list_experiments
Retrieve and filter LangSmith experiment projects for model evaluation and comparison by specifying a dataset ID or name.
Instructions
List LangSmith experiment projects (reference projects) with mandatory dataset filtering.
Fetches experiment projects from LangSmith that are associated with a specific dataset. These are projects used for model evaluation and comparison. Requires either a dataset ID or dataset name to filter experiments.
🧩 PURPOSE
This function provides a convenient way to list and explore LangSmith experiment projects. It supports:
Filtering experiments by reference dataset (mandatory)
Filtering projects by name (partial match)
Limiting the number of results
Automatically extracting deployment IDs from nested project data
Returns simplified project information with key metrics (latency, cost, feedback stats)
⚙️ PARAMETERS
reference_dataset_id : str, optional
The ID of the reference dataset to filter experiments by.
Either this OR reference_dataset_name must be provided (but not both).
reference_dataset_name : str, optional
The name of the reference dataset to filter experiments by.
Either this OR reference_dataset_id must be provided (but not both).
limit : int, default 5 Maximum number of experiments to return. This can be adjusted by agents or users based on their needs.
project_name : str, optional
Filter projects by name using partial matching. If provided, only projects
whose names contain this string will be returned.
Example: project_name="Chat" will match "Chat-LangChain", "ChatBot", etc.
📤 RETURNS
Dict[str, Any] A dictionary containing an "experiments" key with a list of simplified experiment project dictionaries:
```python
{
"experiments": [
{
"name": "Experiment-Chat-LangChain",
"experiment_id": "787d5165-f110-43ff-a3fb-66ea1a70c971",
"feedback_stats": {...}, # Feedback statistics if available
"latency_p50_seconds": 1.626, # 50th percentile latency in seconds
"latency_p99_seconds": 2.390, # 99th percentile latency in seconds
"total_cost": 0.00013005, # Total cost in dollars
"prompt_cost": 0.00002085, # Prompt cost in dollars
"completion_cost": 0.0001092, # Completion cost in dollars
"agent_deployment_id": "deployment-123" # Only if available
},
...
]
}
```🧪 EXAMPLES
1️⃣ List experiments for a dataset by ID
experiments = list_experiments(reference_dataset_id="f5ca13c6-96ad-48ba-a432-ebb6bf94528f")2️⃣ List experiments for a dataset by name
experiments = list_experiments(reference_dataset_name="my-dataset", limit=10)3️⃣ Find experiments with specific name pattern
experiments = list_experiments(
reference_dataset_id="f5ca13c6-96ad-48ba-a432-ebb6bf94528f",
project_name="Chat",
limit=1
)🧠 NOTES FOR AGENTS
Returns simplified experiment information with key metrics (latency, cost, feedback stats)
The
agent_deployment_idfield is automatically extracted from nested project data when available, making it easy to identify agent deploymentsExperiments are filtered to include only reference projects (associated with datasets)
The function uses
name_containsfor filtering, so partial matches workYou must provide either
reference_dataset_idORreference_dataset_name, but not bothExperiment projects are used for model evaluation and comparison across different runs
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| reference_dataset_id | No | ||
| reference_dataset_name | No | ||
| limit | No | ||
| project_name | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||