{% include 'pages/navbar.html' %}
← LLM campaigns
New LLM {% if mode == 'llm_gen' %}generation{% else %}evaluation{% endif %} campaign
Campaign
Configuration
Data
Campaign Id
Next
Preset
[None]
{% for config_name in configs.keys() %}
{{ config_name }}
{% endfor %}
{% if mode == 'llm_eval' %} {% include 'include/annotation_span_categories.html' %}
✨ Pre-fill prompt template
📝 Add example to template
{% endif %}
Prompt template
Prompt for the model. See the instructions for configuring the prompt at
factgenie wiki
.
System message
Role of the model (optional).
{% if mode == 'llm_gen' %}
Start with
The model will need to start the generated text with this string (optional).
{% endif %}
LLM evaluator
Select one of the available LLM evaluators (or add your own class to
factgenie/models.py
).
{% for metric_type in metric_types %}
{{ metric_type }}
{% endfor %}
API URL
For Ollama API, this is the API URL, e.g.
http://my-server.com:11434/api/
. The parameter is ignored for OpenAI API.
Model
The identifier of the model you are querying.
Model arguments
API arguments to be passed to the model. Internally, we use
ast.literal_eval()
for determining the argument type. Use floating point format (e.g. 0.0) for the numbers that should be interpreted as floats.
+
Extra arguments
Any other parameters used by the metric.
+
Back
Save config as...
Next
{% include 'include/data_selection.html' %}
Back
Create campaign
{% include 'include/example_annotation_modal.html' %}
Save config as...
Config name
.yaml
{% for filename in configs.keys() %}
{{ filename }}
{% endfor %}