## Chat Completions

`aisearch.instances.chat_completions(strid, InstanceChatCompletionsParams**kwargs)  -> InstanceChatCompletionsResponse`

**post** `/accounts/{account_id}/ai-search/instances/{id}/chat/completions`

Performs a chat completion request against an AI Search instance, using indexed content as context for generating responses.

### Parameters

- `account_id: str`

- `id: str`

  AI Search instance ID. Lowercase alphanumeric, hyphens, and underscores.

- `messages: Iterable[Message]`

  - `content: Optional[str]`

  - `role: Literal["system", "developer", "user", 2 more]`

    - `"system"`

    - `"developer"`

    - `"user"`

    - `"assistant"`

    - `"tool"`

- `aisearch_options: Optional[AISearchOptions]`

  - `cache: Optional[AISearchOptionsCache]`

    - `cache_threshold: Optional[Literal["super_strict_match", "close_enough", "flexible_friend", "anything_goes"]]`

      - `"super_strict_match"`

      - `"close_enough"`

      - `"flexible_friend"`

      - `"anything_goes"`

    - `enabled: Optional[bool]`

  - `query_rewrite: Optional[AISearchOptionsQueryRewrite]`

    - `enabled: Optional[bool]`

    - `model: Optional[Literal["@cf/meta/llama-3.3-70b-instruct-fp8-fast", "@cf/zai-org/glm-4.7-flash", "@cf/meta/llama-3.1-8b-instruct-fast", 25 more]]`

      - `"@cf/meta/llama-3.3-70b-instruct-fp8-fast"`

      - `"@cf/zai-org/glm-4.7-flash"`

      - `"@cf/meta/llama-3.1-8b-instruct-fast"`

      - `"@cf/meta/llama-3.1-8b-instruct-fp8"`

      - `"@cf/meta/llama-4-scout-17b-16e-instruct"`

      - `"@cf/qwen/qwen3-30b-a3b-fp8"`

      - `"@cf/deepseek-ai/deepseek-r1-distill-qwen-32b"`

      - `"@cf/moonshotai/kimi-k2-instruct"`

      - `"@cf/google/gemma-3-12b-it"`

      - `"anthropic/claude-3-7-sonnet"`

      - `"anthropic/claude-sonnet-4"`

      - `"anthropic/claude-opus-4"`

      - `"anthropic/claude-3-5-haiku"`

      - `"cerebras/qwen-3-235b-a22b-instruct"`

      - `"cerebras/qwen-3-235b-a22b-thinking"`

      - `"cerebras/llama-3.3-70b"`

      - `"cerebras/llama-4-maverick-17b-128e-instruct"`

      - `"cerebras/llama-4-scout-17b-16e-instruct"`

      - `"cerebras/gpt-oss-120b"`

      - `"google-ai-studio/gemini-2.5-flash"`

      - `"google-ai-studio/gemini-2.5-pro"`

      - `"grok/grok-4"`

      - `"groq/llama-3.3-70b-versatile"`

      - `"groq/llama-3.1-8b-instant"`

      - `"openai/gpt-5"`

      - `"openai/gpt-5-mini"`

      - `"openai/gpt-5-nano"`

      - `""`

    - `rewrite_prompt: Optional[str]`

  - `reranking: Optional[AISearchOptionsReranking]`

    - `enabled: Optional[bool]`

    - `match_threshold: Optional[float]`

    - `model: Optional[Literal["@cf/baai/bge-reranker-base", ""]]`

      - `"@cf/baai/bge-reranker-base"`

      - `""`

  - `retrieval: Optional[AISearchOptionsRetrieval]`

    - `boost_by: Optional[Iterable[AISearchOptionsRetrievalBoostBy]]`

      Metadata fields to boost search results by. Overrides the instance-level boost_by config. Direction defaults to 'asc' for numeric/datetime fields, 'exists' for text/boolean fields. Fields must match 'timestamp' or a defined custom_metadata field.

      - `field: str`

        Metadata field name to boost by. Use 'timestamp' for document freshness, or any custom_metadata field. Numeric and datetime fields support asc/desc directions; text/boolean fields support exists/not_exists.

      - `direction: Optional[Literal["asc", "desc", "exists", "not_exists"]]`

        Boost direction. 'desc' = higher values rank higher (e.g. newer timestamps). 'asc' = lower values rank higher. 'exists' = boost chunks that have the field. 'not_exists' = boost chunks that lack the field. Optional ��� defaults to 'asc' for numeric/datetime fields, 'exists' for text/boolean fields.

        - `"asc"`

        - `"desc"`

        - `"exists"`

        - `"not_exists"`

    - `context_expansion: Optional[int]`

    - `filters: Optional[Dict[str, object]]`

    - `fusion_method: Optional[Literal["max", "rrf"]]`

      - `"max"`

      - `"rrf"`

    - `keyword_match_mode: Optional[Literal["and", "or"]]`

      Controls which documents are candidates for BM25 scoring. 'and' restricts candidates to documents containing all query terms; 'or' includes any document containing at least one term, ranked by BM25 relevance. Defaults to 'and'. Legacy values 'exact_match' and 'fuzzy_match' are accepted and map to 'and' and 'or' respectively.

      - `"and"`

      - `"or"`

    - `match_threshold: Optional[float]`

    - `max_num_results: Optional[int]`

    - `retrieval_type: Optional[Literal["vector", "keyword", "hybrid"]]`

      - `"vector"`

      - `"keyword"`

      - `"hybrid"`

    - `return_on_failure: Optional[bool]`

- `model: Optional[Literal["@cf/meta/llama-3.3-70b-instruct-fp8-fast", "@cf/zai-org/glm-4.7-flash", "@cf/meta/llama-3.1-8b-instruct-fast", 25 more]]`

  - `"@cf/meta/llama-3.3-70b-instruct-fp8-fast"`

  - `"@cf/zai-org/glm-4.7-flash"`

  - `"@cf/meta/llama-3.1-8b-instruct-fast"`

  - `"@cf/meta/llama-3.1-8b-instruct-fp8"`

  - `"@cf/meta/llama-4-scout-17b-16e-instruct"`

  - `"@cf/qwen/qwen3-30b-a3b-fp8"`

  - `"@cf/deepseek-ai/deepseek-r1-distill-qwen-32b"`

  - `"@cf/moonshotai/kimi-k2-instruct"`

  - `"@cf/google/gemma-3-12b-it"`

  - `"anthropic/claude-3-7-sonnet"`

  - `"anthropic/claude-sonnet-4"`

  - `"anthropic/claude-opus-4"`

  - `"anthropic/claude-3-5-haiku"`

  - `"cerebras/qwen-3-235b-a22b-instruct"`

  - `"cerebras/qwen-3-235b-a22b-thinking"`

  - `"cerebras/llama-3.3-70b"`

  - `"cerebras/llama-4-maverick-17b-128e-instruct"`

  - `"cerebras/llama-4-scout-17b-16e-instruct"`

  - `"cerebras/gpt-oss-120b"`

  - `"google-ai-studio/gemini-2.5-flash"`

  - `"google-ai-studio/gemini-2.5-pro"`

  - `"grok/grok-4"`

  - `"groq/llama-3.3-70b-versatile"`

  - `"groq/llama-3.1-8b-instant"`

  - `"openai/gpt-5"`

  - `"openai/gpt-5-mini"`

  - `"openai/gpt-5-nano"`

  - `""`

- `stream: Optional[bool]`

### Returns

- `class InstanceChatCompletionsResponse: …`

  - `choices: List[Choice]`

    - `message: ChoiceMessage`

      - `content: Optional[str]`

      - `role: Literal["system", "developer", "user", 2 more]`

        - `"system"`

        - `"developer"`

        - `"user"`

        - `"assistant"`

        - `"tool"`

    - `index: Optional[int]`

  - `chunks: List[Chunk]`

    - `id: str`

    - `score: float`

    - `text: str`

    - `type: str`

    - `item: Optional[ChunkItem]`

      - `key: str`

      - `metadata: Optional[Dict[str, object]]`

      - `timestamp: Optional[float]`

    - `scoring_details: Optional[ChunkScoringDetails]`

      - `fusion_method: Optional[Literal["rrf", "max"]]`

        - `"rrf"`

        - `"max"`

      - `keyword_rank: Optional[float]`

      - `keyword_score: Optional[float]`

      - `reranking_score: Optional[float]`

      - `vector_rank: Optional[float]`

      - `vector_score: Optional[float]`

  - `id: Optional[str]`

  - `model: Optional[str]`

  - `object: Optional[str]`

### Example

```python
import os
from cloudflare import Cloudflare

client = Cloudflare(
    api_token=os.environ.get("CLOUDFLARE_API_TOKEN"),  # This is the default and can be omitted
)
response = client.aisearch.instances.chat_completions(
    id="my-ai-search",
    account_id="c3dc5f0b34a14ff8e1b3ec04895e1b22",
    messages=[{
        "content": "content",
        "role": "system",
    }],
)
print(response.id)
```

#### Response

```json
{
  "choices": [
    {
      "message": {
        "content": "content",
        "role": "system"
      },
      "index": 0
    }
  ],
  "chunks": [
    {
      "id": "id",
      "score": 0,
      "text": "text",
      "type": "type",
      "item": {
        "key": "key",
        "metadata": {
          "foo": "bar"
        },
        "timestamp": 0
      },
      "scoring_details": {
        "fusion_method": "rrf",
        "keyword_rank": 0,
        "keyword_score": 0,
        "reranking_score": 0,
        "vector_rank": 0,
        "vector_score": 0
      }
    }
  ],
  "id": "id",
  "model": "model",
  "object": "object"
}
```