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import hashlib
import json
import logging
import os
import time
import traceback
from datetime import date, datetime
import litellm
from langfuse.model import CreateGeneration, CreateTrace
from tools.search_hadith import SearchHadith
from tools.search_mawsuah import SearchMawsuah
from tools.search_quran import SearchQuran
from util.prompt_mgr import PromptMgr
if os.environ.get("LANGFUSE_SECRET_KEY"):
from langfuse import Langfuse
lf = Langfuse()
lf.auth_check()
logger = logging.getLogger(__name__ + ".Ansari")
logger.setLevel(logging.INFO)
console_handler = logging.StreamHandler()
console_handler.setLevel(logging.INFO)
logger.addHandler(console_handler)
class Ansari:
def __init__(self, settings, message_logger=None, json_format=False):
self.settings = settings
sq = SearchQuran(settings.KALEMAT_API_KEY.get_secret_value())
sh = SearchHadith(settings.KALEMAT_API_KEY.get_secret_value())
sm = SearchMawsuah(settings.VECTARA_AUTH_TOKEN.get_secret_value(), settings.VECTARA_CUSTOMER_ID, settings.VECTARA_CORPUS_ID)
self.tools = {sq.get_fn_name(): sq, sh.get_fn_name(): sh, sm.get_fn_name(): sm}
self.model = settings.MODEL
self.pm = PromptMgr()
self.sys_msg = self.pm.bind(settings.SYSTEM_PROMPT_FILE_NAME).render()
self.functions = [x.get_function_description() for x in self.tools.values()]
self.message_history = [{"role": "system", "content": self.sys_msg}]
self.json_format = json_format
self.message_logger = message_logger
def set_message_logger(self, message_logger):
self.message_logger = message_logger
# The trace id is a hash of the first user input and the time.
def compute_trace_id(self):
today = date.today()
hashstring = str(today) + self.message_history[1]["content"]
result = hashlib.md5(hashstring.encode())
return "chash_" + result.hexdigest()
def greet(self):
self.greeting = self.pm.bind("greeting")
return self.greeting.render()
def process_input(self, user_input):
self.message_history.append({"role": "user", "content": user_input})
return self.process_message_history()
def log(self):
if not os.environ.get("LANGFUSE_SECRET_KEY"):
return
trace_id = self.compute_trace_id()
logger.info(f"trace id is {trace_id}")
trace = lf.trace(CreateTrace(id=trace_id, name="ansari-trace"))
generation = trace.generation(
CreateGeneration(
name="ansari-gen",
startTime=self.start_time,
endTime=datetime.now(),
model=self.settings.MODEL,
prompt=self.message_history[:-1],
completion=self.message_history[-1]["content"],
)
)
def replace_message_history(self, message_history):
self.message_history = [
{"role": "system", "content": self.sys_msg}
] + message_history
for m in self.process_message_history():
if m:
yield m
def process_message_history(self):
# Keep processing the user input until we get something from the assistant
self.start_time = datetime.now()
count = 0
failures = 0
while self.message_history[-1]["role"] != "assistant":
try:
logger.info(f"Processing one round {self.message_history}")
# This is pretty complicated so leaving a comment.
# We want to yield from so that we can send the sequence through the input
# Also use functions only if we haven't tried too many times
use_function = True
if count >= self.settings.MAX_FUNCTION_TRIES:
use_function = False
logger.warning("Not using functions -- tries exceeded")
yield from self.process_one_round(use_function)
count += 1
except Exception as e:
failures += 1
logger.warning("Exception occurred: {e}")
logger.warning(traceback.format_exc())
logger.warning("Retrying in 5 seconds...")
time.sleep(5)
if failures >= self.settings.MAX_FAILURES:
logger.error("Too many failures, aborting")
raise Exception("Too many failures")
break
self.log()
def process_one_round(self, use_function=True):
response = None
failures = 0
while not response:
try:
if use_function:
if self.json_format:
response = litellm.completion(
model=self.model,
messages=self.message_history,
stream=True,
functions=self.functions,
timeout=30.0,
temperature=0.0,
metadata={"generation-name": "ansari"},
response_format={"type": "json_object"},
num_retries=1,
)
else:
response = litellm.completion(
model=self.model,
messages=self.message_history,
stream=True,
functions=self.functions,
timeout=30.0,
temperature=0.0,
metadata={"generation-name": "ansari"},
num_retries=1,
)
else:
if self.json_format:
response = litellm.completion(
model=self.model,
messages=self.message_history,
stream=True,
timeout=30.0,
temperature=0.0,
response_format={"type": "json_object"},
metadata={"generation-name": "ansari"},
num_retries=1,
)
else:
response = litellm.completion(
model=self.model,
messages=self.message_history,
stream=True,
timeout=30.0,
temperature=0.0,
metadata={"generation-name": "ansari"},
num_retries=1,
)
except Exception as e:
failures += 1
logger.warning("Exception occurred: ", e)
logger.warning(traceback.format_exc())
logger.warning("Retrying in 5 seconds...")
time.sleep(5)
if failures >= self.settings.MAX_FAILURES:
logger.error("Too many failures, aborting")
raise Exception("Too many failures")
break
words = ""
function_name = ""
function_arguments = ""
response_mode = "" # words or fn
for tok in response:
logger.debug(f"Tok is {tok}")
delta = tok.choices[0].delta
if not response_mode:
# This code should only trigger the first
# time through the loop.
if "function_call" in delta and delta.function_call:
# We are in function mode
response_mode = "fn"
function_name = delta.function_call.name
else:
response_mode = "words"
logger.info("Response mode: " + response_mode)
# We process things differently depending on whether it is a function or a
# text
if response_mode == "words":
if delta.content == None: # End token
self.message_history.append({"role": "assistant", "content": words})
if self.message_logger:
self.message_logger.log("assistant", words)
break
elif delta.content != None:
words += delta.content
yield delta.content
else:
continue
elif response_mode == "fn":
logger.debug("Delta in: ", delta)
if (
not "function_call" in delta or delta["function_call"] is None
): # End token
function_call = function_name + "(" + function_arguments + ")"
# The function call below appends the function call to the message history
print(f"{function_name=}, {function_arguments=}")
yield self.process_fn_call(input, function_name, function_arguments)
#
break
elif (
"function_call" in delta
and delta.function_call
and delta.function_call.arguments
):
function_arguments += delta.function_call.arguments
logger.debug(f"Function arguments are {function_arguments}")
yield "" # delta['function_call']['arguments'] # we shouldn't yield anything if it's a fn
else:
logger.warning(f"Weird delta: {delta}")
continue
else:
raise Exception("Invalid response mode: " + response_mode)
def process_fn_call(self, orig_question, function_name, function_arguments):
if function_name in self.tools.keys():
args = json.loads(function_arguments)
query = args["query"]
results = self.tools[function_name].run_as_list(query)
logger.debug(f"Results are {results}")
# Now we have to pass the results back in
if len(results) > 0:
for result in results:
self.message_history.append(
{"role": "function", "name": function_name, "content": result}
)
if self.message_logger:
self.message_logger.log("function", result, function_name)
else:
self.message_history.append(
{
"role": "function",
"name": function_name,
"content": "No results found",
}
)
if self.message_logger:
self.message_logger.log(
"function", "No results found", function_name
)
else:
logger.warning(f"Unknown function name: {function_name}")
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