Add AI Badgr as OpenAI-compatible provider

docs/my-website/docs/providers/aibadgr.md

@@ -0,0 +1,380 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# AI Badgr (Budget/Utility, OpenAI-compatible)
+
+## Overview
+
+| Property | Details |
+|-------|-------|
+| Description | AI Badgr is a budget-friendly, utility-focused provider offering OpenAI-compatible APIs for LLMs. Ideal for cost-conscious applications and high-volume workloads. |
+| Provider Route on LiteLLM | `aibadgr/` |
+| Link to Provider Doc | [AI Badgr Documentation ↗](https://aibadgr.com) |
+| Base URL | `https://aibadgr.com/api/v1` |
+| Supported Operations | [`/chat/completions`](#sample-usage) |
+
+<br />
+<br />
+
+**We support ALL AI Badgr models, just set `aibadgr/` as a prefix when sending completion requests**
+
+## Available Models
+
+AI Badgr offers three tiers of models optimized for different use cases and budgets:
+
+### Tier-Based Models (Recommended)
+
+| Model | Description | Use Case |
+|-------|-------------|----------|
+| `aibadgr/basic` | Entry-level model for simple tasks | Basic text generation, simple Q&A |
+| `aibadgr/normal` | Balanced performance and cost | General-purpose applications |
+| `aibadgr/premium` | Best performance tier | Complex reasoning, production workloads |
+
+### Power-User Model Names
+
+For advanced users who prefer specific model implementations:
+
+| Model | Maps To | Description |
+|-------|---------|-------------|
+| `aibadgr/phi-3-mini` | basic | Microsoft Phi-3 Mini |
+| `aibadgr/mistral-7b` | normal | Mistral 7B base model |
+| `aibadgr/llama3-8b-instruct` | premium | Meta Llama 3 8B Instruct |
+
+:::info
+OpenAI model names are accepted and automatically mapped to appropriate AI Badgr models.
+:::
+
+## Required Variables
+
+```python showLineNumbers title="Environment Variables"
+os.environ["AIBADGR_API_KEY"] = ""  # your AI Badgr API key
+```
+
+Get your API key from [AI Badgr dashboard](https://aibadgr.com).
+
+## Usage - LiteLLM Python SDK
+
+### Non-streaming
+
+```python showLineNumbers title="AI Badgr Non-streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["AIBADGR_API_KEY"] = ""  # your AI Badgr API key
+
+messages = [{"content": "What is the capital of France?", "role": "user"}]
+
+# AI Badgr call with premium tier
+response = completion(
+    model="aibadgr/premium", 
+    messages=messages
+)
+
+print(response)
+```
+
+### Streaming
+
+```python showLineNumbers title="AI Badgr Streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["AIBADGR_API_KEY"] = ""  # your AI Badgr API key
+
+messages = [{"content": "Write a short poem about AI", "role": "user"}]
+
+# AI Badgr call with streaming
+response = completion(
+    model="aibadgr/premium", 
+    messages=messages,
+    stream=True
+)
+
+for chunk in response:
+    print(chunk)
+```
+
+### Using Different Tiers
+
+```python showLineNumbers title="AI Badgr Tier Selection"
+import os
+import litellm
+from litellm import completion
+
+os.environ["AIBADGR_API_KEY"] = ""  # your AI Badgr API key
+
+# Basic tier for simple tasks
+basic_response = completion(
+    model="aibadgr/basic", 
+    messages=[{"role": "user", "content": "Say hello"}]
+)
+
+# Normal tier for general use
+normal_response = completion(
+    model="aibadgr/normal", 
+    messages=[{"role": "user", "content": "Explain photosynthesis"}]
+)
+
+# Premium tier for complex tasks
+premium_response = completion(
+    model="aibadgr/premium", 
+    messages=[{"role": "user", "content": "Write a detailed technical explanation"}]
+)
+```
+
+### Function Calling
+
+```python showLineNumbers title="AI Badgr Function Calling"
+import os
+import litellm
+from litellm import completion
+
+os.environ["AIBADGR_API_KEY"] = ""  # your AI Badgr API key
+
+tools = [
+    {
+        "type": "function",
+        "function": {
+            "name": "get_weather",
+            "description": "Get the current weather in a location",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "location": {
+                        "type": "string",
+                        "description": "The city and state, e.g. San Francisco, CA"
+                    },
+                    "unit": {
+                        "type": "string",
+                        "enum": ["celsius", "fahrenheit"]
+                    }
+                },
+                "required": ["location"]
+            }
+        }
+    }
+]
+
+response = completion(
+    model="aibadgr/premium",
+    messages=[{"role": "user", "content": "What's the weather like in New York?"}],
+    tools=tools,
+    tool_choice="auto"
+)
+
+print(response)
+```
+
+## Usage - LiteLLM Proxy
+
+Add the following to your LiteLLM Proxy configuration file:
+
+```yaml showLineNumbers title="config.yaml"
+model_list:
+  - model_name: budget-basic
+    litellm_params:
+      model: aibadgr/basic
+      api_key: os.environ/AIBADGR_API_KEY
+
+  - model_name: budget-normal
+    litellm_params:
+      model: aibadgr/normal
+      api_key: os.environ/AIBADGR_API_KEY
+
+  - model_name: budget-premium
+    litellm_params:
+      model: aibadgr/premium
+      api_key: os.environ/AIBADGR_API_KEY
+```
+
+Start your LiteLLM Proxy server:
+
+```bash showLineNumbers title="Start LiteLLM Proxy"
+litellm --config config.yaml
+
+# RUNNING on http://0.0.0.0:4000
+```
+
+<Tabs>
+<TabItem value="openai-sdk" label="OpenAI SDK">
+
+```python showLineNumbers title="AI Badgr via Proxy - Non-streaming"
+from openai import OpenAI
+
+# Initialize client with your proxy URL
+client = OpenAI(
+    base_url="http://localhost:4000",  # Your proxy URL
+    api_key="your-proxy-api-key"       # Your proxy API key
+)
+
+# Non-streaming response
+response = client.chat.completions.create(
+    model="budget-premium",
+    messages=[{"role": "user", "content": "Explain quantum computing in simple terms"}]
+)
+
+print(response.choices[0].message.content)
+```
+
+```python showLineNumbers title="AI Badgr via Proxy - Streaming"
+from openai import OpenAI
+
+# Initialize client with your proxy URL
+client = OpenAI(
+    base_url="http://localhost:4000",  # Your proxy URL
+    api_key="your-proxy-api-key"       # Your proxy API key
+)
+
+# Streaming response
+response = client.chat.completions.create(
+    model="budget-premium",
+    messages=[{"role": "user", "content": "Write a Python function to sort a list"}],
+    stream=True
+)
+
+for chunk in response:
+    if chunk.choices[0].delta.content is not None:
+        print(chunk.choices[0].delta.content, end="")
+```
+
+</TabItem>
+
+<TabItem value="litellm-sdk" label="LiteLLM SDK">
+
+```python showLineNumbers title="AI Badgr via Proxy - LiteLLM SDK"
+import litellm
+
+# Configure LiteLLM to use your proxy
+response = litellm.completion(
+    model="litellm_proxy/budget-premium",
+    messages=[{"role": "user", "content": "What are the benefits of renewable energy?"}],
+    api_base="http://localhost:4000",
+    api_key="your-proxy-api-key"
+)
+
+print(response.choices[0].message.content)
+```
+
+```python showLineNumbers title="AI Badgr via Proxy - LiteLLM SDK Streaming"
+import litellm
+
+# Configure LiteLLM to use your proxy with streaming
+response = litellm.completion(
+    model="litellm_proxy/budget-premium",
+    messages=[{"role": "user", "content": "Implement a binary search algorithm"}],
+    api_base="http://localhost:4000",
+    api_key="your-proxy-api-key",
+    stream=True
+)
+
+for chunk in response:
+    if hasattr(chunk.choices[0], 'delta') and chunk.choices[0].delta.content is not None:
+        print(chunk.choices[0].delta.content, end="")
+```
+
+</TabItem>
+
+<TabItem value="curl" label="cURL">
+
+```bash showLineNumbers title="AI Badgr via Proxy - cURL"
+curl http://localhost:4000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer your-proxy-api-key" \
+  -d '{
+    "model": "budget-premium",
+    "messages": [{"role": "user", "content": "What is machine learning?"}]
+  }'
+```
+
+```bash showLineNumbers title="AI Badgr via Proxy - cURL Streaming"
+curl http://localhost:4000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer your-proxy-api-key" \
+  -d '{
+    "model": "budget-premium",
+    "messages": [{"role": "user", "content": "Write a REST API in Python"}],
+    "stream": true
+  }'
+```
+
+</TabItem>
+</Tabs>
+
+For more detailed information on using the LiteLLM Proxy, see the [LiteLLM Proxy documentation](../providers/litellm_proxy).
+
+## Supported OpenAI Parameters
+
+AI Badgr supports the following OpenAI-compatible parameters:
+
+| Parameter | Type | Description |
+|-----------|------|-------------|
+| `messages` | array | **Required**. Array of message objects with 'role' and 'content' |
+| `model` | string | **Required**. Model ID (e.g., basic, normal, premium) |
+| `stream` | boolean | Optional. Enable streaming responses |
+| `temperature` | float | Optional. Sampling temperature (0.0 to 2.0) |
+| `top_p` | float | Optional. Nucleus sampling parameter |
+| `max_tokens` | integer | Optional. Maximum tokens to generate |
+| `frequency_penalty` | float | Optional. Penalize frequent tokens |
+| `presence_penalty` | float | Optional. Penalize tokens based on presence |
+| `stop` | string/array | Optional. Stop sequences |
+| `n` | integer | Optional. Number of completions to generate |
+| `tools` | array | Optional. List of available tools/functions |
+| `tool_choice` | string/object | Optional. Control tool/function calling |
+| `response_format` | object | Optional. Response format specification |
+| `seed` | integer | Optional. Random seed for reproducibility |
+| `user` | string | Optional. User identifier |
+
+## Advanced Usage
+
+### Custom API Base
+
+If you need to override the API base URL:
+
+```python showLineNumbers title="Custom API Base"
+import litellm
+
+response = litellm.completion(
+    model="aibadgr/premium",
+    messages=[{"role": "user", "content": "Hello"}],
+    api_base="https://custom-aibadgr-endpoint.com/api/v1",
+    api_key="your-api-key"
+)
+```
+
+Or use the environment variable:
+
+```python showLineNumbers title="Custom API Base via Environment"
+import os
+import litellm
+
+os.environ["AIBADGR_BASE_URL"] = "https://custom-aibadgr-endpoint.com/api/v1"
+os.environ["AIBADGR_API_KEY"] = "your-api-key"
+
+response = litellm.completion(
+    model="aibadgr/premium",
+    messages=[{"role": "user", "content": "Hello"}]
+)
+```
+
+## Best Practices
+
+### Choose the Right Tier
+
+- **basic**: Use for simple, high-volume tasks where speed and cost matter more than sophistication
+- **normal**: Good balance for most applications
+- **premium**: Best for complex reasoning, production-critical workloads, or when quality is paramount
+
+### Cost Optimization
+
+AI Badgr is designed for budget-conscious applications:
+
+- Start with `basic` tier and upgrade only if needed
+- Use `normal` tier for most production workloads
+- Reserve `premium` tier for complex reasoning tasks
+
+## Additional Resources
+
+- [AI Badgr Official Documentation](https://aibadgr.com)
+- [AI Badgr Dashboard](https://aibadgr.com)

docs/my-website/sidebars.js

@@ -665,6 +665,7 @@ const sidebars = {
         },
         "providers/litellm_proxy",
         "providers/ai21",
+        "providers/aibadgr",
         "providers/aiml",
         "providers/aleph_alpha",
         "providers/anyscale",

litellm/llms/openai_like/providers.json

@@ -1,4 +1,9 @@
 {
+  "aibadgr": {
+    "base_url": "https://aibadgr.com/api/v1",
+    "api_key_env": "AIBADGR_API_KEY",
+    "api_base_env": "AIBADGR_BASE_URL"
+  },
   "publicai": {
     "base_url": "https://api.publicai.co/v1",
     "api_key_env": "PUBLICAI_API_KEY",