Comments (2)
To resolve the issue where there is no response when running the Flow using cURL or the Python API, and attempts to ping the server result in an "unknown host" error, you can follow the documentation provided for deploying Langflow apps in backend-only mode or on Google Cloud Platform (GCP).
Here are the steps to ensure proper deployment and interaction with the Langflow server:
-
Start Langflow in Backend-Only Mode:
python3 -m langflow run --backend-only
This command will start Langflow in backend-only mode, exposing the API without running the frontend UI. The terminal should print
Welcome to ⛓ Langflow
, and a blank window should open athttp://127.0.0.1:7864/all
. -
Download Your Flow's cURL Call:
- Click on API in the Langflow UI.
- Click curl > Copy code and save the code to your local machine. The cURL command will look something like this:
curl -X POST \ "http://127.0.0.1:7864/api/v1/run/ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef?stream=false" \ -H 'Content-Type: application/json' \ -d '{"input_value": "message", "output_type": "chat", "input_type": "chat", "tweaks": {"Prompt-kvo86": {}, "OpenAIModel-MilkD": {}, "ChatOutput-ktwdw": {}, "ChatInput-xXC4F": {}}}'
-
Run the cURL Command:
curl -X POST \ "http://127.0.0.1:7864/api/v1/run/ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef?stream=false" \ -H 'Content-Type: application/json' \ -d '{"input_value": "message", "output_type": "chat", "input_type": "chat", "tweaks": {"Prompt-kvo86": {}, "OpenAIModel-MilkD": {}, "ChatOutput-ktwdw": {}, "ChatInput-xXC4F": {}}}'
-
Download Your Flow's Python API Call:
- Click on API in the Langflow UI.
- Click Python API > Copy code and save the code to your local machine. The Python code will look something like this:
import requests from typing import Optional BASE_API_URL = "http://127.0.0.1:7864/api/v1/run" FLOW_ID = "ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef" def run_flow(message: str, flow_id: str, output_type: str = "chat", input_type: str = "chat", tweaks: Optional[dict] = None, api_key: Optional[str] = None) -> dict: api_url = f"{BASE_API_URL}/{flow_id}" payload = { "input_value": message, "output_type": output_type, "input_type": input_type, } headers = None if tweaks: payload["tweaks"] = tweaks if api_key: headers = {"x-api-key": api_key} response = requests.post(api_url, json=payload, headers=headers) return response.json() message = "message" print(run_flow(message=message, flow_id=FLOW_ID))
-
Run Your Python App:
python3 app.py
-
Check Your Environment Configuration:
Ensure that your.env
file is correctly configured. Here is an example configuration:DOMAIN=localhost STACK_NAME=langflow-stack ENVIRONMENT=development TRAEFIK_PUBLIC_NETWORK=traefik-public TRAEFIK_TAG=langflow-traefik TRAEFIK_PUBLIC_TAG=traefik-public # RabbitMQ configuration RABBITMQ_DEFAULT_USER=langflow RABBITMQ_DEFAULT_PASS=langflow # Database configuration DB_USER=langflow DB_PASSWORD=langflow DB_HOST=db DB_PORT=5432 DB_NAME=langflow # Logging configuration LOG_LEVEL=debug # DB configuration POSTGRES_USER=langflow POSTGRES_PASSWORD=langflow POSTGRES_DB=langflow POSTGRES_PORT=5432 # Flower configuration LANGFLOW_CACHE_TYPE=redis LANGFLOW_REDIS_HOST=result_backend LANGFLOW_REDIS_PORT=6379 LANGFLOW_REDIS_DB=0 LANGFLOW_REDIS_EXPIRE=3600 LANGFLOW_REDIS_PASSWORD= FLOWER_UNAUTHENTICATED_API=True BROKER_URL=amqp://langflow:langflow@broker:5672 RESULT_BACKEND=redis://result_backend:6379/0 C_FORCE_ROOT="true" # Frontend configuration VITE_PROXY_TARGET=http://backend:7860/api/ BACKEND_URL=http://backend:7860 # PGAdmin configuration [email protected] PGADMIN_DEFAULT_PASSWORD=admin # OpenAI configuration (for testing purposes) OPENAI_API_KEY=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 # Superuser configuration LANGFLOW_SUPERUSER=superuser LANGFLOW_SUPERUSER_PASSWORD=superuser # New user configuration LANGFLOW_NEW_USER_IS_ACTIVE=False
-
Deploy Langflow on Google Cloud Platform (GCP):
If you are deploying Langflow on GCP, you can use the following script to set up the environment and deploy the application:# Set the VM, image, and networking configuration VM_NAME="langflow-dev" IMAGE_FAMILY="debian-11" IMAGE_PROJECT="debian-cloud" BOOT_DISK_SIZE="100GB" ZONE="us-central1-a" REGION="us-central1" VPC_NAME="default" SUBNET_NAME="default" SUBNET_RANGE="10.128.0.0/20" NAT_GATEWAY_NAME="nat-gateway" CLOUD_ROUTER_NAME="nat-client" # Set the GCP project's compute region gcloud config set compute/region $REGION # Check if the VPC exists, and create it if not vpc_exists=$(gcloud compute networks list --filter="name=$VPC_NAME" --format="value(name)") if [[ -z "$vpc_exists" ]]; then gcloud compute networks create $VPC_NAME --subnet-mode=custom fi # Check if the subnet exists, and create it if not subnet_exists=$(gcloud compute networks subnets list --filter="name=$SUBNET_NAME AND region=$REGION" --format="value(name)") if [[ -z "$subnet_exists" ]]; then gcloud compute networks subnets create $SUBNET_NAME --network=$VPC_NAME --region=$REGION --range=$SUBNET_RANGE fi # Create a firewall rule to allow TCP port 7860 for all instances in the VPC firewall_7860_exists=$(gcloud compute firewall-rules list --filter="name=allow-tcp-7860" --format="value(name)") if [[ -z "$firewall_7860_exists" ]]; then gcloud compute firewall-rules create allow-tcp-7860 --network $VPC_NAME --allow tcp:7860 --source-ranges 0.0.0.0/0 --direction INGRESS fi # Create a firewall rule to allow IAP traffic firewall_iap_exists=$(gcloud compute firewall-rules list --filter="name=allow-iap" --format="value(name)") if [[ -z "$firewall_iap_exists" ]]; then gcloud compute firewall-rules create allow-iap --network $VPC_NAME --allow tcp:80,tcp:443,tcp:22,tcp:3389 --source-ranges 35.235.240.0/20 --direction INGRESS fi # Define the startup script as a multiline Bash here-doc STARTUP_SCRIPT=$(cat <<'EOF' #!/bin/bash # Update and upgrade the system apt -y update apt -y upgrade # Install Python 3 pip, Langflow, and Nginx apt -y install python3-pip pip install langflow langflow --host 0.0.0.0 --port 7860 EOF ) # Create a temporary file to store the startup script tempfile=$(mktemp) echo "$STARTUP_SCRIPT" > $tempfile # Create the VM instance with the specified configuration and startup script gcloud compute instances create $VM_NAME \ --image-family $IMAGE_FAMILY \ --image-project $IMAGE_PROJECT \ --boot-disk-size $BOOT_DISK_SIZE \ --machine-type=n1-standard-4 \ --metadata-from-file startup-script=$tempfile \ --zone $ZONE \ --network $VPC_NAME \ --subnet $SUBNET_NAME \ --preemptible # Remove the temporary file after the VM is created rm $tempfile
By following these steps and ensuring your environment is correctly configured, you should be able to deploy your Langflow app correctly and resolve the issue of no response when running the Flow using cURL or the Python API. If the "unknown host" error persists, ensure that the server is running and accessible at the specified address (http://127.0.0.1:7864
) [1][2][3][4][5].
To continue talking to Dosu, mention @dosu.
from langflow.
The Issue is solved!
from langflow.
Related Issues (20)
- [Feature Request] Add support for `dimensions` parameter in embedding models
- [Feature Request] Support secretes stored in Kubernetes
- [Feature Request] A generic SecretService to support store secrets
- langflow build hangs HOT 3
- [Tests] Add astra db integration tests
- How to implement timed updates of data to the knowledge base in Langflow HOT 1
- [Feature Requests] Support Astra Vectorize
- Error code 422 Unprocessable Entity, When Running cURL Code for Langflow Flow with TWEAKS HOT 1
- some advise HOT 1
- 对话AzureOpenAI 报错 HOT 3
- TWEAKS never work via API HOT 2
- If I want to execute a flow using a webhook in the form of a curl command, how should I do it? HOT 3
- Proposal: Enhancing the `get_messages` Method to Support Timestamp Filtering
- Chroma and Astra DB Search components not allowing Chat Input HOT 19
- [a58 bug] Chat Input stopped working with Azure OpenAI model/embedding component HOT 2
- [a58 bug] Azure OpenAI global variables passed via "--env-file" doesn't work correctly HOT 1
- Qdrant Search: Invalid Input from "Chat Input" in v1.0.0a58 HOT 3
- [Feature Request] Control Output Values of ChatMemory and MessageHistory Components
- Faiss search error HOT 2
- The outout of the Chat Input is not been recognized as text by OpenAI model HOT 6
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from langflow.