Python: Add Health Data example

python/examples/healthData/demo.py

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+import asyncio
+import json
+import sys
+from dotenv import dotenv_values
+import schema as health
+from typechat import Failure, TypeChatValidator, create_language_model
+from translator import TranslatorWithHistory
+
+health_instructions = """
+Help me enter my health data step by step.
+Ask specific questions to gather required and optional fields I have not already providedStop asking if I don't know the answer
+Automatically fix my spelling mistakes
+My health data may be complex: always record and return ALL of it.
+Always return a response:
+- If you don't understand what I say, ask a question.
+- At least respond with an OK message.
+
+"""
+
+
+async def main():
+    vals = dotenv_values()
+    model = create_language_model(vals)
+    validator = TypeChatValidator(health.HealthDataResponse)
+    translator = TranslatorWithHistory(
+        model, validator, health.HealthDataResponse, additional_agent_instructions=health_instructions
+    )
+    print("💉💊🤧> ", end="", flush=True)
+    for line in sys.stdin:
+        result = await translator.translate(line)
+        if isinstance(result, Failure):
+            print("Translation Failed ❌")
+            print(f"Context: {result.message}")
+        else:
+            result = result.value
+            print("Translation Succeeded! ✅\n")
+            print("JSON View")
+            print(json.dumps(result, indent=2))
+
+            message = result.get("message", None)
+            not_translated = result.get("notTranslated", None)
+
+            if message:
+                print(f"\n📝: {message}" )
+
+            if not_translated:
+                print(f"\n🤔: I did not understand\n {not_translated}" )
+
+        print("\n💉💊🤧> ", end="", flush=True)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/examples/healthData/input.txt

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+#
+# Conversations with a Health Data Agent
+# For each conversation: 
+# You start with the first line 
+# Then type the next line in response
+#
+
+# ================
+# USE GPT4
+# ================
+# Conversation:
+i want to record my shingles
+August 2016
+It lasted 3 months
+I also broke my foot
+I broke it in high school
+2001
+The foot took a year to be ok
+
+# Conversation: 
+klaritin
+2 tablets 3 times a day
+300 mg
+actually that is 1 tablet
+@clear
+
+# Conversation: 
+klaritin
+1 pill, morning and before bedtime
+Can't remember
+Actually, that is 3 tablets
+500 mg
+@clear
+
+#Conversation
+I am taking binadryl now
+As needed. Groceery store strength
+That is all I have
+I also got allergies. Pollen
+@clear
+
+# Conversation: 
+Robotussin
+1 cup
+Daily, as needed
+Robotussin with Codeine
+Put down strength as I don't know
+@clear
+
+# Conversation: 
+Hey
+Melatonin
+1 3mg tablet every night
+@clear
+
+# Conversation: 
+I got the flu
+Started 2 weeks ago
+Its gone now. Only lasted about a week
+I took some sudafed though
+I took 2 sudafed twice a day. Regular strength
+@clear
+

python/examples/healthData/schema.py

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+from typing import TypedDict, Annotated, NotRequired, Literal
+
+
+def Doc(s: str) -> str:
+    return s
+
+
+class Quantity(TypedDict):
+    value: Annotated[float, Doc("Exact number")]
+    units: Annotated[str, Doc("UNITS include mg, kg, cm, pounds, liter, ml, tablet, pill, cup, per-day, per-week..ETC")]
+
+
+class ApproxDatetime(TypedDict):
+    displayText: Annotated[str, Doc("Default: Unknown. Required")]
+    timestamp: NotRequired[Annotated[str, Doc("If precise timestamp can be set")]]
+
+
+class ApproxQuantity(TypedDict):
+    displayText: Annotated[str, Doc("Default: Unknown. Required")]
+    quantity: NotRequired[Annotated[Quantity, Doc("Optional: only if precise quantities are available")]]
+
+
+class OtherHealthData(TypedDict):
+    """
+    Use for health data that match nothing else. E.g. immunization, blood prssure etc
+    """
+
+    text: str
+    when: NotRequired[ApproxDatetime]
+
+
+class Condition(TypedDict):
+    """
+    Disease, Ailment, Injury, Sickness
+    """
+
+    name: Annotated[str, Doc("Fix any spelling mistakes, especially phonetic spelling")]
+    startDate: Annotated[ApproxDatetime, Doc("When the condition started? Required")]
+    status: Annotated[
+        Literal["active", "recurrence", "relapse", "inactive", "remission", "resolved", "unknown"],
+        Doc("Always ask for current status of the condition"),
+    ]
+    endDate: NotRequired[Annotated[ApproxDatetime, Doc("If the condition was no longer active")]]
+
+
+class Medication(TypedDict):
+    """
+    Meds, pills etc.
+    """
+
+    name: Annotated[str, Doc("Fix any spelling mistakes, especially phonetic spelling")]
+    dose: Annotated[ApproxQuantity, Doc("E.g. 2 tablets, 1 cup. Required")]
+    frequency: Annotated[ApproxQuantity, Doc("E.g. twice a day. Required")]
+    strength: Annotated[ApproxQuantity, Doc("E.g. 50 mg. Required")]
+
+
+class HealthData(TypedDict, total=False):
+    medication: list[Medication]
+    condition: list[Condition]
+    other: list[OtherHealthData]
+
+
+class HealthDataResponse(TypedDict, total=False):
+    data: Annotated[HealthData, Doc("Return this if JSON has ALL required information. Else ask questions")]
+    message: Annotated[str, Doc("Use this to ask questions and give pertinent responses")]
+    notTranslated: Annotated[str, Doc("Use this parts of the user request not translateed, off topic, etc")]

python/examples/healthData/translator.py

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+import json
+from textwrap import dedent, indent
+from typing import TypeVar, Any, override, TypedDict, Literal
+
+from typechat import TypeChatValidator, TypeChatModel, TypeChatTranslator, Result, Failure
+
+from datetime import datetime
+
+T = TypeVar("T", covariant=True)
+
+
+class ChatMessage(TypedDict):
+    source: Literal["system", "user", "assistant"]
+    body: Any
+
+
+class TranslatorWithHistory(TypeChatTranslator[T]):
+    _chat_history: list[ChatMessage]
+    _max_prompt_length: int
+    _additional_agent_instructions: str
+
+    def __init__(
+        self, model: TypeChatModel, validator: TypeChatValidator[T], target_type: type[T], additional_agent_instructions: str
+    ):
+        super().__init__(model=model, validator=validator, target_type=target_type)
+        self._chat_history = []
+        self._max_prompt_length = 2048
+        self._additional_agent_instructions = additional_agent_instructions
+
+    @override
+    async def translate(self, request: str) -> Result[T]:
+        result = await super().translate(request=request)
+        if not isinstance(result, Failure):
+            self._chat_history.append(ChatMessage(source="assistant", body=result.value))
+        return result
+
+    @override
+    def _create_request_prompt(self, intent: str) -> str:
+        # TODO: drop history entries if we exceed the max_prompt_length
+        history_str = json.dumps(self._chat_history, indent=2, default=lambda o: None, allow_nan=False)
+        history_str = indent(history_str, "            ")
+
+        schema_str = indent(self._schema_str, "            ")
+
+        instructions_str = indent(self._additional_agent_instructions, "            ")
+
+        now = datetime.now()
+
+        prompt = F"""
+            user: You are a service that translates user requests into JSON objects of type  "{self._type_name}" according to the following TypeScript definitions:
+            '''
+            {schema_str}
+            '''
+
+            user:
+            Use precise date and times RELATIVE TO CURRENT DATE: {now.strftime('%A, %m %d, %Y')} CURRENT TIME: {now.strftime("%H:%M:%S")}
+            Also turn ranges like next week and next month into precise dates
+
+            user:
+            {instructions_str}
+
+            system:
+            IMPORTANT CONTEXT for the user request:
+            {history_str}
+
+            user:
+            The following is a user request:
+            '''
+            {intent}
+            '''
+             The following is the user request translated into a JSON object with 2 spaces of indentation and no properties with the value undefined:
+            """
+        prompt = dedent(prompt)
+        return prompt