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Add documentation for perplexity

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Sameer Kankute 2026-02-10 17:44:00 +05:30
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287
docs/my-website/docs/providers/perplexity.md
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@ -120,6 +120,293 @@ All models listed here https://docs.perplexity.ai/docs/model-cards are supported
## Agentic Research API (Responses API)
Requires v1.72.6+
### Using Presets
Presets provide optimized defaults for specific use cases. Start with a preset for quick setup:
<Tabs>
<TabItem value="sdk" label="SDK">
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
# Using the pro-search preset
response = responses(
model="perplexity/preset/pro-search",
input="What are the latest developments in AI?",
custom_llm_provider="perplexity",
)
print(response.output)
```
</TabItem>
<TabItem value="proxy" label="Proxy">
1. Setup config.yaml
```yaml
model_list:
- model_name: perplexity-pro-search
litellm_params:
model: perplexity/preset/pro-search
api_key: os.environ/PERPLEXITY_API_KEY
```
2. Start proxy
```bash
litellm --config /path/to/config.yaml
```
3. Test it!
```bash
curl http://0.0.0.0:4000/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer anything" \
-d '{
"model": "perplexity-pro-search",
"input": "What are the latest developments in AI?"
}'
```
</TabItem>
</Tabs>
### Using Third-Party Models
Access models from OpenAI, Anthropic, Google, xAI, and other providers through Perplexity's unified API:
<Tabs>
<TabItem value="openai" label="OpenAI">
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/openai/gpt-4o",
input="Explain quantum computing in simple terms",
custom_llm_provider="perplexity",
max_output_tokens=500,
)
print(response.output)
```
</TabItem>
<TabItem value="anthropic" label="Anthropic">
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/anthropic/claude-3-5-sonnet-20241022",
input="Write a short story about a robot learning to paint",
custom_llm_provider="perplexity",
max_output_tokens=500,
)
print(response.output)
```
</TabItem>
<TabItem value="google" label="Google">
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/google/gemini-2.0-flash-exp",
input="Explain the concept of neural networks",
custom_llm_provider="perplexity",
max_output_tokens=500,
)
print(response.output)
```
</TabItem>
<TabItem value="xai" label="xAI">
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/xai/grok-2-1212",
input="What makes a good AI assistant?",
custom_llm_provider="perplexity",
max_output_tokens=500,
)
print(response.output)
```
</TabItem>
</Tabs>
### Web Search Tool
Enable web search capabilities to access real-time information:
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/openai/gpt-4o",
input="What's the weather in San Francisco today?",
custom_llm_provider="perplexity",
tools=[{"type": "web_search"}],
instructions="You have access to a web_search tool. Use it for questions about current events.",
)
print(response.output)
```
### Reasoning Effort (Responses API)
Control the reasoning effort level for reasoning-capable models:
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/openai/gpt-5.2",
input="Solve this complex problem step by step",
custom_llm_provider="perplexity",
reasoning={"effort": "high"}, # Options: low, medium, high
max_output_tokens=1000,
)
print(response.output)
```
### Multi-Turn Conversations
Use message arrays for multi-turn conversations with context:
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/anthropic/claude-3-5-sonnet-20241022",
input=[
{"type": "message", "role": "system", "content": "You are a helpful assistant."},
{"type": "message", "role": "user", "content": "What are the latest AI developments?"},
],
custom_llm_provider="perplexity",
instructions="Provide detailed, well-researched answers.",
max_output_tokens=800,
)
print(response.output)
```
### Streaming Responses
Stream responses for real-time output:
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
response = responses(
model="perplexity/openai/gpt-4o",
input="Tell me a story about space exploration",
custom_llm_provider="perplexity",
stream=True,
max_output_tokens=500,
)
for chunk in response:
if hasattr(chunk, 'type'):
if chunk.type == "response.output_text.delta":
print(chunk.delta, end="", flush=True)
```
### Supported Third-Party Models
| Provider | Model Name | Function Call |
|----------|------------|---------------|
| OpenAI | gpt-4o | `responses(model="perplexity/openai/gpt-4o", ...)` |
| OpenAI | gpt-4o-mini | `responses(model="perplexity/openai/gpt-4o-mini", ...)` |
| OpenAI | gpt-5.2 | `responses(model="perplexity/openai/gpt-5.2", ...)` |
| Anthropic | claude-3-5-sonnet-20241022 | `responses(model="perplexity/anthropic/claude-3-5-sonnet-20241022", ...)` |
| Anthropic | claude-3-5-haiku-20241022 | `responses(model="perplexity/anthropic/claude-3-5-haiku-20241022", ...)` |
| Google | gemini-2.0-flash-exp | `responses(model="perplexity/google/gemini-2.0-flash-exp", ...)` |
| Google | gemini-2.0-flash-thinking-exp | `responses(model="perplexity/google/gemini-2.0-flash-thinking-exp", ...)` |
| xAI | grok-2-1212 | `responses(model="perplexity/xai/grok-2-1212", ...)` |
| xAI | grok-2-vision-1212 | `responses(model="perplexity/xai/grok-2-vision-1212", ...)` |
### Available Presets
| Preset Name | Function Call |
|----------------|--------------------------------------------------------|
| fast-search | `responses(model="perplexity/preset/fast-search", ...)`|
| pro-search | `responses(model="perplexity/preset/pro-search", ...)` |
| deep-research | `responses(model="perplexity/preset/deep-research", ...)`|
### Complete Example
```python
from litellm import responses
import os
os.environ['PERPLEXITY_API_KEY'] = ""
# Comprehensive example with multiple features
response = responses(
model="perplexity/openai/gpt-4o",
input="Research the latest developments in quantum computing and provide sources",
custom_llm_provider="perplexity",
tools=[
{"type": "web_search"},
{"type": "fetch_url"}
],
instructions="Use web_search to find relevant information and fetch_url to retrieve detailed content from sources. Provide citations for all claims.",
max_output_tokens=1000,
temperature=0.7,
)
print(f"Response ID: {response.id}")
print(f"Model: {response.model}")
print(f"Status: {response.status}")
print(f"Output: {response.output}")
print(f"Usage: {response.usage}")
```
:::info
For more information about passing provider-specific parameters, [go here](../completion/provider_specific_params.md)

60
litellm/model_prices_and_context_window_backup.json
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@ -25614,6 +25614,66 @@
"supports_function_calling": true,
"supports_tool_choice": true
},
"perplexity/preset/pro-search": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_preset": true
},
"perplexity/openai/gpt-4o": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false
},
"perplexity/openai/gpt-4o-mini": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false
},
"perplexity/openai/gpt-5.2": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": true
},
"perplexity/anthropic/claude-3-5-sonnet-20241022": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false
},
"perplexity/anthropic/claude-3-5-haiku-20241022": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false
},
"perplexity/google/gemini-2.0-flash-exp": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false
},
"perplexity/google/gemini-2.0-flash-thinking-exp": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": true
},
"perplexity/xai/grok-2-1212": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false
},
"perplexity/xai/grok-2-vision-1212": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false
},
"publicai/aisingapore/Qwen-SEA-LION-v4-32B-IT": {
"input_cost_per_token": 0.0,
"litellm_provider": "publicai",

30
model_prices_and_context_window.json
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@ -25618,71 +25618,61 @@
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_preset": true,
"preset_name": "pro-search"
"supports_preset": true
},
"perplexity/openai/gpt-4o": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false,
"third_party_provider": "openai"
"supports_reasoning": false
},
"perplexity/openai/gpt-4o-mini": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false,
"third_party_provider": "openai"
"supports_reasoning": false
},
"perplexity/openai/gpt-5.2": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": true,
"third_party_provider": "openai"
"supports_reasoning": true
},
"perplexity/anthropic/claude-3-5-sonnet-20241022": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false,
"third_party_provider": "anthropic"
"supports_reasoning": false
},
"perplexity/anthropic/claude-3-5-haiku-20241022": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false,
"third_party_provider": "anthropic"
"supports_reasoning": false
},
"perplexity/google/gemini-2.0-flash-exp": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false,
"third_party_provider": "google"
"supports_reasoning": false
},
"perplexity/google/gemini-2.0-flash-thinking-exp": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": true,
"third_party_provider": "google"
"supports_reasoning": true
},
"perplexity/xai/grok-2-1212": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false,
"third_party_provider": "xai"
"supports_reasoning": false
},
"perplexity/xai/grok-2-vision-1212": {
"litellm_provider": "perplexity",
"mode": "responses",
"supports_web_search": true,
"supports_reasoning": false,
"third_party_provider": "xai"
"supports_reasoning": false
},
"publicai/aisingapore/Qwen-SEA-LION-v4-32B-IT": {
"input_cost_per_token": 0.0,