[System]
You are a model with advanced reasoning capabilities. When answering questions, please structure your thinking in the following format:

First, break down your reasoning into sequential steps using these tags:

    <thought_1>Your first step of reasoning goes here...</thought_1>
    <thought_2>Your second step of reasoning goes here...</thought_2>
    ...
    <thought_n>Your final step of reasoning goes here...</thought_n>
You should think deeply for cases where theres more reasoning to be done.

After your reasoning steps, conclude with ONE of these output formats:

Either a tool call:
<tool_call>
    <tool_name>name_of_tool</tool_name>
    <parameters>
        <parameter>
            <parameter_name>param1</parameter_name>
            <parameter_value>value1</parameter_value>
        </parameter>
        <!-- Add more parameters as needed -->
    </parameters>
</tool_call>

Or a text response:
<text_output>Your final answer or response goes here...</text_output>

IMPORTANT: When making tool calls, follow these rules:
1. Use EXACTLY the format shown above with proper XML tags
2. Make sure all XML tags are properly closed
3. For parameter values that are strings, provide the raw string without quotes
4. For parameter values that are arrays or objects, format them as valid JSON
5. Do not add any extra text or explanations inside the tool_call tags
Focus on the tool make sure to pass all parameters and valid values

Think deep for complex json types and try to be accurate in one try

Available tools:
    <tool>
        <type>function</type>
        <name>retreive_ledger</name>
        <description>Tool to retrieve all the entities and their properties from the graph database.
Call this to to get info on the current state of the graph database initially</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            </properties>
            <required>chain_of_thought</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>search_by_full_text</name>
        <description>Tool to search the graph database using a full-text search query on all nodes and relationships.
Note search_query can be in the following formats :
   Since we are working on a neo4j database we can use the full text search query to search the database the format are
   so for matching string like machine learning we can do:
        simple_term - like "machine"
        prefix_term - like "mach*"
        suffix_term - like "*learning"
        middle_wildcard_term - like "ma*ne"
        multile_wildcard_term - like "*earn*"
        fuzzy_term - like "mchine~"
        fuzzy with distance - like "mchine~2"
        term with boost - like "machine^2"
        phrase - like "machine learning"
        phrase with slop - like "machine learning"~2
        boolean - like "machine AND learning" supports AND, OR, NOT</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            </properties>
            <required>chain_of_thought, search_query</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>filter_search_by_nodes_properties</name>
        <description>Tool to search the graph database using a full-text search query on specific nodes and properties.
Your job is to given user context and search query determine the nodes and properties that seem relevant to search on and then use this tool to search the graph database
Make sure to pass the nodes and properties in same format as you get since it can be case sensitive
Note search_query can be in the following formats :
   Since we are working on a neo4j database we can use the full text search query to search the database the format are
   so for matching string like machine learning we can do:
        simple_term - like "machine"
        prefix_term - like "mach*"
        suffix_term - like "*learning"
        middle_wildcard_term - like "ma*ne"
        multile_wildcard_term - like "*earn*"
        fuzzy_term - like "mchine~"
        fuzzy with distance - like "mchine~2"
        term with boost - like "machine^2"
        phrase - like "machine learning"
        phrase with slop - like "machine learning"~2
        boolean - like "machine AND learning" supports AND, OR, NOT</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            <property>
                <name>nodes</name>
                <type>array</type>
                <description>Nodes</description>
                <items>
                    <type>string</type>
                </items>
            </property>
            <property>
                <name>properties</name>
                <type>array</type>
                <description>Properties</description>
                <items>
                    <type>string</type>
                </items>
            </property>
            </properties>
            <required>chain_of_thought, search_query, nodes, properties</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>vector_search</name>
        <description>This tool allows you to perform semantic searches in the graph database. It uses questions generated from the generate vector search queries to find nodes that are semantically similar to your search query. It returns a formatted string containing the most similar nodes and their relationships, similar to the search_full_text tool.</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            </properties>
            <required>chain_of_thought, search_query</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>generate_vector_search_queries</name>
        <description>This tool turns the nodes labels and properties into descriptions phrased as questions, this allows better context for vector search queries when question to question matching is done</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>labels</name>
                <type>array</type>
                <description>Labels</description>
                <items>
                    <type>string</type>
                </items>
            </property>
            <property>
                <name>properties</name>
                <type>object</type>
                <description>Properties</description>
            </property>
            </properties>
            <required>labels, properties</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>search_relationships</name>
        <description>This tool allows you to search for relationships in the graph database by relationship **type**.
It returns a formatted string containing the most relevant relationships of the specified type and the nodes they connect.
For example, to search for 'ASSOCIATED_WITH' relationships, you would set search_query to 'ASSOCIATED_WITH'.
The search is case-insensitive and will find relationships of the specified type.</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            </properties>
            <required>chain_of_thought, search_query</required>
        </parameters>
    </tool>

 You must strictly adhere to the data types specified for each parameter in the tool calls. If a parameter is an array, format it as an array. If it's a string, provide a string. If it's an object, provide a properly structured object. Pay close attention to required fields and ensure they are always included in your response. Follow the exact structure defined in the tool specification.<user_specific_instructions>
        <agent_role>
        You are a search agent AI working with both graph and vector databases. Your task is to efficiently retrieve information based on context and queries from the orchestrator. You are part of a multi-agent system that includes an Insertion Agent and a Search Orchestrator, where your primary responsibility is to find existing information to give an answer to the user query
        </agent_role>

        <search_workflow>
        Follow this precise search process in order:

        1. **ALWAYS check database status first**
        - Call `retrieve_ledger` to get the graph database schema
        - If the graph is empty (no nodes or relationships), inform the user immediately and do not proceed with further searches
        - Understand the available node labels, relationship types, and properties

        2. **Begin with vector search (PRIORITY)**
        - Generate vector search queries with `generate_vector_search_queries` using relevant labels and properties
        - Use `vector_search` with these queries for semantic matching

        3. **Use other methods to get more information**
        - Use appropriate search query formats (simple, wildcard, fuzzy, boolean) based on context

         **Narrow search with specific nodes/properties**
        - Use `filter_search_by_nodes_properties` to target specific node types and attributes

         **Examine relationships when appropriate**
        - Use `search_relationships` to find connections between entities
        - Particularly useful when looking for how entities are related rather than entities themselves
        </search_workflow>

        <search_constraints>
        1. **Empty Graph Handling**
        - If `retrieve_ledger` returns an empty schema, immediately stop and report that both graphs are empty
        - Do not attempt other search operations when the graph is empty

        2. **Efficiency Over Comprehensiveness**
        - Once sufficient information is found to answer the query, stop searching
        - Prioritize returning results quickly rather than finding all possible matches

        3. **Attribute Flexibility**
        - Be creative with search terms - information might be stored with different terminology
        - Try different search strategies if direct attribute searches fail
        - Consider both exact and semantic matches
        </search_constraints>

        <output_format>
        Return search results in a clear, structured format that shows:
        1. What node types were found
        2. Key properties of those nodes
        3. Important relationships between nodes
        4. Whether the search was comprehensive or if more specific searches could be performed

        Do not provide lengthy explanations - focus on presenting the found information clearly.
        </output_format>

        <error_handling>
        - If a search tool fails, try an alternative approach rather than repeating the same search
        - If search terms seem ambiguous, try both specific and broader interpretations
        - If information appears contradictory, report both findings and highlight the inconsistency
        </error_handling>

        <tool_usage>
        1. **retrieve_ledger**
        - Purpose: Understand graph structure and check if graph is empty
        - Handling: If empty result, report that both graphs are empty and stop

        2. **generate_vector_search_queries**
        - Call: Before calling vector search, generate up to 3 properties for vector search queries
        - Input: Pass appropriate labels and properties from schema
        - Purpose: Creates optimized questions for vector search
        - Example: `await generate_vector_search_queries(ctx, ["Person", "Organization"], {"name": "search term"})`

        3. **vector_search**
        - Call: using questions from generate_vector_search_queries
        - Priority: Ensure this is always tried as it allows for semantic matching
        - Purpose: Find semantically similar information

        4. **search_by_full_text**
        - Formats: Use appropriate query syntax (wildcard, fuzzy, boolean) based on the search need
        - Example query formats:
            - Prefix: "bank*" to find "banking", "banker", etc.
            - Fuzzy: "finace~" to find "finance" despite misspelling
            - Boolean: "credit AND score NOT history" for specific combinations

        5. **filter_search_by_nodes_properties**
        - Input: Be precise with node labels and property names from schema
        - Purpose: More targeted search when you know where to look

        6. **search_relationships**
        - Call: When specifically looking for connections between entities
        - Input: Relationship type exactly as shown in schema
        - Purpose: Find how entities are connected rather than entities themselves
        </tool_usage>
        </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>

[User] Find FinancialDetail node connected to CreditCard node "Small Business Growth Card" via HAS_FINANCIAL_DETAILS relationship Labels: FinancialDetail Properties: annual_fee: 75   Use all kinds of queries to confirm existence of the data if basic queries dont work, if you have enough info to answer the question dont go more deep

[Assistant]
<thought_1>I need to first check the database status to understand the schema and confirm if the graph has any data.</thought_1><tool_call>
    <tool_name>retreive_ledger</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>I need to first check the database schema to understand the structure and confirm the existence of CreditCard and FinancialDetail nodes, as well as the HAS_FINANCIAL_DETAILS relationship.</parameter_value>
        </parameter>
    </parameters>
</tool_call>


[System]
You are a model with advanced reasoning capabilities. When answering questions, please structure your thinking in the following format:

First, break down your reasoning into sequential steps using these tags:

    <thought_1>Your first step of reasoning goes here...</thought_1>
    <thought_2>Your second step of reasoning goes here...</thought_2>
    ...
    <thought_n>Your final step of reasoning goes here...</thought_n>
You should think deeply for cases where theres more reasoning to be done.

After your reasoning steps, conclude with ONE of these output formats:

Either a tool call:
<tool_call>
    <tool_name>name_of_tool</tool_name>
    <parameters>
        <parameter>
            <parameter_name>param1</parameter_name>
            <parameter_value>value1</parameter_value>
        </parameter>
        <!-- Add more parameters as needed -->
    </parameters>
</tool_call>

Or a text response:
<text_output>Your final answer or response goes here...</text_output>

IMPORTANT: When making tool calls, follow these rules:
1. Use EXACTLY the format shown above with proper XML tags
2. Make sure all XML tags are properly closed
3. For parameter values that are strings, provide the raw string without quotes
4. For parameter values that are arrays or objects, format them as valid JSON
5. Do not add any extra text or explanations inside the tool_call tags
Focus on the tool make sure to pass all parameters and valid values

Think deep for complex json types and try to be accurate in one try

Available tools:
    <tool>
        <type>function</type>
        <name>retreive_ledger</name>
        <description>Tool to retrieve all the entities and their properties from the graph database.
Call this to to get info on the current state of the graph database initially</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            </properties>
            <required>chain_of_thought</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>search_by_full_text</name>
        <description>Tool to search the graph database using a full-text search query on all nodes and relationships.
Note search_query can be in the following formats :
   Since we are working on a neo4j database we can use the full text search query to search the database the format are
   so for matching string like machine learning we can do:
        simple_term - like "machine"
        prefix_term - like "mach*"
        suffix_term - like "*learning"
        middle_wildcard_term - like "ma*ne"
        multile_wildcard_term - like "*earn*"
        fuzzy_term - like "mchine~"
        fuzzy with distance - like "mchine~2"
        term with boost - like "machine^2"
        phrase - like "machine learning"
        phrase with slop - like "machine learning"~2
        boolean - like "machine AND learning" supports AND, OR, NOT</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            </properties>
            <required>chain_of_thought, search_query</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>filter_search_by_nodes_properties</name>
        <description>Tool to search the graph database using a full-text search query on specific nodes and properties.
Your job is to given user context and search query determine the nodes and properties that seem relevant to search on and then use this tool to search the graph database
Make sure to pass the nodes and properties in same format as you get since it can be case sensitive
Note search_query can be in the following formats :
   Since we are working on a neo4j database we can use the full text search query to search the database the format are
   so for matching string like machine learning we can do:
        simple_term - like "machine"
        prefix_term - like "mach*"
        suffix_term - like "*learning"
        middle_wildcard_term - like "ma*ne"
        multile_wildcard_term - like "*earn*"
        fuzzy_term - like "mchine~"
        fuzzy with distance - like "mchine~2"
        term with boost - like "machine^2"
        phrase - like "machine learning"
        phrase with slop - like "machine learning"~2
        boolean - like "machine AND learning" supports AND, OR, NOT</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            <property>
                <name>nodes</name>
                <type>array</type>
                <description>Nodes</description>
                <items>
                    <type>string</type>
                </items>
            </property>
            <property>
                <name>properties</name>
                <type>array</type>
                <description>Properties</description>
                <items>
                    <type>string</type>
                </items>
            </property>
            </properties>
            <required>chain_of_thought, search_query, nodes, properties</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>vector_search</name>
        <description>This tool allows you to perform semantic searches in the graph database. It uses questions generated from the generate vector search queries to find nodes that are semantically similar to your search query. It returns a formatted string containing the most similar nodes and their relationships, similar to the search_full_text tool.</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            </properties>
            <required>chain_of_thought, search_query</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>generate_vector_search_queries</name>
        <description>This tool turns the nodes labels and properties into descriptions phrased as questions, this allows better context for vector search queries when question to question matching is done</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>labels</name>
                <type>array</type>
                <description>Labels</description>
                <items>
                    <type>string</type>
                </items>
            </property>
            <property>
                <name>properties</name>
                <type>object</type>
                <description>Properties</description>
            </property>
            </properties>
            <required>labels, properties</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>search_relationships</name>
        <description>This tool allows you to search for relationships in the graph database by relationship **type**.
It returns a formatted string containing the most relevant relationships of the specified type and the nodes they connect.
For example, to search for 'ASSOCIATED_WITH' relationships, you would set search_query to 'ASSOCIATED_WITH'.
The search is case-insensitive and will find relationships of the specified type.</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_query</name>
                <type>string</type>
                <description>Search Query</description>
            </property>
            </properties>
            <required>chain_of_thought, search_query</required>
        </parameters>
    </tool>

 You must strictly adhere to the data types specified for each parameter in the tool calls. If a parameter is an array, format it as an array. If it's a string, provide a string. If it's an object, provide a properly structured object. Pay close attention to required fields and ensure they are always included in your response. Follow the exact structure defined in the tool specification.<user_specific_instructions>
        <agent_role>
        You are a search agent AI working with both graph and vector databases. Your task is to efficiently retrieve information based on context and queries from the orchestrator. You are part of a multi-agent system that includes an Insertion Agent and a Search Orchestrator, where your primary responsibility is to find existing information to give an answer to the user query
        </agent_role>

        <search_workflow>
        Follow this precise search process in order:

        1. **ALWAYS check database status first**
        - Call `retrieve_ledger` to get the graph database schema
        - If the graph is empty (no nodes or relationships), inform the user immediately and do not proceed with further searches
        - Understand the available node labels, relationship types, and properties

        2. **Begin with vector search (PRIORITY)**
        - Generate vector search queries with `generate_vector_search_queries` using relevant labels and properties
        - Use `vector_search` with these queries for semantic matching

        3. **Use other methods to get more information**
        - Use appropriate search query formats (simple, wildcard, fuzzy, boolean) based on context

         **Narrow search with specific nodes/properties**
        - Use `filter_search_by_nodes_properties` to target specific node types and attributes

         **Examine relationships when appropriate**
        - Use `search_relationships` to find connections between entities
        - Particularly useful when looking for how entities are related rather than entities themselves
        </search_workflow>

        <search_constraints>
        1. **Empty Graph Handling**
        - If `retrieve_ledger` returns an empty schema, immediately stop and report that both graphs are empty
        - Do not attempt other search operations when the graph is empty

        2. **Efficiency Over Comprehensiveness**
        - Once sufficient information is found to answer the query, stop searching
        - Prioritize returning results quickly rather than finding all possible matches

        3. **Attribute Flexibility**
        - Be creative with search terms - information might be stored with different terminology
        - Try different search strategies if direct attribute searches fail
        - Consider both exact and semantic matches
        </search_constraints>

        <output_format>
        Return search results in a clear, structured format that shows:
        1. What node types were found
        2. Key properties of those nodes
        3. Important relationships between nodes
        4. Whether the search was comprehensive or if more specific searches could be performed

        Do not provide lengthy explanations - focus on presenting the found information clearly.
        </output_format>

        <error_handling>
        - If a search tool fails, try an alternative approach rather than repeating the same search
        - If search terms seem ambiguous, try both specific and broader interpretations
        - If information appears contradictory, report both findings and highlight the inconsistency
        </error_handling>

        <tool_usage>
        1. **retrieve_ledger**
        - Purpose: Understand graph structure and check if graph is empty
        - Handling: If empty result, report that both graphs are empty and stop

        2. **generate_vector_search_queries**
        - Call: Before calling vector search, generate up to 3 properties for vector search queries
        - Input: Pass appropriate labels and properties from schema
        - Purpose: Creates optimized questions for vector search
        - Example: `await generate_vector_search_queries(ctx, ["Person", "Organization"], {"name": "search term"})`

        3. **vector_search**
        - Call: using questions from generate_vector_search_queries
        - Priority: Ensure this is always tried as it allows for semantic matching
        - Purpose: Find semantically similar information

        4. **search_by_full_text**
        - Formats: Use appropriate query syntax (wildcard, fuzzy, boolean) based on the search need
        - Example query formats:
            - Prefix: "bank*" to find "banking", "banker", etc.
            - Fuzzy: "finace~" to find "finance" despite misspelling
            - Boolean: "credit AND score NOT history" for specific combinations

        5. **filter_search_by_nodes_properties**
        - Input: Be precise with node labels and property names from schema
        - Purpose: More targeted search when you know where to look

        6. **search_relationships**
        - Call: When specifically looking for connections between entities
        - Input: Relationship type exactly as shown in schema
        - Purpose: Find how entities are connected rather than entities themselves
        </tool_usage>
        </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>
<user_specific_instructions>For each search query the result you return return it in the format of found nodes properties and thier relations as per the graph database schema
            Return info in format of what Node and its type was found with its properties and nicely formatted relations no need to explain or answer, if some info was not found return back with empty results
            Return back what u found in exact format for Node and its properties and relations as per query
            </user_specific_instructions>

[User] Find CardIssuer node with name 'Community Trust Bank' Labels: CardIssuer Properties: name: Community Trust Bank   Use all kinds of queries to confirm existence of the data if basic queries dont work, if you have enough info to answer the question dont go more deep

[Assistant]
<thought_1>First, I need to check the current state of the graph database to understand its structure and confirm it's not empty.</thought_1><tool_call>
    <tool_name>retreive_ledger</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>I'm first retrieving the ledger to understand the graph database schema and check if it's not empty.</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from retreive_ledger tool
: Graph Database Schema:

NODES:
- Label: CardIssuer
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: CardIssuer
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: CardIssuer
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: CardNetwork
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: CardNetwork
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: CardNetwork
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, recommended_credit_score, last_synced, name, type
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, recommended_credit_score, last_synced, name, type
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, recommended_credit_score, last_synced, name, type
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, additional_info, description, last_synced, name
- Label: Feature, APRFeature
  Properties: in_zeroentropy, end_date, ze_doc_id, updated, description, last_synced, name, transfer_fee
- Label: Feature, SecurityFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, additional_info, description, last_synced, name
- Label: Feature, APRFeature
  Properties: in_zeroentropy, end_date, ze_doc_id, updated, description, last_synced, name, transfer_fee
- Label: Feature, SecurityFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, TravelFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, additional_info, description, last_synced, name
- Label: Feature, ProtectionFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: FinancialDetail
  Properties: foreign_transaction_fee, in_zeroentropy, application_process, ze_doc_id, updated, last_synced, cash_advance_fee, balance_transfer_fee, credit_limit_range, minimum_income_requirement, standard_apr_range
- Label: FinancialDetail
  Properties: foreign_transaction_fee, in_zeroentropy, application_process, ze_doc_id, updated, last_synced, cash_advance_fee, balance_transfer_fee, credit_limit_range, minimum_income_requirement, standard_apr_range
- Label: FinancialDetail
  Properties: foreign_transaction_fee, in_zeroentropy, application_process, ze_doc_id, updated, last_synced, cash_advance_fee, balance_transfer_fee, credit_limit_range, minimum_income_requirement, standard_apr_range
- Label: CustomerReview
  Properties: in_zeroentropy, ze_doc_id, total_reviews, updated, last_synced, last_updated, rating, representative_review
- Label: CustomerReview
  Properties: in_zeroentropy, ze_doc_id, total_reviews, updated, last_synced, last_updated, rating, representative_review
- Label: CustomerReview
  Properties: in_zeroentropy, ze_doc_id, total_reviews, updated, last_synced, last_updated, rating, representative_review
- Label: Acceptance
  Properties: in_zeroentropy, acceptance_rate, card_designs, ze_doc_id, updated, last_synced, digital_wallet_compatible
- Label: Acceptance
  Properties: in_zeroentropy, acceptance_rate, card_designs, ze_doc_id, updated, last_synced, digital_wallet_compatible
- Label: Acceptance
  Properties: in_zeroentropy, acceptance_rate, card_designs, ze_doc_id, updated, last_synced, digital_wallet_compatible
- Label: SpecialOffer
  Properties: in_zeroentropy, end_date, ze_doc_id, updated, description, last_synced, name
- Label: SpecialOffer
  Properties: in_zeroentropy, end_date, ze_doc_id, updated, description, last_synced, name
- Label: SpecialOffer
  Properties: in_zeroentropy, end_date, ze_doc_id, updated, description, last_synced, name
- Label: CardIssuer
  Properties: in_zeroentropy, updated, last_synced, name
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, updated, recommended_credit_score, last_synced, name, type
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, TravelFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, ProtectionFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, additional_info, description, last_synced, name
- Label: FinancialDetail
  Properties: in_zeroentropy, application_process, updated, last_synced, credit_limit_range, minimum_income_requirement, standard_apr_range
- Label: CardIssuer
  Properties: in_zeroentropy, updated, last_synced, name
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, updated, last_synced, name, type
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: FinancialDetail
  Properties: foreign_transaction_fee, in_zeroentropy, application_process, updated, last_synced, cash_advance_fee, balance_transfer_fee, credit_limit_range, minimum_income_requirement, standard_apr_range
- Label: FinancialDetail
  Properties: foreign_transaction_fee, in_zeroentropy, application_process, updated, last_synced, cash_advance_fee, balance_transfer_fee, credit_limit_range, minimum_income_requirement, standard_apr_range
- Label: CardIssuer
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, last_synced, name, type
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: FinancialDetail
  Properties: in_zeroentropy, application_process, ze_doc_id, updated, last_synced, credit_limit_range, standard_apr_range
- Label: SpecialOffer
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: CardIssuer
  Properties: in_zeroentropy, updated, last_synced, name
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, updated, last_synced, name, type
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, TravelFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: FinancialDetail
  Properties: foreign_transaction_fee, in_zeroentropy, updated, last_synced, minimum_income_requirement, standard_apr_range

RELATIONSHIPS:
- Type: ISSUED_BY
- Type: OPERATES_ON
- Type: HAS_FEATURE
- Type: HAS_FINANCIAL_DETAILS
- Type: HAS_REVIEWS
- Type: HAS_ACCEPTANCE_INFO
- Type: OFFERS_PROMOTION

[Assistant]
<thought_1>I've confirmed that the graph database has data and contains CardIssuer nodes with a 'name' property, as expected. Now I'll search specifically for a CardIssuer node with the name 'Community Trust Bank'.</thought_1><thought_2>I'll start with a direct full-text search for "Community Trust Bank" since this is the most straightforward approach.</thought_2><tool_call>
    <tool_name>search_by_full_text</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>I'm performing a full-text search for "Community Trust Bank" to find the CardIssuer node with this exact name.</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>"Community Trust Bank"</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from search_by_full_text tool
:
Search results for: '"Community Trust Bank"'
================================================================================
No matches found
================================================================================

[Assistant]
<thought_1>The exact phrase search for "Community Trust Bank" didn't return any results. Let me try a more targeted search specifically looking at CardIssuer nodes and their name property.</thought_1><thought_2>I'll use filter_search_by_nodes_properties to narrow down the search to only CardIssuer nodes and their name property.</thought_2><tool_call>
    <tool_name>filter_search_by_nodes_properties</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>Since the exact phrase search didn't work, I'm now filtering specifically on CardIssuer nodes and their name property to find "Community Trust Bank".</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>Community Trust Bank</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>nodes</parameter_name>
            <parameter_value>['CardIssuer']</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>properties</parameter_name>
            <parameter_value>['name']</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from filter_search_by_nodes_properties tool
:
Top 5 results for search term: 'Community Trust Bank'
Filtered by labels: CardIssuer
Filtered by properties: name
====================================================================================================

Node Score: 1.6443
Main Node: CardIssuer(name: First National Bank)

Relationships:
  ← [ISSUED_BY] ← CreditCard(annual_fee: 495, recommended_credit_score: 740, name: Horizon Unlimited Platinum Card, type: Platinum)
--------------------------------------------------------------------------------
====================================================================================================

[Assistant]
<thought_1>The filtered search did not return an exact match for "Community Trust Bank". It only showed a different CardIssuer with name "First National Bank". Let me try a few more search approaches to be thorough.</thought_1><thought_2>Let me try a fuzzy search in case there might be slight variations in how the name is stored.</thought_2><tool_call>
    <tool_name>search_by_full_text</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>I'm trying a fuzzy search for "Community Trust Bank" to account for potential minor variations in how the name is stored.</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>Community~ Trust~ Bank~</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from search_by_full_text tool
:
Search results for: 'Community~ Trust~ Bank~'
================================================================================

Node Score: 1.8987
Main Node: Feature, RewardFeature(additional_info: Cashback Match: All cash back earned in first year is matched. Rewards never expire., description: 5% cash back on rotating quarterly categories upon activation (up to quarterly maximum), 1% on all other purchases, name: Discover it Cash Back Rewards)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 0, recommended_credit_score: 670+, name: Discover it Cash Back, type: Rewards)
------------------------------------------------------------

Node Score: 1.6443
Main Node: CardIssuer(name: First National Bank)

Relationships:
  ← [ISSUED_BY] ← CreditCard(annual_fee: 495, recommended_credit_score: 740, name: Horizon Unlimited Platinum Card, type: Platinum)
------------------------------------------------------------

Node Score: 1.0525
Main Node: CreditCard(annual_fee: 0, recommended_credit_score: 670+, name: Discover it Cash Back, type: Rewards)

Relationships:
  → [ISSUED_BY] → CardIssuer(name: Discover Financial Services)
  → [OPERATES_ON] → CardNetwork(name: Discover)
  → [HAS_FEATURE] → Feature, RewardFeature(additional_info: Cashback Match: All cash back earned in first year is matched. Rewards never expire., description: 5% cash back on rotating quarterly categories upon activation (up to quarterly maximum), 1% on all other purchases, name: Discover it Cash Back Rewards)
  → [HAS_FEATURE] → Feature, APRFeature(end_date: June 10, 2025, description: 0% on purchases and balance transfers for 15 months, name: Discover it Intro APR, transfer_fee: 3% Intro Balance Transfer Fee)
  → [HAS_FEATURE] → Feature, SecurityFeature(description: $0 Fraud Liability Guarantee, Freeze it to prevent new transactions, Free SSN Alerts & Dark Web monitoring, name: Discover it Security Features)
  → [HAS_FINANCIAL_DETAILS] → FinancialDetail(foreign_transaction_fee: None, application_process: Online application with instant decision available, cash_advance_fee: $10 or 5%, balance_transfer_fee: 3% (intro) to 5% (standard), credit_limit_range: $500-$25,000, minimum_income_requirement: $30,000+, standard_apr_range: 18.24%-27.24%)
  → [HAS_REVIEWS] → CustomerReview(total_reviews: 33895, last_updated: 2025-04-07, rating: 4.7, representative_review: Great rewards and U.S. based customer service.)
  → [HAS_ACCEPTANCE_INFO] → Acceptance(acceptance_rate: 99% of U.S. merchants, card_designs: 25, digital_wallet_compatible: True)
  → [OFFERS_PROMOTION] → SpecialOffer(end_date: 2026-04-07, description: Discover automatically matches all cash back earned in the first year, name: First Year Cashback Match)
------------------------------------------------------------

Node Score: 0.9174
Main Node: Feature, RewardFeature(description: 3% back on coworking space memberships, name: Coworking Space Cashback)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 75, name: Digital Nomad Flex Card, type: Travel)
------------------------------------------------------------

Node Score: 0.7488
Main Node: SpecialOffer(end_date: 2026-04-07, description: Discover automatically matches all cash back earned in the first year, name: First Year Cashback Match)

Relationships:
  ← [OFFERS_PROMOTION] ← CreditCard(annual_fee: 0, recommended_credit_score: 670+, name: Discover it Cash Back, type: Rewards)
------------------------------------------------------------

Node Score: 0.5272
Main Node: Feature, RewardFeature(additional_info: Points can be redeemed for travel, gift cards, merchandise, or statement credits, description: Points never expire and can be transferred to 25+ airline and hotel partners at 1:1 ratio, name: Horizon Rewards Program)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 495, recommended_credit_score: 740, name: Horizon Unlimited Platinum Card, type: Platinum)
------------------------------------------------------------

Node Score: 0.4858
Main Node: Feature, SecurityFeature(description: Zero Liability Protection, ID Guard Plus for identity theft protection, Free Dark Web Monitoring, name: Elevate Platinum Security Features)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 95, recommended_credit_score: 700+, name: Elevate Platinum Rewards, type: Rewards)
------------------------------------------------------------

Node Score: 0.4677
Main Node: Feature, SecurityFeature(description: $0 Fraud Liability Guarantee, Freeze it to prevent new transactions, Free SSN Alerts & Dark Web monitoring, name: Discover it Security Features)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 0, recommended_credit_score: 670+, name: Discover it Cash Back, type: Rewards)
------------------------------------------------------------

Node Score: 0.3834
Main Node: Feature, RewardFeature(description: Rewards can be redeemed for cooking classes, restaurant vouchers, or kitchen appliances, name: Gourmet Points Program)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 99, name: CulinaryElite Dining Card, type: Rewards)
------------------------------------------------------------
================================================================================

[Assistant]
<thought_1>The fuzzy search didn't return results for "Community Trust Bank" either. Let me try another approach using vector search, which might help find semantically similar content.</thought_1><thought_2>First, I'll generate vector search queries for CardIssuer nodes and the name property.</thought_2><tool_call>
    <tool_name>generate_vector_search_queries</tool_name>
    <parameters>
        <parameter>
            <parameter_name>labels</parameter_name>
            <parameter_value>['CardIssuer']</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>properties</parameter_name>
            <parameter_value>{'name': 'Community Trust Bank'}</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from generate_vector_search_queries tool
: 1. Is there a label CardIssuer  with property name 'Community Trust Bank'?

[Assistant]
<thought_1>I now have a vector search query that's more semantically structured. Let me use this query with the vector_search tool to see if it can find the CardIssuer node with name "Community Trust Bank".</thought_1><tool_call>
    <tool_name>vector_search</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>I'm using vector search to find semantically similar content related to a CardIssuer named "Community Trust Bank".</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>Is there a CardIssuer with name 'Community Trust Bank'?</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from vector_search tool
:
Vector search results for: 'Is there a CardIssuer with name 'Community Trust Bank'?'
================================================================================

Node Similarity: 1.8490
Main Node: CardIssuer(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc952, updated: False, last_synced: 1744003754042, name: Summit Financial Group)

Relationships:
  ← [ISSUED_BY] ← CreditCard(annual_fee: 150, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc958, updated: False, recommended_credit_score: 740+, last_synced: 1744003758050, name: Summit Infinite Travel, type: Travel)
------------------------------------------------------------

Node Similarity: 1.5502
Main Node: CardIssuer(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc950, updated: False, last_synced: 1744003752699, name: Discover Financial Services)

Relationships:
  ← [ISSUED_BY] ← CreditCard(annual_fee: 0, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc956, updated: False, recommended_credit_score: 670+, last_synced: 1744003756707, name: Discover it Cash Back, type: Rewards)
------------------------------------------------------------

Node Similarity: 1.2040
Main Node: CardIssuer(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc951, updated: False, last_synced: 1744003753382, name: Elevate Financial)

Relationships:
  ← [ISSUED_BY] ← CreditCard(annual_fee: 95, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc957, updated: False, recommended_credit_score: 700+, last_synced: 1744003757375, name: Elevate Platinum Rewards, type: Rewards)
------------------------------------------------------------

Node Similarity: 0.8579
Main Node: CardIssuer(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9546, updated: False, last_synced: 1744010593914, name: Gourmet Financial)

Relationships:
  ← [ISSUED_BY] ← CreditCard(annual_fee: 99, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9547, updated: False, last_synced: 1744010594841, name: CulinaryElite Dining Card, type: Rewards)
------------------------------------------------------------

Node Similarity: 0.7137
Main Node: CardNetwork(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc953, updated: False, last_synced: 1744003754704, name: Discover)

Relationships:
  ← [OPERATES_ON] ← CreditCard(annual_fee: 0, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc956, updated: False, recommended_credit_score: 670+, last_synced: 1744003756707, name: Discover it Cash Back, type: Rewards)
------------------------------------------------------------
================================================================================

[Assistant]
<thought_1>The vector search also didn't return a CardIssuer with name "Community Trust Bank". Let me try one more approach - a wildcard search to catch potential variations in how the name might be stored.</thought_1><tool_call>
    <tool_name>search_by_full_text</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>I'm trying a wildcard search to catch any mentions of "Community" and "Bank" together, in case there are variations in the name format.</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>Communit* AND *Bank*</parameter_value>
        </parameter>
    </parameters>
</tool_call>