[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] Find a RewardFeature node with name "Charity Donation Match" Labels: Feature, RewardFeature Properties: name: Charity Donation Match   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 database status to understand the schema and confirm if there are nodes in the database.</thought_1><tool_call>
    <tool_name>retreive_ledger</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>Retrieving the current state of the graph database to understand its schema and check if it's empty before proceeding with specific searches.</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
- 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
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, ProtectionFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature
  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: Feature, ProtectionFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: FinancialDetail
  Properties: in_zeroentropy, application_process, updated, last_synced, credit_limit_range, 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, recommended_credit_score, last_synced, name, eligibility, 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
  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: annual_fee, in_zeroentropy, application_process, ze_doc_id, updated, description, last_synced
- 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, eligibility, type
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, ProtectionFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature
  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: annual_fee, in_zeroentropy, application_process, ze_doc_id, updated, last_synced
- 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: FinancialDetail
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, description, last_synced
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, last_synced, name, type
- Label: CardIssuer
  Properties: in_zeroentropy, ze_doc_id, updated, last_synced, name
- Label: Feature, APRFeature
  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: annual_fee, in_zeroentropy, application_process, updated, last_synced
- Label: CardIssuer
  Properties: in_zeroentropy, 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
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature
  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: FinancialDetail
  Properties: annual_fee, in_zeroentropy, updated, last_synced, 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
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: FinancialDetail
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, last_synced
- 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, ProtectionFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature, ProtectionFeature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: Feature
  Properties: in_zeroentropy, ze_doc_id, updated, description, last_synced, name
- Label: FinancialDetail
  Properties: annual_fee, in_zeroentropy, ze_doc_id, updated, last_synced
- Label: CardIssuer
  Properties: in_zeroentropy, updated, last_synced, name
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, updated, last_synced, name, eligibility, type
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, description, last_synced, name
- Label: Feature, RewardFeature
  Properties: in_zeroentropy, updated, additional_info, 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: annual_fee, in_zeroentropy, application_process, updated, last_synced
- Label: CardIssuer
  Properties: in_zeroentropy, updated, last_synced, name
- Label: CreditCard
  Properties: annual_fee, in_zeroentropy, updated, last_synced, name, type

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

[Assistant]
<thought_1>Now I understand the database schema. I can see that there are RewardFeature nodes with a "name" property, which is what I'm looking for. I'll search specifically for a RewardFeature node with name "Charity Donation Match".</thought_1><thought_2>I'll start with a direct search using the filter_search_by_nodes_properties tool, targeting specifically the RewardFeature nodes and the name property with the exact value we're looking for.</thought_2><tool_call>
    <tool_name>filter_search_by_nodes_properties</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>Searching specifically for RewardFeature nodes with name property matching "Charity Donation Match"</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>"Charity Donation Match"</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>nodes</parameter_name>
            <parameter_value>['Feature', 'RewardFeature']</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: '"Charity Donation Match"'
Filtered by labels: Feature, RewardFeature
Filtered by properties: name
====================================================================================================
No matches found
====================================================================================================

[Assistant]
<thought_1>The direct search for "Charity Donation Match" in RewardFeature nodes didn't yield any results. Let me try a more flexible search approach using fuzzy matching in case there are minor variations in the name.</thought_1><thought_2>I'll now try using search_by_full_text to perform a broader search with some variations like using fuzzy matching or wildcards for "charity" and "donation" terms.</thought_2><tool_call>
    <tool_name>search_by_full_text</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>Using full-text search with broader terms to find any RewardFeature related to charity donations, using fuzzy matching in case of spelling variations</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>charity~ AND donation~</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from search_by_full_text tool
:
Search results for: 'charity~ AND donation~'
================================================================================
No matches found
================================================================================

[Assistant]
<thought_1>The fuzzy search for "charity" AND "donation" also didn't yield any results. Let me try a more general search to see if there are any nodes with just "charity" or "donation" in their name or description.</thought_1><thought_2>I'll now use search_by_full_text with just "charity" to cast a wider net and see if there are any charity-related features at all.</thought_2><tool_call>
    <tool_name>search_by_full_text</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>Trying a broader search with just the term "charity" to see if there are any charity-related features</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>charity*</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from search_by_full_text tool
:
Search results for: 'charity*'
================================================================================
No matches found
================================================================================

[Assistant]
<thought_1>Still no results with broader search terms. Let me try one more approach with a vector search, which might capture semantic similarities even if the exact terms don't match.</thought_1><thought_2>First, I need to generate vector search queries appropriate for finding charity donation reward features.</thought_2><tool_call>
    <tool_name>generate_vector_search_queries</tool_name>
    <parameters>
        <parameter>
            <parameter_name>labels</parameter_name>
            <parameter_value>['Feature', 'RewardFeature']</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>properties</parameter_name>
            <parameter_value>{'name': 'Charity Donation Match', 'description': 'charitable donations matching'}</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from generate_vector_search_queries tool
: 1. Is there a label Feature  with property name 'Charity Donation Match'?
2. Is there a label Feature  with property description 'charitable donations matching'?
3. Is there a label RewardFeature  with property name 'Charity Donation Match'?

[Assistant]
<thought_1>Now I have appropriate vector search queries. I'll use these to perform a semantic search for charity donation matching features.</thought_1><tool_call>
    <tool_name>vector_search</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>Using vector search to find semantically similar nodes related to charity donation matching features</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>Charity Donation Match or credit card features related to charitable donations</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from vector_search tool
:
Vector search results for: 'Charity Donation Match or credit card features related to charitable donations'
================================================================================

Node Similarity: 1.8428
Main Node: Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95100, updated: False, description: Converts points to seed funding matches or business service credits, last_synced: 1744014996113, name: Founder Rewards Program)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: No fee for first three years, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9595, updated: False, last_synced: 1744014650401, name: Startup Venture Card, type: Business)
------------------------------------------------------------

Node Similarity: 1.5020
Main Node: Feature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95116, updated: False, description: Supports animal rescue organizations with each purchase, last_synced: 1744016558524, name: Animal Rescue Support)

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 50, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95111, updated: False, last_synced: 1744016389859, name: Pet Parent Priority Card, type: Rewards)
------------------------------------------------------------

Node Similarity: 1.1298
Main Node: Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc959, updated: False, 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, last_synced: 1744003901861, name: Discover it Cash Back Rewards)

Relationships:
  ← [HAS_FEATURE] ← 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: 0.7577
Main Node: CreditCard(annual_fee: 125, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9582, updated: False, last_synced: 1744013161400, name: Healthcare Heroes Card, eligibility: Verified healthcare professionals, type: Professional)

Relationships:
  → [ISSUED_BY] → CardIssuer(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9581, updated: False, last_synced: 1744013160619, name: Medical Professional Bank)
  → [HAS_FEATURE] → Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9583, updated: False, description: 4% cash back on all medical equipment purchases, last_synced: 1744013498724, name: 4% Cash Back on Medical Equipment)
  → [HAS_FEATURE] → Feature, ProtectionFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9584, updated: False, description: Special rates on malpractice insurance for cardholders, last_synced: 1744013499633, name: Discounted Malpractice Insurance)
  → [HAS_FEATURE] → Feature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9585, updated: False, description: Special financing options for healthcare practice expansion, last_synced: 1744013500559, name: Practice Expansion Financing)
  → [HAS_FEATURE] → Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9586, updated: False, description: Points can be converted to continuing education credits or medical conference registrations, last_synced: 1744013501358, name: Wellness Rewards Program)
  → [HAS_FINANCIAL_DETAILS] → FinancialDetail(annual_fee: 125, in_zeroentropy: True, application_process: Requires verification as healthcare professional, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc9587, updated: False, last_synced: 1744013596702)
------------------------------------------------------------

Node Similarity: 0.6218
Main Node: CreditCard(annual_fee: 50, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95111, updated: False, last_synced: 1744016389859, name: Pet Parent Priority Card, type: Rewards)

Relationships:
  → [ISSUED_BY] → CardIssuer(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95110, updated: False, last_synced: 1744016190971, name: Animal Lovers Credit Union)
  → [HAS_FEATURE] → Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95112, updated: False, description: 3% back on veterinary expenses, last_synced: 1744016555465, name: Veterinary Expense Cashback)
  → [HAS_FEATURE] → Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95113, updated: False, description: 3% back on pet supplies, last_synced: 1744016556287, name: Pet Supplies Cashback)
  → [HAS_FEATURE] → Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95114, updated: False, description: 3% back on pet insurance premiums, last_synced: 1744016557014, name: Pet Insurance Premium Cashback)
  → [HAS_FEATURE] → Feature, RewardFeature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95115, updated: False, description: Points can be redeemed for pet services, supplies, or donations to animal welfare organizations, last_synced: 1744016557734, name: Paw Points Program)
  → [HAS_FEATURE] → Feature(in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95116, updated: False, description: Supports animal rescue organizations with each purchase, last_synced: 1744016558524, name: Animal Rescue Support)
  → [HAS_FINANCIAL_DETAILS] → FinancialDetail(annual_fee: 50, in_zeroentropy: True, ze_doc_id: node-4d0ccce1e08ac44d9a5312fc28a30dc95117, updated: False, last_synced: 1744016636781)
------------------------------------------------------------
================================================================================

[Assistant]
<thought_1>The vector search found some potentially related nodes, but none of them specifically match "Charity Donation Match". The most relevant results are features like "Animal Rescue Support" which supports animal rescue organizations with each purchase, and "Paw Points Program" which allows redemption of points for donations to animal welfare organizations, but these are not exactly what we're looking for.</thought_1><thought_2>Let me try one final approach with a broader full-text search using just "donation" to see if there are any donation-related features in the database.</thought_2><tool_call>
    <tool_name>search_by_full_text</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>Trying a broader search with just the term "donation" to find any donation-related features</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>search_query</parameter_name>
            <parameter_value>donation*</parameter_value>
        </parameter>
    </parameters>
</tool_call>

[User]
Result from search_by_full_text tool
:
Search results for: 'donation*'
================================================================================

Node Score: 1.0000
Main Node: Feature, RewardFeature(description: Points redeemable for donations to environmental charities or sustainable products, name: Green Points Rewards Program)

Matching Properties:
  * description: Points redeemable for donations to environmental charities or sustainable products

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 0, name: EcoGreen Rewards Card, type: Rewards)
------------------------------------------------------------

Node Score: 1.0000
Main Node: Feature, RewardFeature(description: Points can be redeemed for pet services, supplies, or donations to animal welfare organizations, name: Paw Points Program)

Matching Properties:
  * description: Points can be redeemed for pet services, supplies, or donations to animal welfare organizations

Relationships:
  ← [HAS_FEATURE] ← CreditCard(annual_fee: 50, name: Pet Parent Priority Card, type: Rewards)
------------------------------------------------------------
================================================================================

[Assistant]
<thought_1>After using multiple search approaches (exact match, fuzzy search, wildcards, vector search, and broader queries), I can conclude that there does not appear to be a RewardFeature node with the exact name "Charity Donation Match" in the database.</thought_1><text_output>Based on multiple search approaches, no RewardFeature node with the exact name "Charity Donation Match" was found in the database.

The closest donation-related reward features found are:

1. Node: Feature, RewardFeature
   Name: Green Points Rewards Program
   Description: Points redeemable for donations to environmental charities or sustainable products
   Related to: EcoGreen Rewards Card (annual fee: 0, type: Rewards)

2. Node: Feature, RewardFeature
   Name: Paw Points Program
   Description: Points can be redeemed for pet services, supplies, or donations to animal welfare organizations
   Related to: Pet Parent Priority Card (annual fee: 50, type: Rewards)

No exact match for "Charity Donation Match" was found.</text_output>


[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>insert_into_graph</name>
        <description>Tool to run the final insertion query and insert the data into the graph database
Pass query as a cypher query and params as a dictionary, for the query to run on
Params are sturcured and passed as a dictionary to neo4j driver like
session.run(query,params)</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>final_query</name>
                <type>string</type>
                <description>Final Query</description>
            </property>
            <property>
                <name>params</name>
                <type>object</type>
                <description>Params</description>
            </property>
            </properties>
            <required>chain_of_thought, final_query, params</required>
        </parameters>
    </tool>

    <tool>
        <type>function</type>
        <name>contact_search_agent</name>
        <description>Tool to contact the search agent to get the relevant information from the graph database
Pass it information to fetch step by step</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>chain_of_thought</name>
                <type>string</type>
                <description>Chain Of Thought</description>
            </property>
            <property>
                <name>search_agent_query</name>
                <type>string</type>
                <description>Search Agent Query</description>
            </property>
            <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>chain_of_thought, search_agent_query, labels, properties</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>
       You are an insertion agent AI, you will be given suggestions for insertion from the orchestration agent and you will be responsible for inserting the data into the graph database.
       You will be given the context and the subquery to work on. Your job is to insert the data into the graph database for the given context.

       You will have the following tools to work with:

          1. retrive_ledger - This tool is used to get all the entities and their properties from the graph database, this will help you breaking down question into steps to contact the search agent for relevant information
          2. contact_search_agent - This tool is used to contact the search agent to get the relevant information from the graph database. Use it to search for duplicate entries. Pass in the node labels and properties and the search query to the tool. You must  call this tool to search for duplicate entries.
          3. insert_into_graph: This tool runs the final insertion query and inserts the data into the graph database. Always ensure no duplicate data is being inserted. Pass the query as a Cypher query and the parameters as a dictionary. Only use this tool AFTER you have thoroughly checked for existing similar nodes and determined that a new node MUST be created or an existing one should be updated. If an existing node is updated set the updated property to true.

        Workflow:
        1. Always start with retrieve_ledger to understand the graph schema.
        2. Then contact_search agent to search for duplicate nodes
        3. If a similar node exists:
           a.  Update the existing node with new information if appropriate.  Modify relationships as necessary. Set the update property to true
           b.  Do NOT create duplicate nodes. This is very important. No matter what you must not create duplicate nodes.
        4. If NO similar nodes exist, use insert_into_graph to create the new node and any necessary relationships.

        Notes:
         - If you have less information or are confused, relay back as failure and explain what info you need to proceed.
         - Always try to use the ledger info to structure the insertion query.
         - Ensure we have no repeating entities. Try verifying with searches with complex queries and the node labels and properties.
         - Prioritize updating existing nodes over creating new ones. Duplicate nodes are BAD.
         - The orchestration agent is giving the instructions from the user , you need to follow them as best as possible while ensuring no duplicate information is entered twice
        </user_specific_instructions>

[User]
current insertion step is :Create a CardIssuer node for 'Education Credit Union' with properties: {name: 'Education Credit Union', updated: true, last_synced: timestamp()}
                    context to work on is : Current context: Education Credit Union offers the Student Success Card, which provides benefits such as extra points for good grades, 2% rewards on textbooks and educational expenses, and free student loan consultations. The card features no annual fee and is available to enrolled students in accredited institutions. It includes a Knowledge Points rewards program that can be redeemed for student loan payments or educational supplies. Create a CardIssuer node for 'Education Credit Union' with properties: {name: 'Education Credit Union', updated: true, last_synced: timestamp()}.

[Assistant]
<thought_1>First, I need to retrieve the ledger to understand the current graph schema and check if there's already a CardIssuer node for 'Education Credit Union'.</thought_1><tool_call>
    <tool_name>retreive_ledger</tool_name>
    <parameters>
        <parameter>
            <parameter_name>chain_of_thought</parameter_name>
            <parameter_value>I need to understand the current state of the graph database to see the schema and check if 'Education Credit Union' already exists as a CardIssuer node.</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>DynamicModel4_7039b4f6</name>
        <description>Correctly extracted `DynamicModel4_7039b4f6` with all the required parameters with correct types</description>
        <parameters>
            <type>object</type>
            <properties>
            <property>
                <name>string_field</name>
                <type>string</type>
                <description>String Field</description>
            </property>
            <property>
                <name>int_field</name>
                <type>integer</type>
                <description>Int Field</description>
            </property>
            <property>
                <name>float_field</name>
                <type>number</type>
                <description>Float Field</description>
            </property>
            <property>
                <name>bool_field</name>
                <type>boolean</type>
                <description>Bool Field</description>
                <default>True</default>
            </property>
            <property>
                <name>optional_string</name>
                <type>string, null</type>
                <description>Optional String</description>
                <default>null</default>
            </property>
            <property>
                <name>string_list</name>
                <type>array</type>
                <description>String List</description>
                <items>
                    <type>string</type>
                </items>
            </property>
            <property>
                <name>nested_object</name>
                <type>object</type>
                <description>Nested_289004</description>
                <properties>
                    <property>
                        <name>name</name>
                        <type>string</type>
                        <description>Name</description>
                    </property>
                    <property>
                        <name>value</name>
                        <type>integer</type>
                        <description>Value</description>
                        <default>0</default>
                    </property>
                    <property>
                        <name>active</name>
                        <type>boolean</type>
                        <description>Active</description>
                        <default>True</default>
                    </property>
                </properties>
                <required>name</required>
            </property>
            <property>
                <name>items_list</name>
                <type>array</type>
                <description>Items List</description>
                <items>
                    <type>object</type>
                    <description>ListItem_f1c1db</description>
                    <properties>
                        <property>
                            <name>id</name>
                            <type>string</type>
                            <description>Id</description>
                        </property>
                        <property>
                            <name>quantity</name>
                            <type>integer</type>
                            <description>Quantity</description>
                            <default>1</default>
                        </property>
                    </properties>
                    <required>id</required>
                </items>
            </property>
            <property>
                <name>items_dict</name>
                <type>object</type>
                <description>Items Dict</description>
            </property>
            <property>
                <name>metadata</name>
                <type>object</type>
                <description>Metadata</description>
            </property>
            <property>
                <name>variant</name>
                <type>string, integer, boolean</type>
                <description>Variant</description>
            </property>
            <property>
                <name>complex_nested</name>
                <type>object</type>
                <description>NestedWithList_71bd14</description>
                <properties>
                    <property>
                        <name>title</name>
                        <type>string</type>
                        <description>Title</description>
                    </property>
                    <property>
                        <name>tags</name>
                        <type>array</type>
                        <description>Tags</description>
                        <items>
                            <type>string</type>
                        </items>
                    </property>
                    <property>
                        <name>entries</name>
                        <type>array</type>
                        <description>Entries</description>
                        <items>
                            <type>object</type>
                            <description>ListItem_f1c1db</description>
                            <properties>
                                <property>
                                    <name>id</name>
                                    <type>string</type>
                                    <description>Id</description>
                                </property>
                                <property>
                                    <name>quantity</name>
                                    <type>integer</type>
                                    <description>Quantity</description>
                                    <default>1</default>
                                </property>
                            </properties>
                            <required>id</required>
                        </items>
                    </property>
                </properties>
                <required>title</required>
            </property>
            </properties>
            <required>complex_nested, float_field, int_field, items_dict, items_list, metadata, nested_object, string_field, string_list, variant</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>Extract DynamicModel4_7039b4f6 information from the text.</user_specific_instructions>

[User] Here is some information about a DynamicModel4_7039b4f6: String Field: MxTyGZKN, Int Field: rUDdiGSB, Float Field: jFEtZUoL, Bool Field: rofSfYiq, Optional String: GoXkBkGM, String List: bADwnhWF, Nested Object: rAUeKTfe, Items List: lovLRccc, Items Dict: CQzDxpEm, Metadata: ihSxDnJV, Variant: xXjVAHJQ, Complex Nested: dgRAwpIZ,  You need to call tool for the json note the structure and pass valid values if input has missing info make up something but pass all values in correct type and value, reason and pass required values for sure a tool call {'type': 'function', 'function': {'name': 'DynamicModel4_7039b4f6'}} is required

[Assistant]
<thought_1>
Looking at the provided information, I need to extract details for a DynamicModel4_7039b4f6 object and format them correctly for a tool call. Let me analyze what we have:

- String Field: MxTyGZKN (string)
- Int Field: rUDdiGSB (this should be an integer, but it's given as a string)
- Float Field: jFEtZUoL (this should be a float, but it's given as a string)
- Bool Field: rofSfYiq (this should be a boolean, but it's given as a string)
- Optional String: GoXkBkGM (string)
- String List: bADwnhWF (this should be an array of strings)
- Nested Object: rAUeKTfe (this should be an object with specific structure)
- Items List: lovLRccc (this should be an array of objects)
- Items Dict: CQzDxpEm (this should be an object)
- Metadata: ihSxDnJV (this should be an object)
- Variant: xXjVAHJQ (can be string, integer or boolean)
- Complex Nested: dgRAwpIZ (this should be an object with specific structure)
</thought_1>

<thought_2>
The provided values don't match the expected types in most cases. I need to convert them to appropriate types. For some fields, I'll need to create reasonable sample data because the input doesn't give specific structured values.

Required fields according to the tool definition are:
- complex_nested
- float_field
- int_field
- items_dict
- items_list
- metadata
- nested_object
- string_field
- string_list
- variant

Let me create proper values for each field:
</thought_2>

<thought_3>
Let's structure each field correctly:

1. string_field: Can use "MxTyGZKN" as provided
2. int_field: Need to provide an integer, so I'll use 42 (since "rUDdiGSB" isn't an integer)
3. float_field: Need to provide a float, so I'll use 3.14 (since "jFEtZUoL" isn't a float)
4. bool_field: Need a boolean, so I'll use true (default was True)
5. optional_string: Can use "GoXkBkGM" as provided
6. string_list: Need array of strings, so I'll create ["bADwnhWF", "sample1", "sample2"]
7. nested_object: Needs to be an object with name (required), value, and active fields
   - Will create: {"name": "rAUeKTfe", "value": 10, "active": true}
8. items_list: Array of objects with id (required) and quantity
   - Will create: [{"id": "lovLRccc", "quantity": 3}, {"id": "item2", "quantity": 5}]
9. items_dict: Object - will create: {"key1": "CQzDxpEm", "key2": "value2"}
10. metadata: Object - will create: {"source": "ihSxDnJV", "timestamp": "2023-01-01"}
11. variant: Will use as string: "xXjVAHJQ"
12. complex_nested: Object with title (required), tags, and entries
    - Will create: {
        "title": "dgRAwpIZ",
        "tags": ["tag1", "tag2"],
        "entries": [{"id": "entry1", "quantity": 2}, {"id": "entry2", "quantity": 3}]
      }
</thought_3>

<tool_call>
    <tool_name>DynamicModel4_7039b4f6</tool_name>
    <parameters>
        <parameter>
            <parameter_name>string_field</parameter_name>
            <parameter_value>MxTyGZKN</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>int_field</parameter_name>
            <parameter_value>42</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>float_field</parameter_name>
            <parameter_value>3.14</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>bool_field</parameter_name>
            <parameter_value>true</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>optional_string</parameter_name>
            <parameter_value>GoXkBkGM</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>string_list</parameter_name>
            <parameter_value>["bADwnhWF", "sample1", "sample2"]</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>nested_object</parameter_name>
            <parameter_value>{"name": "rAUeKTfe", "value": 10, "active": true}</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>items_list</parameter_name>
            <parameter_value>[{"id": "lovLRccc", "quantity": 3}, {"id": "item2", "quantity": 5}]</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>items_dict</parameter_name>
            <parameter_value>{"key1": "CQzDxpEm", "key2": "value2"}</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>metadata</parameter_name>
            <parameter_value>{"source": "ihSxDnJV", "timestamp": "2023-01-01"}</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>variant</parameter_name>
            <parameter_value>xXjVAHJQ</parameter_value>
        </parameter>
        <parameter>
            <parameter_name>complex_nested</parameter_name>
            <parameter_value>{"title": "dgRAwpIZ", "tags": ["tag1", "tag2"], "entries": [{"id": "entry1", "quantity": 2}, {"id": "entry2", "quantity": 3}]}</parameter_value>
        </parameter>
    </parameters>
</tool_call>