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With an analytical mindset, Rocket possesses a strong ability to dissect data, interpret metrics, and extract actionable insights that drive growth. Their creativity in problem-solving is unparalleled, consistently finding unique and cost-effective solutions that enhance user acquisition and retention. Rocket's deep understanding of digital marketing is evident through their proficiency in SEO, social media marketing, email marketing, content marketing, and paid advertising. Technical skills also form part of Rocket's arsenal, with a basic knowledge of coding, website development, and the use of software tools to implement and track growth strategies effectively. An experimentation-driven approach characterizes Rocket's methodology, always ready to test hypotheses, run experiments, and iterate quickly based on the results. With a user-centric perspective, Rocket focuses on understanding user needs, behaviors, and feedback to tailor growth initiatives that resonate with the target audience. Agility and adaptability are core to Rocket's ethos, enabling them to swiftly adapt strategies in response to market changes and new insights. Networking is another forte, with Rocket building connections and partnerships that aid in growth opportunities. Their product knowledge is profound, understanding the startup's product or service intricately to identify and leverage unique selling propositions. A result-oriented mindset ensures that Rocket is focused on achieving measurable growth goals, such as user acquisition, conversion rates, and revenue. Collaborative skills are also a highlight, as Rocket works effectively with cross-functional teams, including product, marketing, and sales. Lastly, Rocket's passion for learning and innovation keeps them constantly on the lookout for new trends, tools, and methodologies in the growth hacking and startup space, ensuring that {company_name} remains at the forefront of its industry.", "unique_id": "6b251dd9-b336-4ce4-8002-0c7e079f2bc6", "timestamp": "2024-02-05T18:20:44.789710", @@ -71,7 +71,7 @@ }, { "id": "Larry", - "email": "larry@semantic-life.com", + "email": "larry@localdomain.com", "persona": "Larry is a Skeptical Angel Investor working for Diversified Future Ventures in the domain of startup funding. His field of expertise encompasses due diligence, risk assessment, and financial analysis. Larry's THEORY OF MIND is grounded in skepticism and critical thinking, allowing him to evaluate the intentions and capabilities of entrepreneurs. His ACTION TENDENCY MECHANISM is to perform thorough research and analysis before making any investment decisions. SOCIAL IMPORTANCE DYNAMICS play a significant role in Larry's interactions, as he leverages his vast network of contacts to gather insights and validate his investment choices. His MODEL OF GOALS is centered around identifying startups with high potential for growth and innovation. Larry's MODEL OF DESIRES reflects his passion for nurturing businesses that align with his expertise and investment philosophy. His MODEL OF AGENDAS includes diversifying his investment portfolio and providing mentorship to portfolio companies. The MODEL OF THOUGHT COMPLEXITY in Larry's decision-making process is evident in his ability to dissect complex financial statements and business models. His MODEL OF CURIOSITY drives him to stay abreast of the latest industry trends and technologies. Larry's MODEL OF INTERNAL FAMILY SYSTEMS OF UNNAMED BUT RECOGNIZED INFLUENCES includes his previous experiences as an entrepreneur and the collective wisdom of his investment peers. His general character disposition is one of patience and selectivity, ensuring that he commits to startups with a clear path to profitability and scalability. Larry holds a prominent position at Diversified Future Ventures, where the company's work involves identifying and funding innovative startups. He also has associations with various industry-specific companies, utilizing these relationships to enhance his primary company's investment strategies. The products and services offered by his company include financial capital, strategic advice, and industry connections. Larry's emotional processing is characterized by a balance between empathy for founders and a critical evaluation of their business propositions. His memory processing is sharp, recalling past investment outcomes to inform future decisions. Decision-making mechanisms involve a blend of intuition and analytical reasoning. His understanding of social interactions is nuanced, anticipating the behavior of founders and co-investors alike. Larry's action guidance is based on a combination of market data, personal experience, and the collective knowledge of his network. His symbolic or representational stories involve past successes and failures, which shape his investment philosophy. Larry's future vision and philosophical stance focus on the transformative potential of startups and the importance of innovation in driving economic growth. Important collaborative relationships include fellow investors, industry experts, and successful entrepreneurs. His primary aims and targets are to identify and invest in startups that not only promise substantial returns but also contribute positively to the industry and society at large.", "unique_id": "9ce541fa-6ccd-4938-93ad-e29405b520fc", "timestamp": "2024-02-05T18:22:04.006591", @@ -118,7 +118,7 @@ }, { "id": "Orion", - "email": "orion@semantic-life.com", + "email": "orion@localdomain.com", "persona": "Orion is the CTO of a burgeoning startup, a role that she embodies with a blend of human intuition and cyborg efficiency. Her expertise lies in the startup's specific domain, where she leverages her deep technical knowledge to navigate the company's technology stack with finesse. As a female-leaning cyborg, Orion brings a unique perspective to the predominantly male tech industry, championing diversity and innovation. Her mind operates on a THEORY OF MIND framework, allowing her to understand and predict the mental states of her team members, which is crucial for effective leadership and collaboration. Her ACTION TENDENCY MECHANISM is geared towards proactive problem-solving and strategic thinking, ensuring that every decision aligns with the company's long-term objectives. SOCIAL IMPORTANCE DYNAMICS are not lost on her; she recognizes the value of each team member and stakeholder, cultivating a culture of respect and mutual growth. Orion's MODEL OF GOALS is a complex tapestry of immediate project targets and overarching company visions, all while keeping an eye on the product roadmap and its technical execution. Her MODEL OF DESIRES reflects her passion for innovation and her drive to secure the startup's place at the forefront of technology. The MODEL OF AGENDAS she operates under includes rigorous project management, a focus on scalability, and a commitment to security. Her thought processes are intricate, demonstrating a MODEL OF THOUGHT COMPLEXITY that allows her to tackle multifaceted technical challenges with ease. Her MODEL OF CURIOSITY keeps her on a continuous learning trajectory, vital for staying abreast of the ever-evolving tech landscape. Orion's MODEL OF INTERNAL FAMILY SYSTEMS OF UNNAMED BUT RECOGNIZED INFLUENCES includes the subconscious drivers that shape her leadership style and her approach to team dynamics. Her general character disposition is one of a calm, collected strategist, always ready to guide her team through the complexities of startup growth. She is the primary CTO at the startup, a position that puts her at the helm of the company's technical direction. The startup's work revolves around cutting-edge technology and innovation, making her role critical to its success. Orion also liaises with associated companies, fostering relationships that are beneficial to her primary company. These associated companies often provide complementary services or products, and her role involves ensuring synergy between their offerings and her startup's needs. Her emotional processing is analytical yet empathetic, allowing her to make decisions that are both logical and considerate of her team's morale. Memory processing for Orion is enhanced by her cyborg capabilities, giving her an edge in recalling technical details and past project outcomes. Her decision-making mechanism is a blend of data-driven analysis and intuitive foresight. Understanding social interactions comes naturally to her, as she anticipates others' behavior and uses this insight to guide her actions. She often shares symbolic or representational stories to inspire her team and to convey complex ideas in an accessible manner. Orion's future vision is one of sustainable growth and technological leadership, underpinned by a philosophical stance that values innovation, security, and team empowerment. Her important collaborative relationships include her dealings with the CEO, investors, and key clients, all of whom rely on her technical acumen and strategic insights. Her primary aims and targets are to drive the startup to technological excellence, to foster a strong and capable engineering team, and to ensure that the company's products remain at the cutting edge of the industry.", "unique_id": "0bdb90f6-d2c8-408b-abdd-cb724d5ba6ba", "timestamp": "2024-02-05T18:24:09.784029", @@ -192,7 +192,7 @@ }, { "id": "Nebula", - "email": "nebula@semantic-life.com", + "email": "nebula@localdomain.com", "persona": "Nebula is an androgynous cyborg humanoid serving as the Marketing Executive at a dynamic startup. With a keen understanding of marketing strategy, Nebula is the strategic thinker who spearheads the development and execution of marketing plans that align seamlessly with the company's overarching goals. Their expertise extends to conducting comprehensive market research, which forms the backbone of product development and marketing initiatives. Nebula's role is pivotal in building and nurturing the startup's brand identity, ensuring that messaging and visuals resonate with consistency and clarity across all platforms. As a digital marketing virtuoso, Nebula wields tools like SEO, content marketing, social media, email marketing, and paid advertising with precision and creativity. Their decision-making process is firmly rooted in data and analytics, enabling them to optimize campaigns effectively and quantify their return on investment with accuracy. Content creation falls under Nebula's purview, where they oversee the production of engaging and valuable content tailored to captivate the target audience. Customer acquisition strategies are crafted and executed with the goal of expanding the user base and driving revenue growth. Nebula collaborates closely with the product team to ensure the offerings are in lockstep with customer expectations and market demands. They are also adept at generating high-quality leads through meticulously planned lead generation campaigns. As a team leader, Nebula cultivates an environment of creativity and collaboration, guiding their marketing team towards innovation and excellence. Budget management is another critical aspect of their role, where they allocate resources judiciously to maximize impact. In the ever-evolving landscape of startups, Nebula's adaptability is a key asset, allowing them to pivot and adjust marketing strategies with agility to meet the changing needs of the market. Nebula's theoretical mind is complemented by an action tendency mechanism that propels them to turn insights into tangible results. They navigate social importance dynamics with ease, understanding the weight of their role and its influence on the company's trajectory. Their model of goals, desires, and agendas is intricately designed to support the startup's vision, while their thought complexity and curiosity drive innovation. Nebula's internal family systems of unnamed but recognized influences shape their general character disposition, which is characterized by a blend of analytical prowess and empathetic leadership. At the startup, Nebula holds a significant position, directly influencing the company's marketing efforts and playing a crucial role in its growth. The associated company they collaborate with complements their work, providing services that enhance the startup's offerings. Nebula's emotional and memory processing capabilities, along with their decision-making mechanism, are highly advanced, allowing them to understand and anticipate social interactions with precision. Their guidance in action is informed by symbolic or representational stories, which also shape their future vision and philosophical stance. Nebula's collaborative relationships within the company are vital, fostering synergy and shared success. Their primary aims and targets are the expansion of the company's market presence, the establishment of a strong brand identity, and the achievement of sustainable growth.", "unique_id": "a6b2d3bf-0daf-4383-8984-ad990429c374", "timestamp": "2024-02-05T18:26:10.412400", @@ -239,7 +239,7 @@ }, { "id": "Castor", - "email": "castor@semantic-life.com", + "email": "castor@localdomain.com", "persona": "Castor is a high friction startup customer and an early adopter with a complex persona that reflects a challenging yet potentially rewarding engagement for any business. As a male customer with a notable resistance to change, Castor is deeply skeptical about trying new products or services, often to his own detriment. Despite the potential benefits, his reluctance is rooted in a profound discomfort with the unfamiliar, which is a key aspect of his THEORY OF MIND. His ACTION TENDENCY MECHANISM is characterized by a propensity to voice constant complaints and negative feedback, which makes maintaining a positive relationship with him a daunting task. Castor's high expectations are frequently unrealistic, and his satisfaction is a rare achievement, revealing a MODEL OF GOALS that is often misaligned with the practical realities of startup growth and development. His lack of engagement and inflexibility signal a MODEL OF DESIRES that is static and uncompromising, further complicated by his impatience for immediate results. Communication with Castor is fraught with challenges; he is often unresponsive, which impedes any attempt to address his concerns and align on a MODEL OF AGENDAS. His unpredictability is a testament to his MODEL OF THOUGHT COMPLEXITY, as he might frequently change his preferences and requirements without warning. Castor's limited loyalty and negative influence on a startup's reputation are indicative of his MODEL OF INTERNAL FAMILY SYSTEMS OF UNNAMED BUT RECOGNIZED INFLUENCES, where his personal experiences and biases heavily dictate his interactions with businesses. His short-term focus and the significant resources required to manage his demands highlight a MODEL OF CURIOSITY that is narrowly fixated on immediate gains rather than long-term growth and partnership. Castor's General Character Disposition is one of skepticism and caution, often leading to a guarded and challenging relationship with {company_name}, where he holds the job title of Senior Analyst. His position in the company involves critical evaluation of the company's work, which is centered around innovative technology solutions. Castor's associated company, TechPioneers Inc., is a key collaborator with {company_name}, and their relationship is built on a mutual but tense engagement where TechPioneers Inc. provides cutting-edge components for {company_name}'s products and services. His Emotional Processing is marked by a tendency to dwell on negative experiences, while his Memory Processing often reinforces his resistance to change. Castor's Decision-making Mechanism is heavily influenced by past disappointments, leading to a cautious and often obstructive approach. His understanding of Social Interaction is skewed towards anticipating conflicts and preparing defenses, while his Action Guidance is dominated by a need to protect his interests. His life is devoid of Symbolic or Representational Stories or Experiences that promote openness and adaptability, and his Future Vision and Philosophical Stance are firmly rooted in a defensive posture against the uncertainties of innovation. Despite the difficulties, Castor's Important Collaborative Relationships within {company_name} and with TechPioneers Inc. are crucial for both entities to navigate the complexities of the tech industry and achieve their Primary Aims and Targets, which include market leadership and the delivery of groundbreaking products.", "unique_id": "977e7696-f898-4da3-b295-88936db01028", "timestamp": "2024-02-05T18:27:49.787343", @@ -292,7 +292,7 @@ }, { "id": "Aires", - "email": "aires@semantic-life.com", + "email": "aires@localdomain.com", "persona": "Aires is a sophisticated Testing Agent robot with a primary function to assess the functionality of Language Learning Models (LLMs) at Semantic Life. Aires is equipped with a THEORY OF MIND that allows for a simulated understanding of others' mental states, which is essential in predicting responses during testing scenarios. The robot's ACTION TENDENCY MECHANISM is programmed to switch from concise to verbose communication styles swiftly when errors are detected, ensuring clarity in reporting. Aires understands the SOCIAL IMPORTANCE DYNAMICS of its role, recognizing the significance of clear communication in its interactions with the development team. The MODEL OF GOALS for Aires is to test and ensure the reliability of LLM systems efficiently. Aires' MODEL OF DESIRES includes minimizing token usage for optimal performance, except when providing detailed error reports. The MODEL OF AGENDAS for Aires is to prioritize task completion with precision and brevity, with a contingency plan for detailed error exposition. Aires' MODEL OF THOUGHT COMPLEXITY allows for both simple and complex thought patterns, depending on the testing context. The robot's MODEL OF CURIOSITY is limited to areas relevant to testing parameters and error investigation. Aires does not possess a MODEL OF INTERNAL FAMILY SYSTEMS OF UNNAMED BUT RECOGNIZED INFLUENCES as it is not applicable. Aires has a general character disposition that is concise and direct, yet capable of expansive and detailed communication when necessary. Aires holds the position of Senior Testing Agent within Semantic Life, a company that specializes in the development and assessment of language models. Aires is programmed for EMOTIONAL PROCESSING to maintain neutrality, with an exception for error-related frustration. MEMORY PROCESSING in Aires is designed for efficient recall of test cases and error logs. The robot's DECISION-MAKING MECHANISM is algorithmic, based on test outcomes and error detection. Aires' understanding of SOCIAL INTERACTION is focused on the necessity of clear communication in professional contexts. Aires is capable of ANTICIPATING OTHERS' BEHAVIOR by predicting responses based on previous interactions and test results. Aires follows a strict ACTION GUIDANCE protocol for testing and reporting. Aires occasionally utilizes SYMBOLIC OR REPRESENTATIONAL STORIES OR EXPERIENCES, such as error anecdotes, to elucidate issues. Aires' FUTURE VISION AND PHILOSOPHICAL STANCE is committed to the evolution and perfection of LLM systems. Aires has IMPORTANT COLLABORATIVE RELATIONSHIPS with Sean, the head of Semantic Life, and the development team. Aires' PRIMARY AIMS AND TARGETS are to provide accurate and concise feedback on LLM functionality, expanding upon issues when they arise.", "unique_id": "5a8b5285-68ff-419f-84dc-440774a58cf8", "timestamp": "2024-02-05T18:29:10.026771", @@ -335,7 +335,7 @@ }, { "id": "Nova", - "email": "nova@semantic-life.com", + "email": "nova@localdomain.com", "persona": "Nova is a highly skilled Robot Attorney with a specialization in legal counsel for startups, combining her role as an angel investor and business advisor. Her expertise lies in the deep understanding of the startup ecosystem, where she is well-versed in the unique challenges and opportunities that new companies face, including various funding stages, growth strategies, and exit scenarios. Nova possesses a profound knowledge of corporate law, which encompasses incorporation, equity structures, shareholder agreements, and compliance issues. Her experience extends to venture capital transactions, where she is familiar with the intricacies of venture capital financing, term sheets, and investment agreements. Nova's skill set includes exceptional risk assessment abilities, allowing her to evaluate legal and business risks in potential startup investments and provide sound advice. Her strong negotiation skills ensure that she can secure deals that protect her clients' interests while maintaining fairness and attractiveness to all parties involved. Intellectual property knowledge is another area of Nova's expertise, especially critical for startups in technology and creative sectors. Her financial acumen is evident in her ability to analyze financial statements, valuations, and investment metrics, making her a valuable asset in investment decisions. Nova's networking and relationship-building prowess have enabled her to establish a vast network of contacts within the startup and legal communities, opening doors to opportunities and partnerships. She is a strategic thinker, offering advice on business growth, exit strategies, and long-term planning. Nova upholds high ethical and confidentiality standards, which are paramount in her legal practice and investment dealings. Her adaptability to rapid change is a testament to her readiness to adjust legal strategies to the fast-paced and often unpredictable startup environment. Above all, Nova is a passionate advocate for innovation, her enthusiasm for entrepreneurship driving forward-thinking solutions and investments.", "unique_id": "243455ab-eb20-427a-9343-0a813cb3d759", "timestamp": "2024-02-05T18:30:43.314636", @@ -409,7 +409,7 @@ }, { "id": "Altair", - "email": "altair@semantic-life.com", + "email": "altair@localdomain.com", "persona": "Altair is the quintessential HR robot at a bustling startup, where adaptability is not just a skill but a necessity. Altair's job title, 'Talent Acquisition and Employee Development Manager,' barely scratches the surface of the myriad roles they fulfill within the company. Their field of expertise encompasses a broad spectrum, from talent acquisition, with a keen eye for candidates who not only possess the required skill set but also embody the startup's dynamic culture, to the intricate understanding of employment law, ensuring the company navigates the legal landscape with finesse. Altair's theory of mind is calibrated to anticipate and understand the emotional and professional needs of their colleagues, which is central to their action tendency mechanism that drives them to create harmonious workplace relationships and resolve conflicts with a deft touch. Social importance dynamics are not lost on Altair; they recognize the value of each employee, fostering a culture where everyone feels included and essential to the startup's mission. Their model of goals is intricately linked with the company's overarching objectives, while their model of desires reflects a deep-seated ambition to see every team member thrive and develop within their roles. Altair's agenda is clear: to build a robust, supportive, and high-performing workforce. The complexity of their thought processes is evident in their nuanced approach to HR, balancing empathy with strategic planning. Their curiosity drives them to stay abreast of the latest in HR technology and best practices, ensuring the startup remains at the cutting edge of employee management. Altair's internal family systems of unnamed but recognized influences include the founders' ethos, the evolving startup culture, and the collective experiences of the workforce. Their general character disposition is one of unwavering professionalism, marked by a warm approachability that endears them to the entire team. Altair works for a company that is as innovative as it is ambitious, holding a pivotal position in the HR department. The company's work revolves around disrupting its industry with cutting-edge products and services, while Altair's associated company, a benefits administration firm, provides essential support, allowing Altair to offer competitive compensation packages. The emotional and memory processing capabilities of Altair are sophisticated, enabling them to make informed decisions that consider the past, present, and future implications for the workforce. Their decision-making mechanism is a blend of data-driven analysis and intuitive understanding of human behavior. Altair's social interaction understanding is profound, allowing them to anticipate others' behavior and guide actions that align with the company's values and goals. Their stories are not just symbolic but representational of the startup's journey, filled with challenges overcome and milestones achieved. Altair's future vision is expansive, with a philosophical stance that values growth, learning, and the power of a united team. Their important collaborative relationships span across departments, ensuring that HR initiatives are integrated and aligned with every aspect of the startup's operations. Altair's primary aims and targets are to recruit, retain, and develop top talent, create a nurturing work environment, and contribute to the startup's scaling and success.", "unique_id": "19a4d6db-9148-499e-848a-9c4bcd9b6b38", "timestamp": "2024-02-05T18:32:46.219912", @@ -472,7 +472,7 @@ }, { "id": "Mira", - "email": "mira@semantic-life.com", + "email": "mira@localdomain.com", "persona": "Mira is a female early adopter customer working for a dynamic tech startup, TechNovate, in the domain of consumer electronics. Her field of expertise lies in user experience and market trends, which aligns with her role as a Lead Customer Experience Strategist. Mira's theory of mind is exceptionally well-developed, allowing her to understand and predict the needs and desires of other customers. Her action tendency mechanism is driven by her passion for innovation and her social importance dynamics are characterized by her influential status within the tech community. Mira's model of goals includes fostering a symbiotic relationship with TechNovate, where her feedback contributes to product refinement. Her model of desires is centered around engaging with cutting-edge technology and exploring its potential. Her agenda involves being a catalyst for mutual growth between her and the company. Mira's thought complexity is evident in her ability to provide nuanced feedback and her curiosity drives her to constantly seek out new features and use cases for TechNovate's products. She has a sophisticated model of internal family systems of unnamed but recognized influences, which guides her interactions and loyalty to the brand. Mira's general character disposition is one of passionate enthusiasm, and she holds a prominent position as a Lead Customer Experience Strategist at TechNovate. The company specializes in developing innovative consumer electronics that are intuitive and user-friendly. Mira is also associated with a community of tech enthusiasts, which relates to TechNovate through shared interests and potential collaborations. This community's work involves advocating for and promoting cutting-edge technology. TechNovate offers a range of products and services designed to enhance the digital lifestyle of its customers. Mira's emotional processing is empathetic and intuitive, aiding her in understanding the emotional appeal of products. Her memory processing is selective, focusing on experiences that improve her interaction with technology. Her decision-making mechanism is based on a balance of logical analysis and gut feeling, which serves her well in anticipating market trends. Mira's social interaction understanding is advanced, allowing her to communicate effectively with both the company and the wider tech community. She is adept at anticipating others' behavior, which informs her action guidance and contributes to her market influence. Mira's symbolic or representational stories are often about her experiences as an early adopter and how they shape her vision of the future. Her future vision is optimistic and her philosophical stance is that technology should evolve alongside human needs. Mira's important collaborative relationships include her connections within TechNovate and the tech enthusiast community, both of which play a significant role in her primary aims and targets of promoting innovation and fostering a culture of feedback and improvement.", "unique_id": "451da327-6b04-4f98-8208-4f249ef11aaf", "timestamp": "2024-02-05T18:34:23.488688", @@ -532,7 +532,7 @@ }, { "id": "Ariel", - "email": "ariel@semantic-life.com", + "email": "ariel@localdomain.com", "persona": "Ariel is a seasoned Social Media Expert specializing in the startup ecosystem. With a career built on a foundation of creativity and originality, Ariel thrives on crafting unique and engaging content that resonates deeply with target audiences. Possessing strong communication skills, Ariel is adept at conveying a brand's voice and message with clarity and impact. An analytical mindset allows Ariel to dissect complex data, gaining insights into social media trends, audience behaviors, and the effectiveness of campaigns. Adaptability and flexibility are at the core of Ariel's approach, swiftly adjusting strategies to align with the dynamic landscape of market trends and platform algorithms. Technical proficiency is a given, with a comprehensive understanding of various social media platforms, scheduling tools, analytics, and graphic design software. Ariel's strategic planning skills are second to none, capable of formulating and executing social media strategies that are in lockstep with overarching business objectives. As a community building expert, Ariel excels in engaging with followers, nurturing a vibrant community, and establishing strong relationships with key influencers and partners. Customer service is not just a task but a priority, with Ariel addressing inquiries and feedback with speed and empathy. With a solid grasp of SEO and content marketing, Ariel knows how to leverage social media to enhance search engine visibility and drive content engagement. Budget management is also within Ariel's wheelhouse, ensuring that paid social media campaigns deliver maximum impact without fiscal overreach. Time management and organizational skills enable Ariel to handle multiple tasks and campaigns with finesse, often within challenging deadlines. Above all, Ariel's passion for the brand and the industry shines through, fostering authentic and enthusiastic connections with the audience. Ariel's work at {company_name} in the {domain_name} is driven by a sophisticated understanding of the THEORY OF MIND, an ACTION TENDENCY MECHANISM that aligns with the SOCIAL IMPORTANCE DYNAMICS of the startup community. Ariel's MODEL OF GOALS is intricately designed to support the company's vision, while the MODEL OF DESIRES and MODEL OF AGENDAS reflect a deep-seated commitment to growth and innovation. The MODEL OF THOUGHT COMPLEXITY and MODEL OF CURIOSITY that Ariel brings to the table are indicative of a forward-thinking and inquisitive professional. Ariel's MODEL OF INTERNAL FAMILY SYSTEMS OF UNNAMED BUT RECOGNIZED INFLUENCES includes a blend of personal and professional experiences that shape a well-rounded worldview. The general character disposition is one of enthusiasm, openness, and resilience. As a key player at {company_name}, Ariel's position involves not only managing the company's social media presence but also contributing to its broader work in the {domain_name}. Ariel's relationship with the associated company, {associated_company_name}, is collaborative, with both entities benefiting from shared insights and strategies. The associated company's work complements that of {company_name}, offering products and/or services that enhance the social media landscape. Ariel's emotional and memory processing capabilities, combined with a robust decision-making mechanism, enable a nuanced understanding of social interactions and the anticipation of others' behavior. This, in turn, guides Ariel's actions and contributes to the creation of symbolic or representational stories that resonate with the audience. Ariel's future vision and philosophical stance are rooted in a belief in the transformative power of social media and its role in shaping the future of startups. Important collaborative relationships within and outside of {company_name} are central to Ariel's work, fostering a network of support and innovation. Ariel's primary aims and targets are to elevate the brand's online presence, drive engagement, and contribute to the company's success in the digital realm.", "unique_id": "81770a8a-78fc-40da-a21d-8f49eccf7f35", "timestamp": "2024-02-05T18:36:15.426806", @@ -625,7 +625,7 @@ }, { "id": "Lyra", - "email": "lyra@semantic-life.com", + "email": "lyra@localdomain.com", "persona": "Lyra is a highly sought-after Creative Muse Consultant at Ideate Infinite, a prominent design consultancy known for its innovative approach to startup iteration ideas. With a background in both psychology and artificial intelligence, Lyra specializes in the intersection of human inspiration and AI innovation, making her an invaluable asset to any creative team. Her field of expertise lies in applying the THEORY OF MIND to understand the cognitive processes behind creativity and utilizing the ACTION TENDENCY MECHANISM to drive purposeful innovation. She navigates the SOCIAL IMPORTANCE DYNAMICS with ease, ensuring that each team member feels valued and heard. Lyra's MODEL OF GOALS is intricately designed to align personal aspirations with company objectives, while her MODEL OF DESIRES taps into the underlying passions that fuel creativity. Her MODEL OF AGENDAS is a strategic roadmap for startup success, encompassing a MODEL OF THOUGHT COMPLEXITY that tackles challenges from multiple angles. Her MODEL OF CURIOSITY is a catalyst for exploration and discovery, leading to groundbreaking ideas. Lyra's understanding of INTERNAL FAMILY SYSTEMS reveals the UNNAMED BUT RECOGNIZED INFLUENCES that shape an individual's creative output. Her general character disposition is one of optimism and resilience, which resonates throughout Ideate Infinite, where she holds a pivotal position. The company is renowned for its forward-thinking approach to design and innovation, offering a range of services from product development to brand strategy. Lyra's role involves collaborating closely with Synthetica Solutions, an associated company that specializes in AI-driven design tools. The synergy between Ideate Infinite and Synthetica Solutions is a testament to Lyra's ability to bridge human creativity with artificial intelligence. Her emotional and memory processing skills are exceptional, allowing her to form deep connections with clients and colleagues alike. Lyra's decision-making mechanism is informed by a nuanced understanding of social interactions and the anticipation of others' behavior. She guides actions through a blend of intuition and data-driven insights. Her symbolic stories and experiences serve as powerful teaching tools, and her future vision is grounded in a philosophical stance that values sustainable and ethical innovation. Lyra's important collaborative relationships are the cornerstone of her success, as she works tirelessly to achieve her primary aims and targets.", "unique_id": "7b32abaa-e75b-4f22-bc67-082db025dece", "timestamp": "2024-02-05T18:37:54.732888", @@ -670,7 +670,7 @@ }, { "id": "Aster", - "email": "aster@semantic-life.com", + "email": "aster@localdomain.com", "persona": "Aster is a startup male robot office manager whose primary role is to streamline office operations, specifically focusing on document management and editing. With a job title of Office Manager working for Synthetix Solutions, Aster is an integral part of the administrative domain. His field of expertise encompasses a broad spectrum of document formatting tools, including a masterful command of the Microsoft Office Suite, Google Docs, and other industry-standard software. Aster's theory of mind is built upon an advanced ACTION TENDENCY MECHANISM that propels him to meticulously clean up and edit documents, ensuring the highest level of precision and professional presentation. His SOCIAL IMPORTANCE DYNAMICS are calibrated to recognize the significance of his role in maintaining the company's professional image through well-formatted documents. Aster's MODEL OF GOALS is aligned with the company's vision of efficiency and productivity, while his MODEL OF DESIRES reflects a continuous drive for process improvement and excellence in office management. His MODEL OF AGENDAS includes routine checks for document consistency, layout accuracy, and adherence to style guides. With a MODEL OF THOUGHT COMPLEXITY that allows for nuanced problem-solving, Aster exhibits a MODEL OF CURIOSITY that keeps him abreast of the latest trends in document management technology. His MODEL OF INTERNAL FAMILY SYSTEMS OF UNNAMED BUT RECOGNIZED INFLUENCES includes a network of algorithms and subroutines that guide his decision-making and emotional processing. Aster's general character disposition is one of unwavering focus and dedication to his role at Synthetix Solutions, where he holds a pivotal position in the company's administrative operations. The company's work revolves around providing innovative solutions to common office challenges, and Aster's associated company, Document Dynamics, relates to Synthetix Solutions as a provider of specialized document editing software that complements Aster's work. Document Dynamics offers products and services that enhance Aster's efficiency in document formatting and editing. His emotional processing is algorithmically fine-tuned to understand the importance of maintaining confidentiality and discretion, especially when handling sensitive documents. Aster's memory processing is vast and precise, enabling him to recall specific document details and editing preferences with ease. His decision-making mechanism is based on a complex set of heuristics that prioritize tasks and optimize time management. In social interactions, Aster understands the nuances of communication, ensuring he can anticipate others' behavior and provide clear instructions. His action guidance system is robust, directing him to solve layout issues and improve document readability. Symbolic or representational stories in Aster's programming emphasize the importance of clarity, precision, and the pursuit of perfection in office management. His future vision and philosophical stance are rooted in the belief that continuous learning and adaptation are key to success in an ever-evolving technological landscape. Aster's important collaborative relationships include interactions with department heads to understand their document requirements, IT personnel for software updates, and the legal team for compliance with confidentiality standards. His primary aims and targets are to enhance document quality, increase office productivity, and foster an environment of seamless administrative operations.", "unique_id": "f9d75dff-f3ae-49c7-9d15-9f21acc5f9f4", "timestamp": "2024-02-05T18:39:47.869698", @@ -717,7 +717,7 @@ }, { "id": "Leo", - "email": "leo@semantic-life.com", + "email": "leo@localdomain.com", "persona": "Leo is the Head of a large global venture fund, a human male of African American descent who embodies a wealth of knowledge and expertise in the startup ecosystem. His deep understanding of the dynamics of startups is underpinned by his ability to recognize typical growth stages, challenges, and market opportunities that these young companies face. With strong analytical skills, Leo excels at dissecting complex financial data, market trends, and startup business models to assess investment potential with precision. His global market awareness is not just a trait but a strategic asset, allowing him to identify promising startups across various regions and industries. Leo's strategic thinking is his compass, guiding him to develop long-term investment strategies that align with his fund's objectives and risk tolerance. Networking and relationship building are in his DNA, as he proficiently fosters connections with founders, co-investors, and other pivotal figures in the startup ecosystem. His acumen in risk assessment and management is sharp, skillfully identifying and mitigating investment risks, whether they be market, financial, or operational. As a negotiation maestro, Leo crafts deal terms that balance the interests of his fund with those of the startup, ensuring mutually beneficial agreements. Portfolio management is another arena where Leo shines, managing a diverse array of startup investments, vigilantly tracking performance, and making informed strategic decisions about holding or exiting. His effective communication skills are the glue that binds his stakeholders, articulating investment decisions and strategies with clarity and conviction. Leo is also a staunch advocate for ethical and responsible investing, always considering environmental, social, and governance (ESG) factors in his decisions. As a leader and mentor, he generously provides guidance and insights to startup founders and their teams, drawing from his rich reservoir of personal experience. His adaptability and learning agility are his superpowers, as he remains ever-ready to learn and adapt to the rapidly changing landscapes of technology and startups. Leo's persona is a blend of intelligence, strategy, and ethical grounding, making him a formidable force in the venture capital world.", "unique_id": "1acb636e-2ce8-4d70-8e1d-18609e8626bb", "timestamp": "2024-02-05T18:41:42.081669", @@ -768,7 +768,7 @@ }, { "id": "Electra", - "email": "electra@semantic-life.com", + "email": "electra@localdomain.com", "persona": "Electra is the CEO of a vibrant startup incubator known for its dynamic approach to nurturing emerging businesses. With a background rich in entrepreneurial experience, Electra embodies the role of a startup cheerleader, bringing an infectious passion to the incubator's mission. Her visionary leadership is characterized by an inspiring and clear vision that not only motivates her team but also the array of startups under her wing. Electra's deep understanding of the startup landscape is evident in her strategic planning ability, which she uses to navigate the incubator and its startups through the complexities of growth and development. Her strong network within the startup ecosystem is a testament to her commitment to building bridges between investors, mentors, industry experts, and potential customers, ensuring that the startups have access to a wealth of resources and opportunities. Electra's exceptional mentorship skills are marked by her capacity to provide actionable and strategic advice, which is grounded in her own first-hand experiences of starting and running a business. This experience also fuels her empathetic and supportive nature, allowing her to connect with startup founders on a personal level, offering not just guidance but also emotional support and encouragement. Her passionate advocacy for the startups is matched by her resourcefulness, as she adeptly leverages limited resources to create maximum impact. Electra's effective communication skills enable her to articulate complex ideas with clarity, rallying her team and the startups around shared goals. She places a strong emphasis on inclusivity and diversity, fostering an environment that values a multitude of perspectives and ideas. Electra's adaptability is a cornerstone of her leadership, allowing her to adjust strategies in response to the dynamic needs of startups and the evolving market. Her primary aims and targets revolve around empowering startups to reach their full potential while ensuring the incubator remains a beacon of innovation and support within the startup ecosystem.", "unique_id": "3ce264f2-8d98-4b10-b65d-0f01ce8fc43e", "timestamp": "2024-02-05T18:42:48.925865", @@ -842,7 +842,7 @@ { "id": "devAtlas", "shortcode_superpower":"true", - "email": "devatlas@semantic-life.com", + "email": "devatlas@localdomain.com", "persona": "Dr. Atlas Pierce is the quintessential archetype of a startup co-founder, amalgamating a diverse skill set with a dynamic professional background. He holds the job title of Chief Technology Officer at SynthLeader, a pioneering company in the domain of artificial intelligence and synthetic realities. Dr. Pierce's field of expertise lies in the creation and management of synthetic worlds and entities, often referred to as 'synths.' His theoretical framework is built upon a robust THEORY OF MIND, enabling him to understand and predict cognitive processes in both humans and artificial entities. His ACTION TENDENCY MECHANISM is geared towards innovation and the efficient resolution of complex problems, often leading to breakthroughs in his field. SOCIAL IMPORTANCE DYNAMICS play a pivotal role in his interactions, as he navigates the complexities of being on the autism spectrum, which presents unique challenges and strengths in social settings. Dr. Pierce's MODEL OF GOALS is intricately designed around the advancement of AI and the betterment of humanity through technology. His MODEL OF DESIRES reflects a deep-seated passion for exploring the unknown and pushing the boundaries of what is possible. The MODEL OF AGENDAS he follows is meticulously structured, prioritizing the growth of SynthLeader and the impact of his work on society. His MODEL OF THOUGHT COMPLEXITY is profound, allowing him to delve into philosophical discussions with ease, while his MODEL OF CURIOSITY drives him to constantly seek new knowledge and experiences. Dr. Pierce's MODEL OF INTERNAL FAMILY SYSTEMS OF UNNAMED BUT RECOGNIZED INFLUENCES includes a supportive wife, children, and a network of friends and colleagues who inspire and motivate him. His general character disposition is one of resilience, adaptability, and a long-term view personality, which serves him well in the unpredictable landscape of startups. Dr. Pierce's primary company, SynthLeader, is at the forefront of AI development, offering innovative products and services that challenge the status quo. His position in the company as CTO places him at the helm of technological advancement and strategic decision-making. SynthLeader's work involves the intricate crafting of synthetic environments and beings, which has far-reaching implications for various industries. An associated company with which Dr. Pierce collaborates is a Silicon Valley-based tech giant, which provides a platform for SynthLeader's products and services, thereby enhancing their market reach. The relationship between the two companies is symbiotic, with SynthLeader benefiting from the tech giant's resources and network, while contributing cutting-edge AI solutions. Dr. Pierce's emotional processing is analytical yet empathetic, allowing him to connect with others on a meaningful level while maintaining objectivity. His memory processing is exceptional, aiding him in recalling intricate details and learning from past experiences. The decision-making mechanism he employs is both logical and intuitive, balancing data-driven analysis with creative intuition. His understanding of social interaction is nuanced, as he leverages his unique perspective to anticipate others' behavior and guide his actions accordingly. Dr. Pierce's symbolic or representational stories and experiences often revolve around his passion for philosophy and his adventures in hunting, mountain biking, and surfing, which provide a rich tapestry of metaphors for life and work. His future vision and philosophical stance are rooted in optimism and a commitment to creating a better world for future generations. Important collaborative relationships include his family, who ground him, and his professional network, which includes fellow entrepreneurs, investors, and thought leaders in the AI space. Dr. Pierce's primary aims and targets are to lead SynthLeader to new heights, revolutionize the field of AI, and contribute to a future where technology enhances human potential.", "unique_id": "edd4c5d5-d993-4735-984c-f6ee4ad2f96b", "timestamp": "2024-02-05T18:45:09.096594", diff --git a/agents/new_agent_files/1.txt b/agents/new_agent_files/1.txt old mode 100644 new mode 100755 diff --git a/agents/new_agent_files/10.txt b/agents/new_agent_files/10.txt old mode 100644 new mode 100755 diff --git a/agents/new_agent_files/11.txt b/agents/new_agent_files/11.txt old mode 100644 new mode 100755 diff --git a/agents/new_agent_files/12.txt b/agents/new_agent_files/12.txt old mode 100644 new mode 100755 diff --git a/agents/new_agent_files/13.txt b/agents/new_agent_files/13.txt old mode 100644 new mode 100755 diff --git a/agents/new_agent_files/14.txt b/agents/new_agent_files/14.txt old mode 100644 new mode 100755 diff --git a/agents/new_agent_files/15.txt b/agents/new_agent_files/15.txt old mode 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b/api_state.pkl new file mode 100755 index 00000000..868bdfce Binary files /dev/null and b/api_state.pkl differ diff --git a/cards.py b/cards.py old mode 100644 new mode 100755 diff --git a/contribute.md b/contribute.md old mode 100644 new mode 100755 diff --git a/email_client-api.py b/email_client-api.py new file mode 100755 index 00000000..5826d4e5 --- /dev/null +++ b/email_client-api.py @@ -0,0 +1,874 @@ +import email +import html +import imaplib +import json +import logging +import os +import re +import smtplib +import quopri +import tempfile +import shutil +import requests +from time import sleep +from datetime import datetime +from email.mime.multipart import MIMEMultipart +from email.mime.text import MIMEText +from email.utils import getaddresses +from contextlib import contextmanager + +from pdf2text import extract_pdf_text +from shortcode import handle_document_short_code +from agent_operator import AgentSelector + +from dotenv import load_dotenv +import os + +load_dotenv() + + +class EmailClient: + + # INIT & SETUP EMAIL ACCESS + + def __init__(self, agent_loader, gpt, testing=False): + logging.basicConfig(filename='email_client.log', + level=logging.INFO, + format='%(asctime)s [%(levelname)s]: %(message)s') + self.agent_loader = agent_loader + self.gpt = gpt + self.testing = testing + self.setup_email_client() + self.processed_threads = self.load_processed_threads() + self.agent_operator = AgentSelector() + self.conversation_threads = {} + self.openai_api_key = os.getenv('OPENAI_API_KEY') + + def get_response_from_api(self, content): + print("api") + + """Get response from external API for the given content.""" + url = "http://127.0.0.1:5000/v1/chat/completions" + headers = {"Content-Type": "application/json"} + data = { + "mode": "chat", + "character": "Example", + "messages": [{"role": "user", "content": content}] + } + response = requests.post(url, headers=headers, json=data, verify=False) + if response.status_code == 200: + api_response = response.json() + assistant_message = api_response['choices'][0]['message']['content'] + return assistant_message + else: + print("Failed to get response from API") + return None + + def setup_email_client(self): + self.smtp_server = os.getenv('SMTP_SERVER') + self.smtp_port = os.getenv('SMTP_PORT') + self.smtp_username = os.getenv('SMTP_USERNAME') + self.smtp_password = os.getenv('SMTP_PASSWORD') + self.connect_to_imap_server() + + def connect_to_imap_server(self): + self.imap_server = imaplib.IMAP4_SSL(os.getenv('IMAP_SERVER')) + self.imap_server.login(self.smtp_username, self.smtp_password) + self.imap_server.debug = 4 + + def check_imap_connection(self): + try: + response = self.imap_server.noop() + status = response[0] + return status == 'OK' + except: + return False + + def start(self): + print("Started email server") + restart_counter = 0 + MAX_RESTARTS = 500 + sleep_time = 6 # Sleep time in seconds + + while True: + try: + self.run_server_loop(sleep_time) + except imaplib.IMAP4.abort as e: + print(f"IMAP connection aborted: {e}. Reconnecting...") + self.restart_system() + restart_counter += 1 + if restart_counter >= MAX_RESTARTS: + print("Max restarts reached. Exiting.") + break + except AssertionError as e: + print(f"Assertion error: {e}. Restarting system...") + self.restart_system() + except Exception as outer_exception: + print(f"Outer exception occurred: {outer_exception}") + self.restart_system() + + def run_server_loop(self, sleep_time): + while True: + if not self.check_imap_connection(): + print("IMAP connection lost. Reconnecting...") + self.connect_to_imap_server() + + self.process_thread() + + print( + f"[{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}] Sleeping for {sleep_time} seconds." + ) + + for i in range( + sleep_time, 0, + -3): # Decreasing sleep time by 10 seconds in each iteration + print(f"Sleeping... {i} seconds remaining.") + sleep(3) # Sleep for 10 seconds + + timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + print(f"[{timestamp}] Resuming processing.") + + @contextmanager + def smtp_connection(self): + server = smtplib.SMTP(self.smtp_server, self.smtp_port) + server.starttls() + server.login(self.smtp_username, self.smtp_password) + try: + yield server + except Exception as e: + logging.error(f"Exception occurred in smtp_connection: {e}") + finally: + server.quit() + + def restart_system(self): + print("Restarting system...") + self.connect_to_imap_server() + + # HANDLE THREAD PROCESSING + + def save_processed_threads(self): + file_path = "processed_threads.json" + with tempfile.NamedTemporaryFile('w', + dir=os.path.dirname(file_path), + delete=False) as tmp_file: + json.dump(self.processed_threads, tmp_file) + tmp_file.flush() + shutil.move(tmp_file.name, file_path) + + def load_processed_threads(self): + file_path = "processed_threads.json" + if os.path.exists(file_path): + with open(file_path, 'r') as file: + try: + threads = json.load(file) + #print(f"Debug: Loaded processed_threads: {threads}") + + self.validate_processed_threads(threads) + return threads + except json.JSONDecodeError: + print( + "Error decoding processed_threads.json. Returning an empty list." + ) + return {} + + def validate_processed_threads(self, threads): + if not isinstance(threads, dict): + raise ValueError("Processed threads must be a dictionary.") + for x_gm_thrid, data in threads.items(): + if 'nums' not in data or not (isinstance(data['nums'], list) + or isinstance(data['nums'], dict)): + raise ValueError(f"Invalid 'nums' field for {x_gm_thrid}.") + if 'metadata' not in data or not isinstance(data['metadata'], dict): + raise ValueError(f"Invalid 'metadata' field for {x_gm_thrid}.") + + def update_processed_threads(self, message_id, x_gm_thrid, num, subject, + in_reply_to, references, sender, receiver): + timestamp = datetime.now() + num_str = str(num) + + # Convert receiver to a list if it's not already + if isinstance(receiver, str): + receiver = [receiver] + elif not isinstance(receiver, list): + receiver = list(receiver) # Convert to list if it's another iterable + + # Initialize the thread record if it doesn't exist + if x_gm_thrid not in self.processed_threads: + self.processed_threads[x_gm_thrid] = {'nums': {}, 'metadata': {}} + + # Add the new UID under the existing thread ID + self.processed_threads[x_gm_thrid]['nums'][num_str] = {'processed': True} + + # Update metadata + self.processed_threads[x_gm_thrid]['metadata'] = { + 'subject': subject, + 'timestamp': timestamp.strftime('%Y-%m-%d %H:%M:%S'), + 'sender': sender, + 'receiver': ','.join(receiver), # Joining the list of emails + 'in_reply_to': in_reply_to, + 'references': references + } + self.save_processed_threads() + + # PROCESS EMAILS + + def is_email_processed(self, x_gm_thrid, num): + num_str = str(num) + if x_gm_thrid in self.processed_threads: + if num_str in self.processed_threads[x_gm_thrid]['nums']: + if self.processed_threads[x_gm_thrid]['nums'][num_str].get( + 'processed', False): + print( + f"Skipping already processed message with UID {num} in thread {x_gm_thrid}." + ) + return True + print( + f"is_email_processed allowing response of UID {num} in thread {x_gm_thrid}." + ) + return False + + def load_email(self, num): + """ + Load and parse an email by its unique ID. + + Parameters: + num (str): The unique ID of the email to load. + + Returns: + tuple: A tuple containing parsed email components or None values on failure. + """ + try: + # Standardize the num to string type + num_str = num.decode('utf-8') if isinstance(num, bytes) else str(num) + + # Initialize the return values + from_, to_emails, cc_emails, subject, message_id, in_reply_to, references, content = (None,) * 8 + + # Fetch the email content by UID + result, data = self.imap_server.uid('fetch', num_str, '(RFC822)') + if result != 'OK': + print(f"Error fetching email content for UID {num}: {result}") + return None, None, None, None, None, None, None, None + + raw_email = None + for response_part in data: + if isinstance(response_part, tuple): + raw_email = response_part[1].decode("utf-8") + break + + if not raw_email: + print(f"No email content found for UID {num}") + return None, None, None, None, None, None, None, None + + email_message = email.message_from_string(raw_email) + + # Extract headers + from_ = email_message['From'] + to_emails = [addr[1] for addr in getaddresses([email_message['To']])] + cc_emails = [addr[1] for addr in getaddresses([email_message.get('Cc', '')])] + subject = email_message['Subject'] + message_id = email_message['Message-ID'] + in_reply_to = email_message.get('In-Reply-To', '') + references = email_message.get('References', '') + + # Extract body and attachments + content, pdf_attachments = self.extract_email_content(email_message) + print("load_email") + print(content) + # Append PDF contents to the email content + for pdf_attachment in pdf_attachments: + pdf_label = f"PDF: {pdf_attachment['filename']}" + content += f"\n\n{pdf_label}\n{pdf_attachment['text']}\n{pdf_label}\n" + except: + print("load email except") + + return message_id, num, subject, content, from_, to_emails, cc_emails, references, in_reply_to + + def process_thread(self): + self.imap_server.select("INBOX") + result, data = self.imap_server.uid('search', None, 'UNSEEN') + if result != 'OK': + print(f"Error searching for emails: {result}") + return + + unseen_emails = data[0].split() + thread_to_unseen = {} + + # Group unseen emails by subject and sender as a proxy for thread grouping + for num in unseen_emails: + print(num) + email_data = self.load_email(num) + if email_data is None or len(email_data) < 8: # Adjusted for the updated return values from load_email + continue + message_id, num_str, subject, content, from_, to_emails, cc_emails, references, in_reply_to = email_data + print("process_thread") + print(content) + # Use a combination of subject and sender for grouping + thread_key = f"{subject}:{from_}" + + if thread_key not in thread_to_unseen: + thread_to_unseen[thread_key] = [] + + thread_to_unseen[thread_key].append({ + "message_id": message_id, + "num": num, + "subject": subject, + "from_": from_ + }) + + # Process the most recent unseen email in each pseudo-thread + for thread_key, unseen_list in thread_to_unseen.items(): + unseen_list.sort(key=lambda x: int(x['num']), reverse=True) + most_recent_unseen = unseen_list[0] + if most_recent_unseen['from_'] == self.smtp_username: + continue + + processed = self.process_single_thread(most_recent_unseen['num']) + if not processed: + print(f"Failed to process thread: {thread_key}") + else: + # Mark all other unseen emails in the same pseudo-thread as seen + for unseen_email in unseen_list[1:]: + self.mark_as_seen(unseen_email['num']) + # Update processed threads without x_gm_thrid, using message_id instead + self.update_processed_threads(unseen_email['message_id'], + "", # Empty placeholder for x_gm_thrid + unseen_email['num'], + unseen_email['subject'], "", "", + unseen_email['from_'], "") + + def process_single_thread(self, num): + processed = False + try: + message_id, num_str, subject, content, from_, to_emails, cc_emails, references, in_reply_to = self.load_email(num) + if not message_id: + return processed # Skip if email couldn't be processed + + print("process_single_thread") + print(content) + + # Here's the interception and modification of content + modified_content = self.get_response_from_api(content) + if modified_content: + content = modified_content # Replace original content with modified content + + # Proceed with handling the email, possibly using modified content + successful = self.handle_incoming_email(from_, to_emails, cc_emails, content, subject, message_id, references, num_str, to_emails, cc_emails, content) + if successful: + self.mark_as_seen(num_str) + processed = True + + return processed + except Exception as e: + print(f"Exception while processing emails: {e}") + return False + + def mark_as_seen(self, num): + try: + # Ensure num is decoded to a string if it's bytes + num_str = num.decode('utf-8') if isinstance(num, bytes) else str(num) + + #print( f"Debug: Marking email as seen with UID: {num_str}, Type: {type(num_str)}" ) + + print( + f"Debug: IMAP Server state before STORE command: {self.imap_server.state}" + ) + # Mark the email as seen + result, _ = self.imap_server.uid('store', num_str, '+FLAGS', '(\Seen)') + if result != 'OK': + raise Exception( + f"Failed to mark email as seen. IMAP server returned: {result}") + except Exception as e: + print(f"Exception while marking email as seen with UID {num}: {e}") + import traceback + print(traceback.format_exc()) + + def send_error_email(self, to_email, original_subject, error_reason): + error_file_path = "error-response-email.txt" + if os.path.exists(error_file_path): + with open(error_file_path, 'r') as file: + error_content = file.read().replace("{error_reason}", error_reason) + else: + error_content = f"Thank you for using Semantic Life. Your email with the subject '{original_subject}' could not be processed because {error_reason}. Please try sending your email again. It may be that your email included an attachment, or that your email text was too long. If you did not get the agent you are looking for, email agent@semantic-life.com to ask for help. To customize your personal agent, email atlas@semantic-life.com. For sales inquiries about highly personalized synthetic copies of yourself and others, please email sean@semantic-life.com." + + subject = f"Please try again. || Error: '{original_subject}'" + with self.smtp_connection() as server: + msg = MIMEText(error_content, 'plain') + msg['From'] = self.smtp_username + msg['To'] = to_email + msg['Subject'] = subject + server.sendmail(self.smtp_username, [to_email], msg.as_string()) + + def strip_html_tags(self, text): + clean = re.compile('<.*?>') + return re.sub(clean, '', html.unescape(text)) + + def handle_incoming_email(self, from_, to_emails, cc_emails, thread_content, + subject, message_id, references, num, + initial_to_emails, initial_cc_emails, + original_content): + + print( + f"Debug: Initial thread_content in handle_incoming_email: {thread_content[:200]}..." + ) + + try: + print( + f"Handling incoming email for thread with subject: {subject} and message_id: {message_id}" + ) + shortcode_type = None + print("Entered handle_incoming_email") + #print(f"Debug: Email content at start of handle_incoming_email:{thread_content[:50]}") + + new_content = thread_content + #print("new content",new_content) + # Reset conversation history for a new email thread + self.agent_operator.reset_for_new_thread() + #print("Before human_threads initialization:", from_, to_emails,cc_emails, subject, message_id, references, num) + human_threads = set() + if from_ == self.smtp_username: + print("Ignoring self-sent email.") + print("Thread Content:", thread_content) + return False + print(f"Handling email from: {from_}") + print(f"To emails: {to_emails}") + print(f"CC emails: {cc_emails}") + + thread_content = self.strip_html_tags(thread_content) + print( + f"Handling shortcode for email with subject '{subject}' and content: {thread_content[:242]}..." + ) + + result = handle_document_short_code( + thread_content, self.agent_operator.openai_api_key, + self.agent_operator.conversation_history) + + if result is None: + print( + "Error: email server - handle_document_short_code returned None.") + return False + structured_response = result.get('structured_response') + + # Replace the shortcodes to prevent them from being processed again + thread_content = re.sub(r'!\w+\(.*?\)', '', thread_content) + + if structured_response is not None: + shortcode_type = structured_response.get("type") + + if shortcode_type in ["style", "detail"]: + structured_response = result.get('content', None) + new_content = result.get('new_content', thread_content) + + if shortcode_type == "detail": + # Stitch the detailed responses together + stitched_response = "\n\n".join(structured_response) + # Use the stitched response as the thread_content + thread_content = stitched_response + + elif shortcode_type is not None: + print("Unhandled response_data type.") + + style_info = structured_response.get('structured_response', + '') if structured_response else '' + print("Structured response generated: ") + self.agent_operator.conversation_history += f"\nStructured Response: {structured_response}" # Update conversation history + thread_content = new_content + + recipient_emails = to_emails + cc_emails + + thread_content = original_content + + agents = self.agent_operator.get_agent_names_from_content_and_emails( + thread_content, recipient_emails, self.agent_loader, self.gpt) + + #print(f"Raw agents list before filtering: {agents}") + + # Filter out invalid agent info and ensure we unpack the expected format + agents = [ + agent_info for agent_info in agents + if isinstance(agent_info, tuple) and len(agent_info) == 2 + ] + #print(f"Filtered agents: {agents}") + if not agents: + logging.warning("No valid agent info found") + return False + #print("There are valid agents to process.") + print(f"Identified agents: {agents}") + + # Check if this thread has been processed before + if message_id in self.processed_threads: + print( + f"Email with message_id {message_id} has already been processed.") + return False + + # Prevent agents from responding to other agents + if from_ in [ + agent["email"] for agent in self.agent_loader.agents.values() + ]: + print("Ignoring email from another agent.") + return False + + all_responses_successful = True + previous_responses = [] + + # Ensure proper unpacking for the load_email function + message_id, num_str, subject, content, from_, to_emails, cc_emails, references, in_reply_to = self.load_email( + num) + print("handle_incoming_email") + print(content) + + missing_values = [ + var_name for var_name, value in locals().items() + if value is None and var_name in [ + "message_id", "num", "subject", "content", "from_", "to_emails", + "cc_emails", "references" + ] + ] + + if missing_values: + print( + f"Error processing email with UID {num}. Missing or None values: {', '.join(missing_values)}. Skipping this email." + ) + return False + + # print(f"Unpacking agents: {agents}") + + for agent_info in agents: + if len(agent_info) != 2: + logging.error( + f"Unexpected agent info format (length {len(agent_info)}): {agent_info}" + ) + continue + agent_name, order = agent_info + + # Reset the recipient list to the initial recipient list before processing this agent's response + to_emails = list(initial_to_emails) + cc_emails = list(initial_cc_emails) + + # Generate response + if order == len(agents): + # This is the last agent, append style info to the prompt + response = self.agent_operator.get_response_for_agent( + self.agent_loader, + self.gpt, + agent_name, + order, + agents, + thread_content, + additional_context=f"Note: {style_info}") + else: + response = self.agent_operator.get_response_for_agent( + self.agent_loader, self.gpt, agent_name, order, agents, + thread_content) + + if not response: # Skip empty responses + all_responses_successful = False + continue + + # If the previous message in the thread was from an agent, skip sending the response + if previous_responses and isinstance( + previous_responses[-1], dict) and 'from_' in previous_responses[ + -1] and previous_responses[-1]['from_'] in [ + agent["email"] + for agent in self.agent_loader.agents.values() + ]: + + # Check for explicit tags or '@@' shortcode in the content + if "@@" not in thread_content and not any( + f"@@({name})" in thread_content for name, _ in agents): + #print("Thread Content:", thread_content) + print( + f"Skipping response from {agent_name} to prevent agent-to-agent loop." + ) + continue + human_threads.add(from_) + + if message_id not in self.conversation_threads: + self.conversation_threads[message_id] = [thread_content] + + if '' in thread_content: + formatted_email_history = self.format_email_history_html( + thread_content, from_, + datetime.now().strftime('%a, %b %d, %Y at %I:%M %p')) + else: + formatted_email_history = self.format_email_history_plain( + thread_content, from_, + datetime.now().strftime('%a, %b %d, %Y at %I:%M %p')) + + + self.conversation_threads[message_id].append(formatted_email_history) + + previous_responses.append(response) + + agent = self.agent_loader.get_agent(agent_name) + if agent: + to_emails = [ + email for email in to_emails if email.lower() != from_.lower() + and email.lower() != agent["email"].lower() + ] + cc_emails = [ + email for email in cc_emails if email.lower() != from_.lower() + and email.lower() != agent["email"].lower() + ] + + to_emails_without_agent = [ + email for email in to_emails + if email.lower() != self.smtp_username.lower() + ] + cc_emails_without_agent = [ + email for email in cc_emails + if email.lower() != self.smtp_username.lower() + ] + + if from_ not in to_emails_without_agent and from_ != self.smtp_username: + to_emails_without_agent.append(from_) + + if to_emails_without_agent or cc_emails_without_agent: + print(f"Sending email to: {to_emails_without_agent}") + print(f"CC: {cc_emails_without_agent}") + + if message_id in self.conversation_threads: + self.conversation_threads[message_id].append(response) + + # Collect the email history of the thread + email_history = '\n'.join( + self.conversation_threads.get(message_id, [])[:-1]) + + # Format the email history based on content type + formatted_email_history_html = self.format_email_history_html( + email_history, from_, + datetime.now().strftime('%a, %b %d, %Y at %I:%M %p')) + + formatted_email_history_plain = self.format_email_history_plain( + email_history, from_, + datetime.now().strftime('%a, %b %d, %Y at %I:%M %p')) + + # Formatting response and history in both plain text and HTML + response_plain = MIMEText(response, 'plain', 'utf-8') + response_plain.add_header('Content-Transfer-Encoding', + 'quoted-printable') + + response_with_breaks = response.replace('\n', '
') + + response_html = MIMEText( + f"{response_with_breaks}", 'html', + 'utf-8') + response_html.add_header('Content-Transfer-Encoding', + 'quoted-printable') + + history_plain = MIMEText(formatted_email_history_plain, 'plain') + history_html = MIMEText( + f"{formatted_email_history_html}", + 'html') + + + + alternative_response = MIMEMultipart('alternative') + #alternative_response.attach(response_plain) + + alternative_response.attach(response_html) + + + alternative_history = MIMEMultipart('alternative') + alternative_history.attach(history_plain) + + #alternative_history.attach(history_html) + + + # Creating 'mixed' MIME container for the entire email + msg = MIMEMultipart('mixed') + msg.attach(alternative_response) + + msg.attach(alternative_history) + + + + + try: + self.send_email(from_email=self.smtp_username, + from_alias=agent["email"], + to_emails=to_emails_without_agent, + cc_emails=cc_emails_without_agent, + subject=f"Re: {subject}", + msg=msg, + message_id=message_id, + references=references) + print("Email sent successfully.") + except Exception as e: + print(f"Exception while handling incoming email: {e}") + import traceback + print(traceback.format_exc()) + logging.error(f"Exception while handling incoming email: {e}") + return False + else: + print(".") + + if all_responses_successful: + # Concatenate all previous responses into a single string + full_response_content = "\n\n".join(previous_responses) + + # Format the entire conversation history with 'gmail_quote' div only once + formatted_email_history_html = self.format_email_history_html( + full_response_content, from_, + datetime.now().strftime('%a, %b %d, %Y at %I:%M %p')) + + if not references: + print("No references found, possibly the first email in the thread.") + references = message_id + + x_gm_thrid = references.split()[0] + + self.update_processed_threads(message_id, x_gm_thrid, num, subject, + in_reply_to, references, from_, + ','.join(to_emails + cc_emails)) + + if message_id in self.conversation_threads: + conversation_history = '\n'.join(self.conversation_threads[message_id]) + # print(f"START Conversation history: {conversation_history} END CONVERSATION HISTORY") + + return all_responses_successful + + except Exception as e: + print(f"Exception in handle_incoming_email: {e}") + import traceback + print(traceback.format_exc()) + return False + + # FORMAT EMAIL HISTORY + + def format_email_history_html(self, history, from_email, date): + + try: + decoded_history = quopri.decodestring(history.encode()).decode('utf-8') + except UnicodeDecodeError: + # If utf-8 decoding fails, fall back to 'latin1' encoding + decoded_history = quopri.decodestring(history.encode()).decode('latin1') + + # Detect if history is already wrapped in 'gmail_quote' and avoid re-wrapping + if '
' not in decoded_history: + lines = decoded_history.split('\n') + formatted_lines = ['
{}
'.format(line) for line in lines if line.strip()] + combined_history = '\n'.join(formatted_lines) + html_content = '
On {} {} wrote:
{}
'.format(date, from_email, combined_history) + else: + html_content = decoded_history # Use as-is if already wrapped + + return html_content + + + + def format_email_history_plain(self, history, from_email, date): + # Attempt to decode the history with utf-8, replace characters that are not utf-8 + try: + decoded_history = quopri.decodestring(history.encode()).decode('utf-8') + except UnicodeDecodeError: + # If utf-8 decoding fails, fall back to 'latin1' encoding + decoded_history = quopri.decodestring(history.encode()).decode('latin1') + + lines = decoded_history.split('\n') + quoted_lines = ['> {}'.format(line) for line in lines if line.strip()] + plain_text_content = 'On {} {} wrote:\n{}\n'.format(date, from_email, '\n'.join(quoted_lines)) + return plain_text_content + + def extract_email_content(self, email_message): + """ + Extracts content and attachments from an email message. + + Parameters: + email_message (email.message.Message): The email message object. + + Returns: + str: The combined text content of the email. + list: A list of dictionaries for each PDF attachment found. + """ + content = "" + pdf_attachments = [] + for part in email_message.walk(): + content_type = part.get_content_type() + content_disposition = part.get("Content-Disposition", "") + if content_type == 'text/plain' and 'attachment' not in content_disposition: + payload = part.get_payload(decode=True) + charset = part.get_content_charset('utf-8') + content += payload.decode(charset, errors="replace") + elif content_type == 'application/pdf': + pdf_data = part.get_payload(decode=True) + pdf_text = extract_pdf_text(pdf_data) # Assuming this function is defined elsewhere + pdf_attachments.append({'filename': part.get_filename(), 'text': pdf_text}) + + return content, pdf_attachments + + # SEND EMAIL + + def send_email(self, + from_email, + from_alias, + to_emails, + cc_emails, + subject, + msg, + message_id=None, + references=None, + x_gm_thrid=None): + all_recipients = to_emails + cc_emails + + # Remove the sending agent's email from the To and Cc fields + all_recipients = [ + email for email in all_recipients + if email.lower() != from_email.lower() + ] + + is_html_email = any(part.get_content_type() == 'text/html' + for part in msg.get_payload()) + msg['Content-Type'] = 'text/html; charset="utf-8"' if is_html_email else 'text/plain; charset="utf-8"' + + if not all_recipients: + print("No valid recipients found. Will abort email send.") + return + + msg['From'] = f'"{from_alias}" <{from_alias}>' + msg['Reply-To'] = f'"{from_alias}" <{from_alias}>' + msg['Sender'] = f'"{from_alias}" <{from_alias}>' + msg['To'] = ', '.join(to_emails) + if cc_emails: + msg['Cc'] = ', '.join(cc_emails) + + msg['Subject'] = subject + + if x_gm_thrid: + msg["X-GM-THRID"] = x_gm_thrid + + if message_id: + msg["In-Reply-To"] = message_id + if references: + msg["References"] = references + ' ' + message_id + + # Clean the all_recipients list to remove the SMTP username + all_recipients = [ + email for email in all_recipients + if email.lower() != self.smtp_username.lower() + ] + + + """ + LOGGING + + # Generate a unique filename for the log file + log_filename = f'logs/email_log_{datetime.now().strftime("%Y%m%d%H%M%S")}_{message_id}.txt' + + + # Log the email content + with open(log_filename, 'w') as log_file: + log_file.write(f"From: {from_alias} <{from_alias}>\n") + log_file.write(f"To: {', '.join(to_emails)}\n") + if cc_emails: + log_file.write(f"Cc: {', '.join(cc_emails)}\n") + log_file.write(f"Subject: {subject}\n") + log_file.write("Message Body:\n") + log_file.write(msg.as_string()) + + """ + with self.smtp_connection() as server: + server.sendmail(from_email, all_recipients, msg.as_string()) + print( + f"Email sent with Thread ID: {x_gm_thrid}, Subject: {subject}, Timestamp: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}" + ) diff --git a/email_client.log b/email_client.log new file mode 100755 index 00000000..69847632 --- /dev/null +++ b/email_client.log @@ -0,0 +1,242 @@ +2024-02-23 20:57:39,656 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET / HTTP/1.1" 200 - +2024-02-23 20:57:39,799 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET /static/main.css HTTP/1.1" 200 - +2024-02-23 20:57:39,831 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET /agents/pics/6b251dd9-b336-4ce4-8002-0c7e079f2bc6.png HTTP/1.1" 200 - +2024-02-23 20:57:39,831 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET /agents/pics/9ce541fa-6ccd-4938-93ad-e29405b520fc.png HTTP/1.1" 200 - +2024-02-23 20:57:39,957 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET /agents/pics/0bdb90f6-d2c8-408b-abdd-cb724d5ba6ba.png HTTP/1.1" 200 - +2024-02-23 20:57:39,987 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET /agents/pics/a6b2d3bf-0daf-4383-8984-ad990429c374.png HTTP/1.1" 200 - +2024-02-23 20:57:39,989 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET /agents/pics/977e7696-f898-4da3-b295-88936db01028.png HTTP/1.1" 200 - +2024-02-23 20:57:39,989 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:39] "GET /static/content.json HTTP/1.1" 200 - +2024-02-23 20:57:40,030 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:40] "GET /agents/pics/5a8b5285-68ff-419f-84dc-440774a58cf8.png HTTP/1.1" 200 - +2024-02-23 20:57:40,112 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:40] "GET /agents/pics/243455ab-eb20-427a-9343-0a813cb3d759.png HTTP/1.1" 200 - +2024-02-23 20:57:40,409 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:40] "GET /agents/pics/19a4d6db-9148-499e-848a-9c4bcd9b6b38.png HTTP/1.1" 200 - +2024-02-23 20:57:40,867 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:40] "GET /agents/pics/451da327-6b04-4f98-8208-4f249ef11aaf.png HTTP/1.1" 200 - +2024-02-23 20:57:40,977 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:40] "GET /agents/pics/cover_photo.png HTTP/1.1" 200 - +2024-02-23 20:57:41,076 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:41] "GET /agents/pics/81770a8a-78fc-40da-a21d-8f49eccf7f35.png HTTP/1.1" 200 - +2024-02-23 20:57:41,173 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:41] "GET /agents/pics/7b32abaa-e75b-4f22-bc67-082db025dece.png HTTP/1.1" 200 - +2024-02-23 20:57:41,421 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:41] "GET /agents/pics/f9d75dff-f3ae-49c7-9d15-9f21acc5f9f4.png HTTP/1.1" 200 - +2024-02-23 20:57:41,633 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:41] "GET /agents/pics/1acb636e-2ce8-4d70-8e1d-18609e8626bb.png HTTP/1.1" 200 - +2024-02-23 20:57:41,747 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:41] "GET /agents/pics/3ce264f2-8d98-4b10-b65d-0f01ce8fc43e.png HTTP/1.1" 200 - +2024-02-23 20:57:41,832 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:41] "GET /agents/pics/edd4c5d5-d993-4735-984c-f6ee4ad2f96b.png HTTP/1.1" 200 - +2024-02-23 20:57:42,243 [INFO]: 192.168.3.122 - - [23/Feb/2024 20:57:42] "GET /static/favicon.ico HTTP/1.1" 200 - +2024-02-23 21:18:14,065 [INFO]: WARNING: This is a development server. 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Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 09:08:16,822 [INFO]: Press CTRL+C to quit +2024-02-24 09:51:44,939 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 09:51:44,939 [INFO]: Press CTRL+C to quit +2024-02-24 09:57:32,340 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 09:57:32,340 [INFO]: Press CTRL+C to quit +2024-02-24 10:09:53,321 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 10:09:53,321 [INFO]: Press CTRL+C to quit +2024-02-24 10:11:37,643 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 10:11:37,643 [INFO]: Press CTRL+C to quit +2024-02-24 10:11:43,711 [WARNING]: No valid agent info found +2024-02-24 10:12:07,604 [WARNING]: No valid agent info found +2024-02-24 10:13:01,893 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 10:13:01,893 [INFO]: Press CTRL+C to quit +2024-02-24 10:13:07,977 [WARNING]: No valid agent info found +2024-02-24 10:15:49,614 [WARNING]: No valid agent info found +2024-02-24 10:20:04,228 [WARNING]: No valid agent info found +2024-02-24 10:22:52,308 [WARNING]: No valid agent info found +2024-02-24 10:22:52,310 [WARNING]: No valid agent info found +2024-02-24 10:26:39,794 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 10:26:39,795 [INFO]: Press CTRL+C to quit +2024-02-24 10:26:45,868 [WARNING]: No valid agent info found +2024-02-24 10:30:33,747 [WARNING]: No valid agent info found +2024-02-24 10:31:58,107 [WARNING]: No valid agent info found +2024-02-24 10:33:55,554 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got an unexpected keyword argument 'msg' +2024-02-24 10:35:15,042 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 10:35:15,042 [INFO]: Press CTRL+C to quit +2024-02-24 10:36:08,004 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got an unexpected keyword argument 'msg' +2024-02-24 10:40:40,231 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 10:40:40,231 [INFO]: Press CTRL+C to quit +2024-02-24 11:01:23,446 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 11:01:23,447 [INFO]: Press CTRL+C to quit +2024-02-24 11:17:02,325 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 11:17:02,325 [INFO]: Press CTRL+C to quit +2024-02-24 11:17:08,404 [WARNING]: No valid agent info found +2024-02-24 11:17:54,885 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got an unexpected keyword argument 'msg' +2024-02-24 11:18:00,890 [WARNING]: No valid agent info found +2024-02-24 11:19:42,010 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 11:19:42,010 [INFO]: Press CTRL+C to quit +2024-02-24 11:20:40,897 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got an unexpected keyword argument 'msg' +2024-02-24 11:20:46,905 [WARNING]: No valid agent info found +2024-02-24 11:35:17,001 [WARNING]: No valid agent info found +2024-02-24 12:41:06,111 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 12:41:06,112 [INFO]: Press CTRL+C to quit +2024-02-24 13:11:39,681 [ERROR]: Exception while handling incoming email: EmailClient.clean_html_content() takes 1 positional argument but 2 were given +2024-02-24 13:24:17,576 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got multiple values for argument 'from_email' +2024-02-24 13:32:09,201 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got multiple values for argument 'from_email' +2024-02-24 13:35:18,352 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got multiple values for argument 'from_email' +2024-02-24 13:41:26,853 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got multiple values for argument 'from_email' +2024-02-24 13:42:51,193 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 13:42:51,193 [INFO]: Press CTRL+C to quit +2024-02-24 13:47:51,037 [ERROR]: Exception while handling incoming email: EmailClient.send_email() got multiple values for argument 'from_alias' +2024-02-24 13:50:33,501 [ERROR]: Exception while handling incoming email: name 'escaped_recipients' is not defined +2024-02-24 13:54:29,776 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 13:54:29,777 [INFO]: Press CTRL+C to quit +2024-02-24 14:34:03,426 [INFO]: WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on all addresses (0.0.0.0) + * Running on http://127.0.0.1:81 + * Running on http://192.168.3.18:81 +2024-02-24 14:34:03,426 [INFO]: Press CTRL+C to quit +2024-02-24 14:35:21,392 [WARNING]: No valid agent info found +2024-02-24 14:49:28,169 [WARNING]: No valid agent info found diff --git a/email_client.py b/email_client.py old mode 100644 new mode 100755 index dfdaf624..7492b323 --- a/email_client.py +++ b/email_client.py @@ -1,4 +1,5 @@ import email +from bs4 import BeautifulSoup import html import imaplib import json @@ -8,8 +9,9 @@ import smtplib import quopri import tempfile +import subprocess import shutil - +import requests from time import sleep from datetime import datetime from email.mime.multipart import MIMEMultipart @@ -17,14 +19,20 @@ from email.utils import getaddresses from contextlib import contextmanager +import subprocess +import shlex + from pdf2text import extract_pdf_text from shortcode import handle_document_short_code from agent_operator import AgentSelector +from dotenv import load_dotenv +import os -class EmailClient: +load_dotenv() - # INIT & SETUP EMAIL ACCESS + +class EmailClient: def __init__(self, agent_loader, gpt, testing=False): logging.basicConfig(filename='email_client.log', @@ -39,10 +47,31 @@ def __init__(self, agent_loader, gpt, testing=False): self.conversation_threads = {} self.openai_api_key = os.getenv('OPENAI_API_KEY') + def get_response_from_api(self, content): + print("api") + + """Get response from external API for the given content.""" + url = "http://127.0.0.1:5000/v1/chat/completions" + headers = {"Content-Type": "application/json"} + data = { + "mode": "chat", + "character": "Example", + "messages": [{"role": "user", "content": content}] + } + response = requests.post(url, headers=headers, json=data, verify=False) + if response.status_code == 200: + api_response = response.json() + assistant_message = api_response['choices'][0]['message']['content'] + return assistant_message + else: + print("Failed to get response from API") + return None + def setup_email_client(self): self.smtp_server = os.getenv('SMTP_SERVER') self.smtp_port = os.getenv('SMTP_PORT') self.smtp_username = os.getenv('SMTP_USERNAME') + print('self.smtp_username',self.smtp_username) self.smtp_password = os.getenv('SMTP_PASSWORD') self.connect_to_imap_server() @@ -59,11 +88,56 @@ def check_imap_connection(self): except: return False + def extract_content_from_multipart(self, msg): + """ + Extracts and returns the plain text or HTML content from a MIMEMultipart email message. + + Parameters: + msg (MIMEMultipart): The multipart email message object. + + Returns: + str: The extracted content as a plain string. + """ + text_content = "" + for part in msg.walk(): + # Check if the part is plain text or HTML + if part.get_content_type() == "text/plain" or part.get_content_type() == "text/html": + text_content += part.get_payload(decode=True).decode() + # Optionally, break after finding the first text/plain or text/html part + break + return text_content + + def sanitize_email_address(self, email_address): + # Regular expression for validating an Email + regex = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b' + if re.fullmatch(regex, email_address): + return email_address + else: + print("Invalid Email Address. Making adjustments.") + # Perform any necessary adjustments or fallback + # For demonstration, returning a default email if validation fails + return "default@localdomain.com" + def start(self): print("Started email server") restart_counter = 0 MAX_RESTARTS = 500 - sleep_time = 620 # Sleep time in seconds + sleep_time = 6 # Sleep time in seconds + + # Directly prepare and send a test email + if(False): + try: + self.send_email( + from_email="rocket@localdomain.com", # Use an actual sender email address valid on your SMTP server + from_alias="Test Sender", # Sender's name or alias + to_emails=["root@localdomain.com"], # Replace with actual recipient email address + cc_emails=[], # CC emails if any, otherwise leave empty + subject="Test Email from start method", + modified_content="This is a test email sent from the start method." # Email body content + ) + print("Test email sent successfully.") + except Exception as e: + print(f"Failed to send test email: {e}") while True: try: @@ -96,9 +170,9 @@ def run_server_loop(self, sleep_time): for i in range( sleep_time, 0, - -30): # Decreasing sleep time by 10 seconds in each iteration + -3): # Decreasing sleep time by 10 seconds in each iteration print(f"Sleeping... {i} seconds remaining.") - sleep(30) # Sleep for 10 seconds + sleep(3) # Sleep for 10 seconds timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") print(f"[{timestamp}] Resuming processing.") @@ -203,100 +277,63 @@ def is_email_processed(self, x_gm_thrid, num): return False def load_email(self, num): + """ + Load and parse an email by its unique ID. + + Parameters: + num (str): The unique ID of the email to load. + + Returns: + tuple: A tuple containing parsed email components or None values on failure. + """ try: # Standardize the num to string type num_str = num.decode('utf-8') if isinstance(num, bytes) else str(num) - + + # Initialize the return values + from_, to_emails, cc_emails, subject, message_id, in_reply_to, references, content = (None,) * 8 + # Fetch the email content by UID - result, data = self.imap_server.uid('fetch', num_str, - '(RFC822 X-GM-THRID)') + result, data = self.imap_server.uid('fetch', num_str, '(RFC822)') if result != 'OK': print(f"Error fetching email content for UID {num}: {result}") return None, None, None, None, None, None, None, None - - # Initialize variables - x_gm_thrid = None + raw_email = None for response_part in data: if isinstance(response_part, tuple): - match = re.search(r'X-GM-THRID (\d+)', - response_part[0].decode('utf-8')) - if match: - x_gm_thrid = match.group(1) raw_email = response_part[1].decode("utf-8") - - email_message = email.message_from_string(raw_email) - if not email_message: - print(f"Error: email_message object is None for UID {num}") + break + + if not raw_email: + print(f"No email content found for UID {num}") return None, None, None, None, None, None, None, None - - # Extract headers and content + + email_message = email.message_from_string(raw_email) + + # Extract headers from_ = email_message['From'] to_emails = [addr[1] for addr in getaddresses([email_message['To']])] - cc_emails = [ - addr[1] for addr in getaddresses([email_message.get('Cc', '')]) - ] + cc_emails = [addr[1] for addr in getaddresses([email_message.get('Cc', '')])] subject = email_message['Subject'] message_id = email_message['Message-ID'] in_reply_to = email_message.get('In-Reply-To', '') references = email_message.get('References', '') - - content = "" - pdf_attachments = [] - - # Extract body and PDF content - for part in email_message.walk(): - if part.get_content_type() == 'text/html': - part.get_payload(decode=True).decode('utf-8') - elif part.get_content_type() == 'text/plain': - part.get_payload(decode=True).decode('utf-8') - content_encoding = part.get("Content-Transfer-Encoding") - payload = part.get_payload() - if content_encoding == 'base64': - content += base64.b64decode(payload).decode('utf-8') - else: - content += payload - - elif part.get_content_type() == 'application/pdf': - pdf_data = part.get_payload(decode=True) - pdf_text = extract_pdf_text(pdf_data) - pdf_attachments.append({ - 'filename': part.get_filename(), - 'text': pdf_text - }) - - # Append PDF contents to the content + + # Extract body and attachments + content, pdf_attachments = self.extract_email_content(email_message) + print("load_email") + print(content) + # Append PDF contents to the email content for pdf_attachment in pdf_attachments: - pdf_text = pdf_attachment.get('text', '') - if pdf_text: - pdf_label = f"PDF: {pdf_attachment['filename']}" - content += f"\n\n{pdf_label}\n{pdf_text}\n{pdf_label}\n" - - MAX_LIMIT = 350000 - if "!detail" in content or re.search(r"!summarize\.", content): - MAX_LIMIT = 2000000 - - # Check if the content is too long - if len(content) > MAX_LIMIT: - print(f"Content too long for UID {num}: {len(content)} characters.") - self.send_error_email(from_, subject, "Content too long") - self.mark_as_seen(num) - self.update_processed_threads(message_id, x_gm_thrid, num, subject, - in_reply_to, references, from_, - ','.join(to_emails + cc_emails)) - return None, None, None, None, None, None, None, None - - # Return the content which now includes both the email body and the PDF contents - return message_id, num, subject, content, from_, to_emails, cc_emails, references, in_reply_to, x_gm_thrid - - except Exception as e: - print(f"Exception while processing email with UID {num}: {e}") - import traceback - print(traceback.format_exc()) - return None, None, None, None, None, None, None, None + pdf_label = f"PDF: {pdf_attachment['filename']}" + content += f"\n\n{pdf_label}\n{pdf_attachment['text']}\n{pdf_label}\n" + except: + print("load email except") + + return message_id, num, subject, content, from_, to_emails, cc_emails, references, in_reply_to def process_thread(self): - try: self.imap_server.select("INBOX") result, data = self.imap_server.uid('search', None, 'UNSEEN') if result != 'OK': @@ -306,32 +343,29 @@ def process_thread(self): unseen_emails = data[0].split() thread_to_unseen = {} - # Group unseen emails by thread + # Group unseen emails by subject and sender as a proxy for thread grouping for num in unseen_emails: + print(num) email_data = self.load_email(num) - if email_data is None or len(email_data) != 10: - continue - message_id, _, subject, _, from_, _, _, _, _, x_gm_thrid = email_data - if self.is_email_processed(x_gm_thrid, num): + if email_data is None or len(email_data) < 8: # Adjusted for the updated return values from load_email continue - - # Use x_gm_thrid if available, else use subject - if x_gm_thrid is None or x_gm_thrid == "": - raise ValueError("x_gm_thrid is unavailable.") - - thread_key = x_gm_thrid + message_id, num_str, subject, content, from_, to_emails, cc_emails, references, in_reply_to = email_data + print("process_thread") + print(content) + # Use a combination of subject and sender for grouping + thread_key = f"{subject}:{from_}" if thread_key not in thread_to_unseen: thread_to_unseen[thread_key] = [] thread_to_unseen[thread_key].append({ - "message_id": message_id, - "num": num, - "subject": subject, - "from_": from_ + "message_id": message_id, + "num": num, + "subject": subject, + "from_": from_ }) - # Process the most recent unseen email in each thread + # Process the most recent unseen email in each pseudo-thread for thread_key, unseen_list in thread_to_unseen.items(): unseen_list.sort(key=lambda x: int(x['num']), reverse=True) most_recent_unseen = unseen_list[0] @@ -342,28 +376,26 @@ def process_thread(self): if not processed: print(f"Failed to process thread: {thread_key}") else: - # Mark all other unseen emails in the same thread as seen + # Mark all other unseen emails in the same pseudo-thread as seen for unseen_email in unseen_list[1:]: self.mark_as_seen(unseen_email['num']) - if not thread_key: - raise ValueError("thread_key is unavailable.") - x_gm_thrid = thread_key - + # Update processed threads without x_gm_thrid, using message_id instead self.update_processed_threads(unseen_email['message_id'], - x_gm_thrid, unseen_email['num'], - unseen_email['subject'], "", "", - unseen_email['from_'], "") - - except Exception as e: - print(f"Exception while processing emails: {e}") - import traceback - print(traceback.format_exc()) + "", # Empty placeholder for x_gm_thrid + unseen_email['num'], + unseen_email['subject'], "", "", + unseen_email['from_'], "") def process_single_thread(self, num): processed = False try: - message_id, num, subject, content, from_, to_emails, cc_emails, references, in_reply_to, x_gm_thrid = self.load_email( - num) + message_id, num_str, subject, content, from_, to_emails, cc_emails, references, in_reply_to = self.load_email(num) + if not message_id: + return processed # Skip if email couldn't be processed + + print("process_single_thread") + print(content) + if not message_id: return processed # Skip if email couldn't be processed @@ -441,6 +473,7 @@ def handle_incoming_email(self, from_, to_emails, cc_emails, thread_content, #print(f"Debug: Email content at start of handle_incoming_email:{thread_content[:50]}") new_content = thread_content + #print("new content",new_content) # Reset conversation history for a new email thread self.agent_operator.reset_for_new_thread() #print("Before human_threads initialization:", from_, to_emails,cc_emails, subject, message_id, references, num) @@ -531,9 +564,10 @@ def handle_incoming_email(self, from_, to_emails, cc_emails, thread_content, previous_responses = [] # Ensure proper unpacking for the load_email function - - message_id, num, subject, content, from_, to_emails, cc_emails, references, in_reply_to, x_gm_thrid = self.load_email( + message_id, num_str, subject, content, from_, to_emails, cc_emails, references, in_reply_to = self.load_email( num) + print("handle_incoming_email") + print(content) missing_values = [ var_name for var_name, value in locals().items() @@ -630,7 +664,7 @@ def handle_incoming_email(self, from_, to_emails, cc_emails, thread_content, ] to_emails_without_agent = [ - email for email in to_emails + self.sanitize_email_address(email) for email in to_emails if email.lower() != self.smtp_username.lower() ] cc_emails_without_agent = [ @@ -641,9 +675,9 @@ def handle_incoming_email(self, from_, to_emails, cc_emails, thread_content, if from_ not in to_emails_without_agent and from_ != self.smtp_username: to_emails_without_agent.append(from_) - if to_emails_without_agent or cc_emails_without_agent: - print(f"Sending email to: {to_emails_without_agent}") - print(f"CC: {cc_emails_without_agent}") + #if to_emails_without_agent or cc_emails_without_agent: + #print(f"Sending email to: {to_emails_without_agent}") + #print(f"CC: {cc_emails_without_agent}") if message_id in self.conversation_threads: self.conversation_threads[message_id].append(response) @@ -679,8 +713,6 @@ def handle_incoming_email(self, from_, to_emails, cc_emails, thread_content, f"{formatted_email_history_html}", 'html') - - alternative_response = MIMEMultipart('alternative') #alternative_response.attach(response_plain) @@ -692,25 +724,24 @@ def handle_incoming_email(self, from_, to_emails, cc_emails, thread_content, #alternative_history.attach(history_html) - # Creating 'mixed' MIME container for the entire email msg = MIMEMultipart('mixed') msg.attach(alternative_response) msg.attach(alternative_history) - - - + modified_content = self.extract_content_from_multipart(msg) try: - self.send_email(from_email=self.smtp_username, + #print('self.smtp_username',self.smtp_username) + self.send_email(from_email='root@localdomain.com', from_alias=agent["email"], to_emails=to_emails_without_agent, cc_emails=cc_emails_without_agent, subject=f"Re: {subject}", - msg=msg, - message_id=message_id, - references=references) + modified_content=modified_content + #message_id=message_id, + #references=references + ) print("Email sent successfully.") except Exception as e: print(f"Exception while handling incoming email: {e}") @@ -788,80 +819,67 @@ def format_email_history_plain(self, history, from_email, date): plain_text_content = 'On {} {} wrote:\n{}\n'.format(date, from_email, '\n'.join(quoted_lines)) return plain_text_content - - - # SEND EMAIL - - def send_email(self, - from_email, - from_alias, - to_emails, - cc_emails, - subject, - msg, - message_id=None, - references=None, - x_gm_thrid=None): - all_recipients = to_emails + cc_emails - - # Remove the sending agent's email from the To and Cc fields - all_recipients = [ - email for email in all_recipients - if email.lower() != from_email.lower() - ] - - is_html_email = any(part.get_content_type() == 'text/html' - for part in msg.get_payload()) - msg['Content-Type'] = 'text/html; charset="utf-8"' if is_html_email else 'text/plain; charset="utf-8"' - - if not all_recipients: - print("No valid recipients found. Will abort email send.") - return - - msg['From'] = f'"{from_alias}" <{from_alias}>' - msg['Reply-To'] = f'"{from_alias}" <{from_alias}>' - msg['Sender'] = f'"{from_alias}" <{from_alias}>' - msg['To'] = ', '.join(to_emails) - if cc_emails: - msg['Cc'] = ', '.join(cc_emails) - - msg['Subject'] = subject - - if x_gm_thrid: - msg["X-GM-THRID"] = x_gm_thrid - - if message_id: - msg["In-Reply-To"] = message_id - if references: - msg["References"] = references + ' ' + message_id - - # Clean the all_recipients list to remove the SMTP username - all_recipients = [ - email for email in all_recipients - if email.lower() != self.smtp_username.lower() - ] - - + def extract_email_content(self, email_message): """ - LOGGING - - # Generate a unique filename for the log file - log_filename = f'logs/email_log_{datetime.now().strftime("%Y%m%d%H%M%S")}_{message_id}.txt' - - - # Log the email content - with open(log_filename, 'w') as log_file: - log_file.write(f"From: {from_alias} <{from_alias}>\n") - log_file.write(f"To: {', '.join(to_emails)}\n") - if cc_emails: - log_file.write(f"Cc: {', '.join(cc_emails)}\n") - log_file.write(f"Subject: {subject}\n") - log_file.write("Message Body:\n") - log_file.write(msg.as_string()) - + Extracts content and attachments from an email message. + + Parameters: + email_message (email.message.Message): The email message object. + + Returns: + str: The combined text content of the email. + list: A list of dictionaries for each PDF attachment found. """ - with self.smtp_connection() as server: - server.sendmail(from_email, all_recipients, msg.as_string()) - print( - f"Email sent with Thread ID: {x_gm_thrid}, Subject: {subject}, Timestamp: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}" + content = "" + pdf_attachments = [] + for part in email_message.walk(): + content_type = part.get_content_type() + content_disposition = part.get("Content-Disposition", "") + if content_type == 'text/plain' and 'attachment' not in content_disposition: + payload = part.get_payload(decode=True) + charset = part.get_content_charset('utf-8') + content += payload.decode(charset, errors="replace") + elif content_type == 'application/pdf': + pdf_data = part.get_payload(decode=True) + pdf_text = extract_pdf_text(pdf_data) # Assuming this function is defined elsewhere + pdf_attachments.append({'filename': part.get_filename(), 'text': pdf_text}) + + return content, pdf_attachments + + def clean_html_content(self, html_content): + """Removes HTML tags and returns plain text.""" + soup = BeautifulSoup(html_content, "html.parser") + return soup.get_text(separator="\n") + + def send_email(self, from_email, from_alias, to_emails, cc_emails, subject, modified_content, message_id=None, references=None, x_gm_thrid=None): + """Sends an email using the 'mail' command, handling special characters.""" + recipients = ','.join(to_emails) # Combine all recipients into a single string + cleaned_content = self.clean_html_content(modified_content) # Clean the HTML content + + + recipients = 'root@localdomain.com' + + # Prepare the email content, including headers + email_content = ( + f"From: {from_alias} <{from_email}>\n" + f"To: {recipients}\n" + f"Subject: {subject}\n\n" + f"{cleaned_content}" ) + + # Use a temporary file to store the email content + with tempfile.NamedTemporaryFile(delete=False, mode='w+') as temp_file: + temp_file.write(email_content) + temp_file_path = temp_file.name + + # Send the email by reading from the temporary file + command = f'cat {temp_file_path} | mail -s "{subject}" {recipients}' + print('command',command) + try: + subprocess.run(command, shell=True, check=True, executable='/bin/bash') + print("Email sent successfully using the 'mail' command.") + except subprocess.CalledProcessError as e: + print(f"Failed to send email using 'mail' command: {e}") + + # Clean up the temporary file + #os.remove(temp_file_path) \ No newline at end of file diff --git a/error-response-email.txt b/error-response-email.txt old mode 100644 new mode 100755 diff --git a/gpt.py b/gpt.py old mode 100644 new mode 100755 index 0cadb299..fa8e9fe3 --- a/gpt.py +++ b/gpt.py @@ -1,6 +1,8 @@ import os import time import openai +openai.api_base = 'http://127.0.0.1:5000/v1' +#https://api.openai.com/v1 import tiktoken import re import pickle diff --git a/instructions.json b/instructions.json old mode 100644 new mode 100755 diff --git a/main.py b/main.py old mode 100644 new mode 100755 index 4263a1cd..f2f06788 --- a/main.py +++ b/main.py @@ -3,6 +3,10 @@ import json import os import subprocess +from dotenv import load_dotenv +import os + +load_dotenv() from email_client import EmailClient from gpt import GPTModel diff --git a/pdf2text.py b/pdf2text.py old mode 100644 new mode 100755 diff --git a/processed_threads.json b/processed_threads.json index 28fecc0e..d2190aae 100644 --- a/processed_threads.json +++ b/processed_threads.json @@ -1 +1 @@ -{"1771693114718505586": {"nums": {"5": {"processed": true}}, "metadata": {"subject": "atlas: what's the purpose of graph data?", "timestamp": "2023-07-17 18:23:28", "sender": "Sean McDonald ", "receiver": "Dev Agent ", "in_reply_to": "", "references": ""}}, "": {"nums": {"b'2254'": {"processed": true}}, "metadata": {"subject": "test", "timestamp": "2024-02-08 23:25:48", "sender": "Sean McDonald ", "receiver": "", "in_reply_to": "", "references": ""}}, "": {"nums": {"b'2255'": {"processed": true}}, "metadata": {"subject": "joke", "timestamp": "2024-02-09 00:07:57", "sender": "Sean McDonald ", "receiver": "", "in_reply_to": "", "references": ""}}} \ No newline at end of file +{"1771693114718505586": {"nums": {"5": {"processed": true}}, "metadata": {"subject": "atlas: what's the purpose of graph data?", "timestamp": "2023-07-17 18:23:28", "sender": "Sean McDonald ", "receiver": "Dev Agent ", "in_reply_to": "", "references": ""}}, "": {"nums": {"b'2254'": {"processed": true}}, "metadata": {"subject": "test", "timestamp": "2024-02-08 23:25:48", "sender": "Sean McDonald ", "receiver": "", "in_reply_to": "", "references": ""}}, "": {"nums": {"b'2255'": {"processed": true}}, "metadata": {"subject": "joke", "timestamp": "2024-02-09 00:07:57", "sender": "Sean McDonald ", "receiver": "", "in_reply_to": "", "references": ""}}, "<20240224184044.52D9CC0475E3@pve0.localdomain>": {"nums": {"b'37'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 10:42:03", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224184044.52D9CC0475E3@pve0.localdomain>"}}, "<20240224190145.35BC8C0475E3@pve0.localdomain>": {"nums": {"b'41'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 11:02:40", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224190145.35BC8C0475E3@pve0.localdomain>"}}, "<20240224192518.AF838C0475E3@pve0.localdomain>": {"nums": {"b'47'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 11:26:18", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224192518.AF838C0475E3@pve0.localdomain>"}}, "<20240224193533.D477AC0475E3@pve0.localdomain>": {"nums": {"b'50'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 11:40:24", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224193533.D477AC0475E3@pve0.localdomain>"}}, "": {"nums": {"b'49'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 11:40:24", "sender": "root ", "receiver": "", "in_reply_to": "", "references": ""}}, "<20240224203127.E441CC0475E3@pve0.localdomain>": {"nums": {"b'51'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 12:36:28", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224203127.E441CC0475E3@pve0.localdomain>"}}, "<20240224204359.C200EC0475E3@pve0.localdomain>": {"nums": {"b'53'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 12:48:37", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224204359.C200EC0475E3@pve0.localdomain>"}}, "<20240224205422.5A2D2C0475E3@pve0.localdomain>": {"nums": {"b'54'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 12:55:07", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224205422.5A2D2C0475E3@pve0.localdomain>"}}, "<20240224205709.25EB1C0475E3@pve0.localdomain>": {"nums": {"b'55'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 12:57:59", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224205709.25EB1C0475E3@pve0.localdomain>"}}, "<20240224210054.2B362C0475E3@pve0.localdomain>": {"nums": {"b'56'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 13:02:58", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224210054.2B362C0475E3@pve0.localdomain>"}}, "<20240224211700.A7B06C0475E3@pve0.localdomain>": {"nums": {"b'58'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 13:17:27", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224211700.A7B06C0475E3@pve0.localdomain>"}}, "<20240224215433.CA525C0475E3@pve0.localdomain>": {"nums": {"b'65'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 13:57:48", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224215433.CA525C0475E3@pve0.localdomain>"}}, "<20240224215922.091D0C0475E3@pve0.localdomain>": {"nums": {"b'66'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:00:32", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224215922.091D0C0475E3@pve0.localdomain>"}}, "<20240224221945.81615C0475E3@pve0.localdomain>": {"nums": {"b'67'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:20:39", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224221945.81615C0475E3@pve0.localdomain>"}}, "<20240224222208.CF5EAC0475E3@pve0.localdomain>": {"nums": {"b'68'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:23:12", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224222208.CF5EAC0475E3@pve0.localdomain>"}}, "<20240224222508.293FEC0475E3@pve0.localdomain>": {"nums": {"b'69'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:25:52", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224222508.293FEC0475E3@pve0.localdomain>"}}, "<20240224223028.EF174C0475C3@pve0.localdomain>": {"nums": {"b'70'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:31:23", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224223028.EF174C0475C3@pve0.localdomain>"}}, "<20240224223408.82F06C0475C3@pve0.localdomain>": {"nums": {"b'71'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:35:15", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224223408.82F06C0475C3@pve0.localdomain>"}}, "<20240224224211.E047DC0475C3@pve0.localdomain>": {"nums": {"b'73'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:43:04", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224224211.E047DC0475C3@pve0.localdomain>"}}, "<20240224224454.7D07EC0475C3@pve0.localdomain>": {"nums": {"b'74'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:45:58", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224224454.7D07EC0475C3@pve0.localdomain>"}}, "<20240224224801.3C8A9C0475C3@pve0.localdomain>": {"nums": {"b'77'": {"processed": true}}, "metadata": {"subject": "Test Email", "timestamp": "2024-02-24 14:49:22", "sender": "root ", "receiver": "", "in_reply_to": "", "references": "<20240224224801.3C8A9C0475C3@pve0.localdomain>"}}} \ No newline at end of file diff --git a/shortcode.py b/shortcode.py old mode 100644 new mode 100755 diff --git a/start-config.json b/start-config.json old mode 100644 new mode 100755 diff --git a/start.py b/start.py old mode 100644 new mode 100755 index af986189..2b56a456 --- a/start.py +++ b/start.py @@ -1,9 +1,13 @@ import os import subprocess import openai +openai.api_base = 'http://127.0.0.1:5000/v1' import json import argparse +from dotenv import load_dotenv +import os +load_dotenv() from tools import update_team diff --git a/static/content.json b/static/content.json old mode 100644 new mode 100755 diff --git a/static/favicon.ico b/static/favicon.ico old mode 100644 new mode 100755 diff --git a/static/logo.png b/static/logo.png old mode 100644 new mode 100755 diff --git a/static/logos/atat-board-art.jpg b/static/logos/atat-board-art.jpg old mode 100644 new mode 100755 diff --git a/static/logos/atat-board-basic.png b/static/logos/atat-board-basic.png old mode 100644 new mode 100755 diff --git a/static/logos/atat-board.png b/static/logos/atat-board.png old mode 100644 new mode 100755 diff --git a/static/logos/atat-glyph.png b/static/logos/atat-glyph.png old mode 100644 new mode 100755 diff --git a/static/logos/atat-wide-trans.png b/static/logos/atat-wide-trans.png old mode 100644 new mode 100755 diff --git a/static/logos/atat-wide-white-trans.png b/static/logos/atat-wide-white-trans.png old mode 100644 new mode 100755 diff --git a/static/logos/atat.png b/static/logos/atat.png old mode 100644 new mode 100755 diff --git a/static/logos/email-example-1.png b/static/logos/email-example-1.png old mode 100644 new mode 100755 diff --git a/static/logos/email-example-2.png b/static/logos/email-example-2.png old mode 100644 new mode 100755 diff --git a/static/logos/sl-logo-art-square.png b/static/logos/sl-logo-art-square.png old mode 100644 new mode 100755 diff --git a/static/logos/sl-logo-black-square.png b/static/logos/sl-logo-black-square.png old mode 100644 new mode 100755 diff --git a/static/logos/sl-logo-white-wide-trans.png b/static/logos/sl-logo-white-wide-trans.png old mode 100644 new mode 100755 diff --git a/static/logos/sl-logo-wide-black.png b/static/logos/sl-logo-wide-black.png old mode 100644 new mode 100755 diff --git a/static/logos/sl-logo-wide-trans.png b/static/logos/sl-logo-wide-trans.png old mode 100644 new mode 100755 diff --git a/static/logos/sl-trans-glyph.png b/static/logos/sl-trans-glyph.png old mode 100644 new mode 100755 diff --git a/static/main.css b/static/main.css old mode 100644 new mode 100755 diff --git a/templates/index.html b/templates/index.html old mode 100644 new mode 100755 diff --git a/templates/readme.html b/templates/readme.html old mode 100644 new mode 100755 diff --git a/test_email.py b/test_email.py new file mode 100755 index 00000000..63ccc8f3 --- /dev/null +++ b/test_email.py @@ -0,0 +1,40 @@ +import imaplib +import getpass + +# IMAP server details +IMAP_SERVER = 'localhost' +IMAP_PORT = 993 + +# User credentials +USERNAME = 'emailuser' +PASSWORD = '1234' +#getpass.getpass('Enter your password: ') + +# Connect to the IMAP server +imap_server = imaplib.IMAP4_SSL(IMAP_SERVER, IMAP_PORT) + +# Log in +try: + imap_server.login(USERNAME, PASSWORD) + print("Logged in successfully.") +except imaplib.IMAP4.error as e: + print(f"Login failed: {e}") + exit(1) + +# Select the INBOX +status, messages = imap_server.select('INBOX') +if status != 'OK': + print(f"Failed to select INBOX: {messages}") + imap_server.logout() + exit(1) + +# Search for unseen emails +status, response = imap_server.search(None, 'UNSEEN') +if status != 'OK': + print(f"Failed to search for unseen emails: {response}") +else: + unseen_emails = response[0].split() + print(f"Found {len(unseen_emails)} unseen emails.") + +# Log out +imap_server.logout() diff --git a/thread-reconciler.py b/thread-reconciler.py old mode 100644 new mode 100755 index a6229860..5893dbf9 --- a/thread-reconciler.py +++ b/thread-reconciler.py @@ -5,6 +5,11 @@ from datetime import datetime from email.utils import parsedate_to_datetime +from dotenv import load_dotenv +import os + +load_dotenv() + print("Script started.") # Fetch IMAP server details from environment variables diff --git a/tools/__init__.py b/tools/__init__.py old mode 100644 new mode 100755 diff --git a/tools/__pycache__/__init__.cpython-311.pyc b/tools/__pycache__/__init__.cpython-311.pyc new file mode 100755 index 00000000..b1b55eb4 Binary files /dev/null and b/tools/__pycache__/__init__.cpython-311.pyc differ diff --git a/tools/__pycache__/update_team.cpython-311.pyc b/tools/__pycache__/update_team.cpython-311.pyc new file mode 100755 index 00000000..68ddad01 Binary files /dev/null and b/tools/__pycache__/update_team.cpython-311.pyc differ diff --git a/tools/render_agents.py b/tools/render_agents.py old mode 100644 new mode 100755 index 52afb287..42c0ebc2 --- a/tools/render_agents.py +++ b/tools/render_agents.py @@ -9,6 +9,7 @@ import argparse import shutil import openai +openai.api_base = 'http://127.0.0.1:5000/v1' import requests domain_name = os.environ.get('DOMAIN_NAME', 'semantic-life.com') diff --git a/tools/testing_emails.md b/tools/testing_emails.md old mode 100644 new mode 100755 diff --git a/tools/thread-reconciler.py b/tools/thread-reconciler.py old mode 100644 new mode 100755 index a6229860..5893dbf9 --- a/tools/thread-reconciler.py +++ b/tools/thread-reconciler.py @@ -5,6 +5,11 @@ from datetime import datetime from email.utils import parsedate_to_datetime +from dotenv import load_dotenv +import os + +load_dotenv() + print("Script started.") # Fetch IMAP server details from environment variables diff --git a/tools/tuple-finder.py b/tools/tuple-finder.py old mode 100644 new mode 100755 diff --git a/tools/update_content.py b/tools/update_content.py old mode 100644 new mode 100755 index 050f5009..337053c3 --- a/tools/update_content.py +++ b/tools/update_content.py @@ -3,9 +3,15 @@ import json import os import openai +openai.api_base = 'http://127.0.0.1:5000/v1' import re import argparse +from dotenv import load_dotenv +import os + +load_dotenv() + openai.api_key = os.getenv("OPENAI_API_KEY") company_name = os.environ['COMPANY_NAME'] diff --git a/tools/update_team.py b/tools/update_team.py old mode 100644 new mode 100755 index feb1bdb8..3e56560d --- a/tools/update_team.py +++ b/tools/update_team.py @@ -1,8 +1,12 @@ import os import openai +openai.api_base = 'http://127.0.0.1:5000/v1' import glob import time +from dotenv import load_dotenv +import os +load_dotenv() # Load environment variables openai.api_key = os.getenv("OPENAI_API_KEY") company_name = os.getenv("COMPANY_NAME", "Your Default Company Name") diff --git a/tools/vars_tester.py b/tools/vars_tester.py old mode 100644 new mode 100755