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移除kwargs中的hashing_kv参数取为变量

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yuanxiaobin
2024-12-06 15:23:18 +08:00
parent 633fb55b5b
commit a1c4a036fd
1 changed files with 6 additions and 5 deletions
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11
lightrag/llm.py
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@@ -73,11 +73,12 @@ async def openai_complete_if_cache(
messages.extend(history_messages)
messages.append({"role": "user", "content": prompt})
hashing_kv: BaseKVStorage = kwargs.pop("hashing_kv", None)
# Handle cache
mode = kwargs.pop("mode", "default")
args_hash = compute_args_hash(model, messages)
cached_response, quantized, min_val, max_val = await handle_cache(
kwargs.get("hashing_kv"), args_hash, prompt, mode
hashing_kv, args_hash, prompt, mode
)
if cached_response is not None:
return cached_response
@@ -219,12 +220,12 @@ async def bedrock_complete_if_cache(
# Add user prompt
messages.append({"role": "user", "content": [{"text": prompt}]})
hashing_kv: BaseKVStorage = kwargs.pop("hashing_kv", None)
# Handle cache
mode = kwargs.pop("mode", "default")
args_hash = compute_args_hash(model, messages)
cached_response, quantized, min_val, max_val = await handle_cache(
kwargs.get("hashing_kv"), args_hash, prompt, mode
hashing_kv, args_hash, prompt, mode
)
if cached_response is not None:
return cached_response
@@ -250,12 +251,12 @@ async def bedrock_complete_if_cache(
args["inferenceConfig"][inference_params_map.get(param, param)] = (
kwargs.pop(param)
)
hashing_kv: BaseKVStorage = kwargs.pop("hashing_kv", None)
# Handle cache
mode = kwargs.pop("mode", "default")
args_hash = compute_args_hash(model, messages)
cached_response, quantized, min_val, max_val = await handle_cache(
kwargs.get("hashing_kv"), args_hash, prompt, mode
hashing_kv, args_hash, prompt, mode
)
if cached_response is not None:
return cached_response