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update litellm to support o3-mini and deepseek. Update docs.
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@@ -38,6 +38,7 @@ Here's a detailed breakdown of supported models and their capabilities, you can
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| GPT-4 | 8,192 tokens | High-accuracy tasks, complex reasoning |
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| GPT-4 Turbo | 128,000 tokens | Long-form content, document analysis |
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| GPT-4o & GPT-4o-mini | 128,000 tokens | Cost-effective large context processing |
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| o3-mini | 200,000 tokens | Fast reasoning, complex reasoning |
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<Note>
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1 token ≈ 4 characters in English. For example, 8,192 tokens ≈ 32,768 characters or about 6,000 words.
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@@ -162,7 +163,8 @@ Here's a detailed breakdown of supported models and their capabilities, you can
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<Tab title="Others">
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| Provider | Context Window | Key Features |
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|----------|---------------|--------------|
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| Deepseek Chat | 128,000 tokens | Specialized in technical discussions |
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| Deepseek Chat | 64,000 tokens | Specialized in technical discussions |
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| Deepseek R1 | 64,000 tokens | Affordable reasoning model |
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| Claude 3 | Up to 200K tokens | Strong reasoning, code understanding |
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| Gemma Series | 8,192 tokens | Efficient, smaller-scale tasks |
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@@ -296,6 +298,10 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
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# llm: sambanova/Meta-Llama-3.1-8B-Instruct
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# llm: sambanova/BioMistral-7B
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# llm: sambanova/Falcon-180B
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# Open Router Models - Affordable reasoning
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# llm: openrouter/deepseek/deepseek-r1
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# llm: openrouter/deepseek/deepseek-chat
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```
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<Info>
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@@ -691,6 +697,27 @@ Learn how to get the most out of your LLM configuration:
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- Support for long context windows
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</Info>
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</Accordion>
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<Accordion title="Open Router">
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```python Code
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OPENROUTER_API_KEY=<your-api-key>
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```
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Example usage:
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```python Code
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llm = LLM(
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model="openrouter/deepseek/deepseek-r1",
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base_url="https://openrouter.ai/api/v1",
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api_key=OPENROUTER_API_KEY
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)
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```
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<Info>
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Open Router models:
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- openrouter/deepseek/deepseek-r1
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- openrouter/deepseek/deepseek-chat
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</Info>
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</Accordion>
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</AccordionGroup>
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## Common Issues and Solutions
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