documentation and cleanup

gpt4all-bindings/python/README.md

@@ -1,11 +1,9 @@
 # Python GPT4All
 
-This package contains a set of Python bindings that runs the `llmodel` C-API.
+This package contains a set of Python bindings around the `llmodel` C-API.
 
 
-# Local Installation Instructions
-
-TODO: Right now instructions in main README still depend on Qt6 setup. To setup Python bindings, we just need `llmodel` to be built which is much simpler. However, in the future, the below installation instructions should be sequentially organized such that we expect the main README's instructions were followed first.
+## Local Build Instructions
 
 1. Setup `llmodel`
 
@@ -23,7 +21,6 @@ Confirm that `libllmodel.*` exists in `gpt4all-backend/llmodel/build`.
 
 ```
 cd ../../gpt4all-bindings/python
-pip3 install -r requirements.txt
 pip3 install -e .
 ```
 

gpt4all-bindings/python/docs/index.md

@@ -1,6 +1,6 @@
 # GPT4All
 
-In this package, we introduce Python bindings built around GPT4All's C/C++ ecosystem.
+In this package, we introduce Python bindings built around GPT4All's C/C++ model backends.
 
 ## Quickstart
 
@@ -11,7 +11,7 @@ pip install gpt4all
 In Python, run the following commands to retrieve a GPT4All model and generate a response
 to a prompt.
 
-**Download Note*:*
+**Download Note*:**
 By default, models are stored in `~/.cache/gpt4all/` (you can change this with `model_path`). If the file already exists, model download will be skipped.
 
 ```python
@@ -19,4 +19,14 @@ import gpt4all
 gptj = gpt4all.GPT4All("ggml-gpt4all-j-v1.3-groovy")
 messages = [{"role": "user", "content": "Name 3 colors"}]
 gptj.chat_completion(messages)
-```
+```
+
+## Give it a try!
+[Google Colab Tutorial](https://colab.research.google.com/drive/1QRFHV5lj1Kb7_tGZZGZ-E6BfX6izpeMI?usp=sharing)
+
+
+## Best Practices
+GPT4All models are designed to run locally on your own CPU. Large prompts may require longer computation time and
+result in worse performance. Giving an instruction to the model will typically produce the best results.
+
+There are two methods to interface with the underlying language model, `chat_completion()` and `generate()`. Chat completion formats a user-provided message dictionary into a prompt template (see API documentation for more details and options). This will usually produce much better results and is the approach we recommend. You may also prompt the model with `generate()` which will just pass the raw input string to the model. 

gpt4all-bindings/python/gpt4all/gpt4all.py

@@ -15,7 +15,7 @@ from . import pyllmodel
 DEFAULT_MODEL_DIRECTORY = os.path.join(str(Path.home()), ".cache", "gpt4all").replace("\\", "\\\\")
 
 class GPT4All():
-    """Python API for retrieving and interacting with GPT4All models
+    """Python API for retrieving and interacting with GPT4All models.
     
     Attribuies:
         model: Pointer to underlying C model.
@@ -50,7 +50,7 @@ class GPT4All():
     @staticmethod
     def list_models():
         """
-        Fetch model list from https://gpt4all.io/models/models.json
+        Fetch model list from https://gpt4all.io/models/models.json.
 
         Returns:
             Model list in JSON format.
@@ -60,7 +60,7 @@ class GPT4All():
         return model_json
 
     @staticmethod
-    def retrieve_model(model_name: str, model_path: str = None, allow_download = True):
+    def retrieve_model(model_name: str, model_path: str = None, allow_download: bool = True) -> str:
         """
         Find model file, and if it doesn't exist, download the model.
 
@@ -113,8 +113,18 @@ class GPT4All():
             raise ValueError("Invalid model directory")
         
     @staticmethod
-    def download_model(model_filename, model_path):
-        # TODO: Find good way of safely removing file that got interrupted.
+    def download_model(model_filename: str, model_path: str) -> str:
+        """
+        Download model from https://gpt4all.io.
+
+        Args:
+            model_filename: Filename of model (with .bin extension).
+            model_path: Path to download model to.
+
+        Returns:
+            Model file destination.
+        """
+
         def get_download_url(model_filename):
             return f"https://gpt4all.io/models/{model_filename}"
     
@@ -122,6 +132,7 @@ class GPT4All():
         download_path = os.path.join(model_path, model_filename).replace("\\", "\\\\")
         download_url = get_download_url(model_filename)
 
+        # TODO: Find good way of safely removing file that got interrupted.
         response = requests.get(download_url, stream=True)
         total_size_in_bytes = int(response.headers.get("content-length", 0))
         block_size = 1048576  # 1 MB
@@ -141,9 +152,16 @@ class GPT4All():
         print("Model downloaded at: " + download_path)
         return download_path
 
-    def generate(self, prompt: str, **generate_kwargs):
+    def generate(self, prompt: str, **generate_kwargs) -> str:
         """
         Surfaced method of running generate without accessing model object.
+
+        Args:
+            prompt: Raw string to be passed to model.
+            **generate_kwargs: Optional kwargs to pass to prompt context.
+        
+        Returns:
+            Raw string of generated model response.
         """
         return self.model.generate(prompt, **generate_kwargs)
     
@@ -158,13 +176,13 @@ class GPT4All():
         generated content.
 
         Args:
-            messages: Each dictionary should have a "role" key
+            messages: List of dictionaries. Each dictionary should have a "role" key
                 with value of "system", "assistant", or "user" and a "content" key with a
                 string value. Messages are organized such that "system" messages are at top of prompt,
                 and "user" and "assistant" messages are displayed in order. Assistant messages get formatted as
                 "Reponse: {content}". 
-            default_prompt_header: If True (default), add default prompt header after any user specified system messages and
-                before user/assistant messages.
+            default_prompt_header: If True (default), add default prompt header after any system role messages and
+                before user/assistant role messages.
             default_prompt_footer: If True (default), add default footer at end of prompt.
             verbose: If True (default), print full prompt and generated response.
 
@@ -175,7 +193,6 @@ class GPT4All():
                     generated tokens in response, and total tokens.  
                 "choices": List of message dictionary where "content" is generated response and "role" is set
                 as "assistant". Right now, only one choice is returned by model.
-            
         """
        
         full_prompt = self._build_prompt(messages, 
@@ -210,6 +227,7 @@ class GPT4All():
     def _build_prompt(messages: List[Dict], 
                       default_prompt_header=True, 
                       default_prompt_footer=False) -> str:
+        # Helper method to format messages into prompt.
         full_prompt = ""
 
         for message in messages:
@@ -238,7 +256,7 @@ class GPT4All():
 
     @staticmethod
     def get_model_from_type(model_type: str) -> pyllmodel.LLModel:
-        # This needs to be updated for each new model
+        # This needs to be updated for each new model type
         # TODO: Might be worth converting model_type to enum
 
         if model_type == "gptj":

gpt4all-bindings/python/mkdocs.yml

@@ -68,9 +68,4 @@ extra:
   generator: false
   analytics:
     provider: google
-    property: G-NPXC8BYHJV
-  #social:
-  #  - icon: fontawesome/brands/twitter
-  #    link: https://twitter.com/nomic_ai
-  #  - icon: material/fruit-pineapple
-  #    link: https://www.youtube.com/watch?v=628eVJgHD6I
+    property: G-NPXC8BYHJV

gpt4all-bindings/python/setup.py

@@ -61,7 +61,7 @@ copy_prebuilt_C_lib(SRC_CLIB_DIRECtORY,
 
 setup(
     name=package_name,
-    version="0.1.9",
+    version="0.2.0",
     description="Python bindings for GPT4All",
     author="Richard Guo",
     author_email="richard@nomic.ai",