guidance-example.py
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import guidance
gpt35 = guidance.models.OpenAI("gpt-3.5-turbo")
import re
from guidance import gen, select, system, user, assistant
@guidance
def plan_for_goal(lm, goal: str):
# This is a helper function which we will use below
def parse_best(prosandcons, options):
best = re.search(r'Best=(\d+)', prosandcons)
if not best:
best = re.search(r'Best.*?(\d+)', 'Best= option is 3')
if best:
best = int(best.group(1))
else:
best = 0
return options[best]
# Some general instruction to the model
with system():
lm += "You are a helpful assistant."
# Simulate a simple request from the user
# Note that we switch to using 'lm2' here, because these are intermediate steps (so we don't want to overwrite the current lm object)
with user():
lm2 = lm + f"""\
I want to {goal}
Can you please generate one option for how to accomplish this?
Please make the option very short, at most one line."""
# Generate several options. Note that this means several sequential generation requests
n_options = 5
with assistant():
options = []
for i in range(n_options):
options.append((lm2 + gen(name='option', temperature=1.0, max_tokens=50))["option"])
# Have the user request pros and cons
with user():
lm2 += f"""\
I want to {goal}
Can you please comment on the pros and cons of each of the following options, and then pick the best option?
---
"""
for i, opt in enumerate(options):
lm2 += f"Option {i}: {opt}\n"
lm2 += f"""\
---
Please discuss each option very briefly (one line for pros, one for cons), and end by saying Best=X, where X is the number of the best option."""
# Get the pros and cons from the model
with assistant():
lm2 += gen(name='prosandcons', temperature=0.0, max_tokens=600, stop="Best=") + "Best=" + gen("best", regex="[0-9]+")
# The user now extracts the one selected as the best, and asks for a full plan
# We switch back to 'lm' because this is the final result we want
with user():
lm += f"""\
I want to {goal}
Here is my plan: {options[int(lm2["best"])]}
Please elaborate on this plan, and tell me how to best accomplish it."""
# The plan is generated
with assistant():
lm += gen(name='plan', max_tokens=500)
return lm
1 | import guidance |
2 | gpt35 = guidance.models.OpenAI("gpt-3.5-turbo") |
3 | |
4 | import re |
5 | from guidance import gen, select, system, user, assistant |
6 | |
7 | @guidance |
8 | def plan_for_goal(lm, goal: str): |
9 | |
10 | # This is a helper function which we will use below |
11 | def parse_best(prosandcons, options): |
12 | best = re.search(r'Best=(\d+)', prosandcons) |
13 | if not best: |
14 | best = re.search(r'Best.*?(\d+)', 'Best= option is 3') |
15 | if best: |
16 | best = int(best.group(1)) |
17 | else: |
18 | best = 0 |
19 | return options[best] |
20 | |
21 | # Some general instruction to the model |
22 | with system(): |
23 | lm += "You are a helpful assistant." |
24 | |
25 | # Simulate a simple request from the user |
26 | # Note that we switch to using 'lm2' here, because these are intermediate steps (so we don't want to overwrite the current lm object) |
27 | with user(): |
28 | lm2 = lm + f"""\ |
29 | I want to {goal} |
30 | Can you please generate one option for how to accomplish this? |
31 | Please make the option very short, at most one line.""" |
32 | |
33 | # Generate several options. Note that this means several sequential generation requests |
34 | n_options = 5 |
35 | with assistant(): |
36 | options = [] |
37 | for i in range(n_options): |
38 | options.append((lm2 + gen(name='option', temperature=1.0, max_tokens=50))["option"]) |
39 | |
40 | # Have the user request pros and cons |
41 | with user(): |
42 | lm2 += f"""\ |
43 | I want to {goal} |
44 | Can you please comment on the pros and cons of each of the following options, and then pick the best option? |
45 | --- |
46 | """ |
47 | for i, opt in enumerate(options): |
48 | lm2 += f"Option {i}: {opt}\n" |
49 | lm2 += f"""\ |
50 | --- |
51 | Please discuss each option very briefly (one line for pros, one for cons), and end by saying Best=X, where X is the number of the best option.""" |
52 | |
53 | # Get the pros and cons from the model |
54 | with assistant(): |
55 | lm2 += gen(name='prosandcons', temperature=0.0, max_tokens=600, stop="Best=") + "Best=" + gen("best", regex="[0-9]+") |
56 | |
57 | # The user now extracts the one selected as the best, and asks for a full plan |
58 | # We switch back to 'lm' because this is the final result we want |
59 | with user(): |
60 | lm += f"""\ |
61 | I want to {goal} |
62 | Here is my plan: {options[int(lm2["best"])]} |
63 | Please elaborate on this plan, and tell me how to best accomplish it.""" |
64 | |
65 | # The plan is generated |
66 | with assistant(): |
67 | lm += gen(name='plan', max_tokens=500) |
68 | |
69 | return lm |
70 | |
71 |