{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"# Load configuration from YAML file\n",
"config = {\n",
" \"model_name\": \"llama3-70b-8192\",\n",
"}\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/yale/work/meta-prompt/.venv/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7861\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/yale/work/meta-prompt/.venv/lib/python3.10/site-packages/langchain_core/_api/deprecation.py:141: LangChainDeprecationWarning: The class `ChatOpenAI` was deprecated in LangChain 0.0.10 and will be removed in 0.3.0. An updated version of the class exists in the langchain-openai package and should be used instead. To use it run `pip install -U langchain-openai` and import as `from langchain_openai import ChatOpenAI`.\n",
" warn_deprecated(\n"
]
}
],
"source": [
"import json\n",
"import yaml\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.chat_models import ChatOpenAI\n",
"from langchain.schema.output_parser import StrOutputParser\n",
"\n",
"class TaskDescriptionGenerator:\n",
" def __init__(self, model_temperature=0.7):\n",
" self.model = ChatOpenAI(model=config[\"model_name\"], temperature=model_temperature)\n",
" self.output_parser = StrOutputParser()\n",
" \n",
" self.description_prompt = ChatPromptTemplate.from_template(\n",
" \"\"\"Given the following JSON example for a task type:\n",
" {raw_example}\n",
"\n",
" Provide a concise description of the task type, including the format and style of the output.\n",
"\n",
" Format your response as follows:\n",
" Task Description: [Your description here]\n",
" \"\"\"\n",
" )\n",
"\n",
" self.briefs_prompt = ChatPromptTemplate.from_template(\n",
" \"\"\"Given the following task type description:\n",
" Task Description: {description}\n",
"\n",
" Generate descriptions for 3 new examples with detailed attributes\n",
" based on this task type.\n",
"\n",
" Format your response as a valid YAML object with a single key\n",
" 'brief_descriptions' containing a YAML array of 3 objects, each\n",
" with a 'description' field.\n",
" \"\"\"\n",
" )\n",
"\n",
" self.examples_from_briefs_prompt = ChatPromptTemplate.from_template(\n",
" \"\"\"Given the following task type description, brief description for new examples, \n",
" and JSON example:\n",
"\n",
" Task Description: {description}\n",
" Brief Description: {brief_description}\n",
"\n",
" Example:\n",
" {raw_example}\n",
"\n",
" Generate 3 more input/output examples for this task type, based on the brief\n",
" description, in the same JSON format.\n",
"\n",
" Format your response as a valid JSON object with a single key 'examples' \n",
" containing a JSON array of 3 objects, each with 'input' and 'output' fields.\n",
" \"\"\"\n",
" )\n",
"\n",
" self.examples_prompt = ChatPromptTemplate.from_template(\n",
" \"\"\"Given the following task type description, and input/output example:\n",
" Task Description: {description}\n",
" Example: {example}\n",
"\n",
" Generate 3 new input/output examples for this task type.\n",
"\n",
" Format your response as a valid JSON object with a single key 'examples' \n",
" containing a JSON array of 3 objects, each with 'input' and 'output' fields.\n",
" \"\"\"\n",
" )\n",
"\n",
" self.description_chain = self.description_prompt | self.model | self.output_parser\n",
" self.briefs_chain = self.briefs_prompt | self.model | self.output_parser\n",
" # bind json_object to the model\n",
" json_model = self.model.bind(response_format={\"type\": \"json_object\"})\n",
" self.examples_from_briefs_chain = self.examples_from_briefs_prompt | json_model | self.output_parser\n",
" self.examples_chain = self.examples_prompt | json_model | self.output_parser\n",
"\n",
" def generate_description(self, raw_example_str):\n",
" result = self.description_chain.invoke({\n",
" \"raw_example\": raw_example_str\n",
" })\n",
" return result.split(\"Task Description: \")[1].strip()\n",
"\n",
" def generate_briefs(self, description):\n",
" result = self.briefs_chain.invoke({\n",
" \"description\": description\n",
" })\n",
" # return result.split(\"Brief Description: \")[1].strip()\n",
" return result\n",
"\n",
" def generate_examples_from_briefs(self, description, brief_description, raw_example_str):\n",
" result = self.examples_from_briefs_chain.invoke({\n",
" \"description\": description,\n",
" \"brief_description\": brief_description,\n",
" \"raw_example\": raw_example_str\n",
" })\n",
"\n",
" try:\n",
" result = result.strip()\n",
" if result.startswith('```') and result.endswith('```'):\n",
" result = result.strip('```').strip()\n",
" if result.startswith('json'):\n",
" result = result.strip('json').strip()\n",
" return json.loads(result)\n",
" except json.JSONDecodeError as e:\n",
" raise ValueError(f\"The generated examples are not in valid JSON format. Error: {str(e)} Result: {result}\")\n",
" \n",
" def generate_examples(self, description, example):\n",
" result = self.examples_chain.invoke({\n",
" \"description\": description,\n",
" \"example\": example\n",
" })\n",
" \n",
" try:\n",
" result = result.strip()\n",
" if result.startswith('```') and result.endswith('```'):\n",
" result = result.strip('```').strip()\n",
" if result.startswith('json'):\n",
" result = result.strip('json').strip()\n",
" return json.loads(result)\n",
" except json.JSONDecodeError as e:\n",
" raise ValueError(f\"The generated examples are not in valid JSON format. Error: {str(e)} Result: {result}\")\n",
"\n",
" def process(self, input_str):\n",
" try:\n",
" # Try to parse as JSON\n",
" try:\n",
" data = json.loads(input_str)\n",
" except json.JSONDecodeError:\n",
" # If JSON parsing fails, try to parse as YAML\n",
" try:\n",
" data = yaml.safe_load(input_str)\n",
" except yaml.YAMLError as e:\n",
" raise ValueError(\"Invalid input string. Error: {}\".format(str(e)))\n",
" \n",
" if not isinstance(data, dict) or 'input' not in data or 'output' not in data:\n",
" raise ValueError(\"Invalid input format. Expected an object with 'input' and 'output' fields.\")\n",
" \n",
" description = self.generate_description(json.dumps(data, ensure_ascii=False))\n",
" brief_description = self.generate_briefs(description)\n",
" new_examples_from_briefs = self.generate_examples_from_briefs(description, brief_description, json.dumps(data, ensure_ascii=False))\n",
" new_examples = self.generate_examples(description, json.dumps(data, ensure_ascii=False))\n",
" \n",
" output = {\n",
" \"task_description\": description,\n",
" \"brief_description\": brief_description,\n",
" \"additional_examples\": list(new_examples_from_briefs.values()) + list(new_examples.values())\n",
" }\n",
" \n",
" return json.dumps(output, indent=2, ensure_ascii=False)\n",
" \n",
" except Exception as e:\n",
" raise RuntimeError(f\"An error occurred during processing: {str(e)}\")\n",
" \n",
"\n",
"import gradio as gr\n",
"\n",
"def process_json(input_json):\n",
" try:\n",
" generator = TaskDescriptionGenerator()\n",
" result = generator.process(input_json)\n",
" return \"Process completed successfully. Result:\\n\" + result\n",
" except Exception as e:\n",
" return f\"An error occurred: {str(e)}\"\n",
"\n",
"demo = gr.Interface(\n",
" fn=process_json,\n",
" inputs=gr.Textbox(label=\"Input JSON\"),\n",
" outputs=gr.Textbox(label=\"Output\"),\n",
" title=\"Task Description Generator\",\n",
" description=\"Enter a JSON object with 'input' and 'output' fields to generate a task description and additional examples.\"\n",
")\n",
"\n",
"if __name__ == \"__main__\":\n",
" demo.launch()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
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"nbformat_minor": 2
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