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https://github.com/crewAIInc/crewAI.git
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4 Commits
bugfix/fix
...
devin/1740
| Author | SHA1 | Date | |
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46dfa8577c | ||
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ed1bfe7b6f | ||
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435f372796 | ||
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02c63fbcb9 |
@@ -114,6 +114,7 @@ class Agent(BaseAgent):
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@model_validator(mode="after")
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def post_init_setup(self):
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self._set_knowledge()
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self.agent_ops_agent_name = self.role
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self.llm = create_llm(self.llm)
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@@ -133,11 +134,8 @@ class Agent(BaseAgent):
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self.cache_handler = CacheHandler()
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self.set_cache_handler(self.cache_handler)
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def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
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def _set_knowledge(self):
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try:
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if self.embedder is None and crew_embedder:
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self.embedder = crew_embedder
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if self.knowledge_sources:
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full_pattern = re.compile(r"[^a-zA-Z0-9\-_\r\n]|(\.\.)")
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knowledge_agent_name = f"{re.sub(full_pattern, '_', self.role)}"
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@@ -351,6 +351,3 @@ class BaseAgent(ABC, BaseModel):
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if not self._rpm_controller:
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self._rpm_controller = rpm_controller
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self.create_agent_executor()
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def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
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pass
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@@ -216,43 +216,10 @@ MODELS = {
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"watsonx/ibm/granite-3-8b-instruct",
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],
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"bedrock": [
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"bedrock/us.amazon.nova-pro-v1:0",
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"bedrock/us.amazon.nova-micro-v1:0",
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"bedrock/us.amazon.nova-lite-v1:0",
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"bedrock/us.anthropic.claude-3-5-sonnet-20240620-v1:0",
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"bedrock/us.anthropic.claude-3-5-haiku-20241022-v1:0",
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"bedrock/us.anthropic.claude-3-5-sonnet-20241022-v2:0",
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"bedrock/us.anthropic.claude-3-7-sonnet-20250219-v1:0",
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"bedrock/us.anthropic.claude-3-sonnet-20240229-v1:0",
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"bedrock/us.anthropic.claude-3-opus-20240229-v1:0",
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"bedrock/us.anthropic.claude-3-haiku-20240307-v1:0",
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"bedrock/us.meta.llama3-2-11b-instruct-v1:0",
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"bedrock/us.meta.llama3-2-3b-instruct-v1:0",
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"bedrock/us.meta.llama3-2-90b-instruct-v1:0",
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"bedrock/us.meta.llama3-2-1b-instruct-v1:0",
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"bedrock/us.meta.llama3-1-8b-instruct-v1:0",
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"bedrock/us.meta.llama3-1-70b-instruct-v1:0",
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"bedrock/us.meta.llama3-3-70b-instruct-v1:0",
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"bedrock/us.meta.llama3-1-405b-instruct-v1:0",
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"bedrock/eu.anthropic.claude-3-5-sonnet-20240620-v1:0",
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"bedrock/eu.anthropic.claude-3-sonnet-20240229-v1:0",
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"bedrock/eu.anthropic.claude-3-haiku-20240307-v1:0",
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"bedrock/eu.meta.llama3-2-3b-instruct-v1:0",
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"bedrock/eu.meta.llama3-2-1b-instruct-v1:0",
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"bedrock/apac.anthropic.claude-3-5-sonnet-20240620-v1:0",
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"bedrock/apac.anthropic.claude-3-5-sonnet-20241022-v2:0",
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"bedrock/apac.anthropic.claude-3-sonnet-20240229-v1:0",
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"bedrock/apac.anthropic.claude-3-haiku-20240307-v1:0",
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"bedrock/amazon.nova-pro-v1:0",
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"bedrock/amazon.nova-micro-v1:0",
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"bedrock/amazon.nova-lite-v1:0",
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"bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0",
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"bedrock/anthropic.claude-3-5-haiku-20241022-v1:0",
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"bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0",
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"bedrock/anthropic.claude-3-7-sonnet-20250219-v1:0",
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"bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
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"bedrock/anthropic.claude-3-opus-20240229-v1:0",
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"bedrock/anthropic.claude-3-haiku-20240307-v1:0",
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"bedrock/anthropic.claude-3-opus-20240229-v1:0",
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"bedrock/anthropic.claude-v2:1",
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"bedrock/anthropic.claude-v2",
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"bedrock/anthropic.claude-instant-v1",
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@@ -267,6 +234,8 @@ MODELS = {
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"bedrock/ai21.j2-mid-v1",
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"bedrock/ai21.j2-ultra-v1",
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"bedrock/ai21.jamba-instruct-v1:0",
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"bedrock/meta.llama2-13b-chat-v1",
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"bedrock/meta.llama2-70b-chat-v1",
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"bedrock/mistral.mistral-7b-instruct-v0:2",
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"bedrock/mistral.mixtral-8x7b-instruct-v0:1",
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],
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@@ -600,7 +600,6 @@ class Crew(BaseModel):
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agent.i18n = i18n
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# type: ignore[attr-defined] # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
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agent.crew = self # type: ignore[attr-defined]
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agent.set_knowledge(crew_embedder=self.embedder)
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# TODO: Create an AgentFunctionCalling protocol for future refactoring
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if not agent.function_calling_llm: # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
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agent.function_calling_llm = self.function_calling_llm # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
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@@ -4,7 +4,7 @@ SQLite-based implementation of flow state persistence.
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import json
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import sqlite3
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from datetime import datetime, timezone
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from datetime import datetime
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from pathlib import Path
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from typing import Any, Dict, Optional, Union
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@@ -34,7 +34,6 @@ class SQLiteFlowPersistence(FlowPersistence):
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ValueError: If db_path is invalid
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"""
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from crewai.utilities.paths import db_storage_path
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# Get path from argument or default location
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path = db_path or str(Path(db_storage_path()) / "flow_states.db")
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@@ -47,8 +46,7 @@ class SQLiteFlowPersistence(FlowPersistence):
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def init_db(self) -> None:
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"""Create the necessary tables if they don't exist."""
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with sqlite3.connect(self.db_path) as conn:
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conn.execute(
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"""
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conn.execute("""
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CREATE TABLE IF NOT EXISTS flow_states (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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flow_uuid TEXT NOT NULL,
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@@ -56,15 +54,12 @@ class SQLiteFlowPersistence(FlowPersistence):
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timestamp DATETIME NOT NULL,
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state_json TEXT NOT NULL
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)
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"""
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)
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""")
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# Add index for faster UUID lookups
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conn.execute(
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"""
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conn.execute("""
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CREATE INDEX IF NOT EXISTS idx_flow_states_uuid
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ON flow_states(flow_uuid)
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"""
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)
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""")
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def save_state(
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self,
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@@ -90,22 +85,19 @@ class SQLiteFlowPersistence(FlowPersistence):
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)
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with sqlite3.connect(self.db_path) as conn:
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conn.execute(
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"""
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conn.execute("""
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INSERT INTO flow_states (
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flow_uuid,
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method_name,
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timestamp,
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state_json
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) VALUES (?, ?, ?, ?)
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""",
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(
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flow_uuid,
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method_name,
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datetime.now(timezone.utc).isoformat(),
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json.dumps(state_dict),
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),
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)
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""", (
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flow_uuid,
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method_name,
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datetime.utcnow().isoformat(),
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json.dumps(state_dict),
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))
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def load_state(self, flow_uuid: str) -> Optional[Dict[str, Any]]:
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"""Load the most recent state for a given flow UUID.
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@@ -117,16 +109,13 @@ class SQLiteFlowPersistence(FlowPersistence):
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The most recent state as a dictionary, or None if no state exists
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"""
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with sqlite3.connect(self.db_path) as conn:
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cursor = conn.execute(
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"""
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cursor = conn.execute("""
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SELECT state_json
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FROM flow_states
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WHERE flow_uuid = ?
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ORDER BY id DESC
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LIMIT 1
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""",
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(flow_uuid,),
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)
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""", (flow_uuid,))
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row = cursor.fetchone()
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if row:
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@@ -30,14 +30,8 @@ class TokenCalcHandler(CustomLogger):
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if hasattr(usage, "prompt_tokens"):
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self.token_cost_process.sum_prompt_tokens(usage.prompt_tokens)
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if hasattr(usage, "completion_tokens"):
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self.token_cost_process.sum_completion_tokens(
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usage.completion_tokens
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)
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if (
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hasattr(usage, "prompt_tokens_details")
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and usage.prompt_tokens_details
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and usage.prompt_tokens_details.cached_tokens
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):
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self.token_cost_process.sum_completion_tokens(usage.completion_tokens)
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if hasattr(usage, "prompt_tokens_details") and usage.prompt_tokens_details:
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self.token_cost_process.sum_cached_prompt_tokens(
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usage.prompt_tokens_details.cached_tokens
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)
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