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docs - response headers

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Ishaan Jaff 2024-07-20 15:19:15 -07:00
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docs/my-website/docs/providers/openai.md
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@ -238,6 +238,104 @@ response = completion(
## Advanced ## Advanced
### Getting OpenAI API Response Headers
Set `litellm.return_response_headers = True` to get raw response headers from OpenAI
You can expect to always get the `response_headers` field from `litellm.completion()`, `litellm.embedding()` functions
<Tabs>
<TabItem value="litellm.completion" label="litellm.completion">
```python
litellm.return_response_headers = True
# /chat/completion
response = completion(
model="gpt-4o-mini",
messages=[
{
"role": "user",
"content": "hi",
}
],
)
print(f"response: {response}")
print("response_headers=", response.response_headers)
```
</TabItem>
<TabItem value="litellm.completion - streaming" label="litellm.completion + stream">
```python
litellm.return_response_headers = True
# /chat/completion
response = completion(
model="gpt-4o-mini",
stream=True,
messages=[
{
"role": "user",
"content": "hi",
}
],
)
print(f"response: {response}")
print("response_headers=", response.response_headers)
for chunk in response:
print(chunk)
```
</TabItem>
<TabItem value="litellm.embedding" label="litellm.embedding">
```python
litellm.return_response_headers = True
# embedding
embedding_response = litellm.embedding(
model="text-embedding-ada-002",
input="hello",
)
embedding_response_headers = embedding_response.response_headers
print("embedding_response_headers=", embedding_response_headers)
```
</TabItem>
</Tabs>
Expected Response Headers from OpenAI
```json
{
"date": "Sat, 20 Jul 2024 22:05:23 GMT",
"content-type": "application/json",
"transfer-encoding": "chunked",
"connection": "keep-alive",
"access-control-allow-origin": "*",
"openai-model": "text-embedding-ada-002",
"openai-organization": "*****",
"openai-processing-ms": "20",
"openai-version": "2020-10-01",
"strict-transport-security": "max-age=15552000; includeSubDomains; preload",
"x-ratelimit-limit-requests": "5000",
"x-ratelimit-limit-tokens": "5000000",
"x-ratelimit-remaining-requests": "4999",
"x-ratelimit-remaining-tokens": "4999999",
"x-ratelimit-reset-requests": "12ms",
"x-ratelimit-reset-tokens": "0s",
"x-request-id": "req_cc37487bfd336358231a17034bcfb4d9",
"cf-cache-status": "DYNAMIC",
"set-cookie": "__cf_bm=E_FJY8fdAIMBzBE2RZI2.OkMIO3lf8Hz.ydBQJ9m3q8-1721513123-1.0.1.1-6OK0zXvtd5s9Jgqfz66cU9gzQYpcuh_RLaUZ9dOgxR9Qeq4oJlu.04C09hOTCFn7Hg.k.2tiKLOX24szUE2shw; path=/; expires=Sat, 20-Jul-24 22:35:23 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None, *cfuvid=SDndIImxiO3U0aBcVtoy1TBQqYeQtVDo1L6*Nlpp7EU-1721513123215-0.0.1.1-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None",
"x-content-type-options": "nosniff",
"server": "cloudflare",
"cf-ray": "8a66409b4f8acee9-SJC",
"content-encoding": "br",
"alt-svc": "h3=\":443\"; ma=86400"
}
```
### Parallel Function calling ### Parallel Function calling
See a detailed walthrough of parallel function calling with litellm [here](https://docs.litellm.ai/docs/completion/function_call) See a detailed walthrough of parallel function calling with litellm [here](https://docs.litellm.ai/docs/completion/function_call)
```python ```python