### Initialize and Start the Application

Source: https://github.com/deepgram-starters/go-text-intelligence/blob/main/AGENTS.md

Commands to clone submodules, install dependencies, and launch the backend and frontend servers.

```bash
# Initialize (clone submodules + install deps)
make init

# Set up environment
test -f .env || cp sample.env .env  # then set DEEPGRAM_API_KEY

# Start both servers
make start
# Backend: http://localhost:8081
# Frontend: http://localhost:8080
```

--------------------------------

### Install Dependencies

Source: https://github.com/deepgram-starters/go-text-intelligence/blob/main/AGENTS.md

Commands to install backend Go modules and frontend Node.js dependencies.

```bash
go mod download
cd frontend && corepack pnpm install
```

--------------------------------

### Manage Application Lifecycle

Source: https://github.com/deepgram-starters/go-text-intelligence/blob/main/AGENTS.md

Commands for starting, stopping, and rebuilding the application environment.

```bash
make start
```

```bash
# Terminal 1 — Backend
go run .

# Terminal 2 — Frontend
cd frontend && corepack pnpm run dev -- --port 8080 --no-open
```

```bash
lsof -ti:8080,8081 | xargs kill -9 2>/dev/null
```

```bash
rm -rf frontend/node_modules frontend/.vite
make init
```

--------------------------------

### Initialize and run the Go application

Source: https://github.com/deepgram-starters/go-text-intelligence/blob/main/README.md

Use the Makefile to set up the environment and start the local server. Ensure the DEEPGRAM_API_KEY is configured in the .env file.

```bash
make init
cp sample.env .env  # Add your DEEPGRAM_API_KEY
make start
```

--------------------------------

### Project Initialization and Development Commands

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Use these Makefile commands to manage project dependencies, start servers, and run tests.

```bash
# Check prerequisites (git, go, pnpm)
make check-prereqs

# Initialize project (clone submodules + install dependencies)
make init

# Start both backend and frontend servers
make start
# Backend: http://localhost:8081
# Frontend: http://localhost:8080

# Start servers separately
make start-backend   # Go server on port 8081
make start-frontend  # Vite dev server on port 8080

# Run conformance tests
make test

# Update frontend submodule to latest
make update

# Clean build artifacts
make clean

# Check repository and submodule status
make status
```

--------------------------------

### Conventional Commit Examples

Source: https://github.com/deepgram-starters/go-text-intelligence/blob/main/AGENTS.md

Standardized commit message formats for project version control.

```text
feat(go-text-intelligence): add diarization support
fix(go-text-intelligence): resolve WebSocket close handling
refactor(go-text-intelligence): simplify session endpoint
chore(deps): update frontend submodule
```

--------------------------------

### Get Application Metadata

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Retrieves application metadata, including use case and framework information, from the configuration file.

```bash
# Get metadata
curl -X GET http://localhost:8081/api/metadata

# Response:
# {
#   "title": "Go Text Intelligence",
#   "description": "Get started using Deepgram's Text Intelligence with this Go demo app",
#   "author": "Deepgram DX Team <devrel@deepgram.com> (https://developers.deepgram.com)",
#   "repository": "https://github.com/deepgram-starters/go-text-intelligence",
# }
```

--------------------------------

### Get Application Metadata

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Returns application metadata from the `deepgram.toml` configuration file including use case, framework, and tags.

```APIDOC
## Get Application Metadata

### Description
Returns application metadata from the `deepgram.toml` configuration file including use case, framework, and tags.

### Method
GET

### Endpoint
/api/metadata

### Request Example
```bash
curl -X GET http://localhost:8081/api/metadata
```

### Response
#### Success Response (200)
- **title** (string) - The title of the application.
- **description** (string) - A description of the application.
- **author** (string) - The author of the application.
- **repository** (string) - The URL of the application's repository.

#### Response Example
```json
{
  "title": "Go Text Intelligence",
  "description": "Get started using Deepgram's Text Intelligence with this Go demo app",
  "author": "Deepgram DX Team <devrel@deepgram.com> (https://developers.deepgram.com)",
  "repository": "https://github.com/deepgram-starters/go-text-intelligence"
}
```
```

--------------------------------

### Get Session Token

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Retrieves a signed HS256 JWT session token valid for one hour, required for subsequent API requests.

```bash
# Get a session token
curl -X GET http://localhost:8081/api/session

# Response:
# {"token":"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."}

# Store token for use in subsequent requests
TOKEN=$(curl -s http://localhost:8081/api/session | jq -r '.token')
echo "Session token: $TOKEN"
```

--------------------------------

### Get Session Token

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Issues a signed JWT session token required for authenticating subsequent API requests. Tokens expire after 1 hour and use HS256 signing.

```APIDOC
## Get Session Token

### Description
Issues a signed JWT session token required for authenticating subsequent API requests. Tokens expire after 1 hour and use HS256 signing.

### Method
GET

### Endpoint
/api/session

### Request Example
```bash
curl -X GET http://localhost:8081/api/session
```

### Response
#### Success Response (200)
- **token** (string) - The JWT session token.

#### Response Example
```json
{
  "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
}
```
```

--------------------------------

### Environment Configuration

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Configure the server by copying the sample template and setting required environment variables.

```bash
# sample.env - Copy to .env and configure
DEEPGRAM_API_KEY=your_api_key_here  # Required - get from https://console.deepgram.com
PORT=8081                            # Optional - backend server port
HOST=0.0.0.0                         # Optional - server bind address
SESSION_SECRET=your_secret_here      # Optional - JWT signing secret for production

# Quick setup
cp sample.env .env
# Edit .env to add your DEEPGRAM_API_KEY
```

--------------------------------

### Project Testing Commands

Source: https://github.com/deepgram-starters/go-text-intelligence/blob/main/AGENTS.md

Commands for running automated conformance tests and verifying API endpoints manually.

```bash
# Run conformance tests (requires app to be running)
make test

# Manual endpoint check
curl -sf http://localhost:8081/api/metadata | python3 -m json.tool
curl -sf http://localhost:8081/api/session | python3 -m json.tool
```

--------------------------------

### Analyze Text from URL

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Fetches and analyzes text content from a provided URL. This field is mutually exclusive with the text field.

```bash
# Analyze content from a URL
curl -X POST "http://localhost:8081/api/text-intelligence?summarize=true&topics=true&language=en" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://example.com/article.txt"
  }'

# Error response for invalid URL:
# {
#   "error": {
#     "type": "validation_error",
#     "code": "INVALID_URL",
#     "message": "Failed to fetch URL: connection refused",
#     "details": {}
#   }
# }
```

--------------------------------

### Health Check Endpoint

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Use this endpoint to verify service availability for monitoring and orchestration.

```bash
# Health check
curl -X GET http://localhost:8081/health

# Response:
# {"status":"ok","service":"text-intelligence"}
```

--------------------------------

### API Error Response Format

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Reference for the standardized error response structure returned by the API.

```bash
# Missing authentication
curl -X POST "http://localhost:8081/api/text-intelligence" \
  -H "Content-Type: application/json" \
  -d '{"text": "Hello"}'

# Response (401):
# {
#   "error": {
#     "type": "AuthenticationError",
#     "code": "MISSING_TOKEN",
#     "message": "Authorization header with Bearer token is required"
#   }
# }

# Invalid/expired token response (401):
# {
#   "error": {
#     "type": "AuthenticationError",
#     "code": "INVALID_TOKEN",
#     "message": "Session expired, please refresh the page"
#   }
# }

# Missing text/url field (400):
# {
#   "error": {
#     "type": "validation_error",
#     "code": "INVALID_TEXT",
#     "message": "Request must contain either 'text' or 'url' field",
#     "details": {}
#   }
# }

# Both text and url provided (400):
# {
#   "error": {
#     "type": "validation_error",
#     "code": "INVALID_TEXT",
#     "message": "Request must contain either 'text' or 'url', not both",
#     "details": {}
#   }
# }
```

--------------------------------

### Selective Feature Analysis

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Enables specific analysis features independently via query parameters and supports language specification.

```bash
# Summarization only (v2)
curl -X POST "http://localhost:8081/api/text-intelligence?summarize=v2" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"text": "Your long text content here for summarization..."}'

# Sentiment analysis only
curl -X POST "http://localhost:8081/api/text-intelligence?sentiment=true" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"text": "This product exceeded my expectations. Highly satisfied!"}'

# Topics and intents detection
curl -X POST "http://localhost:8081/api/text-intelligence?topics=true&intents=true" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"text": "I want to book a flight to Paris next week for a business meeting."}'

# Specify language (default: en)
curl -X POST "http://localhost:8081/api/text-intelligence?summarize=true&language=es" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"text": "Tu texto en español aquí..."}'
```

--------------------------------

### Analyze Text with Text Intelligence

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Performs comprehensive text analysis including summarization, topics, sentiment, and intent detection using the Read API.

```bash
# Basic text analysis with all features enabled
curl -X POST "http://localhost:8081/api/text-intelligence?summarize=true&topics=true&sentiment=true&intents=true" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "I absolutely love this new phone! The camera quality is amazing and the battery lasts all day. The only downside is the price, but I think it is worth every penny. I would definitely recommend this to anyone looking for a premium smartphone experience."
  }'

# Response structure:
# {
#   "results": {
#     "summary": {
#       "text": "The reviewer loves their new phone, praising the camera and battery life..."
#     },
#     "topics": {
#       "segments": [{"topics": [{"topic": "smartphone", "confidence_score": 0.95}]}]
#     },
#     "sentiments": {
#       "average": {"sentiment": "positive", "sentiment_score": 0.87},
#       "segments": [...]
#     },
#     "intents": {
#       "segments": [{"intents": [{"intent": "recommend", "confidence_score": 0.92}]}]
#     }
#   }
# }
```

--------------------------------

### Analyze Text with Text Intelligence

Source: https://context7.com/deepgram-starters/go-text-intelligence/llms.txt

Analyzes text content using Deepgram's Read API. Supports summarization, topic detection, sentiment analysis, and intent detection via query parameters. Requires JWT authentication.

```APIDOC
## Analyze Text with Text Intelligence

### Description
Analyzes text content using Deepgram's Read API. Supports summarization, topic detection, sentiment analysis, and intent detection via query parameters. Requires JWT authentication.

### Method
POST

### Endpoint
/api/text-intelligence

### Query Parameters
- **summarize** (boolean or string) - Required/Optional - Enable summarization. Can be `true` or `v2` for specific version.
- **topics** (boolean) - Required/Optional - Enable topic detection.
- **sentiment** (boolean) - Required/Optional - Enable sentiment analysis.
- **intents** (boolean) - Required/Optional - Enable intent detection.
- **language** (string) - Optional - Specify the language of the text (default: 'en').

### Request Body
- **text** (string) - Required - The text content to analyze. Mutually exclusive with `url`.
- **url** (string) - Required - The URL of the content to analyze. Mutually exclusive with `text`.

### Request Example
```json
{
  "text": "I absolutely love this new phone! The camera quality is amazing and the battery lasts all day. The only downside is the price, but I think it is worth every penny. I would definitely recommend this to anyone looking for a premium smartphone experience."
}
```

### Response
#### Success Response (200)
- **results** (object) - Contains the analysis results.
  - **summary** (object) - Summary of the text.
    - **text** (string) - The summarized text.
  - **topics** (object) - Detected topics.
    - **segments** (array) - Array of topic segments.
      - **topics** (array) - Array of detected topics within a segment.
        - **topic** (string) - The detected topic.
        - **confidence_score** (number) - The confidence score for the topic.
  - **sentiments** (object) - Sentiment analysis results.
    - **average** (object) - Overall sentiment.
      - **sentiment** (string) - The overall sentiment (e.g., 'positive', 'negative', 'neutral').
      - **sentiment_score** (number) - The sentiment score.
    - **segments** (array) - Sentiment analysis for text segments.
  - **intents** (object) - Detected intents.
    - **segments** (array) - Array of intent segments.
      - **intents** (array) - Array of detected intents within a segment.
        - **intent** (string) - The detected intent.
        - **confidence_score** (number) - The confidence score for the intent.

#### Response Example
```json
{
  "results": {
    "summary": {
      "text": "The reviewer loves their new phone, praising the camera and battery life..."
    },
    "topics": {
      "segments": [{"topics": [{"topic": "smartphone", "confidence_score": 0.95}]}]
    },
    "sentiments": {
      "average": {"sentiment": "positive", "sentiment_score": 0.87},
      "segments": [...] 
    },
    "intents": {
      "segments": [{"intents": [{"intent": "recommend", "confidence_score": 0.92}]}]
    }
  }
}
```

#### Error Response (4xx/5xx)
- **error** (object) - Contains error details.
  - **type** (string) - The type of error.
  - **code** (string) - The error code.
  - **message** (string) - A description of the error.
  - **details** (object) - Additional error details.

#### Error Response Example
```json
{
  "error": {
    "type": "validation_error",
    "code": "INVALID_URL",
    "message": "Failed to fetch URL: connection refused",
    "details": {}
  }
}
```
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.