Langtrace is an open source observability software which lets you capture, debug and analyze traces and metrics from all your applications that leverages LLM APIs, Vector Databases and LLM based Frameworks.
The traces generated by Langtrace adhere to Open Telemetry Standards(OTEL). We are developing semantic conventions for the traces generated by this project. You can checkout the current definitions in this repository. Note: This is an ongoing development and we encourage you to get involved and welcome your feedback.
To use the managed SaaS version of Langtrace, follow the steps below:
- Sign up by going to this link.
- Create a new Project after signing up. Projects are containers for storing traces and metrics generated by your application. If you have only one application, creating 1 project will do.
- Generate an API key by going inside the project.
- In your application, install the Langtrace SDK and initialize it with the API key you generated in the step 3.
- The code for installing and setting up the SDK is shown below:
npmi @langtrase/typescript-sdkimport*asLangtracefrom'@langtrase/typescript-sdk'// Must precede any llm module importsLangtrace.init({api_key: <your_api_key>})OR
import*asLangtracefrom'@langtrase/typescript-sdk'// Must precede any llm module importsLangTrace.init()// LANGTRACE_API_KEY as an ENVIRONMENT variablepipinstalllangtrace-python-sdkfromlangtrace_python_sdkimportlangtracelangtrace.init(api_key=<your_api_key>)OR
fromlangtrace_python_sdkimportlangtracelangtrace.init() # LANGTRACE_API_KEY as an ENVIRONMENT variableTo run the Langtrace locally, you have to run three services:
- Next.js app
- Postgres database
- Clickhouse database
Requirements:
- Docker
- Docker Compose
Feel free to modify the .env file to suit your needs.
docker compose upThe application will be available at http://localhost:3000.
Note
if you wish to build the docker image locally and use it, run the docker compose up command with the --build flag.
Tip
to manually pull the docker image from docker hub, run the following command:
docker pull scale3labs/langtrace-client:latestTo delete containers and volumes
```bashdocker compose down -v-v flag is used to delete volumes
The following are some commands that may come handy during setup and debugging.
Connecting to postgres db
docker exec -it langtrace-postgres psql --dbname=langtrace --username=ltuser --passwordConnecting to clickhouse server
docker exec -it langtrace-clickhouse clickhouse-clientChecking langtrace client app logs
docker logs langtraceIf you want to follow the logs
docker logs -f langtraceRunning prisma schema apply command
docker exec -it langtrace npm run create-tablesTable not found error OR Column not found error
Its likely that schema is not applied to the database or the schema is not in sync with the database. To fix this, run the following command:docker exec -it langtrace npm run create-tablesPrisma schema not in sync with database
If you have made changes to the prisma schema and want to apply the changes to the database, run the following command:docker exec -it langtrace npm run create-tablesDocker compose failing to setup with `Additional property required is not allowed` errors
Its likely that you are using an older version of docker-compose. Update docker-compose to the latest version.Certain docker compose schema used in this project are only supported in newer versions of docker-compose.
Either you update the docker compose version OR remove the depends_on property that is causing the error.
Clickhouse server not starting
If clickhouse server is not starting, it is likely that the port 8123 is already in use. You can change the port in the docker-compose file.Install the langtrace SDK in your application by following the same instructions under the Langtrace Cloud section above for sending traces to your self hosted setup.
Langtrace automatically captures traces from the following vendors:
| Vendor | Type | Typescript SDK | Python SDK |
|---|---|---|---|
| OpenAI | LLM | ✅ | ✅ |
| Anthropic | LLM | ✅ | ✅ |
| Azure OpenAI | LLM | ✅ | ✅ |
| Langchain | Framework | ❌ | ✅ |
| LlamaIndex | Framework | ✅ | ✅ |
| Pinecone | Vector Database | ✅ | ✅ |
| ChromaDB | Vector Database | ✅ | ✅ |
- To request for features, head over here to start a discussion.
- To raise an issue, head over here and create an issue.
We welcome contributions to this project. To get started, fork this repository and start developing. To get involved, join our Slack workspace.
To report security vulnerabilites, email us at security@scale3labs.com. You can read more on security here.
- Langtrace application(this repository) is licensed under the AGPL 3.0 License. You can read about this license here.
- Langtrace SDKs are licensed under the Apache 2.0 License. You can read about this license here.
1. Can I self host and run Langtrace in my own cloud? Yes, you can absolutely do that. Follow the self hosting setup instructions laid out above.
2. What is the pricing for Langtrace cloud? Currently, we are not charging anything for Langtrace cloud and we are primarily looking for feedback so we can continue to improve the project. We will inform our users when we decide to monetize it.
3. What is the tech stack of Langtrace? Langtrace uses NextJS for the frontend and APIs. It uses PostgresDB as a metadata store and Clickhouse DB for storing spans, metrics, logs and traces.
4. Can I contribute to this project? Absolutely! We love developers and welcome contributions. Get involved early by joining our slack workspace.
5. What skillset is required to contribute to this project? Programming Languages: Typescript and Python. Framework knowledge: NextJS. Database: Postgres and Prisma ORM. Nice to haves: Opentelemetry instrumentation framework, experience with distributed tracing.