update vars.env to add llm and base_url params, remove datetime.timedelta from tool calls (#336)

Author: jin-nvidia

industries/healthcare/agentic-healthcare-front-desk/README.md

@@ -41,15 +41,14 @@ The agentic tool calling capability in each of the customer care assistants is p
 
 ## Prerequisites
 ### Hardware 
-There are no local GPU requirements for running any application in this repo. The LLMs utilized in LangGraph in this repo are by default set to calling NVIDIA AI Endpoints, as seen in the directory [`graph_definitions/`](./graph_definitions/), and require a valid NVIDIA API KEY.
+There are no local GPU requirements for running any application in this repo. The LLMs utilized in LangGraph in this repo are by default set to calling NVIDIA AI Endpoints since `BASE_URL` is set to the default value of `"https://integrate.api.nvidia.com/v1"` in [vars.env](./vars.env), and require a valid NVIDIA API KEY. As seen in the [graph definitions](./graph_definitions/):
 ```python
 from langchain_nvidia_ai_endpoints import ChatNVIDIA
-llm_model = "meta/llama-3.1-70b-instruct" 
-assistant_llm = ChatNVIDIA(model=llm_model)
+assistant_llm = ChatNVIDIA(model=llm_model, ...)
 ```
-You can experiment with other LLMs available on build.nvidia.com by changing the `model` param for `ChatNVIDIA` in the Python files in the directory [`graph_definitions/`](./graph_definitions/).
+You can experiment with other LLMs available on build.nvidia.com by changing the `LLM_MODEL` values in [vars.env](./vars.env), for passing into `ChatNVIDIA` in the Python files in the directory [`graph_definitions/`](./graph_definitions/).
 
-If instead of calling NVIDIA AI Endpoints with an API key, you would like to host your own LLM NIM instance, please refer to the [Docker tab of the LLM NIM](https://build.nvidia.com/meta/llama-3_1-70b-instruct?snippet_tab=Docker) on how to host, and add a [`base_url` parameter](https://python.langchain.com/docs/integrations/chat/nvidia_ai_endpoints/#working-with-nvidia-nims) to point to your own instance when specifying `ChatNVIDIA` in the Python files in the directory [`graph_definitions/`](./graph_definitions/). For the hardware configuration of self hosting the LLM, please refer to the [documentation for LLM support matrix](https://docs.nvidia.com/nim/large-language-models/latest/support-matrix.html).
+If instead of calling NVIDIA AI Endpoints with an API key, you would like to host your own LLM NIM instance, please refer to the [Docker tab of the LLM NIM](https://build.nvidia.com/meta/llama-3_1-70b-instruct?snippet_tab=Docker) on how to host, and changed the `BASE_URL` parameter in [vars.env](./vars.env) to [point to your own instance](https://python.langchain.com/docs/integrations/chat/nvidia_ai_endpoints/#working-with-nvidia-nims) when specifying `ChatNVIDIA` in the Python files in the directory [`graph_definitions/`](./graph_definitions/). For the hardware configuration of self hosting the LLM, please refer to the [documentation for LLM support matrix](https://docs.nvidia.com/nim/large-language-models/latest/support-matrix.html).
 
 ### NVIDIA API KEY
 You will need an NVIDIA API KEY to call NVIDIA AI Endpoints.  You can use different model API endpoints with the same API key, so even if you change the LLM specification in `ChatNVIDIA(model=llm_model)` you can still use the same API KEY.

industries/healthcare/agentic-healthcare-front-desk/graph_definitions/graph.py

@@ -49,8 +49,7 @@
 #################
 patient_id = '14867dba-fb11-4df3-9829-8e8e081b39e6' # test patient id from looking through https://launch.smarthealthit.org/
 save_graph_to_png = True
-main_llm_model = "meta/llama-3.1-70b-instruct"
-specialized_llm_model = "meta/llama-3.1-70b-instruct"
+
 env_var_file = "vars.env"
 
 local_file_constant = "sample_db/test_db.sqlite"
@@ -73,9 +72,19 @@
 RIVA_ASR_FUNCTION_ID = os.getenv("RIVA_ASR_FUNCTION_ID", None)
 RIVA_TTS_FUNCTION_ID = os.getenv("RIVA_TTS_FUNCTION_ID", None)
 
+
+assert os.environ['LLM_MODEL'] is not None, "Make sure you have your LLM_MODEL exported as a environment variable!"
+main_llm_model = os.getenv("LLM_MODEL", None)
+
+assert os.environ['LLM_MODEL'] is not None, "Make sure you have your LLM_MODEL exported as a environment variable!"
+specialized_llm_model = os.getenv("LLM_MODEL", None)
+
+assert os.environ['BASE_URL'] is not None, "Make sure you have your BASE_URL exported as a environment variable!"
+base_url = os.getenv("BASE_URL", None)
+
 ### define which llm to use
-main_assistant_llm = ChatNVIDIA(model=main_llm_model)#, base_url=base_url 
-specialized_assistant_llm = ChatNVIDIA(model=specialized_llm_model)#, base_url=base_url
+main_assistant_llm = ChatNVIDIA(model=main_llm_model, base_url=base_url)
+specialized_assistant_llm = ChatNVIDIA(model=specialized_llm_model, base_url=base_url)
 
 def update_dialog_stack(left: list[str], right: Optional[str]) -> list[str]:
     """Push or pop the state."""
@@ -247,7 +256,7 @@ def print_gathered_patient_info(
     patient_dob: datetime.date,
     allergies_medication: List[str],
     current_symptoms: str,
-    current_symptoms_duration: datetime.timedelta,
+    current_symptoms_duration: str,
     pharmacy_location: str
 ):
     """This function prints out and transmits the gathered information for each patient intake field:
@@ -373,7 +382,7 @@ class ToPatientIntakeAssistant(BaseModel):
     patient_dob: datetime.date = Field(description="The patient's date of birth.")
     allergies_medication: List[str] = Field(description="A list of allergies in medication for the patient.")
     current_symptoms: str = Field(description="A description of the current symptoms for the patient.")
-    current_symptoms_duration: datetime.timedelta = Field(description="The time duration of current symptoms.")
+    current_symptoms_duration: str = Field(description="The time duration of current symptoms.")
     pharmacy_location: str = Field(description="The patient's pharmacy location.")
     request: str = Field(
         description="Any necessary information the patient intake assistant should clarify before proceeding."

industries/healthcare/agentic-healthcare-front-desk/graph_definitions/graph_appointment_making_only.py

@@ -42,7 +42,6 @@
 patient_id = '14867dba-fb11-4df3-9829-8e8e081b39e6' # test patient id from looking through https://launch.smarthealthit.org/
 save_graph_to_png = True
 
-llm_model = "meta/llama-3.1-70b-instruct"
 env_var_file = "vars.env"
 
 local_file_constant = "sample_db/test_db.sqlite"
@@ -63,8 +62,14 @@
 RIVA_ASR_FUNCTION_ID = os.getenv("RIVA_ASR_FUNCTION_ID", None)
 RIVA_TTS_FUNCTION_ID = os.getenv("RIVA_TTS_FUNCTION_ID", None)
 
+assert os.environ['LLM_MODEL'] is not None, "Make sure you have your LLM_MODEL exported as a environment variable!"
+llm_model = os.getenv("LLM_MODEL", None)
+
+assert os.environ['BASE_URL'] is not None, "Make sure you have your BASE_URL exported as a environment variable!"
+base_url = os.getenv("BASE_URL", None)
+
 ### define which llm to use
-assistant_llm = ChatNVIDIA(model=llm_model) # base_url=base_url)
+assistant_llm = ChatNVIDIA(model=llm_model, base_url=base_url)
 
 ########################
 ### Define the tools ###

industries/healthcare/agentic-healthcare-front-desk/graph_definitions/graph_medication_lookup_only.py

@@ -49,7 +49,6 @@
 #################
 patient_id = '14867dba-fb11-4df3-9829-8e8e081b39e6' # test patient id from looking through https://launch.smarthealthit.org/
 save_graph_to_png = True
-llm_model = "meta/llama-3.1-70b-instruct"
 env_var_file = "vars.env"
 
 
@@ -62,14 +61,20 @@
 
 assert os.environ['NVIDIA_API_KEY'] is not None, "Make sure you have your NVIDIA_API_KEY exported as a environment variable!"
 assert os.environ['TAVILY_API_KEY'] is not None, "Make sure you have your TAVILY_API_KEY exported as a environment variable!"
-
 NVIDIA_API_KEY=os.getenv("NVIDIA_API_KEY", None)
 RIVA_API_URI = os.getenv("RIVA_API_URI", None)
+
 RIVA_ASR_FUNCTION_ID = os.getenv("RIVA_ASR_FUNCTION_ID", None)
 RIVA_TTS_FUNCTION_ID = os.getenv("RIVA_TTS_FUNCTION_ID", None)
 
+assert os.environ['LLM_MODEL'] is not None, "Make sure you have your LLM_MODEL exported as a environment variable!"
+llm_model = os.getenv("LLM_MODEL", None)
+
+assert os.environ['BASE_URL'] is not None, "Make sure you have your BASE_URL exported as a environment variable!"
+base_url = os.getenv("BASE_URL", None)
+
 ### define which llm to use
-assistant_llm = ChatNVIDIA(model=llm_model)#, base_url=base_url
+assistant_llm = ChatNVIDIA(model=llm_model, base_url=base_url)
 
 ########################
 ### Define the tools ###

industries/healthcare/agentic-healthcare-front-desk/graph_definitions/graph_patient_intake_only.py

@@ -37,7 +37,6 @@
 patient_id = '14867dba-fb11-4df3-9829-8e8e081b39e6' # test patient id from looking through https://launch.smarthealthit.org/
 save_graph_to_png = True
 
-llm_model = "meta/llama-3.1-70b-instruct"
 env_var_file = "vars.env"
 
 
@@ -48,14 +47,20 @@
 print("Your NVIDIA_API_KEY is set to: ", os.environ['NVIDIA_API_KEY'])
 
 assert os.environ['NVIDIA_API_KEY'] is not None, "Make sure you have your NVIDIA_API_KEY exported as a environment variable!"
-
 NVIDIA_API_KEY=os.getenv("NVIDIA_API_KEY", None)
+
 RIVA_API_URI = os.getenv("RIVA_API_URI", None)
 RIVA_ASR_FUNCTION_ID = os.getenv("RIVA_ASR_FUNCTION_ID", None)
 RIVA_TTS_FUNCTION_ID = os.getenv("RIVA_TTS_FUNCTION_ID", None)
 
+assert os.environ['LLM_MODEL'] is not None, "Make sure you have your LLM_MODEL exported as a environment variable!"
+llm_model = os.getenv("LLM_MODEL", None)
+
+assert os.environ['BASE_URL'] is not None, "Make sure you have your BASE_URL exported as a environment variable!"
+base_url = os.getenv("BASE_URL", None)
+
 ### define which llm to use
-assistant_llm = ChatNVIDIA(model=llm_model) # base_url=base_url
+assistant_llm = ChatNVIDIA(model=llm_model, base_url=base_url)
 
 ########################
 ### Define the tools ###
@@ -73,7 +78,7 @@ def print_gathered_patient_info(
     patient_dob: datetime.date,
     allergies_medication: List[str],
     current_symptoms: str,
-    current_symptoms_duration: datetime.timedelta,
+    current_symptoms_duration: str,
     pharmacy_location: str
 ):
     """This function prints out and transmits the gathered information for each patient intake field:

industries/healthcare/agentic-healthcare-front-desk/vars.env

@@ -2,4 +2,6 @@ NVIDIA_API_KEY="nvapi-"
 TAVILY_API_KEY="tvly-"
 RIVA_API_URI=grpc.nvcf.nvidia.com:443
 RIVA_ASR_FUNCTION_ID=1598d209-5e27-4d3c-8079-4751568b1081
-RIVA_TTS_FUNCTION_ID=0149dedb-2be8-4195-b9a0-e57e0e14f972
+RIVA_TTS_FUNCTION_ID=0149dedb-2be8-4195-b9a0-e57e0e14f972
+BASE_URL="https://integrate.api.nvidia.com/v1"
+LLM_MODEL="meta/llama-3.3-70b-instruct"