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docs: replace gpt-3.5-turbo with gpt-4o in pages and blog examples

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Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
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2
docs/my-website/blog/litellm_observatory/index.md
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@ -93,7 +93,7 @@ Our focus moving forward is on being the first to detect issues, even when they
The `TestOAIAzureRelease` test is designed to catch a class of bugs that only surface after sustained runtime:
- **Duration**: Runs continuously for 3 hours
- **Behavior**: Cycles through specified models (such as `gpt-4` and `gpt-3.5-turbo`), issuing requests continuously
- **Behavior**: Cycles through specified models (such as `gpt-4` and `gpt-4o`), issuing requests continuously
- **Why 3 Hours**: This helps catch issues where HTTP clients degrade or fail after extended use (for example, a bug observed in LiteLLM v1.81.3)
- **Pass / Fail Criteria**: The test passes if fewer than 1% of requests fail. If the failure rate exceeds 1%, the test fails and we are notified in Slack
- **Key Detail**: The same HTTP client is reused for the entire run, allowing us to detect lifecycle-related bugs that only appear under prolonged reuse

12
docs/my-website/src/pages/completion/supported.md
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@ -4,9 +4,9 @@
| Model Name | Function Call | Required OS Variables |
|------------------|----------------------------------------|--------------------------------------|
| gpt-3.5-turbo | `completion('gpt-3.5-turbo', messages)` | `os.environ['OPENAI_API_KEY']` |
| gpt-3.5-turbo-16k | `completion('gpt-3.5-turbo-16k', messages)` | `os.environ['OPENAI_API_KEY']` |
| gpt-3.5-turbo-16k-0613 | `completion('gpt-3.5-turbo-16k-0613', messages)` | `os.environ['OPENAI_API_KEY']` |
| gpt-4o | `completion('gpt-4o', messages)` | `os.environ['OPENAI_API_KEY']` |
| gpt-4o-16k | `completion('gpt-4o-16k', messages)` | `os.environ['OPENAI_API_KEY']` |
| gpt-4o-16k-0613 | `completion('gpt-4o-16k-0613', messages)` | `os.environ['OPENAI_API_KEY']` |
| gpt-4 | `completion('gpt-4', messages)` | `os.environ['OPENAI_API_KEY']` |
| gpt-5-pro | `completion('gpt-5-pro', messages)` | `os.environ['OPENAI_API_KEY']` |
@ -15,7 +15,7 @@ For Azure calls add the `azure/` prefix to `model`. If your azure deployment nam
| Model Name | Function Call | Required OS Variables |
|------------------|-----------------------------------------|-------------------------------------------|
| gpt-3.5-turbo | `completion('azure/gpt-3.5-turbo-deployment', messages)` | `os.environ['AZURE_API_KEY']`,`os.environ['AZURE_API_BASE']`,`os.environ['AZURE_API_VERSION']` |
| gpt-4o | `completion('azure/gpt-4o-deployment', messages)` | `os.environ['AZURE_API_KEY']`,`os.environ['AZURE_API_BASE']`,`os.environ['AZURE_API_VERSION']` |
| gpt-4 | `completion('azure/gpt-4-deployment', messages)` | `os.environ['AZURE_API_KEY']`,`os.environ['AZURE_API_BASE']`,`os.environ['AZURE_API_VERSION']` |
### OpenAI Text Completion Models
@ -62,8 +62,8 @@ All the text models from [OpenRouter](https://openrouter.ai/docs) are supported
| Model Name | Function Call | Required OS Variables |
|------------------|--------------------------------------------|--------------------------------------|
| openai/gpt-3.5-turbo | `completion('openai/gpt-3.5-turbo', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OR_API_KEY']` |
| openai/gpt-3.5-turbo-16k | `completion('openai/gpt-3.5-turbo-16k', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OR_API_KEY']` |
| openai/gpt-4o | `completion('openai/gpt-4o', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OR_API_KEY']` |
| openai/gpt-4o-16k | `completion('openai/gpt-4o-16k', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OR_API_KEY']` |
| openai/gpt-4 | `completion('openai/gpt-4', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OR_API_KEY']` |
| openai/gpt-4-32k | `completion('openai/gpt-4-32k', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OR_API_KEY']` |
| anthropic/claude-2 | `completion('anthropic/claude-2', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OR_API_KEY']` |

2
docs/my-website/src/pages/observability/callbacks.md
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@ -26,5 +26,5 @@ os.environ['SENTRY_DSN'], os.environ['SENTRY_API_TRACE_RATE']= ""
os.environ['POSTHOG_API_KEY'], os.environ['POSTHOG_API_URL'] = "api-key", "api-url"
os.environ["HELICONE_API_KEY"] = ""
response = completion(model="gpt-3.5-turbo", messages=messages)
response = completion(model="gpt-4o", messages=messages)
```

4
docs/my-website/src/pages/observability/helicone_integration.md
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@ -24,7 +24,7 @@ os.environ["OPENAI_API_KEY"], os.environ["COHERE_API_KEY"] = "", ""
litellm.success_callback=["helicone"]
#openai call
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
response = completion(model="gpt-4o", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
#cohere call
response = completion(model="command-nightly", messages=[{"role": "user", "content": "Hi 👋 - i'm cohere"}])
@ -47,7 +47,7 @@ litellm.api_base = "https://oai.hconeai.com/v1"
litellm.headers = {"Helicone-Auth": f"Bearer {os.getenv('HELICONE_API_KEY')}"}
response = litellm.completion(
model="gpt-3.5-turbo",
model="gpt-4o",
messages=[{"role": "user", "content": "how does a court case get to the Supreme Court?"}]
)

2
docs/my-website/src/pages/observability/supabase_integration.md
View file

@ -55,7 +55,7 @@ litellm.success_callback=["supabase"]
litellm.failure_callback=["supabase"]
#openai call
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
response = completion(model="gpt-4o", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
#bad call
response = completion(model="chatgpt-test", messages=[{"role": "user", "content": "Hi 👋 - i'm a bad call to test error logging"}])

6
docs/my-website/src/pages/stream.md
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@ -7,7 +7,7 @@
LiteLLM supports streaming the model response back by passing `stream=True` as an argument to the completion function
### Usage
```python
response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
response = completion(model="gpt-4o", messages=messages, stream=True)
for chunk in response:
print(chunk['choices'][0]['delta'])
@ -24,7 +24,7 @@ import asyncio
async def test_get_response():
user_message = "Hello, how are you?"
messages = [{"content": user_message, "role": "user"}]
response = await acompletion(model="gpt-3.5-turbo", messages=messages)
response = await acompletion(model="gpt-4o", messages=messages)
return response
response = asyncio.run(test_get_response())
@ -47,7 +47,7 @@ import os
os.environ["OPENAI_API_KEY"] = ""
response = completion(model="gpt-3.5-turbo", messages=messages, stream=True, stream_options={"include_usage": True})
response = completion(model="gpt-4o", messages=messages, stream=True, stream_options={"include_usage": True})
for chunk in response:
print(chunk['choices'][0]['delta'])
```

6
docs/my-website/src/pages/token_usage.md
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@ -17,7 +17,7 @@ However, we also expose 3 public helper functions to calculate token usage acros
from litellm import token_counter
messages = [{"role": "user", "content": "Hey, how's it going"}]
print(token_counter(model="gpt-3.5-turbo", messages=messages))
print(token_counter(model="gpt-4o", messages=messages))
```
2. `cost_per_token`
@ -27,7 +27,7 @@ from litellm import cost_per_token
prompt_tokens = 5
completion_tokens = 10
prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar = cost_per_token(model="gpt-3.5-turbo", prompt_tokens=prompt_tokens, completion_tokens=completion_tokens)
prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar = cost_per_token(model="gpt-4o", prompt_tokens=prompt_tokens, completion_tokens=completion_tokens)
print(prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar)
```
@ -39,7 +39,7 @@ from litellm import completion_cost
prompt = "Hey, how's it going"
completion = "Hi, I'm gpt - I am doing well"
cost_of_query = completion_cost(model="gpt-3.5-turbo", prompt=prompt, completion=completion))
cost_of_query = completion_cost(model="gpt-4o", prompt=prompt, completion=completion))
print(cost_of_query)
```