diff --git a/docs/02-dynamic-routes.ipynb b/docs/02-dynamic-routes.ipynb
index 06c4f737be0526d1dba1ea670bdcc09dc2b9d1dd..d024ded3cfd35d255513479809fe7586b78822af 100644
--- a/docs/02-dynamic-routes.ipynb
+++ b/docs/02-dynamic-routes.ipynb
@@ -46,9 +46,36 @@
"metadata": {
"id": "dLElfRhgur0v"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "[notice] A new release of pip is available: 23.1.2 -> 24.0\n",
+ "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Requirement already satisfied: tzdata in c:\\users\\siraj\\documents\\personal\\work\\aurelio\\virtual environments\\semantic_router\\lib\\site-packages (2024.1)\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "[notice] A new release of pip is available: 23.1.2 -> 24.0\n",
+ "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
+ ]
+ }
+ ],
"source": [
- "!pip install -qU semantic-router==0.0.34"
+ "!pip install -qU semantic-router==0.0.34\n",
+ "!pip install tzdata"
]
},
{
@@ -136,7 +163,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "\u001b[32m2024-04-27 02:19:43 INFO semantic_router.utils.logger local\u001b[0m\n"
+ "\u001b[32m2024-04-29 01:50:52 INFO semantic_router.utils.logger local\u001b[0m\n"
]
}
],
@@ -255,7 +282,7 @@
{
"data": {
"text/plain": [
- "'18:19'"
+ "'17:50'"
]
},
"execution_count": 6,
@@ -369,7 +396,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "\u001b[32m2024-04-27 02:19:45 INFO semantic_router.utils.logger Adding `get_time` route\u001b[0m\n"
+ "\u001b[32m2024-04-29 01:50:53 INFO semantic_router.utils.logger Adding `get_time` route\u001b[0m\n"
]
}
],
@@ -411,48 +438,18 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "\u001b[33m2024-04-27 02:19:45 WARNING semantic_router.utils.logger No LLM provided for dynamic route, will use OpenAI LLM default. Ensure API key is set in OPENAI_API_KEY environment variable.\u001b[0m\n",
- "\u001b[32m2024-04-27 02:19:45 INFO semantic_router.utils.logger Extracting function input...\u001b[0m\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "##################################################\n",
- "tools\n",
- "None\n",
- "##################################################\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\u001b[32m2024-04-27 02:19:46 INFO semantic_router.utils.logger LLM output: {\n",
+ "\u001b[33m2024-04-29 01:50:54 WARNING semantic_router.utils.logger No LLM provided for dynamic route, will use OpenAI LLM default. Ensure API key is set in OPENAI_API_KEY environment variable.\u001b[0m\n",
+ "\u001b[32m2024-04-29 01:50:54 INFO semantic_router.utils.logger Extracting function input...\u001b[0m\n",
+ "\u001b[32m2024-04-29 01:50:55 INFO semantic_router.utils.logger LLM output: {\n",
"\t\"timezone\": \"America/New_York\"\n",
"}\u001b[0m\n",
- "\u001b[32m2024-04-27 02:19:46 INFO semantic_router.utils.logger Function inputs: {'timezone': 'America/New_York'}\u001b[0m\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "##################################################\n",
- "completion.choices[0].message.tool_calls\n",
- "None\n",
- "##################################################\n",
- "##################################################\n",
- "extracted_inputs\n",
- "{'timezone': 'America/New_York'}\n",
- "##################################################\n"
+ "\u001b[32m2024-04-29 01:50:55 INFO semantic_router.utils.logger Function inputs: {'timezone': 'America/New_York'}\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
- "'18:19'"
+ "'17:50'"
]
},
"execution_count": 12,
@@ -473,7 +470,7 @@
{
"data": {
"text/plain": [
- "OpenAILLM(name='gpt-3.5-turbo', client=<openai.OpenAI object at 0x00000152CAD11ED0>, temperature=0.01, max_tokens=200)"
+ "OpenAILLM(name='gpt-3.5-turbo', client=<openai.OpenAI object at 0x00000129AFF58190>, temperature=0.01, max_tokens=200)"
]
},
"execution_count": 13,
diff --git a/docs/10-dynamic-routes-via-openai-function-calling.ipynb b/docs/10-dynamic-routes-via-openai-function-calling.ipynb
index e20ade1b8218bdf94269d24669f9b7f79a991949..79a68dc05db8880b598fb976bff332899a42f4a0 100644
--- a/docs/10-dynamic-routes-via-openai-function-calling.ipynb
+++ b/docs/10-dynamic-routes-via-openai-function-calling.ipynb
@@ -40,11 +40,21 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"metadata": {
"id": "dLElfRhgur0v"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "[notice] A new release of pip is available: 23.1.2 -> 24.0\n",
+ "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
+ ]
+ }
+ ],
"source": [
"!pip install -qU semantic-router==0.0.34"
]
@@ -69,7 +79,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 3,
"metadata": {
"id": "kc9Ty6Lgur0x"
},
@@ -78,7 +88,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "c:\\Users\\Siraj\\Documents\\Personal\\Work\\Aurelio\\Virtual Environments\\semantic_router\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+ "c:\\Users\\Siraj\\Documents\\Personal\\Work\\Aurelio\\Virtual Environments\\semantic_router_2\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
@@ -121,7 +131,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -134,7 +144,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "\u001b[32m2024-04-28 22:54:05 INFO semantic_router.utils.logger local\u001b[0m\n"
+ "\u001b[32m2024-04-29 01:48:49 INFO semantic_router.utils.logger local\u001b[0m\n"
]
}
],
@@ -170,7 +180,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 5,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -185,7 +195,7 @@
"RouteChoice(name='chitchat', function_call=None, similarity_score=None)"
]
},
- "execution_count": 4,
+ "execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@@ -214,7 +224,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 6,
"metadata": {
"id": "5jaF1Xa5ur0y"
},
@@ -240,7 +250,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -253,10 +263,10 @@
{
"data": {
"text/plain": [
- "'14:54'"
+ "'17:48'"
]
},
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
@@ -276,7 +286,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -294,7 +304,7 @@
" 'output': \"<class 'str'>\"}"
]
},
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -308,7 +318,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
@@ -323,7 +333,7 @@
" 'required': ['timezone']}}}"
]
},
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -346,7 +356,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"metadata": {
"id": "iesBG9P3ur0z"
},
@@ -375,7 +385,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 11,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -388,7 +398,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "\u001b[32m2024-04-28 22:54:06 INFO semantic_router.utils.logger Adding `get_time` route\u001b[0m\n"
+ "\u001b[32m2024-04-29 01:48:50 INFO semantic_router.utils.logger Adding `get_time` route\u001b[0m\n"
]
}
],
@@ -407,7 +417,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 12,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -421,7 +431,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "\u001b[33m2024-04-28 22:54:07 WARNING semantic_router.utils.logger No LLM provided for dynamic route, will use OpenAI LLM default. Ensure API key is set in OPENAI_API_KEY environment variable.\u001b[0m\n"
+ "\u001b[33m2024-04-29 01:48:52 WARNING semantic_router.utils.logger No LLM provided for dynamic route, will use OpenAI LLM default. Ensure API key is set in OPENAI_API_KEY environment variable.\u001b[0m\n"
]
},
{
@@ -430,7 +440,7 @@
"RouteChoice(name='get_time', function_call={'timezone': 'America/New_York'}, similarity_score=None)"
]
},
- "execution_count": 11,
+ "execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
@@ -442,16 +452,16 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "'14:54'"
+ "'17:48'"
]
},
- "execution_count": 12,
+ "execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@@ -478,7 +488,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
@@ -487,7 +497,7 @@
"RouteChoice(name='chitchat', function_call=None, similarity_score=None)"
]
},
- "execution_count": 13,
+ "execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
@@ -506,7 +516,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
@@ -515,7 +525,7 @@
"RouteChoice(name=None, function_call=None, similarity_score=None)"
]
},
- "execution_count": 14,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
diff --git a/semantic_router/llms/openai.py b/semantic_router/llms/openai.py
index 9072821092c32bb105865624b051890d21c48757..0989df3e91439c766f7530c9a7db99906d3c87de 100644
--- a/semantic_router/llms/openai.py
+++ b/semantic_router/llms/openai.py
@@ -1,5 +1,5 @@
import os
-from typing import Any, List, Optional
+from typing import List, Optional, Any
import openai
@@ -8,6 +8,7 @@ from semantic_router.schema import Message
from semantic_router.utils.defaults import EncoderDefault
from semantic_router.utils.logger import logger
import json
+from openai.types.chat import ChatCompletionMessageToolCall
class OpenAILLM(BaseLLM):
client: Optional[openai.OpenAI]
@@ -36,12 +37,12 @@ class OpenAILLM(BaseLLM):
self.temperature = temperature
self.max_tokens = max_tokens
- def __call__(self, messages: List[Message], function_schema: dict = None) -> str:
+ def __call__(self, messages: List[Message], openai_function_schema: Optional[dict[str, Any]] = None) -> str:
if self.client is None:
raise ValueError("OpenAI client is not initialized.")
try:
- if function_schema:
- tools = [function_schema]
+ if openai_function_schema:
+ tools = [openai_function_schema]
else:
tools = None
completion = self.client.chat.completions.create(
@@ -49,34 +50,27 @@ class OpenAILLM(BaseLLM):
messages=[m.to_openai() for m in messages],
temperature=self.temperature,
max_tokens=self.max_tokens,
- tools=tools,
+ tools=tools, # type: ignore # MyPy expecting Iterable[ChatCompletionToolParam] | NotGiven, but dict is accepted by OpenAI.
)
output = completion.choices[0].message.content
- if function_schema:
+ if openai_function_schema:
return completion.choices[0].message.tool_calls
- # tool_calls = completion.choices[0].message.tool_calls
- # if not tool_calls:
- # raise Exception("No tool calls available in the completion response.")
- # tool_call = tool_calls[0]
- # arguments_json = tool_call.function.arguments
- # arguments_dict = json.loads(arguments_json)
- # return arguments_dict
-
if not output:
raise Exception("No output generated")
return output
except Exception as e:
logger.error(f"LLM error: {e}")
raise Exception(f"LLM error: {e}") from e
-#
- def extract_function_inputs_openai(self, query: str, function_schema: dict) -> dict:
+
+
+ def extract_function_inputs_openai(self, query: str, openai_function_schema: dict[str, Any]) -> dict:
messages = []
system_prompt = "You are an intelligent AI. Given a command or request from the user, call the function to complete the request."
messages.append(Message(role="system", content=system_prompt))
messages.append(Message(role="user", content=query))
- output = self(messages=messages, function_schema=function_schema)
+ output = self(messages=messages, openai_function_schema=openai_function_schema)
if not output:
raise Exception("No output generated for extract function input")
if len(output) != 1:
@@ -85,4 +79,3 @@ class OpenAILLM(BaseLLM):
arguments_json = tool_call.function.arguments
function_inputs = json.loads(arguments_json)
return function_inputs
-
\ No newline at end of file
diff --git a/semantic_router/route.py b/semantic_router/route.py
index 3a62fab163ca33737cdcc170e42d2dfa5120295e..080afd61598090bf60db1c49010ea165ca56c5e9 100644
--- a/semantic_router/route.py
+++ b/semantic_router/route.py
@@ -67,23 +67,27 @@ class Route(BaseModel):
"LLM is required for dynamic routes. Please ensure the `llm` "
"attribute is set."
)
- elif query is None:
+ if query is None or type(query) != str:
raise ValueError(
"Query is required for dynamic routes. Please ensure the `query` "
"argument is passed."
)
- if self.function_schema:
- extracted_inputs = self.llm.extract_function_inputs(
- query=query, function_schema=self.function_schema
- )
- func_call = extracted_inputs
- elif self.openai_function_schema:
- if not isinstance(self.llm, OpenAILLM):
- raise TypeError("LLM must be an instance of OpenAILLM for openai_function_schema.")
- extracted_inputs = self.llm.extract_function_inputs_openai(
- query=query, function_schema=self.openai_function_schema
- )
- func_call = extracted_inputs
+ if self.function_schema:
+ extracted_inputs = self.llm.extract_function_inputs(
+ query=query,
+ function_schema=self.function_schema
+ )
+ func_call = extracted_inputs
+ elif self.openai_function_schema: # Logically must be self.openai_function_schema, but keeps MyPy happy.
+ if not isinstance(self.llm, OpenAILLM):
+ raise TypeError(
+ "LLM must be an instance of OpenAILLM for openai_function_schema."
+ )
+ extracted_inputs = self.llm.extract_function_inputs_openai(
+ query=query,
+ openai_function_schema=self.openai_function_schema
+ )
+ func_call = extracted_inputs
else:
# otherwise we just pass None for the call
func_call = None
diff --git a/semantic_router/utils/function_call.py b/semantic_router/utils/function_call.py
index c5e3a355691300e00b1003d1ad2cd4a336cd7aa4..562da07b35018dcb8d6621f164578dbfa477afb7 100644
--- a/semantic_router/utils/function_call.py
+++ b/semantic_router/utils/function_call.py
@@ -8,6 +8,7 @@ from semantic_router.schema import Message, RouteChoice
from semantic_router.utils.logger import logger
import re
+
def get_schema(item: Union[BaseModel, Callable]) -> Dict[str, Any]:
if isinstance(item, BaseModel):
signature_parts = []
@@ -39,6 +40,7 @@ def get_schema(item: Union[BaseModel, Callable]) -> Dict[str, Any]:
}
return schema
+
def convert_param_type_to_json_type(param_type: str) -> str:
if param_type == "int":
return "number"
@@ -55,48 +57,50 @@ def convert_param_type_to_json_type(param_type: str) -> str:
else:
return "object"
+
def get_schema_openai_func_calling(item: Callable) -> Dict[str, Any]:
if not callable(item):
raise ValueError("Provided item must be a callable function.")
-
+
docstring = inspect.getdoc(item)
signature = inspect.signature(item)
-
+
schema = {
"type": "function",
"function": {
"name": item.__name__,
"description": docstring if docstring else "No description available.",
- "parameters": {
- "type": "object",
- "properties": {},
- "required": []
- }
- }
+ "parameters": {"type": "object", "properties": {}, "required": []},
+ },
}
-
+
for param_name, param in signature.parameters.items():
- param_type = param.annotation.__name__ if param.annotation != inspect.Parameter.empty else "Any"
+ param_type = (
+ param.annotation.__name__
+ if param.annotation != inspect.Parameter.empty
+ else "Any"
+ )
param_description = "No description available."
param_required = param.default is inspect.Parameter.empty
-
+
# Attempt to extract the parameter description from the docstring
if docstring:
param_doc_regex = re.compile(rf":param {param_name}:(.*?)\n(?=:\w|$)", re.S)
match = param_doc_regex.search(docstring)
if match:
param_description = match.group(1).strip()
-
+
schema["function"]["parameters"]["properties"][param_name] = {
"type": convert_param_type_to_json_type(param_type),
- "description": param_description
+ "description": param_description,
}
-
+
if param_required:
schema["function"]["parameters"]["required"].append(param_name)
-
+
return schema
+
# TODO: Add route layer object to the input, solve circular import issue
async def route_and_execute(
query: str, llm: BaseLLM, functions: List[Callable], layer