xinyin025/LangBot
1
0
Fork 0
mirror of https://github.com/langbot-app/LangBot.git synced 2026-06-18 19:44:21 +00:00
Code Issues Packages Projects Releases Wiki Activity

style: restrict line-length

Browse Source
This commit is contained in:
Junyan Qin
2025-05-10 18:04:58 +08:00
parent b30016ed08
commit 055b389353
134 changed files with 1096 additions and 2595 deletions
Download Patch File Download Diff File Expand all files Collapse all files
pkg/pipeline/preproc/preproc.py
+9 -17
View File
@@ -44,9 +44,7 @@ class PreProcessor(stage.PipelineStage):
query.use_llm_model = conversation.use_llm_model
query.use_funcs = (
conversation.use_funcs
if query.use_llm_model.model_entity.abilities.__contains__('tool_call')
else None
conversation.use_funcs if query.use_llm_model.model_entity.abilities.__contains__('tool_call') else None
)
query.variables = {
@@ -59,10 +57,9 @@ class PreProcessor(stage.PipelineStage):
# Check if this model supports vision, if not, remove all images
# TODO this checking should be performed in runner, and in this stage, the image should be reserved
if (
query.pipeline_config['ai']['runner']['runner'] == 'local-agent'
and not query.use_llm_model.model_entity.abilities.__contains__('vision')
):
if query.pipeline_config['ai']['runner'][
'runner'
] == 'local-agent' and not query.use_llm_model.model_entity.abilities.__contains__('vision'):
for msg in query.messages:
if isinstance(msg.content, list):
for me in msg.content:
@@ -78,14 +75,11 @@ class PreProcessor(stage.PipelineStage):
content_list.append(llm_entities.ContentElement.from_text(me.text))
plain_text += me.text
elif isinstance(me, platform_message.Image):
if (
query.pipeline_config['ai']['runner']['runner'] != 'local-agent'
or query.use_llm_model.model_entity.abilities.__contains__('vision')
):
if query.pipeline_config['ai']['runner'][
'runner'
] != 'local-agent' or query.use_llm_model.model_entity.abilities.__contains__('vision'):
if me.base64 is not None:
content_list.append(
llm_entities.ContentElement.from_image_base64(me.base64)
)
content_list.append(llm_entities.ContentElement.from_image_base64(me.base64))
query.variables['user_message_text'] = plain_text
@@ -104,6 +98,4 @@ class PreProcessor(stage.PipelineStage):
query.prompt.messages = event_ctx.event.default_prompt
query.messages = event_ctx.event.prompt
return entities.StageProcessResult(
result_type=entities.ResultType.CONTINUE, new_query=query
)
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)