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/assistants

Behandelt Threads, Nachrichten, Assistenten.

LiteLLM deckt derzeit ab

  • Assistenten erstellen
  • Assistenten löschen
  • Assistenten abrufen
  • Thread erstellen
  • Thread abrufen
  • Nachrichten hinzufĂĽgen
  • Nachrichten abrufen
  • Thread ausfĂĽhren

Unterstützte Anbieter:​

Schnellstart​

Einen bestehenden Assistenten aufrufen.

  • Den Assistenten abrufen

  • Einen Thread erstellen, wenn ein Benutzer eine Konversation beginnt.

  • Nachrichten zum Thread hinzufĂĽgen, während der Benutzer Fragen stellt.

  • Den Assistenten im Thread ausfĂĽhren, um eine Antwort zu generieren, indem das Modell und die Tools aufgerufen werden.

SDK + PROXY​

Einen Assistenten erstellen

import litellm
import os 

# setup env
os.environ["OPENAI_API_KEY"] = "sk-.."

assistant = litellm.create_assistants(
            custom_llm_provider="openai",
            model="gpt-4-turbo",
            instructions="You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
            name="Math Tutor",
            tools=[{"type": "code_interpreter"}],
)

### ASYNC USAGE ### 
# assistant = await litellm.acreate_assistants(
#             custom_llm_provider="openai",
#             model="gpt-4-turbo",
#             instructions="You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
#             name="Math Tutor",
#             tools=[{"type": "code_interpreter"}],
# )

Den Assistenten abrufen

from litellm import get_assistants, aget_assistants
import os 

# setup env
os.environ["OPENAI_API_KEY"] = "sk-.."

assistants = get_assistants(custom_llm_provider="openai")

### ASYNC USAGE ### 
# assistants = await aget_assistants(custom_llm_provider="openai")

Einen Thread erstellen

from litellm import create_thread, acreate_thread
import os 

os.environ["OPENAI_API_KEY"] = "sk-.."

new_thread = create_thread(
            custom_llm_provider="openai",
            messages=[{"role": "user", "content": "Hey, how's it going?"}],  # type: ignore
        )

### ASYNC USAGE ### 
# new_thread = await acreate_thread(custom_llm_provider="openai",messages=[{"role": "user", "content": "Hey, how's it going?"}])

Nachrichten zum Thread hinzufĂĽgen

from litellm import create_thread, get_thread, aget_thread, add_message, a_add_message
import os 

os.environ["OPENAI_API_KEY"] = "sk-.."

## CREATE A THREAD
_new_thread = create_thread(
            custom_llm_provider="openai",
            messages=[{"role": "user", "content": "Hey, how's it going?"}],  # type: ignore
        )

## OR retrieve existing thread
received_thread = get_thread(
            custom_llm_provider="openai",
            thread_id=_new_thread.id,
        )

### ASYNC USAGE ### 
# received_thread = await aget_thread(custom_llm_provider="openai", thread_id=_new_thread.id,)

## ADD MESSAGE TO THREAD
message = {"role": "user", "content": "Hey, how's it going?"}
added_message = add_message(
            thread_id=_new_thread.id, custom_llm_provider="openai", **message
        )

### ASYNC USAGE ### 
# added_message = await a_add_message(thread_id=_new_thread.id, custom_llm_provider="openai", **message)

Den Assistenten im Thread ausfĂĽhren

from litellm import get_assistants, create_thread, add_message, run_thread, arun_thread
import os 

os.environ["OPENAI_API_KEY"] = "sk-.."
assistants = get_assistants(custom_llm_provider="openai")

## get the first assistant ###
assistant_id = assistants.data[0].id

## GET A THREAD
_new_thread = create_thread(
            custom_llm_provider="openai",
            messages=[{"role": "user", "content": "Hey, how's it going?"}],  # type: ignore
        )

## ADD MESSAGE
message = {"role": "user", "content": "Hey, how's it going?"}
added_message = add_message(
            thread_id=_new_thread.id, custom_llm_provider="openai", **message
        )

## 🚨 RUN THREAD
response = run_thread(
            custom_llm_provider="openai", thread_id=thread_id, assistant_id=assistant_id
        )

### ASYNC USAGE ### 
# response = await arun_thread(custom_llm_provider="openai", thread_id=thread_id, assistant_id=assistant_id)

print(f"run_thread: {run_thread}")

Streaming​

from litellm import run_thread_stream 
import os

os.environ["OPENAI_API_KEY"] = "sk-.."

message = {"role": "user", "content": "Hey, how's it going?"}  

data = {"custom_llm_provider": "openai", "thread_id": _new_thread.id, "assistant_id": assistant_id, **message}

run = run_thread_stream(**data)
with run as run:
    assert isinstance(run, AssistantEventHandler)
    for chunk in run: 
      print(f"chunk: {chunk}")
    run.until_done()

👉 Proxy API Referenz​

Azure OpenAI​

Konfiguration

assistant_settings:
  custom_llm_provider: azure
  litellm_params: 
    api_key: os.environ/AZURE_API_KEY
    api_base: os.environ/AZURE_API_BASE

curl

curl -X POST "https://:4000/v1/assistants" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
    "name": "Math Tutor",
    "tools": [{"type": "code_interpreter"}],
    "model": "<my-azure-deployment-name>"
  }'

OpenAI-kompatible APIs​

Um OpenAI-kompatible Assistants APIs aufzurufen (z.B. Astra Assistants API), fĂĽgen Sie einfach openai/ zum Modellnamen hinzu

Konfiguration

assistant_settings:
  custom_llm_provider: openai
  litellm_params: 
    api_key: os.environ/ASTRA_API_KEY
    api_base: os.environ/ASTRA_API_BASE

curl

curl -X POST "https://:4000/v1/assistants" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
    "name": "Math Tutor",
    "tools": [{"type": "code_interpreter"}],
    "model": "openai/<my-astra-model-name>"
  }'