[Enterprise](/content/enterprise/index.html)

Products

[Pricing](/content/pricing/index.html) [Docs](https://docs.potpie.ai/) [Blog](/content/blog/index.html)

[5k+](https://github.com/potpie-ai/potpie)

[Sign UP](https://app.potpie.ai/)

\\
\\
Specialists](/content/potpie-specialists/index.html) \\
\\
Forge](/content/potpie-forge/index.html) \\
\\
Recipes](/content/potpie-recipe/index.html) \\
\\
Trace](/content/potpie-trace/index.html)

Potpie supports Multi-LLMs

Dhiren Mathur

Feb 27, 2025

[TL/DR;](/content/blog/potpie-supports-multi-llms#header-0/index.html) [What is Multi-LLM Support Feature?](/content/blog/potpie-supports-multi-llms#header-1/index.html) [Key Features:](/content/blog/potpie-supports-multi-llms#header-2/index.html) [How it works?](/content/blog/potpie-supports-multi-llms#header-3/index.html) [How Provider Selection Works:](/content/blog/potpie-supports-multi-llms#header-4/index.html) [Supported LLM Providers](/content/blog/potpie-supports-multi-llms#header-5/index.html) [How to Use It](/content/blog/potpie-supports-multi-llms#header-6/index.html) [Using local setup for Potpie](/content/blog/potpie-supports-multi-llms#header-8/index.html) [Examples](/content/blog/potpie-supports-multi-llms#header-9/index.html) [Start Using Multi-LLM Support Today](/content/blog/potpie-supports-multi-llms#header-10/index.html)

### TL/DR;

Unlock the power of multiple AI models with Potpie’s Multi-LLM Support feature. Seamlessly integrate OpenAI, Gemini, Claude, and more to optimize performance, cost, and flexibility. Learn how to set up and configure your preferred LLM for smarter AI Agents today!

Every day at Potpie, we’re focused on making our AI Agents smarter, faster, and more adaptable to real-world developer needs. We continuously refine their capabilities, ensuring they stay ahead with modern and more powerful features that provide greater flexibility and efficiency.

‍With that goal in mind, we're excited to introduce **Multi-LLM Support**, a new feature that allows our AI Agents to work with multiple Large Language Models from different providers, making them even more versatile and customizable for your specific needs.

This upgrade enables AI Agents to go beyond a single model provider by dynamically connecting to various LLMs based on your preferences. Whether it's leveraging OpenAI's capabilities, exploring the Claude's code understanding, or utilizing cost-effective alternatives like DeepSeek, Multi-LLM Support ensures that you can select the best model for your specific use case, providing developers with unprecedented flexibility.

‍This feature is available in our latest release (v0.1.1), which you can access here: [https://github.com/potpie-ai/potpie/releases/tag/v0.1.1](https://github.com/potpie-ai/potpie/releases/tag/v0.1.1)

To power this feature, we've integrated LiteLLM, a lightweight framework that standardizes API calls across multiple AI providers. This allows Potpie to seamlessly route requests to different LLMs while handling request formatting, and model-specific optimizations under the hood.

### What is Multi-LLM Support Feature?

The **Multi-LLM Support** feature allows users to integrate their preferred language model provider based on their specific needs for cost, performance, and capabilities. With this update, AI Agents can now use different LLMs while keeping their full capabilities, providing accurate and informed responses from your chosen model.

### Key Features:

\- **Provider Flexibility**: Users can select from multiple LLM providers including OpenAI, Anthropic, Google, Meta, and DeepSeek.

\- **Model Selection**: Configure different models for lightweight tasks versus complex reasoning, optimizing for both performance and cost.

\- **Seamless Integration**: All existing Potpie features continue to work regardless of which underlying LLM powers your agents.

\- **API Key Management**: Securely use your own API keys for any supported provider.

‍This feature enhances the AI Agent's ability to adapt to different requirements while reducing dependency on a single model provider.

‍Several AI development platforms offer multi-model support, but Potpie's implementation stands out for its seamless integration with custom AI Agents. Unlike simpler implementations that just route prompts to different providers, Potpie's Multi-LLM Support maintains context awareness and specialized capabilities across different providers.

### How it works?

The Multi-LLM Support feature is built using **LiteLLM**, a lightweight framework that makes it easy to connect with different AI providers. This open-source tool ensures that all API calls follow a standard format, allowing Potpie to seamlessly work with multiple LLMs without compatibility issues.

‍LiteLLM provides a seamless way to interact with different LLMs, enabling our Multi-LLM Support feature to:

‍\- **Standardize API Calls**: Maintain consistent API formats across different providers

\- **Handle Provider-Specific Optimizations**: Adjust parameters for each model's requirements

\- **Manage Authentication**: Handle different API key formats securely

\- **Support Streaming**: Enable streaming capabilities for interactive responses

\- **Structure Outputs**: Work with structured data using the Instructor library

‍By incorporating LiteLLM, we ensure that our Multi-LLM Support feature delivers consistent, high-quality responses regardless of the underlying provider, enhancing the AI Agent's flexibility without compromising functionality.

‍The Multi-LLM Support feature operates using a provider service architecture that dynamically selects and configures LLMs based on user preferences and task requirements:

### How Provider Selection Works:

**Model Configuration**

The system maintains pre-configured settings for popular LLMs, including:

\- Small Models: Optimized for lightweight, faster tasks

\- Large Models: Designed for complex reasoning and advanced capabilities

\- Custom Configurations: Support for user-defined models and settings

‍ **Dynamic Provider Selection**

When an AI Agent needs to generate a response, the system:

1\. Checks user preferences for their default provider

2\. Determines if the task requires a "small" or "large" model

3\. Retrieves the appropriate API key

4\. Configures the correct parameters for the selected model

5\. Routes the request to the appropriate provider

### Supported LLM Providers

Potpie's Multi-LLM Support feature comes with built-in support for the following providers:

‍1\. **OpenAI's GPT** – Versatile language models with strong natural language understanding and code generation capabilities

‍2\. **Google's Gemini** – Optimized for multimodal tasks with advanced reasoning and contextual awareness

‍3\. **Anthropic's Claude** – Specialized in code understanding and generation with advanced capabilities for technical problem-solving

‍4\. **Meta's Llama** – Open-source foundation models known for strong performance with greater customization options

‍5\. **DeepSeek** – Cost-efficient models with strong reasoning capabilities, ideal for complex problem-solving

‍We will continue expanding support for more LLMs based on community feedback and emerging advancements in AI models, ensuring developers always have access to the best tools for their needs.

### How to Use It

There are two main ways to use the Multi-LLM Support feature: using Potpie's dashboard with the default supported providers or setting up Potpie locally for maximum customization.

##### Using Potpie Dashboard

To leverage the benefits of multiple LLMs in your AI Agents via your Potpie dashboard, here’s how you can get started:

- **Login to the Potpie Dashboard**: Use your GitHub credentials to access your account - app.potpie.ai

- **Go to the Key Management Screen**: Navigate to the Key Management section.

- **Select Your AI Provider**: Under the Set Global AI Provider section, choose from multiple LLM models.

- **Choose Your API Key Option**: Select whether you want to use your own API key or Potpie’s key. If you wish to go with your own API key, you will need to select your desired LLM and then enter your API Key.

- **Start Using Your AI Agent**: Once set up, your AI Agent will interact with the selected model, providing responses tailored to the capabilities of that LLM.

With this flexibility, you can experiment with different LLMs and optimize performance based on your project’s specific requirements.

**Note:** If you select Deepseek, Meta-Llama, or Gemini as your desired LLM model, you will need to enter the OpenRouter API key. However, for other LLM models, you can enter their respective API keys.

### Using local setup for Potpie

Setting up Potpie locally is straightforward and provides full control over your AI Agents' LLM configurations:

‍1\. First, install Potpie on your local machine following our [Getting Started Guide](https://github.com/potpie-ai/potpie/blob/main/GETTING_STARTED.md)

‍2\. Configure your preferred LLM by setting these four key parameters:

\`LLM\_PROVIDER\` – The name of your AI provider (e.g., OpenRouter, Ollama)

\`LLM\_API\_KEY\` – Your API key for the chosen provider

\`LOW\_REASONING\_MODEL\` – The model used for lightweight tasks

\`HIGH\_REASONING\_MODEL\` – The model used for complex reasoning

Here's an example configuration using OpenRouter with DeepSeek models:

\`\`\`

LLM\_PROVIDER=openrouter

LLM\_API\_KEY=sk-or-your-key

LOW\_REASONING\_MODEL=openrouter/deepseek/deepseek-chat

HIGH\_REASONING\_MODEL=openrouter/deepseek/deepseek-chat

\`\`\`

For Ollama users, the configuration would look like this:

\`\`\`

LLM\_PROVIDER=ollama

LLM\_API\_KEY=ollama

LOW\_REASONING\_MODEL=ollama\_chat/qwen2.5-coder:7b

HIGH\_REASONING\_MODEL=ollama\_chat/qwen2.5-coder:7b

\`\`\`

For those using any of our default supported LLMs (Anthropic, Gemini, OpenAI, Deepseek, and Meta-Llama), you don't need to specify reasoning models—Potpie automatically assigns the best-suited model based on our tested configurations.

### Examples

Let's see how you might use different models for different use cases:

‍Using Claude for Advanced Code Understanding

‍Claude excels at code comprehension and technical problem-solving:

\`\`\`

LLM\_PROVIDER=anthropic

LLM\_API\_KEY=your-anthropic-key

\`\`\`

With this configuration, your AI Agent will leverage Claude's strong code understanding capabilities to provide more accurate technical assistance.

‍Using DeepSeek for Cost-Efficient Operations

‍DeepSeek offers powerful reasoning at a lower cost:

\`\`\`

LLM\_PROVIDER=openrouter

LLM\_API\_KEY=your-openrouter-key

LOW\_REASONING\_MODEL=openrouter/deepseek/deepseek-chat

HIGH\_REASONING\_MODEL=openrouter/deepseek/deepseek-r1

\`\`\`

This setup helps you balance cost and performance for projects with budget constraints.

### Start Using Multi-LLM Support Today

You can now integrate your preferred AI models directly into Potpie. Whether you want to leverage the power of OpenAI, explore the capabilities of Gemini, or experiment with Claude, Potpie gives you complete control over which LLM powers your AI Agents.

‍

Set up Potpie locally today and start building with the AI model that best suits your needs:

\- Checkout [Potpie GitHub Repository](https://github.com/potpie-ai/potpie)

\- Getting Started Guide, [click here](https://github.com/potpie-ai/potpie/blob/main/GETTING_STARTED.md)

Got stuck anywhere? Join our [Discord Server](https://discord.gg/NxUQCcz6) for community support!

" height="176.48689063250688px" id="t2zO9Quc7" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.55" stroke="rgb(180, 209, 63)" transform="translate(0.773 0.758)" width="307.0499654602649px"/></svg>)

" height="127.83155915492955px" id="F7uNl9dyd" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(8.021 100.549)" width="136.10429429577454px"/><path d="M 120.738 0 L 166.541 2.512 L 302.646 81.116 L 259.995 105.741 L 140.463 174.742 L 48.783 121.822 L 39.844 116.65 L 21.917 106.308 L 4.359 96.162 L 0 69.714 Z M 84.883 90.646 L 93.847 95.818 L 111.75 106.16 L 140.734 122.881 L 155.534 97.468 L 158.883 91.73 L 212.812 81.264 L 161.197 51.467 L 141.177 39.918 L 130.096 46.32 L 124.653 49.473 L 69.099 81.535 Z M 27.753 84.712 L 130.096 25.635 L 146.718 16.031 L 130.096 15.292 L 26.472 75.132 Z" fill="rgb(0, 53, 51)" height="174.74215475179432px" id="XL4eRTHOZ" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(3.647 4.386)" width="302.6461113816823px"/><path d="M 0 0 L 0 10.343 L 16.622 0.739 Z" fill="rgb(0, 53, 51)" height="10.34275225352113px" id="cBwRaCSIs" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(133.76 19.669)" width="16.622023943661958px"/><path d="M 0 59.84 L 1.28 69.419 L 103.623 10.343 L 103.623 0 Z" fill="rgb(0, 53, 51)" height="69.41898253521126px" id="yI1DYW3PI" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(30.132 19.669)" width="103.62314999999992px"/><path d="M 0 0 L 0 49.251 L 14.357 57.55 L 17.706 51.812 L 71.636 41.346 L 20.021 11.549 Z" fill="rgb(0, 53, 51)" height="57.54972676056339px" id="swIgz6ZQs" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(144.827 44.294)" width="71.63555704225351px"/><path d="M 0 41.617 L 15.785 50.728 L 24.748 55.9 L 42.651 66.242 L 72.078 49.251 L 72.078 0 L 60.997 6.403 L 55.555 9.555 Z" fill="rgb(0, 53, 51)" height="66.2424190140845px" id="Ou0foMTnv" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(72.761 44.294)" width="72.07816690140838px"/><path d="M 0 93.626 L 0 142.877 L 162.183 49.251 L 162.183 0 L 119.532 24.626 Z" fill="rgb(0, 53, 51)" height="142.87681267605637px" id="F6Glizjhy" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(144.11 85.495)" width="162.1830021126761px"/><path d="M 0 0 L 0 49.251 L 4.359 75.699 L 4.359 26.448 Z" fill="rgb(0, 53, 51)" height="75.69868943661974px" id="CEJbzDHVA" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.46" stroke="rgb(180, 209, 63)" transform="translate(3.661 74.105)" width="4.358684366197165px"/></svg>)

" height="275.2348071827544px" id="tOCVqXAMo" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.05" stroke="rgb(180, 209, 63)" transform="translate(2.023 1.876)" width="306.08189403973506px"/></svg>)

" height="272.22086421478906px" id="PPsuL8gM9" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.04" stroke="rgb(180, 209, 63)" transform="translate(2.016 1.798)" width="306.4324539473682px"/></svg>)

" height="176.48689063250686px" id="YZ_qP17EP" stroke-dasharray="" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.55" stroke="rgb(180, 209, 63)" transform="translate(0.773 0.758)" width="307.04996546026496px"/><g d="M 62.549 28.787 C 62.536 28.761 62.526 28.736 62.519 28.709 C 62.535 28.768 62.56 28.824 62.6 28.878 C 62.578 28.849 62.562 28.818 62.549 28.787 Z M 62.549 28.787 L 62.6 28.878 C 62.56 28.824 62.535 28.768 62.519 28.709 Z M 54.656 27.136 L 53.678 29.273 C 52.829 31.129 53.725 33.105 56.041 34.482 L 67.491 41.285 L 70.928 43.27 C 73.406 44.7 77.049 45.237 80.421 44.654 L 121.141 37.611 C 120.159 39.696 120.291 41.929 121.582 44.003 C 125.001 49.499 120.112 55.555 110.627 57.574 C 105.569 58.649 101.585 60.95 99.722 63.869 C 96.226 69.347 85.734 72.169 76.215 70.194 C 71.142 69.142 65.525 69.424 60.847 70.967 C 52.07 73.864 40.885 72.132 35.787 67.087 C 33.07 64.398 28.45 62.529 23.146 61.975 C 13.195 60.934 6.552 55.458 8.262 49.704 C 9.172 46.637 7.711 43.493 4.263 41.1 C -2.205 36.611 -1.202 29.951 6.515 26.18 C 10.627 24.17 13.008 21.221 13.03 18.11 C 13.07 12.271 21.254 7.547 31.367 7.524 C 36.757 7.511 41.866 6.135 45.347 3.761 C 50.795 0.044 59.728 -0.975 67.055 0.959 Z M 121.101 29.063 C 121.295 29.225 121.319 29.421 121.365 29.811 C 121.437 30.422 121.416 31.043 121.303 31.658 C 121.245 31.973 121.216 32.132 121.07 32.303 C 120.952 32.442 120.731 32.596 120.516 32.689 C 120.25 32.804 119.941 32.858 119.324 32.965 L 78.041 40.112 C 77.569 40.193 77.056 40.118 76.707 39.917 L 73.268 37.93 C 72.552 37.516 72.859 36.812 73.828 36.645 L 118.972 28.911 C 119.692 28.787 120.052 28.726 120.384 28.774 C 120.655 28.814 120.941 28.93 121.101 29.063 Z M 77.422 5.057 L 85.829 15.345 L 85.834 15.352 C 85.944 15.485 85.999 15.553 86.076 15.611 C 86.144 15.664 86.226 15.711 86.317 15.751 C 86.42 15.796 86.54 15.83 86.779 15.895 L 107.021 21.407 L 107.041 21.413 C 107.775 21.613 108.144 21.713 108.236 21.838 C 108.316 21.947 108.297 22.073 108.187 22.173 C 108.059 22.288 107.655 22.352 106.863 22.48 L 64.254 29.318 C 63.803 29.4 63.362 29.338 63.037 29.193 L 62.989 29.169 C 62.826 29.09 62.694 28.987 62.61 28.87 L 62.559 28.779 L 62.529 28.701 C 62.501 28.597 62.509 28.489 62.561 28.376 L 73.706 5.239 L 73.713 5.226 C 74.151 4.315 74.371 3.857 74.769 3.71 C 75.115 3.582 75.548 3.562 75.927 3.654 C 76.364 3.761 76.717 4.193 77.422 5.057 Z" fill="transparent" height="72.36999344346039px" id="PThBnjLXo" transform="translate(95.525 49.205)" width="122.67217843649964px"><path d="M 0.03 0.077 C 0.017 0.052 0.007 0.027 0 0 C 0.016 0.059 0.041 0.115 0.081 0.169 C 0.059 0.139 0.043 0.109 0.03 0.077 Z" fill="rgb(180, 209, 63)" height="1px" id="FZhYXbO6L" transform="translate(62.519 28.709)" width="1px"/><path d="M 62.549 28.787 L 62.6 28.878 C 62.56 28.824 62.535 28.768 62.519 28.709 Z M 54.656 27.136 L 53.678 29.273 C 52.829 31.129 53.725 33.105 56.041 34.482 L 67.491 41.285 L 70.928 43.27 C 73.406 44.7 77.049 45.237 80.421 44.654 L 121.141 37.611 C 120.159 39.696 120.291 41.929 121.582 44.003 C 125.001 49.499 120.112 55.555 110.627 57.574 C 105.569 58.649 101.585 60.95 99.722 63.869 C 96.226 69.347 85.734 72.169 76.215 70.194 C 71.142 69.142 65.525 69.424 60.847 70.967 C 52.07 73.864 40.885 72.132 35.787 67.087 C 33.07 64.398 28.45 62.529 23.146 61.975 C 13.195 60.934 6.552 55.458 8.262 49.704 C 9.172 46.637 7.711 43.493 4.263 41.1 C -2.205 36.611 -1.202 29.951 6.515 26.18 C 10.627 24.17 13.008 21.221 13.03 18.11 C 13.07 12.271 21.254 7.547 31.367 7.524 C 36.757 7.511 41.866 6.135 45.347 3.761 C 50.795 0.044 59.728 -0.975 67.055 0.959 Z M 121.101 29.063 C 121.295 29.225 121.319 29.421 121.365 29.811 C 121.437 30.422 121.416 31.043 121.303 31.658 C 121.245 31.973 121.216 32.132 121.07 32.303 C 120.952 32.442 120.731 32.596 120.516 32.689 C 120.25 32.804 119.941 32.858 119.324 32.965 L 78.041 40.112 C 77.569 40.193 77.056 40.118 76.707 39.917 L 73.268 37.93 C 72.552 37.516 72.859 36.812 73.828 36.645 L 118.972 28.911 C 119.692 28.787 120.052 28.726 120.384 28.774 C 120.655 28.814 120.941 28.93 121.101 29.063 Z M 77.422 5.057 L 85.829 15.345 L 85.834 15.352 C 85.944 15.485 85.999 15.553 86.076 15.611 C 86.144 15.664 86.226 15.711 86.317 15.751 C 86.42 15.796 86.54 15.83 86.779 15.895 L 107.021 21.407 L 107.041 21.413 C 107.775 21.613 108.144 21.713 108.236 21.838 C 108.316 21.947 108.297 22.073 108.187 22.173 C 108.059 22.288 107.655 22.352 106.863 22.48 L 64.254 29.318 C 63.803 29.4 63.362 29.338 63.037 29.193 L 62.989 29.169 C 62.826 29.09 62.694 28.987 62.61 28.87 L 62.559 28.779 L 62.529 28.701 C 62.501 28.597 62.509 28.489 62.561 28.376 L 73.706 5.239 L 73.713 5.226 C 74.151 4.315 74.371 3.857 74.769 3.71 C 75.115 3.582 75.548 3.562 75.927 3.654 C 76.364 3.761 76.717 4.193 77.422 5.057 Z" fill="rgb(180, 209, 63)" height="72.36999344346039px" id="AQyCIziS7" transform="translate(0 0)" width="122.67217843649964px"/></g></svg>)

" height="150.90560294117645px" id="jxii70vzV" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(24.37 4.791)" width="261.37546588235216px"/><path d="M 29.623 10.224 L 36.309 7.429 L 43.611 4.988 L 51.344 3.009 L 59.322 1.509 L 67.439 0.515 L 75.693 0.009 L 84.164 0 L 92.557 0.515 L 100.919 1.544 L 108.728 3.018 L 116.384 4.988 L 123.793 7.455 L 130.373 10.224 L 136.629 13.481 L 142.286 17.103 L 147.097 20.91 L 151.356 25.179 L 154.784 29.643 L 157.336 34.117 L 159.104 38.936 L 159.995 43.657 L 159.981 48.672 L 159.104 53.438 L 157.336 58.222 L 154.784 62.73 L 151.356 67.194 L 147.128 71.41 L 142.286 75.271 L 136.629 78.892 L 130.373 82.149 L 123.686 84.945 L 116.384 87.386 L 108.728 89.356 L 100.843 90.838 L 92.557 91.859 L 84.164 92.374 L 75.632 92.365 L 67.439 91.859 L 59.322 90.865 L 51.344 89.365 L 43.611 87.386 L 36.233 84.918 L 29.623 82.149 L 23.351 78.883 L 17.709 75.271 L 12.928 71.464 L 8.639 67.194 L 5.227 62.775 L 2.613 58.124 L 0.892 53.438 L 0 48.592 L 0 43.782 L 0.892 38.936 L 2.613 34.25 L 5.227 29.599 L 8.639 25.179 L 12.867 20.963 L 17.709 17.103 L 23.351 13.49 Z" fill="rgb(0, 53, 51)" height="92.37355058823529px" id="LN6Mj2wjX" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(75.05 69.207)" width="159.99511058823543px"/><path d="M 29.623 10.224 L 36.309 7.429 L 43.611 4.988 L 51.344 3.009 L 59.322 1.509 L 67.439 0.515 L 75.693 0.009 L 84.164 0 L 92.557 0.515 L 100.919 1.544 L 108.729 3.018 L 116.383 4.988 L 123.794 7.455 L 130.374 10.224 L 136.63 13.481 L 142.287 17.103 L 147.098 20.91 L 151.357 25.179 L 154.785 29.643 L 157.337 34.117 L 159.103 38.936 L 159.996 43.657 L 159.979 48.672 L 159.103 53.438 L 157.337 58.222 L 154.785 62.73 L 151.357 67.194 L 147.129 71.41 L 142.287 75.271 L 136.63 78.892 L 130.374 82.149 L 123.687 84.946 L 116.383 87.385 L 108.729 89.355 L 100.843 90.838 L 92.557 91.858 L 84.164 92.374 L 75.632 92.365 L 67.439 91.858 L 59.322 90.864 L 51.344 89.364 L 43.611 87.385 L 36.233 84.918 L 29.623 82.149 L 23.351 78.883 L 17.709 75.271 L 12.928 71.463 L 8.639 67.194 L 5.227 62.775 L 2.613 58.124 L 0.892 53.438 L 0 48.592 L 0 43.781 L 0.892 38.936 L 2.613 34.25 L 5.227 29.599 L 8.639 25.179 L 12.867 20.963 L 17.709 17.103 L 23.351 13.49 Z" fill="rgb(0, 53, 51)" height="92.37427764705882px" id="jDPtsCydt" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(75.76 83.833)" width="159.99583764705716px"/><path d="M 29.623 10.224 L 36.309 7.429 L 43.611 4.988 L 51.344 3.009 L 59.322 1.509 L 67.439 0.515 L 75.693 0.009 L 84.164 0 L 92.557 0.515 L 100.919 1.544 L 108.728 3.018 L 116.384 4.988 L 123.793 7.455 L 130.373 10.224 L 136.629 13.481 L 142.286 17.103 L 147.097 20.91 L 151.356 25.179 L 154.784 29.643 L 157.336 34.117 L 159.104 38.936 L 159.995 43.657 L 159.981 48.672 L 159.104 53.438 L 157.336 58.222 L 154.784 62.73 L 151.356 67.194 L 147.128 71.41 L 142.286 75.271 L 136.629 78.892 L 130.373 82.149 L 123.686 84.945 L 116.384 87.386 L 108.728 89.356 L 100.843 90.838 L 92.557 91.859 L 84.164 92.374 L 75.632 92.365 L 67.439 91.859 L 59.322 90.865 L 51.344 89.365 L 43.611 87.386 L 36.233 84.918 L 29.623 82.149 L 23.351 78.883 L 17.709 75.271 L 12.928 71.464 L 8.639 67.194 L 5.227 62.775 L 2.613 58.124 L 0.892 53.438 L 0 48.592 L 0 43.782 L 0.892 38.936 L 2.613 34.25 L 5.227 29.599 L 8.639 25.179 L 12.867 20.963 L 17.709 17.103 L 23.351 13.49 Z" fill="rgb(0, 53, 51)" height="92.37355058823529px" id="UKafYhxUp" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(75.05 69.207)" width="159.99511058823543px"/><path d="M 29.623 10.224 L 36.309 7.429 L 43.611 4.988 L 51.344 3.009 L 59.322 1.509 L 67.439 0.515 L 75.693 0.009 L 84.164 0 L 92.557 0.515 L 100.919 1.544 L 108.728 3.018 L 116.384 4.988 L 123.793 7.455 L 130.373 10.224 L 136.629 13.481 L 142.286 17.103 L 147.097 20.91 L 151.356 25.179 L 154.784 29.643 L 157.336 34.117 L 159.104 38.936 L 159.995 43.657 L 159.981 48.672 L 159.104 53.438 L 157.336 58.222 L 154.784 62.73 L 151.356 67.194 L 147.128 71.41 L 142.286 75.271 L 136.629 78.892 L 130.373 82.149 L 123.686 84.945 L 116.384 87.386 L 108.728 89.356 L 100.843 90.838 L 92.557 91.859 L 84.164 92.373 L 75.632 92.365 L 67.439 91.859 L 59.322 90.865 L 51.344 89.365 L 43.611 87.386 L 36.233 84.918 L 29.623 82.149 L 23.351 78.883 L 17.709 75.271 L 12.928 71.463 L 8.639 67.194 L 5.227 62.775 L 2.613 58.124 L 0.892 53.438 L 0 48.592 L 0 43.781 L 0.892 38.936 L 2.613 34.25 L 5.227 29.599 L 8.639 25.179 L 12.867 20.963 L 17.709 17.103 L 23.351 13.49 Z" fill="rgb(0, 53, 51)" height="92.3733688235294px" id="BTS7eFR5p" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(75.05 48.404)" width="159.99511058823543px"/><path d="M 128.886 85.255 L 0 105.189 L 0 19.934 L 128.886 0 Z" fill="transparent" height="105.18923470588237px" id="XpYvdAzW3" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="round" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(57.724 4.311)" width="128.88608117646865px"/><path d="M 92.835 53.589 L 92.835 138.028 L 0 84.439 L 0 0 Z" fill="transparent" height="138.02757352941174px" id="K8lS4_UO3" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="round" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(192.202 5.927)" width="92.8345058823547px"/><path d="M 30.371 77.481 L 0 142.926 L 0 65.41 L 30.371 0 Z" fill="transparent" height="142.92631411764705px" id="ckGqTr2MB" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="round" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(21.656 34.705)" width="30.37088294117827px"/><path d="M 30.371 77.481 L 0 142.928 L 0 65.411 L 30.371 0 Z" fill="transparent" height="142.9275864705882px" id="r3233RfUB" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="round" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(254.683 70.769)" width="30.371064705883697px"/><path d="M 92.835 53.589 L 92.835 138.027 L 0 84.439 L 0 0 Z" fill="transparent" height="138.02721000000003px" id="LSrhVSYKp" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="round" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(21.656 104.548)" width="92.83486941176557px"/><path d="M 128.886 85.255 L 0 105.19 L 0 19.934 L 128.886 0 Z" fill="transparent" height="105.18959823529411px" id="x2Xopuli2" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="round" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(120.064 138.931)" width="128.88626294117825px"/><path d="M 29.623 10.224 L 36.309 7.429 L 43.611 4.988 L 51.344 3.009 L 59.322 1.509 L 67.439 0.515 L 75.693 0.009 L 84.164 0 L 92.557 0.515 L 100.919 1.544 L 108.728 3.017 L 116.384 4.988 L 123.793 7.455 L 130.373 10.224 L 136.629 13.481 L 142.286 17.103 L 147.097 20.91 L 151.356 25.179 L 154.784 29.643 L 157.336 34.116 L 159.104 38.936 L 159.995 43.657 L 159.981 48.672 L 159.104 53.438 L 157.336 58.221 L 154.784 62.73 L 151.356 67.194 L 147.128 71.41 L 142.286 75.271 L 136.629 78.892 L 130.373 82.149 L 123.686 84.945 L 116.384 87.385 L 108.728 89.356 L 100.843 90.838 L 92.557 91.859 L 84.164 92.373 L 75.632 92.364 L 67.439 91.859 L 59.322 90.865 L 51.344 89.365 L 43.611 87.385 L 36.233 84.918 L 29.623 82.149 L 23.351 78.883 L 17.709 75.271 L 12.928 71.463 L 8.639 67.194 L 5.227 62.774 L 2.613 58.124 L 0.892 53.438 L 0 48.592 L 0 43.781 L 0.892 38.936 L 2.613 34.249 L 5.227 29.599 L 8.639 25.179 L 12.867 20.963 L 17.709 17.103 L 23.351 13.49 Z" fill="rgb(0, 53, 51)" height="92.3733688235294px" id="dtqTIoHPq" stroke-dasharray="" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-width="5.69" stroke="rgb(180, 209, 63)" transform="translate(75.05 30.156)" width="159.99511058823543px"/></svg>)

" width="309px"><path d="M 0 0 C 62.424 52.356 97.323 76.699 124.122 133.612 C 125.774 137.121 129.275 139.414 133.153 139.414 L 178.332 139.414 C 182.27 139.414 185.824 137.027 187.434 133.433 C 220.347 59.939 255.786 56.508 309 0 C 223.902 11.24 92.218 13.79 0 0 Z" fill="rgb(244, 255, 200)" height="139.41414141414143px" id="YPPdTHgjp" width="309px"/></g></svg>)

" width="291.547144895145px"><path d="M 2.159 40.336 L 81.816 193.109 C 85.087 199.382 91.575 203.316 98.649 203.316 L 199.157 203.316 C 206.445 203.316 213.09 199.143 216.257 192.578 L 289.654 40.384 C 294.95 29.401 288.66 16.33 276.702 13.944 C 186.518 -4.05 102.962 -5.096 14.535 13.537 C 2.503 16.072 -3.526 29.434 2.159 40.336 Z" fill="rgb(174, 218, 0)" height="203.31595618278868px" id="beF0XCFO6" transform="translate(0 0)" width="291.54714489452647px"/></g></svg>)

" width="279.949712674067px"><path d="M 1.851 35.23 L 64.467 192.416 C 68.34 202.139 77.749 208.518 88.214 208.518 L 194.612 208.518 C 205.187 208.518 214.67 202.007 218.469 192.138 L 278.208 36.927 C 285.378 18.296 269.348 -1.055 249.578 1.717 C 168.185 13.131 109.4 10.303 29.167 0.211 C 9.712 -2.236 -5.406 17.013 1.851 35.23 Z" fill="rgb(145, 181, 0)" height="208.51809526570761px" id="tGoxWLGVd" transform="translate(0 0)" width="279.94971259877605px"/></g></svg>)

[Try Potpie →](https://app.potpie.ai/) [Book a demo](https://cal.com/team/potpie/potpie-s-product-demo)

Recommended Blogs

\\
\\
Evals\\
\\
Evaluating AI Coding Agents in the Real World\\
\\
\\
\\
Kshitij Mishra\\
\\
Apr 9, 2026](/content/blog/evaluating-ai-coding-agents-in-the-real-world/index.html)

\\
\\
compliance\\
\\
Compliance Is Architecture: Why Your AI Agent Needs a Context Graph\\
\\
\\
\\
Yash Krishnan\\
\\
Apr 9, 2026](/content/blog/compliance-is-architecture-why-your-ai-agent-needs-a-context-graph/index.html)

\\
\\
Complaince\\
\\
Compliance as Architecture: Building Trustworthy AI from the Ground Up\\
\\
\\
\\
Yash Krishan\\
\\
Feb 2, 2026](/content/blog/compliance-as-architecture-building-trustworthy-ai-from-the-ground-up/index.html)

\\
\\
Product\\
\\
How Customer Onboarding Works at Potpie\\
\\
\\
\\
Kshitij Mishra\\
\\
Mar 18, 2026](/content/blog/how-onboarding-works-at-potpie/index.html)

\\
\\
Knowledge Graph\\
\\
Building a Distributed Knowledge Graph Pipeline\\
\\
\\
\\
Dhiren Mathur\\
\\
Mar 16, 2026](/content/blog/building-a-distributed-knowledge-graph-pipeline/index.html)

\\
\\
Evals\\
\\
Repository Intelligence: Building the Next Generation of Agent Evaluation Data\\
\\
\\
\\
Deeptendu\\
\\
Feb 27, 2026](/content/blog/the-agent-evaluation-gap/index.html)

\\
\\
Agents\\
\\
AI Memory is Broken: we need brains, not hard drives\\
\\
\\
\\
Deepesh Genani\\
\\
Feb 4, 2026](/content/blog/ai-memory-is-broken-we-need-brains-not-hard-drives/index.html)

\\
\\
Behind the scenes : Potpie SWE Bench Agent \\
\\
\\
\\
Nandan\\
\\
Jan 29, 2026](/content/blog/behind-the-scenes-potpie-swe-bench-agent/index.html)

\\
\\
Engineering Agents\\
\\
Agentic COSS 2025\\
\\
\\
\\
Aditi Kothari\\
\\
Mar 20, 2025](/content/blog/agentic-coss-2025/index.html)

\\
\\
Open Source\\
\\
Open-source custom AI agents \\
\\
\\
\\
Aditi Kothari\\
\\
Mar 20, 2025](/content/blog/open-source-custom-ai-agents/index.html)

\\
\\
Product\\
\\
Release of New web access feature\\
\\
\\
\\
Ayush Thakur\\
\\
Feb 20, 2025](/content/blog/release-of-new-web-access-feature/index.html)

\\
\\
Product\\
\\
Deconstructing Potpie’s Debugging agent\\
\\
\\
\\
Dhiren Mathur\\
\\
Nov 15, 2025](/content/blog/deconstructing-potpie%E2%80%99s-debugging-agent/index.html)

\\
\\
Open Source\\
\\
Leveraging Codebase Knowledge Graphs for Agentic Code Generation\\
\\
\\
\\
Dhiren Mathur\\
\\
Oct 15, 2025](/content/blog/leveraging-codebase-knowledge-graphs-for-agentic-code-generation/index.html)

Spec driven development for large scale engineering

Product

[Enterprise](/content/enterprise/index.html)

[Use-cases](/#product)

[Blog](/content/blog/index.html)

[Pricing](/#home-pricing)

[Potpie for VS Code](https://marketplace.visualstudio.com/items?itemName=PotpieAI.potpie-vscode-extension)

[Documentation](https://docs.potpie.ai/introduction)

Company

[Trust Center](https://trust.potpie.ai/)

[Press](https://www.forbes.com/sites/davidprosser/2026/02/23/how-poptie-plans-to-help-enterprises-smash-the-ai-agent-barrier/)

[Careers](https://wellfound.com/company/potpie-ai/jobs)

[Open Source](https://github.com/potpie-ai/potpie)

[Contact Us](/content/contact/index.html)

Legal

[Privacy Policy](/content/legal/privacy-policy/index.html)

[Terms](/content/legal/terms-of-service/index.html)

© 2026 Potpie. All rights reserved.

\[CODEBASE Q&A AGENT\]
