Hua/nanobot
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

resolve conflicts with main

Browse Source
This commit is contained in:
Re-bin
2026-02-03 06:16:17 +00:00
parent 42f62c0c1a 30d6e4b4b6
commit eb20cea668
10 changed files with 109 additions and 28 deletions
Download Patch File Download Diff File Expand all files Collapse all files

41
nanobot/agent/context.py
View File

@@ -1,5 +1,7 @@
"""Context builder for assembling agent prompts."""
import base64
import mimetypes
from pathlib import Path
from typing import Any
@@ -114,32 +116,53 @@ When remembering something, write to {workspace_path}/memory/MEMORY.md"""
self,
history: list[dict[str, Any]],
current_message: str,
skill_names: list[str] | None = None
skill_names: list[str] | None = None,
media: list[str] | None = None,
) -> list[dict[str, Any]]:
"""
Build the complete message list for an LLM call.
Args:
history: Previous conversation messages.
current_message: The new user message.
skill_names: Optional skills to include.
media: Optional list of local file paths for images/media.
Returns:
List of messages including system prompt.
"""
messages = []
# System prompt
system_prompt = self.build_system_prompt(skill_names)
messages.append({"role": "system", "content": system_prompt})
# History
messages.extend(history)
# Current message
messages.append({"role": "user", "content": current_message})
# Current message (with optional image attachments)
user_content = self._build_user_content(current_message, media)
messages.append({"role": "user", "content": user_content})
return messages
def _build_user_content(self, text: str, media: list[str] | None) -> str | list[dict[str, Any]]:
"""Build user message content with optional base64-encoded images."""
if not media:
return text
images = []
for path in media:
p = Path(path)
mime, _ = mimetypes.guess_type(path)
if not p.is_file() or not mime or not mime.startswith("image/"):
continue
b64 = base64.b64encode(p.read_bytes()).decode()
images.append({"type": "image_url", "image_url": {"url": f"data:{mime};base64,{b64}"}})
if not images:
return text
return images + [{"type": "text", "text": text}]
def add_tool_result(
self,

9
nanobot/agent/loop.py
View File

@@ -152,7 +152,8 @@ class AgentLoop:
# Build initial messages (use get_history for LLM-formatted messages)
messages = self.context.build_messages(
history=session.get_history(),
current_message=msg.content
current_message=msg.content,
media=msg.media if msg.media else None,
)
# Agent loop
@@ -189,7 +190,8 @@ class AgentLoop:
# Execute tools
for tool_call in response.tool_calls:
logger.debug(f"Executing tool: {tool_call.name}")
args_str = json.dumps(tool_call.arguments)
logger.debug(f"Executing tool: {tool_call.name} with arguments: {args_str}")
result = await self.tools.execute(tool_call.name, tool_call.arguments)
messages = self.context.add_tool_result(
messages, tool_call.id, tool_call.name, result
@@ -281,7 +283,8 @@ class AgentLoop:
)
for tool_call in response.tool_calls:
logger.debug(f"Executing tool: {tool_call.name}")
args_str = json.dumps(tool_call.arguments)
logger.debug(f"Executing tool: {tool_call.name} with arguments: {args_str}")
result = await self.tools.execute(tool_call.name, tool_call.arguments)
messages = self.context.add_tool_result(
messages, tool_call.id, tool_call.name, result

9
nanobot/channels/base.py
View File

@@ -72,7 +72,14 @@ class BaseChannel(ABC):
if not allow_list:
return True
return str(sender_id) in allow_list
sender_str = str(sender_id)
if sender_str in allow_list:
return True
if "|" in sender_str:
for part in sender_str.split("|"):
if part and part in allow_list:
return True
return False
async def _handle_message(
self,

6
nanobot/channels/telegram.py
View File

@@ -199,8 +199,10 @@ class TelegramChannel(BaseChannel):
user = update.effective_user
chat_id = message.chat_id
# Get sender identifier (prefer username, fallback to user_id)
sender_id = str(user.username or user.id)
# Use stable numeric ID, but keep username for allowlist compatibility
sender_id = str(user.id)
if user.username:
sender_id = f"{sender_id}|{user.username}"
# Store chat_id for replies
self._chat_ids[sender_id] = chat_id

4
nanobot/cli/commands.py
View File

@@ -506,6 +506,7 @@ def cron_add(
at: str = typer.Option(None, "--at", help="Run once at time (ISO format)"),
deliver: bool = typer.Option(False, "--deliver", "-d", help="Deliver response to channel"),
to: str = typer.Option(None, "--to", help="Recipient for delivery"),
channel: str = typer.Option(None, "--channel", help="Channel for delivery (e.g. 'telegram', 'whatsapp')"),
):
"""Add a scheduled job."""
from nanobot.config.loader import get_data_dir
@@ -534,6 +535,7 @@ def cron_add(
message=message,
deliver=deliver,
to=to,
channel=channel,
)
console.print(f"[green]✓[/green] Added job '{job.name}' ({job.id})")
@@ -624,11 +626,13 @@ def status():
has_openrouter = bool(config.providers.openrouter.api_key)
has_anthropic = bool(config.providers.anthropic.api_key)
has_openai = bool(config.providers.openai.api_key)
has_gemini = bool(config.providers.gemini.api_key)
has_vllm = bool(config.providers.vllm.api_base)
console.print(f"OpenRouter API: {'[green]✓[/green]' if has_openrouter else '[dim]not set[/dim]'}")
console.print(f"Anthropic API: {'[green]✓[/green]' if has_anthropic else '[dim]not set[/dim]'}")
console.print(f"OpenAI API: {'[green]✓[/green]' if has_openai else '[dim]not set[/dim]'}")
console.print(f"Gemini API: {'[green]✓[/green]' if has_gemini else '[dim]not set[/dim]'}")
vllm_status = f"[green]✓ {config.providers.vllm.api_base}[/green]" if has_vllm else "[dim]not set[/dim]"
console.print(f"vLLM/Local: {vllm_status}")

10
nanobot/config/schema.py
View File

@@ -51,7 +51,9 @@ class ProvidersConfig(BaseModel):
openai: ProviderConfig = Field(default_factory=ProviderConfig)
openrouter: ProviderConfig = Field(default_factory=ProviderConfig)
groq: ProviderConfig = Field(default_factory=ProviderConfig)
zhipu: ProviderConfig = Field(default_factory=ProviderConfig)
vllm: ProviderConfig = Field(default_factory=ProviderConfig)
gemini: ProviderConfig = Field(default_factory=ProviderConfig)
class GatewayConfig(BaseModel):
@@ -90,20 +92,24 @@ class Config(BaseSettings):
return Path(self.agents.defaults.workspace).expanduser()
def get_api_key(self) -> str | None:
"""Get API key in priority order: OpenRouter > Anthropic > OpenAI > Groq > vLLM."""
"""Get API key in priority order: OpenRouter > Anthropic > OpenAI > Gemini > Zhipu > Groq > vLLM."""
return (
self.providers.openrouter.api_key or
self.providers.anthropic.api_key or
self.providers.openai.api_key or
self.providers.gemini.api_key or
self.providers.zhipu.api_key or
self.providers.groq.api_key or
self.providers.vllm.api_key or
None
)
def get_api_base(self) -> str | None:
"""Get API base URL if using OpenRouter or vLLM."""
"""Get API base URL if using OpenRouter, Zhipu or vLLM."""
if self.providers.openrouter.api_key:
return self.providers.openrouter.api_base or "https://openrouter.ai/api/v1"
if self.providers.zhipu.api_key:
return self.providers.zhipu.api_base
if self.providers.vllm.api_base:
return self.providers.vllm.api_base
return None

19
nanobot/providers/litellm_provider.py
View File

@@ -13,7 +13,7 @@ class LiteLLMProvider(LLMProvider):
"""
LLM provider using LiteLLM for multi-provider support.
Supports OpenRouter, Anthropic, OpenAI, and many other providers through
Supports OpenRouter, Anthropic, OpenAI, Gemini, and many other providers through
a unified interface.
"""
@@ -47,6 +47,10 @@ class LiteLLMProvider(LLMProvider):
os.environ.setdefault("ANTHROPIC_API_KEY", api_key)
elif "openai" in default_model or "gpt" in default_model:
os.environ.setdefault("OPENAI_API_KEY", api_key)
elif "gemini" in default_model.lower():
os.environ.setdefault("GEMINI_API_KEY", api_key)
elif "zhipu" in default_model or "glm" in default_model or "zai" in default_model:
os.environ.setdefault("ZHIPUAI_API_KEY", api_key)
elif "groq" in default_model:
os.environ.setdefault("GROQ_API_KEY", api_key)
@@ -83,11 +87,24 @@ class LiteLLMProvider(LLMProvider):
if self.is_openrouter and not model.startswith("openrouter/"):
model = f"openrouter/{model}"
# For Zhipu/Z.ai, ensure prefix is present
# Handle cases like "glm-4.7-flash" -> "zhipu/glm-4.7-flash"
if ("glm" in model.lower() or "zhipu" in model.lower()) and not (
model.startswith("zhipu/") or
model.startswith("zai/") or
model.startswith("openrouter/")
):
model = f"zhipu/{model}"
# For vLLM, use hosted_vllm/ prefix per LiteLLM docs
# Convert openai/ prefix to hosted_vllm/ if user specified it
if self.is_vllm:
model = f"hosted_vllm/{model}"
# For Gemini, ensure gemini/ prefix if not already present
if "gemini" in model.lower() and not model.startswith("gemini/"):
model = f"gemini/{model}"
kwargs: dict[str, Any] = {
"model": model,
"messages": messages,