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docs add examples with litellm proxy

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Ishaan Jaff 2024-08-14 17:13:26 -07:00
parent f186da28be
commit 2019682a97
1 changed files with 136 additions and 3 deletions
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139
docs/my-website/docs/providers/anthropic.md
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@ -270,7 +270,45 @@ response = await litellm.acompletion(
``` ```
</TabItem> </TabItem>
<TabItem value="proxy" label="PROXY"> <TabItem value="proxy" label="LiteLLM Proxy">
```python
import openai
client = openai.AsyncOpenAI(
api_key="anything", # litellm proxy api key
base_url="http://0.0.0.0:4000" # litellm proxy base url
)
response = await client.chat.completions.create(
model="anthropic/claude-3-5-sonnet-20240620",
messages=[
{
"role": "system",
"content": [
{
"type": "text",
"text": "You are an AI assistant tasked with analyzing legal documents.",
},
{
"type": "text",
"text": "Here is the full text of a complex legal agreement",
"cache_control": {"type": "ephemeral"},
},
],
},
{
"role": "user",
"content": "what are the key terms and conditions in this agreement?",
},
],
extra_headers={
"anthropic-version": "2023-06-01",
"anthropic-beta": "prompt-caching-2024-07-31",
},
)
```
</TabItem> </TabItem>
</Tabs> </Tabs>
@ -318,7 +356,45 @@ response = await litellm.acompletion(
) )
``` ```
</TabItem> </TabItem>
<TabItem value="proxy" label="PROXY"> <TabItem value="proxy" label="LiteLLM Proxy">
```python
import openai
client = openai.AsyncOpenAI(
api_key="anything", # litellm proxy api key
base_url="http://0.0.0.0:4000" # litellm proxy base url
)
response = await client.chat.completions.create(
model="anthropic/claude-3-5-sonnet-20240620",
messages = [{"role": "user", "content": "What's the weather like in Boston today?"}]
tools = [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given 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"],
},
"cache_control": {"type": "ephemeral"}
},
}
],
extra_headers={
"anthropic-version": "2023-06-01",
"anthropic-beta": "prompt-caching-2024-07-31",
},
)
```
</TabItem> </TabItem>
</Tabs> </Tabs>
@ -387,7 +463,64 @@ response = await litellm.acompletion(
) )
``` ```
</TabItem> </TabItem>
<TabItem value="proxy" label="PROXY"> <TabItem value="proxy" label="LiteLLM Proxy">
```python
import openai
client = openai.AsyncOpenAI(
api_key="anything", # litellm proxy api key
base_url="http://0.0.0.0:4000" # litellm proxy base url
)
response = await client.chat.completions.create(
model="anthropic/claude-3-5-sonnet-20240620",
messages=[
# System Message
{
"role": "system",
"content": [
{
"type": "text",
"text": "Here is the full text of a complex legal agreement"
* 400,
"cache_control": {"type": "ephemeral"},
}
],
},
# marked for caching with the cache_control parameter, so that this checkpoint can read from the previous cache.
{
"role": "user",
"content": [
{
"type": "text",
"text": "What are the key terms and conditions in this agreement?",
"cache_control": {"type": "ephemeral"},
}
],
},
{
"role": "assistant",
"content": "Certainly! the key terms and conditions are the following: the contract is 1 year long for $10/mo",
},
# The final turn is marked with cache-control, for continuing in followups.
{
"role": "user",
"content": [
{
"type": "text",
"text": "What are the key terms and conditions in this agreement?",
"cache_control": {"type": "ephemeral"},
}
],
},
],
extra_headers={
"anthropic-version": "2023-06-01",
"anthropic-beta": "prompt-caching-2024-07-31",
},
)
```
</TabItem> </TabItem>
</Tabs> </Tabs>