openai[patch]: release 0.2.6 (#27924)

Some additions in support of [predicted
outputs](https://platform.openai.com/docs/guides/latency-optimization#use-predicted-outputs)
feature:
- Bump openai sdk version
- Add integration test
- Add example to integration docs

The `prediction` kwarg is already plumbed through model invocation.

docs/docs/integrations/chat/openai.ipynb

@@ -509,6 +509,101 @@
     "output_message.content"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "5c35d0a4-a6b8-4d35-a02b-a37a8bda5692",
+   "metadata": {},
+   "source": [
+    "## Predicted output\n",
+    "\n",
+    ":::info\n",
+    "Requires `langchain-openai>=0.2.6`\n",
+    ":::\n",
+    "\n",
+    "Some OpenAI models (such as their `gpt-4o` and `gpt-4o-mini` series) support [Predicted Outputs](https://platform.openai.com/docs/guides/latency-optimization#use-predicted-outputs), which allow you to pass in a known portion of the LLM's expected output ahead of time to reduce latency. This is useful for cases such as editing text or code, where only a small part of the model's output will change.\n",
+    "\n",
+    "Here's an example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "88fee1e9-58c1-42ad-ae23-24b882e175e7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/// <summary>\n",
+      "/// Represents a user with a first name, last name, and email.\n",
+      "/// </summary>\n",
+      "public class User\n",
+      "{\n",
+      "    /// <summary>\n",
+      "    /// Gets or sets the user's first name.\n",
+      "    /// </summary>\n",
+      "    public string FirstName { get; set; }\n",
+      "\n",
+      "    /// <summary>\n",
+      "    /// Gets or sets the user's last name.\n",
+      "    /// </summary>\n",
+      "    public string LastName { get; set; }\n",
+      "\n",
+      "    /// <summary>\n",
+      "    /// Gets or sets the user's email.\n",
+      "    /// </summary>\n",
+      "    public string Email { get; set; }\n",
+      "}\n",
+      "{'token_usage': {'completion_tokens': 226, 'prompt_tokens': 166, 'total_tokens': 392, 'completion_tokens_details': {'accepted_prediction_tokens': 49, 'audio_tokens': None, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 107}, 'prompt_tokens_details': {'audio_tokens': None, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_45cf54deae', 'finish_reason': 'stop', 'logprobs': None}\n"
+     ]
+    }
+   ],
+   "source": [
+    "code = \"\"\"\n",
+    "/// <summary>\n",
+    "/// Represents a user with a first name, last name, and username.\n",
+    "/// </summary>\n",
+    "public class User\n",
+    "{\n",
+    "    /// <summary>\n",
+    "    /// Gets or sets the user's first name.\n",
+    "    /// </summary>\n",
+    "    public string FirstName { get; set; }\n",
+    "\n",
+    "    /// <summary>\n",
+    "    /// Gets or sets the user's last name.\n",
+    "    /// </summary>\n",
+    "    public string LastName { get; set; }\n",
+    "\n",
+    "    /// <summary>\n",
+    "    /// Gets or sets the user's username.\n",
+    "    /// </summary>\n",
+    "    public string Username { get; set; }\n",
+    "}\n",
+    "\"\"\"\n",
+    "\n",
+    "llm = ChatOpenAI(model=\"gpt-4o\")\n",
+    "query = (\n",
+    "    \"Replace the Username property with an Email property. \"\n",
+    "    \"Respond only with code, and with no markdown formatting.\"\n",
+    ")\n",
+    "response = llm.invoke(\n",
+    "    [{\"role\": \"user\", \"content\": query}, {\"role\": \"user\", \"content\": code}],\n",
+    "    prediction={\"type\": \"content\", \"content\": code},\n",
+    ")\n",
+    "print(response.content)\n",
+    "print(response.response_metadata)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2ee1b26d-a388-4e7c-9f40-bfd1388ecc03",
+   "metadata": {},
+   "source": [
+    "Note that currently predictions are billed as additional tokens and may increase your usage and costs in exchange for this reduced latency."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "feb4a499",
@@ -601,7 +696,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -615,7 +710,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.10.4"
   }
  },
  "nbformat": 4,

libs/partners/openai/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "langchain-openai"
-version = "0.2.5"
+version = "0.2.6"
 description = "An integration package connecting OpenAI and LangChain"
 authors = []
 readme = "README.md"
@@ -24,7 +24,7 @@ ignore_missing_imports = true
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
 langchain-core = "^0.3.15"
-openai = "^1.52.0"
+openai = "^1.54.0"
 tiktoken = ">=0.7,<1"
 
 [tool.ruff.lint]

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -3,6 +3,7 @@
 import base64
 import json
 from pathlib import Path
+from textwrap import dedent
 from typing import Any, AsyncIterator, List, Literal, Optional, cast
 
 import httpx
@@ -1018,3 +1019,45 @@ def test_audio_input_modality() -> None:
 
     assert isinstance(output, AIMessage)
     assert "audio" in output.additional_kwargs
+
+
+def test_prediction_tokens() -> None:
+    code = dedent("""
+    /// <summary>
+    /// Represents a user with a first name, last name, and username.
+    /// </summary>
+    public class User
+    {
+        /// <summary>
+        /// Gets or sets the user's first name.
+        /// </summary>
+        public string FirstName { get; set; }
+
+        /// <summary>
+        /// Gets or sets the user's last name.
+        /// </summary>
+        public string LastName { get; set; }
+
+        /// <summary>
+        /// Gets or sets the user's username.
+        /// </summary>
+        public string Username { get; set; }
+    }
+    """)
+
+    llm = ChatOpenAI(model="gpt-4o")
+    query = (
+        "Replace the Username property with an Email property. "
+        "Respond only with code, and with no markdown formatting."
+    )
+    response = llm.invoke(
+        [{"role": "user", "content": query}, {"role": "user", "content": code}],
+        prediction={"type": "content", "content": code},
+    )
+    assert isinstance(response, AIMessage)
+    assert response.response_metadata is not None
+    output_token_details = response.response_metadata["token_usage"][
+        "completion_tokens_details"
+    ]
+    assert output_token_details["accepted_prediction_tokens"] > 0
+    assert output_token_details["rejected_prediction_tokens"] > 0