sdk-py 0.1.43

sdk-py: Handle stream(params=)

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -7,35 +7,29 @@ body:
       value: >
         Thank you for taking the time to file a bug report. 
         
-        Use this to report bugs in LangChain. 
-        
-        If you're not certain that your issue is due to a bug in LangChain, please use [GitHub Discussions](https://github.com/langchain-ai/langchain/discussions)
-        to ask for help with your issue.
+        Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use [GitHub Discussions](https://github.com/langchain-ai/langgraph/discussions).
         
         Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
         if there's another way to solve your problem:
         
-        [LangGraph documentation](https://langchain-ai.github.io/langgraph/).
+        [LangGraph Github Discussions](https://github.com/langchain-ai/langgraph/discussions),
+        [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
+        [LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
         [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
         [GitHub search](https://github.com/langchain-ai/langgraph),
-        [LangChain Github Discussions](https://github.com/langchain-ai/langgraph/discussions),
-        [LangChain Github Issues](https://github.com/langchain-ai/langgraph/issues),
-        [LangChain ChatBot](https://chat.langchain.com/)
   - type: checkboxes
     id: checks
     attributes:
       label: Checked other resources
-      description: Please confirm and check all the following options.
+      description: Before submitting this issue, please confirm that you have completed all the steps below by checking each option. These steps help ensure your issue is well-defined, relevant, and actionable.
       options:
-        - label: I added a very descriptive title to this issue.
+        - label: This is a bug, not a usage question. For questions, please use GitHub Discussions.
           required: true
-        - label: I searched the [LangGraph](https://langchain-ai.github.io/langgraph/)/LangChain documentation with the integrated search.
+        - label: I added a clear and detailed title that summarizes the issue.
           required: true
-        - label: I used the GitHub search to find a similar question and didn't find it.
+        - label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
           required: true
-        - label: I am sure that this is a bug in LangGraph/LangChain rather than my code.
-          required: true
-        - label: I am sure this is better as an issue [rather than a GitHub discussion](https://github.com/langchain-ai/langgraph/discussions/new/choose), since this is a LangGraph bug and not a design question.
+        - label: I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
           required: true
   - type: textarea
     id: reproduction
@@ -45,14 +39,6 @@ body:
       label: Example Code
       description: |
         Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
-        
-        If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
-        
-        **Important!** 
-        
-        * Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
-        * Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
-
       placeholder: |
         from langgraph.graph import StateGraph
 
@@ -92,25 +78,8 @@ body:
     attributes:
       label: System Info
       description: |
-        Please share your system info with us. 
-        
-        "pip freeze | grep langchain" 
-        platform (windows / linux / mac)
-        python version
-        
-        OR if you're on a recent version of langchain-core you can paste the output of:
-        
         python -m langchain_core.sys_info
       placeholder: |
-        "pip freeze | grep langgraph"
-        platform
-        python version
-        
-        Alternatively, if you're on a recent version of langchain-core you can paste the output of:
-        
         python -m langchain_core.sys_info
-        
-        These will only surface LangChain packages, don't forget to include any other relevant
-        packages you're using (if you're not sure what's relevant, you can paste the entire output of `pip freeze`).
     validations:
       required: true

.github/scripts/run_langgraph_cli_test.py

@@ -0,0 +1,115 @@
+import asyncio
+import json
+import os
+import pathlib
+import sys
+import langgraph_cli
+import langgraph_cli.docker
+import langgraph_cli.config
+
+from langgraph_cli.exec import Runner, subp_exec
+from langgraph_cli.progress import Progress
+from langgraph_cli.constants import DEFAULT_PORT
+
+
+def test(
+    config: pathlib.Path,
+    port: int,
+    tag: str,
+    verbose: bool,
+):
+    with Runner() as runner, Progress(message="Pulling...") as set:
+        # check docker available
+        capabilities = langgraph_cli.docker.check_capabilities(runner)
+        # open config
+        config_json = langgraph_cli.config.validate_config_file(config)
+
+        set("Running...")
+        args = [
+            "run",
+            "--rm",
+            "-p",
+            f"{port}:8000",
+        ]
+        if isinstance(config_json["env"], str):
+            args.extend(
+                [
+                    "--env-file",
+                    str(config.parent / config_json["env"]),
+                ]
+            )
+        else:
+            for k, v in config_json["env"].items():
+                args.extend(
+                    [
+                        "-e",
+                        f"{k}={v}",
+                    ]
+                )
+        if capabilities.healthcheck_start_interval:
+            args.extend(
+                [
+                    "--health-interval",
+                    "5s",
+                    "--health-retries",
+                    "1",
+                    "--health-start-period",
+                    "10s",
+                    "--health-start-interval",
+                    "1s",
+                ]
+            )
+        else:
+            args.extend(
+                [
+                    "--health-interval",
+                    "5s",
+                    "--health-retries",
+                    "2",
+                ]
+            )
+
+        _task = None
+
+        def on_stdout(line: str):
+            nonlocal _task
+            if "GET /ok" in line or "Uvicorn running on" in line:
+                set("")
+                sys.stdout.write(
+                    f"""Ready!
+- API: http://localhost:{port}
+"""
+                )
+                sys.stdout.flush()
+                _task.cancel()
+                return True
+            return False
+
+        async def subp_exec_task(*args, **kwargs):
+            nonlocal _task
+            _task = asyncio.create_task(subp_exec(*args, **kwargs))
+            await _task
+
+        try:
+            runner.run(
+                subp_exec_task(
+                    "docker",
+                    *args,
+                    tag,
+                    verbose=verbose,
+                    on_stdout=on_stdout,
+                )
+            )
+        except asyncio.CancelledError:
+            pass
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-t", "--tag", type=str)
+    parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
+    parser.add_argument("-p", "--port", default=DEFAULT_PORT)
+    args = parser.parse_args()
+    test(pathlib.Path(args.config), args.port, args.tag, verbose=True)

.github/workflows/_integration_test.yml

@@ -39,22 +39,36 @@ jobs:
       - name: Install cli globally
         if: steps.changed-files.outputs.all
         run: pip install -e .
-      - name: Start service A
+      - name: Build and test service A
         if: steps.changed-files.outputs.all
+        working-directory: libs/cli/examples
         run: |
-          timeout 60 langgraph test -c examples/langgraph.json --verbose || (exit "$(($? == 124 ? 0 : $?))")
-      - name: Start service B
+          # The build-arg isn't used; just testing that we accept other args
+          langgraph build -t langgraph-test-a  --base-image "langchain/langgraph-trial"
+          cp .env.example .envg
+          timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
+      - name: Build and test service B
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs
         run: |
-          timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
-      - name: Start service C
+          langgraph build -t langgraph-test-b  --base-image "langchain/langgraph-trial"
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
+      - name: Build and test service C
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_a
         run: |
-          timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
-      - name: Start service D
+          langgraph build -t langgraph-test-c  --base-image "langchain/langgraph-trial"
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
+      - name: Build and test service D
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_b
         run: |
-          timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
+          langgraph build -t langgraph-test-d  --base-image "langchain/langgraph-trial"
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
+
+      - name: Build JS service
+        if: steps.changed-files.outputs.all
+        working-directory: libs/cli/js-examples
+        run: |
+          langgraph build -t langgraph-test-e
+  

.github/workflows/_test.yml

@@ -21,6 +21,7 @@ jobs:
           - "3.10"
           - "3.11"
           - "3.12"
+          - "3.13"
 
     name: "test #${{ matrix.python-version }}"
     steps:
@@ -32,6 +33,12 @@ jobs:
           poetry-version: ${{ env.POETRY_VERSION }}
           working-directory: ${{ inputs.working-directory }}
           cache-key: test-${{ inputs.working-directory }}
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        if: ${{ !github.event.pull_request.head.repo.fork }}
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
 
       - name: Install dependencies
         shell: bash

.github/workflows/_test_langgraph.yml

@@ -16,14 +16,22 @@ jobs:
           - "3.10"
           - "3.11"
           - "3.12"
+          - "3.13"
         core-version:
-          - ">=0.2.39,<0.3.0"
           - "latest"
+        ff-send-v2:
+          - "false"
+        include:
+          - python-version: "3.11"
+            core-version: ">=0.2.42,<0.3.0"
+          - python-version: "3.11"
+            core-version: "latest"
+            ff-send-v2: "true"
 
     defaults:
       run:
         working-directory: libs/langgraph
-    name: "test #${{ matrix.python-version }} (langchain-core: ${{ matrix.core-version }})"
+    name: "test #${{ matrix.python-version }} (langchain-core: ${{ matrix.core-version }}, ff-send-v2: ${{ matrix.ff-send-v2 }})"
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
@@ -32,6 +40,12 @@ jobs:
           python-version: ${{ matrix.python-version }}
           poetry-version: ${{ env.POETRY_VERSION }}
           cache-key: test-langgraph
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        if: ${{ !github.event.pull_request.head.repo.fork }}
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
 
       - name: Install dependencies
         shell: bash
@@ -43,8 +57,10 @@ jobs:
 
       - name: Run tests
         shell: bash
+        env:
+          LANGGRAPH_FF_SEND_V2: ${{ matrix.ff-send-v2 }}
         run: |
-          make test
+          make test_parallel
 
       - name: Ensure the tests did not create any additional files
         shell: bash

.github/workflows/_test_release.yml

@@ -93,3 +93,5 @@ jobs:
           # This is *only for CI use* and is *extremely dangerous* otherwise!
           # https://github.com/pypa/gh-action-pypi-publish#tolerating-release-package-file-duplicates
           skip-existing: true
+          # Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
+          attestations: false

.github/workflows/_test_scheduler_kafka.yml

@@ -27,6 +27,12 @@ jobs:
           python-version: ${{ matrix.python-version }}
           poetry-version: ${{ env.POETRY_VERSION }}
           cache-key: test-scheduler-kafka
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        if: ${{ !github.event.pull_request.head.repo.fork }}
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
 
       - name: Install dependencies
         shell: bash

.github/workflows/ci.yml

@@ -31,6 +31,7 @@ jobs:
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
+            "libs/checkpoint-duckdb",
             "libs/checkpoint-postgres",
             "libs/scheduler-kafka",
           ]
@@ -47,6 +48,7 @@ jobs:
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
+            "libs/checkpoint-duckdb",
             "libs/checkpoint-postgres"
           ]
     uses: ./.github/workflows/_test.yml

.github/workflows/deploy_docs.yml

@@ -25,7 +25,7 @@ jobs:
   get-changed-files:
     runs-on: ubuntu-latest
     outputs:
-      changed-files: ${{ steps.changed-files.outputs.all }}
+      changed-files: ${{ steps.changed-files.outputs.added_modified }}
     steps:
       - uses: actions/checkout@v4
       - name: Get changed files
@@ -44,6 +44,8 @@ jobs:
   deploy:
     # needs: run-changed-notebooks
     runs-on: ubuntu-latest
+    env:
+      GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
     steps:
       - uses: actions/checkout@v4
         with:
@@ -58,8 +60,14 @@ jobs:
 
       - name: Install dependencies
         run: |
-          poetry install --with docs
-          poetry run pip install -U pytest pytest-check-links langsmith langchain GitPython
+          poetry install --with test --no-root
+          poetry run pip install -U \
+            pytest \
+            pytest-check-links \
+            langsmith \
+            langchain \
+            GitPython \
+            "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
 
       - name: Lint Docs
         # This step lints the docs using the existing linting set up.
@@ -80,8 +88,13 @@ jobs:
               --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
               --check-links-ignore "https://x.com/.*" \
               --check-links-ignore "https://github\.com/.*" \
+              --check-links-ignore "http://localhost:8123/.*" \
               --check-links-ignore "/.*\.(ipynb|html)$" \
-              --check-links $(find docs/site -name "index.html" | grep -v 'storm/index.html')
+              --check-links-ignore "https://python\.langchain\.com/.*" \
+              --check-links-ignore "https://openai\.com/.*" \
+              --check-links-ignore "https://pepy\.tech/.*" \
+              --check-links $(find docs/site -name "index.html" | grep -v 'storm/index.html') 
+              
           else
             echo "Fetching changes from origin/main..."
             git fetch origin main
@@ -92,6 +105,7 @@ jobs:
               echo "Running link check on HTML files matching changed notebook files..."
               poetry run pytest -v \
                 --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
+                --check-links-ignore "http://localhost:8123/.*" \
                 --check-links-ignore "https://x.com/.*" \
                 --check-links-ignore "https://github\.com/.*" \
                 --check-links-ignore "/.*\.(ipynb|html)$" \

.github/workflows/release.yml

@@ -270,6 +270,8 @@ jobs:
           packages-dir: ${{ inputs.working-directory }}/dist/
           verbose: true
           print-hash: true
+          # Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
+          attestations: false
 
   mark-release:
     needs:

CONTRIBUTING.md

@@ -49,7 +49,7 @@ gain understanding of concepts and how they interact by showing one way to achie
 
 They should **avoid** giving
 multiple permutations of ways to achieve that goal in-depth. Choice is burdensome. Instead, they should guide a new user through a recommended path to accomplishing a concrete goal. While the end result of a tutorial does not necessarily need to
-be completely production-ready, it should be useful and practically satisfy the the goal that you clearly stated in the tutorial's introduction.
+be completely production-ready, it should be useful and practically satisfy the goal that you clearly stated in the tutorial's introduction.
 
 To quote the Diataxis website:
 

Makefile

@@ -13,7 +13,7 @@ serve-clean-docs: clean-docs
 	poetry run python -m mkdocs serve -c -f docs/mkdocs.yml --strict -w ./libs/langgraph
 
 serve-docs: build-typedoc
-	poetry run python -m mkdocs serve -f docs/mkdocs.yml -w ./libs/langgraph --dirty
+	poetry run python -m mkdocs serve -f docs/mkdocs.yml -w ./libs/langgraph  -w ./libs/checkpoint --dirty
 
 clean-docs:
 	find ./docs/docs -name "*.ipynb" -type f -delete

README.md

@@ -16,6 +16,8 @@
 
 LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
 
+[LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform) is infrastructure for deploying LangGraph agents. It is a commercial solution for deploying agentic applications to production, built on the open-source LangGraph framework. The LangGraph Platform consists of several components that work together to support the development, deployment, debugging, and monitoring of LangGraph applications: [LangGraph Server](https://langchain-ai.github.io/langgraph/concepts/langgraph_server) (APIs), [LangGraph SDKs](https://langchain-ai.github.io/langgraph/concepts/sdk) (clients for the APIs), [LangGraph CLI](https://langchain-ai.github.io/langgraph/concepts/langgraph_cli) (command line tool for building the server), [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio) (UI/debugger),
+
 To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available for free [here](https://academy.langchain.com/courses/intro-to-langgraph).
 
 ### Key Features
@@ -26,6 +28,16 @@ To learn more about LangGraph, check out our first LangChain Academy course, *In
 - **Streaming Support**: Stream outputs as they are produced by each node (including token streaming).
 - **Integration with LangChain**: LangGraph integrates seamlessly with [LangChain](https://github.com/langchain-ai/langchain/) and [LangSmith](https://docs.smith.langchain.com/) (but does not require them).
 
+### LangGraph Platform
+
+LangGraph Platform is a commercial solution for deploying agentic applications to production, built on the open-source LangGraph framework.
+Here are some common issues that arise in complex deployments, which LangGraph Platform addresses:
+
+- **Streaming support**: LangGraph Server provides [multiple streaming modes](https://langchain-ai.github.io/langgraph/concepts/streaming) optimized for various application needs
+- **Background runs**: Runs agents asynchronously in the background
+- **Support for long running agents**: Infrastructure that can handle long running processes
+- **[Double texting](https://langchain-ai.github.io/langgraph/concepts/double_texting)**: Handle the case where you get two messages from the user before the agent can respond
+- **Handle burstiness**: Task queue for ensuring requests are handled consistently without loss, even under heavy loads
 
 ## Installation
 
@@ -226,7 +238,7 @@ final_state["messages"][-1].content
 * [How-to Guides](https://langchain-ai.github.io/langgraph/how-tos/): Accomplish specific things within LangGraph, from streaming, to adding memory & persistence, to common design patterns (branching, subgraphs, etc.), these are the place to go if you want to copy and run a specific code snippet.
 * [Conceptual Guides](https://langchain-ai.github.io/langgraph/concepts/high_level/): In-depth explanations of the key concepts and principles behind LangGraph, such as nodes, edges, state and more.
 * [API Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
-* [Cloud (beta)](https://langchain-ai.github.io/langgraph/cloud/): With one click, deploy LangGraph applications to LangGraph Cloud.
+* [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform): LangGraph Platform is a commercial solution for deploying agentic applications in production, built on the open-source LangGraph framework.
 
 ## Contributing
 

docs/_scripts/execute_notebooks.sh

@@ -24,7 +24,7 @@ export -f execute_notebook
 
 # Check if custom notebook paths are provided
 if [ $# -gt 0 ]; then
-    notebooks="$@"
+    notebooks=$(echo "$@" | tr ' ' '\n' | grep -vFf <(echo "$SKIP_NOTEBOOKS"))
 else
     # Find all notebooks and filter out those in the skip list
     notebooks=$(find docs/docs/tutorials docs/docs/how-tos -name "*.ipynb" | grep -v ".ipynb_checkpoints" | grep -vFf <(echo "$SKIP_NOTEBOOKS"))

docs/_scripts/generate_api_reference_links.py

@@ -0,0 +1,246 @@
+import importlib
+import inspect
+import logging
+import os
+import re
+from typing import List, Literal, Optional
+from typing_extensions import TypedDict
+
+import nbformat
+from nbconvert.preprocessors import Preprocessor
+
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+# Base URL for all class documentation
+_LANGCHAIN_API_REFERENCE = "https://python.langchain.com/api_reference/"
+_LANGGRAPH_API_REFERENCE = "https://langchain-ai.github.io/langgraph/reference/"
+
+
+# (alias/re-exported modules, source module, class, docs namespace)
+MANUAL_API_REFERENCES_LANGGRAPH = [
+    (
+        ["langgraph.prebuilt"],
+        "langgraph.prebuilt.chat_agent_executor",
+        "create_react_agent",
+        "prebuilt",
+    ),
+    (["langgraph.prebuilt"], "langgraph.prebuilt.tool_node", "ToolNode", "prebuilt"),
+    (
+        ["langgraph.prebuilt"],
+        "langgraph.prebuilt.tool_node",
+        "tools_condition",
+        "prebuilt",
+    ),
+    (
+        ["langgraph.prebuilt"],
+        "langgraph.prebuilt.tool_node",
+        "InjectedState",
+        "prebuilt",
+    ),
+    # Graph
+    (["langgraph.graph"], "langgraph.graph.message", "add_messages", "graphs"),
+    (["langgraph.graph"], "langgraph.graph.state", "StateGraph", "graphs"),
+    (["langgraph.graph"], "langgraph.graph.state", "CompiledStateGraph", "graphs"),
+    ([], "langgraph.types", "StreamMode", "types"),
+    (["langgraph.graph"], "langgraph.constants", "START", "constants"),
+    (["langgraph.graph"], "langgraph.constants", "END", "constants"),
+    (["langgraph.constants"], "langgraph.types", "Send", "types"),
+    (["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
+    ([], "langgraph.types", "RetryPolicy", "types"),
+    ([], "langgraph.checkpoint.base", "Checkpoint", "checkpoints"),
+    ([], "langgraph.checkpoint.base", "CheckpointMetadata", "checkpoints"),
+    ([], "langgraph.checkpoint.base", "BaseCheckpointSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.base", "SerializerProtocol", "checkpoints"),
+    ([], "langgraph.checkpoint.serde.jsonplus", "JsonPlusSerializer", "checkpoints"),
+    ([], "langgraph.checkpoint.memory", "MemorySaver", "checkpoints"),
+    ([], "langgraph.checkpoint.sqlite.aio", "AsyncSqliteSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.sqlite", "SqliteSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"),
+]
+
+WELL_KNOWN_LANGGRAPH_OBJECTS = {
+    (module_, class_): (source_module, namespace)
+    for (modules, source_module, class_, namespace) in MANUAL_API_REFERENCES_LANGGRAPH
+    for module_ in modules + [source_module]
+}
+
+
+def _make_regular_expression(pkg_prefix: str) -> re.Pattern:
+    if not pkg_prefix.isidentifier():
+        raise ValueError(f"Invalid package prefix: {pkg_prefix}")
+    return re.compile(
+        r"from\s+(" + pkg_prefix + "(?:_\w+)?(?:\.\w+)*?)\s+import\s+"
+        r"((?:\w+(?:,\s*)?)*"  # Match zero or more words separated by a comma+optional ws
+        r"(?:\s*\(.*?\))?)",  # Match optional parentheses block
+        re.DOTALL,  # Match newlines as well
+    )
+
+
+# Regular expression to match langchain import lines
+_IMPORT_LANGCHAIN_RE = _make_regular_expression("langchain")
+_IMPORT_LANGGRAPH_RE = _make_regular_expression("langgraph")
+
+
+def _get_full_module_name(module_path, class_name) -> Optional[str]:
+    """Get full module name using inspect"""
+    try:
+        module = importlib.import_module(module_path)
+        class_ = getattr(module, class_name)
+        module = inspect.getmodule(class_)
+        if module is None:
+            # For constants, inspect.getmodule() might return None
+            # In this case, we'll return the original module_path
+            return module_path
+        return module.__name__
+    except AttributeError as e:
+        logger.warning(f"Could not find module for {class_name}, {e}")
+        return None
+    except ImportError as e:
+        logger.warning(f"Failed to load for class {class_name}, {e}")
+        return None
+
+
+def _get_doc_title(data: str, file_name: str) -> str:
+    try:
+        return re.findall(r"^#\s*(.*)", data, re.MULTILINE)[0]
+    except IndexError:
+        pass
+    # Parse the rst-style titles
+    try:
+        return re.findall(r"^(.*)\n=+\n", data, re.MULTILINE)[0]
+    except IndexError:
+        return file_name
+
+
+class ImportInformation(TypedDict):
+    imported: str  # imported class name
+    source: str  # module path
+    docs: str  # URL to the documentation
+    title: str  # Title of the document
+
+
+def _get_imports(
+    code: str, doc_title: str, package_ecosystem: Literal["langchain", "langgraph"]
+) -> List[ImportInformation]:
+    """Get imports from the given code block.
+
+    Args:
+        code: Python code block from which to extract imports
+        doc_title: Title of the document
+        package_ecosystem: "langchain" or "langgraph". The two live in different
+            repositories and have separate documentation sites.
+
+    Returns:
+        List of import information for the given code block
+    """
+    imports = []
+
+    if package_ecosystem == "langchain":
+        pattern = _IMPORT_LANGCHAIN_RE
+    elif package_ecosystem == "langgraph":
+        pattern = _IMPORT_LANGGRAPH_RE
+    else:
+        raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")
+
+    for import_match in pattern.finditer(code):
+        module = import_match.group(1)
+        if "pydantic_v1" in module:
+            continue
+        imports_str = (
+            import_match.group(2).replace("(\n", "").replace("\n)", "")
+        )  # Handle newlines within parentheses
+        # remove any newline and spaces, then split by comma
+        imported_classes = [
+            imp.strip()
+            for imp in re.split(r",\s*", imports_str.replace("\n", ""))
+            if imp.strip()
+        ]
+        for class_name in imported_classes:
+            module_path = _get_full_module_name(module, class_name)
+            if not module_path:
+                continue
+            if len(module_path.split(".")) < 2:
+                continue
+
+            if package_ecosystem == "langchain":
+                pkg = module_path.split(".")[0].replace("langchain_", "")
+                top_level_mod = module_path.split(".")[1]
+
+                url = (
+                    _LANGCHAIN_API_REFERENCE
+                    + pkg
+                    + "/"
+                    + top_level_mod
+                    + "/"
+                    + module_path
+                    + "."
+                    + class_name
+                    + ".html"
+                )
+            elif package_ecosystem == "langgraph":
+                if (module, class_name) not in WELL_KNOWN_LANGGRAPH_OBJECTS:
+                    # Likely not documented yet
+                    continue
+
+                source_module, namespace = WELL_KNOWN_LANGGRAPH_OBJECTS[
+                    (module, class_name)
+                ]
+                url = (
+                    _LANGGRAPH_API_REFERENCE
+                    + namespace
+                    + "/#"
+                    + source_module
+                    + "."
+                    + class_name
+                )
+            else:
+                raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")
+
+            # Add the import information to our list
+            imports.append(
+                {
+                    "imported": class_name,
+                    "source": module,
+                    "docs": url,
+                    "title": doc_title,
+                }
+            )
+
+    return imports
+
+
+class ImportPreprocessor(Preprocessor):
+    """A preprocessor to replace imports in each Python code cell with links to their
+    documentation and append the import info in a comment."""
+
+    def preprocess(self, nb, resources):
+        self.all_imports = []
+        file_name = os.path.basename(resources.get("metadata", {}).get("name", ""))
+        _DOC_TITLE = _get_doc_title(nb.cells[0].source, file_name)
+
+        cells = []
+        for cell in nb.cells:
+            if cell.cell_type == "code":
+                cells.append(cell)
+                imports = _get_imports(
+                    cell.source, _DOC_TITLE, "langchain"
+                ) + _get_imports(cell.source, _DOC_TITLE, "langgraph")
+                if not imports:
+                    continue
+
+                cells.append(
+                    nbformat.v4.new_markdown_cell(
+                        source=f"""
+<div>
+<b>API Reference:</b>
+{' | '.join(f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports)}
+</div>
+                    """
+                    )
+                )
+            else:
+                cells.append(cell)
+        nb.cells = cells
+        return nb, resources

docs/_scripts/notebook_convert.py

@@ -0,0 +1,126 @@
+import os
+import re
+from pathlib import Path
+
+import nbformat
+from nbconvert.exporters import MarkdownExporter
+from nbconvert.preprocessors import Preprocessor
+
+from generate_api_reference_links import ImportPreprocessor
+
+
+class EscapePreprocessor(Preprocessor):
+    def preprocess_cell(self, cell, resources, cell_index):
+        if cell.cell_type == "markdown":
+            # rewrite markdown links to html links (excluding image links)
+            cell.source = re.sub(
+                r"(?<!!)\[([^\]]*)\]\((?![^\)]*//)([^)]*)(?:\.ipynb)?\)",
+                r'<a href="\2">\1</a>',
+                cell.source,
+            )
+            # Fix image paths in <img> tags
+            cell.source = re.sub(
+                r'<img\s+src="\.?/img/([^"]+)"', r'<img src="../img/\1"', cell.source
+            )
+
+        elif cell.cell_type == "code":
+            # escape ``` in code
+            cell.source = cell.source.replace("```", r"\`\`\`")
+            # escape ``` in output
+            if "outputs" in cell:
+                filter_out = set()
+                for i, output in enumerate(cell["outputs"]):
+                    if "text" in output:
+                        if not output["text"].strip():
+                            filter_out.add(i)
+                            continue
+
+                        value = output["text"].replace("```", r"\`\`\`")
+                        # handle a funky case w/ references in text
+                        value = re.sub(r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value)
+                        output["text"] = value
+                    elif "data" in output:
+                        for key, value in output["data"].items():
+                            if isinstance(value, str):
+                                value = value.replace("```", r"\`\`\`")
+                                # handle a funky case w/ references in text
+                                output["data"][key] = re.sub(
+                                    r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value
+                                )
+                cell["outputs"] = [
+                    output
+                    for i, output in enumerate(cell["outputs"])
+                    if i not in filter_out
+                ]
+
+        return cell, resources
+
+
+class ExtractAttachmentsPreprocessor(Preprocessor):
+    """
+    Extracts all of the outputs from the notebook file.  The extracted
+    outputs are returned in the 'resources' dictionary.
+    """
+
+    def preprocess_cell(self, cell, resources, cell_index):
+        """
+        Apply a transformation on each cell,
+        Parameters
+        ----------
+        cell : NotebookNode cell
+            Notebook cell being processed
+        resources : dictionary
+            Additional resources used in the conversion process.  Allows
+            preprocessors to pass variables into the Jinja engine.
+        cell_index : int
+            Index of the cell being processed (see base.py)
+        """
+
+        # Get files directory if it has been specified
+
+        # Make sure outputs key exists
+        if not isinstance(resources["outputs"], dict):
+            resources["outputs"] = {}
+
+        # Loop through all of the attachments in the cell
+        for name, attach in cell.get("attachments", {}).items():
+            for mime, data in attach.items():
+                if mime not in {
+                    "image/png",
+                    "image/jpeg",
+                    "image/svg+xml",
+                    "application/pdf",
+                }:
+                    continue
+
+                # attachments are pre-rendered. Only replace markdown-formatted
+                # images with the following logic
+                attach_str = f"({name})"
+                if attach_str in cell.source:
+                    data = f"(data:{mime};base64,{data})"
+                    cell.source = cell.source.replace(attach_str, data)
+
+        return cell, resources
+
+
+exporter = MarkdownExporter(
+    preprocessors=[
+        EscapePreprocessor,
+        ExtractAttachmentsPreprocessor,
+        ImportPreprocessor,
+    ],
+    template_name="mdoutput",
+    extra_template_basedirs=[
+        os.path.join(os.path.dirname(__file__), "notebook_convert_templates")
+    ],
+)
+
+
+def convert_notebook(
+    notebook_path: Path,
+) -> Path:
+    with open(notebook_path) as f:
+        nb = nbformat.read(f, as_version=4)
+
+    body, _ = exporter.from_notebook_node(nb)
+    return body

docs/_scripts/notebook_convert_templates/mdoutput/conf.json

@@ -0,0 +1,5 @@
+{
+  "mimetypes": {
+    "text/markdown": true
+  }
+}

docs/_scripts/notebook_convert_templates/mdoutput/index.md.j2

@@ -0,0 +1,33 @@
+{% extends 'markdown/index.md.j2' %}
+
+{%- block traceback_line -%}
+```output
+{{ line.rstrip() | strip_ansi }}
+```
+{%- endblock traceback_line -%}
+
+{%- block stream -%}
+```output
+{{ output.text.rstrip() }}
+```
+{%- endblock stream -%}
+
+{%- block data_text scoped -%}
+```output
+{{ output.data['text/plain'].rstrip() }}
+```
+{%- endblock data_text -%}
+
+{%- block data_html scoped -%}
+```html
+{{ output.data['text/html'] | safe }} 
+```
+{%- endblock data_html -%}
+
+{%- block data_jpg scoped -%}
+![](data:image/jpg;base64,{{ output.data['image/jpeg'] }})
+{%- endblock data_jpg -%}
+
+{%- block data_png scoped -%}
+![](data:image/png;base64,{{ output.data['image/png'] }})
+{%- endblock data_png -%}

docs/_scripts/notebook_hooks.py

@@ -0,0 +1,40 @@
+import logging
+from typing import Any, Dict
+
+from mkdocs.structure.pages import Page
+from mkdocs.structure.files import Files, File
+from notebook_convert import convert_notebook
+
+logger = logging.getLogger(__name__)
+logging.basicConfig()
+logger.setLevel(logging.INFO)
+
+
+class NotebookFile(File):
+    def is_documentation_page(self):
+        return True
+
+
+def on_files(files: Files, **kwargs: Dict[str, Any]):
+    new_files = Files([])
+    for file in files:
+        if file.src_path.endswith(".ipynb"):
+            new_file = NotebookFile(
+                path=file.src_path,
+                src_dir=file.src_dir,
+                dest_dir=file.dest_dir,
+                use_directory_urls=file.use_directory_urls,
+            )
+            new_files.append(new_file)
+        else:
+            new_files.append(file)
+    return new_files
+
+
+def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
+    if page.file.src_path.endswith(".ipynb"):
+        logger.info("Processing Jupyter notebook: %s", page.file.src_path)
+        body = convert_notebook(page.file.abs_src_path)
+        return body
+
+    return markdown

docs/_scripts/prepare_notebooks_for_ci.py

@@ -36,11 +36,11 @@ NOTEBOOKS_NO_EXECUTION = [
     "docs/docs/tutorials/rag/langgraph_self_rag_local.ipynb",
     # this loads a massive dataset from gcp
     "docs/docs/tutorials/usaco/usaco.ipynb",
+    # TODO: figure out why autogen notebook is not runnable (they are just hanging. possible due to code execution?)
+    "docs/docs/how-tos/autogen-integration.ipynb",
     # TODO: need to update these notebooks to make sure they are runnable in CI
     "docs/docs/tutorials/storm/storm.ipynb",  # issues only when running with VCR
     "docs/docs/tutorials/lats/lats.ipynb",  # issues only when running with VCR
-    "docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb",  # taking a very long time to run
-    "docs/docs/tutorials/customer-support/customer-support.ipynb",  # user input - update
     "docs/docs/tutorials/rag/langgraph_crag.ipynb",  # flakiness from tavily
     "docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb",  # Cannot create a consistent method resolution error from VCR
     "docs/docs/how-tos/map-reduce.ipynb"  # flakiness from structured output, only when running with VCR
@@ -70,10 +70,13 @@ def is_comment(code: str) -> bool:
     return code.strip().startswith("#")
 
 
-def has_blocklisted_command(code: str) -> bool:
+def has_blocklisted_command(code: str, metadata: dict) -> bool:
+    if 'hide_from_vcr' in metadata:
+        return True
+    
     code = code.strip()
-    for blocklisted_command in BLOCKLIST_COMMANDS:
-        if blocklisted_command in code:
+    for blocklisted_pattern in BLOCKLIST_COMMANDS:
+        if blocklisted_pattern in code:
             return True
     return False
 
@@ -108,7 +111,7 @@ def add_vcr_to_notebook(
         if all(is_comment(line) or not line.strip() for line in lines):
             continue
 
-        if has_blocklisted_command(cell.source):
+        if has_blocklisted_command(cell.source, cell.metadata):
             continue
 
         cell_id = cell.get("id", idx)
@@ -125,6 +128,8 @@ def add_vcr_to_notebook(
         "import msgpack",
         "import base64",
         "import zlib",
+        "import os",
+        "os.environ.pop(\"LANGCHAIN_TRACING_V2\", None)",
         "custom_vcr = vcr.VCR()",
         "",
         "def compress_data(data, compression_level=9):",

docs/cassettes/pass-run-time-values-to-tools_2e3fd1e2-cc19-4023-8ffa-b0fc13da9e09.msgpack.zlib

@@ -0,0 +1 @@
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

docs/cassettes/pass-run-time-values-to-tools_8edb04b9-40b6-46f1-a7a8-4b2d8aba7752.msgpack.zlib

@@ -1 +0,0 @@
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docs/cassettes/shared-state_f9bf2c15.msgpack.zlib

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docs/docs/cloud/concepts/api.md

@@ -1,216 +0,0 @@
-# API Concepts
-
-This page describes the high-level concepts of the LangGraph Cloud API. The conceptual guide of LangGraph (Python library) is [here](../../concepts/high_level.md).
-
-## Data Models
-
-The LangGraph Cloud API consists of a few core data models: [Assistants](#assistants), [Threads](#threads), [Runs](#runs), and [Cron Jobs](#cron-jobs).
-
-### Assistants
-
-When building agents, it is fairly common to make rapid changes that *do not* alter the graph logic. For example, simply changing prompts or the LLM selection can have significant impacts on the behavior of the agents. Assistants offer an easy way to make and save these types of changes to agent configuration. This can have at least two use-cases:
-
-* Assistants give developers a quick and easy way to modify and version graph version for experimentation.
-* Assistants can be modified via LangGraph Studio, offering a no-code way to configure agents  (e.g., for business users). 
-
-#### Configuring Assistants
-
-In practice, an assistant is just an *instance* of a graph with a specific configuration. Because of this, multiple assistants can reference the same graph but can contain different configurations, such as prompts, models, and other graph configuration options. The LangGraph Cloud API provides several endpoints for creating and managing assistants. See the [API reference](../reference/api/api_ref.html#tag/assistantscreate) and [this how-to](../how-tos/configuration_cloud.md) for more details on how to create assistants.
-
-#### Versioning Assistants
-
-![assistant versions](./assistant_version.png)
-
-Once you've created an assistant, you can save and version it to track changes to the configuration over time. You can think about this at three levels:
-
-1) The graph lays out the general agent application logic 
-2) The agent configuration options represent parameters that can be changed 
-3) Assistant versions save and track specific settings of the agent configuration options 
-
-For example, if you have an agent that helps for planning trips, you can create a new assistant *for each user* that passes specific user preferences (e.g., desired airline and car service). As each user interacts with their own assistant, assistant versions can be saved that track the specific desires of the user. Read [this how-to](../how-tos/assistant_versioning.md) to learn how you can use assistant versioning through both the [Studio](../how-tos/index.md/#langgraph-studio) and the SDK.
-
-### Threads
-
-A thread contains the accumulated state of a group of runs. If a run is executed on a thread, then the [state][state] of the underlying graph of the assistant will be persisted to the thread. A thread's current and historical state can be retrieved. To persist state, a thread must be created prior to executing a run.
-
-The state of a thread at a particular point in time is called a checkpoint.
-
-For more on threads and checkpoints, see this section of the [LangGraph conceptual guide](../../concepts/low_level.md#persistence).
-
-The LangGraph Cloud API provides several endpoints for creating and managing threads and thread state. See the [API reference](../reference/api/api_ref.html#tag/threadscreate) for more details.
-
-### Runs
-
-A run is an invocation of an assistant. Each run may have its own input, configuration, and metadata, which may affect execution and output of the underlying graph. A run can optionally be executed on a thread.
-
-The LangGraph Cloud API provides several endpoints for creating and managing runs. See the [API reference](../reference/api/api_ref.html#tag/runscreate) for more details.
-
-### Cron Jobs
-
-It's often useful to run graphs on some schedule. LangGraph Cloud supports cron jobs, which run on a user defined schedule. The user specifies a schedule, an assistant, and some input. After than, on the specified schedule LangGraph cloud will:
-
-- Create a new thread with the specified assistant
-- Send the specified input to that thread
-
-Note that this sends the same input to the thread every time. See the [how-to guide](../how-tos/cron_jobs.md) for creating cron jobs.
-
-The LangGraph Cloud API provides several endpoints for creating and managing cron jobs. See the [API reference](../reference/api/api_ref.html#tag/runscreate/POST/threads/{thread_id}/runs/crons) for more details.
-
-## Features
-
-The LangGraph Cloud API offers several features to support complex agent architectures.
-
-### Streaming
-
-Streaming is critical for making LLM applications feel responsive to end users. When creating a streaming run, the streaming mode determines what data is streamed back to the API client. The LangGraph Cloud API supports five streaming modes.
-
-- `values`: Stream the full state of the graph after each [super-step](https://langchain-ai.github.io/langgraph/concepts/low_level/#graphs) is executed. See the [how-to guide](../how-tos/stream_values.md) for streaming values.
-- `messages`: Stream complete messages (at the end of node execution) as well as tokens for any messages generated inside a node. This mode is primarily meant for powering chat applications. This is only an option if your graph contains a `messages` key. See the [how-to guide](../how-tos/stream_messages.md) for streaming messages.
-- `updates`: Streams updates to the state of the graph after each node is executed. See the [how-to guide](../how-tos/stream_updates.md) for streaming updates.
-- `events`: Stream all events (including the state of the graph) that occur during graph execution. See the [how-to guide](../how-tos/stream_events.md) for streaming events. This can be used to do token-by-token streaming for LLMs.
-- `debug`: Stream debug events throughout graph execution. See the [how-to guide](../how-tos/stream_debug.md) for streaming debug events.
-
-You can also specify multiple streaming modes at the same time. See the [how-to guide](../how-tos/stream_multiple.md) for configuring multiple streaming modes at the same time.
-
-See the [API reference](../reference/api/api_ref.html#tag/runscreate/POST/threads/{thread_id}/runs/stream) for how to create streaming runs.
-
-Streaming modes `values`, `updates`, and `debug` are very similar to modes available in the LangGraph library - for a deeper conceptual explanation of those, you can see the LangGraph library documentation [here](../../concepts/low_level.md#streaming).
-
-Streaming mode `events` is the same as using `.astream_events` in the LangGraph library - for a deeper conceptual explanation of this, you can see the LangGraph library documentation [here](../../concepts/low_level.md#streaming).
-
-#### `mode="messages"`
-Streaming mode `messages` is a new streaming mode, currently only available in the API. What does this mode enable?
-
-This mode is focused on streaming back messages. It currently assumes that you have a `messages` key in your graph that is a list of messages. Assuming we have a simple react agent deployed, what does this stream look like?
-
-All events emitted have two attributes:
-
-- `event`: This is the name of the event
-- `data`: This is data associated with the event
-
-Let's run it on a question that should trigger a tool call:
-
-```python
-thread = await client.threads.create()
-input = {"messages": [{"role": "user", "content": "what's the weather in sf?"}]}
-
-events = []
-async for event in client.runs.stream(
-    thread["thread_id"],
-    assistant_id="agent",  # This may need to change depending on the graph you deployed
-    input=input,
-    stream_mode="messages",
-):
-    print(event.event)
-```
-```shell
-metadata
-messages/complete
-messages/metadata
-messages/partial
-...
-messages/partial
-messages/complete
-messages/complete
-messages/metadata
-messages/partial
-...
-messages/partial
-messages/complete
-end
-```
-
-We first get some `metadata` - this is metadata about the run. 
-
-```python
-StreamPart(event='metadata', data={'run_id': '1ef657cf-ae55-6f65-97d4-f4ed1dbdabc6'})
-```
-
-We then get a `messages/complete` event - this a fully formed message getting emitted. In this case,
-this was the just the input message we sent in. 
-
-```python
-StreamPart(event='messages/complete', data=[{'content': 'hi!', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '833c09a3-bb19-46c9-81d9-1e5954ec5f92', 'example': False}])
-```
-
-We then get a `messages/metadata` - this is just letting us know that a new message is starting.
-
-```python
-StreamPart(event='messages/metadata', data={'run-985c0f14-9f43-40d4-a505-4637fc58e333': {'metadata': {'created_by': 'system', 'run_id': '1ef657de-7594-66df-8eb2-31518e4a1ee2', 'graph_id': 'agent', 'thread_id': 'c178eab5-e293-423c-8e7d-1d113ffe7cd9', 'model_name': 'openai', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca', 'langgraph_step': 1, 'langgraph_node': 'agent', 'langgraph_triggers': ['start:agent'], 'langgraph_task_idx': 0, 'ls_provider': 'openai', 'ls_model_name': 'gpt-4o', 'ls_model_type': 'chat', 'ls_temperature': 0.0}}})
-```
-
-We then get a BUNCH of `messages/partial` events - these are the individual tokens from the LLM! In the case below, we can see the START of a tool call.
-
-```python
-StreamPart(event='messages/partial', data=[{'content': '', 'additional_kwargs': {'tool_calls': [{'index': 0, 'id': 'call_w8Hr8dHGuZCPgRfd5FqRBArs', 'function': {'arguments': '', 'name': 'tavily_search_results_json'}, 'type': 'function'}]}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-985c0f14-9f43-40d4-a505-4637fc58e333', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [{'name': 'tavily_search_results_json', 'args': '', 'id': 'call_w8Hr8dHGuZCPgRfd5FqRBArs', 'error': None}], 'usage_metadata': None}])
-```
-
-After that, we get a `messages/complete` event - this is the AIMessage finishing. It's now a complete tool call:
-
-```python
-StreamPart(event='messages/complete', data=[{'content': '', 'additional_kwargs': {'tool_calls': [{'index': 0, 'id': 'call_w8Hr8dHGuZCPgRfd5FqRBArs', 'function': {'arguments': '{"query":"current weather in San Francisco"}', 'name': 'tavily_search_results_json'}, 'type': 'function'}]}, 'response_metadata': {'finish_reason': 'tool_calls', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_157b3831f5'}, 'type': 'ai', 'name': None, 'id': 'run-985c0f14-9f43-40d4-a505-4637fc58e333', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'current weather in San Francisco'}, 'id': 'call_w8Hr8dHGuZCPgRfd5FqRBArs'}], 'invalid_tool_calls': [], 'usage_metadata': None}])
-```
-
-After that, we get ANOTHER `messages/complete` event. This is a tool message - our agent has called a tool, gotten a response, and now inserting it into the state in the form of a tool message.
-
-```python
-StreamPart(event='messages/complete', data=[{'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'San Francisco\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 37.78, \'lon\': -122.42, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1724877689, \'localtime\': \'2024-08-28 13:41\'}, \'current\': {\'last_updated_epoch\': 1724877000, \'last_updated\': \'2024-08-28 13:30\', \'temp_c\': 23.3, \'temp_f\': 73.9, \'is_day\': 1, \'condition\': {\'text\': \'Partly cloudy\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/116.png\', \'code\': 1003}, \'wind_mph\': 15.0, \'wind_kph\': 24.1, \'wind_degree\': 310, \'wind_dir\': \'NW\', \'pressure_mb\': 1014.0, \'pressure_in\': 29.93, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 57, \'cloud\': 25, \'feelslike_c\': 25.0, \'feelslike_f\': 77.1, \'windchill_c\': 20.9, \'windchill_f\': 69.6, \'heatindex_c\': 23.3, \'heatindex_f\': 74.0, \'dewpoint_c\': 12.9, \'dewpoint_f\': 55.2, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 6.0, \'gust_mph\': 19.5, \'gust_kph\': 31.3}}"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '0112eba5-7660-4375-9f24-c7a1d6777b97', 'tool_call_id': 'call_w8Hr8dHGuZCPgRfd5FqRBArs'}])
-```
-
-After that, we see the agent doing another LLM call and streaming back a response. We then get an `end` event:
-
-```python
-StreamPart(event='end', data=None)
-```
-
-And that's it! This is more focused streaming mode specifically focused on streaming back messages. See this [how-to guide](../how-tos/stream_messages.md) for more information.
-
-
-### Human-in-the-Loop
-
-There are many occasions where the graph cannot run completely autonomously. For instance, the user might need to input some additional arguments to a function call, or select the next edge for the graph to continue on. In these instances, we need to insert some human in the loop interaction, which you can learn about in the [human in the loop how-tos](../how-tos/index.md#human-in-the-loop).
-
-### Double Texting
-
-Many times users might interact with your graph in unintended ways. For instance, a user may send one message and before the graph has finished running send a second message. To solve this issue of "double-texting" (i.e. prompting the graph a second time before the first run has finished), LangGraph has provided four different solutions, all of which are covered in the [Double Texting how-tos](../how-tos/index.md#double-texting). These options are:
-
-- `reject`: This is the simplest option, this just rejects any follow up runs and does not allow double texting. See the [how-to guide](../how-tos/reject_concurrent.md) for configuring the reject double text option.
-- `enqueue`: This is a relatively simple option which continues the first run until it completes the whole run, then sends the new input as a separate run. See the [how-to guide](../how-tos/enqueue_concurrent.md) for configuring the enqueue double text option.
-- `interrupt`: This option interrupts the current execution but saves all the work done up until that point. It then inserts the user input and continues from there. If you enable this option, your graph should be able to handle weird edge cases that may arise. See the [how-to guide](../how-tos/interrupt_concurrent.md) for configuring the interrupt double text option.
-- `rollback`: This option rolls back all work done up until that point. It then sends the user input in, basically as if it just followed the original run input. See the [how-to guide](../how-tos/rollback_concurrent.md) for configuring the rollback double text option.
-
-### Stateless Runs
-
-All runs use the built-in checkpointer to store checkpoints for runs. However, it can often be useful to just kick off a run without worrying about explicitly creating a thread and without wanting to keep those checkpointers around. Stateless runs allow you to do this by exposing an endpoint that:
-
-- Takes in user input
-- Under the hood, creates a thread
-- Runs the agent but skips all checkpointing steps
-- Cleans up the thread afterwards
-
-Stateless runs are still retried as regular retries are per node, while everything still in memory, so doesn't use checkpoints.
-
-The only difference is in stateless background runs, if the task worker dies halfway (not because the run itself failed, for some external reason) then the whole run will be retried like any background run, but
-
-- whereas a stateful background run would retry from the last successful checkpoint
-- a stateless background run would retry from the beginning
-
-See the [how-to guide](../how-tos/stateless_runs.md) for creating stateless runs.
-
-### Webhooks
-
-For all types of runs, langgraph cloud supports completion webhooks. When you create the run you can pass a webhook URL to be called when the completes (successfully or not). This is especially useful for background runs and cron jobs, as the webhook can give you an indication the run has completed and you can perform further actions for your appilcation.
-
-See this [how-to guide](../how-tos/webhooks.md) to learn about how to use webhooks with LangGraph Cloud.
-
-## Deployment
-
-The LangGraph Cloud offers several features to support secure and robost deployments.
-
-### Authentication
-
-LangGraph applications deployed to LangGraph Cloud are automatically configured with LangSmith authentication. In order to call the API, a valid <a href="https://docs.smith.langchain.com/how_to_guides/setup/create_account_api_key#api-keys" target="_blank">LangSmith API key</a> is required.
-
-### Local Testing
-
-Before deploying your app in production to LangGraph Cloud, you may wish to test out your graph locally in order to ensure that everything is running as expected. Luckily, LangGraph makes this easy for you through use of the LangGraph CLI. Read more in this [how-to guide](../deployment/test_locally.md) or look at the [CLI reference](../reference/cli.md) to learn more.

docs/docs/cloud/concepts/cloud.md

@@ -1,28 +0,0 @@
-# Cloud Concepts
-
-This page describes the high-level concepts of the LangGraph Cloud deployment.
-
-## Deployment
-
-A deployment is an instance of a LangGraph API. A single deployment can have many [revisions](#revision). When a deployment is created, all of the necessary infrastructure (e.g. database, containers, secrets store) are automatically provisioned. See the [architecture diagram](#architecture) below for more details.
-
-See the [how-to guide](../deployment/cloud.md#create-new-deployment) for creating a new deployment.
-
-## Revision
-
-A revision is an iteration of a [deployment](#deployment). When a new deployment is created, an initial revision is automatically created. To deploy new code changes or update environment variable configurations for a deployment, a new revision must be created. When a revision is created, a new container image is built automatically.
-
-See the [how-to guide](../deployment/cloud.md#create-new-revision) for creating a new revision.
-
-## Asynchronous Deployment
-
-Infrastructure for [deployments](#deployment) and [revisions](#revision) are provisioned and deployed asynchronously. They are not deployed immediately after submission. Currently, deployment can take up to several minutes.
-
-## Architecture
-
-!!! warning "Subject to Change"
-    The LangGraph Cloud deployment architecture may change in the future.
-
-A high-level diagram of a LangGraph Cloud deployment.
-
-![diagram](langgraph_cloud_architecture.png)

docs/docs/cloud/deployment/cloud.md

@@ -11,7 +11,7 @@ LangGraph Cloud is available within <a href="https://www.langchain.com/langsmith
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `Deployments`. The `Deployments` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
 1. In the top-right corner, select `+ New Deployment` to create a new deployment.
 1. In the `Create New Deployment` panel, fill out the required fields.
     1. `Deployment details`
@@ -38,7 +38,7 @@ When [creating a new deployment](#create-new-deployment), a new revision is crea
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `Deployments`. The `Deployments` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
 1. Select an existing deployment to create a new revision for.
 1. In the `Deployment` view, in the top-right corner, select `+ New Revision`.
 1. In the `New Revision` modal, fill out the required fields.
@@ -56,7 +56,7 @@ Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmi
 
 Build and deployment logs are available for each revision.
 
-Starting from the `Deployment` view...
+Starting from the `LangGraph Cloud` view...
 
 1. Select the desired revision from the `Revisions` table. A panel slides open from the right-hand side and the `Build` tab is selected by default, which displays build logs for the revision.
 1. In the panel, select the `Deploy` tab to view deployment logs for the revision.
@@ -69,7 +69,7 @@ Interrupting a revision will stop deployment of the revision.
 !!! warning "Undefined Behavior"
     Interrupted revisions have undefined behavior. This is only useful if you need to deploy a new revision and you already have a revision "stuck" in progress. In the future, this feature may be removed.
 
-Starting from the `Deployment` view...
+Starting from the `LangGraph Cloud` view...
 
 1. Select the menu icon (three dots) on the right-hand side of the row for the desired revision from the `Revisions` table.
 1. Select `Interrupt` from the menu.
@@ -79,13 +79,13 @@ Starting from the `Deployment` view...
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `Deployments`. The `Deployments` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
 1. Select the menu icon (three dots) on the right-hand side of the row for the desired deployment and select `Delete`.
 1. A `Confirmation` modal will appear. Select `Delete`.
 
 ## Deployment Settings
 
-Starting from the `Deployment` view...
+Starting from the `LangGraph Cloud` view...
 
 1. In the top-right corner, select the gear icon (`Deployment Settings`).
 1. Update the `Git Branch` to the desired branch.

docs/docs/cloud/deployment/semantic_search.md

@@ -0,0 +1,123 @@
+# How to add semantic search to your LangGraph deployment
+
+This guide explains how to add semantic search to your LangGraph deployment's cross-thread [store](../../concepts/persistence.md#memory-store), so that your agent can search for memories and other documents by semantic similarity.
+
+## Prerequisites
+
+- A LangGraph deployment (see [how to deploy](setup_pyproject.md))
+- API keys for your embedding provider (in this case, OpenAI)
+- `langchain >= 0.3.8` (if you specify using the string format below)
+
+## Steps
+
+1. Update your `langgraph.json` configuration file to include the store configuration:
+
+```json
+{
+    ...
+    "store": {
+        "index": {
+            "embed": "openai:text-embeddings-3-small",
+            "dims": 1536,
+            "fields": ["$"]
+        }
+    }
+}
+```
+
+This configuration:
+
+- Uses OpenAI's text-embeddings-3-small model for generating embeddings
+- Sets the embedding dimension to 1536 (matching the model's output)
+- Indexes all fields in your stored data (`["$"]` means index everything, or specify specific fields like `["text", "metadata.title"]`)
+
+2. To use the string embedding format above, make sure your dependencies include `langchain >= 0.3.8`:
+
+```toml
+# In pyproject.toml
+[project]
+dependencies = [
+    "langchain>=0.3.8"
+]
+```
+
+Or if using requirements.txt:
+
+```
+langchain>=0.3.8
+```
+
+## Usage
+
+Once configured, you can use semantic search in your LangGraph nodes. The store requires a namespace tuple to organize memories:
+
+```python
+def search_memory(state: State, *, store: BaseStore):
+    # Search the store using semantic similarity
+    # The namespace tuple helps organize different types of memories
+    # e.g., ("user_facts", "preferences") or ("conversation", "summaries")
+    results = store.search(
+        namespace=("memory", "facts"),  # Organize memories by type
+        query="your search query",
+        limit=3  # number of results to return
+    )
+    return results
+```
+
+## Custom Embeddings
+
+If you want to use custom embeddings, you can pass a path to a custom embedding function:
+
+```json
+{
+    ...
+    "store": {
+        "index": {
+            "embed": "path/to/embedding_function.py:embed",
+            "dims": 1536,
+            "fields": ["$"]
+        }
+    }
+}
+```
+
+The deployment will look for the function in the specified path. The function must be async and accept a list of strings:
+
+```python
+# path/to/embedding_function.py
+from openai import AsyncOpenAI
+
+client = AsyncOpenAI()
+
+async def aembed_texts(texts: list[str]) -> list[list[float]]:
+    """Custom embedding function that must:
+    1. Be async
+    2. Accept a list of strings
+    3. Return a list of float arrays (embeddings)
+    """
+    response = await client.embeddings.create(
+        model="text-embedding-3-small",
+        input=texts
+    )
+    return [e.embedding for e in response.data]
+```
+
+## Querying via the API
+
+You can also query the store using the LangGraph SDK. Since the SDK uses async operations:
+
+```python
+from langgraph_sdk import get_client
+
+async def search_store():
+    client = get_client()
+    results = await client.store.search_items(
+        ("memory", "facts"),
+        query="your search query",
+        limit=3  # number of results to return
+    )
+    return results
+
+# Use in an async context
+results = await search_store()
+```

docs/docs/cloud/deployment/test_locally.md

@@ -8,19 +8,25 @@ Testing locally ensures that there are no errors or conflicts with Python depend
 
 Install the proper packages:
 
-```shell
-pip install langgraph-cli
-```
 
-Ensure you have an API key, which you can create from the LangSmith UI (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:
+=== "pip" 
+    ```bash
+    pip install -U langgraph-cli
+    ```
+=== "Homebrew (macOS only)"
+    ```bash
+    brew install langgraph-cli
+    ```
+
+Ensure you have an API key, which you can create from the [LangSmith UI](https://smith.langchain.com) (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:
 
 ```python
-LANGCHAIN_API_KEY = *********
+LANGSMITH_API_KEY = *********
 ```
 
 ## Start the API server
 
-Once you have downloaded the CLI, you can run the following command to start the API server for local testing:
+Once you have installed the CLI, you can run the following command to start the API server for local testing:
 
 ```shell
 langgraph up
@@ -48,7 +54,7 @@ You can either initialize by passing authentication or by setting an environment
     from langgraph_sdk import get_client
 
     # only pass the url argument to get_client() if you changed the default port when calling langgraph up
-    client = get_client(url=<DEPLOYMENT_URL>,api_key=<LANGCHAIN_API_KEY>)
+    client = get_client(url=<DEPLOYMENT_URL>,api_key=<LANGSMITH_API_KEY>)
     # Using the graph deployed with the name "agent"
     assistant_id = "agent"
     thread = await client.threads.create()
@@ -60,7 +66,7 @@ You can either initialize by passing authentication or by setting an environment
     import { Client } from "@langchain/langgraph-sdk";
 
     // only set the apiUrl if you changed the default port when calling langgraph up
-    const client = new Client({ apiUrl: <DEPLOYMENT_URL>, apiKey: <LANGCHAIN_API_KEY> });
+    const client = new Client({ apiUrl: <DEPLOYMENT_URL>, apiKey: <LANGSMITH_API_KEY> });
     // Using the graph deployed with the name "agent"
     const assistantId = "agent";
     const thread = await client.threads.create();
@@ -72,13 +78,13 @@ You can either initialize by passing authentication or by setting an environment
     curl --request POST \
       --url <DEPLOYMENT_URL>/threads \
       --header 'Content-Type: application/json'
-      --header 'x-api-key: <LANGCHAIN_API_KEY>'
+      --header 'x-api-key: <LANGSMITH_API_KEY>'
     ```
   
 
 #### Initialize with environment variables
 
-If you have a `LANGCHAIN_API_KEY` set in your environment, you do not need to explicitly pass authentication to the client
+If you have a `LANGSMITH_API_KEY` set in your environment, you do not need to explicitly pass authentication to the client
 
 === "Python"
 
@@ -148,7 +154,7 @@ Now we can invoke our graph to ensure it is working. Make sure to change the inp
     }
     ```
 
-  === "CURL"
+=== "CURL"
 
     ```bash
     curl --request POST \
@@ -183,4 +189,4 @@ Now we can invoke our graph to ensure it is working. Make sure to change the inp
      ' 
     ```
 
-If your graph works correctly, you should see your graph output displayed in the console. Of course, there are many more ways you might need to test your graph, for a full list of commands you can send with the SDK, see the [Python](https://langchain-ai.github.io/langgraph/cloud/reference/sdk/python_sdk_ref/) and [JS/TS](https://langchain-ai.github.io/langgraph/cloud/reference/sdk/js_ts_sdk_ref/) references.
+If your graph works correctly, you should see your graph output displayed in the console. Of course, there are many more ways you might need to test your graph, for a full list of commands you can send with the SDK, see the [Python](https://langchain-ai.github.io/langgraph/cloud/reference/sdk/python_sdk_ref/) and [JS/TS](https://langchain-ai.github.io/langgraph/cloud/reference/sdk/js_ts_sdk_ref/) references.

docs/docs/cloud/how-tos/assistant_versioning.md

@@ -1,6 +1,6 @@
 # How to version assistants
 
-In this how-to guide we will walk through how you can create and manage different assistant versions. If you haven't already, you can read [this](../concepts/api.md/#versioning-assistants) conceptual guide to gain a better understanding of what assistant versioning is. This how-to assumes you have a graph that is configurable, which means you have defined a config schema and passed it to your graph as follows:
+In this how-to guide we will walk through how you can create and manage different assistant versions. If you haven't already, you can read [this](../../concepts/assistants.md#versioning-assistants) conceptual guide to gain a better understanding of what assistant versioning is. This how-to assumes you have a graph that is configurable, which means you have defined a config schema and passed it to your graph as follows:
 
 === "Python"
 
@@ -86,19 +86,19 @@ To create an assistant using the studio do the following steps:
 
 1. Click on the "Create New Assistant" button:
 
-![click create](./img/click_create_assistant.png)
+    ![click create](./img/click_create_assistant.png)
 
-2. Use the create assistant pane to enter info for the assistant you wish to create, and then click create:
+1. Use the create assistant pane to enter info for the assistant you wish to create, and then click create:
 
-![create](./img/create_assistant.png)
+    ![create](./img/create_assistant.png)
 
-3. See that your assistant was created and is displayed in the Studio
+1. See that your assistant was created and is displayed in the Studio
 
-![view create](./img/create_assistant_view.png)
+    ![view create](./img/create_assistant_view.png)
 
-4. Click on the edit button next to the selected assistant to manage your created assistant:
+1. Click on the edit button next to the selected assistant to manage your created assistant:
 
-![create edit](./img/edit_created_assistant.png)
+    ![create edit](./img/edit_created_assistant.png)
 
 ## Create a new version for your assistant
 
@@ -131,15 +131,15 @@ Let's now say we wanted to add a system prompt to our assistant. We can do this
 
 1. First, click on the edit button next to the `openai_assistant`. Then, add a system prompt and click "Save New Version":
 
-![create new version](./img/create_new_version.png)
+    ![create new version](./img/create_new_version.png)
 
-2. Then you can see it is selected in the assistant dropdown:
+1. Then you can see it is selected in the assistant dropdown:
 
-![see version dropdown](./img/see_new_version.png)
+    ![see version dropdown](./img/see_new_version.png)
 
-3. And you can see all the version history in the edit pane for the assistant:
+1. And you can see all the version history in the edit pane for the assistant:
 
-![see versions](./img/see_version_history.png)
+    ![see versions](./img/see_version_history.png)
 
 ## Point your assistant to a different version
 

docs/docs/cloud/how-tos/configuration_cloud.md

@@ -83,7 +83,7 @@ We can now call `.get_schemas` to get schemas associated with this graph:
         assistant_id=assistant["assistant_id"]
     )
     # There are multiple types of schemas
-    # We can get the `config_schema` to look at the the configurable parameters
+    # We can get the `config_schema` to look at the configurable parameters
     print(schemas["config_schema"])
     ```
 
@@ -94,7 +94,7 @@ We can now call `.get_schemas` to get schemas associated with this graph:
       assistant["assistant_id"]
     );
     // There are multiple types of schemas
-    // We can get the `config_schema` to look at the the configurable parameters
+    // We can get the `config_schema` to look at the configurable parameters
     console.log(schemas.config_schema);
     ```
 

docs/docs/cloud/how-tos/copy_threads.md

@@ -4,7 +4,7 @@ You may wish to copy (i.e. "fork") an existing thread in order to keep the exist
 
 ## Setup
 
-This code assumes you already have a thread to copy. You can read about what a thread is [here](https://langchain-ai.github.io/langgraph/cloud/concepts/api/#threads) and learn how to stream a run on a thread in [these how-to guides](https://langchain-ai.github.io/langgraph/cloud/how-tos/#streaming).
+This code assumes you already have a thread to copy. You can read about what a thread is [here](../../concepts/langgraph_server.md#threads) and learn how to stream a run on a thread in [these how-to guides](../../how-tos/index.md#streaming_1).
 
 ### SDK initialization
 

docs/docs/cloud/how-tos/enqueue_concurrent.md

@@ -1,6 +1,6 @@
 # Enqueue
 
-This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide](../concepts/api.md#double-texting).
+This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide](../../concepts/double_texting.md).
 
 The guide covers the `enqueue` option for double texting, which adds the interruptions to a queue and executes them in the order they are received by the client. Below is a quick example of using the `enqueue` option.
 

docs/docs/cloud/how-tos/human_in_the_loop_edit_state.md

@@ -6,7 +6,7 @@ This can be in several ways, but the primary supported way is to add an "interru
 
 ## Setup
 
-We are not going to show the full code for the graph we are hosting, but you can see it [here](../../how-tos/human_in_the_loop/edit-graph-state.ipynb#build-the-agent) if you want to. Once this graph is hosted, we are ready to invoke it and wait for user input. 
+We are not going to show the full code for the graph we are hosting, but you can see it [here](../../how-tos/human_in_the_loop/edit-graph-state.ipynb#agent) if you want to. Once this graph is hosted, we are ready to invoke it and wait for user input.
 
 ### SDK initialization
 

docs/docs/cloud/how-tos/human_in_the_loop_user_input.md

@@ -14,7 +14,7 @@ Luckily, LangGraph makes it possible to do similar things in a production way. T
 
 ## Setup
 
-We are not going to show the full code for the graph we are hosting, but you can see it [here](../../how-tos/human_in_the_loop/wait-user-input.ipynb#build-the-agent) if you want to. Once this graph is hosted, we are ready to invoke it and wait for user input. 
+We are not going to show the full code for the graph we are hosting, but you can see it [here](../../how-tos/human_in_the_loop/wait-user-input.ipynb#agent) if you want to. Once this graph is hosted, we are ready to invoke it and wait for user input.
 
 ### SDK initialization
 

docs/docs/cloud/how-tos/index.md

@@ -1,84 +0,0 @@
----
-hide:
-  - toc
----
-
-# How-to Guides
-
-Welcome to the LangGraph Cloud how-to guides! These guides provide practical, step-by-step instructions for accomplishing key tasks in LangGraph Cloud.
-
-## Setup
-
-LangGraph Cloud gives you best in class observability, testing, and hosting services. Learn how to setup your app for deployment to LangGraph Cloud in these how-to guides 
-
-- [How to set up app for deployment (requirements.txt)](../deployment/setup.md)
-- [How to set up app for deployment (pyproject.toml)](../deployment/setup_pyproject.md)
-- [How to set up app for deployment (JavaScript)](../deployment/setup_javascript.md)
-- [How to customize Dockerfile](../deployment/custom_docker.md)
-- [How to test locally](../deployment/test_locally.md)
-
-## Deploy
-
-Learn how to deploy your app to LangGraph Cloud in these how to guides:
-
-- [How to deploy to LangGraph cloud](../deployment/cloud.md)
-
-
-## Streaming
-
-Streaming the results of your LLM application is vital for ensuring a good user experience, especially when your graph may call multiple models and take a long time to fully complete a run. Read about how to stream values from your graph in these how to guides:
-
-- [How to stream values](./stream_values.md)
-- [How to stream updates](./stream_updates.md)
-- [How to stream messages](./stream_messages.md)
-- [How to stream events](./stream_events.md)
-- [How to stream in debug mode](./stream_debug.md)
-- [How to stream multiple modes](./stream_multiple.md)
-
-## Double-texting
-
-Graph execution can take a while, and sometimes users may change their mind about the input they wanted to send before their original input has finished running. For example, a user might notice a typo in their original request and will edit the prompt and resend it. Deciding what to do in these cases is important for ensuring a smooth user experience and preventing your graphs from behaving in unexpected ways. The following how-to guides provide information on the various options LangGraph Cloud gives you for dealing with double-texting:
-
-- [How to use the interrupt option](./interrupt_concurrent.md)
-- [How to use the rollback option](./rollback_concurrent.md)
-- [How to use the reject option](./reject_concurrent.md)
-- [How to use the enqueue option](./enqueue_concurrent.md)
-
-## Human-in-the-loop
-
-When creating complex graphs, leaving every decision up to the LLM can be dangerous, especially when the decisions involve invoking certain tools or accessing specific documents. To remedy this, LangGraph allows you to insert human-in-the-loop behavior to ensure your graph does not have undesired outcomes. Read more about the different ways you can add human-in-the-loop capabilities to your LangGraph Cloud projects in these how-to guides:
-
-- [How to add a breakpoint](./human_in_the_loop_breakpoint.md)
-- [How to wait for user input](./human_in_the_loop_user_input.md)
-- [How to edit graph state](./human_in_the_loop_edit_state.md)
-- [How to replay and branch from prior states](./human_in_the_loop_time_travel.md)
-- [How to review tool calls](./human_in_the_loop_review_tool_calls.md)
-
-## LangGraph Studio
-
-LangGraph Studio is a built-in UI for visualizing, testing, and debugging your agents.
-
-- [How to enter LangGraph Studio](./test_deployment.md)
-- [How to enter LangGraph Studio for local deployment](./test_local_deployment.md)
-- [How to test your graph in LangGraph Studio](./invoke_studio.md)
-- [Interact with threads in LangGraph Studio](./threads_studio.md)
-
-## Different Types of Runs:
-
-LangGraph Cloud supports multiple types of runs besides streaming runs.
-
-- [How to run an agent in the background](./background_run.md)
-- [How to run multiple agents in the same thread](./same-thread.md)
-- [How to create cron jobs](./cron_jobs.md)
-- [How to create stateless runs](./stateless_runs.md)
-
-## Other 
-
-Other guides that may prove helpful!
-
-- [How to configure agents](./configuration_cloud.md)
-- [How to version assistants](./assistant_versioning.md)
-- [How to convert LangGraph calls to LangGraph cloud calls](./langgraph_to_langgraph_cloud.ipynb)
-- [How to integrate webhooks](./webhooks.md)
-- [How to copy threads](./copy_threads.md)
-- [How to check status of your threads](./check_thread_status.md)

docs/docs/cloud/how-tos/interrupt_concurrent.md

@@ -1,6 +1,6 @@
 # Interrupt
 
-This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide](../concepts/api.md#double-texting).
+This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide](../../concepts/double_texting.md).
 
 The guide covers the `interrupt` option for double texting, which interrupts the prior run of the graph and starts a new one with the double-text. This option does not delete the first run, but rather keeps it in the database but sets its status to `interrupted`. Below is a quick example of using the `interrupt` option.
 
@@ -94,6 +94,7 @@ Now we can start our two runs and join the second on euntil it has completed:
         assistant_id,
         input={"messages": [{"role": "user", "content": "what's the weather in sf?"}]},
     )
+    # sleep a bit to get partial outputs from the first run
     await asyncio.sleep(2)
     run = await client.runs.create(
         thread["thread_id"],
@@ -114,6 +115,7 @@ Now we can start our two runs and join the second on euntil it has completed:
       assistantId,
       { input: { messages: [{ role: "human", content: "what's the weather in sf?" }] } }
     );
+    // sleep a bit to get partial outputs from the first run
     await new Promise(resolve => setTimeout(resolve, 2000)); 
 
     let run = await client.runs.create(

docs/docs/cloud/how-tos/reject_concurrent.md

@@ -1,6 +1,6 @@
 # Reject
 
-This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide][double-texting].
+This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide](../../concepts/double_texting.md).
 
 The guide covers the `reject` option for double texting, which rejects the new run of the graph by throwing an error and continues with the original run until completion. Below is a quick example of using the `reject` option.
 

docs/docs/cloud/how-tos/rollback_concurrent.md

@@ -1,6 +1,6 @@
 # Rollback
 
-This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide][double-texting].
+This guide assumes knowledge of what double-texting is, which you can learn about in the [double-texting conceptual guide](../../concepts/double_texting.md).
 
 The guide covers the `rollback` option for double texting, which interrupts the prior run of the graph and starts a new one with the double-text. This option is very similar to the `interrupt` option, but in this case the first run is completely deleted from the database and cannot be restarted. Below is a quick example of using the `rollback` option.
 
@@ -95,7 +95,6 @@ Now let's run a thread with the multitask parameter set to "rollback":
         assistant_id,
         input={"messages": [{"role": "user", "content": "what's the weather in sf?"}]},
     )
-    await asyncio.sleep(2)
     run = await client.runs.create(
         thread["thread_id"],
         assistant_id,
@@ -115,7 +114,6 @@ Now let's run a thread with the multitask parameter set to "rollback":
       assistantId,
       { input: { messages: [{ role: "human", content: "what's the weather in sf?" }] } }
     );
-    await new Promise(resolve => setTimeout(resolve, 2000)); 
 
     let run = await client.runs.create(
       thread["thread_id"],
@@ -139,7 +137,7 @@ Now let's run a thread with the multitask parameter set to "rollback":
     --data "{
       \"assistant_id\": \"agent\",
       \"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"what\'s the weather in sf?\"}]},
-    }" && sleep 2 && curl --request POST \
+    }" && curl --request POST \
     --url <DEPLOY<ENT_URL>>/threads/<THREAD_ID>/runs \
     --header 'Content-Type: application/json' \
     --data "{

docs/docs/cloud/how-tos/stream_debug.md

@@ -1,5 +1,8 @@
 # How to stream debug events
 
+!!! info "Prerequisites"
+    * [Streaming](../../concepts/streaming.md)
+
 This guide covers how to stream debug events from your graph (`stream_mode="debug"`). Streaming debug events produces responses containing `type` and `timestamp` keys. Debug events correspond to different steps in the graph's execution, and there are three different types of steps that will get streamed back to you:
 
 - `checkpoint`: These events will get streamed anytime the graph saves its state, which occurs after every super-step. Read more about checkpoints [here](https://langchain-ai.github.io/langgraph/concepts/low_level/#checkpointer)

docs/docs/cloud/how-tos/stream_events.md

@@ -1,6 +1,9 @@
 # How to stream events
 
-This guide covers how to stream events from your graph (`stream_mode="events"`). Depending on the use case and user experience of your LangGraph application, your application may process event types differently. Read more about events in this [conceptual guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#astream_events-for-streaming-tokens-of-llm-calls).
+!!! info "Prerequisites"
+    * [Streaming](../../concepts/streaming.md#streaming-llm-tokens-and-events-astream_events)
+
+This guide covers how to stream events from your graph (`stream_mode="events"`). Depending on the use case and user experience of your LangGraph application, your application may process event types differently.
 
 ## Setup
 
@@ -289,131 +292,4 @@ Output:
     
     
     Receiving new event of type: end...
-    None
-
-
-## Token-by-Token Streaming
-
-Token-by-token streaming can be implemented with the `events` streaming mode. The `on_chat_model_stream` event type should be processed to stream LLM responses token-by-token.
-
-=== "Python"
-
-    ```python
-    llm_response = ""
-
-    # stream token-by-token
-    async for chunk in client.runs.stream(
-        thread_id=thread["thread_id"],
-        assistant_id=assistant_id,
-        input=input,
-        stream_mode="events",
-    ):
-        if (
-            chunk.event == "events" and
-            chunk.data["event"] == "on_chat_model_stream" and
-            len(chunk.data["data"]["chunk"]["content"]) > 0 and
-            'text' in chunk.data["data"]["chunk"]["content"][0]
-        ):
-            llm_response += chunk.data["data"]["chunk"]["content"][0]['text']
-            print(llm_response)
-    ```
-
-=== "Javascript"
-
-    ```js
-    const llmResponse = "";
-    // stream events
-    const streamResponse = client.runs.stream(
-      thread["thread_id"],
-      assistantID,
-      {
-        input,
-        streamMode: "events"
-      }
-    );
-    for await (const chunk of streamResponse) {
-      if (chunk.event === "events" && chunk.data.event === "on_chat_model_stream" && chunk.data.chunk.content.length > 0 && 'text' in chunk.data.chunk.content[0]) {
-        llmResponse += chunk.data.data.chunk.content[0].text;
-        console.log(llmResponse);
-      }
-    }
-    ```
-
-=== "CURL"
-
-    ```bash
-    curl --request POST \
-     --url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
-     --header 'Content-Type: application/json' \
-     --data "{
-       \"assistant_id\": \"agent\",
-       \"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"What's the weather in sf\"}]},
-       \"stream_mode\": [
-         \"events\"
-       ]
-     }" | sed 's/\r$//' | awk '
-    /^event:/ { event = $2 }
-    /^data:/ {
-        json_data = substr($0, index($0, $2))
-
-        if (event == "events") {
-        print json_data
-        }
-    }' | jq -r '
-        select(.event == "on_chat_model_stream") |
-        .data.chunk.content[] | .text // empty
-    ' | awk '
-    BEGIN { llm_response="" }
-    $0 != "" && $0 != "null" {
-        llm_response = llm_response $0
-        print llm_response
-    }'
-    ```
-
-Output:
-
-    The
-    The search
-    The search results provide
-    The search results provide the current weather conditions
-    The search results provide the current weather conditions in San Francisco.
-    The search results provide the current weather conditions in San Francisco. According
-    The search results provide the current weather conditions in San Francisco. According to the data,
-    The search results provide the current weather conditions in San Francisco. According to the data, as
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12,
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024,
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C).
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The win
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is bl
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 k
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph).
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70%
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles (10 km
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles (10 km).
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles (10 km). Overall
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles (10 km). Overall, it appears
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles (10 km). Overall, it appears to be a nice
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles (10 km). Overall, it appears to be a nice sunny day in San
-    The search results provide the current weather conditions in San Francisco. According to the data, as of 3:19 PM on August 12, 2024, the weather in San Francisco is sunny with a temperature of 60.8°F (16°C). The wind is blowing from the west-southwest at 13.4 mph (21.6 kph). The humidity is 70% and visibility is 6 miles (10 km). Overall, it appears to be a nice sunny day in San Francisco.
-
-
+    None

docs/docs/cloud/how-tos/stream_messages.md

@@ -1,43 +1,9 @@
 # How to stream messages from your graph
 
-This guide covers how to stream messages from your graph. In order to use this mode, the state of the graph you are interacting with MUST have a `messages` key that is a list of messages.
+!!! info "Prerequisites"
+    * [Streaming](../../concepts/streaming.md)
 
-E.g., the state should look something like:
-
-=== "Python"
-
-    ```python
-    from typing import Annotated
-    from typing_extensions import TypedDict
-    from langgraph.graph import add_messages
-    from langchain_core.messages import AnyMessage
-
-    class State(TypedDict):
-        messages: Annotated[list[AnyMessage], add_messages]
-    ```
-
-=== "Javascript"
-
-    ```js
-    import { type BaseMessage } from "@langchain/core/messages";
-    import { Annotation, messagesStateReducer } from "@langchain/langgraph";
-
-    export const StateAnnotation = Annotation.Root({
-      messages: Annotation<BaseMessage[]>({
-        reducer: messagesStateReducer,
-        default: () => [],
-      }),
-    });
-    ```
-
-Alternatively, you can use an instance or subclass of `from langgraph.graph import MessagesState` (`MessagesState` is equivalent to the implementation above). Or in Javascript: `import { MessagesAnnotation } from "@langchain/langgraph";`.
-
-With `stream_mode="messages"` two things will be streamed back:
-
-- It outputs messages produced by any chat model called inside (unless tagged in a special way)
-- It outputs messages returned from nodes (to allow for nodes to return `ToolMessages` and the like)
-
-Read more about how the `messages` streaming mode works [here](https://langchain-ai.github.io/langgraph/cloud/concepts/api/#modemessages)
+This guide covers how to stream messages from your graph. With `stream_mode="messages-tuple"`, messages (i.e. individual LLM tokens) from any chat model invocations inside your graph nodes will be streamed back.
 
 ## Setup
 
@@ -90,101 +56,9 @@ Output:
         'values': None
     }
 
-Let's also define a helper function for better formatting of the tool calls in messages (for CURL we will define a helper script called `process_stream.sh`)
-
-=== "Python"
-
-    ```python
-    def format_tool_calls(tool_calls):
-        if tool_calls:
-            formatted_calls = []
-            for call in tool_calls:
-                formatted_calls.append(
-                    f"Tool Call ID: {call['id']}, Function: {call['name']}, Arguments: {call['args']}"
-                )
-            return "\n".join(formatted_calls)
-        return "No tool calls"
-    ```
-
-=== "Javascript"
-
-    ```js
-    function formatToolCalls(toolCalls) {
-      if (toolCalls && toolCalls.length > 0) {
-        const formattedCalls = toolCalls.map(call => {
-          return `Tool Call ID: ${call.id}, Function: ${call.name}, Arguments: ${call.args}`;
-        });
-        return formattedCalls.join("\n");
-      }
-      return "No tool calls";
-    }
-    ```
-
-=== "CURL"
-
-    ```bash
-    # process_stream.sh
-
-    format_tool_calls() {
-        echo "$1" | jq -r 'map("Tool Call ID: \(.id), Function: \(.name), Arguments: \(.args)") | join("\n")'
-    }
-
-    process_data_item() {
-        local data_item="$1"
-
-        if echo "$data_item" | jq -e '.role == "user"' > /dev/null; then
-            echo "Human: $(echo "$data_item" | jq -r '.content')"
-        else
-            local tool_calls=$(echo "$data_item" | jq -r '.tool_calls // []')
-            local invalid_tool_calls=$(echo "$data_item" | jq -r '.invalid_tool_calls // []')
-            local content=$(echo "$data_item" | jq -r '.content // ""')
-            local response_metadata=$(echo "$data_item" | jq -r '.response_metadata // {}')
-
-            if [ -n "$content" ] && [ "$content" != "null" ]; then
-                echo "AI: $content"
-            fi
-
-            if [ "$tool_calls" != "[]" ]; then
-                echo "Tool Calls:"
-                format_tool_calls "$tool_calls"
-            fi
-
-            if [ "$invalid_tool_calls" != "[]" ]; then
-                echo "Invalid Tool Calls:"
-                format_tool_calls "$invalid_tool_calls"
-            fi
-
-            if [ "$response_metadata" != "{}" ]; then
-                local finish_reason=$(echo "$response_metadata" | jq -r '.finish_reason // "N/A"')
-                echo "Response Metadata: Finish Reason - $finish_reason"
-            fi
-        fi
-    }
-
-    while IFS=': ' read -r key value; do
-        case "$key" in
-            event)
-                event="$value"
-                ;;
-            data)
-                if [ "$event" = "metadata" ]; then
-                    run_id=$(echo "$value" | jq -r '.run_id')
-                    echo "Metadata: Run ID - $run_id"
-                    echo "------------------------------------------------"
-                elif [ "$event" = "messages/partial" ]; then
-                    echo "$value" | jq -c '.[]' | while read -r data_item; do
-                        process_data_item "$data_item"
-                    done
-                    echo "------------------------------------------------"
-                fi
-                ;;
-        esac
-    done
-    ```
-
 ## Stream graph in messages mode
 
-Now we can stream by messages, which will return complete messages (at the end of node execution) as well as tokens for any messages generated inside a node:
+Now we can stream LLM tokens for any messages generated inside a node in the form of tuples `(message, metadata)`. Metadata contains additional information that can be useful for filtering the streamed outputs to a specific node or LLM.
 
 === "Python"
 
@@ -192,41 +66,16 @@ Now we can stream by messages, which will return complete messages (at the end o
     input = {"messages": [{"role": "user", "content": "what's the weather in sf"}]}
     config = {"configurable": {"model_name": "openai"}}
 
-    async for event in client.runs.stream(
+    async for chunk in client.runs.stream(
         thread["thread_id"],
         assistant_id=assistant_id,
         input=input,
         config=config,
-        stream_mode="messages",
+        stream_mode="messages-tuple",
     ):
-        if event.event == "metadata":
-            print(f"Metadata: Run ID - {event.data['run_id']}")
-            print("-" * 50)
-        elif event.event == "messages/partial":
-            for data_item in event.data:
-                if "role" in data_item and data_item["role"] == "user":
-                    print(f"Human: {data_item['content']}")
-                else:
-                    tool_calls = data_item.get("tool_calls", [])
-                    invalid_tool_calls = data_item.get("invalid_tool_calls", [])
-                    content = data_item.get("content", "")
-                    response_metadata = data_item.get("response_metadata", {})
-
-                    if content:
-                        print(f"AI: {content}")
-
-                    if tool_calls:
-                        print("Tool Calls:")
-                        print(format_tool_calls(tool_calls))
-
-                    if invalid_tool_calls:
-                        print("Invalid Tool Calls:")
-                        print(format_tool_calls(invalid_tool_calls))
-
-                    if response_metadata:
-                        finish_reason = response_metadata.get("finish_reason", "N/A")
-                        print(f"Response Metadata: Finish Reason - {finish_reason}")
-            print("-" * 50)
+        print(f"Receiving new event of type: {chunk.event}...")
+        print(chunk.data)
+        print("\n\n")
     ```
 
 === "Javascript"
@@ -248,46 +97,13 @@ Now we can stream by messages, which will return complete messages (at the end o
       {
         input,
         config,
-        streamMode: "messages"
+        streamMode: "messages-tuple"
       }
     );
-
-    for await (const event of streamResponse) {
-      if (event.event === "metadata") {
-        console.log(`Metadata: Run ID - ${event.data.run_id}`);
-        console.log("-".repeat(50));
-      } else if (event.event === "messages/partial") {
-        event.data.forEach(dataItem => {
-          if (dataItem.role && dataItem.role === "user") {
-            console.log(`Human: ${dataItem.content}`);
-          } else {
-            const toolCalls = dataItem.tool_calls || [];
-            const invalidToolCalls = dataItem.invalid_tool_calls || [];
-            const content = dataItem.content || "";
-            const responseMetadata = dataItem.response_metadata || {};
-
-            if (content) {
-              console.log(`AI: ${content}`);
-            }
-
-            if (toolCalls.length > 0) {
-              console.log("Tool Calls:");
-              console.log(formatToolCalls(toolCalls));
-            }
-
-            if (invalidToolCalls.length > 0) {
-              console.log("Invalid Tool Calls:");
-              console.log(formatToolCalls(invalidToolCalls));
-            }
-
-            if (responseMetadata) {
-              const finishReason = responseMetadata.finish_reason || "N/A";
-              console.log(`Response Metadata: Finish Reason - ${finishReason}`);
-            }
-          }
-        });
-        console.log("-".repeat(50));
-      }
+    for await (const chunk of streamResponse) {
+      console.log(`Receiving new event of type: ${chunk.event}...`);
+      console.log(chunk.data);
+      console.log("\n\n");
     }
     ```
 
@@ -295,203 +111,221 @@ Now we can stream by messages, which will return complete messages (at the end o
 
     ```bash
     curl --request POST \
-    --url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
-    --header 'Content-Type: application/json' \
-    --data "{
-    \"assistant_id\": \"agent\",
-    \"config\":{\"configurable\":{\"model_name\":\"openai\"}},
-    \"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"What's the weather in sf\"}]},
-    \"stream_mode\": [
-    \"messages\"
-    ]
-    }" | sed 's/\r$//' | ./process_stream.sh
+     --url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
+     --header 'Content-Type: application/json' \
+     --data "{
+       \"assistant_id\": \"agent\",
+       \"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"what's the weather in la\"}]},
+       \"stream_mode\": [
+         \"messages-tuple\"
+       ]
+     }" | \
+     sed 's/\r$//' | \
+     awk '
+     /^event:/ {
+         if (data_content != "") {
+             print data_content "\n"
+         }
+         sub(/^event: /, "Receiving event of type: ", $0)
+         printf "%s...\n", $0
+         data_content = ""
+     }
+     /^data:/ {
+         sub(/^data: /, "", $0)
+         data_content = $0
+     }
+     END {
+         if (data_content != "") {
+             print data_content "\n"
+         }
+     }
+     '
     ```
 
 
 Output:
 
-    Metadata: Run ID - 1ef2fe5c-6a1d-6575-bc09-d7832711c17e
-    --------------------------------------------------
-    Invalid Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: 
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': ''}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current'}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather'}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in'}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San'}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San Francisco'}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San Francisco'}
-    --------------------------------------------------
-    Tool Calls:
-    Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San Francisco'}
-    Response Metadata: Finish Reason - tool_calls
-    --------------------------------------------------
-    --------------------------------------------------
-    AI: The
-    --------------------------------------------------
-    AI: The current
-    --------------------------------------------------
-    AI: The current weather
-    --------------------------------------------------
-    AI: The current weather in
-    --------------------------------------------------
-    AI: The current weather in San
-    --------------------------------------------------
-    AI: The current weather in San Francisco
-    --------------------------------------------------
-    AI: The current weather in San Francisco is
-    --------------------------------------------------
-    AI: The current weather in San Francisco is over
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F).
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-s
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-south
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 k
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph).
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%,
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles).
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is 
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is 3
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is 3.
-    --------------------------------------------------
-    AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is 3.
-    Response Metadata: Finish Reason - stop
-    --------------------------------------------------
+    Receiving new event of type: metadata...
+    {"run_id": "1ef971e0-9a84-6154-9047-247b4ce89c4d", "attempt": 1}
 
+    ...
+
+    Receiving new event of type: messages...
+    [
+      {
+        "type": "AIMessageChunk",
+        "tool_calls": [
+          {
+            "name": "tavily_search_results_json",
+            "args": {
+              "query": "weat"
+            },
+            "id": "toolu_0114XKXdNtHQEa3ozmY1uDdM",
+            "type": "tool_call"
+          }
+        ],
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "agent",
+        ...
+      }
+    ]
+
+
+
+    Receiving new event of type: messages...
+    [
+      {
+        "type": "AIMessageChunk",
+        "tool_calls": [
+          {
+            "name": "tavily_search_results_json",
+            "args": {
+              "query": "her in san "
+            },
+            "id": "toolu_0114XKXdNtHQEa3ozmY1uDdM",
+            "type": "tool_call"
+          }
+        ],
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "agent",
+        ...
+      }
+    ]
+
+    ...
+
+    Receiving new event of type: messages...
+    [
+      {
+        "type": "AIMessageChunk",
+        "tool_calls": [
+          {
+            "name": "tavily_search_results_json",
+            "args": {
+              "query": "francisco"
+            },
+            "id": "toolu_0114XKXdNtHQEa3ozmY1uDdM",
+            "type": "tool_call"
+          }
+        ],
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "agent",
+        ...
+      }
+    ]
+
+    ...
+
+    Receiving new event of type: messages...
+    [
+      {
+        "content": "[{\"url\": \"https://www.weatherapi.com/\", \"content\": \"{'location': {'name': 'San Francisco', 'region': 'California', 'country': 'United States of America', 'lat': 37.775, 'lon': -122.4183, 'tz_id': 'America/Los_Angeles', 'localtime_epoch': 1730475777, 'localtime': '2024-11-01 08:42'}, 'current': {'last_updated_epoch': 1730475000, 'last_updated': '2024-11-01 08:30', 'temp_c': 11.1, 'temp_f': 52.0, 'is_day': 1, 'condition': {'text': 'Partly cloudy', 'icon': '//cdn.weatherapi.com/weather/64x64/day/116.png', 'code': 1003}, 'wind_mph': 2.2, 'wind_kph': 3.6, 'wind_degree': 192, 'wind_dir': 'SSW', 'pressure_mb': 1018.0, 'pressure_in': 30.07, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 89, 'cloud': 75, 'feelslike_c': 11.5, 'feelslike_f': 52.6, 'windchill_c': 10.0, 'windchill_f': 50.1, 'heatindex_c': 10.4, 'heatindex_f': 50.7, 'dewpoint_c': 9.1, 'dewpoint_f': 48.5, 'vis_km': 16.0, 'vis_miles': 9.0, 'uv': 3.0, 'gust_mph': 6.7, 'gust_kph': 10.8}}\"}]",
+        "type": "tool",
+        "tool_call_id": "toolu_0114XKXdNtHQEa3ozmY1uDdM",
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "action",
+        ...
+      }
+    ]
+
+    ...
+
+    Receiving new event of type: messages...
+    [
+      {
+        "content": [
+          {
+            "text": "\n\nThe search",
+            "type": "text",
+            "index": 0
+          }
+        ],
+        "type": "AIMessageChunk",
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "agent",
+        ...
+      }
+    ]
+
+
+
+    Receiving new event of type: messages...
+    [
+      {
+        "content": [
+          {
+            "text": " results provide",
+            "type": "text",
+            "index": 0
+          }
+        ],
+        "type": "AIMessageChunk",
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "agent",
+        ...
+      }
+    ]
+
+
+
+    Receiving new event of type: messages...
+    [
+      {
+        "content": [
+          {
+            "text": " the current weather conditions",
+            "type": "text",
+            "index": 0
+          }
+        ],
+        "type": "AIMessageChunk",
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "agent",
+        ...
+      }
+    ]
+
+
+
+    Receiving new event of type: messages...
+    [
+      {
+        "content": [
+          {
+            "text": " in San Francisco.",
+            "type": "text",
+            "index": 0
+          }
+        ],
+        "type": "AIMessageChunk",
+        ...
+      },
+      {
+        "graph_id": "agent",
+        "langgraph_node": "agent",
+        ...
+      }
+    ]
+
+    ...

docs/docs/cloud/how-tos/stream_multiple.md

@@ -1,5 +1,8 @@
 # How to configure multiple streaming modes at the same time
 
+!!! info "Prerequisites"
+    * [Streaming](../../concepts/streaming.md)
+
 This guide covers how to configure multiple streaming modes at the same time.
 
 ## Setup
@@ -175,11 +178,6 @@ Output:
     
     
     
-    Receiving new event of type: messages/complete...
-    [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}]
-    
-    
-    
     Receiving new event of type: debug...
     {'type': 'checkpoint', 'timestamp': '2024-06-24T21:34:06.117924+00:00', 'step': 0, 'payload': {'config': {'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'callbacks': [None], 'recursion_limit': 25, 'configurable': {'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'thread_ts': '1ef32717-bc81-68c8-8000-4e18ae7d67a5', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25'}, 'values': {'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}]}, 'metadata': {'source': 'loop', 'step': 0, 'writes': None}}}
     
@@ -305,11 +303,6 @@ Output:
     
     
     
-    Receiving new event of type: messages/complete...
-    [{'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]
-    
-    
-    
     Receiving new event of type: debug...
     {'type': 'checkpoint', 'timestamp': '2024-06-24T21:34:06.124510+00:00', 'step': 1, 'payload': {'config': {'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'callbacks': [None], 'recursion_limit': 25, 'configurable': {'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'thread_ts': '1ef32717-bc91-6a34-8001-26353c117c25', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25'}, 'values': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}, {'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}, 'metadata': {'source': 'loop', 'step': 1, 'writes': {'agent': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}}}}
     
@@ -469,12 +462,7 @@ Output:
     {'event': 'on_chain_stream', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'name': 'LangGraph', 'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'data': {'chunk': ['values', {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}, {'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}, {'content': 'tool_call__begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': None, 'id': '639ca779-403d-4915-a066-327e1f634c8b', 'tool_call_id': 'tool_call_id'}, {'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}]}, 'parent_ids': []}
     
     
-    
-    Receiving new event of type: messages/complete...
-    [{'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]
-    
-    
-    
+
     Receiving new event of type: debug...
     {'type': 'checkpoint', 'timestamp': '2024-06-24T21:34:06.134190+00:00', 'step': 3, 'payload': {'config': {'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'callbacks': [None], 'recursion_limit': 25, 'configurable': {'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'thread_ts': '1ef32717-bca9-6418-8003-8d0d0b06845c', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25'}, 'values': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}, {'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}, {'content': 'tool_call__begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': None, 'id': '639ca779-403d-4915-a066-327e1f634c8b', 'tool_call_id': 'tool_call_id'}, {'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}, 'metadata': {'source': 'loop', 'step': 3, 'writes': {'agent': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}}}}
     

docs/docs/cloud/how-tos/stream_updates.md

@@ -1,6 +1,9 @@
 # How to stream state updates of your graph
 
-This guide covers how to use `stream_mode="updates"` for your graph, which will stream the updates to the graph state that are made after each node is executed. This differs from using `stream_mode="values"`: instead of streaming the entire value of the state at each superstep, it only streams the updates from each of the nodes that made an update to the state at that superstep. Read [this conceptual guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#stream-and-astream) to learn more.
+!!! info "Prerequisites"
+    * [Streaming](../../concepts/streaming.md)
+
+This guide covers how to use `stream_mode="updates"` for your graph, which will stream the updates to the graph state that are made after each node is executed. This differs from using `stream_mode="values"`: instead of streaming the entire value of the state at each superstep, it only streams the updates from each of the nodes that made an update to the state at that superstep.
 
 ## Setup
 
@@ -146,24 +149,69 @@ Now we can stream by updates, which outputs updates made to the state by each no
 Output:
 
     Receiving new event of type: metadata...
-    {'run_id': 'cfc96c16-ed9a-44bd-b5bb-c30e3c0725f0'}
-    
-    
-    
-    Receiving new event of type: data...
-    {'agent': {'messages': [{'content': [{'id': 'toolu_0148tMmDK51iLQfG1yaNwRHM', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-1a9d32b0-7007-4a36-abde-8df812a0ed94', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_0148tMmDK51iLQfG1yaNwRHM'}], 'invalid_tool_calls': []}]}}
-    
-    
-    
-    Receiving new event of type: data...
-    {'action': {'messages': [{'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716062239, \'localtime\': \'2024-05-18 12:57\'}, \'current\': {\'last_updated_epoch\': 1716061500, \'last_updated\': \'2024-05-18 12:45\', \'temp_c\': 18.9, \'temp_f\': 66.0, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 2.2, \'wind_kph\': 3.6, \'wind_degree\': 10, \'wind_dir\': \'N\', \'pressure_mb\': 1017.0, \'pressure_in\': 30.02, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 18.9, \'feelslike_f\': 66.0, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 6.0, \'gust_mph\': 7.5, \'gust_kph\': 12.0}}"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': 'a36e8cd1-0e96-4417-9c15-f10a945d2b42', 'tool_call_id': 'toolu_0148tMmDK51iLQfG1yaNwRHM'}]}}
-    
-    
-    
-    Receiving new event of type: data...
-    {'agent': {'messages': [{'content': 'The weather in Los Angeles is currently overcast with a temperature of around 66°F (18.9°C). There are light winds from the north at around 2-3 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-d5c1c2f0-b12d-41ce-990b-f36570e7483d', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}}
-    
-    
-    
+    {"run_id": "cfc96c16-ed9a-44bd-b5bb-c30e3c0725f0"}
+
+
+
+    Receiving new event of type: updates...
+    {
+      "agent": {
+        "messages": [
+          {
+            "type": "ai",
+            "tool_calls": [
+              {
+                "name": "tavily_search_results_json",
+                "args": {
+                  "query": "weather in los angeles"
+                },
+                "id": "toolu_0148tMmDK51iLQfG1yaNwRHM"
+              }
+            ],
+            ...
+          }
+        ]
+      }
+    }
+
+
+
+    Receiving new event of type: updates...
+    {
+      "action": {
+        "messages": [
+          {
+            "content": [
+              {
+                "url": "https://www.weatherapi.com/",
+                "content": "{\"location\": {\"name\": \"Los Angeles\", \"region\": \"California\", \"country\": \"United States of America\", \"lat\": 34.05, \"lon\": -118.24, \"tz_id\": \"America/Los_Angeles\", \"localtime_epoch\": 1716062239, \"localtime\": \"2024-05-18 12:57\"}, \"current\": {\"last_updated_epoch\": 1716061500, \"last_updated\": \"2024-05-18 12:45\", \"temp_c\": 18.9, \"temp_f\": 66.0, \"is_day\": 1, \"condition\": {\"text\": \"Overcast\", \"icon\": \"//cdn.weatherapi.com/weather/64x64/day/122.png\", \"code\": 1009}, \"wind_mph\": 2.2, \"wind_kph\": 3.6, \"wind_degree\": 10, \"wind_dir\": \"N\", \"pressure_mb\": 1017.0, \"pressure_in\": 30.02, \"precip_mm\": 0.0, \"precip_in\": 0.0, \"humidity\": 65, \"cloud\": 100, \"feelslike_c\": 18.9, \"feelslike_f\": 66.0, \"vis_km\": 16.0, \"vis_miles\": 9.0, \"uv\": 6.0, \"gust_mph\": 7.5, \"gust_kph\": 12.0}}"
+              }
+            ],
+            "type": "tool",
+            "name": "tavily_search_results_json",
+            "tool_call_id": "toolu_0148tMmDK51iLQfG1yaNwRHM",
+            ...
+          }
+        ]
+      }
+    }
+
+
+
+    Receiving new event of type: updates...
+    {
+      "agent": {
+        "messages": [
+          {
+            "content": "The weather in Los Angeles is currently overcast with a temperature of around 66°F (18.9°C). There are light winds from the north at around 2-3 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.",
+            "type": "ai",
+            ...
+          }
+        ]
+      }
+    }
+
+
+
     Receiving new event of type: end...
     None

docs/docs/cloud/how-tos/stream_values.md

@@ -1,6 +1,9 @@
 # How to stream full state of your graph
 
-This guide covers how to use `stream_mode="values"`, which streams the value of the state at each superstep. This differs from using `stream_mode="updates"`: instead of streaming just the updates to the state from each node, it streams the entire graph state at that superstep. Read [this conceptual guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#stream-and-astream) to learn more.
+!!! info "Prerequisites"
+    * [Streaming](../../concepts/streaming.md)
+
+This guide covers how to use `stream_mode="values"`, which streams the value of the state at each superstep. This differs from using `stream_mode="updates"`: instead of streaming just the updates to the state from each node, it streams the entire graph state at that superstep.
 
 ## Setup
 
@@ -133,30 +136,93 @@ Now we can stream by values, which streams the full state of the graph after eac
 Output:
 
     Receiving new event of type: metadata...
-    {'run_id': 'f08791ce-0a3d-44e0-836c-ff62cd2e2786'}
-    
-    
-    
+    {"run_id": "f08791ce-0a3d-44e0-836c-ff62cd2e2786"}
+
+
+
     Receiving new event of type: values...
-    {'messages': [{'role': 'human', 'content': 'what's the weather in la'}]}
-    
-    
-    
+    {
+      "messages": [
+        {
+          "role": "human",
+          "content": "what's the weather in la"
+        }
+      ]
+    }
+
+
+
     Receiving new event of type: values...
-    {'messages': [{'content': 'what's the weather in la', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'faa15565-8823-4aa1-87af-e21b40526fae', 'example': False}, {'content': [{'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3fe1db7a-6b8d-4d83-ba07-8657190ad811', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}], 'invalid_tool_calls': []}]}
-    
-    
-    
+    {
+      "messages": [
+        {
+          "content": "what's the weather in la",
+          "type": "human",
+          ...
+        },
+        {
+          "content": "",
+          "type": "ai",
+          "tool_calls": [
+            {
+              "name": "tavily_search_results_json",
+              "args": {
+                "query": "weather in los angeles"
+              },
+              "id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
+            }
+          ],
+          ...
+        }
+      ]
+    }
+
+    ...
+
     Receiving new event of type: values...
-    {'messages': [{'content': 'what's the weather in la', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'faa15565-8823-4aa1-87af-e21b40526fae', 'example': False}, {'content': [{'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3fe1db7a-6b8d-4d83-ba07-8657190ad811', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}], 'invalid_tool_calls': []}, {'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716310320, \'localtime\': \'2024-05-21 9:52\'}, \'current\': {\'last_updated_epoch\': 1716309900, \'last_updated\': \'2024-05-21 09:45\', \'temp_c\': 16.7, \'temp_f\': 62.1, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 8.1, \'wind_kph\': 13.0, \'wind_degree\': 250, \'wind_dir\': \'WSW\', \'pressure_mb\': 1015.0, \'pressure_in\': 29.97, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 16.7, \'feelslike_f\': 62.1, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 5.0, \'gust_mph\': 12.5, \'gust_kph\': 20.2}}"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '0d5dab31-5ff8-4ae2-a560-bc4bcba7c9d7', 'tool_call_id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}]}
-    
-    
-    
-    Receiving new event of type: values...
-    {'messages': [{'content': 'what's the weather in la', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'faa15565-8823-4aa1-87af-e21b40526fae', 'example': False}, {'content': [{'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3fe1db7a-6b8d-4d83-ba07-8657190ad811', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}], 'invalid_tool_calls': []}, {'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716310320, \'localtime\': \'2024-05-21 9:52\'}, \'current\': {\'last_updated_epoch\': 1716309900, \'last_updated\': \'2024-05-21 09:45\', \'temp_c\': 16.7, \'temp_f\': 62.1, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 8.1, \'wind_kph\': 13.0, \'wind_degree\': 250, \'wind_dir\': \'WSW\', \'pressure_mb\': 1015.0, \'pressure_in\': 29.97, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 16.7, \'feelslike_f\': 62.1, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 5.0, \'gust_mph\': 12.5, \'gust_kph\': 20.2}}"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '0d5dab31-5ff8-4ae2-a560-bc4bcba7c9d7', 'tool_call_id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}, {'content': 'Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-4d6d4c23-5aad-4042-b0d9-19407a9e08e3', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}
-    
-    
-    
+    {
+      "messages": [
+        {
+          "content": "what's the weather in la",
+          "type": "human",
+          ...
+        },
+        {
+          "content": "",
+          "type": "ai",
+          "tool_calls": [
+            {
+              "name": "tavily_search_results_json",
+              "args": {
+                "query": "weather in los angeles"
+              },
+              "id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
+            }
+          ],
+          ...
+        }
+        {
+          "content": [
+            {
+              "url": "https://www.weatherapi.com/",
+              "content": "{\"location\": {\"name\": \"Los Angeles\", \"region\": \"California\", \"country\": \"United States of America\", \"lat\": 34.05, \"lon\": -118.24, \"tz_id\": \"America/Los_Angeles\", \"localtime_epoch\": 1716310320, \"localtime\": \"2024-05-21 9:52\"}, \"current\": {\"last_updated_epoch\": 1716309900, \"last_updated\": \"2024-05-21 09:45\", \"temp_c\": 16.7, \"temp_f\": 62.1, \"is_day\": 1, \"condition\": {\"text\": \"Overcast\", \"icon\": \"//cdn.weatherapi.com/weather/64x64/day/122.png\", \"code\": 1009}, \"wind_mph\": 8.1, \"wind_kph\": 13.0, \"wind_degree\": 250, \"wind_dir\": \"WSW\", \"pressure_mb\": 1015.0, \"pressure_in\": 29.97, \"precip_mm\": 0.0, \"precip_in\": 0.0, \"humidity\": 65, \"cloud\": 100, \"feelslike_c\": 16.7, \"feelslike_f\": 62.1, \"vis_km\": 16.0, \"vis_miles\": 9.0, \"uv\": 5.0, \"gust_mph\": 12.5, \"gust_kph\": 20.2}}"
+            }
+          ],
+          "type": "tool",
+          "name": "tavily_search_results_json",
+          "tool_call_id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
+          ...
+        },
+        {
+          "content": "Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.",
+          "type": "ai",
+          ...
+        }
+      ]
+    }
+
+
+
     Receiving new event of type: end...
     None
     
@@ -228,40 +294,42 @@ If we want to just get the final result, we can use this endpoint and just keep
 
 Output:
 
-    {'messages': [{'content': 'what's the weather in la',
-       'additional_kwargs': {},
-       'response_metadata': {},
-       'type': 'human',
-       'name': None,
-       'id': 'e78c2f94-d810-42fc-a399-11f6bb1b1092',
-       'example': False},
-      {'content': [{'id': 'toolu_01SBMoAGr4U9x3ibztm2UUom',
-         'input': {'query': 'weather in los angeles'},
-         'name': 'tavily_search_results_json',
-         'type': 'tool_use'}],
-       'additional_kwargs': {},
-       'response_metadata': {},
-       'type': 'ai',
-       'name': None,
-       'id': 'run-80767ab8-09fc-40ec-9e45-657ddef5e0b1',
-       'example': False,
-       'tool_calls': [{'name': 'tavily_search_results_json',
-         'args': {'query': 'weather in los angeles'},
-         'id': 'toolu_01SBMoAGr4U9x3ibztm2UUom'}],
-       'invalid_tool_calls': []},
-      {'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716310320, \'localtime\': \'2024-05-21 9:52\'}, \'current\': {\'last_updated_epoch\': 1716309900, \'last_updated\': \'2024-05-21 09:45\', \'temp_c\': 16.7, \'temp_f\': 62.1, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 8.1, \'wind_kph\': 13.0, \'wind_degree\': 250, \'wind_dir\': \'WSW\', \'pressure_mb\': 1015.0, \'pressure_in\': 29.97, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 16.7, \'feelslike_f\': 62.1, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 5.0, \'gust_mph\': 12.5, \'gust_kph\': 20.2}}"}]',
-       'additional_kwargs': {},
-       'response_metadata': {},
-       'type': 'tool',
-       'name': 'tavily_search_results_json',
-       'id': 'af25e94a-c119-48c3-bbd3-096e42f472ac',
-       'tool_call_id': 'toolu_01SBMoAGr4U9x3ibztm2UUom'},
-      {'content': 'Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.',
-       'additional_kwargs': {},
-       'response_metadata': {},
-       'type': 'ai',
-       'name': None,
-       'id': 'run-b90f0037-e56a-4f3b-ad92-00d10d079a9e',
-       'example': False,
-       'tool_calls': [],
-       'invalid_tool_calls': []}]}
+    {
+      "messages": [
+        {
+          "content": "what's the weather in la",
+          "type": "human",
+          ...
+        },
+        {
+          "type": "ai",
+          "tool_calls": [
+            {
+              "name": "tavily_search_results_json",
+              "args": {
+                "query": "weather in los angeles"
+              },
+              "id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
+            }
+          ],
+          ...
+        }
+        {
+          "content": [
+            {
+              "url": "https://www.weatherapi.com/",
+              "content": "{\"location\": {\"name\": \"Los Angeles\", \"region\": \"California\", \"country\": \"United States of America\", \"lat\": 34.05, \"lon\": -118.24, \"tz_id\": \"America/Los_Angeles\", \"localtime_epoch\": 1716310320, \"localtime\": \"2024-05-21 9:52\"}, \"current\": {\"last_updated_epoch\": 1716309900, \"last_updated\": \"2024-05-21 09:45\", \"temp_c\": 16.7, \"temp_f\": 62.1, \"is_day\": 1, \"condition\": {\"text\": \"Overcast\", \"icon\": \"//cdn.weatherapi.com/weather/64x64/day/122.png\", \"code\": 1009}, \"wind_mph\": 8.1, \"wind_kph\": 13.0, \"wind_degree\": 250, \"wind_dir\": \"WSW\", \"pressure_mb\": 1015.0, \"pressure_in\": 29.97, \"precip_mm\": 0.0, \"precip_in\": 0.0, \"humidity\": 65, \"cloud\": 100, \"feelslike_c\": 16.7, \"feelslike_f\": 62.1, \"vis_km\": 16.0, \"vis_miles\": 9.0, \"uv\": 5.0, \"gust_mph\": 12.5, \"gust_kph\": 20.2}}"
+            }
+          ],
+          "type": "tool",
+          "name": "tavily_search_results_json",
+          "tool_call_id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
+          ...
+        },
+        {
+          "content": "Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.",
+          "type": "ai",
+          ...
+        }
+      ]
+    }