Modiifed: documentation

docs/gptty/index.md

@@ -14,142 +14,142 @@ Classes
 `UniversalCompletion(api_key: str = '', org_id: str = '', output_file: str = 'output.txt', your_name: str = 'question', gpt_name: str = 'response', model: str = 'text-davinci-003', temperature: float = 0.0, max_tokens: int = 250, max_context_length: int = 150, context_keywords_only: bool = True, preserve_new_lines: bool = False)`
 :   Initializes a new instance of the UniversalCompletion class.
 
+Parameters:
+    api_key (str): The OpenAI API key.
+    org_id (str): The OpenAI organization ID.
+    output_file (str): The name of the file where the output should be stored.
+    your_name (str): The name that will be used to identify user inputs in the chat history.
+    gpt_name (str): The name that will be used to identify GPT outputs in the chat history.
+    model (str): The name of the model to use for generating text.
+    temperature (float): The temperature to use for the text generation process. Higher values make output more random.
+    max_tokens (int): The maximum number of tokens in the output text.
+    max_context_length (int): The maximum number of tokens in the input text.
+    context_keywords_only (bool): If True, only keywords from the input text are taken into account in the generation process.
+    preserve_new_lines (bool): If True, new lines in the output text are preserved.
+
+Returns:
+    None
+
+### Methods
+
+`a_fetch_response(self, prompt: Union[str, List[Dict[str, str]]], max_tokens: Optional[int] = None, temperature: Optional[float] = None, model_type: Optional[str] = None) ‑> Union[openai.api_resources.completion.Completion, openai.api_resources.chat_completion.ChatCompletion, None]`
+:   Asynchronously fetches a response from the model based on the provided prompt.
+
+    Parameters:
+        prompt (Union[str, List[Dict[str, str]]]): The input prompt for the model. This can either be a string or a list of message dictionaries for chat models.
+        max_tokens (Optional[int]): The maximum number of tokens for the model to generate. Defaults to None, in which case it uses the instance's default.
+        temperature (Optional[float]): The randomness factor for the model's output. Defaults to None, in which case it uses the instance's default.
+        model_type (Optional[str]): The type of the model. Defaults to None, in which case it uses the instance's default.
+
+    Returns:
+        Optional[Union[openai.Completion, openai.ChatCompletion]]: The model's response as a Completion or ChatCompletion object, or None if the model type is not recognized.
+
+    Example usage:
+        >>> g = UniversalCompletion(api_key="your-api-key", org_id="your-org-id")
+        >>> g.connect()
+        >>> g.set_model('gpt-3.5-turbo')
+        >>> prompt = [{"role": "user", "content": "What is an abstraction?"}]
+        >>> response = asyncio.run(g.a_fetch_response(prompt=prompt))
+        >>> print(response.choices[0].message['content'])
+
+`build_context(self, prompt: str, context: List[Dict[str, str]], max_context_length: int, model_type: Optional[str] = None, context_keywords_only: bool = True, additional_context: str = '') ‑> Union[str, List[Dict[str, str]]]`
+:   Builds a full query context for a given prompt and context.
+
+    Parameters:
+        prompt (str): The main prompt to build the context around.
+        context (List[Dict[str, str]]): List of past prompts and responses.
+        max_context_length (int): Maximum length of the context to return.
+        model_type (Optional[str]): Type of the language model. If 'v1/chat/completions', return a list of dicts 
+                                    with 'role' and 'content' keys. If not, return a string. Default is None.
+        context_keywords_only (bool, optional): If True, use only the most common phrases and words from the context 
+                                                and additional context. Default is True.
+        additional_context (str, optional): Additional context to add to the context. Default is an empty string.
+
+    Returns:
+        Union[str, List[Dict[str, str]]]: If `model_type` is 'v1/chat/completions', returns a list of dicts with 
+                                          'role' and 'content' keys. If not, returns a string.
+
+`connect(self, api_key=None, org_id=None) ‑> None`
+:   Connects to the OpenAI API using the provided organization ID and API key.
+
+    Parameters:
+        api_key (str): The OpenAI API key, defaults to the corresponding class element.
+        org_id (str): The OpenAI organization ID, defaults to the corresponding class element.
+
+    Returns:
+        None
+
+`fetch_response(self, prompt: Union[str, List[Dict[str, str]]], max_tokens: Optional[int] = None, temperature: Optional[float] = None, model_type: Optional[str] = None) ‑> Union[openai.api_resources.completion.Completion, openai.api_resources.chat_completion.ChatCompletion, None]`
+:   Fetches a response from the model based on the provided prompt.
+
+    Parameters:
+        prompt (Union[str, List[Dict[str, str]]]): The input prompt for the model. This can either be a string or a list of message dictionaries for chat models.
+        max_tokens (Optional[int]): The maximum number of tokens for the model to generate. Defaults to None, in which case it uses the instance's default.
+        temperature (Optional[float]): The randomness factor for the model's output. Defaults to None, in which case it uses the instance's default.
+        model_type (Optional[str]): The type of the model. Defaults to None, in which case it uses the instance's default.
+
+    Returns:
+        Optional[Union[openai.Completion, openai.ChatCompletion]]: The model's response as a Completion or ChatCompletion object, or None if the model type is not recognized.
+
+    Example usage:
+        >>> g = UniversalCompletion(api_key="your-api-key", org_id="your-org-id")
+        >>> g.connect()
+        >>> g.set_model('gpt-3.5-turbo')
+        >>> prompt = [{"role": "user", "content": "What is an abstraction?"}]
+        >>> response = g.fetch_response(prompt=prompt)
+        >>> print(response.choices[0].message['content'])
+
+`get_available_models(self) ‑> List[str]`
+:   Retrieves a list of available models from the OpenAI API.
+
+    Parameters:
+        None
+
+    Returns:
+        List[str]: A list of model IDs available for use.
+
+`is_valid_model(self, model_name: str) ‑> bool`
+:   Checks whether the given model name is valid and available.
+
     Parameters:
-        api_key (str): The OpenAI API key.
-        org_id (str): The OpenAI organization ID.
-        output_file (str): The name of the file where the output should be stored.
-        your_name (str): The name that will be used to identify user inputs in the chat history.
-        gpt_name (str): The name that will be used to identify GPT outputs in the chat history.
-        model (str): The name of the model to use for generating text.
-        temperature (float): The temperature to use for the text generation process. Higher values make output more random.
-        max_tokens (int): The maximum number of tokens in the output text.
-        max_context_length (int): The maximum number of tokens in the input text.
-        context_keywords_only (bool): If True, only keywords from the input text are taken into account in the generation process.
-        preserve_new_lines (bool): If True, new lines in the output text are preserved.
-
+        model_name (str): The name of the model to validate.
+
+    Returns:
+        bool: True if the model name is valid and available, False otherwise.
+
+`set_model(self, model_name: str) ‑> None`
+:   Sets the model to be used for the class instance. The model name provided must be a valid and available model.
+
+    Parameters:
+        model_name (str): The name of the model to set.
+
     Returns:
         None
 
-    ### Methods
-
-    `a_fetch_response(self, prompt: Union[str, List[Dict[str, str]]], max_tokens: Optional[int] = None, temperature: Optional[float] = None, model_type: Optional[str] = None) ‑> Union[openai.api_resources.completion.Completion, openai.api_resources.chat_completion.ChatCompletion, None]`
-    :   Asynchronously fetches a response from the model based on the provided prompt.
-        
-        Parameters:
-            prompt (Union[str, List[Dict[str, str]]]): The input prompt for the model. This can either be a string or a list of message dictionaries for chat models.
-            max_tokens (Optional[int]): The maximum number of tokens for the model to generate. Defaults to None, in which case it uses the instance's default.
-            temperature (Optional[float]): The randomness factor for the model's output. Defaults to None, in which case it uses the instance's default.
-            model_type (Optional[str]): The type of the model. Defaults to None, in which case it uses the instance's default.
-        
-        Returns:
-            Optional[Union[openai.Completion, openai.ChatCompletion]]: The model's response as a Completion or ChatCompletion object, or None if the model type is not recognized.
-        
-        Example usage:
-            >>> g = UniversalCompletion(api_key="your-api-key", org_id="your-org-id")
-            >>> g.connect()
-            >>> g.set_model('gpt-3.5-turbo')
-            >>> prompt = [{"role": "user", "content": "What is an abstraction?"}]
-            >>> response = asyncio.run(g.a_fetch_response(prompt=prompt))
-            >>> print(response.choices[0].message['content'])
-
-    `build_context(self, prompt: str, context: List[Dict[str, str]], max_context_length: int, model_type: Optional[str] = None, context_keywords_only: bool = True, additional_context: str = '') ‑> Union[str, List[Dict[str, str]]]`
-    :   Builds a full query context for a given prompt and context.
-        
-        Parameters:
-            prompt (str): The main prompt to build the context around.
-            context (List[Dict[str, str]]): List of past prompts and responses.
-            max_context_length (int): Maximum length of the context to return.
-            model_type (Optional[str]): Type of the language model. If 'v1/chat/completions', return a list of dicts 
-                                        with 'role' and 'content' keys. If not, return a string. Default is None.
-            context_keywords_only (bool, optional): If True, use only the most common phrases and words from the context 
-                                                    and additional context. Default is True.
-            additional_context (str, optional): Additional context to add to the context. Default is an empty string.
-        
-        Returns:
-            Union[str, List[Dict[str, str]]]: If `model_type` is 'v1/chat/completions', returns a list of dicts with 
-                                              'role' and 'content' keys. If not, returns a string.
-
-    `connect(self, api_key=None, org_id=None) ‑> None`
-    :   Connects to the OpenAI API using the provided organization ID and API key.
-        
-        Parameters:
-            api_key (str): The OpenAI API key, defaults to the corresponding class element.
-            org_id (str): The OpenAI organization ID, defaults to the corresponding class element.
-        
-        Returns:
-            None
-
-    `fetch_response(self, prompt: Union[str, List[Dict[str, str]]], max_tokens: Optional[int] = None, temperature: Optional[float] = None, model_type: Optional[str] = None) ‑> Union[openai.api_resources.completion.Completion, openai.api_resources.chat_completion.ChatCompletion, None]`
-    :   Fetches a response from the model based on the provided prompt.
-        
-        Parameters:
-            prompt (Union[str, List[Dict[str, str]]]): The input prompt for the model. This can either be a string or a list of message dictionaries for chat models.
-            max_tokens (Optional[int]): The maximum number of tokens for the model to generate. Defaults to None, in which case it uses the instance's default.
-            temperature (Optional[float]): The randomness factor for the model's output. Defaults to None, in which case it uses the instance's default.
-            model_type (Optional[str]): The type of the model. Defaults to None, in which case it uses the instance's default.
-        
-        Returns:
-            Optional[Union[openai.Completion, openai.ChatCompletion]]: The model's response as a Completion or ChatCompletion object, or None if the model type is not recognized.
-        
-        Example usage:
-            >>> g = UniversalCompletion(api_key="your-api-key", org_id="your-org-id")
-            >>> g.connect()
-            >>> g.set_model('gpt-3.5-turbo')
-            >>> prompt = [{"role": "user", "content": "What is an abstraction?"}]
-            >>> response = g.fetch_response(prompt=prompt)
-            >>> print(response.choices[0].message['content'])
-
-    `get_available_models(self) ‑> List[str]`
-    :   Retrieves a list of available models from the OpenAI API.
-        
-        Parameters:
-            None
-        
-        Returns:
-            List[str]: A list of model IDs available for use.
-
-    `is_valid_model(self, model_name: str) ‑> bool`
-    :   Checks whether the given model name is valid and available.
-        
-        Parameters:
-            model_name (str): The name of the model to validate.
-        
-        Returns:
-            bool: True if the model name is valid and available, False otherwise.
-
-    `set_model(self, model_name: str) ‑> None`
-    :   Sets the model to be used for the class instance. The model name provided must be a valid and available model.
-        
-        Parameters:
-            model_name (str): The name of the model to set.
-        
-        Returns:
-            None
-        
-        Raises:
-            AssertionError: If the model name is not valid or available.
-
-    `usage_stats_today(self) ‑> Optional[Tuple[int, int, int]]`
-    :   Retrieves usage statistics for the current day from the OpenAI API.
-        
-        Parameters:
-            None
-        
-        Returns:
-            requests_today (int): The total number of requests made today.
-            query_tokens_today (int): The total number of context tokens used in queries today.
-            response_tokens_today (int): The total number of generated tokens in responses today.
-            
-        If any error occurs during the process, this method will return None.
-
-    `validate_model_type(self, model_name: str) ‑> str`
-    :   Validates the model type based on the model name provided.
-        
-        Parameters:
-            model_name (str): The name of the model to validate.
-        
-        Returns:
-            str: The corresponding API endpoint ('v1/completions' or 'v1/chat/completions') based on the model type.
-        
-        Raises:
-            Exception: If the model name does not match any of the known model types or is not a valid or available model.
+    Raises:
+        AssertionError: If the model name is not valid or available.
+
+`usage_stats_today(self) ‑> Optional[Tuple[int, int, int]]`
+:   Retrieves usage statistics for the current day from the OpenAI API.
+
+    Parameters:
+        None
+
+    Returns:
+        requests_today (int): The total number of requests made today.
+        query_tokens_today (int): The total number of context tokens used in queries today.
+        response_tokens_today (int): The total number of generated tokens in responses today.
+
+    If any error occurs during the process, this method will return None.
+
+`validate_model_type(self, model_name: str) ‑> str`
+:   Validates the model type based on the model name provided.
+
+    Parameters:
+        model_name (str): The name of the model to validate.
+
+    Returns:
+        str: The corresponding API endpoint ('v1/completions' or 'v1/chat/completions') based on the model type.
+
+    Raises:
+        Exception: If the model name does not match any of the known model types or is not a valid or available model.