Docstring (#110)

* Update docstring

* update docstrings

* 0.3.1

docs/build_docs.py

@@ -26,7 +26,7 @@
 import textwrap
 import typing
 
-# For showing the conditional imports and types in `content_types.py` 
+# For showing the conditional imports and types in `content_types.py`
 typing.TYPE_CHECKING = True
 
 from absl import app

google/generativeai/__init__.py

@@ -12,60 +12,31 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""A high level client library for generative AI.
+"""Google AI Python SDK
 
 ## Setup
 
 ```posix-terminal
 pip install google-generativeai
 ```
 
-```
-import google.generativeai as palm
-import os
-
-palm.configure(api_key=os.environ['API_KEY'])
-```
-
-## Text
-
-Use the `palm.generate_text` function to have the model complete some initial
-text.
-
-```
-response = palm.generate_text(prompt="The opposite of hot is")
-print(response.result) #  'cold.'
-```
+## GenerativeModel
 
-## Chat
+Use `genai.GenerativeModel` to access the API:
 
-Use the `palm.chat` function to have a discussion with a model:
-
-```
-chat = palm.chat(messages=["Hello."])
-print(chat.last) #  'Hello! What can I help you with?'
-chat = chat.reply("Can you tell me a joke?")
-print(chat.last) #  'Why did the chicken cross the road?'
 ```
+import google.generativeai as genai
+import os
 
-## Models
-
-Use the model service discover models and find out more about them:
-
-Use `palm.get_model` to get details if you know a model's name:
-
-```
-model = palm.get_model('models/chat-bison-001') # 🦬
-```
+genai.configure(api_key=os.environ['API_KEY'])
 
-Use `palm.list_models` to discover models:
+model = genai.Model(name='gemini-pro')
+response = model.generate_content('Please summarise this document: ...')
 
-```
-import pprint
-for model in palm.list_models():
-    pprint.pprint(model) # 🦎🦦🦬🦄
+print(response.text)
 ```
 
+See the [python quickstart](https://ai.google.dev/tutorials/python_quickstart) for more details.
 """
 from __future__ import annotations
 

google/generativeai/types/generation_types.py

@@ -54,6 +54,64 @@ class GenerationConfigDict(TypedDict):
 
 @dataclasses.dataclass
 class GenerationConfig:
+    """A simple dataclass used to configure the generation parameters of `GenerativeModel.generate_content`.
+
+    Attributes:
+        candidate_count:
+            Number of generated responses to return.
+        stop_sequences:
+            The set of character sequences (up
+            to 5) that will stop output generation. If
+            specified, the API will stop at the first
+            appearance of a stop sequence. The stop sequence
+            will not be included as part of the response.
+        max_output_tokens:
+            The maximum number of tokens to include in a
+            candidate.
+
+            If unset, this will default to output_token_limit specified
+            in the model's specification.
+        temperature:
+            Controls the randomness of the output. Note: The
+
+            default value varies by model, see the `Model.temperature`
+            attribute of the `Model` returned the `genai.get_model`
+            function.
+
+            Values can range from [0.0,1.0], inclusive. A value closer
+            to 1.0 will produce responses that are more varied and
+            creative, while a value closer to 0.0 will typically result
+            in more straightforward responses from the model.
+        top_p:
+            Optional. The maximum cumulative probability of tokens to
+            consider when sampling.
+
+            The model uses combined Top-k and nucleus sampling.
+
+            Tokens are sorted based on their assigned probabilities so
+            that only the most likely tokens are considered. Top-k
+            sampling directly limits the maximum number of tokens to
+            consider, while Nucleus sampling limits number of tokens
+            based on the cumulative probability.
+
+            Note: The default value varies by model, see the
+            `Model.top_p` attribute of the `Model` returned the
+            `genai.get_model` function.
+
+        top_k (int):
+            Optional. The maximum number of tokens to consider when
+            sampling.
+
+            The model uses combined Top-k and nucleus sampling.
+
+            Top-k sampling considers the set of `top_k` most probable
+            tokens. Defaults to 40.
+
+            Note: The default value varies by model, see the
+            `Model.top_k` attribute of the `Model` returned the
+            `genai.get_model` function.
+    """
+
     candidate_count: int | None = None
     stop_sequences: Iterable[str] | None = None
     max_output_tokens: int | None = None

google/generativeai/version.py

@@ -14,4 +14,4 @@
 # limitations under the License.
 from __future__ import annotations
 
-__version__ = "0.3.0"
+__version__ = "0.3.1"