Streamline Your Business: Automate Typeforms with AI Agents and VectorShift

Automating type forms has never been easier with the help of AI agents deployed from Vector Shift. In this section, we'll showcase how you can set up a pipeline to automatically respond to type form inquiries, without writing a single line of code.

First, we'll create a new pipeline from scratch on the Vector Shift dashboard. We'll set up an input node to receive the type form data, including the name, email address, and inquiry. These inputs will then be processed by separate large language model nodes, one to extract the email address and another to generate a concise response based on the name and inquiry.

The email address extracted by the first language model node will be used to populate the recipient field in a Gmail node, which will create a draft email with the generated response. This allows for human review and editing before the email is sent.

To connect the type form to the pipeline, we'll use the automation feature in Vector Shift. We'll select the type form as the application and configure the automation to trigger on new entries. By mapping the type form fields to the corresponding input nodes in the pipeline, we can seamlessly integrate the two systems.

Once the automation is set up and deployed, any new submissions to the type form will automatically trigger the pipeline, generating a personalized email response that can be reviewed and sent. This streamlined process eliminates the need for manual data entry and ensures timely and consistent communication with your customers or leads.

By leveraging the power of AI-powered solutions like Vector Shift, you can transform your type form workflows, saving time and improving the overall customer experience.

Vector Shift is a powerful platform that enables you to automate various tasks with the help of AI agents. In this section, we will explore how you can leverage Vector Shift's drag-and-drop interfaces to build applications that leverage large language models (LLMs) without writing a single line of code.

The key features that make Vector Shift a compelling choice for LLM-powered app development include:

1. Intuitive Drag-and-Drop Interface: Vector Shift's visual programming environment allows you to easily connect different components, such as input nodes, language models, and output nodes, to create complex workflows.

2. Seamless Integration with LLMs: Vector Shift provides access to a variety of pre-trained LLMs, including OpenAI's models, which you can easily integrate into your applications.

3. Knowledge Base Integration: Vector Shift enables you to connect your applications to external knowledge bases, allowing the LLMs to leverage contextual information for more informed and relevant responses.

4. Automated Workflows: By connecting your applications to external services, such as email or messaging platforms, you can create end-to-end automated workflows that handle user inquiries and provide timely responses.

To demonstrate the power of Vector Shift, we walked through the process of automating a Typeform using AI agents. This involved setting up input nodes to capture user information, connecting them to LLM nodes for generating responses, and integrating a Gmail node to send the responses back to the user.

The key steps in this process included:

1. Configuring the input nodes to extract the necessary information from the Typeform (name, email, and inquiry).
2. Utilizing separate LLM nodes to process the email address and the combined name and inquiry, ensuring accurate and targeted responses.
3. Integrating a knowledge base to provide context-aware responses, leveraging relevant information about Vector Shift.
4. Connecting the LLM-generated responses to a Gmail node, allowing for seamless delivery of the responses to the user.

By following this approach, you can easily automate various types of forms, chatbots, and other applications, all without writing a single line of code. Vector Shift's intuitive interface and powerful integration capabilities make it a compelling choice for anyone looking to harness the power of LLMs in their business or personal projects.

In this section, we will explore how to leverage large language models to automate personalized email responses to customer inquiries. By integrating a type form with a Vector Shift pipeline, we can create a seamless workflow that extracts key information from the form, generates a tailored response, and sends it directly to the customer's email.

The key steps involved in this process are:

1. Configuring the Input Nodes: We set up separate input nodes to capture the customer's name, email address, and inquiry. This allows the large language model to parse and utilize this information effectively.

2. Leveraging Large Language Models: We employ two large language model nodes - one to extract the email address, and another to generate a concise, context-aware response based on the customer's name and inquiry.

3. Integrating the Knowledge Base: By connecting a knowledge base to the pipeline, we can provide the large language model with relevant context and information to craft more informed and detailed responses.

4. Automating the Email Workflow: The final step involves connecting the pipeline to the type form and configuring the automation to trigger a response whenever a new entry is submitted.

This approach enables you to provide personalized and efficient customer support, freeing up your team's time and resources while ensuring a high level of responsiveness and attention to each inquiry.

To automate the Type Form response, we'll leverage the power of knowledge bases and large language models within the Vector Shift platform. This approach allows us to provide context-aware and concise responses to inquiries.

1. Separate Email Extraction: We create a dedicated large language model node to extract the email address from the Type Form input. This ensures the email is accurately captured as the recipient for the response.

2. Leveraging Context with Knowledge Base: We integrate a knowledge base that contains relevant information, such as Vector Shift documentation. This allows the large language model to reference the context and provide more detailed and accurate responses to the inquiries.

3. Personalized Response Generation: The second large language model node is responsible for generating a personalized response based on the user's name and inquiry. It utilizes the context from the knowledge base to craft a concise and informative answer.

4. Seamless Integration with Gmail: The workflow connects the extracted email address and the generated response to a Gmail node, allowing for a smooth delivery of the response directly to the user's inbox.

By combining the power of knowledge bases, large language models, and the versatility of the Vector Shift platform, we can create a highly efficient and context-aware Type Form automation solution. This approach ensures that users receive tailored and informative responses, streamlining the communication process and enhancing the overall user experience.

In this video, we have successfully automated a Typeform using Vector Shift, an integrated framework of no-code generative AI solutions. By creating a pipeline within Vector Shift, we were able to automate the process of responding to inquiries submitted through the Typeform.

The key steps involved in this automation process were:

1. Setting up input nodes to capture the name, email address, and inquiry from the Typeform.
2. Utilizing two separate large language model nodes - one to extract the email address and another to generate a concise response based on the name and inquiry.
3. Connecting the email address to a Gmail node to create a draft email with the generated response.
4. Integrating the Typeform with the Vector Shift pipeline to trigger the automation when a new entry is submitted.

This demonstration showcases the power of Vector Shift in automating various tasks, including form responses, without the need for any coding. By leveraging the capabilities of large language models and the intuitive interface of Vector Shift, businesses and individuals can streamline their workflows and improve efficiency.

The ability to customize the system prompts, knowledge base, and other settings within Vector Shift allows for a high degree of flexibility and personalization, ensuring that the automated responses are tailored to the specific needs of the user or organization.

Overall, this video highlights the practical applications of AI agents deployed from Vector Shift, demonstrating how they can be utilized to automate repetitive tasks and enhance productivity.