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Merge branch 'main' into docker_anchors
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@Josh-XT
Josh-XT authored Oct 22, 2024
2 parents a7fe244 + 4254d87 commit eb9bacd
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Showing 8 changed files with 165 additions and 146 deletions.
54 changes: 42 additions & 12 deletions agixt/Agent.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,10 @@
ChainStep,
ChainStepArgument,
ChainStepResponse,
Chain as ChainDB,
Provider as ProviderModel,
User,
Extension,
UserPreferences,
get_session,
)
Expand Down Expand Up @@ -481,23 +483,49 @@ def update_agent_config(self, new_config, config_key):

if config_key == "commands":
for command_name, enabled in new_config.items():
# First try to find an existing command
command = session.query(Command).filter_by(name=command_name).first()

if not command:
# If the command doesn't exist, create it (this handles chain commands)
command = Command(name=command_name)
session.add(command)
session.commit()

agent_command = (
session.query(AgentCommand)
.filter_by(agent_id=agent.id, command_id=command.id)
.first()
)
# Check if this is a chain command
chain = session.query(ChainDB).filter_by(name=command_name).first()
if chain:
# Find or create the AGiXT Chains extension
extension = (
session.query(Extension)
.filter_by(name="AGiXT Chains")
.first()
)
if not extension:
extension = Extension(name="AGiXT Chains")
session.add(extension)
session.commit()

# Create a new command entry for the chain
command = Command(name=command_name, extension_id=extension.id)
session.add(command)
session.commit()
else:
logging.error(f"Command {command_name} not found.")
continue

# Now handle the agent command association
try:
agent_command = (
session.query(AgentCommand)
.filter_by(agent_id=agent.id, command_id=command.id)
.first()
)
except:
agent_command = None

if agent_command:
agent_command.state = enabled
else:
agent_command = AgentCommand(
agent_id=agent.id, command_id=command.id, state=enabled
agent_id=self.agent_id,
command_id=command.id,
state=enabled,
)
session.add(agent_command)
else:
Expand All @@ -511,7 +539,9 @@ def update_agent_config(self, new_config, config_key):
agent_setting.value = str(setting_value)
else:
agent_setting = AgentSettingModel(
agent_id=agent.id, name=setting_name, value=str(setting_value)
agent_id=agent.id,
name=setting_name,
value=str(setting_value),
)
session.add(agent_setting)

Expand Down
144 changes: 82 additions & 62 deletions agixt/XT.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -483,27 +483,18 @@ async def run_chain_step(
role=self.agent_name,
message=f"[ACTIVITY] Running prompt: `{prompt_name}` with args:\n```json\n{json.dumps(args, indent=2)}```",
)
if "user_input" in args:
user_input = args["user_input"]
del args["user_input"]
if "browse_links" not in args:
args["browse_links"] = False
if "log_output" in args:
del args["log_output"]
if "voice_response" in args:
del args["voice_response"]
if "log_user_input" in args:
del args["log_user_input"]
if "prompt_name" in args:
del args["prompt_name"]
if prompt_name != "":
result = await self.inference(
if "browse_links" not in args:
args["browse_links"] = False
args["prompt_name"] = prompt_name
args["log_user_input"] = False
args["voice_response"] = False
args["log_output"] = False
args["user_input"] = user_input
result = self.ApiClient.prompt_agent(
agent_name=agent_name,
prompt_name=prompt_name,
user_input=user_input,
log_user_input=False,
log_output=False,
voice_response=False,
**args,
prompt_args=args,
)
elif prompt_type == "chain":
self.conversation.log_interaction(
Expand Down Expand Up @@ -647,51 +638,73 @@ async def learn_from_websites(
async def learn_spreadsheet(self, user_input, file_path):
file_name = os.path.basename(file_path)
file_type = str(file_name).split(".")[-1]
if file_type.lower() == "csv":
df = pd.read_csv(file_path)
else: # Excel file
try:
if file_type.lower() == "csv":
df = pd.read_csv(file_path)
else: # Excel file
try:
xl = pd.ExcelFile(file_path)
if len(xl.sheet_names) > 1:
sheet_count = len(xl.sheet_names)
for i, sheet_name in enumerate(xl.sheet_names, 1):
df = xl.parse(sheet_name)
csv_file_path = file_path.replace(
f".{file_type}", f"_{i}.csv"
)
csv_file_name = os.path.basename(csv_file_path)
self.conversation.log_interaction(
role=self.agent_name,
message=f"[ACTIVITY] ({i}/{sheet_count}) Converted sheet `{sheet_name}` in `{file_name}` to CSV file `{csv_file_name}`.",
)
df.to_csv(csv_file_path, index=False)
message = await self.learn_spreadsheet(
user_input=user_input,
file_path=csv_file_path,
)
self.conversation.log_interaction(
role=self.agent_name, message=f"[ACTIVITY] {message}"
)
return f"Processed all sheets in [{file_name}]({file_path})."
else:
df = pd.read_excel(file_path)
except Exception as e:
self.conversation.log_interaction(
role=self.agent_name,
message=f"[ACTIVITY][ERROR] Failed to read Excel file `{file_name}`: {str(e)}",
)
return f"Failed to read [{file_name}]({file_path}). Error: {str(e)}"

try:
xl = pd.ExcelFile(file_path)
if len(xl.sheet_names) > 1:
sheet_count = len(xl.sheet_names)
for i, sheet_name in enumerate(xl.sheet_names, 1):
df = xl.parse(sheet_name)
csv_file_path = file_path.replace(f".{file_type}", f"_{i}.csv")
csv_file_name = os.path.basename(csv_file_path)
self.conversation.log_interaction(
role=self.agent_name,
message=f"[ACTIVITY] ({i}/{sheet_count}) Converted sheet `{sheet_name}` in `{file_name}` to CSV file `{csv_file_name}`.",
)
df.to_csv(csv_file_path, index=False)
message = await self.learn_spreadsheet(
user_input=user_input,
file_path=csv_file_path,
)
self.conversation.log_interaction(
role=self.agent_name, message=f"[ACTIVITY] {message}"
)
return f"Processed all sheets in [{file_name}]({file_path})."
else:
df = pd.read_excel(file_path)
df_dict = df.to_dict("records")
# Test JSON serialization before proceeding
json.dumps(df_dict)
except Exception as e:
self.conversation.log_interaction(
role=self.agent_name,
message=f"[ACTIVITY][ERROR] Failed to read Excel file `{file_name}`: {str(e)}",
)
return f"Failed to read [{file_name}]({file_path}). Error: {str(e)}"
logging.error(f"Error converting DataFrame to dict: {e}")
return f"Failed to process [{file_name}]({file_path}). Error converting data format: {str(e)}"

df_dict = df.to_dict("records")
self.input_tokens += get_tokens(json.dumps(df_dict))
for item in df_dict:
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
message = f"Content from file uploaded at {timestamp} named `{file_name}`:\n```json\n{json.dumps(item, indent=2)}```\n"
await self.file_reader.write_text_to_memory(
user_input=f"{user_input}\n{message}",
text=message,
external_source=f"file {file_path}",
)
try:
self.input_tokens += get_tokens(json.dumps(df_dict))
except Exception as e:
logging.error(f"Error calculating tokens: {e}")
# Continue processing even if token calculation fails

return f"Read [{file_name}]({file_path}) into memory."
try:
for item in df_dict:
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
message = f"Content from file uploaded at {timestamp} named `{file_name}`:\n```json\n{json.dumps(item, indent=2)}```\n"
await self.file_reader.write_text_to_memory(
user_input=f"{user_input}\n{message}",
text=message,
external_source=f"file {file_path}",
)
return f"Read [{file_name}]({file_path}) into memory."
except Exception as e:
logging.error(f"Error writing to memory: {e}")
return f"Failed to save [{file_name}]({file_path}) to memory. Error: {str(e)}"

except Exception as e:
logging.error(f"Unexpected error processing spreadsheet: {e}")
return f"Failed to process [{file_name}]({file_path}). Unexpected error: {str(e)}"

async def learn_from_file(
self,
Expand Down Expand Up @@ -756,7 +769,7 @@ async def learn_from_file(
message=f"[ACTIVITY] Converting PowerPoint file [{file_name}]({file_url}) to PDF.",
)
try:
subprocess.run(
result = subprocess.run(
[
"libreoffice",
"--headless",
Expand All @@ -768,10 +781,17 @@ async def learn_from_file(
],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
timeout=30,
)
if result.returncode != 0:
raise Exception(
f"Conversion failed: {result.stderr.decode('utf-8', errors='ignore')}"
)
except Exception as e:
logging.error(f"Error converting PowerPoint to PDF: {e}")
return f"Failed to convert PowerPoint file [{file_name}]({file_url}) to PDF. Error: {str(e)}"
file_path = pdf_file_path
file_type = "pdf"
if user_input == "":
user_input = "Describe each stage of this image."
disallowed_types = ["exe", "bin", "rar"]
Expand Down Expand Up @@ -1328,7 +1348,7 @@ async def chat_completions(self, prompt: ChatCompletions):
analyze_user_input = (
str(self.agent_settings["analyze_user_input"]).lower() == "true"
)
auto_continue = False
auto_continue = True
if "auto_continue" in self.agent_settings:
auto_continue = str(self.agent_settings["auto_continue"]).lower() == "true"
include_sources = False
Expand Down
28 changes: 4 additions & 24 deletions agixt/endpoints/Agent.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -344,30 +344,10 @@ async def toggle_command(
raise HTTPException(status_code=403, detail="Access Denied")
ApiClient = get_api_client(authorization=authorization)
agent = Agent(agent_name=agent_name, user=user, ApiClient=ApiClient)
try:
if payload.command_name == "*":
for each_command_name in agent.AGENT_CONFIG["commands"]:
agent.AGENT_CONFIG["commands"][each_command_name] = payload.enable

agent.update_agent_config(
new_config=agent.AGENT_CONFIG["commands"], config_key="commands"
)
return ResponseMessage(
message=f"All commands enabled for agent '{agent_name}'."
)
else:
agent.AGENT_CONFIG["commands"][payload.command_name] = payload.enable
agent.update_agent_config(
new_config=agent.AGENT_CONFIG["commands"], config_key="commands"
)
return ResponseMessage(
message=f"Command '{payload.command_name}' toggled for agent '{agent_name}'."
)
except Exception as e:
raise HTTPException(
status_code=500,
detail=f"Error enabling all commands for agent '{agent_name}': {str(e)}",
)
update_config = agent.update_agent_config(
new_config={payload.command_name: payload.enable}, config_key="commands"
)
return ResponseMessage(message=update_config)


# Get agent browsed links
Expand Down
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