Merge branch 'master' into redis/langchain-redis-docs

docs/docs/integrations/chat/openai.ipynb

@@ -56,23 +56,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "e817fe2e-4f1d-4533-b19e-2400b1cf6ce8",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdin",
-     "output_type": "stream",
-     "text": [
-      "Enter your OpenAI API key:  ········\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import getpass\n",
     "import os\n",
     "\n",
-    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"Enter your OpenAI API key: \")"
+    "if not os.environ.get(\"OPENAI_API_KEY\"):\n",
+    "    os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"Enter your OpenAI API key: \")"
    ]
   },
   {
@@ -126,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "id": "522686de",
    "metadata": {
     "tags": []
@@ -281,12 +274,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 4,
    "id": "b7ea7690-ec7a-4337-b392-e87d1f39a6ec",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
+    "from pydantic import BaseModel, Field\n",
     "\n",
     "\n",
     "class GetWeather(BaseModel):\n",
@@ -322,6 +315,47 @@
     "ai_msg"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "67b0f63d-15e6-45e0-9e86-2852ddcff54f",
+   "metadata": {},
+   "source": [
+    "### ``strict=True``\n",
+    "\n",
+    ":::info Requires ``langchain-openai>=0.1.21rc1``\n",
+    "\n",
+    ":::\n",
+    "\n",
+    "As of Aug 6, 2024, OpenAI supports a `strict` argument when calling tools that will enforce that the tool argument schema is respected by the model. See more here: https://platform.openai.com/docs/guides/function-calling\n",
+    "\n",
+    "**Note**: If ``strict=True`` the tool definition will also be validated, and a subset of JSON schema are accepted. Crucially, schema cannot have optional args (those with default values). Read the full docs on what types of schema are supported here: https://platform.openai.com/docs/guides/structured-outputs/supported-schemas. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "dc8ac4f1-4039-4392-90c1-2d8331cd6910",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_VYEfpPDh3npMQ95J9EWmWvSn', 'function': {'arguments': '{\"location\":\"San Francisco, CA\"}', 'name': 'GetWeather'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 17, 'prompt_tokens': 68, 'total_tokens': 85}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_3aa7262c27', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-a4c6749b-adbb-45c7-8b17-8d6835d5c443-0', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'San Francisco, CA'}, 'id': 'call_VYEfpPDh3npMQ95J9EWmWvSn', 'type': 'tool_call'}], usage_metadata={'input_tokens': 68, 'output_tokens': 17, 'total_tokens': 85})"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "llm_with_tools = llm.bind_tools([GetWeather], strict=True)\n",
+    "ai_msg = llm_with_tools.invoke(\n",
+    "    \"what is the weather like in San Francisco\",\n",
+    ")\n",
+    "ai_msg"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "768d1ae4-4b1a-48eb-a329-c8d5051067a3",
@@ -412,9 +446,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "poetry-venv-2",
+   "display_name": "poetry-venv-311",
    "language": "python",
-   "name": "poetry-venv-2"
+   "name": "poetry-venv-311"
   },
   "language_info": {
    "codemirror_mode": {

libs/core/langchain_core/utils/function_calling.py

@@ -322,6 +322,8 @@ def format_tool_to_openai_tool(tool: BaseTool) -> ToolDescription:
 
 def convert_to_openai_function(
     function: Union[Dict[str, Any], Type, Callable, BaseTool],
+    *,
+    strict: Optional[bool] = None,
 ) -> Dict[str, Any]:
     """Convert a raw function/class to an OpenAI function.
 
@@ -330,6 +332,9 @@ def convert_to_openai_function(
             Tool object, or a Python function. If a dictionary is passed in, it is
             assumed to already be a valid OpenAI function or a JSON schema with
             top-level 'title' and 'description' keys specified.
+        strict: If True, model output is guaranteed to exactly match the JSON Schema
+            provided in the function definition. If None, ``strict`` argument will not
+            be included in function definition.
 
     Returns:
         A dict version of the passed in function which is compatible with the OpenAI
@@ -344,25 +349,27 @@ def convert_to_openai_function(
     if isinstance(function, dict) and all(
         k in function for k in ("name", "description", "parameters")
     ):
-        return function
+        oai_function = function
     # a JSON schema with title and description
     elif isinstance(function, dict) and all(
         k in function for k in ("title", "description", "properties")
     ):
         function = function.copy()
-        return {
+        oai_function = {
             "name": function.pop("title"),
             "description": function.pop("description"),
             "parameters": function,
         }
     elif isinstance(function, type) and is_basemodel_subclass(function):
-        return cast(Dict, convert_pydantic_to_openai_function(function))
+        oai_function = cast(Dict, convert_pydantic_to_openai_function(function))
     elif is_typeddict(function):
-        return cast(Dict, _convert_typed_dict_to_openai_function(cast(Type, function)))
+        oai_function = cast(
+            Dict, _convert_typed_dict_to_openai_function(cast(Type, function))
+        )
     elif isinstance(function, BaseTool):
-        return cast(Dict, format_tool_to_openai_function(function))
+        oai_function = cast(Dict, format_tool_to_openai_function(function))
     elif callable(function):
-        return cast(Dict, convert_python_function_to_openai_function(function))
+        oai_function = cast(Dict, convert_python_function_to_openai_function(function))
     else:
         raise ValueError(
             f"Unsupported function\n\n{function}\n\nFunctions must be passed in"
@@ -371,9 +378,18 @@ def convert_to_openai_function(
             " 'title' and 'description' keys."
         )
 
+    if strict is not None:
+        oai_function["strict"] = strict
+        # As of 08/06/24, OpenAI requires that additionalProperties be supplied and set
+        # to False if strict is True.
+        oai_function["parameters"]["additionalProperties"] = False
+    return oai_function
+
 
 def convert_to_openai_tool(
     tool: Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool],
+    *,
+    strict: Optional[bool] = None,
 ) -> Dict[str, Any]:
     """Convert a raw function/class to an OpenAI tool.
 
@@ -382,15 +398,19 @@ def convert_to_openai_tool(
             BaseTool. If a dictionary is passed in, it is assumed to already be a valid
             OpenAI tool, OpenAI function, or a JSON schema with top-level 'title' and
             'description' keys specified.
+        strict: If True, model output is guaranteed to exactly match the JSON Schema
+            provided in the function definition. If None, ``strict`` argument will not
+            be included in tool definition.
 
     Returns:
         A dict version of the passed in tool which is compatible with the
             OpenAI tool-calling API.
     """
     if isinstance(tool, dict) and tool.get("type") == "function" and "function" in tool:
         return tool
-    function = convert_to_openai_function(tool)
-    return {"type": "function", "function": function}
+    oai_function = convert_to_openai_function(tool, strict=strict)
+    oai_tool: Dict[str, Any] = {"type": "function", "function": oai_function}
+    return oai_tool
 
 
 def tool_example_to_messages(

libs/core/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "langchain-core"
-version = "0.2.28"
+version = "0.2.29rc1"
 description = "Building applications with LLMs through composability"
 authors = []
 license = "MIT"

libs/langchain/tests/unit_tests/chat_models/test_base.py

@@ -113,7 +113,11 @@ def test_configurable() -> None:
             "tools": [
                 {
                     "type": "function",
-                    "function": {"name": "foo", "description": "foo", "parameters": {}},
+                    "function": {
+                        "name": "foo",
+                        "description": "foo",
+                        "parameters": {},
+                    },
                 }
             ]
         },