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https://github.com/open-webui/pipelines
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feat: functions
This commit is contained in:
Timothy J. Baek
parent
6fa2f2c450
commit
828ad33cce
191
examples/function_calling_filter_pipeline.py
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191
examples/function_calling_filter_pipeline.py
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from typing import List, Optional
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from pydantic import BaseModel
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from schemas import OpenAIChatMessage
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import os
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import requests
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import json
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from utils.main import (
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get_last_user_message,
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add_or_update_system_message,
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get_function_specs,
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)
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from typing import Literal
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class Pipeline:
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def __init__(self):
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# Pipeline filters are only compatible with Open WebUI
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# You can think of filter pipeline as a middleware that can be used to edit the form data before it is sent to the OpenAI API.
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self.type = "filter"
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# Assign a unique identifier to the pipeline.
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# The identifier must be unique across all pipelines.
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# The identifier must be an alphanumeric string that can include underscores or hyphens. It cannot contain spaces, special characters, slashes, or backslashes.
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self.id = "function_calling_filter_pipeline"
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self.name = "Function Calling Filter"
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class Valves(BaseModel):
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# List target pipeline ids (models) that this filter will be connected to.
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# If you want to connect this filter to all pipelines, you can set pipelines to ["*"]
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pipelines: List[str] = []
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# Assign a priority level to the filter pipeline.
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# The priority level determines the order in which the filter pipelines are executed.
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# The lower the number, the higher the priority.
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priority: int = 0
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# Valves for function calling
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OPENAI_API_BASE_URL: str
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OPENAI_API_KEY: str
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TASK_MODEL: str
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TEMPLATE: str
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# Initialize valves
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self.valves = Valves(
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**{
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"pipelines": ["*"], # Connect to all pipelines
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"OPENAI_API_BASE_URL": "https://api.openai.com/v1",
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"OPENAI_API_KEY": os.getenv("OPENAI_API_KEY"),
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"TASK_MODEL": "gpt-3.5-turbo",
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"TEMPLATE": """Use the following context as your learned knowledge, inside <context></context> XML tags.
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<context>
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{{CONTEXT}}
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</context>
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When answer to user:
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- If you don't know, just say that you don't know.
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- If you don't know when you are not sure, ask for clarification.
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Avoid mentioning that you obtained the information from the context.
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And answer according to the language of the user's question.""",
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}
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)
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class Functions:
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def get_current_weather(
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self,
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location: str,
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unit: Literal["metric", "fahrenheit"] = "fahrenheit",
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) -> str:
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"""
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Get the current weather for a location. If the location is not found, return an empty string.
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:param location: The location to get the weather for.
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:param unit: The unit to get the weather in. Default is fahrenheit.
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:return: The current weather for the location.
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"""
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print(location, unit)
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return f"{location}: Sunny"
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def get_user_name(self, user_id: str) -> str:
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"""
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Get the user's name from the user_id.
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"""
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print(user_id)
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return "John Doe"
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self.functions = Functions()
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async def on_startup(self):
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# This function is called when the server is started.
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print(f"on_startup:{__name__}")
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pass
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async def on_shutdown(self):
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# This function is called when the server is stopped.
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print(f"on_shutdown:{__name__}")
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pass
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async def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
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if body.get("title", False):
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return body
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print(f"pipe:{__name__}")
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print(user)
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user_message = get_last_user_message(body["messages"])
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function_specs = get_function_specs(self.functions)
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fc_system_prompt = (
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f"Functions: {json.dumps(function_specs, indent=2)}"
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+ """
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If a function doesn't match the query, return an empty string. Else, pick a function, fill in the parameters from the function's schema, and return it in the format { name: \"functionName\", parameters: { key: value } }. Only pick a function if the user asks."
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"""
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)
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print(fc_system_prompt)
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r = None
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try:
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r = requests.post(
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url=f"{self.valves.OPENAI_API_BASE_URL}/chat/completions",
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json={
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"model": self.valves.TASK_MODEL,
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"messages": [
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{
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"role": "system",
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"content": fc_system_prompt,
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},
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{
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"role": "user",
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"content": "History:\n"
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+ "\n".join(
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[
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f"{message['role']}: {message['content']}"
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for message in body["messages"][::-1][:4]
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]
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)
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+ f"Query: {user_message}",
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},
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],
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# TODO: dynamically add response_format?
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# "response_format": {"type": "json_object"},
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},
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headers={
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"Authorization": f"Bearer {self.valves.OPENAI_API_KEY}",
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"Content-Type": "application/json",
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},
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stream=False,
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)
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r.raise_for_status()
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response = r.json()
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content = response["choices"][0]["message"]["content"]
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if content != "":
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result = json.loads(content)
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print(result)
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#
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if "name" in result:
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function = getattr(self.functions, result["name"])
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function_result = None
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try:
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function_result = function(**result["parameters"])
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except Exception as e:
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print(e)
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if function_result:
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system_prompt = self.valves.TEMPLATE.replace(
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"{{CONTEXT}}", function_result
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)
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print(system_prompt)
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messages = add_or_update_system_message(
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system_prompt, body["messages"]
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)
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return {**body, "messages": messages}
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except Exception as e:
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print(f"Error: {e}")
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if r:
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try:
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print(r.json())
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except:
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pass
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return body
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@ -4,6 +4,9 @@ import time
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from typing import List
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from schemas import OpenAIChatMessage
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import inspect
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from typing import get_type_hints, Literal
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def stream_message_template(model: str, message: str):
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return {
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@ -42,3 +45,95 @@ def get_last_assistant_message(messages: List[dict]) -> str:
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return item["text"]
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return message["content"]
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return None
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def add_or_update_system_message(content: str, messages: List[dict]):
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"""
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Adds a new system message at the beginning of the messages list
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or updates the existing system message at the beginning.
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:param msg: The message to be added or appended.
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:param messages: The list of message dictionaries.
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:return: The updated list of message dictionaries.
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"""
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if messages and messages[0].get("role") == "system":
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messages[0]["content"] += f"{content}\n{messages[0]['content']}"
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else:
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# Insert at the beginning
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messages.insert(0, {"role": "system", "content": content})
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return messages
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def doc_to_dict(docstring):
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lines = docstring.split("\n")
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description = lines[1].strip()
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param_dict = {}
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for line in lines:
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if ":param" in line:
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line = line.replace(":param", "").strip()
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param, desc = line.split(":", 1)
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param_dict[param.strip()] = desc.strip()
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ret_dict = {"description": description, "params": param_dict}
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return ret_dict
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def get_function_specs(functions) -> List[dict]:
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function_list = [
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{"name": func, "function": getattr(functions, func)}
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for func in dir(functions)
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if callable(getattr(functions, func)) and not func.startswith("__")
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]
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specs = []
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for function_item in function_list:
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function_name = function_item["name"]
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function = function_item["function"]
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function_doc = doc_to_dict(function.__doc__ or function_name)
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specs.append(
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{
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"name": function_name,
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# TODO: multi-line desc?
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"description": function_doc.get("description", function_name),
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"parameters": {
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"type": "object",
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"properties": {
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param_name: {
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"type": param_annotation.__name__.lower(),
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**(
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{
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"enum": (
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param_annotation.__args__
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if hasattr(param_annotation, "__args__")
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else None
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)
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}
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if hasattr(param_annotation, "__args__")
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else {}
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),
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"description": function_doc.get("params", {}).get(
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param_name, param_name
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),
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}
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for param_name, param_annotation in get_type_hints(
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function
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).items()
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if param_name != "return"
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},
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"required": [
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name
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for name, param in inspect.signature(
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function
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).parameters.items()
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if param.default is param.empty
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],
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},
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}
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)
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return specs
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