Documentation Index
Fetch the complete documentation index at: https://docs.pinkfish.ai/llms.txt
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Server path: /gemini | Type: Application | PCID required: Yes
| Tool | Description |
|---|
gemini_generate_content | Generate content using Google Gemini models |
gemini_chat | Have a conversation using Gemini models |
gemini_analyze_image | Analyze an image using Gemini vision capabilities |
gemini_embed_content | Create embeddings for text using Gemini models |
gemini_list_models | List available Gemini models |
gemini_count_tokens | Count tokens in text for Gemini models |
gemini_generate_code | Generate code using Gemini models optimized for programming |
gemini_summarize_text | Summarize long text using Gemini models |
gemini_generate_content
Generate content using Google Gemini models
Parameters:
| Parameter | Type | Required | Default | Description |
|---|
model | string | No | "gemini-2.5-flash" | Gemini model to use |
prompt | string | Yes | — | Text prompt for content generation |
temperature | number | No | — | Sampling temperature |
topP | number | No | — | Nucleus sampling parameter |
topK | number | No | — | Top-k sampling parameter |
maxOutputTokens | number | No | — | Maximum tokens to generate |
stopSequences | string[] | No | — | Stop sequences to end generation |
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
},
"model": {
"type": "string",
"default": "gemini-2.5-flash",
"description": "Gemini model to use"
},
"prompt": {
"type": "string",
"description": "Text prompt for content generation"
},
"temperature": {
"type": "number",
"description": "Sampling temperature"
},
"topP": {
"type": "number",
"description": "Nucleus sampling parameter"
},
"topK": {
"type": "number",
"description": "Top-k sampling parameter"
},
"maxOutputTokens": {
"type": "number",
"description": "Maximum tokens to generate"
},
"stopSequences": {
"type": "array",
"items": {
"type": "string"
},
"description": "Stop sequences to end generation"
}
},
"required": [
"PCID",
"prompt"
]
}
gemini_chat
Have a conversation using Gemini models
Parameters:
| Parameter | Type | Required | Default | Description |
|---|
model | string | No | "gemini-2.5-flash" | Gemini model to use |
messages | object[] | Yes | — | Conversation history |
temperature | number | No | — | Sampling temperature |
maxOutputTokens | number | No | — | Maximum tokens to generate |
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
},
"model": {
"type": "string",
"default": "gemini-2.5-flash",
"description": "Gemini model to use"
},
"messages": {
"type": "array",
"items": {
"type": "object",
"properties": {
"role": {
"type": "string",
"enum": [
"user",
"model"
],
"description": "Message role"
},
"parts": {
"type": "array",
"items": {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "Message text content"
}
}
},
"description": "Message parts"
}
}
},
"description": "Conversation history"
},
"temperature": {
"type": "number",
"description": "Sampling temperature"
},
"maxOutputTokens": {
"type": "number",
"description": "Maximum tokens to generate"
}
},
"required": [
"PCID",
"messages"
]
}
gemini_analyze_image
Analyze an image using Gemini vision capabilities
Parameters:
| Parameter | Type | Required | Default | Description |
|---|
model | string | No | "gemini-2.5-flash" | Gemini model with vision capabilities |
imageUrl | string | No | — | URL of image to analyze |
imageBase64 | string | No | — | Base64 encoded image data |
prompt | string | Yes | — | Question or instruction about the image |
temperature | number | No | — | Sampling temperature |
maxOutputTokens | number | No | — | Maximum tokens to generate |
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
},
"model": {
"type": "string",
"default": "gemini-2.5-flash",
"description": "Gemini model with vision capabilities"
},
"imageUrl": {
"type": "string",
"description": "URL of image to analyze"
},
"imageBase64": {
"type": "string",
"description": "Base64 encoded image data"
},
"prompt": {
"type": "string",
"description": "Question or instruction about the image"
},
"temperature": {
"type": "number",
"description": "Sampling temperature"
},
"maxOutputTokens": {
"type": "number",
"description": "Maximum tokens to generate"
}
},
"required": [
"PCID",
"prompt"
]
}
gemini_embed_content
Create embeddings for text using Gemini models
Parameters:
| Parameter | Type | Required | Default | Description |
|---|
model | string | No | "text-embedding-004" | Gemini embedding model |
content | string | Yes | — | Text content to embed |
taskType | string | No | — | Task type for embedding optimization |
title | string | No | — | Optional title for the content |
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
},
"model": {
"type": "string",
"default": "text-embedding-004",
"description": "Gemini embedding model"
},
"content": {
"type": "string",
"description": "Text content to embed"
},
"taskType": {
"type": "string",
"enum": [
"RETRIEVAL_QUERY",
"RETRIEVAL_DOCUMENT",
"SEMANTIC_SIMILARITY",
"CLASSIFICATION",
"CLUSTERING"
],
"description": "Task type for embedding optimization"
},
"title": {
"type": "string",
"description": "Optional title for the content"
}
},
"required": [
"PCID",
"content"
]
}
gemini_list_models
List available Gemini models
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
}
},
"required": [
"PCID"
]
}
gemini_count_tokens
Count tokens in text for Gemini models
Parameters:
| Parameter | Type | Required | Default | Description |
|---|
model | string | No | "gemini-2.5-flash" | Gemini model for token counting |
text | string | Yes | — | Text to count tokens for |
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
},
"model": {
"type": "string",
"default": "gemini-2.5-flash",
"description": "Gemini model for token counting"
},
"text": {
"type": "string",
"description": "Text to count tokens for"
}
},
"required": [
"PCID",
"text"
]
}
gemini_generate_code
Generate code using Gemini models optimized for programming
Parameters:
| Parameter | Type | Required | Default | Description |
|---|
model | string | No | "gemini-2.5-flash" | Gemini model to use |
prompt | string | Yes | — | Code generation prompt |
language | string | No | — | Programming language (e.g., “python”, “javascript”) |
temperature | number | No | — | Low temperature for more deterministic code |
maxOutputTokens | number | No | — | Maximum tokens to generate |
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
},
"model": {
"type": "string",
"default": "gemini-2.5-flash",
"description": "Gemini model to use"
},
"prompt": {
"type": "string",
"description": "Code generation prompt"
},
"language": {
"type": "string",
"description": "Programming language (e.g., \"python\", \"javascript\")"
},
"temperature": {
"type": "number",
"default": 0.1,
"description": "Low temperature for more deterministic code"
},
"maxOutputTokens": {
"type": "number",
"description": "Maximum tokens to generate"
}
},
"required": [
"PCID",
"prompt"
]
}
gemini_summarize_text
Summarize long text using Gemini models
Parameters:
| Parameter | Type | Required | Default | Description |
|---|
model | string | No | "gemini-2.5-flash" | Gemini model to use |
text | string | Yes | — | Text to summarize |
summaryLength | string | No | "medium" | Desired summary length |
focusAreas | string[] | No | — | Specific areas to focus on in summary |
{
"type": "object",
"properties": {
"PCID": {
"type": "string",
"description": "Pink Connect ID"
},
"model": {
"type": "string",
"default": "gemini-2.5-flash",
"description": "Gemini model to use"
},
"text": {
"type": "string",
"description": "Text to summarize"
},
"summaryLength": {
"type": "string",
"enum": [
"short",
"medium",
"long"
],
"default": "medium",
"description": "Desired summary length"
},
"focusAreas": {
"type": "array",
"items": {
"type": "string"
},
"description": "Specific areas to focus on in summary"
}
},
"required": [
"PCID",
"text"
]
}