docs: add changelog entry for infrastructure scaling improvements

cookbook/example_evaluating_multi_turn_conversations.ipynb

@@ -111,73 +111,7 @@
     "id": "d3f4e177"
    },
    "outputs": [],
-   "source": [
-    "# This is a simple cooking assistant chatbot traced with Langfuse and uses OpenAI as the LLM.\n",
-    "from langfuse.openai import openai\n",
-    "from langfuse import get_client, observe\n",
-    "\n",
-    "\n",
-    "\n",
-    "class SimpleChat:\n",
-    "    def __init__(self, model=\"gpt-3.5-turbo\"):\n",
-    "        self.conversation_history = [\n",
-    "          {\n",
-    "            \"role\": \"system\",\n",
-    "            \"content\": \"You are a helpful cooking assistant that answers questions about recipes and cooking.\"\n",
-    "          }\n",
-    "        ]\n",
-    "        self.model = model\n",
-    "\n",
-    "    @observe\n",
-    "    def add_message(self, messages):\n",
-    "        \"\"\"\n",
-    "        Args:\n",
-    "            messages: Either a string (single user message) or a list of message dictionaries\n",
-    "        \"\"\"\n",
-    "        try:\n",
-    "            # Handle both string and array inputs\n",
-    "            if isinstance(messages, str):\n",
-    "                messages = [{\"role\": \"user\", \"content\": messages}]\n",
-    "\n",
-    "            # Add messages to history\n",
-    "            self.conversation_history.extend(messages)\n",
-    "\n",
-    "            # Call OpenAI API using the new client\n",
-    "            response = openai.chat.completions.create(\n",
-    "                model=self.model,\n",
-    "                messages=self.conversation_history,\n",
-    "                max_tokens=500,\n",
-    "                temperature=0.7\n",
-    "            )\n",
-    "\n",
-    "            # Extract and add assistant response\n",
-    "            assistant_message = response.choices[0].message.content\n",
-    "            self.conversation_history.append({\"role\": \"assistant\", \"content\": assistant_message})\n",
-    "            get_client().update_current_trace(input=messages, output=assistant_message)\n",
-    "\n",
-    "            return assistant_message\n",
-    "\n",
-    "        except Exception as e:\n",
-    "            return f\"Error: {str(e)}\"\n",
-    "\n",
-    "    def show_history(self):\n",
-    "        import json\n",
-    "        print(\"Conversation history:\")\n",
-    "        print(json.dumps(self.conversation_history, indent=2))\n",
-    "        print()\n",
-    "\n",
-    "    def clear_history(self):\n",
-    "        self.conversation_history = [\n",
-    "          {\n",
-    "            \"role\": \"system\",\n",
-    "            \"content\": \"You are a helpful cooking assistant that answers questions about recipes and cooking.\"\n",
-    "          }\n",
-    "        ]\n",
-    "        print(\"Conversation cleared!\")\n",
-    "\n",
-    "# Create a chat instance\n",
-    "chat = SimpleChat()"
-   ]
+   "source": "# This is a simple cooking assistant chatbot traced with Langfuse and uses OpenAI as the LLM.\nfrom langfuse.openai import openai\nfrom langfuse import get_client, observe\n\n\n\nclass SimpleChat:\n    def __init__(self, model=\"gpt-3.5-turbo\"):\n        self.conversation_history = [\n          {\n            \"role\": \"system\",\n            \"content\": \"You are a helpful cooking assistant that answers questions about recipes and cooking.\"\n          }\n        ]\n        self.model = model\n\n    @observe\n    def add_message(self, messages):\n        \"\"\"\n        Args:\n            messages: Either a string (single user message) or a list of message dictionaries\n        \"\"\"\n        try:\n            # Handle both string and array inputs\n            if isinstance(messages, str):\n                messages = [{\"role\": \"user\", \"content\": messages}]\n\n            # Add messages to history\n            self.conversation_history.extend(messages)\n\n            # Call OpenAI API using the new client\n            response = openai.chat.completions.create(\n                model=self.model,\n                messages=self.conversation_history,\n                max_tokens=500,\n                temperature=0.7\n            )\n\n            # Extract and add assistant response\n            assistant_message = response.choices[0].message.content\n            self.conversation_history.append({\"role\": \"assistant\", \"content\": assistant_message})\n            get_client().update_current_observation(input=messages, output=assistant_message)\n\n            return assistant_message\n\n        except Exception as e:\n            return f\"Error: {str(e)}\"\n\n    def show_history(self):\n        import json\n        print(\"Conversation history:\")\n        print(json.dumps(self.conversation_history, indent=2))\n        print()\n\n    def clear_history(self):\n        self.conversation_history = [\n          {\n            \"role\": \"system\",\n            \"content\": \"You are a helpful cooking assistant that answers questions about recipes and cooking.\"\n          }\n        ]\n        print(\"Conversation cleared!\")\n\n# Create a chat instance\nchat = SimpleChat()"
   },
   {
    "cell_type": "markdown",
@@ -388,4 +322,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}