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Fixing duplicate llm_pkey errors #389

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merged 10 commits into from
Sep 17, 2024
Merged

Fixing duplicate llm_pkey errors #389

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4dc0648
Fixed for multithreading and clarity
HowieG Sep 13, 2024
a393331
dont need threading
HowieG Sep 13, 2024
3edb4e8
leftover line
HowieG Sep 13, 2024
d81695d
fixed for threading
HowieG Sep 14, 2024
fde9953
saving state. will replace with better solution
HowieG Sep 14, 2024
ab1c752
removing self from llm_event in handle_response llm tracker logic due…
HowieG Sep 14, 2024
8bbc4d1
cleaning up time travel output
HowieG Sep 14, 2024
48d9d02
Merge branch 'ttd-misc' into diplicate-key-bug
HowieG Sep 14, 2024
1ed9256
removing unused line
HowieG Sep 14, 2024
e42d6bf
Merge branch 'main' into concurrency-fixes
siyangqiu Sep 17, 2024
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1 change: 0 additions & 1 deletion agentops/llms/__init__.py
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Expand Up @@ -43,7 +43,6 @@ class LlmTracker:

def __init__(self, client):
self.client = client
self.completion = ""

def override_api(self):
"""
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50 changes: 24 additions & 26 deletions agentops/llms/anthropic.py
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Expand Up @@ -31,27 +31,27 @@
from anthropic.resources import AsyncMessages
from anthropic.types import Message

self.llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)
llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)

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if session is not None:
self.llm_event.session_id = session.session_id
llm_event.session_id = session.session_id

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def handle_stream_chunk(chunk: Message):
try:
# We take the first chunk and accumulate the deltas from all subsequent chunks to build one full chat completion
if chunk.type == "message_start":
self.llm_event.returns = chunk
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.model = kwargs["model"]
self.llm_event.prompt = kwargs["messages"]
self.llm_event.prompt_tokens = chunk.message.usage.input_tokens
self.llm_event.completion = {
llm_event.returns = chunk
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.model = kwargs["model"]
llm_event.prompt = kwargs["messages"]
llm_event.prompt_tokens = chunk.message.usage.input_tokens
llm_event.completion = {

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"role": chunk.message.role,
"content": "", # Always returned as [] in this instance type
}

elif chunk.type == "content_block_start":
if chunk.content_block.type == "text":
self.llm_event.completion["content"] += chunk.content_block.text
llm_event.completion["content"] += chunk.content_block.text

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elif chunk.content_block.type == "tool_use":
self.tool_id = chunk.content_block.id
Expand All @@ -62,7 +62,7 @@

elif chunk.type == "content_block_delta":
if chunk.delta.type == "text_delta":
self.llm_event.completion["content"] += chunk.delta.text
llm_event.completion["content"] += chunk.delta.text

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elif chunk.delta.type == "input_json_delta":
self.tool_event[self.tool_id].logs[
Expand All @@ -73,15 +73,15 @@
pass

elif chunk.type == "message_delta":
self.llm_event.completion_tokens = chunk.usage.output_tokens
llm_event.completion_tokens = chunk.usage.output_tokens

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elif chunk.type == "message_stop":
self.llm_event.end_timestamp = get_ISO_time()
self._safe_record(session, self.llm_event)
llm_event.end_timestamp = get_ISO_time()
self._safe_record(session, llm_event)

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except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
session, ErrorEvent(trigger_event=llm_event, exception=e)
)

kwargs_str = pprint.pformat(kwargs)
Expand Down Expand Up @@ -124,23 +124,21 @@

# Handle object responses
try:
self.llm_event.returns = response.model_dump()
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.prompt = kwargs["messages"]
self.llm_event.prompt_tokens = response.usage.input_tokens
self.llm_event.completion = {
llm_event.returns = response.model_dump()
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.prompt = kwargs["messages"]
llm_event.prompt_tokens = response.usage.input_tokens
llm_event.completion = {

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"role": "assistant",
"content": response.content[0].text,
}
self.llm_event.completion_tokens = response.usage.output_tokens
self.llm_event.model = response.model
self.llm_event.end_timestamp = get_ISO_time()
llm_event.completion_tokens = response.usage.output_tokens
llm_event.model = response.model
llm_event.end_timestamp = get_ISO_time()

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self._safe_record(session, self.llm_event)
self._safe_record(session, llm_event)

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except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
)
self._safe_record(session, ErrorEvent(trigger_event=llm_event, exception=e))

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kwargs_str = pprint.pformat(kwargs)
response = pprint.pformat(response)
logger.warning(
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46 changes: 22 additions & 24 deletions agentops/llms/cohere.py
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Expand Up @@ -52,32 +52,32 @@

# from cohere.types.chat import ChatGenerationChunk
# NOTE: Cohere only returns one message and its role will be CHATBOT which we are coercing to "assistant"
self.llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)
llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)

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if session is not None:
self.llm_event.session_id = session.session_id
llm_event.session_id = session.session_id

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self.action_events = {}

def handle_stream_chunk(chunk, session: Optional[Session] = None):

# We take the first chunk and accumulate the deltas from all subsequent chunks to build one full chat completion
if isinstance(chunk, StreamedChatResponse_StreamStart):
self.llm_event.returns = chunk
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.model = kwargs.get("model", "command-r-plus")
self.llm_event.prompt = kwargs["message"]
self.llm_event.completion = ""
llm_event.returns = chunk
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.model = kwargs.get("model", "command-r-plus")
llm_event.prompt = kwargs["message"]
llm_event.completion = ""

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return

try:
if isinstance(chunk, StreamedChatResponse_StreamEnd):
# StreamedChatResponse_TextGeneration = LLMEvent
self.llm_event.completion = {
llm_event.completion = {

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"role": "assistant",
"content": chunk.response.text,
}
self.llm_event.end_timestamp = get_ISO_time()
self._safe_record(session, self.llm_event)
llm_event.end_timestamp = get_ISO_time()
self._safe_record(session, llm_event)

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# StreamedChatResponse_SearchResults = ActionEvent
search_results = chunk.response.search_results
Expand Down Expand Up @@ -115,7 +115,7 @@
self._safe_record(session, action_event)

elif isinstance(chunk, StreamedChatResponse_TextGeneration):
self.llm_event.completion += chunk.text
llm_event.completion += chunk.text

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elif isinstance(chunk, StreamedChatResponse_ToolCallsGeneration):
pass
elif isinstance(chunk, StreamedChatResponse_CitationGeneration):
Expand All @@ -139,7 +139,7 @@

except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
session, ErrorEvent(trigger_event=llm_event, exception=e)
)

kwargs_str = pprint.pformat(kwargs)
Expand Down Expand Up @@ -175,35 +175,33 @@
# Not enough to record StreamedChatResponse_ToolCallsGeneration because the tool may have not gotten called

try:
self.llm_event.returns = response
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.prompt = []
llm_event.returns = response
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.prompt = []

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if response.chat_history:
role_map = {"USER": "user", "CHATBOT": "assistant", "SYSTEM": "system"}

for i in range(len(response.chat_history) - 1):
message = response.chat_history[i]
self.llm_event.prompt.append(
llm_event.prompt.append(

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{
"role": role_map.get(message.role, message.role),
"content": message.message,
}
)

last_message = response.chat_history[-1]
self.llm_event.completion = {
llm_event.completion = {

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"role": role_map.get(last_message.role, last_message.role),
"content": last_message.message,
}
self.llm_event.prompt_tokens = response.meta.tokens.input_tokens
self.llm_event.completion_tokens = response.meta.tokens.output_tokens
self.llm_event.model = kwargs.get("model", "command-r-plus")
llm_event.prompt_tokens = response.meta.tokens.input_tokens
llm_event.completion_tokens = response.meta.tokens.output_tokens
llm_event.model = kwargs.get("model", "command-r-plus")

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self._safe_record(session, self.llm_event)
self._safe_record(session, llm_event)

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except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
)
self._safe_record(session, ErrorEvent(trigger_event=llm_event, exception=e))

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kwargs_str = pprint.pformat(kwargs)
response = pprint.pformat(response)
logger.warning(
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50 changes: 23 additions & 27 deletions agentops/llms/groq.py
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Expand Up @@ -37,21 +37,21 @@
from groq.resources.chat import AsyncCompletions
from groq.types.chat import ChatCompletionChunk

self.llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)
llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)

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if session is not None:
self.llm_event.session_id = session.session_id
llm_event.session_id = session.session_id

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def handle_stream_chunk(chunk: ChatCompletionChunk):
# NOTE: prompt/completion usage not returned in response when streaming
# We take the first ChatCompletionChunk and accumulate the deltas from all subsequent chunks to build one full chat completion
if self.llm_event.returns == None:
self.llm_event.returns = chunk
if llm_event.returns == None:
llm_event.returns = chunk

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try:
accumulated_delta = self.llm_event.returns.choices[0].delta
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.model = chunk.model
self.llm_event.prompt = kwargs["messages"]
accumulated_delta = llm_event.returns.choices[0].delta
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.model = chunk.model
llm_event.prompt = kwargs["messages"]

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# NOTE: We assume for completion only choices[0] is relevant
choice = chunk.choices[0]
Expand All @@ -70,21 +70,19 @@

if choice.finish_reason:
# Streaming is done. Record LLMEvent
self.llm_event.returns.choices[0].finish_reason = (
choice.finish_reason
)
self.llm_event.completion = {
llm_event.returns.choices[0].finish_reason = choice.finish_reason
llm_event.completion = {

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"role": accumulated_delta.role,
"content": accumulated_delta.content,
"function_call": accumulated_delta.function_call,
"tool_calls": accumulated_delta.tool_calls,
}
self.llm_event.end_timestamp = get_ISO_time()
llm_event.end_timestamp = get_ISO_time()

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self._safe_record(session, self.llm_event)
self._safe_record(session, llm_event)

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except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
session, ErrorEvent(trigger_event=llm_event, exception=e)
)

kwargs_str = pprint.pformat(kwargs)
Expand Down Expand Up @@ -127,19 +125,17 @@

# v1.0.0+ responses are objects
try:
self.llm_event.returns = response.model_dump()
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.prompt = kwargs["messages"]
self.llm_event.prompt_tokens = response.usage.prompt_tokens
self.llm_event.completion = response.choices[0].message.model_dump()
self.llm_event.completion_tokens = response.usage.completion_tokens
self.llm_event.model = response.model

self._safe_record(session, self.llm_event)
llm_event.returns = response.model_dump()
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.prompt = kwargs["messages"]
llm_event.prompt_tokens = response.usage.prompt_tokens
llm_event.completion = response.choices[0].message.model_dump()
llm_event.completion_tokens = response.usage.completion_tokens
llm_event.model = response.model

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self._safe_record(session, llm_event)

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except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
)
self._safe_record(session, ErrorEvent(trigger_event=llm_event, exception=e))

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kwargs_str = pprint.pformat(kwargs)
response = pprint.pformat(response)
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50 changes: 23 additions & 27 deletions agentops/llms/litellm.py
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Expand Up @@ -49,21 +49,21 @@
from openai.types.chat import ChatCompletionChunk
from litellm.utils import CustomStreamWrapper

self.llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)
llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)

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if session is not None:
self.llm_event.session_id = session.session_id
llm_event.session_id = session.session_id

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def handle_stream_chunk(chunk: ChatCompletionChunk):
# NOTE: prompt/completion usage not returned in response when streaming
# We take the first ChatCompletionChunk and accumulate the deltas from all subsequent chunks to build one full chat completion
if self.llm_event.returns == None:
self.llm_event.returns = chunk
if llm_event.returns == None:
llm_event.returns = chunk

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try:
accumulated_delta = self.llm_event.returns.choices[0].delta
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.model = chunk.model
self.llm_event.prompt = kwargs["messages"]
accumulated_delta = llm_event.returns.choices[0].delta
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.model = chunk.model
llm_event.prompt = kwargs["messages"]

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# NOTE: We assume for completion only choices[0] is relevant
choice = chunk.choices[0]
Expand All @@ -82,21 +82,19 @@

if choice.finish_reason:
# Streaming is done. Record LLMEvent
self.llm_event.returns.choices[0].finish_reason = (
choice.finish_reason
)
self.llm_event.completion = {
llm_event.returns.choices[0].finish_reason = choice.finish_reason
llm_event.completion = {

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"role": accumulated_delta.role,
"content": accumulated_delta.content,
"function_call": accumulated_delta.function_call,
"tool_calls": accumulated_delta.tool_calls,
}
self.llm_event.end_timestamp = get_ISO_time()
llm_event.end_timestamp = get_ISO_time()

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self._safe_record(session, self.llm_event)
self._safe_record(session, llm_event)

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except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
session, ErrorEvent(trigger_event=llm_event, exception=e)
)

kwargs_str = pprint.pformat(kwargs)
Expand Down Expand Up @@ -149,19 +147,17 @@

# v1.0.0+ responses are objects
try:
self.llm_event.returns = response
self.llm_event.agent_id = check_call_stack_for_agent_id()
self.llm_event.prompt = kwargs["messages"]
self.llm_event.prompt_tokens = response.usage.prompt_tokens
self.llm_event.completion = response.choices[0].message.model_dump()
self.llm_event.completion_tokens = response.usage.completion_tokens
self.llm_event.model = response.model

self._safe_record(session, self.llm_event)
llm_event.returns = response
llm_event.agent_id = check_call_stack_for_agent_id()
llm_event.prompt = kwargs["messages"]
llm_event.prompt_tokens = response.usage.prompt_tokens
llm_event.completion = response.choices[0].message.model_dump()
llm_event.completion_tokens = response.usage.completion_tokens
llm_event.model = response.model

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self._safe_record(session, llm_event)

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except Exception as e:
self._safe_record(
session, ErrorEvent(trigger_event=self.llm_event, exception=e)
)
self._safe_record(session, ErrorEvent(trigger_event=llm_event, exception=e))

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kwargs_str = pprint.pformat(kwargs)
response = pprint.pformat(response)
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