Update app.py

app.py

@@ -23,14 +23,14 @@ import pandas as pd
 
 load_dotenv()
 
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")
-FMP_API_KEY = os.getenv("FMP_API_KEY")
-
-print("DEBUG: GROQ_API_KEY ->", GROQ_API_KEY)
-print("DEBUG: FMP_API_KEY ->", FMP_API_KEY)
+# Omit printing actual keys for safety.
+groq_api_key = os.getenv("GROQ_API_KEY")
+fmp_api_key = os.getenv("FMP_API_KEY")
+print("DEBUG: GROQ_API_KEY ->", "***REDACTED***" if groq_api_key else None)
+print("DEBUG: FMP_API_KEY ->", "***REDACTED***" if fmp_api_key else None)
 
 embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
-llm = Groq(model="llama3-70b-8192", api_key=GROQ_API_KEY)
+llm = Groq(model="llama3-70b-8192", api_key=groq_api_key)
 
 service_context = ServiceContext.from_defaults(
     llm=llm,
@@ -39,9 +39,13 @@ service_context = ServiceContext.from_defaults(
 )
 
 def fetch_annual_report_10k(symbol: str) -> str:
+    """Fetch the latest 10-K JSON response for a given stock ticker."""
     print("DEBUG: fetch_annual_report_10k called with symbol:", symbol)
     current_year = datetime.datetime.now().year
-    url = f"https://financialmodelingprep.com/api/v4/financial-reports-json?symbol={symbol}&year={current_year}&period=FY&apikey={FMP_API_KEY}"
+    url = (
+        "https://financialmodelingprep.com/api/v4/financial-reports-json"
+        f"?symbol={symbol}&year={current_year}&period=FY&apikey={fmp_api_key}"
+    )
     print("DEBUG: URL ->", url)
     try:
         response = requests.get(url, timeout=10)
@@ -99,9 +103,10 @@ async def on_chat_start():
         annual_report_text = fetch_annual_report_10k(ticker_symbol)
         print("DEBUG: annual_report_text snippet ->", annual_report_text[:200])
 
-        if annual_report_text.startswith("HTTP error") or \
-           annual_report_text.startswith("Request error") or \
-           annual_report_text.startswith("An unexpected error occurred"):
+        # Check for various errors
+        if (annual_report_text.startswith("HTTP error") or
+            annual_report_text.startswith("Request error") or
+            annual_report_text.startswith("An unexpected error occurred")):
             await cl.Message(content=annual_report_text).send()
             return
 
@@ -114,15 +119,19 @@ async def on_chat_start():
         cl.user_session.set("index", index)
         query_engine = index.as_query_engine()
 
+        # Summaries
         summary_response = await cl.make_async(query_engine.query)(summary_prompt)
-        print("DEBUG: summary_response snippet ->", summary_response[:200])
-
-        await cl.Message(content=f"**Summary:**\n{summary_response}").send()
+        # Convert to string in case it's a special object
+        summary_text = str(summary_response)
+        print("DEBUG: summary_response snippet ->", summary_text[:200])
+        await cl.Message(content=f"**Summary:**\n{summary_text}").send()
 
+        # Questions
         questions_response = await cl.make_async(query_engine.query)(question_prompt)
-        print("DEBUG: questions_response snippet ->", questions_response[:200])
+        questions_text = str(questions_response)
+        print("DEBUG: questions_response snippet ->", questions_text[:200])
 
-        questions_format = str(questions_response).split('\n')
+        questions_format = questions_text.split('\n')
         relevant_questions = [
             question.strip() for question in questions_format
             if question.strip() and question.strip()[0].isdigit()
@@ -131,9 +140,10 @@ async def on_chat_start():
         await cl.Message(content="Generated strategic questions and answers:").send()
         for question in relevant_questions:
             await cl.Message(content=f"**{question}**").send()
-            answer = await cl.make_async(query_engine.query)(question)
-            print(f"DEBUG: Answer for '{question[:30]}' snippet ->", answer[:200])
-            await cl.Message(content=f"**Answer:**\n{answer}").send()
+            answer_obj = await cl.make_async(query_engine.query)(question)
+            answer_text = str(answer_obj)
+            print(f"DEBUG: Answer for '{question[:30]}' snippet ->", answer_text[:200])
+            await cl.Message(content=f"**Answer:**\n{answer_text}").send()
 
         msg.content = "Processing done. You can now ask more questions about the 10-K report!"
         await msg.update()
@@ -155,11 +165,20 @@ async def main(message: cl.Message):
     user_query = message.content
     print("DEBUG: user_query ->", user_query)
 
-    response = await cl.make_async(query_engine.query)(user_query)
-    print("DEBUG: response snippet ->", str(response)[:200])
+    try:
+        # Run the query
+        raw_response = await cl.make_async(query_engine.query)(user_query)
+        # Convert to string to avoid 'Response' object subscript issues
+        response_str = str(raw_response)
+        print("DEBUG: response_str snippet ->", response_str[:200])
 
-    response_message = cl.Message(content="")
-    for token in str(response):
-        await response_message.stream_token(token=token)
+        # Stream the text token by token
+        response_message = cl.Message(content="")
+        for token in response_str:
+            await response_message.stream_token(token=token)
 
-    await response_message.send()
+        await response_message.send()
+
+    except Exception as e:
+        print("DEBUG: Error in main query ->", str(e))
+        await cl.Message(content=f"Error while processing your question: {str(e)}").send()