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fix: enhance llm-katan OpenAI API compatibility for issue #241 #354

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Merged
merged 7 commits into from
Oct 7, 2025
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Merged

fix: enhance llm-katan OpenAI API compatibility for issue #241 #354

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a6b308c
fix: enhance llm-katan OpenAI API compatibility for issue #241
yossiovadia Oct 6, 2025
415346a
bump llm-katan version to 0.1.9 for PyPI release
yossiovadia Oct 6, 2025
29ffb27
chore: trigger CI re-run to check pre-commit status
yossiovadia Oct 6, 2025
d3dcf38
trigger pre-commit formatting fix
yossiovadia Oct 7, 2025
6886362
fix: apply black formatting to llm-katan Python files
yossiovadia Oct 7, 2025
c5968f0
fix: apply black formatting to llm-katan Python files for CI compliance
yossiovadia Oct 7, 2025
528bc6d
Merge branch 'main' into fix/llm-katan-openai-compatibility-241
yossiovadia Oct 7, 2025
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61 changes: 42 additions & 19 deletions e2e-tests/llm-katan/llm_katan/model.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -103,9 +103,7 @@ async def generate(
raise RuntimeError("Model not loaded. Call load_model() first.")

max_tokens = max_tokens or self.config.max_tokens
temperature = (
temperature if temperature is not None else self.config.temperature
)
temperature = temperature if temperature is not None else self.config.temperature

# Convert messages to prompt
prompt = self._messages_to_prompt(messages)
Expand Down Expand Up @@ -136,20 +134,27 @@ async def generate(
"object": "chat.completion",
"created": int(time.time()),
"model": self.config.served_model_name,
"system_fingerprint": "llm-katan-transformers",
"choices": [
{
"index": 0,
"message": {"role": "assistant", "content": generated_text},
"logprobs": None,
"finish_reason": "stop",
}
],
"usage": {
"prompt_tokens": prompt_tokens,
"completion_tokens": completion_tokens,
"total_tokens": total_tokens,
"prompt_tokens_details": {"cached_tokens": 0},
"completion_tokens_details": {"reasoning_tokens": 0},
},
}

# Add token_usage as alias for better SDK compatibility
response_data["token_usage"] = response_data["usage"]

if stream:
# For streaming, yield chunks
words = generated_text.split()
Expand All @@ -159,12 +164,12 @@ async def generate(
"object": "chat.completion.chunk",
"created": response_data["created"],
"model": self.config.served_model_name,
"system_fingerprint": "llm-katan-transformers",
"choices": [
{
"index": 0,
"delta": {
"content": word + " " if i < len(words) - 1 else word
},
"delta": {"content": word + " " if i < len(words) - 1 else word},
"logprobs": None,
"finish_reason": None,
}
],
Expand All @@ -178,7 +183,15 @@ async def generate(
"object": "chat.completion.chunk",
"created": response_data["created"],
"model": self.config.served_model_name,
"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
"system_fingerprint": "llm-katan-transformers",
"choices": [{"index": 0, "delta": {}, "logprobs": None, "finish_reason": "stop"}],
"usage": {
"prompt_tokens": prompt_tokens,
"completion_tokens": completion_tokens,
"total_tokens": total_tokens,
"prompt_tokens_details": {"cached_tokens": 0},
"completion_tokens_details": {"reasoning_tokens": 0},
},
}
yield final_chunk
else:
Expand Down Expand Up @@ -268,9 +281,7 @@ async def generate(
from vllm.sampling_params import SamplingParams

max_tokens = max_tokens or self.config.max_tokens
temperature = (
temperature if temperature is not None else self.config.temperature
)
temperature = temperature if temperature is not None else self.config.temperature

# Convert messages to prompt
prompt = self._messages_to_prompt(messages)
Expand All @@ -282,9 +293,7 @@ async def generate(

# Generate
loop = asyncio.get_event_loop()
outputs = await loop.run_in_executor(
None, self.engine.generate, [prompt], sampling_params
)
outputs = await loop.run_in_executor(None, self.engine.generate, [prompt], sampling_params)

output = outputs[0]
generated_text = output.outputs[0].text.strip()
Expand All @@ -295,21 +304,27 @@ async def generate(
"object": "chat.completion",
"created": int(time.time()),
"model": self.config.served_model_name,
"system_fingerprint": "llm-katan-vllm",
"choices": [
{
"index": 0,
"message": {"role": "assistant", "content": generated_text},
"logprobs": None,
"finish_reason": "stop",
}
],
"usage": {
"prompt_tokens": len(output.prompt_token_ids),
"completion_tokens": len(output.outputs[0].token_ids),
"total_tokens": len(output.prompt_token_ids)
+ len(output.outputs[0].token_ids),
"total_tokens": len(output.prompt_token_ids) + len(output.outputs[0].token_ids),
"prompt_tokens_details": {"cached_tokens": 0},
"completion_tokens_details": {"reasoning_tokens": 0},
},
}

# Add token_usage as alias for better SDK compatibility
response_data["token_usage"] = response_data["usage"]

if stream:
# For streaming, yield chunks (simplified for now)
words = generated_text.split()
Expand All @@ -319,12 +334,12 @@ async def generate(
"object": "chat.completion.chunk",
"created": response_data["created"],
"model": self.config.served_model_name,
"system_fingerprint": "llm-katan-vllm",
"choices": [
{
"index": 0,
"delta": {
"content": word + " " if i < len(words) - 1 else word
},
"delta": {"content": word + " " if i < len(words) - 1 else word},
"logprobs": None,
"finish_reason": None,
}
],
Expand All @@ -338,7 +353,15 @@ async def generate(
"object": "chat.completion.chunk",
"created": response_data["created"],
"model": self.config.served_model_name,
"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
"system_fingerprint": "llm-katan-vllm",
"choices": [{"index": 0, "delta": {}, "logprobs": None, "finish_reason": "stop"}],
"usage": {
"prompt_tokens": len(output.prompt_token_ids),
"completion_tokens": len(output.outputs[0].token_ids),
"total_tokens": len(output.prompt_token_ids) + len(output.outputs[0].token_ids),
"prompt_tokens_details": {"cached_tokens": 0},
"completion_tokens_details": {"reasoning_tokens": 0},
},
}
yield final_chunk
else:
Expand Down
17 changes: 9 additions & 8 deletions e2e-tests/llm-katan/llm_katan/server.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,9 +160,7 @@ async def chat_completions(request: ChatCompletionRequest, http_request: Request

try:
# Convert messages to dict format
messages = [
{"role": msg.role, "content": msg.content} for msg in request.messages
]
messages = [{"role": msg.role, "content": msg.content} for msg in request.messages]

# Update metrics
metrics["total_requests"] += 1
Expand All @@ -181,8 +179,13 @@ async def generate_stream():

return StreamingResponse(
generate_stream(),
media_type="text/plain",
headers={"Cache-Control": "no-cache", "Connection": "keep-alive"},
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"Access-Control-Allow-Origin": "*",
"Access-Control-Allow-Headers": "Content-Type",
},
)
else:
# Non-streaming response
Expand All @@ -198,9 +201,7 @@ async def generate_stream():
response_time = time.time() - start_time
metrics["response_times"].append(response_time)
if "choices" in response and response["choices"]:
generated_text = (
response["choices"][0].get("message", {}).get("content", "")
)
generated_text = response["choices"][0].get("message", {}).get("content", "")
token_count = len(generated_text.split()) # Rough token estimate
metrics["total_tokens_generated"] += token_count

Expand Down
2 changes: 1 addition & 1 deletion e2e-tests/llm-katan/pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"

[project]
name = "llm-katan"
version = "0.1.8"
version = "0.1.9"
description = "LLM Katan - Lightweight LLM Server for Testing - Real tiny models with FastAPI and HuggingFace"
readme = "README.md"
authors = [
Expand Down
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