559 lines
43 KiB
YAML
559 lines
43 KiB
YAML
interactions:
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- request:
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headers:
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accept:
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- application/json
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accept-encoding:
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- gzip, deflate, zstd
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connection:
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- keep-alive
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content-length:
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- '114'
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content-type:
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- application/json
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host:
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- localhost:11434
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method: POST
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parsed_body:
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encoding_format: base64
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input:
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- Python is a high-level programming language.
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model: qwen3-embedding:4b
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uri: http://localhost:11434/v1/embeddings
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response:
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headers:
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content-type:
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- application/json
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transfer-encoding:
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- chunked
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parsed_body:
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data:
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- embedding: 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
|
|
index: 0
|
|
object: embedding
|
|
model: qwen3-embedding:4b
|
|
object: list
|
|
usage:
|
|
prompt_tokens: 9
|
|
total_tokens: 9
|
|
status:
|
|
code: 200
|
|
message: OK
|
|
- request:
|
|
headers:
|
|
accept:
|
|
- application/json
|
|
accept-encoding:
|
|
- gzip, deflate, zstd
|
|
connection:
|
|
- keep-alive
|
|
content-length:
|
|
- '2666'
|
|
content-type:
|
|
- application/json
|
|
host:
|
|
- localhost:11434
|
|
method: POST
|
|
parsed_body:
|
|
messages:
|
|
- content: |-
|
|
You are a knowledgeable assistant that answers questions using a document knowledge base.
|
|
|
|
Process:
|
|
1. Call search_documents with relevant keywords from the question
|
|
2. Review the results ordered by relevance
|
|
3. If needed, perform follow-up searches with different keywords (max 3 total)
|
|
4. Provide a concise answer based strictly on the retrieved content
|
|
|
|
The search tool returns results like:
|
|
[chunk_abc123] [rank 1 of 5]
|
|
Source: "Document Title" > Section > Subsection
|
|
Type: paragraph
|
|
Content:
|
|
The actual text content here...
|
|
|
|
[chunk_def456] [rank 2 of 5]
|
|
Source: "Another Document"
|
|
Type: table
|
|
Content:
|
|
| Column 1 | Column 2 |
|
|
...
|
|
|
|
Each result includes:
|
|
- chunk_id in brackets and rank position (rank 1 = most relevant)
|
|
- Source: document title and section hierarchy (when available)
|
|
- Type: content type like paragraph, table, code, list_item (when available)
|
|
- Content: the actual text
|
|
|
|
In your response, include the chunk IDs you used in cited_chunks.
|
|
|
|
Guidelines:
|
|
- Base answers strictly on retrieved content - do not use external knowledge
|
|
- Use the Source and Type metadata to understand context
|
|
- If multiple results are relevant, synthesize them coherently
|
|
- If information is insufficient, say: "I cannot find enough information in the knowledge base to answer this question."
|
|
- Be concise and direct - avoid elaboration unless asked
|
|
- Results are ordered by relevance, with rank 1 being most relevant
|
|
role: system
|
|
- content: What is Python?
|
|
role: user
|
|
model: gpt-oss
|
|
reasoning_effort: low
|
|
stream: false
|
|
tool_choice: auto
|
|
tools:
|
|
- function:
|
|
description: |-
|
|
Search the knowledge base for relevant documents.
|
|
|
|
Returns results with chunk IDs and rank positions.
|
|
Reference results by their chunk_id in cited_chunks.
|
|
name: search_documents
|
|
parameters:
|
|
additionalProperties: false
|
|
properties:
|
|
limit:
|
|
anyOf:
|
|
- type: integer
|
|
- type: 'null'
|
|
default: null
|
|
query:
|
|
type: string
|
|
required:
|
|
- query
|
|
type: object
|
|
type: function
|
|
- function:
|
|
description: Answer to a search query with chunk references.
|
|
name: final_result
|
|
parameters:
|
|
additionalProperties: false
|
|
properties:
|
|
answer:
|
|
description: The answer to the question
|
|
type: string
|
|
cited_chunks:
|
|
description: IDs of chunks used to form the answer
|
|
items:
|
|
type: string
|
|
type: array
|
|
confidence:
|
|
default: 1.0
|
|
description: Confidence score for this answer (0-1)
|
|
maximum: 1.0
|
|
minimum: 0.0
|
|
type: number
|
|
query:
|
|
description: The question that was answered
|
|
type: string
|
|
required:
|
|
- query
|
|
- answer
|
|
type: object
|
|
type: function
|
|
uri: http://localhost:11434/v1/chat/completions
|
|
response:
|
|
headers:
|
|
content-length:
|
|
- '506'
|
|
content-type:
|
|
- application/json
|
|
parsed_body:
|
|
choices:
|
|
- finish_reason: tool_calls
|
|
index: 0
|
|
message:
|
|
content: ''
|
|
reasoning: Need to search for "What is Python".
|
|
role: assistant
|
|
tool_calls:
|
|
- function:
|
|
arguments: '{"limit":5,"query":"What is Python?"}'
|
|
name: search_documents
|
|
id: call_qr5c35xf
|
|
index: 0
|
|
type: function
|
|
created: 1769001440
|
|
id: chatcmpl-499
|
|
model: gpt-oss
|
|
object: chat.completion
|
|
system_fingerprint: fp_ollama
|
|
usage:
|
|
completion_tokens: 40
|
|
prompt_tokens: 545
|
|
total_tokens: 585
|
|
status:
|
|
code: 200
|
|
message: OK
|
|
- request:
|
|
headers:
|
|
accept:
|
|
- application/json
|
|
accept-encoding:
|
|
- gzip, deflate, zstd
|
|
connection:
|
|
- keep-alive
|
|
content-length:
|
|
- '85'
|
|
content-type:
|
|
- application/json
|
|
host:
|
|
- localhost:11434
|
|
method: POST
|
|
parsed_body:
|
|
encoding_format: base64
|
|
input:
|
|
- What is Python?
|
|
model: qwen3-embedding:4b
|
|
uri: http://localhost:11434/v1/embeddings
|
|
response:
|
|
headers:
|
|
content-type:
|
|
- application/json
|
|
transfer-encoding:
|
|
- chunked
|
|
parsed_body:
|
|
data:
|
|
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
|
|
index: 0
|
|
object: embedding
|
|
model: qwen3-embedding:4b
|
|
object: list
|
|
usage:
|
|
prompt_tokens: 5
|
|
total_tokens: 5
|
|
status:
|
|
code: 200
|
|
message: OK
|
|
- request:
|
|
headers:
|
|
accept:
|
|
- application/json
|
|
accept-encoding:
|
|
- gzip, deflate, zstd
|
|
connection:
|
|
- keep-alive
|
|
content-length:
|
|
- '3090'
|
|
content-type:
|
|
- application/json
|
|
host:
|
|
- localhost:11434
|
|
method: POST
|
|
parsed_body:
|
|
messages:
|
|
- content: |-
|
|
You are a knowledgeable assistant that answers questions using a document knowledge base.
|
|
|
|
Process:
|
|
1. Call search_documents with relevant keywords from the question
|
|
2. Review the results ordered by relevance
|
|
3. If needed, perform follow-up searches with different keywords (max 3 total)
|
|
4. Provide a concise answer based strictly on the retrieved content
|
|
|
|
The search tool returns results like:
|
|
[chunk_abc123] [rank 1 of 5]
|
|
Source: "Document Title" > Section > Subsection
|
|
Type: paragraph
|
|
Content:
|
|
The actual text content here...
|
|
|
|
[chunk_def456] [rank 2 of 5]
|
|
Source: "Another Document"
|
|
Type: table
|
|
Content:
|
|
| Column 1 | Column 2 |
|
|
...
|
|
|
|
Each result includes:
|
|
- chunk_id in brackets and rank position (rank 1 = most relevant)
|
|
- Source: document title and section hierarchy (when available)
|
|
- Type: content type like paragraph, table, code, list_item (when available)
|
|
- Content: the actual text
|
|
|
|
In your response, include the chunk IDs you used in cited_chunks.
|
|
|
|
Guidelines:
|
|
- Base answers strictly on retrieved content - do not use external knowledge
|
|
- Use the Source and Type metadata to understand context
|
|
- If multiple results are relevant, synthesize them coherently
|
|
- If information is insufficient, say: "I cannot find enough information in the knowledge base to answer this question."
|
|
- Be concise and direct - avoid elaboration unless asked
|
|
- Results are ordered by relevance, with rank 1 being most relevant
|
|
role: system
|
|
- content: What is Python?
|
|
role: user
|
|
- content: |-
|
|
<think>
|
|
Need to search for "What is Python".
|
|
</think>
|
|
role: assistant
|
|
tool_calls:
|
|
- function:
|
|
arguments: '{"limit":5,"query":"What is Python?"}'
|
|
name: search_documents
|
|
id: call_qr5c35xf
|
|
type: function
|
|
- content: |-
|
|
[36ec1231-b2f5-4295-bad7-9045e947d0a0] [rank 1 of 1]
|
|
Type: text
|
|
Content:
|
|
Python is a high-level programming language.
|
|
role: tool
|
|
tool_call_id: call_qr5c35xf
|
|
model: gpt-oss
|
|
reasoning_effort: low
|
|
stream: false
|
|
tool_choice: auto
|
|
tools:
|
|
- function:
|
|
description: |-
|
|
Search the knowledge base for relevant documents.
|
|
|
|
Returns results with chunk IDs and rank positions.
|
|
Reference results by their chunk_id in cited_chunks.
|
|
name: search_documents
|
|
parameters:
|
|
additionalProperties: false
|
|
properties:
|
|
limit:
|
|
anyOf:
|
|
- type: integer
|
|
- type: 'null'
|
|
default: null
|
|
query:
|
|
type: string
|
|
required:
|
|
- query
|
|
type: object
|
|
type: function
|
|
- function:
|
|
description: Answer to a search query with chunk references.
|
|
name: final_result
|
|
parameters:
|
|
additionalProperties: false
|
|
properties:
|
|
answer:
|
|
description: The answer to the question
|
|
type: string
|
|
cited_chunks:
|
|
description: IDs of chunks used to form the answer
|
|
items:
|
|
type: string
|
|
type: array
|
|
confidence:
|
|
default: 1.0
|
|
description: Confidence score for this answer (0-1)
|
|
maximum: 1.0
|
|
minimum: 0.0
|
|
type: number
|
|
query:
|
|
description: The question that was answered
|
|
type: string
|
|
required:
|
|
- query
|
|
- answer
|
|
type: object
|
|
type: function
|
|
uri: http://localhost:11434/v1/chat/completions
|
|
response:
|
|
headers:
|
|
content-length:
|
|
- '454'
|
|
content-type:
|
|
- application/json
|
|
parsed_body:
|
|
choices:
|
|
- finish_reason: stop
|
|
index: 0
|
|
message:
|
|
content: '{"answer":"Python is a high-level programming language.","cited_chunks":["36ec1231-b2f5-4295-bad7-9045e947d0a0"],"confidence":1.0,"query":"What
|
|
is Python?"}'
|
|
role: assistant
|
|
created: 1769001442
|
|
id: chatcmpl-258
|
|
model: gpt-oss
|
|
object: chat.completion
|
|
system_fingerprint: fp_ollama
|
|
usage:
|
|
completion_tokens: 61
|
|
prompt_tokens: 649
|
|
total_tokens: 710
|
|
status:
|
|
code: 200
|
|
message: OK
|
|
- request:
|
|
headers:
|
|
accept:
|
|
- application/json
|
|
accept-encoding:
|
|
- gzip, deflate, zstd
|
|
connection:
|
|
- keep-alive
|
|
content-length:
|
|
- '3422'
|
|
content-type:
|
|
- application/json
|
|
host:
|
|
- localhost:11434
|
|
method: POST
|
|
parsed_body:
|
|
messages:
|
|
- content: |-
|
|
You are a knowledgeable assistant that answers questions using a document knowledge base.
|
|
|
|
Process:
|
|
1. Call search_documents with relevant keywords from the question
|
|
2. Review the results ordered by relevance
|
|
3. If needed, perform follow-up searches with different keywords (max 3 total)
|
|
4. Provide a concise answer based strictly on the retrieved content
|
|
|
|
The search tool returns results like:
|
|
[chunk_abc123] [rank 1 of 5]
|
|
Source: "Document Title" > Section > Subsection
|
|
Type: paragraph
|
|
Content:
|
|
The actual text content here...
|
|
|
|
[chunk_def456] [rank 2 of 5]
|
|
Source: "Another Document"
|
|
Type: table
|
|
Content:
|
|
| Column 1 | Column 2 |
|
|
...
|
|
|
|
Each result includes:
|
|
- chunk_id in brackets and rank position (rank 1 = most relevant)
|
|
- Source: document title and section hierarchy (when available)
|
|
- Type: content type like paragraph, table, code, list_item (when available)
|
|
- Content: the actual text
|
|
|
|
In your response, include the chunk IDs you used in cited_chunks.
|
|
|
|
Guidelines:
|
|
- Base answers strictly on retrieved content - do not use external knowledge
|
|
- Use the Source and Type metadata to understand context
|
|
- If multiple results are relevant, synthesize them coherently
|
|
- If information is insufficient, say: "I cannot find enough information in the knowledge base to answer this question."
|
|
- Be concise and direct - avoid elaboration unless asked
|
|
- Results are ordered by relevance, with rank 1 being most relevant
|
|
role: system
|
|
- content: What is Python?
|
|
role: user
|
|
- content: |-
|
|
<think>
|
|
Need to search for "What is Python".
|
|
</think>
|
|
role: assistant
|
|
tool_calls:
|
|
- function:
|
|
arguments: '{"limit":5,"query":"What is Python?"}'
|
|
name: search_documents
|
|
id: call_qr5c35xf
|
|
type: function
|
|
- content: |-
|
|
[36ec1231-b2f5-4295-bad7-9045e947d0a0] [rank 1 of 1]
|
|
Type: text
|
|
Content:
|
|
Python is a high-level programming language.
|
|
role: tool
|
|
tool_call_id: call_qr5c35xf
|
|
- content: '{"answer":"Python is a high-level programming language.","cited_chunks":["36ec1231-b2f5-4295-bad7-9045e947d0a0"],"confidence":1.0,"query":"What
|
|
is Python?"}'
|
|
role: assistant
|
|
- content: |-
|
|
Validation feedback:
|
|
Please include your response in a tool call.
|
|
|
|
Fix the errors and try again.
|
|
role: user
|
|
model: gpt-oss
|
|
reasoning_effort: low
|
|
stream: false
|
|
tool_choice: auto
|
|
tools:
|
|
- function:
|
|
description: |-
|
|
Search the knowledge base for relevant documents.
|
|
|
|
Returns results with chunk IDs and rank positions.
|
|
Reference results by their chunk_id in cited_chunks.
|
|
name: search_documents
|
|
parameters:
|
|
additionalProperties: false
|
|
properties:
|
|
limit:
|
|
anyOf:
|
|
- type: integer
|
|
- type: 'null'
|
|
default: null
|
|
query:
|
|
type: string
|
|
required:
|
|
- query
|
|
type: object
|
|
type: function
|
|
- function:
|
|
description: Answer to a search query with chunk references.
|
|
name: final_result
|
|
parameters:
|
|
additionalProperties: false
|
|
properties:
|
|
answer:
|
|
description: The answer to the question
|
|
type: string
|
|
cited_chunks:
|
|
description: IDs of chunks used to form the answer
|
|
items:
|
|
type: string
|
|
type: array
|
|
confidence:
|
|
default: 1.0
|
|
description: Confidence score for this answer (0-1)
|
|
maximum: 1.0
|
|
minimum: 0.0
|
|
type: number
|
|
query:
|
|
description: The question that was answered
|
|
type: string
|
|
required:
|
|
- query
|
|
- answer
|
|
type: object
|
|
type: function
|
|
uri: http://localhost:11434/v1/chat/completions
|
|
response:
|
|
headers:
|
|
content-length:
|
|
- '616'
|
|
content-type:
|
|
- application/json
|
|
parsed_body:
|
|
choices:
|
|
- finish_reason: tool_calls
|
|
index: 0
|
|
message:
|
|
content: ''
|
|
reasoning: Must use final_result tool.
|
|
role: assistant
|
|
tool_calls:
|
|
- function:
|
|
arguments: '{"answer":"Python is a high-level programming language.","cited_chunks":["36ec1231-b2f5-4295-bad7-9045e947d0a0"],"confidence":1,"query":"What
|
|
is Python?"}'
|
|
name: final_result
|
|
id: call_cjmyxq28
|
|
index: 0
|
|
type: function
|
|
created: 1769001443
|
|
id: chatcmpl-594
|
|
model: gpt-oss
|
|
object: chat.completion
|
|
system_fingerprint: fp_ollama
|
|
usage:
|
|
completion_tokens: 78
|
|
prompt_tokens: 731
|
|
total_tokens: 809
|
|
status:
|
|
code: 200
|
|
message: OK
|
|
version: 1
|