Source: https://ailoot.ai/models/en/cohere-command-r-plus-08-2024/ Canonical: https://ailoot.ai/models/en/cohere-command-r-plus-08-2024/ Language: en # Cohere: Command R+ (08-2024) [Markdown](https://ailoot.ai/models/en/cohere-command-r-plus-08-2024/index.md) · [JSON](https://ailoot.ai/models/en/cohere-command-r-plus-08-2024/facts.json) ## [Cohere: Command R+ (08-2024)](https://ailoot.ai/models/en/cohere-command-r-plus-08-2024/) Command R+ (08-2024) is Cohere’s 104B text model for complex document-grounded answers and multi-step tool use. It combines a 128K context with multilingual generation, source-span citations and agent workflows that use the application’s actual tool observations. - [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/cohere-command-r-plus-08-2024/#method-0) - [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/cohere-command-r-plus-08-2024/#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. Command R+ (08-2024) is Cohere’s August 2024 large text model for complex retrieval-augmented answers and agent tasks. The exact edition has 104 billion parameters and a 128K context, accepting text and producing text. The published maker profile lists a 4,000-token maximum output. R+ is the larger companion to Command R and has a particular emphasis on combining tools across multiple steps. #### Model and edition changes The model uses an autoregressive transformer with grouped-query attention, supervised fine-tuning and preference training. It is trained on 23 languages and evaluated on ten principal languages. The August refresh improves tool-selection decisions, system-instruction following, structured data analysis and robustness to non-semantic prompt changes. It also supports retrieval workflows without citations, several safety modes and declining questions that cannot be answered. For multilingual work, specify the output language and the names, codes or source quotations that must remain unchanged. A grounded answer can explain material in a different language, while keeping the evidence available for review. Provide a current source for time-sensitive facts, or obtain one through a suitable application tool. #### Grounded answers and citations The producer’s RAG template accepts a conversation and retrieved document snippets, normally around 100–400 words per chunk, with short descriptive keys and text or semi-structured values. The model is specifically trained to answer from those snippets and connect answer spans with the supporting sources. Use the exact edition’s template when that trained grounding behaviour matters. Accurate citation mode identifies relevant and cited documents, generates an answer and inserts grounding spans. Fast mode generates the cited answer directly, reducing output tokens at a trade-off in grounding accuracy. Keep source identifiers available for both modes. A practical report request can ask the model to compare evidence against named criteria and cite the supporting passage beside each finding. #### Tool-assisted work R+ supports both a single-step function-calling template and multi-step tool use for harder workflows. In the single-step flow, the model selects functions and JSON arguments, the application performs them, and a later model response uses the returned results. The documented directly\_answer choice lets the model avoid an unnecessary external operation. In a multi-step agent, subsequent decisions can combine observations from different tools until the task reaches its specified result. A useful agent brief defines the question, allowed operations and final deliverable. For example, a research assistant may need to retrieve relevant product records, compare the supplied requirements and produce an evidence-backed recommendation. Give each tool a clear purpose and associate its result with the call that produced it. An operation proposed in text is distinct from execution by the application. #### Preparing and reviewing the result Organise the source snippets around the actual question and reserve room for tool history and the answer. If the available evidence conflicts, ask the model to explain the disagreement rather than choose an unsupported value. For structured data work, define the fields, units and representation of missing information. The final result should be a reviewable answer or report tied to the supplied evidence and actual observations. R+’s size and agent focus do not independently supply a search connection, execute a database action or validate generated code. Those steps belong to the surrounding workflow, and their returned evidence is what makes a conclusion checkable. Practical task ### Answer from product evidence Technical example in English ``` Answer from product evidence Use only these snippets to answer whether Team Plan supports both requested features. S1: Team Plan includes shared folders and 30-day activity history. S2: Single sign-on is available on Enterprise Plan. Request: We need shared folders and single sign-on. State what is supported, cite each source identifier and leave unsupported assumptions unresolved. ``` #### Expected result ``` A feature-by-feature answer with a source identifier beside each finding and a concise conclusion about the two requirements. ``` #### Check the result ``` Check that S1 supports shared folders and S2 does not establish single sign-on for Team Plan. ``` **Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `cohere/command-r-plus-08-2024` [`cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/#m=cohere%2Fcommand-r-plus-08-2024&route=Ultra&caller=cohere%2Fcommand-r-plus-08-2024&fmt=chat) Cohere /`cohere/command-r-plus-08-2024` ### Overview Command R+ (08-2024) is Cohere’s 104B text model for complex document-grounded answers and multi-step tool use. It combines a 128K context with multilingual generation, source-span citations and agent workflows that use the application’s actual tool observations. 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 cohere/command-r-plus-08-2024 | Default— | | Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— | | Field`messages[].role` | Type`string` | RequirementRequired | Values & limits Examples: system, user, assistant, tool, function Conditions: These roles are explicitly represented by Source compatibility types; the exact model role set remains model-specific. Model-specific | Default— | | Field`messages[].content` | Type`string\|content_part[]\|null` | RequirementOptional | Values & limits | Default— | | Field`messages[].tool_calls` | Type`tool_call[]` | RequirementOptional | Values & limits | Default— | | Field`messages[].tool_call_id` | Type`string` | RequirementOptional | Values & limits Applies when: role=tool; use actual returned ID | Default— | | Field`messages[].name` | Type`string` | RequirementOptional | Values & limits | Default— | | Field`messages[].reasoning_content` | Type`string` | RequirementOptional | Values & limits Applies when: Round-trip actual returned reasoning where this model uses it | Default— | | Field`messages[].reasoning_details` | Type`object\|array` | RequirementOptional | Values & limits Model-specific | Default— | | Field`max_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— | | Field`max_completion_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— | | Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse | | Field`stream_options.include_usage` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— | | Field`temperature` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`top_p` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`stop` | Type`string\|string[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tools` | Type`function_tool[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tools[].type` | Type`string` | RequirementOptional | Values & limits function Model-specific | Default— | | Field`tools[].function.name` | Type`string` | RequirementRequired | Values & limits Applies when: function tool supplied | Default— | | Field`tools[].function.description` | Type`string` | RequirementOptional | Values & limits | Default— | | Field`tools[].function.parameters` | Type`JSON_schema` | RequirementOptional | Values & limits | Default— | | Field`tool_choice` | Type`string\|object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`parallel_tool_calls` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— | | Field`response_format` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`reasoning_effort` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`reasoning` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`service_tier` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`instructions` | Type`string` | RequirementOptional | Values & limits Compatibility field | Default— | | Field`functions` | Type`function[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`function_call` | Type`string\|object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`prompt_cache_options` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`modalities` | Type`string[]` | RequirementOptional | Values & limits text | Default— | | Field`provider` | Type`object` | RequirementOptional | Values & limits Conditions: provider.options is rejected on this Ultra text route | Default— | | Field`cache_control.ttl` | Type`string` | RequirementOptional | Values & limits Conditions: 1h is rejected in actual prompt-cache locations | Default— | 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, temperature, top\_p, stop, max\_tokens, max\_completion\_tokens, reasoning, response\_format, tools, tool\_choice | | Parameter`control_scope` | Contractmodel-specific; user function tools differ from hosted tools | | Parameter`output_modalities` | Contracttext | | Parameter`hosted_operations` | Contractfalse | | Parameter`multimodal_input_binding` | Contractnull | 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 Standard rate When fast mode is selected Flex mode Standard rate When flex mode is selected Maximum reasoning effort Standard rate When maximum reasoning effort uses the default adjustment #### Ailoot rates #### Prices by configuration Match each charge to the conditions shown. Use one rate for each set of alternative configurations. | Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge | | --- | --- | --- | --- | --- | | ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **—** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **—** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · OpenAI Chat curlPython SDKPython stream ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "cohere/command-r-plus-08-2024", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}') 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='cohere/command-r-plus-08-2024',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) 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")) ``` ```python from openai import OpenAI import os from pathlib import Path 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) 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)) with client.chat.completions.stream(model='cohere/command-r-plus-08-2024',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream: with Path("stream-events.jsonl").open("w",encoding="utf-8") as log: for event in stream: payload=event.to_dict(mode="json") log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush() print(json.dumps(payload,ensure_ascii=False)) final=stream.get_final_completion() save_result(final.to_dict(mode="json"),"stream-result") ``` ### 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** [`cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/#m=cohere%2Fcommand-r-plus-08-2024&route=Ultra&caller=cohere%2Fcommand-r-plus-08-2024&fmt=chat) #### Method path aliases Use the method paths shown above. #### Related caller IDs [`cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/#m=cohere%2Fcommand-r-plus-08-2024&route=Ultra&caller=cohere%2Fcommand-r-plus-08-2024&fmt=chat) **Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `cohere/command-r-plus-08-2024` [`cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/#m=cohere%2Fcommand-r-plus-08-2024&route=Ultra&caller=cohere%2Fcommand-r-plus-08-2024&fmt=messages) Cohere /`cohere/command-r-plus-08-2024` ### Overview Command R+ (08-2024) is Cohere’s 104B text model for complex document-grounded answers and multi-step tool use. It combines a 128K context with multilingual generation, source-span citations and agent workflows that use the application’s actual tool observations. 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 cohere/command-r-plus-08-2024 | 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 Standard rate When fast mode is selected Flex mode Standard rate When flex mode is selected Maximum reasoning effort Standard rate When maximum reasoning effort uses the default adjustment #### Ailoot rates #### Prices by configuration Match each charge to the conditions shown. Use one rate for each set of alternative configurations. | Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge | | --- | --- | --- | --- | --- | | ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **—** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **—** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · Anthropic Messages Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result ```json { "model": "cohere/command-r-plus-08-2024", "max_tokens": 128, "messages": [ { "role": "user", "content": "Summarize the incident report." } ], "stream": false } ``` ```bash set -eu : "${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': 'cohere/command-r-plus-08-2024', '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': 'cohere/command-r-plus-08-2024', '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** [`cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/#m=cohere%2Fcommand-r-plus-08-2024&route=Ultra&caller=cohere%2Fcommand-r-plus-08-2024&fmt=messages) #### Method path aliases Use the method paths shown above. #### Related caller IDs [`cohere/command-r-plus-08-2024`](https://ailoot.ai/models/en/#m=cohere%2Fcommand-r-plus-08-2024&route=Ultra&caller=cohere%2Fcommand-r-plus-08-2024&fmt=messages) FAQ · Cohere: Command R+ (08-2024) What inputs and results are available? `POST /v1/chat/completions` · `cohere/command-r-plus-08-2024`: `text` → `text` `POST /v1/messages` · `cohere/command-r-plus-08-2024`: `text` → `json`, `sse` Which fields does the request use? `POST /v1/chat/completions` · `cohere/command-r-plus-08-2024`: `model`, `messages`, `stream`, `modalities`, `provider` `POST /v1/messages` · `cohere/command-r-plus-08-2024`: `model`, `messages`, `max_tokens`, `stream` What limits apply? `POST /v1/chat/completions` · `cohere/command-r-plus-08-2024`: `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. Subscription discounts for regular use. Promo codes offer up to 50% off token purchases. Subscription Choose a discounted plan for your regular requests. Promo code: up to 50% off Enter your code at checkout. The price updates to reflect the current promotion. Spending in your history The model, tokens and amount are recorded for each request. [Choose a subscription](https://ailoot.ai/docs/en/billing/subscriptions/) · [View model prices](https://ailoot.ai/models/en/) ## Connect the API to a product you sell. Use Ailoot in SaaS, apps and bots under its official service offer and licence agreement. Request a reseller licence for resale. Commercial application Add text, image, video and audio generation to paid features in your service. Reseller licence Send a description of your project and how you provide access. Request written terms for use and resale. Documents on the website The service offer, licence agreement and data processing policy are available before you connect. [Request a reseller licence](mailto:support@ailoot.ai) · [Service offer and licence agreement](https://ailoot.ai/legal/offer?lang=en) ## Ailoot · The company and its project portfolio Ailoot combines established operating experience, a large client base, stable service and ongoing KPI control. The company and its project portfolio: millions of customers; monthly sales in the billions. Ailoot brings that operating experience to API access for AI features in customer products, agents, applications and automations.