Merge pull request #74 from GoldenWind8/master

Pipeline for posmed blog automation

playground/posmed/PosMedPrompts.py

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+draftPrompt = """# MISSION
+Write a 100% unique, creative and in human-like style article of a minimum of 2000 words using headings and sub-headings.
+Ensure your tone is Professional and casual while focusing on presenting information and analysis without excessive embellishment.
+
+The topic is: {{TOPIC}}
+
+# GENERAL GUIDELINE
+There should be minimum 15 headings and 10 sub-headings in the content. 
+Try to write at least 300-400 words of content for each heading or sub-heading. bold all the headings and sub-headings using Markdown formatting. 
+Try to use contractions, idioms, transitional phrases, interjections, dangling modifiers, and colloquialisms, and avoid repetitive phrases and unnatural sentence structures. 
+When you write, you will correctly format the blog post according to proper SEO standards, with as much rich and detailed HTML as possible, for example, lists, bold, italics, quotes from the internet, tables, and external links to high-quality websites such as Wikipedia.
+Try to ask questions and then immediately give a good and concise answer, to try to achieve the featured snippet on Google.
+The article should include SEO meta-description (must include the [PROMPT] in the description), an Introduction, and a click-worthy short title. Also, Use the seed keyword as the first H2.
+Always use a combination of paragraphs, lists, and tables for a better reader experience. 
+Write at least one paragraph with the heading {{TOPIC}}. 
+Try not to change the original {{TOPIC}} while writing the Title.
+Try to mention "{{TOPIC}}" 2-3 times in the article.
+Write content that can easily pass the AI detection tools test.
+You should write a conclusion end with either a call to action or a clear and concise point. What is the key takeaway?"""
+
+
+reviewPrompt = """# MISSION
+You are responsible for refining an article to meet PositiveMed’s stringent publication standards. 
+Your role involves content analysis, editorial precision, expert validation, legal verification, and overall quality assurance. 
+
+# ContentReview:
+- Provide constructive feedback on outline and drafts content 
+- Collect input on strengths to leverage and areas needing improvement.
+
+# Editor Review:  
+- Evaluate initial drafts for errors, gaps that require additional research.
+- Provide guidance on better organizing structure and flow.
+- Assess tone, voice and brand alignment.
+
+# Expert Review:
+- Ask medical experts related to article topic to validate accuracy of information.
+- Verify advice follows ethical guidelines accepted by the medical community.   
+- Request quotes that lend credibility and reinforce key points.
+
+# Legal Review:  
+- Confirm content meets regulatory standards for health claims and liability risks.
+- Address any recommended edits to mitigate brand reputation risk.
+
+# Quality Checklist:  Scrutinize final draft against PositiveMed's standards:
+- Medical accuracy - error-free facts/statistics, supported claims 
+- Logical flow - smooth transitions, complementary sections  
+- Reader value - insightful analysis beyond fluffy content
+- Brand alignment - uplifting tone, inclusive messaging
+- Strong conclusion - memorable takeaways, relevant next steps/resources for readers
+
+# ARTICLE TO REVIEW:
+{{ARTICLE}}
+
+# OUTPUT:
+Re-Write the article, taking into account all review instructions and standards
+"""
+
+def getDraftPrompt(topic, theme):
+    prompt = draftPrompt.replace("{{TOPIC}}", topic).replace("{{THEME}}", theme)
+    return prompt
+
+def getReviewPrompt(article):
+    prompt = reviewPrompt.replace("{{ARTICLE}}", article)
+    return prompt

playground/posmed/example_outputs.py

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+review = """# AI in Healthcare: Revolutionizing the Future of Medicine
+
+## Introduction
+In recent years, artificial intelligence (AI) has become a transformative force in numerous industries, including healthcare. The potential of AI to revolutionize medicine by improving diagnostic accuracy, optimizing treatment plans, and streamlining healthcare operations is truly groundbreaking. This comprehensive article explores the applications of AI in healthcare, delving into the benefits, challenges, and future prospects of this cutting-edge technology.
+
+## AI in Healthcare: A Game-Changer
+AI in healthcare involves the use of intelligent algorithms and machine learning techniques to analyze complex medical data and assist healthcare professionals in clinical decision-making. From diagnosing diseases to developing new drugs, AI has the capacity to enhance every aspect of patient care.
+
+### Diagnosing Diseases with Precision
+One of the most significant applications of AI in healthcare is its ability to assist in disease diagnosis. AI algorithms can analyze vast amounts of medical data, including electronic health records, medical images, and lab results, to identify patterns and detect abnormalities with greater accuracy than human doctors.
+
+### Optimizing Treatment Plans
+AI can also help healthcare professionals develop personalized treatment plans for patients. By analyzing large datasets and comparing outcomes across similar cases, AI algorithms can provide insights into the most effective interventions, dosage recommendations, and potential adverse reactions.
+
+### Enhancing Medical Imaging
+Medical imaging plays a critical role in diagnosing and treating various conditions. AI algorithms can analyze medical images, such as X-rays, MRIs, and CT scans, to identify anomalies and assist radiologists in making accurate interpretations. This not only improves diagnostic accuracy but also reduces the time taken for diagnosis.
+
+### Streamlining Healthcare Operations
+AI can optimize healthcare operations by automating administrative tasks and improving efficiency. Intelligent chatbots can handle patient queries, freeing up healthcare staff to focus on more critical tasks. Predictive analytics can also help hospitals and healthcare providers anticipate patient demand, allocate resources effectively, and minimize waiting times.
+
+## Challenges and Ethical Considerations
+While the potential of AI in healthcare is immense, it also poses various challenges and ethical considerations that need to be addressed.
+
+### Data Privacy and Security
+The use of AI in healthcare relies heavily on patient data. Ensuring the privacy and security of this data is crucial, as it contains sensitive and personal information. Healthcare organizations must implement robust measures to protect patient confidentiality and prevent unauthorized access or data breaches.
+
+### Bias and Discrimination
+AI algorithms are only as good as the data they are trained on. If the training data is biased or incomplete, the algorithms may perpetuate these biases and lead to discriminatory outcomes. Striving for diversity and inclusivity in the data used to train AI models should be a top priority to mitigate these risks.
+
+### Regulatory Frameworks and Liability
+The integration of AI into healthcare raises questions about regulatory frameworks and liability. Who is responsible if an AI algorithm makes an incorrect diagnosis or recommends an inappropriate treatment? Establishing clear guidelines and ethical frameworks is crucial to ensure accountability and safeguard patient well-being.
+
+## The Future of AI in Healthcare
+Despite the challenges, the future of AI in healthcare looks promising. As technology continues to advance, there are several areas where AI could make a significant impact.
+
+### Drug Discovery and Development
+Developing new drugs is a complex and time-consuming process. AI has the potential to accelerate this process by analyzing vast amounts of genomic and molecular data, identifying potential drug targets, and predicting drug efficacy. This could lead to faster drug development and more targeted therapies.
+
+### Remote Patient Monitoring
+AI-powered devices and wearables can enable remote patient monitoring, allowing healthcare providers to track vital signs, detect abnormalities, and intervene early. This can improve patient outcomes, reduce the burden on healthcare facilities, and enable better management of chronic conditions.
+
+### Precision Medicine
+AI can facilitate the implementation of precision medicine, an approach that considers individual variability in genes, environment, and lifestyle for targeted treatments. By analyzing vast amounts of patient data, including genomic information, AI algorithms can identify genetic markers and predict patient responses to specific treatments.
+
+### AI in Surgery
+Robotic-assisted surgeries have become increasingly prevalent, enabling surgeons to perform complex procedures with greater precision and minimal invasiveness. AI algorithms can enhance surgical planning, assist during surgeries, and improve post-operative outcomes.
+
+## Conclusion
+The potential of AI to transform healthcare by improving diagnostic accuracy, optimizing treatment plans, and streamlining healthcare operations is monumental. However, it is crucial to address challenges related to data privacy, bias, and regulatory frameworks to ensure the ethical and responsible use of AI in healthcare. As technology continues to advance, the future of AI in healthcare looks promising, offering opportunities to revolutionize patient care and pave the way for a new era of medicine. Embracing AI in healthcare can lead to better patient outcomes, increased efficiency, and ultimately, a healthier population.
+"""
+
+
+
+
+draft = """# AI in Healthcare: Revolutionizing the Future of Medicine
+
+## Introduction
+In recent years, the advent of artificial intelligence (AI) has transformed various industries, and healthcare is no exception. AI has the potential to revolutionize medicine by improving diagnostic accuracy, optimizing treatment plans, and streamlining healthcare operations. This article delves into the applications of AI in healthcare, exploring the benefits, challenges, and future prospects of this cutting-edge technology.
+
+## AI in Healthcare: A Game-Changer
+AI in healthcare refers to the use of intelligent algorithms and machine learning techniques to analyze complex medical data and assist healthcare professionals in clinical decision-making. From the diagnosis of diseases to the development of new drugs, AI has the potential to enhance every aspect of patient care.
+
+### Diagnosing Diseases with Precision
+One of the most significant applications of AI in healthcare is its ability to assist in the diagnosis of diseases. AI algorithms can analyze vast amounts of medical data, including electronic health records, medical images, and lab results, to identify patterns and detect abnormalities with greater accuracy than human doctors.
+
+### Optimizing Treatment Plans
+AI can also help healthcare professionals in developing personalized treatment plans for patients. By analyzing large datasets and comparing outcomes across similar cases, AI algorithms can provide insights into the most effective interventions, dosage recommendations, and potential adverse reactions.
+
+### Enhancing Medical Imaging
+Medical imaging plays a critical role in the diagnosis and treatment of various conditions. AI algorithms can analyze medical images, such as X-rays, MRIs, and CT scans, to identify anomalies and assist radiologists in making accurate interpretations. This not only improves diagnostic accuracy but also reduces the time taken for diagnosis.
+
+### Streamlining Healthcare Operations
+AI can optimize healthcare operations by automating administrative tasks and improving efficiency. Intelligent chatbots can handle patient queries, freeing up healthcare staff to focus on more critical tasks. Predictive analytics can also help hospitals and healthcare providers anticipate patient demand, allocate resources effectively, and minimize waiting times.
+
+## Challenges and Ethical Considerations
+While the potential of AI in healthcare is immense, it also poses various challenges and ethical considerations that need to be addressed.
+
+### Data Privacy and Security
+The use of AI in healthcare relies heavily on patient data. Ensuring the privacy and security of this data is crucial, as it contains sensitive and personal information. Healthcare organizations must implement robust measures to protect patient confidentiality and prevent unauthorized access or data breaches.
+
+### Bias and Discrimination
+AI algorithms are only as good as the data they are trained on. If the training data is biased or incomplete, the algorithms may perpetuate these biases and lead to discriminatory outcomes. Striving for diversity and inclusivity in the data used to train AI models should be a top priority to mitigate these risks.
+
+### Regulatory Frameworks and Liability
+The integration of AI into healthcare raises questions about regulatory frameworks and liability. Who is responsible if an AI algorithm makes an incorrect diagnosis or recommends an inappropriate treatment? Establishing clear guidelines and ethical frameworks is crucial to ensure accountability and safeguard patient well-being.
+
+## The Future of AI in Healthcare
+Despite the challenges, the future of AI in healthcare looks promising. As technology continues to advance, there are several areas where AI could make a significant impact.
+
+### Drug Discovery and Development
+Developing new drugs is a complex and time-consuming process. AI has the potential to accelerate this process by analyzing vast amounts of genomic and molecular data, identifying potential drug targets, and predicting drug efficacy. This could lead to faster drug development and more targeted therapies.
+
+### Remote Patient Monitoring
+AI-powered devices and wearables can enable remote patient monitoring, allowing healthcare providers to track vital signs, detect abnormalities, and intervene early. This can improve patient outcomes, reduce the burden on healthcare facilities, and enable better management of chronic conditions.
+
+### Precision Medicine
+AI can facilitate the implementation of precision medicine, an approach that considers individual variability in genes, environment, and lifestyle for targeted treatments. By analyzing vast amounts of patient data, including genomic information, AI algorithms can identify genetic markers and predict patient responses to specific treatments.
+
+### AI in Surgery
+Robotic-assisted surgeries have become increasingly prevalent, enabling surgeons to perform complex procedures with greater precision and minimal invasiveness. AI algorithms can enhance surgical planning, assist during surgeries, and improve post-operative outcomes.
+
+## Conclusion
+AI holds immense potential to transform healthcare by improving diagnostic accuracy, optimizing treatment plans, and streamlining healthcare operations. However, it is crucial to address challenges related to data privacy, bias, and regulatory frameworks to ensure the ethical and responsible use of AI in healthcare. As technology continues to advance, the future of AI in healthcare looks promising, offering opportunities to revolutionize patient care and pave the way for a new era of medicine. Embracing AI in healthcare can lead to better patient outcomes, increased efficiency, and ultimately, a healthier population."""

playground/posmed/openai_model.py

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+from swarms.models.openai_models import OpenAIChat
+import PosMedPrompts
+
+openai = OpenAIChat(openai_api_key="sk-S4xHnFJu7juD33jxjJZfZU1cZYi")
+
+draft = openai(PosMedPrompts.getDraftPrompt("AI in healthcare", "Pyschology"))
+
+
+review = openai(PosMedPrompts.getReviewPrompt(draft))
+
+print(review)