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fix: fix product name
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‎README.md‎

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#### LLM Configuration
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<pre><code>config.set_provider_config("llm", "(LLMName)", "(Arguments dict)")</code></pre>
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<p>The "LLMName" can be one of the following: ["DeepSeek", "OpenAI", "XAI", "SiliconFlow", "Aliyun", "PPIO", "TogetherAI", "Gemini", "Ollama", "Novita", "JiekouAI"]</p>
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<p>The "LLMName" can be one of the following: ["DeepSeek", "OpenAI", "XAI", "SiliconFlow", "Aliyun", "PPIO", "TogetherAI", "Gemini", "Ollama", "Novita", "Jiekou.AI"]</p>
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<p> The "Arguments dict" is a dictionary that contains the necessary arguments for the LLM class.</p>
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<details>
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</details>
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<details>
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<summary>Example (Claude Sonnet 4.5 from JiekouAI)</summary>
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<p> Make sure you have prepared your JiekouAI API KEY as an env variable <code>JIEKOU_API_KEY</code>. You can create an API Key <a href="https://jiekou.ai/settings/key-management?utm_source=github_deep-searcher">here</a>. </p>
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<summary>Example (Claude Sonnet 4.5 from Jiekou.AI)</summary>
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<p> Make sure you have prepared your Jiekou.AI API KEY as an env variable <code>JIEKOU_API_KEY</code>. You can create an API Key <a href="https://jiekou.ai/settings/key-management?utm_source=github_deep-searcher">here</a>. </p>
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<pre><code>config.set_provider_config("llm", "JiekouAI", {"model": "claude-sonnet-4-5-20250929"})</code></pre>
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<p> More details about JiekouAI: https://docs.jiekou.ai/docs/support/quickstart?utm_source=github_deep-searcher </p>
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<p> More details about Jiekou.AI: https://docs.jiekou.ai/docs/support/quickstart?utm_source=github_deep-searcher </p>
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</details>
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<details>
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</details>
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<details>
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<summary>Example (JiekouAI embedding)</summary>
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<p> Make sure you have prepared your JiekouAI API KEY as an env variable <code>JIEKOU_API_KEY</code>.</p>
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<summary>Example (Jiekou.AI embedding)</summary>
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<p> Make sure you have prepared your Jiekou.AI API KEY as an env variable <code>JIEKOU_API_KEY</code>.</p>
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<pre><code>config.set_provider_config("embedding", "JiekouAIEmbedding", {"model": "qwen/qwen3-embedding-8b"})</code></pre>
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<p> More details about JiekouAI: https://docs.jiekou.ai/docs/support/quickstart?utm_source=github_deep-searcher </p>
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<p> More details about Jiekou.AI: https://docs.jiekou.ai/docs/support/quickstart?utm_source=github_deep-searcher </p>
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</details>
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<details>
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- [PPIO](https://ppinfra.com/model-api/product/llm-api?utm_source=github_deep-searcher) (`PPIO_API_KEY` env variable required)
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- [Novita AI](https://novita.ai/docs/api-reference/model-apis-llm-create-embeddings?utm_source=github_deep-searcher&utm_medium=github_readme&utm_campaign=link) (`NOVITA_API_KEY` env variable required)
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- [IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai/foundation-models#ibmembedding) (`WATSONX_APIKEY`, `WATSONX_URL`, `WATSONX_PROJECT_ID` env variables required)
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- [JiekouAI](https://jiekou.ai/?utm_source=github_deep-searcher) (`JIEKOU_API_KEY` env variable required)
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- [Jiekou.AI](https://jiekou.ai/?utm_source=github_deep-searcher) (`JIEKOU_API_KEY` env variable required)
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### 🔹 LLM Support
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- [OpenAI](https://platform.openai.com/docs/models) (`OPENAI_API_KEY` env variable required)
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- [Ollama](https://ollama.com/)
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- [Novita AI](https://novita.ai/docs/guides/introduction?utm_source=github_deep-searcher&utm_medium=github_readme&utm_campaign=link) (`NOVITA_API_KEY` env variable required)
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- [IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai/foundation-models#ibmfm) (`WATSONX_APIKEY`, `WATSONX_URL`, `WATSONX_PROJECT_ID` env variable required)
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- [JiekouAI](https://jiekou.ai/?utm_source=github_deep-searcher) (`JIEKOU_API_KEY` env variable required)
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- [Jiekou.AI](https://jiekou.ai/?utm_source=github_deep-searcher) (`JIEKOU_API_KEY` env variable required)
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### 🔹 Document Loader
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- Local File

‎deepsearcher/config.yaml‎

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## api_key: "sk_xxxxxx" # Uncomment to override the `PPIO_API_KEY` set in the environment variable
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## base_url: ""
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# provider: "JiekouAI"
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# provider: "Jiekou.AI"
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# config:
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# model: "claude-sonnet-4-5-20250929"
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## api_key: "xxxx" # Uncomment to override the `JIEKOU_API_KEY` set in the environment variable

‎deepsearcher/embedding/jiekouai_embedding.py‎

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from deepsearcher.embedding.base import BaseEmbedding
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# TODO: Update with actual JiekouAI model dimensions when available
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# TODO: Update with actual Jiekou.AI model dimensions when available
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JIEKOUAI_MODEL_DIM_MAP = {
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"qwen/qwen3-embedding-0.6b": 1024,
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"qwen/qwen3-embedding-8b": 1024,
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class JiekouAIEmbedding(BaseEmbedding):
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"""
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JiekouAI embedding model implementation.
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Jiekou.AI embedding model implementation.
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This class provides an interface to the JiekouAI embedding API, which offers
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This class provides an interface to the Jiekou.AI embedding API, which offers
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various embedding models for text processing.
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"""
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def __init__(self, model="qwen/qwen3-embedding-8b", batch_size=32, **kwargs):
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"""
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Initialize the JiekouAI embedding model.
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Initialize the Jiekou.AI embedding model.
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Args:
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model (str): The model identifier to use for embeddings. Default is "baai/bge-m3".
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batch_size (int): Maximum number of texts to process in a single batch. Default is 32.
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**kwargs: Additional keyword arguments.
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- api_key (str, optional): The JiekouAI API key. If not provided,
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- api_key (str, optional): The Jiekou.AI API key. If not provided,
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it will be read from the JIEKOU_API_KEY environment variable.
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- model_name (str, optional): Alternative way to specify the model.
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‎deepsearcher/llm/jiekouai.py‎

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class JiekouAI(BaseLLM):
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"""
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JiekouAI language model implementation.
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Jiekou.AI language model implementation.
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This class provides an interface to interact with language models
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hosted on the JiekouAI platform.
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hosted on the Jiekou.AI platform.
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Attributes:
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model (str): The model identifier to use on JiekouAI platform.
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client: The OpenAI-compatible client instance for JiekouAI API.
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model (str): The model identifier to use on Jiekou.AI platform.
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client: The OpenAI-compatible client instance for Jiekou.AI API.
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"""
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def __init__(self, model: str = "claude-sonnet-4-5-20250929", **kwargs):
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"""
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Initialize a JiekouAI language model client.
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Initialize a Jiekou.AI language model client.
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Args:
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model (str, optional): The model identifier to use. Defaults to "claude-sonnet-4-5-20250929".
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**kwargs: Additional keyword arguments to pass to the OpenAI client.
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- api_key: JiekouAI API key. If not provided, uses JIEKOU_API_KEY environment variable.
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- base_url: JiekouAI API base URL. If not provided, defaults to "https://api.jiekou.ai/openai/v1".
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- api_key: Jiekou.AI API key. If not provided, uses JIEKOU_API_KEY environment variable.
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- base_url: Jiekou.AI API base URL. If not provided, defaults to "https://api.jiekou.ai/openai/v1".
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"""
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from openai import OpenAI as OpenAI_
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def chat(self, messages: List[Dict]) -> ChatResponse:
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"""
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Send a chat message to the JiekouAI model and get a response.
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Send a chat message to the Jiekou.AI model and get a response.
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Args:
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messages (List[Dict]): A list of message dictionaries, typically in the format

‎docs/configuration/embedding.md‎

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| **NovitaEmbedding** | Novita AI embedding | Cost-effective |
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| **SentenceTransformerEmbedding** | Sentence Transfomer Embedding | Self-hosted option |
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| **IBM watsonx.ai** | Various options | IBM's Enterprise AI platform |
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| **JiekouAIEmbedding** | JiekouAI embedding | High quality, cost-effective |
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| **JiekouAIEmbedding** | Jiekou.AI embedding | High quality, cost-effective |
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## 🔍 Provider Examples
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```
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*Requires `pip install ibm-watsonx-ai`*
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??? example "JiekouAI"
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??? example "Jiekou.AI"
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```python
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config.set_provider_config("embedding", "JiekouAIEmbedding", {"model": "qwen/qwen3-embedding-8b"})

‎docs/configuration/llm.md‎

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| **Bedrock** | Amazon Bedrock LLMs | anthropic.claude, ai21.j2 |
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| **Novita** | Novita AI models | Various options |
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| **IBM watsonx.ai** | IBM Enterprise AI platform | Various options |
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| **JiekouAI** | JiekouAI models | Claude, OpenAI, Deepseek, Grok, Qwen, etc. |
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| **Jiekou.AI** | Jiekou.AI models | Claude, OpenAI, Deepseek, Grok, Qwen, etc. |
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More details about WatsonX: [https://www.ibm.com/products/watsonx-ai/foundation-models](https://www.ibm.com/products/watsonx-ai/foundation-models)
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```
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??? example "Jiekou.AI"
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config.set_provider_config("llm", "JiekouAI", {"model": "claude-sonnet-4-5-20250929"})
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```
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*Requires `JIEKOU_API_KEY` environment variable*
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More details about JiekouAI: [https://docs.jiekou.ai/docs/support/quickstart](https://docs.jiekou.ai/docs/support/quickstart)
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More details about Jiekou.AI: [https://docs.jiekou.ai/docs/support/quickstart](https://docs.jiekou.ai/docs/support/quickstart)
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‎docs/integrations/index.md‎

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| **[PPIO](https://ppinfra.com/model-api/product/llm-api)** | `PPIO_API_KEY` | Flexible cloud embeddings |
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| **[Novita AI](https://novita.ai/docs/api-reference/model-apis-llm-create-embeddings)** | `NOVITA_API_KEY` | Rich model selection |
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| **[IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai/foundation-models#ibmembedding)** | `WATSONX_APIKEY`, `WATSONX_URL`, `WATSONX_PROJECT_ID` | IBM's Enterprise AI platform |
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| **[JiekouAI](https://jiekou.ai/?utm_source=github_deep-searcher)** | `JIEKOU_API_KEY` | JiekouAI's embedding models |
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| **[Jiekou.AI](https://jiekou.ai/?utm_source=github_deep-searcher)** | `JIEKOU_API_KEY` | Jiekou.AI's embedding models |
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## 🧠 Large Language Models {#llm-support}
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| **[Ollama](https://ollama.com/)** | None | Local LLM deployment |
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| **[Novita AI](https://novita.ai/docs/guides/introduction)** | `NOVITA_API_KEY` | Diverse AI services |
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| **[IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai/foundation-models#ibmfm)** | `WATSONX_APIKEY`, `WATSONX_URL`, `WATSONX_PROJECT_ID` | IBM's Enterprise AI platform |
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| **[JiekouAI](https://jiekou.ai/?utm_source=github_deep-searcher)** | `JIEKOU_API_KEY` | Various open-source and closed-source models |
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| **[Jiekou.AI](https://jiekou.ai/?utm_source=github_deep-searcher)** | `JIEKOU_API_KEY` | Various open-source and closed-source models |
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## 📄 Document Loader {#document-loader}
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‎env.example‎

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# PPIO API Key (required if using PPIO models)
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PPIO_API_KEY=your_ppio_api_key_here
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# JiekouAI API Key (required if using JiekouAI models)
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# Jiekou.AI API Key (required if using Jiekou.AI models)
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JIEKOU_API_KEY=your_jiekouai_api_key_here
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# Together AI API Key (required if using Together AI models)

‎tests/embedding/test_jiekouai_embedding.py‎

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import os
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import requests
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from deepsearcher.embedding import JiekouAIEmbedding
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‎tests/llm/test_jiekouai.py‎

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class TestJiekouAI(unittest.TestCase):
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"""Tests for the JiekouAI LLM provider."""
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"""Tests for the Jiekou.AI LLM provider."""
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def setUp(self):
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"""Set up test fixtures."""

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