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feat(ui): add models via ui

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adds ability to add models via ui to the proxy. also fixes additional bugs around new /model/new endpoint
This commit is contained in:
Krrish Dholakia 2024-04-04 18:56:20 -07:00
parent 2472311a3f
commit e3c2bdef4d
34 changed files with 333 additions and 108 deletions
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41
litellm/proxy/proxy_server.py
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@ -2407,12 +2407,13 @@ class ProxyConfig:
if isinstance(_litellm_params, dict):
# decrypt values
for k, v in _litellm_params.items():
# decode base64
decoded_b64 = base64.b64decode(v)
# decrypt value
_litellm_params[k] = decrypt_value(
value=decoded_b64, master_key=master_key
)
if isinstance(v, str):
# decode base64
decoded_b64 = base64.b64decode(v)
# decrypt value
_litellm_params[k] = decrypt_value(
value=decoded_b64, master_key=master_key
)
_litellm_params = LiteLLM_Params(**_litellm_params)
else:
raise Exception(
@ -6769,7 +6770,7 @@ async def info_budget(data: BudgetRequest):
dependencies=[Depends(user_api_key_auth)],
)
async def add_new_model(
model_params: ModelParams,
model_params: Deployment,
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
):
global llm_router, llm_model_list, general_settings, user_config_file_path, proxy_config, prisma_client, master_key
@ -6793,15 +6794,19 @@ async def add_new_model(
- store keys separately
"""
# encrypt litellm params #
for k, v in model_params.litellm_params.items():
encrypted_value = encrypt_value(value=v, master_key=master_key) # type: ignore
model_params.litellm_params[k] = base64.b64encode(
encrypted_value
).decode("utf-8")
_litellm_params_dict = model_params.litellm_params.model_dump(
exclude_none=True
)
for k, v in _litellm_params_dict.items():
if isinstance(v, str):
encrypted_value = encrypt_value(value=v, master_key=master_key) # type: ignore
model_params.litellm_params[k] = base64.b64encode(
encrypted_value
).decode("utf-8")
await prisma_client.db.litellm_proxymodeltable.create(
data={
"model_name": model_params.model_name,
"litellm_params": json.dumps(model_params.litellm_params), # type: ignore
"litellm_params": model_params.litellm_params.model_dump_json(exclude_none=True), # type: ignore
"model_info": model_params.model_info.model_dump_json( # type: ignore
exclude_none=True
),
@ -6852,10 +6857,18 @@ async def model_info_v2(
"""
global llm_model_list, general_settings, user_config_file_path, proxy_config
if llm_model_list is None or not isinstance(llm_model_list, list):
raise HTTPException(
status_code=500,
detail={
"error": f"Invalid llm model list. llm_model_list={llm_model_list}"
},
)
# Load existing config
config = await proxy_config.get_config()
all_models = config.get("model_list", [])
all_models = llm_model_list
if user_model is not None:
# if user does not use a config.yaml, https://github.com/BerriAI/litellm/issues/2061
all_models += [user_model]