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Update instructor tutorial (#7784)

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Nikolaiev Dmytro 2025-01-15 18:10:50 -05:00 • committed by GitHub
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docs/my-website/docs/tutorials/instructor.md
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@ -1,32 +1,22 @@
# Instructor - Function Calling
Use LiteLLM Router with [jxnl's instructor library](https://github.com/jxnl/instructor) for function calling in prod.
Use LiteLLM with [jxnl's instructor library](https://github.com/jxnl/instructor) for function calling in prod.
## Usage
```python
import litellm
from litellm import Router
import os
import instructor
from litellm import completion
from pydantic import BaseModel
litellm.set_verbose = True # 👈 print DEBUG LOGS
os.environ["LITELLM_LOG"] = "DEBUG" # 👈 print DEBUG LOGS
client = instructor.patch(
Router(
model_list=[
{
"model_name": "gpt-3.5-turbo", openai model name
"litellm_params": { # params for litellm completion/embedding call - e.g.: https://github.com/BerriAI/litellm/blob/62a591f90c99120e1a51a8445f5c3752586868ea/litellm/router.py#L111
"model": "azure/chatgpt-v-2",
"api_key": os.getenv("AZURE_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
}
]
)
)
client = instructor.from_litellm(completion)
# import dotenv
# dotenv.load_dotenv()
class UserDetail(BaseModel):
@ -35,7 +25,7 @@ class UserDetail(BaseModel):
user = client.chat.completions.create(
model="gpt-3.5-turbo",
model="gpt-4o-mini",
response_model=UserDetail,
messages=[
{"role": "user", "content": "Extract Jason is 25 years old"},
@ -52,22 +42,17 @@ print(f"user: {user}")
## Async Calls
```python
import litellm
import asyncio
import instructor
from litellm import Router
import instructor, asyncio
from pydantic import BaseModel
aclient = instructor.apatch(
aclient = instructor.patch(
Router(
model_list=[
{
"model_name": "gpt-3.5-turbo",
"litellm_params": {
"model": "azure/chatgpt-v-2",
"api_key": os.getenv("AZURE_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
"model_name": "gpt-4o-mini",
"litellm_params": {"model": "gpt-4o-mini"},
}
],
default_litellm_params={"acompletion": True}, # 👈 IMPORTANT - tells litellm to route to async completion function.
@ -82,7 +67,7 @@ class UserExtract(BaseModel):
async def main():
model = await aclient.chat.completions.create(
model="gpt-3.5-turbo",
model="gpt-4o-mini",
response_model=UserExtract,
messages=[
{"role": "user", "content": "Extract jason is 25 years old"},