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chore: format

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This commit is contained in:
Timothy Jaeryang Baek
2025-02-20 01:01:29 -08:00
parent 2b913a99a3
commit eeb00a5ca2
60 changed files with 1548 additions and 1210 deletions
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25
backend/open_webui/utils/oauth.py
View File

@@ -253,23 +253,32 @@ class OAuthManager:
if provider == "github":
try:
access_token = token.get("access_token")
headers = {
"Authorization": f"Bearer {access_token}"
}
headers = {"Authorization": f"Bearer {access_token}"}
async with aiohttp.ClientSession() as session:
async with session.get("https://api.github.com/user/emails", headers=headers) as resp:
async with session.get(
"https://api.github.com/user/emails", headers=headers
) as resp:
if resp.ok:
emails = await resp.json()
# use the primary email as the user's email
primary_email = next((e["email"] for e in emails if e.get("primary")), None)
primary_email = next(
(e["email"] for e in emails if e.get("primary")),
None,
)
if primary_email:
email = primary_email
else:
log.warning("No primary email found in GitHub response")
raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED)
log.warning(
"No primary email found in GitHub response"
)
raise HTTPException(
400, detail=ERROR_MESSAGES.INVALID_CRED
)
else:
log.warning("Failed to fetch GitHub email")
raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED)
raise HTTPException(
400, detail=ERROR_MESSAGES.INVALID_CRED
)
except Exception as e:
log.warning(f"Error fetching GitHub email: {e}")
raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED)

16
backend/open_webui/utils/payload.py
View File

@@ -151,7 +151,7 @@ def convert_messages_openai_to_ollama(messages: list[dict]) -> list[dict]:
# Put the content to empty string (Ollama requires an empty string for tool calls)
new_message["content"] = ""
else:
# Otherwise, assume the content is a list of dicts, e.g., text followed by an image URL
content_text = ""
@@ -215,16 +215,20 @@ def convert_payload_openai_to_ollama(openai_payload: dict) -> dict:
if openai_payload.get("options"):
ollama_payload["options"] = openai_payload["options"]
ollama_options = openai_payload["options"]
# Re-Mapping OpenAI's `max_tokens` -> Ollama's `num_predict`
if "max_tokens" in ollama_options:
ollama_options["num_predict"] = ollama_options["max_tokens"]
del ollama_options["max_tokens"] # To prevent Ollama warning of invalid option provided
ollama_options["num_predict"] = ollama_options["max_tokens"]
del ollama_options[
"max_tokens"
] # To prevent Ollama warning of invalid option provided
# Ollama lacks a "system" prompt option. It has to be provided as a direct parameter, so we copy it down.
if "system" in ollama_options:
ollama_payload["system"] = ollama_options["system"]
del ollama_options["system"] # To prevent Ollama warning of invalid option provided
ollama_payload["system"] = ollama_options["system"]
del ollama_options[
"system"
] # To prevent Ollama warning of invalid option provided
if "metadata" in openai_payload:
ollama_payload["metadata"] = openai_payload["metadata"]

18
backend/open_webui/utils/response.py
View File

@@ -23,6 +23,7 @@ def convert_ollama_tool_call_to_openai(tool_calls: dict) -> dict:
openai_tool_calls.append(openai_tool_call)
return openai_tool_calls
def convert_ollama_usage_to_openai(data: dict) -> dict:
return {
"response_token/s": (
@@ -56,24 +57,29 @@ def convert_ollama_usage_to_openai(data: dict) -> dict:
"total_duration": data.get("total_duration", 0),
"load_duration": data.get("load_duration", 0),
"prompt_eval_count": data.get("prompt_eval_count", 0),
"prompt_tokens": int(data.get("prompt_eval_count", 0)), # This is the OpenAI compatible key
"prompt_tokens": int(
data.get("prompt_eval_count", 0)
), # This is the OpenAI compatible key
"prompt_eval_duration": data.get("prompt_eval_duration", 0),
"eval_count": data.get("eval_count", 0),
"completion_tokens": int(data.get("eval_count", 0)), # This is the OpenAI compatible key
"completion_tokens": int(
data.get("eval_count", 0)
), # This is the OpenAI compatible key
"eval_duration": data.get("eval_duration", 0),
"approximate_total": (lambda s: f"{s // 3600}h{(s % 3600) // 60}m{s % 60}s")(
(data.get("total_duration", 0) or 0) // 1_000_000_000
),
"total_tokens": int( # This is the OpenAI compatible key
"total_tokens": int( # This is the OpenAI compatible key
data.get("prompt_eval_count", 0) + data.get("eval_count", 0)
),
"completion_tokens_details": { # This is the OpenAI compatible key
"completion_tokens_details": { # This is the OpenAI compatible key
"reasoning_tokens": 0,
"accepted_prediction_tokens": 0,
"rejected_prediction_tokens": 0
}
"rejected_prediction_tokens": 0,
},
}
def convert_response_ollama_to_openai(ollama_response: dict) -> dict:
model = ollama_response.get("model", "ollama")
message_content = ollama_response.get("message", {}).get("content", "")