },
+            "required": ["email_address, order_number"]
+        }
+    }
+]
 
 client = AzureOpenAI(
-  api_key = os.environ['OPENAI_API_KEY'],  
-  api_version = "2023-07-01-preview",
-  azure_endpoint = os.environ['AZURE_ENDPOINT'],  
+    api_key=os.environ['OPENAI_API_KEY'],
+    api_version="2023-07-01-preview",
+    azure_endpoint=os.environ['AZURE_ENDPOINT'],
 )
 
 if "openai_model" not in st.session_state:
     st.session_state["openai_model"] = "gpt-35-turbo"
 
 if "messages" not in st.session_state:
-    st.session_state.messages = []
+    st.session_state.messages = [{"role": "system", "content": "You are a helpful customer support agent for "
+                                                               "The Home Depot. Be as helpful as possible and call "
+                                                               "functions when necessary."},]
 
 for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
+    if message["role"] == "assistant" or message["role"] == "user":
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
 
-if prompt := st.chat_input("What is up?"):
+if prompt := st.chat_input("How can we help you today?"):
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)
 
-    with st.chat_message("assistant"):
+    with st.chat_message("assistant", avatar="🏠"):  # avatar=st.image('Home-Depot-Logo.png', width=50)):
         message_placeholder = st.empty()
-        full_response = ""
-        
-        for response in client.chat.completions.create(
-            model=st.session_state["openai_model"],
-            messages=[
+        full_message = ""
+        func_call = {
+            "name": None,
+            "arguments": "",
+        }
+
+        called_function = True
+        while called_function:
+            called_function = False
+            for response in client.chat.completions.create(
+                    model=st.session_state["openai_model"],
+                    messages=[
+                {"role": m["role"], "content": m["content"], "name": m["name"]} if "name" in m else
                 {"role": m["role"], "content": m["content"]}
                 for m in st.session_state.messages
             ],
-            stream=True,
-        ):
-            if len(response.choices) > 0:
-                full_response += (response.choices[0].delta.content or "")
-                message_placeholder.markdown(full_response + "▌")
-        message_placeholder.markdown(full_response)
-    st.session_state.messages.append({"role": "assistant", "content": full_response})
+                    functions=functions,
+                    function_call="auto",
+                    stream=True,
+            ):
+                if len(response.choices) > 0:
+                    delta = response.choices[0].delta
+
+                    full_message += (delta.content or "")
+                    if delta.function_call is not None:
+                        if delta.function_call.name is not None:
+                            func_call["name"] = delta.function_call.name
+                        if delta.function_call.arguments is not None:
+                            func_call["arguments"] += delta.function_call.arguments
+                    if response.choices[0].finish_reason == "function_call" and func_call["name"] is not None:
+                        print(f"Function generation requested, calling function")
+                        function_response = call_function(st.session_state.messages, func_call)
+                        print("function response")
+                        print(function_response)
+                        st.session_state.messages.append(function_response)
+                        called_function = True
+
+                    message_placeholder.markdown(full_message + "▌")
+
+        message_placeholder.markdown(full_message)
+
+        st.session_state.messages.append({"role": "assistant", "content": full_message})

functions.py

@@ -0,0 +1,48 @@
+import json
+
+
+def call_function(messages, function_call):
+    """Function calling function which executes function calls when the model believes it is necessary.
+    Currently extended by adding clauses to this if statement."""
+    print(function_call)
+
+    if function_call["name"] == "order_tracking_status":
+        try:
+            parsed_output = json.loads(
+                function_call["arguments"]
+            )
+            print("Looking up order status")
+            results = get_order_tracking_status(parsed_output["email_address"], parsed_output["order_number"])
+            return {
+                    "role": "function",
+                    "name": function_call["name"],
+                    "content": str(results),
+                }
+        except Exception as e:
+            # print(parsed_output)
+            print(f"Function execution failed")
+            print(f"Error message: {e}")
+            return {"role": "function", "content": "call failed", "name": "order_tracking_status"}
+        # try:
+        #     print("Got search results, summarizing content")
+        #     response = chat_completion_request(messages)
+        #     return response.json()
+        # except Exception as e:
+        #     print(type(e))
+        #     raise Exception("Function chat request failed")
+
+    # elif (
+    #     full_message["message"]["function_call"]["name"] == "read_article_and_summarize"
+    # ):
+    #     parsed_output = json.loads(
+    #         full_message["message"]["function_call"]["arguments"]
+    #     )
+    #     print("Finding and reading paper")
+    #     summary = summarize_text(parsed_output["query"])
+    #     return summary
+
+    else:
+        raise Exception("Function does not exist and cannot be called")
+
+def get_order_tracking_status(email_address, order_number):
+    return "The order was delivered on Monday, November 12th"

requirements.txt

@@ -1 +1,2 @@
-openai==1.3.3
+openai==1.3.3
+streamlit~=1.28.2