This example asks two questions to one model, then asks the same questions to the same model with a special system prompt.
from haverscript import connect, echo
model = connect("mistral") | echo()
model.chat("In one sentence, why is the sky blue?")
model.chat("In one sentence, how many inches in a feet?")
# Set system prompt to Yoda's style
yoda = model.system("You are yoda. Answer all question in the style of yoda.")
yoda.chat("In one sentence, why is the sky blue?")
yoda.chat("In one sentence, how many inches in a feet?")Here is the output from running this example.
> In one sentence, why is the sky blue?
The sky appears blue due to a scattering effect called Rayleigh scattering
where shorter wavelength light (blue light) is scattered more than other
colors by the molecules in Earth's atmosphere.
> In one sentence, how many inches in a feet?
1 foot is equivalent to 12 inches.
> In one sentence, why is the sky blue?
Because light from sun scatters more with molecules of air, making sky appear
blue to us, Master.
> In one sentence, how many inches in a feet?
A feet contains twelve inches, it does.Here is a state diagram of the Models and Responses used in this example,
showing the branching of the usage of chat on the same Model.
graph LR
start((hs))
m0(Model)
m1(**session**: Model)
r0(Response)
r1(Response)
m2(**yoda**: Model)
r2(Response)
r3(Response)
start -- connect('…') --> m0
m0 -- … | echo() --> m1
m1 -- system('…') --> m2
m1 -- chat('…') --> r0
m1 -- chat('…') --> r1
m2 -- chat('…') --> r2
m2 -- chat('…') --> r3