adding support for custom prompt templates to together ai

This commit is contained in:
Krrish Dholakia 2023-09-05 12:20:09 -07:00
parent 64f3d3c56e
commit 8845938b31
3 changed files with 118 additions and 28 deletions

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@ -1,34 +1,38 @@
# liteLLM Together AI Tutorial
# Llama2 Together AI Tutorial
https://together.ai/
```python
!pip install litellm==0.1.371
!pip install litellm
```
```python
import os
from litellm import completion
os.environ["TOGETHER_AI_TOKEN"] = "" #@param
os.environ["TOGETHERAI_API_KEY"] = "" #@param
user_message = "Hello, whats the weather in San Francisco??"
messages = [{ "content": user_message,"role": "user"}]
```
## Calling togethercomputer/llama-2-70b-chat
## Calling Llama2 on TogetherAI
https://api.together.xyz/playground/chat?model=togethercomputer%2Fllama-2-70b-chat
```python
model_name = "togethercomputer/llama-2-70b-chat"
response = completion(model=model_name, messages=messages, together_ai=True)
model_name = "together_ai/togethercomputer/llama-2-70b-chat"
response = completion(model=model_name, messages=messages)
print(response)
```
{'choices': [{'finish_reason': 'stop', 'index': 0, 'message': {'role': 'assistant', 'content': "\n\nI'm not able to provide real-time weather information. However, I can suggest"}}], 'created': 1691629657.9288375, 'model': 'togethercomputer/llama-2-70b-chat', 'usage': {'prompt_tokens': 9, 'completion_tokens': 17, 'total_tokens': 26}}
LiteLLM handles the prompt formatting for Together AI's Llama2 models as well, converting your message to the
`[INST] <your instruction> [/INST]` format required.
[Implementation Code](https://github.com/BerriAI/litellm/blob/64f3d3c56ef02ac5544983efc78293de31c1c201/litellm/llms/prompt_templates/factory.py#L17)
## With Streaming
@ -39,23 +43,95 @@ for chunk in response:
print(chunk['choices'][0]['delta']) # same as openai format
```
<litellm.utils.CustomStreamWrapper object at 0x7ad005e93ee0>
{'role': 'assistant', 'content': '\\n'}
{'role': 'assistant', 'content': '\\n'}
{'role': 'assistant', 'content': 'I'}
{'role': 'assistant', 'content': 'm'}
{'role': 'assistant', 'content': ' not'}
{'role': 'assistant', 'content': ' able'}
{'role': 'assistant', 'content': ' to'}
{'role': 'assistant', 'content': ' provide'}
{'role': 'assistant', 'content': ' real'}
{'role': 'assistant', 'content': '-'}
{'role': 'assistant', 'content': 'time'}
{'role': 'assistant', 'content': ' weather'}
{'role': 'assistant', 'content': ' information'}
{'role': 'assistant', 'content': '.'}
{'role': 'assistant', 'content': ' However'}
{'role': 'assistant', 'content': ','}
{'role': 'assistant', 'content': ' I'}
{'role': 'assistant', 'content': ' can'}
## Use Llama2 variants with Custom Prompt Templates
Using a version of Llama2 on TogetherAI that needs custom prompt formatting?
You can create a custom prompt template.
Let's make one for `OpenAssistant/llama2-70b-oasst-sft-v10`!
The accepted template format is: [Reference](https://huggingface.co/OpenAssistant/llama2-70b-oasst-sft-v10-)
```
"""
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
"""
```
Let's register our custom prompt template: [Implementation Code](https://github.com/BerriAI/litellm/blob/64f3d3c56ef02ac5544983efc78293de31c1c201/litellm/llms/prompt_templates/factory.py#L77)
```
import litellm
litellm.register_prompt_template(
model="OpenAssistant/llama2-70b-oasst-sft-v10",
roles={"system":"<|im_start|>system", "assistant":"<|im_start|>assistant", "user":"<|im_start|>user"}, # tell LiteLLM how you want to map the openai messages to this model
pre_message_sep= "\n",
post_message_sep= "\n"
)
```
Let's use it!
```
from litellm import completion
# set env variable
os.environ["TOGETHERAI_API_KEY"] = ""
messages=[{"role":"user", "content": "Write me a poem about the blue sky"}]
completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", messages=messages)
```
**Complete Code**
```
import litellm
from litellm import completion
# set env variable
os.environ["TOGETHERAI_API_KEY"] = ""
litellm.register_prompt_template(
model="OpenAssistant/llama2-70b-oasst-sft-v10",
roles={"system":"<|im_start|>system", "assistant":"<|im_start|>assistant", "user":"<|im_start|>user"}, # tell LiteLLM how you want to map the openai messages to this model
pre_message_sep= "\n",
post_message_sep= "\n"
)
messages=[{"role":"user", "content": "Write me a poem about the blue sky"}]
response = completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", messages=messages)
print(response)
```
**Output**
```
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": ".\n\nThe sky is a canvas of blue,\nWith clouds that drift and move,",
"role": "assistant",
"logprobs": null
}
}
],
"created": 1693941410.482018,
"model": "OpenAssistant/llama2-70b-oasst-sft-v10",
"usage": {
"prompt_tokens": 7,
"completion_tokens": 16,
"total_tokens": 23
},
"litellm_call_id": "f21315db-afd6-4c1e-b43a-0b5682de4b06"
}
```

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@ -396,7 +396,21 @@ def test_completion_together_ai():
except Exception as e:
pytest.fail(f"Error occurred: {e}")
test_completion_together_ai()
def test_customprompt_together_ai():
try:
litellm.register_prompt_template(
model="OpenAssistant/llama2-70b-oasst-sft-v10",
roles={"system":"<|im_start|>system", "assistant":"<|im_start|>assistant", "user":"<|im_start|>user"}, # tell LiteLLM how you want to map the openai messages to this model
pre_message_sep= "\n",
post_message_sep= "\n"
)
response = completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", messages=messages)
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
test_customprompt_together_ai()
def test_completion_sagemaker():
try:

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@ -1,6 +1,6 @@
[tool.poetry]
name = "litellm"
version = "0.1.532"
version = "0.1.533"
description = "Library to easily interface with LLM API providers"
authors = ["BerriAI"]
license = "MIT License"