Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LOGFIRE_BASE_URL | No | The base URL of the Logfire API instance | https://logfire-api.pydantic.dev |
| LOGFIRE_READ_TOKEN | Yes | Your Logfire read token for accessing the Logfire APIs |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| find_exceptions_in_file | Get the details about the 10 most recent exceptions on the file. |
| arbitrary_query | Run an arbitrary query on the Pydantic Logfire database. The SQL reference is available via the `sql_reference` tool. |
| logfire_link | Creates a link to help the user to view the trace in the Logfire UI. |
| schema_reference | The database schema for the Logfire DataFusion database. This includes all tables, columns, and their types as well as descriptions.
For example:
```sql
-- The records table contains spans and logs.
CREATE TABLE records (
message TEXT, -- The message of the record
span_name TEXT, -- The name of the span, message is usually templated from this
trace_id TEXT, -- The trace ID, identifies a group of spans in a trace
exception_type TEXT, -- The type of the exception
exception_message TEXT, -- The message of the exception
-- other columns...
);
```
The SQL syntax is similar to Postgres, although the query engine is actually Apache DataFusion.
To access nested JSON fields e.g. in the `attributes` column use the `->` and `->>` operators.
You may need to cast the result of these operators e.g. `(attributes->'cost')::float + 10`.
You should apply as much filtering as reasonable to reduce the amount of data queried.
Filters on `start_timestamp`, `service_name`, `span_name`, `metric_name`, `trace_id` are efficient. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |