release: v1

.github/scripts/check_diff.py

@@ -121,25 +121,25 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
     if job == "codspeed":
         py_versions = ["3.12"]  # 3.13 is not yet supported
     elif dir_ == "libs/core":
-        py_versions = ["3.9", "3.10", "3.11", "3.12", "3.13"]
+        py_versions = ["3.10", "3.11", "3.12", "3.13"]
     # custom logic for specific directories
     elif dir_ == "libs/partners/milvus":
         # milvus doesn't allow 3.12 because they declare deps in funny way
-        py_versions = ["3.9", "3.11"]
+        py_versions = ["3.10", "3.11"]
 
     elif dir_ in PY_312_MAX_PACKAGES:
-        py_versions = ["3.9", "3.12"]
+        py_versions = ["3.10", "3.12"]
 
     elif dir_ == "libs/langchain" and job == "extended-tests":
-        py_versions = ["3.9", "3.13"]
+        py_versions = ["3.10", "3.13"]
     elif dir_ == "libs/langchain_v1":
         py_versions = ["3.10", "3.13"]
 
     elif dir_ == ".":
         # unable to install with 3.13 because tokenizers doesn't support 3.13 yet
-        py_versions = ["3.9", "3.12"]
+        py_versions = ["3.10", "3.12"]
     else:
-        py_versions = ["3.9", "3.13"]
+        py_versions = ["3.10", "3.13"]
 
     return [{"working-directory": dir_, "python-version": py_v} for py_v in py_versions]
 

.github/workflows/_release.yml

@@ -371,7 +371,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        partner: [openai, anthropic]
+        partner: [openai]
       fail-fast: false  # Continue testing other partners if one fails
     env:
       ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}

.github/workflows/scheduled_test.yml

@@ -1,5 +1,5 @@
 name: '⏰ Scheduled Integration Tests'
-run-name: "Run Integration Tests - ${{ inputs.working-directory-force || 'all libs' }} (Python ${{ inputs.python-version-force || '3.9, 3.11' }})"
+run-name: "Run Integration Tests - ${{ inputs.working-directory-force || 'all libs' }} (Python ${{ inputs.python-version-force || '3.10, 3.13' }})"
 
 on:
   workflow_dispatch:  # Allows maintainers to trigger the workflow manually in GitHub UI
@@ -9,7 +9,7 @@ on:
         description: "From which folder this pipeline executes - defaults to all in matrix - example value: libs/partners/anthropic"
       python-version-force:
         type: string
-        description: "Python version to use - defaults to 3.9 and 3.11 in matrix - example value: 3.9"
+        description: "Python version to use - defaults to 3.10 and 3.13 in matrix - example value: 3.11"
   schedule:
     - cron:  '0 13 * * *'  # Runs daily at 1PM UTC (9AM EDT/6AM PDT)
 
@@ -40,9 +40,9 @@ jobs:
           PYTHON_VERSION_FORCE: ${{ github.event.inputs.python-version-force || '' }}
         run: |
           # echo "matrix=..." where matrix is a json formatted str with keys python-version and working-directory
-          # python-version should default to 3.9 and 3.11, but is overridden to [PYTHON_VERSION_FORCE] if set
+          # python-version should default to 3.10 and 3.13, but is overridden to [PYTHON_VERSION_FORCE] if set
           # working-directory should default to DEFAULT_LIBS, but is overridden to [WORKING_DIRECTORY_FORCE] if set
-          python_version='["3.9", "3.11"]'
+          python_version='["3.10", "3.13"]'
           working_directory="$DEFAULT_LIBS"
           if [ -n "$PYTHON_VERSION_FORCE" ]; then
             python_version="[\"$PYTHON_VERSION_FORCE\"]"

docs/docs/how_to/multimodal_inputs.ipynb

@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "1fcf7b27-1cc3-420a-b920-0420b5892e20",
    "metadata": {},
    "outputs": [
@@ -102,7 +102,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {
@@ -133,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "99d27f8f-ae78-48bc-9bf2-3cef35213ec7",
    "metadata": {},
    "outputs": [
@@ -163,7 +163,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {
@@ -176,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "325fb4ca",
    "metadata": {},
    "outputs": [
@@ -198,7 +198,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {
@@ -234,7 +234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "6c1455a9-699a-4702-a7e0-7f6eaec76a21",
    "metadata": {},
    "outputs": [
@@ -284,7 +284,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {
@@ -312,7 +312,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "55e1d937-3b22-4deb-b9f0-9e688f0609dc",
    "metadata": {},
    "outputs": [
@@ -342,7 +342,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {
@@ -417,7 +417,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {
@@ -443,7 +443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "83593b9d-a8d3-4c99-9dac-64e0a9d397cb",
    "metadata": {},
    "outputs": [
@@ -488,13 +488,13 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())\n",
+    "print(response.text)\n",
     "response.usage_metadata"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "9bbf578e-794a-4dc0-a469-78c876ccd4a3",
    "metadata": {},
    "outputs": [
@@ -530,7 +530,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message, response, next_message])\n",
-    "print(response.text())\n",
+    "print(response.text)\n",
     "response.usage_metadata"
    ]
   },
@@ -600,7 +600,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "ae076c9b-ff8f-461d-9349-250f396c9a25",
    "metadata": {},
    "outputs": [
@@ -641,7 +641,7 @@
     "    ],\n",
     "}\n",
     "response = llm.invoke([message])\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {

docs/docs/how_to/multimodal_prompts.ipynb

@@ -54,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "5df2e558-321d-4cf7-994e-2815ac37e704",
    "metadata": {},
    "outputs": [
@@ -75,7 +75,7 @@
     "\n",
     "chain = prompt | llm\n",
     "response = chain.invoke({\"image_url\": url})\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {
@@ -117,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "25e4829e-0073-49a8-9669-9f43e5778383",
    "metadata": {},
    "outputs": [
@@ -144,7 +144,7 @@
     "        \"cache_type\": \"ephemeral\",\n",
     "    }\n",
     ")\n",
-    "print(response.text())"
+    "print(response.text)"
    ]
   },
   {

docs/docs/integrations/chat/anthropic.ipynb

@@ -1527,7 +1527,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "30a0af36-2327-4b1d-9ba5-e47cb72db0be",
    "metadata": {},
    "outputs": [
@@ -1563,7 +1563,7 @@
     "response = llm_with_tools.invoke(\n",
     "    \"There's a syntax error in my primes.py file. Can you help me fix it?\"\n",
     ")\n",
-    "print(response.text())\n",
+    "print(response.text)\n",
     "response.tool_calls"
    ]
   },

docs/docs/integrations/chat/bedrock.ipynb

@@ -243,12 +243,12 @@
    "id": "0ef05abb-9c04-4dc3-995e-f857779644d5",
    "metadata": {},
    "source": [
-    "You can filter to text using the [.text()](https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.AIMessage.html#langchain_core.messages.ai.AIMessage.text) method on the output:"
+    "You can filter to text using the [.text](https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.AIMessage.html#langchain_core.messages.ai.AIMessage.text) property on the output:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "2a4e743f-ea7d-4e5a-9b12-f9992362de8b",
    "metadata": {},
    "outputs": [
@@ -262,7 +262,7 @@
    ],
    "source": [
     "for chunk in llm.stream(messages):\n",
-    "    print(chunk.text(), end=\"|\")"
+    "    print(chunk.text, end=\"|\")"
    ]
   },
   {

docs/docs/integrations/chat/litellm.ipynb

@@ -261,7 +261,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "c5fac0e9-05a4-4fc1-a3b3-e5bbb24b971b",
    "metadata": {
     "colab": {
@@ -286,7 +286,7 @@
    ],
    "source": [
     "async for token in llm.astream(\"Hello, please explain how antibiotics work\"):\n",
-    "    print(token.text(), end=\"\")"
+    "    print(token.text, end=\"\")"
    ]
   },
   {