From f6c9019d27bd0787420d7a8e5ab53c9749b23f23 Mon Sep 17 00:00:00 2001 From: Saifeddine ALOUI Date: Tue, 29 Oct 2024 17:16:19 +0100 Subject: [PATCH] added new options --- lollms/personality.py | 209 +++++++++++++++++++++++++++++++++++++++++- 1 file changed, 205 insertions(+), 4 deletions(-) diff --git a/lollms/personality.py b/lollms/personality.py index ff6d71b..511feec 100644 --- a/lollms/personality.py +++ b/lollms/personality.py @@ -2259,6 +2259,83 @@ class APScript(StateMachine): """ pass + def generate_html_from_dict(self, data): + css_style = """ + + """ + + def format_value(value): + if isinstance(value, list): + if not value: + return "Empty list" + items = [f"
  • {item}
    • " for item in value] + return f"" + elif isinstance(value, (str, int, float)): + # Replace pipe character and preserve formatting for multiline strings + if isinstance(value, str) and '|' in value: + value = value.replace('|', '').strip() + return f"
    {value}
    " + else: + return f"
    {str(value)}
    " + + html = css_style + html += "
    " + + # Add header with name if it exists + if "name" in data: + html += f"

    {data['name']}

    " + + # Process all key-value pairs + for key, value in data.items(): + if key != "name": # Skip name as it's already in header + html += "
    " + html += f"
    {key.replace('_', ' ').title()}:
    " + html += format_value(value) + html += "
    " + + html += "
    " + return html + + + def execute_command(self, command: str, parameters:list=[], client:Client=None): """ Recovers user commands and executes them. Each personality can define a set of commands that they can receive and execute @@ -2408,16 +2485,22 @@ class APScript(StateMachine): codes = self.extract_code_blocks(response) return codes - def generate_code(self, prompt, images=[], max_size = None, temperature = None, top_k = None, top_p=None, repeat_penalty=None, repeat_last_n=None, callback=None, debug=False, return_full_generated_code=False ): + def generate_code(self, prompt, images=[], max_size = None, temperature = None, top_k = None, top_p=None, repeat_penalty=None, repeat_last_n=None, callback=None, debug=False, return_full_generated_code=False, accept_all_if_no_code_tags_is_present=False): response_full = "" + full_prompt = self.system_custom_header("Generation infos")+ "Generated code must be put inside the adequate markdown code tag. Use this template:\n```language name\nCode\n```\nMake sure only a single code tag is generated at each dialogue turn." + self.separator_template + self.system_custom_header("User prompt")+ prompt + self.separator_template + self.ai_custom_header("generated code") if len(self.personality.image_files)>0: - response = self.personality.generate_with_images(self.system_custom_header("Generation infos")+ "Generated code must be put inside the adequate markdown code tag. Use this template:\n```language name\nCode\n```\nMake sure only a single code tag is generated at each dialogue turn." + self.separator_template + prompt, self.personality.image_files, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) + response = self.personality.generate_with_images(full_prompt, self.personality.image_files, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) elif len(images)>0: - response = self.personality.generate_with_images(self.system_custom_header("Generation infos")+ "Generated code must be put inside the adequate markdown code tag. Use this template:\n```language name\nCode\n```\nMake sure only a single code tag is generated at each dialogue turn." + self.separator_template + prompt, images, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) + response = self.personality.generate_with_images(full_prompt, images, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) else: - response = self.personality.generate(self.system_custom_header("Generation infos")+ "Generated code must be put inside the adequate markdown code tag. Use this template:\n```language name\nCode\n```\nMake sure only a single code tag is generated at each dialogue turn." + self.separator_template + prompt, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) + response = self.personality.generate(full_prompt, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) response_full += response codes = self.extract_code_blocks(response) + if len(codes)==0 and accept_all_if_no_code_tags_is_present: + if return_full_generated_code: + return response, response_full + else: + return response if len(codes)>0: if not codes[-1]["is_complete"]: code = "\n".join(codes[-1]["content"].split("\n")[:-1]) @@ -2441,6 +2524,124 @@ class APScript(StateMachine): return code else: return None + + def generate_text(self, prompt, images=[], max_size = None, temperature = None, top_k = None, top_p=None, repeat_penalty=None, repeat_last_n=None, callback=None, debug=False, return_full_generated_code=False, accept_all_if_no_code_tags_is_present=False): + response_full = "" + full_prompt = self.system_custom_header("Generation infos")+ "Generated text content must be put inside a markdown code tag. Use this template:\n```\nText\n```\nMake sure only a single text tag is generated at each dialogue turn." + self.separator_template + self.system_custom_header("User prompt")+ prompt + self.separator_template + self.ai_custom_header("generated answer") + if len(self.personality.image_files)>0: + response = self.personality.generate_with_images(full_prompt, self.personality.image_files, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) + elif len(images)>0: + response = self.personality.generate_with_images(full_prompt, images, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) + else: + response = self.personality.generate(full_prompt, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) + response_full += response + codes = self.extract_code_blocks(response) + if len(codes)==0 and accept_all_if_no_code_tags_is_present: + if return_full_generated_code: + return response, response_full + else: + return response + if len(codes)>0: + if not codes[-1]["is_complete"]: + code = "\n".join(codes[-1]["content"].split("\n")[:-1]) + while not codes[-1]["is_complete"]: + response = self.personality.generate(prompt+code+self.user_full_header+"continue the text. Start from last line and continue the text. Put the text inside a markdown code tag."+self.separator_template+self.ai_full_header, max_size, temperature, top_k, top_p, repeat_penalty, repeat_last_n, callback, debug=debug) + response_full += response + codes = self.extract_code_blocks(response) + if len(codes)==0: + break + else: + if not codes[-1]["is_complete"]: + code +="\n"+ "\n".join(codes[-1]["content"].split("\n")[:-1]) + else: + code +="\n"+ "\n".join(codes[-1]["content"].split("\n")) + else: + code = codes[-1]["content"] + + if return_full_generated_code: + return code, response_full + else: + return code + else: + return None + + def generate_structured_content(self, + prompt, + template, + single_shot=False, + output_format="yaml"): + """ + Generate structured content (YAML/JSON) either in single-shot or step-by-step mode. + + Args: + prompt (str): The main prompt describing what to generate + template (dict): Dictionary containing the structure and field-specific prompts + single_shot (bool): If True, generates all content at once. If False, generates field by field + output_format (str): "yaml" or "json" + + Returns: + dict: Contains both the structured data and formatted string + """ + + # Initialize the output dictionary with default values + output_data = {} + for field, field_info in template.items(): + output_data[field] = field_info.get("default", "") + + if single_shot: + # Generate all content at once for powerful LLMs + full_prompt = f"""Generate {output_format.upper()} content for: {prompt} +Use this structure: +{output_data} +""" + response = self.generate_code(full_prompt, callback=self.sink, accept_all_if_no_code_tags_is_present=True) + # Parse the response based on format + if output_format == "yaml": + import yaml + try: + cleaned_response = response.replace("```yaml", "").replace("```", "").strip() + output_data = yaml.safe_load(cleaned_response) + except yaml.YAMLError: + # If parsing fails, fall back to step-by-step + single_shot = False + elif output_format == "json": + import json + try: + cleaned_response = response.replace("```json", "").replace("```", "").strip() + output_data = json.loads(cleaned_response) + except json.JSONDecodeError: + # If parsing fails, fall back to step-by-step + single_shot = False + + if not single_shot: + # Generate each field individually + for field, field_info in template.items(): + if "prompt" in field_info: + field_prompt = field_info["prompt"].format(main_prompt=prompt) + response = self.generate_code(field_prompt, callback=self.sink, accept_all_if_no_code_tags_is_present=True ) + # Clean up the response + cleaned_response = response.strip() + # Apply any field-specific processing + if "processor" in field_info: + cleaned_response = field_info["processor"](cleaned_response) + output_data[field] = cleaned_response + + # Format the output string + if output_format == "yaml": + formatted_string = "" + for key, value in output_data.items(): + if isinstance(value, str) and ("\n" in value or len(value) > 40): + v = value.replace('\n', '\n ') + formatted_string += f"{key}: |\n {v}\n" + else: + formatted_string += f"{key}: {value}\n" + else: # json + formatted_string = json.dumps(output_data, indent=2) + + return { + "data": output_data, + "formatted_string": formatted_string + } def run_workflow(self, prompt:str, previous_discussion_text:str="", callback: Callable[[str | list | None, MSG_OPERATION_TYPE, str, AIPersonality| None], bool]=None, context_details:dict=None, client:Client=None): """