Source: https://ailoot.ai/models/en/kat-coder-pro-v1/ Canonical: https://ailoot.ai/models/en/kat-coder-pro-v1/ Language: en # kat-coder-pro-v1 [Markdown](https://ailoot.ai/models/en/kat-coder-pro-v1/index.md) · [JSON](https://ailoot.ai/models/en/kat-coder-pro-v1/facts.json) ## [kat-coder-pro-v1](https://ailoot.ai/models/en/kat-coder-pro-v1/) KAT-Coder is Kuaishou’s coding-model family for repository-aware development tasks. Its maker workflow combines tool-assisted inspection, patch generation, execution-based review and reflection, producing code or explanations tied to the actual project behavior. - [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/kat-coder-pro-v1/#method-0) - [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/kat-coder-pro-v1/#method-1) About the model This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below. KAT-Coder is Kuaishou’s coding-model family for software-engineering tasks in a tool-enabled environment. The maker’s original release focuses on following a development request through repository inspection, patch creation and review. Its training covers feature implementation and enhancement, bug fixing, refactoring, performance work, test creation, code understanding and configuration-related tasks. The useful artifacts are code and text connected to the actual project behavior. #### Provide the issue and the relevant project context State the behavior to achieve, the current implementation and the conditions that define completion. Include the source files or passages needed to understand the problem and the commands or observations already available from the environment. An original bug-fix brief can identify the input that fails, the expected result and the function whose behavior differs. A feature request can name the user-visible outcome and the interfaces that must remain consistent. The producer’s agentic training uses issue descriptions, branch code, executable environments and verifiable task conditions. Keep those parts aligned in an application-assisted task. A model’s proposal should address the actual checkout and evidence supplied, while the application performs file or execution operations and returns the results. Retain the result of each consequential operation with the continuation. #### Tools and multi-turn development The maker documents instruction following, tool use and extended interaction as central parts of the family’s development. The released coding-agent recipe provides file-reading and editing operations and a completion action. The model can inspect information, request a change and continue from the returned observation. Its role is choosing and describing the next step; the surrounding environment establishes what actually happened. The original release also describes parallel tool requests as an observed capability after agentic training. Use independent operations only when their results can be kept associated with the right request. A repository explanation can combine information from several files, while a patch needs the current contents and behavior of the affected code. Do not substitute a plausible environment result for a missing observation. #### Review candidate changes deliberately The producer’s published agent recipe separates patch generation, filtering, selection and reflection. Filtering combines semantic deduplication with execution-based checks; selection evaluates the remaining candidates; reflection uses the earlier results to guide a later round. Those stages belong to the documented coding workflow rather than being an automatic guarantee attached to every plain text response. For a practical code task, keep the proposed patch, the checks actually run and their outcomes together. A comparison of candidate fixes should explain the condition that distinguishes them, especially when each appears plausible from the diff alone. A failed check can give the next turn a specific issue to address instead of prompting an unrelated rewrite. #### Family and edition distinctions The original maker release distinguishes KAT-Coder from the separate open KAT-Dev-32B model. Training discussions and workflow demonstrations do not make every named family profile an identical checkpoint. Keep the selected profile and the supplied project instructions with the result, and use the specific producer interface or environment recipe for its operations. A useful handoff can contain a focused implementation, a defect explanation or a refactor with the evidence that supports its behavior. Review the changed logic and the actual environment outputs before treating a task as finished. KAT-Coder’s software-engineering purpose is most useful when it stays connected to a concrete development request, the relevant code and a reviewable final artifact. **Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `KAT-Coder-Pro-V1` [`KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/#m=KAT-Coder-Pro-V1&route=Ultra&caller=KAT-Coder-Pro-V1&fmt=chat) Kuaishou /`KAT-Coder-Pro-V1` ### Overview KAT-Coder is Kuaishou’s coding-model family for repository-aware development tasks. Its maker workflow combines tool-assisted inspection, patch generation, execution-based review and reflection, producing code or explanations tied to the actual project behavior. Accepted inputs Text Results Text ### Available in Ailoot · inputs & methods **Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` Input types `text` Output types `text` Output format json or SSE | Field | Type | Requirement | Values & limits | Default | | --- | --- | --- | --- | --- | | Field`model` | Type`string` | RequirementRequired | Values & limits KAT-Coder-Pro-V1 | Default— | | Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— | | Field`messages[].role` | Type`string` | RequirementRequired | Values & limits Model-specific | Default— | | Field`messages[].content` | Type`string` | RequirementOptional | Values & limits Applies when: Text conversation | Default— | | Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse | Input material combinations **Text** · UTF8 text `messages[].content` Method parameters and lifecycle | Parameter | Contract | | --- | --- | | Parameter`content_type` | Contractapplication/json | | Parameter`required` | Contractmodel, messages | | Parameter`material_types` | Contracttext | | Parameter`messages` | Contractmessage array with role/content shape | | Parameter`file_material` | Contractactual UTF-8 document inserted as literal text; no file ID inferred | | Parameter`optional_controls` | Contractstream | | Parameter`control_scope` | ContractText conversation; stream is a boolean and defaults to false. | | Parameter`output_modalities` | Contracttext | | Parameter`hosted_operations` | Contractfalse | | Parameter`multimodal_input_binding` | Contractnull | Method aliases: `/chat/completions` Lifecycle: `synchronous_or_streamed` Send exact model ID with messages. Context length is not an output cap. A text file may supply literal text; image/audio/file-object inputs need exact binding. ### Pricing Tariff references do not add request options. Supported parameters are listed for the selected method. Fast mode Not specified When fast mode is selected Flex mode Not specified When flex mode is selected Maximum reasoning effort Not specified When maximum reasoning effort uses the default adjustment #### Ailoot rates #### Prices by configuration | Configuration | Rate schedule | Charge | | --- | --- | --- | | ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0.00114** / 1K tokens Output · Output tokens **$0.00456** / 1K tokens Input · Cache read **$0** / 1K tokens Input · Cache write **$0** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · OpenAI Chat curlPython SDK ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model":"KAT-Coder-Pro-V1","messages":[{"role":"user","content":"hello"}],"stream":false}') Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \ -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path r=json.loads(Path("result.json").read_text()) for x in r.get("choices",[]): if x.get("message",{}).get("content"): print(x["message"]["content"]) PY_RESULT ``` ```python from openai import OpenAI import os if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0) result=client.chat.completions.create(model="KAT-Coder-Pro-V1", messages=[{"role":"user","content":"hello"}], stream=False) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(result.to_dict(mode="json")) ``` ### Receive and save results #### Ailoot Ultra · OpenAI Chat json or SSE ##### Keep all completed results Keep every complete returned response, file and content part. Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage. ##### If the original response needs checking Keep request/response IDs and headers. No generic text job retrieval URL is supplied. Response fields | Field | Type | | --- | --- | | Field`choices[].index` | Typeinteger | | Field`choices[].message.content` | Typestring\|null | | Field`choices[].message.tool_calls` | Typetool\_call\[\] | | Field`choices[].message.reasoning_content` | Typestring | | Field`choices[].message.reasoning_details` | Typeobject\|array | | Field`choices[].finish_reason` | Typestring\|null | | Field`usage` | Typeobject | Errors and next steps | Response | Condition | Next step | | --- | --- | --- | | Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. | ### Aliases #### Model aliases **Ailoot Ultra** [`KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/#m=KAT-Coder-Pro-V1&route=Ultra&caller=KAT-Coder-Pro-V1&fmt=chat) #### Method path aliases `/chat/completions` #### Related caller IDs [`KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/#m=KAT-Coder-Pro-V1&route=Ultra&caller=KAT-Coder-Pro-V1&fmt=chat) **Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `KAT-Coder-Pro-V1` [`KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/#m=KAT-Coder-Pro-V1&route=Ultra&caller=KAT-Coder-Pro-V1&fmt=messages) Kuaishou /`KAT-Coder-Pro-V1` ### Overview KAT-Coder is Kuaishou’s coding-model family for repository-aware development tasks. Its maker workflow combines tool-assisted inspection, patch generation, execution-based review and reflection, producing code or explanations tied to the actual project behavior. Accepted inputs Text Results json · sse ### Available in Ailoot · inputs & methods **Ailoot Ultra · Anthropic Messages** `POST /v1/messages` Input types `text` Output types `json`, `sse` Output format JSON or SSE | Field | Type | Requirement | Values & limits | Default | | --- | --- | --- | --- | --- | | Field`model` | Type`string` | RequirementRequired | Values & limits KAT-Coder-Pro-V1 | Default— | | Field`messages` | Type`message[]` | RequirementRequired | Values & limits | Default— | | Field`messages[].role` | Type`string` | RequirementRequired | Values & limits user, assistant | Default— | | Field`messages[].content` | Type`string` | RequirementRequired | Values & limits | Default— | | Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits | Default— | | Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse | Input material combinations **Text** · UTF-8 text `messages[].content string` Method parameters and lifecycle | Parameter | Contract | | --- | --- | | Parameter`content_type` | Contractapplication/json | | Parameter`required` | Contractmodel, messages, max\_tokens | | Parameter`optional_controls` | Contractstream | | Parameter`material_types` | Contracttext | | Parameter`text_file_material` | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. | Lifecycle: `synchronous_or_streamed` ### Pricing Tariff references do not add request options. Supported parameters are listed for the selected method. Fast mode Not specified When fast mode is selected Flex mode Not specified When flex mode is selected Maximum reasoning effort Not specified When maximum reasoning effort uses the default adjustment #### Ailoot rates #### Prices by configuration | Configuration | Rate schedule | Charge | | --- | --- | --- | | ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0.00114** / 1K tokens Output · Output tokens **$0.00456** / 1K tokens Input · Cache read **$0** / 1K tokens Input · Cache write **$0** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · Anthropic Messages Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result ```json { "model": "KAT-Coder-Pro-V1", "max_tokens": 128, "messages": [ { "role": "user", "content": "Summarize the incident report." } ], "stream": false } ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json, os from pathlib import Path source_file = Path(os.environ['AILOOT_TEXT_FILE']) if not source_file.is_file(): raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document') text = source_file.read_text(encoding='utf-8') if not text.strip(): raise SystemExit('Choose a document containing text') payload = {'model': 'KAT-Coder-Pro-V1', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]} payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text Path('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8') PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \ -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path result = json.loads(Path('result.json').read_text(encoding='utf-8')) print(json.dumps(result, ensure_ascii=False, indent=2)) PY_RESULT ``` ```python import json, os from pathlib import Path source_file = Path(os.environ['AILOOT_TEXT_FILE']) if not source_file.is_file(): raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document') text = source_file.read_text(encoding='utf-8') if not text.strip(): raise SystemExit('Choose a document containing text') payload = {'model': 'KAT-Coder-Pro-V1', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]} payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text from urllib.request import Request, urlopen from urllib.error import HTTPError api_key = os.environ['AILOOT_API_KEY'] if not api_key.strip(): raise SystemExit('Set AILOOT_API_KEY before making a request') headers = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'} headers['x-api-key'] = api_key request = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST') try: with urlopen(request, timeout=120) as response: raw = response.read() Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8') except HTTPError as error: Path('result.json').write_bytes(error.read()) Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8') raise Path('result.json').write_bytes(raw) import json from pathlib import Path result = json.loads(Path('result.json').read_text(encoding='utf-8')) print(json.dumps(result, ensure_ascii=False, indent=2)) ``` ### Receive and save results #### Ailoot Ultra · Anthropic Messages JSON or SSE ##### Keep all completed results Keep every complete returned response, file and content part. Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output. ##### If the original response needs checking Keep request/response IDs and headers. No generic text job retrieval URL is supplied. Response fields | Field | Type | | --- | --- | | Field`id` | Typestring | | Field`model` | Typestring | | Field`content[]` | Typetext\|thinking\|tool\_use\|other content block | | Field`stop_reason` | Typestring\|null | | Field`usage` | Typeobject | Errors and next steps | Response | Condition | Next step | | --- | --- | --- | | Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. | ### Aliases #### Model aliases **Ailoot Ultra** [`KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/#m=KAT-Coder-Pro-V1&route=Ultra&caller=KAT-Coder-Pro-V1&fmt=messages) #### Method path aliases `/chat/completions` #### Related caller IDs [`KAT-Coder-Pro-V1`](https://ailoot.ai/models/en/#m=KAT-Coder-Pro-V1&route=Ultra&caller=KAT-Coder-Pro-V1&fmt=messages) FAQ · kat-coder-pro-v1 What inputs and results are available? `POST /v1/chat/completions` · `KAT-Coder-Pro-V1`: `text` → `text` `POST /v1/messages` · `KAT-Coder-Pro-V1`: `text` → `json`, `sse` Which fields does the request use? `POST /v1/chat/completions` · `KAT-Coder-Pro-V1`: `model`, `messages`, `stream` `POST /v1/messages` · `KAT-Coder-Pro-V1`: `model`, `messages`, `max_tokens`, `stream` What limits apply? `POST /v1/chat/completions` · `KAT-Coder-Pro-V1`: `messages.min_items`: `1` Connect Ailoot to Claude Code, OpenCode, Hermes or your own app. ## The company and its project portfolio The company and its project portfolio: millions of customers; monthly sales in the billions. ## Buy tokens at a discount. 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