> ## Documentation Index
> Fetch the complete documentation index at: https://docs.embedchain.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# ❓ FAQs

> Collections of all the frequently asked questions

<AccordionGroup>
  <Accordion title="Does Embedchain support OpenAI's Assistant APIs?">
    Yes, it does. Please refer to the [OpenAI Assistant docs page](/examples/openai-assistant).
  </Accordion>

  <Accordion title="How to use MistralAI language model?">
    Use the model provided on huggingface: `mistralai/Mistral-7B-v0.1`

    <CodeGroup>
      ```python main.py theme={null}
      import os
      from embedchain import App

      os.environ["HUGGINGFACE_ACCESS_TOKEN"] = "hf_your_token"

      app = App.from_config("huggingface.yaml")
      ```

      ```yaml huggingface.yaml theme={null}
      llm:
        provider: huggingface
        config:
          model: 'mistralai/Mistral-7B-v0.1'
          temperature: 0.5
          max_tokens: 1000
          top_p: 0.5
          stream: false

      embedder:
        provider: huggingface
        config:
          model: 'sentence-transformers/all-mpnet-base-v2'
      ```
    </CodeGroup>
  </Accordion>

  <Accordion title="How to use ChatGPT 4 turbo model released on OpenAI DevDay?">
    Use the model `gpt-4-turbo` provided my openai.

    <CodeGroup>
      ```python main.py theme={null}
      import os
      from embedchain import App

      os.environ['OPENAI_API_KEY'] = 'xxx'

      # load llm configuration from gpt4_turbo.yaml file
      app = App.from_config(config_path="gpt4_turbo.yaml")
      ```

      ```yaml gpt4_turbo.yaml theme={null}
      llm:
        provider: openai
        config:
          model: 'gpt-4-turbo'
          temperature: 0.5
          max_tokens: 1000
          top_p: 1
          stream: false
      ```
    </CodeGroup>
  </Accordion>

  <Accordion title="How to use GPT-4 as the LLM model?">
    <CodeGroup>
      ```python main.py theme={null}
      import os
      from embedchain import App

      os.environ['OPENAI_API_KEY'] = 'xxx'

      # load llm configuration from gpt4.yaml file
      app = App.from_config(config_path="gpt4.yaml")
      ```

      ```yaml gpt4.yaml theme={null}
      llm:
        provider: openai
        config:
          model: 'gpt-4'
          temperature: 0.5
          max_tokens: 1000
          top_p: 1
          stream: false
      ```
    </CodeGroup>
  </Accordion>

  <Accordion title="I don't have OpenAI credits. How can I use some open source model?">
    <CodeGroup>
      ```python main.py theme={null}
      from embedchain import App

      # load llm configuration from opensource.yaml file
      app = App.from_config(config_path="opensource.yaml")
      ```

      ```yaml opensource.yaml theme={null}
      llm:
        provider: gpt4all
        config:
          model: 'orca-mini-3b-gguf2-q4_0.gguf'
          temperature: 0.5
          max_tokens: 1000
          top_p: 1
          stream: false

      embedder:
        provider: gpt4all
        config:
          model: 'all-MiniLM-L6-v2'
      ```
    </CodeGroup>
  </Accordion>

  <Accordion title="How to stream response while using OpenAI model in Embedchain?">
    You can achieve this by setting `stream` to `true` in the config file.

    <CodeGroup>
      ```yaml openai.yaml theme={null}
      llm:
        provider: openai
        config:
          model: 'gpt-4o-mini'
          temperature: 0.5
          max_tokens: 1000
          top_p: 1
          stream: true
      ```

      ```python main.py theme={null}
      import os
      from embedchain import App

      os.environ['OPENAI_API_KEY'] = 'sk-xxx'

      app = App.from_config(config_path="openai.yaml")

      app.add("https://www.forbes.com/profile/elon-musk")

      response = app.query("What is the net worth of Elon Musk?")
      # response will be streamed in stdout as it is generated.
      ```
    </CodeGroup>
  </Accordion>

  <Accordion title="How to persist data across multiple app sessions?">
    Set up the app by adding an `id` in the config file. This keeps the data for future use. You can include this `id` in the yaml config or input it directly in `config` dict.

    ```python app1.py theme={null}
    import os
    from embedchain import App

    os.environ['OPENAI_API_KEY'] = 'sk-xxx'

    app1 = App.from_config(config={
      "app": {
        "config": {
          "id": "your-app-id",
        }
      }
    })

    app1.add("https://www.forbes.com/profile/elon-musk")

    response = app1.query("What is the net worth of Elon Musk?")
    ```

    ```python app2.py theme={null}
    import os
    from embedchain import App

    os.environ['OPENAI_API_KEY'] = 'sk-xxx'

    app2 = App.from_config(config={
      "app": {
        "config": {
          # this will persist and load data from app1 session
          "id": "your-app-id",
        }
      }
    })

    response = app2.query("What is the net worth of Elon Musk?")
    ```
  </Accordion>
</AccordionGroup>

#### Still have questions?

If docs aren't sufficient, please feel free to reach out to us using one of the following methods:

<Snippet file="get-help.mdx" />