feat: config sync cheapAI to StrongAI; reformats; debug mode UIs

.gitignore

@@ -1,6 +1,7 @@
 *_secret.py
 *_secret.py*
 **test_result.pdf
+**letter.typ
 
 .local/
 .ruff_cache/

_data_test.py

@@ -71,10 +71,9 @@ Languages:
     Fluent in English and French
 """
 pdf_context = {
-  "companyFullName": "Queen of Hearts' Garden",
-  "jobTitle": "Card Guards",
-  "applicantFullName": "Sherlock Holmes",
-  "applicantContactInformation": "221B Baker Street, London, +44 (020) 1234-5678, sherlock.holmes@sherlockHolmes.com",
-  "letter_body": "text,\n\ntest test"
+    "companyFullName": "Queen of Hearts' Garden",
+    "jobTitle": "Card Guards",
+    "applicantFullName": "Sherlock Holmes",
+    "applicantContactInformation": "221B Baker Street, London, +44 (020) 1234-5678, sherlock.holmes@sherlockHolmes.com",
+    "letter_body": "text,\n\ntest test",
 }
-

_test.py

@@ -1,6 +1,6 @@
 from taskAI import TaskAI
 from taskNonAI import compile_pdf
-from _data_test import mock_jd, mock_cv, pdf_context
+from _data_test import mock_cv, pdf_context
 from _secret import api_test
 
 from llama_index.llms.openai_like import OpenAILike
@@ -22,17 +22,24 @@ def test_ai_integration():
     ).chat(messages)
     print(response)
 
+
 def test_taskAI():
     taskAI = TaskAI(api_test)
     gen = taskAI.cv_preprocess(mock_cv)
     for chunk in gen:
         print(chunk)
 
+
 def test_typst_pdf():
-    compile_pdf(tmpl_path='typst/template_letter.tmpl', context=pdf_context, output_path='test_result.pdf')
+    compile_pdf(
+        tmpl_path="typst/template_letter.tmpl",
+        context=pdf_context,
+        output_path="test_result.pdf",
+    )
     # os
 
+
 if __name__ == "__main__":
     # test_taskAI()
     # test_ai_integration()
-    test_typst_pdf()
+    test_typst_pdf()

app.py

@@ -1,4 +1,4 @@
-from config import DEMO_TITLE, IS_SHARE, CV_EXT, EXT_TXT
+from config import DEMO_TITLE, IS_SHARE, IS_DEBUG, CV_EXT, EXT_TXT
 from config import CHEAP_API_BASE, CHEAP_API_KEY, CHEAP_MODEL
 from config import STRONG_API_BASE, STRONG_API_KEY, STRONG_MODEL
 from util import is_valid_url
@@ -23,6 +23,27 @@ def init():
     os.system("shot-scraper install -b firefox")
     download_pandoc()
 
+
+## Config Functions
+
+def set_same_cheap_strong(set_same:bool, cheap_base, cheap_key, cheap_model):
+    setup_zone = gr.Accordion("AI setup (OpenAI-compatible LLM API)", open=True)
+    if set_same:
+        return (gr.Textbox(value=cheap_base, label="API Base", interactive=False),
+                gr.Textbox(value=cheap_key, label="API key", type="password", interactive=False),
+                gr.Textbox(value=cheap_model, label="Model ID", interactive=False),
+                setup_zone,
+                )
+    else:
+        return (gr.Textbox(value=cheap_base, label="API Base", interactive=True),
+                gr.Textbox(value=cheap_key, label="API key", type="password", interactive=True),
+                gr.Textbox(value=cheap_model, label="Model ID", interactive=True),
+                setup_zone,
+                )
+    
+
+## Main Functions
+
 def prepare_input(jd_info, cv_file: str, cv_text):
     if jd_info:
         if is_valid_url(jd_info):
@@ -84,7 +105,7 @@ def finalize_letter_pdf(api_base, api_key, api_model, jd, cv, cover_letter_text)
 
 with gr.Blocks(
     title=DEMO_TITLE,
-    theme=gr.themes.Base(primary_hue="blue", secondary_hue="sky", neutral_hue="slate"),
+    theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky", neutral_hue="slate"),
 ) as app:
     intro = f"""# {DEMO_TITLE}
     > You provide job description and résumé. I write Cover letter for you!  
@@ -94,22 +115,25 @@ with gr.Blocks(
 
     with gr.Row():
         with gr.Column(scale=1):
-            with gr.Accordion("AI setup (OpenAI-compatible LLM API)", open=False):
+            with gr.Accordion("AI setup (OpenAI-compatible LLM API)", open=False) as setup_zone:
+                is_debug = gr.Checkbox( label="Debug Mode", value=IS_DEBUG)
+                
                 gr.Markdown(
                     "**Cheap AI**, an honest format converter and refiner, extracts essential info from job description and résumé, to reduce subsequent cost on Strong AI."
                 )
                 with gr.Group():
                     cheap_base = gr.Textbox(
-                        value=CHEAP_API_BASE, label="API BASE"
+                        value=CHEAP_API_BASE, label="API Base"
                     )
                     cheap_key = gr.Textbox(value=CHEAP_API_KEY, label="API key", type="password")
                     cheap_model = gr.Textbox(value=CHEAP_MODEL, label="Model ID")
                 gr.Markdown(
                     "---\n**Strong AI**, a thoughtful wordsmith, generates perfect cover letters to make both you and recruiters happy."
                 )
+                is_same_cheap_strong = gr.Checkbox(label="the same as Cheap AI", value=False, container=False)
                 with gr.Group():
                     strong_base = gr.Textbox(
-                        value=STRONG_API_BASE, label="API BASE"
+                        value=STRONG_API_BASE, label="API Base"
                     )
                     strong_key = gr.Textbox(
                         value=STRONG_API_KEY, label="API key", type="password"
@@ -155,6 +179,9 @@ with gr.Blocks(
             )
             infer_btn = gr.Button("Go!", variant="primary")
             
+    is_same_cheap_strong.change(fn= set_same_cheap_strong, 
+                                    inputs=[is_same_cheap_strong, cheap_base, cheap_key, cheap_model],
+                                    outputs=[strong_base, strong_key, strong_model, setup_zone])
 
     infer_btn.click(
         fn=prepare_input,

config.py

@@ -12,6 +12,7 @@ STRONG_API_KEY = os.getenv("STRONG_API_KEY") or OPENAI_API_KEY
 STRONG_MODEL = os.getenv("STRONG_MODEL") or "gpt-4"
 
 IS_SHARE = bool(os.getenv("IS_SHARE")) or False
+IS_DEBUG = bool(os.getenv("IS_DEBUG")) or False
 
 DEMO_TITLE = "Cover Letter Generator"
 DEMO_DESCRIPTION = "This is a demo of the OpenAI API for generating cover letters. The model is trained on a dataset of cover letters and job descriptions, and generates a cover letter based on the job description and the applicant's CV. The model is fine-tuned on the OpenAI API, and is able to generate cover letters that are tailored to the job description and the applicant's CV. The model is able to generate cover letters for a wide range of jobs, and is able to generate cover letters that are tailored to the job description and the applicant's CV. The model is able to generate cover letters for a wide range of jobs, and is able to generate cover letters that are tailored to the job description and the applicant's CV. The model is able to generate cover letters for a wide range of jobs, and is able to generate cover letters that are tailored to the job description and the applicant's CV."

setup.sh

@@ -1,3 +1 @@
-pip install -r requirements.txt
-ruff check
-ruff format
+pip install -r requirements.txt

taskAI.py

@@ -5,7 +5,8 @@ from llama_index.core.llms import ChatMessage  # , MessageRole
 from llama_index.core import ChatPromptTemplate
 
 from util import mylogger
-logger = mylogger(__name__,'%(asctime)s:%(filename)s:%(levelname)s:%(message)s')
+
+logger = mylogger(__name__, "%(asctime)s:%(filename)s:%(levelname)s:%(message)s")
 ## define templates
 
 ### topic,input
@@ -40,7 +41,7 @@ JSON_API = ChatPromptTemplate(
         ChatMessage(role="user", content="{content}"),
     ]
 )
-keys_to_template = lambda keys : json.dumps(dict().fromkeys(keys, ""))
+keys_to_template = lambda keys: json.dumps(dict().fromkeys(keys, ""))
 
 ### resume, jd
 LETTER_COMPOSE = ChatPromptTemplate(
@@ -51,16 +52,19 @@ LETTER_COMPOSE = ChatPromptTemplate(
 
 Before officially write the letter, think step by step. First, list what makes a perfect cover letter in general, and in order to write a perfect cover letter, what key points do you have to learn from the RESUME and JOB_DESCRIPTION. Then, carefully analyze the given RESUME and JOB_DESCRIPTION, take a deep breath and propose 3 best tactics to convince recruiter believe the applicant fit for the role. Ensure your thoughts are express clearly and then write the complete cover letter.""",
         ),
-        ChatMessage(role="user", content="<RESUME>\n{resume}\n</RESUME>\n\n<JOB_DESCRIPTION>\n{jd}</JOB_DESCRIPTION>\n<ANALYSIS_REPORT>"),
+        ChatMessage(
+            role="user",
+            content="<RESUME>\n{resume}\n</RESUME>\n\n<JOB_DESCRIPTION>\n{jd}</JOB_DESCRIPTION>\n<ANALYSIS_REPORT>",
+        ),
     ]
 )
 
 ## basic func
 
+
 ## tasks
 class TaskAI(OpenAILike):
     def __init__(self, api: dict[str, str], **kwargs):
-        
         log = logger.info
 
         def guess_window_size(model=api["model"]):
@@ -78,11 +82,20 @@ class TaskAI(OpenAILike):
             return window_size
 
         super().__init__(
-            api_base=api["base"], api_key=api["key"], model=api["model"], is_chat_model=True, context_window=guess_window_size(), **kwargs
+            api_base=api["base"],
+            api_key=api["key"],
+            model=api["model"],
+            is_chat_model=True,
+            context_window=guess_window_size(),
+            **kwargs,
         )
 
     def jd_preprocess(self, input: str):
-        return self.stream_chat(EXTRACT_INFO.format_messages(to_extract="the job description part`", input=input))
+        return self.stream_chat(
+            EXTRACT_INFO.format_messages(
+                to_extract="the job description part`", input=input
+            )
+        )
 
     def cv_preprocess(self, input: str):
         return self.stream_chat(SIMPLIFY_MD.format_messages(input=input))
@@ -91,20 +104,37 @@ class TaskAI(OpenAILike):
         return self.stream_chat(LETTER_COMPOSE.format_messages(resume=resume, jd=jd))
 
     def get_jobapp_meta(self, JD, CV):
-        meta_JD = self.chat(JSON_API.format_messages(template=keys_to_template(["companyFullName", "jobTitle"]), content=JD)).message.content
+        meta_JD = self.chat(
+            JSON_API.format_messages(
+                template=keys_to_template(["companyFullName", "jobTitle"]), content=JD
+            )
+        ).message.content
         # yield meta_JD
-        meta_CV = self.chat(JSON_API.format_messages(template=keys_to_template(["applicantFullNname", "applicantContactInformation"]), content=CV)).message.content
+        meta_CV = self.chat(
+            JSON_API.format_messages(
+                template=keys_to_template(
+                    ["applicantFullNname", "applicantContactInformation"]
+                ),
+                content=CV,
+            )
+        ).message.content
         # yield meta_JD+'\n'+meta_CV
         try:
             meta_JD = json.loads(meta_JD.strip())
             meta_CV = json.loads(meta_CV.strip())
         except:
-            raise ValueError(f"AI didn't return a valid JSON string. Try again or consider a better model for CheapAI. \n{meta_JD}\n{meta_CV}")
+            raise ValueError(
+                f"AI didn't return a valid JSON string. Try again or consider a better model for CheapAI. \n{meta_JD}\n{meta_CV}"
+            )
         meta = dict()
         meta.update(meta_JD)
         meta.update(meta_CV)
         yield json.dumps(meta, indent=2)
 
     def purify_letter(self, full_text):
-        return self.stream_chat(EXTRACT_INFO.format_messages(to_extract="the cover letter section starting from 'Dear Hiring Manager' or similar to 'Sincerely,' or similar ", input=full_text))
-
+        return self.stream_chat(
+            EXTRACT_INFO.format_messages(
+                to_extract="the cover letter section starting from 'Dear Hiring Manager' or similar to 'Sincerely,' or similar ",
+                input=full_text,
+            )
+        )

taskNonAI.py

@@ -40,22 +40,26 @@ def extract_url(url: str) -> Optional[str]:
             f"Please try copy-paste as input. Failed to extract content from: {url}. Didn't find content from given URL!"
         )
 
-def date():
+def _date()->str:
     current_date = datetime.now()
     return current_date.strftime(
         f"%B %d{'th' if 4 <= current_date.day <= 20 or 24 <= current_date.day <= 30 else ['st', 'nd', 'rd'][current_date.day % 10 - 1]} , %Y")
 
-def typst_escape(s):
+def _typst_escape(s)->str:
     return str(s).replace('@','\@').replace('#','\#')
-
-def compile_pdf(context: dict, tmpl_path: str, output_path="/tmp/cover_letter.pdf"):
+ 
+def compile_pdf(context: dict, tmpl_path: str, output_path="/tmp/cover_letter.pdf", is_debug=False)->list[str]:
+    letter_src_filepath = 'typst/letter.typ'
     with open(tmpl_path, "r", encoding='utf8') as f:
         tmpl = Template(f.read())
-    context = {k: typst_escape(v) for k, v in context.items()}
-    context.update({'date_string': date()})
+    context = {k: _typst_escape(v) for k, v in context.items()}
+    context.update({'date_string': _date()})
     letter_typ = tmpl.safe_substitute(context)
-    with open('typst/letter.typ', 'w', encoding='utf8') as f:
+    with open(letter_src_filepath, 'w', encoding='utf8') as f:
         f.write(letter_typ)
-    typst.compile('typst/letter.typ', output_path, root=Path('./typst/'), font_paths=[Path('./fonts/')])
-    os.remove('letter.typ')
-    return output_path
+    typst.compile(letter_src_filepath, output_path, root=Path('./typst/'), font_paths=[Path('./fonts/')])
+    # os.remove(letter_src_filepath)
+    if is_debug:
+        return [letter_src_filepath, output_path]
+    else:
+        return [output_path]

typst/letter.typ

@@ -1,15 +1,15 @@
 #import "template_base.typ": *
 #show: letter.with(
   sender: [
-     123 Main St., Emerald City, KS 12345, (123) 456-7890, dorothy\@wizardofoz.com
+     221B Baker Street, London, +44 (020) 1234-5678, sherlock.holmes\@sherlockHolmes.com
   ],
   recipient: [
     Hiring Manager \
-    Mastercard \
+    Queen of Hearts' Garden \
   ],
   date: [March 30th , 2024],
-  subject: [Cover Letter for Project Management Intern],
-  name: [Dorothy Gale],
+  subject: [Cover Letter for Card Guards],
+  name: [Sherlock Holmes],
 )
 
 text,

util.py

@@ -6,6 +6,7 @@ import logging
 
 from typing import Generator
 
+
 def mylogger(name, format, level=logging.INFO):
     # Create a custom logger
     logger = logging.getLogger(name)
@@ -33,7 +34,7 @@ def is_valid_url(url: str) -> bool:
         return False
 
 
-def is_valid_openai_api_key(api_base:str, api_key: str)->bool:
+def is_valid_openai_api_key(api_base: str, api_key: str) -> bool:
     headers = {"Authorization": f"Bearer {api_key}"}
 
     response = requests.get(api_base, headers=headers)
@@ -41,19 +42,20 @@ def is_valid_openai_api_key(api_base:str, api_key: str)->bool:
     return response.status_code == 200
 
 
-def zip_api(api_base:str, api_key:str, model:str)->dict[str, str]:
+def zip_api(api_base: str, api_key: str, model: str) -> dict[str, str]:
     return {"base": api_base, "key": api_key, "model": model}
 
+
 def stream_together(*gens: Generator):
-    ln=len(gens)
-    result = [""] * ln # Mind type here
+    ln = len(gens)
+    result = [""] * ln  # Mind type here
     while 1:
         stop: bool = True
         for i in range(ln):
             try:
-                n=next(gens[i])
+                n = next(gens[i])
                 if "delta" in dir(n):
-                    n=n.delta
+                    n = n.delta
                 result[i] += n
                 stop = False
             except StopIteration:
@@ -61,4 +63,4 @@ def stream_together(*gens: Generator):
                 pass
         yield result
         if stop:
-            break
+            break