Update

docs/docs/integrations/chat/ollama.ipynb

@@ -119,6 +119,150 @@
     "chat_model(messages)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Extraction\n",
+    " \n",
+    "Update your version of Ollama and supply the [`format`](https://github.com/jmorganca/ollama/blob/main/docs/api.md#json-mode) flag.\n",
+    "\n",
+    "We can enforce the model to produce JSON."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.chat_models import ChatOllama\n",
+    "from langchain.callbacks.manager import CallbackManager\n",
+    "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
+    "\n",
+    "chat_model = ChatOllama(\n",
+    "    model=\"llama2\",\n",
+    "    format=\"json\",\n",
+    "    callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " Sure! Here's a JSON response with the colors of the sky at different times of the day:\n",
+      " Begriffe und Abkürzungen:\n",
+      "\n",
+      "* `time`: The time of day (in 24-hour format)\n",
+      "* `sky_color`: The color of the sky at that time (as a hex code)\n",
+      "\n",
+      "Here are the colors of the sky at different times of the day:\n",
+      "```json\n",
+      "[\n",
+      "  {\n",
+      "    \"time\": \"6am\",\n",
+      "    \"sky_color\": \"#0080c0\"\n",
+      "  },\n",
+      "  {\n",
+      "    \"time\": \"9am\",\n",
+      "    \"sky_color\": \"#3498db\"\n",
+      "  },\n",
+      "  {\n",
+      "    \"time\": \"12pm\",\n",
+      "    \"sky_color\": \"#ef7c00\"\n",
+      "  },\n",
+      "  {\n",
+      "    \"time\": \"3pm\",\n",
+      "    \"sky_color\": \"#9564b6\"\n",
+      "  },\n",
+      "  {\n",
+      "    \"time\": \"6pm\",\n",
+      "    \"sky_color\": \"#e78ac3\"\n",
+      "  },\n",
+      "  {\n",
+      "    \"time\": \"9pm\",\n",
+      "    \"sky_color\": \"#5f006a\"\n",
+      "  }\n",
+      "]\n",
+      "```\n",
+      "In this response, the `time` property is a string in 24-hour format, representing the time of day. The `sky_color` property is a hex code representing the color of the sky at that time. For example, at 6am, the sky is blue (#0080c0), while at 9pm, it's dark blue (#5f006a)."
+     ]
+    }
+   ],
+   "source": [
+    "from langchain.schema import HumanMessage\n",
+    "\n",
+    "messages = [\n",
+    "    HumanMessage(content=\"What color is the sky at different times of the day? Respond using JSON\")\n",
+    "    ]\n",
+    "\n",
+    "chat_model_response = chat_model(messages)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " Sure! Based on the JSON schema you provided, here's the information we can gather about a person named John who is 35 years old and loves pizza:\n",
+      "\n",
+      "**Name:** John\n",
+      "\n",
+      "**Age:** 35 (integer)\n",
+      "\n",
+      "**Favorite food:** Pizza (string)\n",
+      "\n",
+      "So, the JSON object for John would look like this:\n",
+      "```json\n",
+      "{\n",
+      "  \"name\": \"John\",\n",
+      "  \"age\": 35,\n",
+      "  \"fav_food\": \"pizza\"\n",
+      "}\n",
+      "```\n",
+      "Note that we cannot provide additional information about John beyond what is specified in the schema. For example, we do not have any information about his gender, occupation, or address, as those fields are not included in the schema."
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "from langchain.schema import HumanMessage\n",
+    "\n",
+    "json_schema = {\n",
+    "    \"title\": \"Person\",\n",
+    "    \"description\": \"Identifying information about a person.\",\n",
+    "    \"type\": \"object\",\n",
+    "    \"properties\": {\n",
+    "        \"name\": {\"title\": \"Name\", \"description\": \"The person's name\", \"type\": \"string\"},\n",
+    "        \"age\": {\"title\": \"Age\", \"description\": \"The person's age\", \"type\": \"integer\"},\n",
+    "        \"fav_food\": {\n",
+    "            \"title\": \"Fav Food\",\n",
+    "            \"description\": \"The person's favorite food\",\n",
+    "            \"type\": \"string\"\n",
+    "        }\n",
+    "    },\n",
+    "    \"required\": [\"name\", \"age\"]\n",
+    "}\n",
+    "\n",
+    "messages = [\n",
+    "    HumanMessage(content=\"Please tell me about a person using the following JSON schema:\"),\n",
+    "    HumanMessage(content=json.dumps(json_schema, indent=2)),\n",
+    "    HumanMessage(content=\"Now, considering the schema, tell me about a person named John who is 35 years old and loves pizza.\")\n",
+    "    ]\n",
+    "\n",
+    "chat_model_response = chat_model(messages)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -375,5 +519,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

libs/langchain/langchain/llms/ollama.py

@@ -89,11 +89,15 @@ class _OllamaCommon(BaseLanguageModel):
     to more diverse text, while a lower value (e.g., 0.5) will
     generate more focused and conservative text. (Default: 0.9)"""
 
+    format: Optional[str] = None
+    """Specify the format of the output (e.g., JSON)"""
+
     @property
     def _default_params(self) -> Dict[str, Any]:
         """Get the default parameters for calling Ollama."""
         return {
             "model": self.model,
+            "format": self.format,
             "options": {
                 "mirostat": self.mirostat,
                 "mirostat_eta": self.mirostat_eta,
@@ -114,7 +118,7 @@ class _OllamaCommon(BaseLanguageModel):
     @property
     def _identifying_params(self) -> Mapping[str, Any]:
         """Get the identifying parameters."""
-        return {**{"model": self.model}, **self._default_params}
+        return {**{"model": self.model,"format": self.format}, **self._default_params}
 
     def _create_stream(
         self,