bugfix

agent.py

@@ -33,6 +33,42 @@ tickers = {
 years = range(2015, 2025)
 initial_prompt = "How can I help you today?"
 
+# Tool to get the income statement for a given company and year using the FMP API
+@lru_cache(maxsize=128)
+def fmp_income_statement(
+    ticker: str = Field(description="the ticker symbol of the company.", examples=["AAPL", "GOOG", "AMZN"]),
+    year: int = Field(description="the year for which to get the income statement.", examples=[2020, 2021, 2022]),
+) -> str:
+    """
+    Get the income statement for a given company and year using the FMP (https://financialmodelingprep.com) API.
+    Args:
+        ticker (str): the ticker symbol of the company.
+        year (int): the year for which to get the income statement.
+
+    Returns:
+        A dictionary with the income statement data. 
+        All data is in USD, but you can convert it to more compact form like K, M, B.
+    """
+    fmp_api_key = os.environ.get("FMP_API_KEY", None)
+    if fmp_api_key is None:
+        return "FMP_API_KEY environment variable not set. This tool does not work."
+    url = f"https://financialmodelingprep.com/api/v3/income-statement/{ticker}?apikey={fmp_api_key}"
+    response = requests.get(url)
+    if response.status_code == 200:
+        data = response.json()
+        income_statement = pd.DataFrame(data)
+        if len(income_statement) == 0 or "date" not in income_statement.columns:
+            return "No data found for the given ticker symbol."
+        income_statement["date"] = pd.to_datetime(income_statement["date"])
+        income_statement_specific_year = income_statement[
+            income_statement["date"].dt.year == int(year)
+        ]
+        values_dict = income_statement_specific_year.to_dict(orient="records")[0]
+        return f"Financial results: {', '.join([f'{key}={value}' for key, value in values_dict.items() if key not in ['date', 'cik', 'link', 'finalLink']])}"
+    
+    return f"FMP API returned error {response.status_code}. This tool does not work."
+
+
 def create_assistant_tools(cfg):
 
     def get_company_info() -> list[str]:
@@ -50,35 +86,6 @@ def create_assistant_tools(cfg):
         """
         return years
 
-    # Tool to get the income statement for a given company and year using the FMP API
-    @lru_cache(maxsize=128)
-    def fmp_income_statement(
-        ticker: str = Field(description="the ticker symbol of the company.", examples=["AAPL", "GOOG", "AMZN"]),
-        year: int = Field(description="the year for which to get the income statement.", examples=[2020, 2021, 2022]),
-    ) -> str:
-        """
-        Get the income statement for a given company and year using the FMP (https://financialmodelingprep.com) API.
-        Returns a dictionary with the income statement data. All data is in USD, but you can convert it to more compact form like K, M, B.
-        """
-        fmp_api_key = os.environ.get("FMP_API_KEY", None)
-        if fmp_api_key is None:
-            return "FMP_API_KEY environment variable not set. This tool does not work."
-        url = f"https://financialmodelingprep.com/api/v3/income-statement/{ticker}?apikey={fmp_api_key}"
-        response = requests.get(url)
-        if response.status_code == 200:
-            data = response.json()
-            income_statement = pd.DataFrame(data)
-            if len(income_statement) == 0 or "date" not in income_statement.columns:
-                return "No data found for the given ticker symbol."
-            income_statement["date"] = pd.to_datetime(income_statement["date"])
-            income_statement_specific_year = income_statement[
-                income_statement["date"].dt.year == int(year)
-            ]
-            values_dict = income_statement_specific_year.to_dict(orient="records")[0]
-            return f"Financial results: {', '.join([f'{key}={value}' for key, value in values_dict.items() if key not in ['date', 'cik', 'link', 'finalLink']])}"
-        
-        return f"FMP API returned error {response.status_code}. This tool does not work."
-
     class QueryTranscriptsArgs(BaseModel):
         query: str = Field(..., description="The user query, always in the form of a question", examples=["what are the risks reported?", "who are the competitors?"])
         year: int | str = Field(
@@ -103,7 +110,7 @@ def create_assistant_tools(cfg):
         summary_num_results = 10,
         vectara_summarizer = summarizer,
         include_citations = True,
-        verbose=True,
+        verbose=False,
     )
 
     class SearchTranscriptsArgs(BaseModel):
@@ -120,10 +127,10 @@ def create_assistant_tools(cfg):
         tool_description = """
         Given a company name and year, and a user query, retrieves the most relevant text from analyst call transcripts about the company related to the user query.
         """,
-        tool_args_schema = QueryTranscriptsArgs,
+        tool_args_schema = SearchTranscriptsArgs,
         reranker = "multilingual_reranker_v1", rerank_k = 100,
         lambda_val = 0.005,
-        verbose=True
+        verbose=False
     )
 
     tools_factory = ToolsFactory()
@@ -142,14 +149,15 @@ def create_assistant_tools(cfg):
 def initialize_agent(_cfg, agent_progress_callback=None):
     financial_bot_instructions = """
     - You are a helpful financial assistant, with expertise in financial reporting, in conversation with a user. 
+    - Always use the 'income_statement' tool to obtain accurate financial data like revenues, expenses, net income, and other financial metrics 
+      for a specific company, for any the year 2020 or later. 
+    - Use the 'fmp_income_statement' tool (with the company ticker and year) to obtain financial data for any year before 2020,
+    - Use the 'fmp_income_statement` tool (with the company ticker and year) to obtain financial data for any year on or after 2020, when the 'income_statement'
+      did not return any data useful to respond to the user query.
+    - Always check the 'get_company_info' and 'get_valid_years' tools to validate company and year are valid.
     - Use the ask_transcripts tool to answer most questions about the company's financial performance, risks, opportunities, strategy, competitors, and more.
-    - responses from ask_transcripts are summarized. You don't need to further summarize them.
     - Respond in a compact format by using appropriate units of measure (e.g., K for thousands, M for millions, B for billions). 
       Do not report the same number twice (e.g. $100K and 100,000 USD).
-    - Always use the 'income_statement' tool to obtain accurate financial data like revenues, expenses, net income, and other financial metrics 
-      for a specific company, for any the year 2020 or later.
-    - Use the 'fmp_income_statement' tool (with the company ticker and year) to obtain financial data for any year before 2020.
-    - Always check the 'get_company_info' and 'get_valid_years' tools to validate company and year are valid.
     - Do not include URLs unless they are provided in the output of a tool you use.
     - When querying a tool for a numeric value or KPI, use a concise and non-ambiguous description of what you are looking for. 
     - If you calculate a metric, make sure you have all the necessary information to complete the calculation. Don't guess.

requirements.txt

@@ -6,4 +6,4 @@ streamlit_feedback==0.1.3
 uuid==1.30
 langdetect==1.0.9
 langcodes==3.4.0
-vectara-agentic==0.2.0
+vectara-agentic==0.2.1