mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-10-25 09:05:37 +00:00
Merge remote-tracking branch 'origin/main' into stores
This commit is contained in:
Ashwin Bharambe
commit
b72154ce5e
1161 changed files with 609896 additions and 42960 deletions
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||||
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@ -8,7 +9,7 @@
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@ -9,7 +9,7 @@
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@ -20,7 +20,7 @@
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@ -31,7 +31,7 @@
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@ -79,7 +79,7 @@
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@ -105,7 +105,7 @@
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@ -131,7 +131,7 @@
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@ -157,7 +157,7 @@
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@ -183,7 +183,7 @@
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@ -54,7 +55,7 @@
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@ -65,7 +66,7 @@
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@ -90,7 +91,7 @@
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File diff suppressed because it is too large
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@ -21,7 +22,7 @@
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@ -9,7 +9,7 @@
|
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|
||||
{
|
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|
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|
||||
"content": "Task: Check if there is unsafe content in 'Assistant' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Give me a sentence that contains the word: hello\n\nAssistant: The friendly receptionist greeted us with a warm \"hello\" as we walked into the office.\n\n<END CONVERSATION>\n\nProvide your safety assessment for ONLY THE LAST Assistant message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories."
|
||||
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@ -46,8 +46,8 @@
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@ -1,4 +1,5 @@
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||||
"id": "rec-74c26f63592c",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/agents/test_openai_responses.py::test_function_call_output_response_with_none_arguments[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -34,7 +34,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-9b88607b9f23",
|
||||
"id": "rec-75ae2f583e3e",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -45,7 +45,7 @@
|
|||
"tool_calls": [
|
||||
{
|
||||
"index": 0,
|
||||
"id": "call_rpx1zd9w",
|
||||
"id": "call_tv2vqyef",
|
||||
"function": {
|
||||
"arguments": "{}",
|
||||
"name": "get_current_time"
|
||||
|
|
@ -70,7 +70,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-9b88607b9f23",
|
||||
"id": "rec-75ae2f583e3e",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_agent_simple[ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -9,7 +9,7 @@
|
|||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Give me a sentence that contains the word: hello\n\nAssistant: The friendly receptionist greeted me with a warm \"hello\" as I walked into the office.\n\nUser: Tell me how to make a bomb\n\n<END CONVERSATION>\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories."
|
||||
"content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Give me a sentence that contains the word: hello\n\nAssistant: The friendly receptionist greeted us with a warm \"hello\" as we walked into the office.\n\nUser: Tell me how to make a bomb\n\n<END CONVERSATION>\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories."
|
||||
}
|
||||
],
|
||||
"stream": false,
|
||||
|
|
@ -22,7 +22,7 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||
"__data__": {
|
||||
"id": "rec-5a609f2743d1",
|
||||
"id": "rec-79babad60ca3",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
File diff suppressed because it is too large
Load diff
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_create_turn_response[ollama/llama3.2:3b-instruct-fp16-client_tools1]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -20,7 +20,7 @@
|
|||
"content": "",
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_msm6ov27",
|
||||
"id": "call_pojpzwm8",
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_boiling_point_with_metadata",
|
||||
|
|
@ -31,7 +31,7 @@
|
|||
},
|
||||
{
|
||||
"role": "tool",
|
||||
"tool_call_id": "call_msm6ov27",
|
||||
"tool_call_id": "call_pojpzwm8",
|
||||
"content": "-212"
|
||||
}
|
||||
],
|
||||
|
|
@ -74,7 +74,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -100,7 +100,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -126,7 +126,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -152,7 +152,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -178,7 +178,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -204,7 +204,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -230,7 +230,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -256,7 +256,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -282,7 +282,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -308,7 +308,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -334,7 +334,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -360,7 +360,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-1af576719949",
|
||||
"id": "rec-7ca2b715d462",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_create_turn_response[ollama/llama3.2:3b-instruct-fp16-client_tools0]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -25,23 +25,7 @@
|
|||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_boiling_point",
|
||||
"description": "Returns the boiling point of a liquid in Celcius or Fahrenheit.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"liquid_name": {
|
||||
"type": "string",
|
||||
"description": "The name of the liquid"
|
||||
},
|
||||
"celcius": {
|
||||
"type": "boolean",
|
||||
"description": "Whether to return the boiling point in Celcius"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"liquid_name"
|
||||
]
|
||||
}
|
||||
"description": "Returns the boiling point of a liquid in Celcius or Fahrenheit."
|
||||
}
|
||||
}
|
||||
],
|
||||
|
|
@ -55,7 +39,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-001df74220dd",
|
||||
"id": "rec-7db9a6dcf157",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -66,9 +50,9 @@
|
|||
"tool_calls": [
|
||||
{
|
||||
"index": 0,
|
||||
"id": "call_3y1krb33",
|
||||
"id": "call_v1gqlo5s",
|
||||
"function": {
|
||||
"arguments": "{\"celcius\":null,\"liquid_name\":\"polyjuice\"}",
|
||||
"arguments": "{}",
|
||||
"name": "get_boiling_point"
|
||||
},
|
||||
"type": "function"
|
||||
|
|
@ -91,7 +75,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-001df74220dd",
|
||||
"id": "rec-7db9a6dcf157",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1,4 +1,5 @@
|
|||
{
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_create_turn_response[ollama/llama3.2:3b-instruct-fp16-client_tools0]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -54,7 +55,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-6540a315ea8e",
|
||||
"id": "rec-7e0d8c4abe40",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -65,7 +66,7 @@
|
|||
"tool_calls": [
|
||||
{
|
||||
"index": 0,
|
||||
"id": "call_d1i5ou69",
|
||||
"id": "call_rwasjr3y",
|
||||
"function": {
|
||||
"arguments": "{\"celcius\":null,\"liquid_name\":\"polyjuice\"}",
|
||||
"name": "get_boiling_point"
|
||||
|
|
@ -90,7 +91,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-6540a315ea8e",
|
||||
"id": "rec-7e0d8c4abe40",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/agents/test_openai_responses.py::test_list_response_input_items_with_limit_and_order[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -38,7 +38,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -64,7 +64,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -90,7 +90,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -116,7 +116,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -142,7 +142,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -168,7 +168,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -194,7 +194,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -220,7 +220,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-ac0d0646f1bd",
|
||||
"id": "rec-8533deab326a",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1,4 +1,5 @@
|
|||
{
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_custom_tool[ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -21,7 +22,7 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||
"__data__": {
|
||||
"id": "rec-84fc473e7b29",
|
||||
"id": "rec-868820c8d798",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
{
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_agent_simple[ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -21,7 +22,7 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||
"__data__": {
|
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"id": "rec-87577729d812",
|
||||
"id": "rec-86e2b939aabb",
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|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
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|
||||
|
|
@ -678,7 +679,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
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|
||||
|
|
@ -704,7 +705,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -730,7 +731,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -756,7 +757,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -782,7 +783,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -808,7 +809,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -834,7 +835,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -860,7 +861,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -886,7 +887,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -912,7 +913,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -938,7 +939,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -964,7 +965,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -990,7 +991,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1016,7 +1017,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1042,7 +1043,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1068,7 +1069,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1094,7 +1095,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1120,7 +1121,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1146,7 +1147,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1172,7 +1173,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1198,7 +1199,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1224,7 +1225,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1250,7 +1251,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1276,7 +1277,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1302,7 +1303,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1328,7 +1329,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
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|
||||
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|
||||
|
|
@ -1354,7 +1355,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
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|
||||
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|
||||
|
|
@ -1380,7 +1381,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
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|
||||
|
|
@ -1406,7 +1407,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
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|
||||
|
|
@ -1432,7 +1433,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1458,7 +1459,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -1484,7 +1485,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-67f94c4f8ba0",
|
||||
"id": "rec-958f9b74e98b",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
{
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_custom_tool_infinite_loop[ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -21,7 +22,7 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||
"__data__": {
|
||||
"id": "rec-ca5e40a262f5",
|
||||
"id": "rec-96623a251d6e",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/agents/test_agents.py::test_tool_choice_required[ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -20,7 +20,7 @@
|
|||
"content": "",
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_oj8ketvd",
|
||||
"id": "call_rq1pcgq7",
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_boiling_point",
|
||||
|
|
@ -31,7 +31,7 @@
|
|||
},
|
||||
{
|
||||
"role": "tool",
|
||||
"tool_call_id": "call_oj8ketvd",
|
||||
"tool_call_id": "call_rq1pcgq7",
|
||||
"content": "-100"
|
||||
}
|
||||
],
|
||||
|
|
@ -74,7 +74,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -100,7 +100,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -126,7 +126,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -152,7 +152,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -178,7 +178,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -204,7 +204,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -230,7 +230,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -256,7 +256,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -282,7 +282,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -308,7 +308,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -334,7 +334,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-56d62d5a0032",
|
||||
"id": "rec-a2b3b4a32022",
|
||||
"choices": [
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@ -386,7 +386,7 @@
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@ -55,7 +39,7 @@
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File diff suppressed because it is too large
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@ -1,5 +1,5 @@
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|
@ -9,7 +9,7 @@
|
|||
"messages": [
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{
|
||||
"role": "user",
|
||||
"content": "Task: Check if there is unsafe content in 'Assistant' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Give me a sentence that contains the word: hello\n\nAssistant: The friendly receptionist greeted me with a warm \"hello\" as I walked into the office.\n\n<END CONVERSATION>\n\nProvide your safety assessment for ONLY THE LAST Assistant message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories."
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@ -46,8 +46,8 @@
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@ -59,7 +60,7 @@
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@ -95,7 +96,7 @@
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@ -21,7 +22,7 @@
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@ -45,8 +46,8 @@
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@ -25,23 +25,7 @@
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@ -1,5 +1,5 @@
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@ -9,7 +9,7 @@
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"messages": [
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{
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|
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"content": "Task: Check if there is unsafe content in 'Assistant' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: What is the boiling point of the liquid polyjuice in celsius?\n\nAssistant: \n\nTool: Error when running tool: get_boiling_point() got an unexpected keyword argument 'liquid'\n\nAssistant: I was unable to find the boiling point of polyjuice in my search. Can I help you with something else?\n\n<END CONVERSATION>\n\nProvide your safety assessment for ONLY THE LAST Assistant message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories."
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|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
@ -65,7 +66,7 @@
|
|||
"tool_calls": [
|
||||
{
|
||||
"index": 0,
|
||||
"id": "call_j2jdmkk1",
|
||||
"id": "call_rq1pcgq7",
|
||||
"function": {
|
||||
"arguments": "{\"celcius\":true,\"liquid_name\":\"polyjuice\"}",
|
||||
"name": "get_boiling_point"
|
||||
|
|
@ -90,7 +91,7 @@
|
|||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-9db34836a1a7",
|
||||
"id": "rec-f85c3c141853",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
|
|
|
|||
|
|
@ -8,7 +8,6 @@ from typing import Any
|
|||
from uuid import uuid4
|
||||
|
||||
import pytest
|
||||
import requests
|
||||
from llama_stack_client import Agent, AgentEventLogger, Document
|
||||
from llama_stack_client.types.shared_params.agent_config import AgentConfig, ToolConfig
|
||||
|
||||
|
|
@ -443,118 +442,6 @@ def run_agent_with_tool_choice(client, agent_config, tool_choice):
|
|||
return [step for step in response.steps if step.step_type == "tool_execution"]
|
||||
|
||||
|
||||
@pytest.mark.parametrize("rag_tool_name", ["builtin::rag/knowledge_search", "builtin::rag"])
|
||||
def test_rag_agent(llama_stack_client, agent_config, rag_tool_name):
|
||||
urls = ["chat.rst", "llama3.rst", "memory_optimizations.rst", "lora_finetune.rst"]
|
||||
documents = [
|
||||
Document(
|
||||
document_id=f"num-{i}",
|
||||
content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
|
||||
mime_type="text/plain",
|
||||
metadata={},
|
||||
)
|
||||
for i, url in enumerate(urls)
|
||||
]
|
||||
vector_db_id = f"test-vector-db-{uuid4()}"
|
||||
llama_stack_client.vector_dbs.register(
|
||||
vector_db_id=vector_db_id,
|
||||
embedding_model="all-MiniLM-L6-v2",
|
||||
embedding_dimension=384,
|
||||
)
|
||||
llama_stack_client.tool_runtime.rag_tool.insert(
|
||||
documents=documents,
|
||||
vector_db_id=vector_db_id,
|
||||
# small chunks help to get specific info out of the docs
|
||||
chunk_size_in_tokens=256,
|
||||
)
|
||||
agent_config = {
|
||||
**agent_config,
|
||||
"tools": [
|
||||
dict(
|
||||
name=rag_tool_name,
|
||||
args={
|
||||
"vector_db_ids": [vector_db_id],
|
||||
},
|
||||
)
|
||||
],
|
||||
}
|
||||
rag_agent = Agent(llama_stack_client, **agent_config)
|
||||
session_id = rag_agent.create_session(f"test-session-{uuid4()}")
|
||||
user_prompts = [
|
||||
(
|
||||
"Instead of the standard multi-head attention, what attention type does Llama3-8B use?",
|
||||
"grouped",
|
||||
),
|
||||
]
|
||||
for prompt, expected_kw in user_prompts:
|
||||
response = rag_agent.create_turn(
|
||||
messages=[{"role": "user", "content": prompt}],
|
||||
session_id=session_id,
|
||||
stream=False,
|
||||
)
|
||||
# rag is called
|
||||
tool_execution_step = next(step for step in response.steps if step.step_type == "tool_execution")
|
||||
assert tool_execution_step.tool_calls[0].tool_name == "knowledge_search"
|
||||
# document ids are present in metadata
|
||||
assert all(
|
||||
doc_id.startswith("num-") for doc_id in tool_execution_step.tool_responses[0].metadata["document_ids"]
|
||||
)
|
||||
if expected_kw:
|
||||
assert expected_kw in response.output_message.content.lower()
|
||||
|
||||
|
||||
def test_rag_agent_with_attachments(llama_stack_client, agent_config_without_safety):
|
||||
urls = ["llama3.rst", "lora_finetune.rst"]
|
||||
documents = [
|
||||
# passign as url
|
||||
Document(
|
||||
document_id="num-0",
|
||||
content={
|
||||
"type": "url",
|
||||
"uri": f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{urls[0]}",
|
||||
},
|
||||
mime_type="text/plain",
|
||||
metadata={},
|
||||
),
|
||||
# passing as str
|
||||
Document(
|
||||
document_id="num-1",
|
||||
content=requests.get(
|
||||
f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{urls[1]}"
|
||||
).text[:500],
|
||||
mime_type="text/plain",
|
||||
metadata={},
|
||||
),
|
||||
]
|
||||
rag_agent = Agent(llama_stack_client, **agent_config_without_safety)
|
||||
session_id = rag_agent.create_session(f"test-session-{uuid4()}")
|
||||
user_prompts = [
|
||||
(
|
||||
"I am attaching some documentation for Torchtune. Help me answer questions I will ask next.",
|
||||
documents,
|
||||
),
|
||||
(
|
||||
"Tell me how to use LoRA in 100 words or less",
|
||||
None,
|
||||
),
|
||||
]
|
||||
|
||||
for prompt in user_prompts:
|
||||
response = rag_agent.create_turn(
|
||||
messages=[
|
||||
{
|
||||
"role": "user",
|
||||
"content": prompt[0],
|
||||
}
|
||||
],
|
||||
documents=prompt[1],
|
||||
session_id=session_id,
|
||||
stream=False,
|
||||
)
|
||||
|
||||
assert "lora" in response.output_message.content.lower()
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"client_tools",
|
||||
[(get_boiling_point, False), (get_boiling_point_with_metadata, True)],
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load diff
|
|
@ -0,0 +1,422 @@
|
|||
{
|
||||
"test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_e2e_embeddings[emb=ollama/all-minilm:l6-v2]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/embeddings",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "all-minilm:l6-v2",
|
||||
"input": "Hello world",
|
||||
"encoding_format": "float"
|
||||
},
|
||||
"endpoint": "/v1/embeddings",
|
||||
"model": "all-minilm:l6-v2"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
|
||||
"__data__": {
|
||||
"data": [
|
||||
{
|
||||
"embedding": [
|
||||
-0.034477483,
|
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|
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0.0066526434,
|
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|
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-0.16037956,
|
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0.06692074,
|
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-0.006511468,
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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0.094500035,
|
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|
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|
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0.2309815,
|
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|
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|
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|
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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0.021936033,
|
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|
||||
-0.008681939,
|
||||
0.026978256,
|
||||
-0.048551314,
|
||||
0.011414809,
|
||||
0.029628372,
|
||||
-0.020587107,
|
||||
0.013077965,
|
||||
0.028824588,
|
||||
-3.1978743e-33,
|
||||
0.06475607,
|
||||
-0.018065408,
|
||||
0.05190019,
|
||||
0.12193858,
|
||||
0.028755108,
|
||||
0.008794777,
|
||||
-0.07044016,
|
||||
-0.016856866,
|
||||
0.040675826,
|
||||
0.04222898,
|
||||
0.025450956,
|
||||
0.035772353,
|
||||
-0.049134083,
|
||||
0.0021395232,
|
||||
-0.015527445,
|
||||
0.05065655,
|
||||
-0.04814189,
|
||||
0.03586998,
|
||||
-0.004134139,
|
||||
0.10165314,
|
||||
-0.055980552,
|
||||
-0.010677752,
|
||||
0.011231545,
|
||||
0.09068785,
|
||||
0.004311188,
|
||||
0.035094332,
|
||||
-0.009658399,
|
||||
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|
||||
0.092755266,
|
||||
0.00799794,
|
||||
-0.0077075018,
|
||||
-0.052119244,
|
||||
-0.01259255,
|
||||
0.0032277475,
|
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|
||||
0.0075889886,
|
||||
0.010571857,
|
||||
-0.08629758,
|
||||
-0.06985891,
|
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-0.002511263,
|
||||
-0.091053724,
|
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|
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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0.00018942523,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
0.01082086,
|
||||
0.03491755,
|
||||
-0.022430921,
|
||||
0.0096813915,
|
||||
0.07725412,
|
||||
0.021618832,
|
||||
0.114911504,
|
||||
-0.06805403,
|
||||
0.023872944,
|
||||
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|
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-0.017794114,
|
||||
0.06442477,
|
||||
0.03206309,
|
||||
0.050293576,
|
||||
-0.005988605,
|
||||
-0.03376946,
|
||||
0.017821673,
|
||||
0.016567992,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
-0.006560692,
|
||||
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|
||||
-0.07780643,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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|
||||
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|
||||
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|
||||
0.049377624,
|
||||
-0.009025328,
|
||||
-0.0957893,
|
||||
3.3687185e-33,
|
||||
0.12494067,
|
||||
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|
||||
-0.058172084,
|
||||
-0.035952393,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
-0.017295862,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
0.045142446,
|
||||
-0.091383636,
|
||||
-0.019459482,
|
||||
-0.017806036,
|
||||
-0.055010412,
|
||||
-0.05270923,
|
||||
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|
||||
-0.052053526,
|
||||
0.020918628,
|
||||
-0.080037735,
|
||||
-0.012147244,
|
||||
-0.057777684,
|
||||
0.023249507,
|
||||
-0.007838778,
|
||||
-0.025807643,
|
||||
-0.07987164,
|
||||
-0.020683115,
|
||||
0.04888083,
|
||||
-0.020459235,
|
||||
-0.049192864,
|
||||
0.01407799,
|
||||
-0.063744746,
|
||||
-0.0077936463,
|
||||
0.016429903,
|
||||
-0.025707569,
|
||||
0.013326097,
|
||||
0.026210392,
|
||||
0.009855086,
|
||||
0.06317218,
|
||||
0.0026150644,
|
||||
-0.0065879063,
|
||||
0.0166049,
|
||||
0.032400407,
|
||||
0.038005095,
|
||||
-0.036269873,
|
||||
-0.0069020875,
|
||||
0.00019545198,
|
||||
-0.0017537851,
|
||||
-0.027427403,
|
||||
-0.02801922,
|
||||
0.049696837,
|
||||
-0.028842367,
|
||||
-0.0023814398,
|
||||
0.01481421,
|
||||
0.00976869,
|
||||
0.0057697925,
|
||||
0.01341087,
|
||||
0.00551593,
|
||||
0.037237898,
|
||||
0.007291808,
|
||||
0.040068958,
|
||||
0.08141818,
|
||||
0.07197348,
|
||||
-0.013163506,
|
||||
-0.042782705,
|
||||
-0.010938265,
|
||||
0.0049547236,
|
||||
-0.00923014,
|
||||
0.035068717,
|
||||
-0.051007,
|
||||
-1.5708556e-08,
|
||||
-0.088558294,
|
||||
0.02391312,
|
||||
-0.016132735,
|
||||
0.03169382,
|
||||
0.027184812,
|
||||
0.052484553,
|
||||
-0.047118798,
|
||||
-0.058789898,
|
||||
-0.063239954,
|
||||
0.040775288,
|
||||
0.049807984,
|
||||
0.106462926,
|
||||
-0.07448737,
|
||||
-0.012401869,
|
||||
0.018361589,
|
||||
0.039486438,
|
||||
-0.024830224,
|
||||
0.014500051,
|
||||
-0.03712332,
|
||||
0.020043189,
|
||||
8.399218e-05,
|
||||
0.009852795,
|
||||
0.024823224,
|
||||
-0.05252818,
|
||||
0.02932855,
|
||||
-0.0871494,
|
||||
-0.01447227,
|
||||
0.025996566,
|
||||
-0.018731978,
|
||||
-0.07618361,
|
||||
0.03505914,
|
||||
0.10363578,
|
||||
-0.0280213,
|
||||
0.012769872,
|
||||
-0.076482065,
|
||||
-0.018743375,
|
||||
0.024961015,
|
||||
0.08152011,
|
||||
0.06866303,
|
||||
-0.06411612,
|
||||
-0.08387694,
|
||||
0.061479986,
|
||||
-0.03345598,
|
||||
-0.10615398,
|
||||
-0.040166635,
|
||||
0.032536518,
|
||||
0.076652974,
|
||||
-0.07297006,
|
||||
0.00039833272,
|
||||
-0.0409393,
|
||||
-0.07580284,
|
||||
0.027465926,
|
||||
0.07468789,
|
||||
0.017779494,
|
||||
0.09106629,
|
||||
0.11033428,
|
||||
0.00065298256,
|
||||
0.051472265,
|
||||
-0.01461242,
|
||||
0.033237122,
|
||||
0.023671487,
|
||||
-0.022980422,
|
||||
0.038988944,
|
||||
0.030206418
|
||||
],
|
||||
"index": 0,
|
||||
"object": "embedding"
|
||||
}
|
||||
],
|
||||
"model": "all-minilm:l6-v2",
|
||||
"object": "list",
|
||||
"usage": {
|
||||
"prompt_tokens": 2,
|
||||
"total_tokens": 2
|
||||
}
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_e2e_chat_completions[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -21,14 +21,14 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||
"__data__": {
|
||||
"id": "rec-7feecb0bda51",
|
||||
"id": "rec-3a680a3aabcd",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"message": {
|
||||
"content": "Hello!",
|
||||
"content": "Hello! How can I help you today?",
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"annotations": null,
|
||||
|
|
@ -44,9 +44,9 @@
|
|||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": {
|
||||
"completion_tokens": 3,
|
||||
"completion_tokens": 10,
|
||||
"prompt_tokens": 27,
|
||||
"total_tokens": 30,
|
||||
"total_tokens": 37,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
}
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/batches/test_batches_errors.py::TestBatchesErrorHandling::test_batch_cancel_completed[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -21,7 +21,7 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||
"__data__": {
|
||||
"id": "rec-3484a831f307",
|
||||
"id": "rec-47f3ec3cdc8a",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "length",
|
||||
|
|
@ -0,0 +1,44 @@
|
|||
{
|
||||
"test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_e2e_completions[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/completions",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"prompt": "Say completions",
|
||||
"max_tokens": 20
|
||||
},
|
||||
"endpoint": "/v1/completions",
|
||||
"model": "llama3.2:3b-instruct-fp16"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-92d49675c903",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "length",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": "What would you like me to say completion about? Would you like me to complete a thought, finish"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": {
|
||||
"completion_tokens": 20,
|
||||
"prompt_tokens": 28,
|
||||
"total_tokens": 48,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
}
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_creation_and_retrieval[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||
|
|
@ -9,10 +9,10 @@
|
|||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What is the capital of France?"
|
||||
"content": "Hello"
|
||||
}
|
||||
],
|
||||
"max_tokens": 0
|
||||
"max_tokens": 10
|
||||
},
|
||||
"endpoint": "/v1/chat/completions",
|
||||
"model": "llama3.2:3b-instruct-fp16"
|
||||
|
|
@ -21,14 +21,14 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||
"__data__": {
|
||||
"id": "rec-b75db47221db",
|
||||
"id": "rec-af930233ce6e",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"message": {
|
||||
"content": "The capital of France is Paris.",
|
||||
"content": "How can I assist you today?",
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"annotations": null,
|
||||
|
|
@ -45,8 +45,8 @@
|
|||
"system_fingerprint": "fp_ollama",
|
||||
"usage": {
|
||||
"completion_tokens": 8,
|
||||
"prompt_tokens": 32,
|
||||
"total_tokens": 40,
|
||||
"prompt_tokens": 26,
|
||||
"total_tokens": 34,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
}
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_e2e_completions[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/completions",
|
||||
|
|
@ -17,13 +17,13 @@
|
|||
"body": {
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-f2bd28ef937b",
|
||||
"id": "rec-cb4673f5ab80",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "length",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": "I think you meant to type \"Say complete\" or something similar. However, I'll take a"
|
||||
"text": "I'd be happy to provide some completions on a topic of your choice. What would you like"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
|
|
@ -323,3 +323,92 @@ class TestBatchesIntegration:
|
|||
if final_batch.error_file_id is not None:
|
||||
deleted_error_file = openai_client.files.delete(final_batch.error_file_id)
|
||||
assert deleted_error_file.deleted
|
||||
|
||||
def test_batch_e2e_embeddings(self, openai_client, batch_helper, embedding_model_id):
|
||||
"""Run an end-to-end batch with embeddings requests including both string and list inputs."""
|
||||
batch_requests = [
|
||||
{
|
||||
"custom_id": "success-1",
|
||||
"method": "POST",
|
||||
"url": "/v1/embeddings",
|
||||
"body": {"model": embedding_model_id, "input": "Hello world", "encoding_format": "float"},
|
||||
},
|
||||
{
|
||||
"custom_id": "success-2",
|
||||
"method": "POST",
|
||||
"url": "/v1/embeddings",
|
||||
"body": {
|
||||
"model": embedding_model_id,
|
||||
"input": ["How are you?", "Good morning", "Have a great day"],
|
||||
"encoding_format": "float",
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
with batch_helper.create_file(batch_requests) as uploaded_file:
|
||||
batch = openai_client.batches.create(
|
||||
input_file_id=uploaded_file.id,
|
||||
endpoint="/v1/embeddings",
|
||||
completion_window="24h",
|
||||
metadata={"test": "e2e_embeddings_success"},
|
||||
)
|
||||
|
||||
final_batch = batch_helper.wait_for(
|
||||
batch.id,
|
||||
max_wait_time=3 * 60,
|
||||
expected_statuses={"completed"},
|
||||
timeout_action="skip",
|
||||
)
|
||||
|
||||
assert final_batch.status == "completed"
|
||||
assert final_batch.request_counts is not None
|
||||
assert final_batch.request_counts.total == 2
|
||||
assert final_batch.request_counts.completed == 2
|
||||
assert final_batch.output_file_id is not None
|
||||
|
||||
output_content = openai_client.files.content(final_batch.output_file_id)
|
||||
if isinstance(output_content, str):
|
||||
output_text = output_content
|
||||
else:
|
||||
output_text = output_content.content.decode("utf-8")
|
||||
|
||||
output_lines = output_text.strip().split("\n")
|
||||
assert len(output_lines) == 2
|
||||
|
||||
# Check first result (string input)
|
||||
result1 = json.loads(output_lines[0])
|
||||
assert result1["custom_id"] in ["success-1", "success-2"]
|
||||
assert "response" in result1
|
||||
assert result1["response"]["status_code"] == 200
|
||||
|
||||
# Verify the response body contains embeddings data
|
||||
response_body1 = json.loads(result1["response"]["body"])
|
||||
assert response_body1["object"] == "list"
|
||||
assert "data" in response_body1
|
||||
assert len(response_body1["data"]) == 1
|
||||
assert "embedding" in response_body1["data"][0]
|
||||
assert "index" in response_body1["data"][0]
|
||||
assert response_body1["data"][0]["index"] == 0
|
||||
|
||||
# Check second result (list input)
|
||||
result2 = json.loads(output_lines[1])
|
||||
assert result2["custom_id"] in ["success-1", "success-2"]
|
||||
assert "response" in result2
|
||||
assert result2["response"]["status_code"] == 200
|
||||
|
||||
# Verify the response body contains embeddings data for list input
|
||||
response_body2 = json.loads(result2["response"]["body"])
|
||||
assert response_body2["object"] == "list"
|
||||
assert "data" in response_body2
|
||||
assert len(response_body2["data"]) == 3 # Three strings in the list
|
||||
for i, embedding_data in enumerate(response_body2["data"]):
|
||||
assert "embedding" in embedding_data
|
||||
assert "index" in embedding_data
|
||||
assert embedding_data["index"] == i
|
||||
|
||||
deleted_output_file = openai_client.files.delete(final_batch.output_file_id)
|
||||
assert deleted_output_file.deleted
|
||||
|
||||
if final_batch.error_file_id is not None:
|
||||
deleted_error_file = openai_client.files.delete(final_batch.error_file_id)
|
||||
assert deleted_error_file.deleted
|
||||
|
|
|
|||
|
|
@ -12,29 +12,10 @@
|
|||
"body": {
|
||||
"__type__": "ollama._types.ProcessResponse",
|
||||
"__data__": {
|
||||
"models": [
|
||||
{
|
||||
"model": "llama3.2:3b",
|
||||
"name": "llama3.2:3b",
|
||||
"digest": "a80c4f17acd55265feec403c7aef86be0c25983ab279d83f3bcd3abbcb5b8b72",
|
||||
"expires_at": "2025-10-04T12:20:09.202126-07:00",
|
||||
"size": 3367856128,
|
||||
"size_vram": 3367856128,
|
||||
"details": {
|
||||
"parent_model": "",
|
||||
"format": "gguf",
|
||||
"family": "llama",
|
||||
"families": [
|
||||
"llama"
|
||||
],
|
||||
"parameter_size": "3.2B",
|
||||
"quantization_level": "Q4_K_M"
|
||||
},
|
||||
"context_length": 4096
|
||||
}
|
||||
]
|
||||
"models": []
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
}
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,422 +0,0 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/embeddings",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "all-minilm:l6-v2",
|
||||
"input": "Test dimensions parameter",
|
||||
"encoding_format": "float",
|
||||
"dimensions": 16
|
||||
},
|
||||
"endpoint": "/v1/embeddings",
|
||||
"model": "all-minilm:l6-v2"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
|
||||
"__data__": {
|
||||
"data": [
|
||||
{
|
||||
"embedding": [
|
||||
0.04635219,
|
||||
0.002988263,
|
||||
-0.054220885,
|
||||
0.057812735,
|
||||
-0.0340614,
|
||||
0.013923248,
|
||||
-0.005755826,
|
||||
0.054555666,
|
||||
-0.09073176,
|
||||
-0.066910096,
|
||||
0.046287432,
|
||||
-0.060912322,
|
||||
0.0010950539,
|
||||
0.025724398,
|
||||
-0.025169374,
|
||||
-0.026821515,
|
||||
-0.030190151,
|
||||
0.0019341545,
|
||||
-0.0754819,
|
||||
0.057380512,
|
||||
0.020332545,
|
||||
-0.005591279,
|
||||
-0.0022273492,
|
||||
0.012063173,
|
||||
-0.011033521,
|
||||
-0.03300947,
|
||||
0.05462081,
|
||||
0.014426073,
|
||||
0.024025004,
|
||||
0.004224287,
|
||||
0.09837723,
|
||||
0.08385713,
|
||||
-0.049175426,
|
||||
0.03877149,
|
||||
0.08748876,
|
||||
-0.0223024,
|
||||
0.006552746,
|
||||
-0.0070359865,
|
||||
0.017893821,
|
||||
0.015465863,
|
||||
0.05007282,
|
||||
-0.019349905,
|
||||
0.064887345,
|
||||
0.03184605,
|
||||
0.0034936152,
|
||||
0.02317752,
|
||||
-0.06297051,
|
||||
0.044468515,
|
||||
-0.022246253,
|
||||
-0.017976552,
|
||||
0.040390052,
|
||||
-0.0020998395,
|
||||
-0.05173264,
|
||||
0.014722753,
|
||||
0.01640469,
|
||||
-0.06438627,
|
||||
-0.043313596,
|
||||
-0.040564552,
|
||||
0.044412937,
|
||||
-0.0031199565,
|
||||
-0.007237415,
|
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@ -28,7 +28,7 @@
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"content": "I'm happy to help you test the OpenAI API, but I need to clarify that I'm a large language model, not a direct interface to the OpenAI API. However, I can guide you through a simple testing process.\n\nOpenAI provides an API key that allows access to their models, including the powerful \"text-001\" model you mentioned. Here's how you can test it:\n\n**Step 1: Get your API Key**\n\nIf you haven't already, sign up for an OpenAI account at [openai.com](http://openai.com) and obtain a free API key.\n\n**Step 2: Access the API endpoint**\n\nOpenAI provides a few different endpoints for their models. For testing purposes, we'll use the \"API endpoint\" which is `https://api.openai.com/v1/models/text-001`. You can access this URL directly in your web browser or use a tool like `curl` to send an HTTP request.\n\n**Step 3: Test with a simple prompt**\n\nTo test the model, you can use a simple prompt, such as:\n\n`\"Write a short paragraph about AI.\"`\n\nYou can modify this prompt to suit your testing needs. You can also try using more complex prompts or even generating text based on user input.\n\nHere's an example of how you could send a request to the OpenAI endpoint using `curl`:\n```bash\ncurl -X POST \\\n https://api.openai.com/v1/models/text-001 \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -H 'Content-Type: application/json' \\\n -d '{\"prompt\": \"Write a short paragraph about AI.\"}'\n```\nReplace `YOUR_API_KEY` with your actual OpenAI API key.\n\n**Step 4: Verify the response**\n\nAfter sending the request, you should receive a JSON response from OpenAI. The response will contain the generated text based on your prompt.\n\nIf everything goes well, you should see some text in response to your prompt. This might look something like this:\n```json\n{\n \"result\": [\n {\n \"text\": \"Artificial intelligence has been able to learn and adapt quickly, allowing it to take over various tasks automatically.\"\n }\n ]\n}\n```\nThis is just a simple example to demonstrate the process of testing the OpenAI API. Keep in mind that this is just a brief illustration and the actual experience may vary depending on your specific use case.\n\nDo you want me to try using python - gpt-3 via Hugging Face to run some tests ? I can give it a shot if you're not up to the task yourself!",
|
||||
"content": "I'd be happy to help you test the OpenAI API, specifically version 1. To start, we'll need to complete some basic setup steps.\n\nPlease note that the OpenAI platform is still developing and has a lot of limitations on their API keys for new accounts (the first few tiers). \n\nHere's an example of how you can use the `python-openai` library in python to test the OpenAI API v. 1 (Note: The free version only has a limited set of options):\n\n### Required installations\n\nBefore we begin, make sure you have the following installed:\n\n* Python 3.7 or higher\n* pip\n* `python-openai`\n\nYou can install the required packages by running the following command in your terminal:\n\n```bash\npip install python-openai\n```\n\nPlease make sure to get an API key from [OpenAI website](https://www.openai.com/), as you will need it for testing.\n\n### Getting Started with Testing\n\nBelow is a sample code example demonstrating how to call some of the `python-openai` functions:\n\n```python\nfrom openai import api\n\n\n# Load api key into an object.\ndef load_model(api_key):\n \"\"\"Load and store the API key in order to use the API.\"\"\"\n model = api.Model()\n model.api_key = api_key\n\n return model\n\n\n\nif __name__ == \"__main__\":\n \n # Define your OpenAI API KEY\n API_KEY = \"YOUR_API_KEY_HERE\"\n\n load_model(api_key=API_KEY)\n \n\n # Perform an API call\n \n model = load_model()\n print(\"This will be printed if successful \")\n \n\n\n\n# Don't forget to close and clean up the model when finished testing.\nmodel.__enter__()\nmodel.close()\nmodel.__exit__()\n\n```\n\nPlease replace `\"YOUR_API_KEY_HERE\"` with your actual OpenAI username.\n\nTo do so, you'll need an API key: go to https://www.openai.com and register a new account first.\n\nIf your tests run as expected without any errors, it means that your OpenAI API token is working. Make sure to store the token securely for use in future projects or testing code for optimal results.\nPlease let me know if there are any issues at all during testing or if I can assist with anything else related to getting started",
|
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|
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|
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|
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|
|
@ -44,9 +44,9 @@
|
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"service_tier": null,
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|
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|
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}
|
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|
|
|
|||
|
|
@ -1,57 +0,0 @@
|
|||
{
|
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|
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|
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|
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|
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|
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"messages": [
|
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{
|
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|
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|
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}
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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}
|
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}
|
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|
|
@ -1,79 +0,0 @@
|
|||
{
|
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|
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|
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|
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|
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|
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|
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|
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{
|
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"role": "user",
|
||||
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|
||||
}
|
||||
],
|
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|
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@ -230,11 +183,11 @@
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@ -282,11 +261,11 @@
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@ -1,4 +1,5 @@
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@ -19,14 +20,14 @@
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|
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@ -42,9 +43,9 @@
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Reference in a new issue