[fix]Add knowledge graph functionality to document parsing configuration
This commit is contained in:
@@ -119,7 +119,7 @@ def keyword_extraction(chat_mdl, content, topn=3):
|
||||
rendered_prompt = template.render(content=content, topn=topn)
|
||||
|
||||
msg = [{"role": "system", "content": rendered_prompt}, {"role": "user", "content": "Output: "}]
|
||||
_, msg = message_fit_in(msg, chat_mdl.max_length)
|
||||
_, msg = message_fit_in(msg, getattr(chat_mdl, 'max_length', 8096))
|
||||
kwd = chat_mdl.chat(rendered_prompt, msg[1:], {"temperature": 0.2})
|
||||
if isinstance(kwd, tuple):
|
||||
kwd = kwd[0]
|
||||
@@ -194,7 +194,7 @@ def content_tagging(chat_mdl, content, all_tags, examples, topn=3):
|
||||
)
|
||||
|
||||
msg = [{"role": "system", "content": rendered_prompt}, {"role": "user", "content": "Output: "}]
|
||||
_, msg = message_fit_in(msg, chat_mdl.max_length)
|
||||
_, msg = message_fit_in(msg, getattr(chat_mdl, 'max_length', 8096))
|
||||
kwd = chat_mdl.chat(rendered_prompt, msg[1:], {"temperature": 0.5})
|
||||
if isinstance(kwd, tuple):
|
||||
kwd = kwd[0]
|
||||
@@ -314,7 +314,7 @@ def reflect(chat_mdl, history: list[dict], tool_call_res: list[Tuple], user_defi
|
||||
hist[-1]["content"] += user_prompt
|
||||
else:
|
||||
hist.append({"role": "user", "content": user_prompt})
|
||||
_, msg = message_fit_in(hist, chat_mdl.max_length)
|
||||
_, msg = message_fit_in(hist, getattr(chat_mdl, 'max_length', 8096))
|
||||
ans = chat_mdl.chat(msg[0]["content"], msg[1:])
|
||||
ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
|
||||
return """
|
||||
@@ -341,7 +341,7 @@ def tool_call_summary(chat_mdl, name: str, params: dict, result: str, user_defin
|
||||
params=json.dumps(params, ensure_ascii=False, indent=2),
|
||||
result=result)
|
||||
user_prompt = "→ Summary: "
|
||||
_, msg = message_fit_in(form_message(system_prompt, user_prompt), chat_mdl.max_length)
|
||||
_, msg = message_fit_in(form_message(system_prompt, user_prompt), getattr(chat_mdl, 'max_length', 8096))
|
||||
ans = chat_mdl.chat(msg[0]["content"], msg[1:])
|
||||
return re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
|
||||
|
||||
@@ -350,7 +350,7 @@ def rank_memories(chat_mdl, goal:str, sub_goal:str, tool_call_summaries: list[st
|
||||
template = PROMPT_JINJA_ENV.from_string(RANK_MEMORY)
|
||||
system_prompt = template.render(goal=goal, sub_goal=sub_goal, results=[{"i": i, "content": s} for i,s in enumerate(tool_call_summaries)])
|
||||
user_prompt = " → rank: "
|
||||
_, msg = message_fit_in(form_message(system_prompt, user_prompt), chat_mdl.max_length)
|
||||
_, msg = message_fit_in(form_message(system_prompt, user_prompt), getattr(chat_mdl, 'max_length', 8096))
|
||||
ans = chat_mdl.chat(msg[0]["content"], msg[1:], stop="<|stop|>")
|
||||
return re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
|
||||
|
||||
@@ -378,7 +378,7 @@ def gen_json(system_prompt:str, user_prompt:str, chat_mdl, gen_conf = None):
|
||||
cached = get_llm_cache(chat_mdl.llm_name, system_prompt, user_prompt, gen_conf)
|
||||
if cached:
|
||||
return json_repair.loads(cached)
|
||||
_, msg = message_fit_in(form_message(system_prompt, user_prompt), chat_mdl.max_length)
|
||||
_, msg = message_fit_in(form_message(system_prompt, user_prompt), getattr(chat_mdl, 'max_length', 8096))
|
||||
ans = chat_mdl.chat(msg[0]["content"], msg[1:],gen_conf=gen_conf)
|
||||
ans = re.sub(r"(^.*</think>|```json\n|```\n*$)", "", ans, flags=re.DOTALL)
|
||||
try:
|
||||
@@ -641,7 +641,7 @@ def split_chunks(chunks, max_length: int):
|
||||
|
||||
|
||||
async def run_toc_from_text(chunks, chat_mdl, callback=None):
|
||||
input_budget = int(chat_mdl.max_length * INPUT_UTILIZATION) - num_tokens_from_string(
|
||||
input_budget = int(getattr(chat_mdl, 'max_length', 8096) * INPUT_UTILIZATION) - num_tokens_from_string(
|
||||
TOC_FROM_TEXT_USER + TOC_FROM_TEXT_SYSTEM
|
||||
)
|
||||
|
||||
|
||||
Reference in New Issue
Block a user