Merge remote-tracking branch 'origin/main' into dev

Makefile

@@ -44,13 +44,18 @@ install_backend:
 
 backend:
 	make install_backend
-	poetry run uvicorn langflow.main:app --port 7860 --reload --log-level debug
+	poetry run uvicorn src.backend.langflow.main:app --port 7860 --reload --log-level debug
 
 build_and_run:
 	echo 'Removing dist folder'
 	rm -rf dist
 	make build && poetry run pip install dist/*.tar.gz && poetry run langflow
 
+build_and_install:
+	echo 'Removing dist folder'
+	rm -rf dist
+	make build && poetry run pip install dist/*.tar.gz
+
 build_frontend:
 	cd src/frontend && CI='' npm run build
 	cp -r src/frontend/build src/backend/langflow/frontend

README.md

@@ -56,11 +56,11 @@ Alternatively, click the **"Open in Cloud Shell"** button below to launch Google
 
 Langflow integrates with langchain-serve to provide a one-command deployment to Jina AI Cloud.
 
-Start by installing `langchain-serve` with 
+Start by installing `langchain-serve` with
 
 ```bash
 pip install -U langchain-serve
-``` 
+```
 
 Then, run:
 
@@ -115,24 +115,38 @@ You can use Langflow directly on your browser, or use the API endpoints on Jina
   <summary>Show API usage (with python)</summary>
 
   ```python
-  import json
+import requests
-  import requests
 
-  FLOW_PATH = "Time_traveller.json"
+BASE_API_URL = "https://langflow-e3dd8820ec.wolf.jina.ai/api/v1/predict"
+FLOW_ID = "864c4f98-2e59-468b-8e13-79cd8da07468"
+# You can tweak the flow by adding a tweaks dictionary
+# e.g {"OpenAI-XXXXX": {"model_name": "gpt-4"}}
+TWEAKS = {
+  "ChatOpenAI-g4jEr": {},
+  "ConversationChain-UidfJ": {}
+}
 
-  # HOST = 'http://localhost:7860'
+def run_flow(message: str, flow_id: str, tweaks: dict = None) -> dict:
-  HOST = 'https://langflow-f1ed20e309.wolf.jina.ai'
+    """
-  API_URL = f'{HOST}/predict'
+    Run a flow with a given message and optional tweaks.
 
-  def predict(message):
+    :param message: The message to send to the flow
-      with open(FLOW_PATH, "r") as f:
+    :param flow_id: The ID of the flow to run
-          json_data = json.load(f)
+    :param tweaks: Optional tweaks to customize the flow
-      payload = {'exported_flow': json_data, 'message': message}
+    :return: The JSON response from the flow
-      response = requests.post(API_URL, json=payload)
+    """
-      return response.json()
+    api_url = f"{BASE_API_URL}/{flow_id}"
 
+    payload = {"message": message}
 
-  predict('Take me to 1920s Bangalore')
+    if tweaks:
+        payload["tweaks"] = tweaks
+
+    response = requests.post(api_url, json=payload)
+    return response.json()
+
+# Setup any tweaks you want to apply to the flow
+print(run_flow("Your message", flow_id=FLOW_ID, tweaks=TWEAKS))
   ```
 
   ```json

poetry.lock

@@ -909,14 +909,14 @@ test-randomorder = ["pytest-randomly"]
 
 [[package]]
 name = "ctransformers"
-version = "0.2.8"
+version = "0.2.9"
 description = "Python bindings for the Transformer models implemented in C/C++ using GGML library."
 category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "ctransformers-0.2.8-py3-none-any.whl", hash = "sha256:9804640364c13d93d58bfb6a9a1fa90d34b6438955d842c68ab05e5f8f15e023"},
+    {file = "ctransformers-0.2.9-py3-none-any.whl", hash = "sha256:ff0183ccf2bf157102cffacea13476cb78b8a2ffc2e1fdd46b57f8682a8da8ac"},
-    {file = "ctransformers-0.2.8.tar.gz", hash = "sha256:81c0436d8b5315211496566294d51e7bbd07cf6e4305608262eab04603b74b65"},
+    {file = "ctransformers-0.2.9.tar.gz", hash = "sha256:2165c512ee153f763c3d4ab133d666f86460010330d6bc75c0a6db6310ec9fc8"},
 ]
 
 [package.dependencies]
@@ -2444,14 +2444,14 @@ test = ["psutil", "pytest", "pytest-asyncio"]
 
 [[package]]
 name = "langchainplus-sdk"
-version = "0.0.10"
+version = "0.0.11"
 description = "Client library to connect to the LangChainPlus LLM Tracing and Evaluation Platform."
 category = "main"
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "langchainplus_sdk-0.0.10-py3-none-any.whl", hash = "sha256:6ea4013a92a4c33a61d22deb49620577c592a79ee44038b2c751032a71cbc7b6"},
+    {file = "langchainplus_sdk-0.0.11-py3-none-any.whl", hash = "sha256:fbe3482ffe253e439ec8386a2904594a875b590e29e4adcbd938452a69a6c7c6"},
-    {file = "langchainplus_sdk-0.0.10.tar.gz", hash = "sha256:4f810b38df74a99d01e5723e653da02f05df3ee922971cccabc365d00c33dbf6"},
+    {file = "langchainplus_sdk-0.0.11.tar.gz", hash = "sha256:e50679309a31d9526f467aa13d4dbcfba0dc00a295cea72ffcc9972865ecac1b"},
 ]
 
 [package.dependencies]
@@ -4265,14 +4265,14 @@ files = [
 
 [[package]]
 name = "pyparsing"
-version = "3.0.9"
+version = "3.1.0"
 description = "pyparsing module - Classes and methods to define and execute parsing grammars"
 category = "main"
 optional = false
 python-versions = ">=3.6.8"
 files = [
-    {file = "pyparsing-3.0.9-py3-none-any.whl", hash = "sha256:5026bae9a10eeaefb61dab2f09052b9f4307d44aee4eda64b309723d8d206bbc"},
+    {file = "pyparsing-3.1.0-py3-none-any.whl", hash = "sha256:d554a96d1a7d3ddaf7183104485bc19fd80543ad6ac5bdb6426719d766fb06c1"},
-    {file = "pyparsing-3.0.9.tar.gz", hash = "sha256:2b020ecf7d21b687f219b71ecad3631f644a47f01403fa1d1036b0c6416d70fb"},
+    {file = "pyparsing-3.1.0.tar.gz", hash = "sha256:edb662d6fe322d6e990b1594b5feaeadf806803359e3d4d42f11e295e588f0ea"},
 ]
 
 [package.extras]
@@ -5036,14 +5036,14 @@ files = [
 
 [[package]]
 name = "setuptools"
-version = "67.8.0"
+version = "68.0.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "setuptools-67.8.0-py3-none-any.whl", hash = "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f"},
+    {file = "setuptools-68.0.0-py3-none-any.whl", hash = "sha256:11e52c67415a381d10d6b462ced9cfb97066179f0e871399e006c4ab101fc85f"},
-    {file = "setuptools-67.8.0.tar.gz", hash = "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"},
+    {file = "setuptools-68.0.0.tar.gz", hash = "sha256:baf1fdb41c6da4cd2eae722e135500da913332ab3f2f5c7d33af9b492acb5235"},
 ]
 
 [package.extras]

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.1.2"
+version = "0.1.4"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [

src/backend/langflow/__main__.py

@@ -152,6 +152,17 @@ def serve(
         "timeout": timeout,
     }
 
+    if platform.system() in ["Windows"]:
+        # Run using uvicorn on MacOS and Windows
+        # Windows doesn't support gunicorn
+        # MacOS requires an env variable to be set to use gunicorn
+        run_on_windows(host, port, log_level, options, app)
+    else:
+        # Run using gunicorn on Linux
+        run_on_mac_or_linux(host, port, log_level, options, app, open_browser)
+
+
+def run_on_mac_or_linux(host, port, log_level, options, app, open_browser=True):
     webapp_process = Process(
         target=run_langflow, args=(host, port, log_level, options, app)
     )
@@ -169,6 +180,14 @@ def serve(
         webbrowser.open(f"http://{host}:{port}")
 
 
+def run_on_windows(host, port, log_level, options, app):
+    """
+    Run the Langflow server on Windows.
+    """
+    print_banner(host, port)
+    run_langflow(host, port, log_level, options, app)
+
+
 def setup_static_files(app: FastAPI, static_files_dir: Path):
     """
     Setup the static files directory.

src/backend/langflow/graph/graph/base.py

@@ -11,6 +11,7 @@ from langflow.graph.vertex.types import (
 from langflow.interface.tools.constants import FILE_TOOLS
 from langflow.utils import payload
 from langflow.utils.logger import logger
+from langchain.chains.base import Chain
 
 
 class Graph:
@@ -99,7 +100,7 @@ class Graph:
         ]
         return connected_nodes
 
-    def build(self) -> List[Vertex]:
+    def build(self) -> Chain:
         """Builds the graph."""
         # Get root node
         root_node = payload.get_root_node(self)

src/backend/langflow/processing/process.py

@@ -1,5 +1,6 @@
 import contextlib
 import io
+from pathlib import Path
 from langchain.schema import AgentAction
 import json
 from langflow.interface.run import (
@@ -10,8 +11,7 @@ from langflow.interface.run import (
 from langflow.utils.logger import logger
 from langflow.graph import Graph
 
-
+from typing import Any, Dict, List, Optional, Tuple, Union
-from typing import Any, Dict, List, Tuple
 
 
 def fix_memory_inputs(langchain_object):
@@ -20,22 +20,23 @@ def fix_memory_inputs(langchain_object):
     object's input variables. If so, it does nothing. Otherwise, it gets a possible new memory key using the
     get_memory_key function and updates the memory keys using the update_memory_keys function.
     """
-    if hasattr(langchain_object, "memory") and langchain_object.memory is not None:
+    if not hasattr(langchain_object, "memory") or langchain_object.memory is None:
-        try:
+        return
-            if langchain_object.memory.memory_key in langchain_object.input_variables:
+    try:
-                return
+        if langchain_object.memory.memory_key in langchain_object.input_variables:
-        except AttributeError:
+            return
-            input_variables = (
+    except AttributeError:
-                langchain_object.prompt.input_variables
+        input_variables = (
-                if hasattr(langchain_object, "prompt")
+            langchain_object.prompt.input_variables
-                else langchain_object.input_keys
+            if hasattr(langchain_object, "prompt")
-            )
+            else langchain_object.input_keys
-            if langchain_object.memory.memory_key in input_variables:
+        )
-                return
+        if langchain_object.memory.memory_key in input_variables:
+            return
 
-        possible_new_mem_key = get_memory_key(langchain_object)
+    possible_new_mem_key = get_memory_key(langchain_object)
-        if possible_new_mem_key is not None:
+    if possible_new_mem_key is not None:
-            update_memory_keys(langchain_object, possible_new_mem_key)
+        update_memory_keys(langchain_object, possible_new_mem_key)
 
 
 def format_actions(actions: List[Tuple[AgentAction, str]]) -> str:
@@ -131,57 +132,108 @@ def process_graph_cached(data_graph: Dict[str, Any], message: str):
     return {"result": str(result), "thought": thought.strip()}
 
 
-def load_flow_from_json(path: str, build=True):
+def load_flow_from_json(
-    """Load flow from json file"""
+    input: Union[Path, str, dict], tweaks: Optional[dict] = None, build=True
-    # This is done to avoid circular imports
+):
+    """
+    Load flow from a JSON file or a JSON object.
 
-    with open(path, "r", encoding="utf-8") as f:
+    :param input: JSON file path or JSON object
-        flow_graph = json.load(f)
+    :param tweaks: Optional tweaks to be processed
-    data_graph = flow_graph["data"]
+    :param build: If True, build the graph, otherwise return the graph object
-    nodes = data_graph["nodes"]
+    :return: Langchain object or Graph object depending on the build parameter
-    # Substitute ZeroShotPrompt with PromptTemplate
+    """
-    # nodes = replace_zero_shot_prompt_with_prompt_template(nodes)
+    # If input is a file path, load JSON from the file
-    # Add input variables
+    if isinstance(input, (str, Path)):
-    # nodes = payload.extract_input_variables(nodes)
+        with open(input, "r", encoding="utf-8") as f:
+            flow_graph = json.load(f)
+    # If input is a dictionary, assume it's a JSON object
+    elif isinstance(input, dict):
+        flow_graph = input
+    else:
+        raise TypeError(
+            "Input must be either a file path (str) or a JSON object (dict)"
+        )
 
-    # Nodes, edges and root node
+    graph_data = flow_graph["data"]
-    edges = data_graph["edges"]
+    if tweaks is not None:
+        graph_data = process_tweaks(graph_data, tweaks)
+    nodes = graph_data["nodes"]
+    edges = graph_data["edges"]
     graph = Graph(nodes, edges)
+
     if build:
         langchain_object = graph.build()
+
         if hasattr(langchain_object, "verbose"):
             langchain_object.verbose = True
 
         if hasattr(langchain_object, "return_intermediate_steps"):
-            # https://github.com/hwchase17/langchain/issues/2068
             # Deactivating until we have a frontend solution
             # to display intermediate steps
             langchain_object.return_intermediate_steps = False
+
         fix_memory_inputs(langchain_object)
         return langchain_object
+
     return graph
 
 
-def process_tweaks(graph_data: Dict, tweaks: Dict):
+def validate_input(
-    """This function is used to tweak the graph data using the node id and the tweaks dict"""
+    graph_data: Dict[str, Any], tweaks: Dict[str, Dict[str, Any]]
-    # the tweaks dict is a dict of dicts
+) -> List[Dict[str, Any]]:
-    # the key is the node id and the value is a dict of the tweaks
+    if not isinstance(graph_data, dict) or not isinstance(tweaks, dict):
-    # the dict of tweaks contains the name of a certain parameter and the value to be tweaked
+        raise ValueError("graph_data and tweaks should be dictionaries")
+
+    nodes = graph_data.get("data", {}).get("nodes") or graph_data.get("nodes")
+
+    if not isinstance(nodes, list):
+        raise ValueError(
+            "graph_data should contain a list of nodes under 'data' key or directly under 'nodes' key"
+        )
+
+    return nodes
+
+
+def apply_tweaks(node: Dict[str, Any], node_tweaks: Dict[str, Any]) -> None:
+    template_data = node.get("data", {}).get("node", {}).get("template")
+
+    if not isinstance(template_data, dict):
+        logger.warning(
+            f"Template data for node {node.get('id')} should be a dictionary"
+        )
+        return
+
+    for tweak_name, tweak_value in node_tweaks.items():
+        if tweak_name and tweak_value and tweak_name in template_data:
+            template_data[tweak_name]["value"] = tweak_value
+
+
+def process_tweaks(
+    graph_data: Dict[str, Any], tweaks: Dict[str, Dict[str, Any]]
+) -> Dict[str, Any]:
+    """
+    This function is used to tweak the graph data using the node id and the tweaks dict.
+
+    :param graph_data: The dictionary containing the graph data. It must contain a 'data' key with
+                       'nodes' as its child or directly contain 'nodes' key. Each node should have an 'id' and 'data'.
+    :param tweaks: A dictionary where the key is the node id and the value is a dictionary of the tweaks.
+                   The inner dictionary contains the name of a certain parameter as the key and the value to be tweaked.
+
+    :return: The modified graph_data dictionary.
+
+    :raises ValueError: If the input is not in the expected format.
+    """
+    nodes = validate_input(graph_data, tweaks)
 
-    # We need to process the graph data to add the tweaks
-    if "data" not in graph_data and "nodes" in graph_data:
-        nodes = graph_data["nodes"]
-    else:
-        nodes = graph_data["data"]["nodes"]
     for node in nodes:
-        node_id = node["id"]
+        if isinstance(node, dict) and isinstance(node.get("id"), str):
-        if node_id in tweaks:
+            node_id = node["id"]
-            node_tweaks = tweaks[node_id]
+            if node_tweaks := tweaks.get(node_id):
-            template_data = node["data"]["node"]["template"]
+                apply_tweaks(node, node_tweaks)
-            for tweak_name, tweake_value in node_tweaks.items():
+        else:
-                if tweak_name in template_data:
+            logger.warning(
-                    template_data[tweak_name]["value"] = tweake_value
+                "Each node should be a dictionary with an 'id' key of type str"
-                    print(
+            )
-                        f"Something changed in node {node_id} with tweak {tweak_name} and value {tweake_value}"
+
-                    )
     return graph_data

src/frontend/src/components/headerComponent/index.tsx

@@ -1,6 +1,6 @@
 import { BellIcon, Home, Users2 } from "lucide-react";
-import { useContext } from "react";
+import { useContext, useEffect, useState } from "react";
-import { FaGithub } from "react-icons/fa";
+import { FaDiscord, FaGithub, FaTwitter } from "react-icons/fa";
 import { Button } from "../ui/button";
 import { TabsContext } from "../../contexts/tabsContext";
 import AlertDropdown from "../../alerts/alertDropDown";
@@ -11,6 +11,7 @@ import { typesContext } from "../../contexts/typesContext";
 import MenuBar from "./components/menuBar";
 import { Link, useLocation, useParams } from "react-router-dom";
 import { USER_PROJECTS_HEADER } from "../../constants";
+import { getRepoStars } from "../../controllers/API";
 
 export default function Header() {
   const { flows, addFlow, tabId } = useContext(TabsContext);
@@ -22,6 +23,16 @@ export default function Header() {
   const { notificationCenter, setNotificationCenter, setErrorData } =
     useContext(alertContext);
   const location = useLocation();
+
+  const [stars, setStars] = useState(null);
+
+  useEffect(() => {
+    async function fetchStars() {
+      const starsCount = await getRepoStars("logspace-ai", "langflow");
+      setStars(starsCount);
+    }
+    fetchStars();
+  }, []);
   return (
     <div className="w-full h-12 flex justify-between items-center border-b bg-muted">
       <div className="flex gap-2 justify-start items-center w-96">
@@ -57,22 +68,35 @@ export default function Header() {
         </Link>
       </div>
       <div className="flex justify-end px-2 w-96">
-        <div className="ml-auto mr-2 flex gap-5">
+        <div className="ml-auto mr-2 flex gap-5 items-center">
-          <Button
-            asChild
-            variant="outline"
-            className="text-gray-600 dark:text-gray-300 "
-          >
             <a
               href="https://github.com/logspace-ai/langflow"
               target="_blank"
               rel="noreferrer"
-              className="flex"
+              className="inline-flex items-center justify-center text-sm font-medium transition-colors focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:opacity-50 disabled:pointer-events-none ring-offset-background text-gray-600 dark:text-gray-300 border border-input hover:bg-accent hover:text-accent-foreground h-9 px-3 pr-0 rounded-md"
             >
               <FaGithub className="h-5 w-5 mr-2" />
-              Join The Community
+              Star
+              <div className="ml-2 flex text-sm bg-background rounded-md rounded-l-none border px-2 h-9 -mr-px items-center justify-center">
+                {stars}
+              </div>
+            </a>
+            <a
+              href="https://twitter.com/logspace_ai"
+              target="_blank"
+              rel="noreferrer"
+              className="text-muted-foreground"
+            >
+              <FaTwitter className="h-5 w-5" />
+            </a>
+            <a
+              href="https://discord.gg/EqksyE2EX9"
+              target="_blank"
+              rel="noreferrer"
+              className="text-muted-foreground"
+            >
+              <FaDiscord className="h-5 w-5" />
             </a>
-          </Button>
           {/* <button
             className="text-gray-600 hover:text-gray-500 dark:text-gray-300 dark:hover:text-gray-200"
             onClick={() => {
@@ -110,12 +134,6 @@ export default function Header() {
             )}
             <BellIcon className="h-5 w-5" aria-hidden="true" />
           </button>
-          {/* <button>
-            <img
-              src="https://github.com/shadcn.png"
-              className="rounded-full w-8"
-            />
-          </button> */}
         </div>
       </div>
     </div>

src/frontend/src/constants.tsx

@@ -121,11 +121,12 @@ export const getCurlCode = (flow: FlowType): string => {
  */
 export const getPythonCode = (flow: FlowType): string => {
   const flowName = flow.name;
+  const tweaks = buildTweaks(flow);
   return `from langflow import load_flow_from_json
-
+TWEAKS = ${JSON.stringify(tweaks, null, 2)}
-    flow = load_flow_from_json("${flowName}.json")
+flow = load_flow_from_json("${flowName}.json", tweaks=TWEAKS)
-    # Now you can use it like any chain
+# Now you can use it like any chain
-    flow("Hey, have you heard of LangFlow?")`;
+flow("Hey, have you heard of LangFlow?")`;
 };
 
 /**

src/frontend/src/controllers/API/index.ts

@@ -18,6 +18,18 @@ export async function getAll(): Promise<AxiosResponse<APIObjectType>> {
   return await axios.get(`/api/v1/all`);
 }
 
+const GITHUB_API_URL = "https://api.github.com";
+
+export async function getRepoStars(owner, repo) {
+  try {
+    const response = await axios.get(`${GITHUB_API_URL}/repos/${owner}/${repo}`);
+    return response.data.stargazers_count;
+  } catch (error) {
+    console.error("Error fetching repository data:", error);
+    return null;
+  }
+}
+
 /**
  * Sends data to the API for prediction.
  *

tests/test_loading.py

@@ -14,6 +14,15 @@ def test_load_flow_from_json():
     assert isinstance(loaded, Chain)
 
 
+def test_load_flow_from_json_with_tweaks():
+    """Test loading a flow from a json file and applying tweaks"""
+    tweaks = {"dndnode_82": {"model_name": "test model"}}
+    loaded = load_flow_from_json(pytest.BASIC_EXAMPLE_PATH, tweaks=tweaks)
+    assert loaded is not None
+    assert isinstance(loaded, Chain)
+    assert loaded.llm.model_name == "test model"
+
+
 def test_get_root_node():
     with open(pytest.BASIC_EXAMPLE_PATH, "r") as f:
         flow_graph = json.load(f)