GeminiAI Chat with History

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Configuring and publishing the processes

Open the

Read History from File

process.

On the

Start

tab of the

Start

step, select the same Secure Agent that you had selected in the

Run On

field for the

FileConnectionChatHistorydefault

connection.

Save and publish the process.

Open the

Write Chat History in File

process.

Optionally, in the

Prepare History to save in File

step, click the

Assignments

tab. Open the Expression Editor for the

File_Name

field and enter the format to save the file.

The following image shows the assignments of the

File_Name

input field:

Save and publish the process.

Open the

Chat with History

main process.

The process is called by an HTTP request using the following three input parameters mentioned in the

Input Fields

tab of the

Start

step:

User_Prompt

Path_To_File_With_History

User_ID

The User_ID is used as the file name.

On the

Temp Field

tab of the

Start

step, the

Model_LLM

is set to

gemini-1.5 pro

. You can optionally edit the model version. For information about changing the model version, see the Gemini documentation.

In the

Configure Request Parameters

step, click the

Assignments

tab. Open the Expression Editor for the

Prompt_Configuration

field and enter the prompt instructions, as shown in the following sample code:


<generationConfig>
      <stopSequences>.</stopSequences>
      <candidateCount>1</candidateCount>
      <maxOutputTokens>200</maxOutputTokens>
      <temperature>0.5</temperature>
      <topP>0.1</topP>
      <topK>2</topK>
</generationConfig>

For the

Prompt_Configuration

field, enter values for the following properties:

Property	Description
stopSequences	Contains sequences of characters or strings that stop the model's output. This property controls where the model must end its response.
candidateCount	Specifies the number of response candidates that the model must generate. For example, if the value is set to 1, the model generates one response. If set to a higher number, the model generates that many alternative responses for the same input.
maxOutputTokens	Defines the maximum number of tokens the model can generate in its response. Setting a limit ensures that the response is concise and fits within the desired length constraints.
temperature	Controls the randomness of the model's output. A lower value makes the output more deterministic, while a higher value increases randomness and creativity. For example, a temperature of 0.5 balances between deterministic and creative outputs.
topP	Determines the cumulative probability threshold for token selection. The model considers the smallest set of tokens whose cumulative probability meets or exceeds topP. For example, if topP is set to 0.1, the model considers only the top 10% most probable tokens at each step.
topK	Limits the number of the highest-probability tokens to consider during response generation. For example, if topK is set to 2, the model considers only the top 2 tokens at each step, controlling output diversity and quality.

After configuring the prompt instructions, the process reads the file and if it has a history, you must prepare a request with history. The process reads the entire history from the file, but uses only the last question and its response.

The following image shows the assignments of the

Previous_Question

and

Previous_Answer

input fields:

The process reads the file with history. If no file exists or the file is empty, the process prepares a request without history, and then creates or updates the file. It writes the last question and its LLM response in the following format:


Qustion_to_LLM: user question 
Answer_LLM: Gemini answer

If the file contains history, the process prepares the request with history but using only the last question and response. The process then updates the file and appends the new question and answer. You can include additional parsing in a specific location and also include new changes to the request.

Save and publish the process.

Using the GeminiAI Chat with History recipe

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