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[Frontend] Use new Renderer for Completions and Tokenize API (#32863)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2026-01-31 20:51:15 +08:00
committed by GitHub
parent 8980001c93
commit f0a1c8453a
64 changed files with 2116 additions and 2003 deletions
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20
tests/entrypoints/openai/test_completion_with_prompt_embeds.py
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@@ -110,7 +110,7 @@ async def test_completions_with_prompt_embeds(
# Test case: Single prompt embeds input
completion = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="", # Add empty prompt as required parameter
prompt=None,
max_tokens=5,
temperature=0.0,
extra_body={"prompt_embeds": encoded_embeds},
@@ -121,7 +121,7 @@ async def test_completions_with_prompt_embeds(
# Test case: batch completion with prompt_embeds
completion = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="", # Add empty prompt as required parameter
prompt=None,
max_tokens=5,
temperature=0.0,
extra_body={"prompt_embeds": [encoded_embeds, encoded_embeds2]},
@@ -133,7 +133,7 @@ async def test_completions_with_prompt_embeds(
# Test case: streaming with prompt_embeds
single_completion = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="", # Add empty prompt as required parameter
prompt=None,
max_tokens=5,
temperature=0.0,
extra_body={"prompt_embeds": encoded_embeds},
@@ -142,7 +142,7 @@ async def test_completions_with_prompt_embeds(
stream = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="", # Add empty prompt as required parameter
prompt=None,
max_tokens=5,
temperature=0.0,
stream=True,
@@ -162,7 +162,7 @@ async def test_completions_with_prompt_embeds(
# Test case: batch streaming with prompt_embeds
stream = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="", # Add empty prompt as required parameter
prompt=None,
max_tokens=5,
temperature=0.0,
stream=True,
@@ -197,7 +197,7 @@ async def test_completions_with_prompt_embeds(
)
completion_embeds_only = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="",
prompt=None,
max_tokens=5,
temperature=0.0,
extra_body={"prompt_embeds": encoded_embeds},
@@ -215,7 +215,7 @@ async def test_completions_errors_with_prompt_embeds(
# Test error case: invalid prompt_embeds
with pytest.raises(BadRequestError):
await client_with_prompt_embeds.completions.create(
prompt="",
prompt=None,
model=model_name,
max_tokens=5,
temperature=0.0,
@@ -237,7 +237,7 @@ async def test_completions_with_logprobs_and_prompt_embeds(
# Test case: Logprobs using prompt_embeds
completion = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="", # Add empty prompt as required parameter
prompt=None,
max_tokens=5,
temperature=0.0,
echo=False,
@@ -257,7 +257,7 @@ async def test_completions_with_logprobs_and_prompt_embeds(
# Test case: Log probs with batch completion and prompt_embeds
completion = await client_with_prompt_embeds.completions.create(
model=model_name,
prompt="", # Add empty prompt as required parameter
prompt=None,
max_tokens=5,
temperature=0.0,
echo=False,
@@ -287,7 +287,7 @@ async def test_prompt_logprobs_raises_error(
with pytest.raises(BadRequestError, match="not compatible"):
await client_with_prompt_embeds.completions.create(
model=MODEL_NAME,
prompt="",
prompt=None,
max_tokens=5,
temperature=0.0,
extra_body={"prompt_embeds": encoded_embeds, "prompt_logprobs": True},