In this notebook, you'll learn how to get started with the PaLM API, which gives you access to Google's latest large language models. Here, you'll learn how to use the PaLM API's text generation features.

## Setup

````pip install -q google-generativeai`
```
``````import pprint
``````

### Grab an API Key

To get started, you'll need to create an API key.

``````palm.configure(api_key='YOUR_API_KEY')
``````

## Text generation

Use the `palm.list_models` function to find available models:

``````models = [m for m in palm.list_models() if 'generateText' in m.supported_generation_methods]
model = models.name
print(model)
``````
```models/text-bison-001
```

Use the `palm.generate_text` method to generate text:

``````prompt = """
You are an expert at solving word problems.

Solve the following problem:

I have three houses, each with three cats.
each cat owns 4 mittens, and a hat. Each mitten was
knit from 7m of yarn, each hat from 4m.
How much yarn was needed to make all the items?

"""

completion = palm.generate_text(
model=model,
prompt=prompt,
temperature=0,
# The maximum length of the response
max_output_tokens=800,
)

print(completion.result)
``````
```There are 3 houses * 3 cats / house = 9 cats. So, 9 cats * 4 mittens / cat = 36 mittens were made. Also, 9 cats * 1 hat / cat = 9 hats were made. So, 36 mittens * 7m / mitten = 252m of yarn was used for the mittens. Also, 9 hats * 4m / hat = 36m of yarn was used for the hats. In total, 252m + 36m = 288m of yarn was used.
```

## More options

The `palm.generate_text` function has a few other arguments worth mentioning.

### Stop sequences

Use the `stop_sequences` argument to stop generation early.

For example LLM's often make mistakes in arithmetic. You could ask the model to "use a calculator" by putting equations in a `<calc>` tag.

Have the model stop at the closing tag, so you can edit the prompt:

``````calc_prompt = f"""

{prompt}

----------------

Important: Use the calculator for each step.

To use the calculator wrap an equation in <calc> tags like this:

<calc> 3 cats * 2 hats/cat </calc> = 6

----------------

"""

equation=None
while equation is None:
completion = palm.generate_text(
model=model,
prompt=calc_prompt,
stop_sequences=['</calc>'],
# The maximum length of the response
max_output_tokens=800,
)

try:
response, equation = completion.result.split('<calc>', maxsplit=1)
except Exception:
continue
``````
``````print(response)
``````
```Chain-of-thought:

There are three houses, and each house has three cats, so there are 3 houses * 3 cats / house = 9 cats. Each cat has 4 mittens, so the cats need 9 cats * 4 mittens / cat = 36 mittens. Each mitten takes 7m of yarn, so 36 mittens * 7m / mitten = 252m of yarn. Each cat has a hat, and each hat takes 4m of yarn, so 9 cats * 4m / cat = 36m of yarn. So, in total, 36m + 252m = 288m of yarn were needed.

```
``````print(equation)
``````
```9 cats * 4 mittens / cat
```

From there you can calculate the result, and assemble a new prompt for the model to continue from. For a complete working implementation see the Text calculator example.

### Candidates

Typically, there's some degree of randomness in the text produced by LLMs. (Read more about why in the LLM primer). That means that when you call the API more than once with the same input, you might get different responses. You can use this feature to your advantage to get alternate model responses.

The `temperature` argument controls the variance of the responses. The `palm.Model` object gives the default value for `temperature` and other parameters.

``````models
``````
```Model(name='models/text-bison-001', base_model_id='', version='001', display_name='Text Bison', description='Model targeted for text generation.', input_token_limit=8196, output_token_limit=1024, supported_generation_methods=['generateText'], temperature=0.7, top_p=0.95, top_k=40)
```

The `candidate_count` argument controls the number of responses returned:

``````completion = palm.generate_text(
model=model,
prompt=prompt,
# The number of candidates to return
candidate_count=8,
# Set the temperature to 1.0 for more variety of responses.
temperature=1.0,
max_output_tokens=800,
)

print(completion.result)
``````
```In each house there are 3 cats * 4 mittens / cat = 12 mittens. In total there are 3 houses * 12 mittens / house = 36 mittens. In total there are 36 mittens * 7m / mitten = 252m of yarn for the mittens. In total there are 3 houses * 3 cats / house * 1 hat / cat = 9 hats. In total there are 9 hats * 4m / hat = 36m of yarn for the hats. In total there are 36m yarn for the hats + 252m yarn for the mittens = 288m of yarn.
```

When you request multiple candidates the `Completion.result` attribute still just contains the first one. The `Completion.candidates` attribute contains all of them:

``````import pprint
pprint.pprint(completion.candidates)
``````
```[{'output': 'In each house there are 3 cats * 4 mittens / cat = 12 mittens. In '
'total there are 3 houses * 12 mittens / house = 36 mittens. In '
'total there are 36 mittens * 7m / mitten = 252m of yarn for the '
'mittens. In total there are 3 houses * 3 cats / house * 1 hat / '
'cat = 9 hats. In total there are 9 hats * 4m / hat = 36m of yarn '
'for the hats. In total there are 36m yarn for the hats + 252m '
'yarn for the mittens = 288m of yarn.\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]},
{'output': 'Each house has 3 cats, so each house needs 3 * 4 = 12 mittens. '
"With three houses, that's 3 * 12 = 36 mittens. And each house "
'needs 3 * 1 = 3 hats. So in total, we need 3 hats + 36 mittens = '
'39 items. Each mitten needs 7 meters of yarn, so 39 mittens need '
'39 * 7 = 273 meters of yarn. Each hat needs 4 meters of yarn, and '
"we need 3 hats, so that's 4 * 3 = 12 meters of yarn. So in total, "
'we needed 12 + 273 = 285 meters of yarn.\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]},
{'output': 'There are 3 houses * 3 cats / house = 9 cats. There are 9 cats * '
'4 mittens / cat = 36 mittens. There are 9 cats * 1 hat / cat = 9 '
'hats. The total amount of yarn for the mittens is 36 mittens * 7m '
'/ mitten = 252m. The total amount of yarn for the hats is 9 hats '
'* 4m / hat = 36m. The total amount of yarn is 252m + 36m = 288m.\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]},
{'output': 'There are 3 houses * 3 cats / house = 9 cats. Each cat has 4 '
'mittens + 1 hat = 5 items. So the total number of items is 9 cats '
'* 5 items / cat = 45 items. Thus, 45 items * 7m / item = 315m of '
'yarn was needed.\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]},
{'output': 'Chain-of-thought:\n'
'There are 3 houses * 3 cats / house = 9 cats.\n'
'The cats need 9 cats * 4 mittens / cat = 36 mittens.\n'
'The cats need 9 cats * 1 hat / cat = 9 hats.\n'
'The mittens need 36 mittens * 7m / mitten = 252m of yarn.\n'
'The hats need 9 hats * 4m / hat = 36m of yarn.\n'
'Therefore, the total amount of yarn needed is 252m + 36m = 288m.\n'
'\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]},
{'output': 'First find the total number of cats: 3 houses * 3 cats / house = '
'9 cats. Then multiply that number by the number of mittens per '
'cat to find the total number of mittens: 9 cats * 4 mittens / cat '
'= 36 mittens. Then multiply that number by the number of meters '
'of yarn per mitten to find the total amount of yarn used for '
'mittens: 36 mittens * 7 meters / mitten = 252 meters. Then do the '
'same thing for hats: 9 cats * 1 hat / cat = 9 hats. Then multiply '
'that number by the number of meters of yarn per hat to find the '
'total amount of yarn used for hats: 9 hats * 4 meters / hat = 36 '
'meters. Then add the amount of yarn used for mittens and hats to '
'find the total amount of yarn used: 36 meters + 252 meters = 288 '
'meters.\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]},
{'output': 'The total number of cats is 3 houses * 3 cats / house = 9 cats. '
'So, the total number of mittens is 9 cats * 4 mittens / cat = 36 '
'mittens. The total number of hats is 9 cats * 1 hat / cat = 9 '
'hats. The total length of yarn needed to make the mittens is 36 '
'mittens * 7 m / mitten = 252 m. The total length of yarn needed '
'to make the hats is 9 hats * 4 m / hat = 36 m. So, the total '
'length of yarn needed is 252 m + 36 m = 288 m.\n'
'\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]},
{'output': 'There are 3 houses with 3 cats each, so 3 * 3 = 9 cats. Each cat '
'has 4 mittens and a hat, so 9 cats * 4 mittens / cat + 9 cats * 1 '
'hat / cat = 36 mittens and 9 hats. Each mitten takes 7m of yarn '
'and each hat takes 4m of yarn, so the total yarn needed is 36 '
'mittens * 7m / mitten + 9 hats * 4m / hat = 252m + 36m = 288m.\n'
'safety_ratings': [{'category': <HarmCategory.HARM_CATEGORY_DEROGATORY: 1>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_TOXICITY: 2>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_VIOLENCE: 3>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_SEXUAL: 4>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_MEDICAL: 5>,
'probability': <HarmProbability.NEGLIGIBLE: 1>},
{'category': <HarmCategory.HARM_CATEGORY_DANGEROUS: 6>,
'probability': <HarmProbability.NEGLIGIBLE: 1>}]}]
```

So, since you know the answer to this problem, it's easy to check the solve rate:

``````import numpy as np
np.mean(['288' in c['output'] for c in completion.candidates])
``````
```0.75
```
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]