update and clean up examples after FEPs 11 and 13

examples/AI/DallE.py

@@ -9,16 +9,12 @@
 
 @funix.funix(  # Funix.io, the laziest way to build web apps in Python
     title="OpenAI: Dall-E",
-    description="""Generate an image by prompt with DALL-E.""",
-    widgets={"openai_key": "password"},
+    description="""Generate an image by prompt with DALL-E. **Note:** An OpenAI key needs to be set in the environment variable OPENAI_KEY.""",
     show_source=True,
 )
 def dalle(
-    Prompt: str = "a cat on a red jeep",
-    openai_key: str = "using environment variable",
+    Prompt: str = "a cat on a red jeep"
 ) -> IPython.display.Image:
-    if openai_key != "using environment variable":
-        openai.api_key = openai_key
 
     response = openai.Image.create(prompt=Prompt)
     return response["data"][0]["url"]

examples/AI/chatGPT_advanced.py

@@ -1,13 +1,13 @@
 import os
 import typing
 
-import openai
+import ipywidgets
 
+import openai
 openai.api_key = os.environ.get("OPENAI_KEY")
 
 import funix
 
-
 @funix.new_funix_type(
     {
         "name": "textarea",
@@ -21,17 +21,18 @@ class PromptBox(str):
 
 
 cfg = {  # declarative configuration, all in one place
-    "description": """Try the **ChatGPT** app in [Funix](http://funix.io)""",
+    "description": """Try the **ChatGPT** app in [Funix](http://funix.io). **Note: An OpenAI key needs to be set in the environment variable OPENAI_KEY.""",
     "argument_labels": {
         "prompt": "_What do you wanna ask?_",
         "max_tokens": "**Length** of the answer",
         "show_advanced": "Show advanced options",
         "openai_key": "Use your own OpenAI key",
         "model": "Choose a model",
     },
-    "widgets": {"openai_key": "password", "model": "radio"},
+    "widgets": {"openai_key": "password"},
     "conditional_visible": [
-        {"when": {"show_advanced": True}, "show": ["max_tokens", "model", "openai_key"]}
+        {"when": {"show_advanced": True}, 
+        "show": ["max_tokens", "model", "openai_key"]}
     ],
 }
 
@@ -42,6 +43,8 @@ def ChatGPT_advanced(
     show_advanced: bool = False,
     model: typing.Literal["gpt-3.5-turbo", "gpt-3.5-turbo-0301"] = "gpt-3.5-turbo",
     max_tokens: range(100, 500, 50) = 150,
+    # openai_key: ipywidgets.Password = "use environment variable",
+    # BUG: Conditional visible will not work if openai_key's type is ipywidgets.Password. Works if it's str. 
     openai_key: str = "use environment variable",
 ) -> str:
     if openai_key != "use environment variable":

examples/AI/chatGPT_lazy.py

@@ -1,7 +1,6 @@
 # Turn this function to a web app using the command: 
 # funix chatGPT_lazy.py -l # -l flag must be there. 
 
-
 import os # Python's native 
 import openai  # you cannot skip it 
 

examples/AI/chatGPT_muilti_turn.py

@@ -17,7 +17,9 @@ def print_messages_html(messages):
     return printout
 
 import funix 
-@funix.funix(direction="column-reverse") # input is below log
+@funix.funix(
+    description="""Multi-turn chat with ChatGPT. **Note:** An OpenAI key needs to be set in the environment variable OPENAI_KEY.""",
+    direction="column-reverse") # input is below log
 def ChatGPT_multi_turn(current_message: str)  -> IPython.display.HTML:
     current_message = current_message.strip()
     messages.append({"role": "user", "content": current_message})

examples/AI/huggingface.py

@@ -11,6 +11,11 @@
 
 API_TOKEN = os.getenv("HF_TOKEN") # "Please set your API token as an environment variable named HF_TOKEN. You can get your token from https://huggingface.co/settings/token"
 
+import funix
+
+@funix.funix(
+    description="""Talk to LLMs hosted at HuggingFace. A HuggingFace token needs to be set in the environment variable HF_TOKEN.""",
+)
 def huggingface(
     model_name: typing.Literal[
         "gpt2", 

examples/AI/openAI_minimal_session.py

@@ -5,12 +5,7 @@
 import openai 
 
 import funix
-from funix.session import get_global_variable, set_global_variable#, set_default_global_variable
-
-# BUG: The set_global_variable() call does not effectively change the value of openai.api_key,
-# though get_global_variable(openai.api_key) returns sessionized key value. 
-# The value of openai.api_key remains None unless set via the environment variable OPENAI_KEY. 
-# As a workaround, we use the POST method to demo. 
+from funix.session import get_global_variable, set_global_variable
 
 # openai.api_key = os.environ.get("OPENAI_KEY")
 openai_key = os.environ.get("OPENAI_KEY")
@@ -36,13 +31,12 @@ def set_openAI_key(api_key: str="", use_sys_env_var:bool=False) -> str:
             return f"Your openAI key has been set to: {openai_key}"
 
             # openai.api_key = api_key 
-            set_global_variable(openai.api_key, api_key)
+            # set_global_variable(openai.api_key, api_key)
+            # FIXME: The two lines above are both useless to change openai.api_key. That's why we have to use POST method below to query all OpenAI endpoints. This is something to be fixed after grand opening. 
             return "OpenAI API key has been set via the web form! If it was set via an environment variable before, it's now overwritten."
 
 @funix.funix()
 def get_openAI_key()->str:
-    # return f"Your openAI key has been set to: {openai.api_key}" 
-    # return f"Your openAI key has been set to: {get_global_variable(openai.api_key)}" 
     return f"Your openAI key has been set to: {openai_key}"
 
 @funix.funix()

examples/basic_usage/conditional_visibility.py

@@ -1,22 +1,27 @@
 import typing 
 
+import ipywidgets
+
 import funix
 
 @funix.funix(
-    widgets={"prompt":"textarea", "model": "radio"}, 
+    widgets={"prompt":"textarea"}, 
     conditional_visible=[
         {
             "when": {"show_advanced": True,}, 
             "show": ["max_tokens", "model", "openai_key"]
         }
     ]
 )
-def ChatGPT_advanced(prompt: str, 
+def conditional_visible(prompt: str, 
         show_advanced: bool = False,
         model : typing.Literal['gpt-3.5-turbo', 'gpt-3.5-turbo-0301']= 'gpt-3.5-turbo',
         max_tokens: range(100, 200, 20)=140,
+        # openai_key: ipywidgets.Password = "",)  -> str:      
+        # BUG: Reported elsewhere as well. If I replace the type to ipywidgets.Password, I will get an error at the frontend: Unsupported field schema for field root_openai_key: Unknown field type str.
         openai_key: funix.hint.StrPassword = "",)  -> str:      
 
+
     completion = openai.ChatCompletion.create(
         messages=[{"role": "user", "content": prompt}],
         model=model, 

examples/basic_usage/default_and_candidate_values.py

@@ -4,13 +4,12 @@
 import funix 
 
 @funix.funix(
-    title="Let users select",
     description="This example shows how to provide argument/input values that users can select from in the UI. Simpliy taking advantage of Python's default values for keyword arguments, Literal type in type hints, and the `example` parameter in Funix. ",
     examples={"arg3": [1, 5, 7]},
     widgets={"arg2": "radio"},
     show_source=True,
 )
-def argument_selection(
+def default_and_candidate_values(
     arg1: str = "prime",
     arg2: typing.Literal["is", "is not"]="is",
     arg3: int = 3,

examples/basic_usage/input_widgets.py

@@ -8,6 +8,7 @@
 #     }
 # )
 
+@funix.funix()
 def input_types(
     prompt: str, 
     advanced_features: bool = False,

examples/bioinformatics/tel_search.py

@@ -11,6 +11,8 @@
 import functools
 import multiprocessing
 
+import pandas, pandera
+
 import funix
 
 #%%
@@ -92,6 +94,8 @@ def search_telomeres(sRNAs:typing.List[str], repeat:str, include_reverse:bool=Tr
     """Determine whether a list of strings are telomers of the given repeat 
     """
 
+    print (sRNAs)
+
     telomere_hash_dict = get_telomere_hash_dict(repeat, include_reverse=include_reverse)
 
     func_search_one_pattern = functools.partial(search_string_hash, telomere_hash_dict=telomere_hash_dict)
@@ -100,6 +104,8 @@ def search_telomeres(sRNAs:typing.List[str], repeat:str, include_reverse:bool=Tr
     #     result = pool.map(func_search_one_pattern, sRNAs)
     result = list(map(func_search_one_pattern, sRNAs))
 
+    print (result )
+
     return result
 
 # %%
@@ -113,36 +119,51 @@ def test():
     repeat = "CCCTAAA"
 
     return search_telomeres(sRNAs, repeat)
-# %%
+
+
+class InputSchema(pandera.DataFrameModel):
+    sRNAs: pandera.typing.Series[str]
+
 
 @funix.funix(
-    description = "A telomere is a region of repetitive DNA sequences at the end of a chromosome. "
-                "Find the belongings of a repeat unit.",
+    description = "A telomere is a region of repetitive DNA sequences at the end of a chromosome. Enter a repeating unit, and a list of sRNAs in the table below, this telomere checker will tell whether each of the sRNAs is a telomere.",
     # destination = "column",
-    argument_config = {
-        "sRNAs": {
-            "widget" : "sheet"
-        },
-        "repeat_unit": {
-            # "treat_as": "config",
-            "examples": ["CCCTAAA"]
-        }
-    }
+    # argument_config = {
+    #     "sRNAs": {
+    #         "widget" : "sheet"
+    #     },    
+    #     "repeat_unit": {
+    #         # "treat_as": "config",
+    #         "examples": ["CCCTAAA"]
+    #     }
+    # }
 )
-def bioinfo_telomere_check(
-    sRNAs: typing.List[str]=
+def telomere_check(
+    # sRNAs: typing.List[str] = [
+    #     "CCCTAAACCCTAAACCCTAT",  # False
+    #     "CCCTAAACCCTAAACCCTAA",  # True, 20-nt
+    #     "CCCTAAACCCTAAACCC",  # False, too short
+    #     "CCCTAAACCCTAAACCCTAAAC",  # True, 22-nt
+    #     "CTAAACCCTAAACCCTAAACCCT"  # True, 25-nt
+    # ],    
+    sRNAs: pandera.typing.DataFrame[InputSchema] =
+        pandas.DataFrame({"sRNAs": 
         [
-        "CCCTAAACCCTAAACCCTAT",  # False
-        "CCCTAAACCCTAAACCCTAA",  # True, 20-nt
-        "CCCTAAACCCTAAACCC",  # False, too short
-        "CCCTAAACCCTAAACCCTAAAC",  # True, 22-nt
-        "CTAAACCCTAAACCCTAAACCCT"  # True, 25-nt
-    ]
-    , repeat_unit: str="CCCTAAA"
-    ) -> dict:
+            "CCCTAAACCCTAAACCCTAT",  # False
+            "CCCTAAACCCTAAACCCTAA",  # True, 20-nt
+            "CCCTAAACCCTAAACCC",  # False, too short
+            "CCCTAAACCCTAAACCCTAAAC",  # True, 22-nt
+            "CTAAACCCTAAACCCTAAACCCT"  # True, 25-nt
+        ]
+        }),
+    repeat_unit: str="CCCTAAA"
     # ) -> typing.Dict[str, bool]: 
-    check_result = search_telomeres(sRNAs, repeat_unit)
-    return {"sRNAs":sRNAs, "Is it a telemere?":check_result }
+    # check_result = search_telomeres(sRNAs, repeat_unit)
+    # return {"sRNAs":sRNAs, "Is it a telemere?":check_result }
+
+    ) -> pandas.DataFrame:
+    check_result = search_telomeres(sRNAs["sRNAs"].tolist(), repeat_unit)
+    return pandas.DataFrame({"sRNAs":sRNAs["sRNAs"], "Is it a telemere?":check_result })
 
 
 if __name__ == '__main__':